Method for optimizing resource requirements of a cleaning process, cleaning method, use of a control quantity, cleaning system and motor vehicle

Abstract

The invention relates to a method for optimizing the resource requirement of a cleaning process of a surface of a motor vehicle. Furthermore, the invention relates to a cleaning method, to a use of a control quantity, to a cleaning system and to a motor vehicle.

Description

[0001] The present invention relates to a method for optimizing resource requirements of a cleaning process, a cleaning method, a use of a control quantity, a cleaning system and a motor vehicle.

[0002] In particular, the present invention relates to a cleaning method, a method for indirectly deriving a system dependency of a system behavior of a cleaning system of a motor vehicle, in particular preferably of a cleaning process of a surface of a motor vehicle, a method for optimizing resource requirements of a cleaning process of a surface of a motor vehicle, a method for determining a cleaning strategy for cleaning a surface of a motor vehicle to be cleaned, a method for indirectly deriving a system dependency of a system behavior of a system component of a cleaning system of a motor vehicle, a method for diagnosing a deviation between an actual system behavior and an expected system behavior of a system component of a cleaning system of a motor vehicle, a method for selecting a resolution strategy, a use of a selected resolution strategy, a method for indirectly deriving a system dependency of a system behavior of a contamination process of a surface of a motor vehicle, a dependency table and / or a use of a system dependency determining an expected availability at a distance or operating time to be covered of a motor vehicle, a dependency table and / or a use of a system dependency determining an expected distance or operating time to be covered of a motor vehicle at reaching an availability threshold, a use of a dependency table and / or a system dependency for optimizing resource requirements of a cleaning process of a surface of a motor vehicle, a use of a dependency table and / or a system dependency determining a cleaning strategy for cleaning a surface of a motor vehicle to be cleaned, a use of a dependency table and / or a system dependency determining a necessary expected availability gain, a use of a resource-efficient cleaning of at least one surface of a motor vehicle by a system dependency derived by a method for indirectly deriving a system dependency, a use of a resource-efficient cleaning of at least one surface of a motor vehicle by a control quantity setpoint derived by a method for optimizing resource requirements of a cleaning process of a surface of a motor vehicle, a use of a resource-efficient cleaning of at least one surface of a motor vehicle by a cleaning strategy derived by a method for determining a cleaning strategy for cleaning a surface of a motor vehicle to be cleaned, a cleaning system and a motor vehicle.

[0003] The number of sensors installed in motor vehicles has also increased due to the recent stable expansion of driver assistance systems.

[0004] In many modern motor vehicles, sensors support the driver of the motor vehicle within the framework of safety functions, for example in the recognition of obstacles, preferably also in the recognition of pedestrians, and / or within the framework of semi-autonomous or autonomous motor vehicle operation.

[0005] For the functional sensor operation and thus also for the continuous operation of these safety functions and / or for the (partially) autonomous vehicle operation, these sensors depend on surfaces that are not excessively soiled, so that the increasing number of sensors is also accompanied by an increasing need for cleaning.

[0006] Cleaning the sensor surfaces requires resources such as water, cleaning agent, energy, etc., which can only be stored or carried in the vehicle to a limited extent. As a result, the need for resource-saving cleaning processes is increasing.

[0007] In addition, the increasing number of sensors installed in motor vehicles has led to the situation that some of the data can be redundantly acquired by several sensors, but a failure of one sensor often also leads to a failure of the driver assistance system.

[0008] If resources are to be saved, questions arise as to which cleaning strategies can maintain the functionality of the driver assistance system for as long as possible without having to refill the cleaning resources and / or which sensors can be ignored or cleaned with less resources during cleaning.

[0009] The decision process for adequately cleaning the appropriate sensors thus becomes more complex. There are many influences on the determination of adequate cleaning and the implementation.

[0010] In particular, prior art cleaning of the front and / or rear windshield of a motor vehicle using a windshield wiper is known, in which a cleaning fluid can also be applied to the front and / or rear windshield.

[0011] From the document EP 0 932 533 A1 a device for controlling a wiping and / or a washing system of a windshield is known. A sensor device determines the wetness or contamination of the windshield. When a wet or contaminated windshield is detected and when the ignition key is pressed or the reverse gear is engaged, the wiping and / or washing system is switched on. This ensures that a clear view through the window is ensured as a precaution when the vehicle is started and when the reverse gear is engaged. Depending on the degree of wetness and / or contamination, a period for which the wiping and / or washing system is switched on can also be specified.

[0012] DE 103 07 216 A1 discloses a process for operating a washer / wiper system of a motor vehicle windshield using at least one windshield wiper, a washer unit for spraying a cleaning fluid onto the windshield, an electronic control unit, at least one windshield wiper motor and a delivery pump for the windshield cleaning fluid. Depending on the driving situation and / or environmental input parameters, the electronic control unit adaptively controls the wiper speed during the cleaning process.

[0013] DE 10 2009 040 993 A1 discloses a device for operating a wiping and / or rinsing system for a windshield of a vehicle, the device having a control device for controlling a cleaning process of the wiping and / or rinsing system, wherein the windshield of the vehicle can be subjected to a cleaning fluid of the rinsing system and / or a wiper of the wiping system can be moved into contact with the windshield, wherein the control device is adapted to determine a degree of contamination and / or a degree of wetting of the pane depending on at least one detected information and to set at least one specific parameter of the cleaning process depending on the determined degree of contamination and / or degree of wetting, wherein the control device is adapted to determine the degree of contamination and / or the degree of wetting of the pane during the cleaning process and to adjust at least one specific parameter depending on the degree of contamination and / or the degree of wetting during the cleaning process, wherein a predetermined plurality of value combinations of at least two specific parameters for the cleaning process is stored in the control device, and the control device is adapted to select a value combination from the plurality of value combinations depending on the degree of contamination and / or the degree of wetting and to adjust the at least two specific parameters depending on the selected value combination.

[0014] The present invention is based on the task of providing an improvement or an alternative to the prior art.

[0015] According to a first aspect of the present invention, the task is solved by a resource-efficient, preferably resource-saving, cleaning method for at least one surface of a motor vehicle, wherein the motor vehicle comprises a cleaning system and at least one sensor, wherein the sensor is operatively connected to one surface, wherein the cleaning method comprises at least one cleaning process, wherein the cleaning process is adapted for cleaning one surface and comprises a cleaning cycle comprising a start time and an end time, wherein the cleaning system comprises an electronic control unit, a cleaning fluid dispensing system, preferably comprising at least one fluid reservoir, at least one nozzle, and at least one cleaning fluid line, wherein the sensor is adapted to detect at least one measured quantity, preferably an availability of the sensor, a process quantity, preferably a humidity and / or a temperature and / or a rainfall and / or a snowfall in the vicinity of the motor vehicle and / or a coordinate of the motor vehicle, and / or a control quantity, and to transmit the measured quantity to the electronic control unit, wherein the nozzle is adapted to operatively connect the cleaning fluid to the surface, wherein the electronic control unit is adapted to control and / or to adjust the cleaning process by means of at least one control quantity of the cleaning process, wherein a resource requirement of the cleaning process is set depending on a control quantity setpoint,

[0016] characterized in that

[0017] The electronic control unit controls resource-efficient cleaning, preferably resource-saving cleaning, depending on a dependency table comprising at least two data sets, preferably at least 50 data sets, particularly preferably at least 200 data sets, stored in an ordered manner relative to each other, wherein each data set comprises at least one input quantity, preferably a process quantity, preferably a humidity and / or a temperature and / or a rainfall and / or a snowfall in the vicinity of the motor vehicle and / or coordinates of the motor vehicle, and / or a control quantity and / or a vehicle type and / or an availability of a sensor, of the cleaning system, and at least one output quantity, preferably a resource requirement of the cleaning process and / or an availability of a sensor, of the cleaning system,

[0018] and / or

[0019] The electronic control unit controls resource-efficient cleaning, preferably resource-saving cleaning, depending on a system dependency of a system behavior of the cleaning system, in particular of a cleaning process of a surface of the motor vehicle, between an input quantity, preferably at least one control quantity and / or at least one process quantity of the cleaning process, preferably a humidity and / or a temperature and / or a rainfall and / or a snowfall in the vicinity of the motor vehicle and / or coordinates of the motor vehicle, and / or a vehicle type and / or an availability of a sensor, of the cleaning system; and an output quantity, preferably a resource requirement of the cleaning process and / or an availability of a sensor, of the cleaning system, in particular depending on a system dependency derived by the method for indirectly deriving a system dependency of a system behavior of a cleaning system of a motor vehicle according to the second aspect of the present application,

[0020] and / or

[0021] The electronic control unit controls resource-efficient cleaning, preferably resource-saving cleaning, applying a control quantity setpoint, in particular a control quantity setpoint derived by the method according to the third aspect of the present application,

[0022] and / or

[0023] The electronic control unit controls resource-efficient cleaning, preferably resource-saving cleaning, preferably applying a cleaning strategy, in particular a cleaning strategy derived by the method according to the fourth aspect of the present application,

[0024] and / or

[0025] The cleaning method comprises a process step for indirectly deriving a system dependency of a system behavior of a system component of a cleaning system of a motor vehicle, preferably a process step for indirectly deriving a system dependency according to the fifth aspect of the present application,

[0026] and / or

[0027] The cleaning method comprises a process step for diagnosing a system behavior of a system component of the cleaning system of the motor vehicle, preferably a process step for diagnosing a system behavior of a system component of the cleaning system according to the first alternative of the sixth aspect of the present application,

[0028] and / or

[0029] The cleaning method comprises a process step for diagnosing a deviation between an actual system behavior and an expected system behavior of a system component of the cleaning system of the motor vehicle, preferably a process step for diagnosing a deviation between an actual system behavior and an expected system behavior of a system component of the cleaning system according to the second alternative of the sixth aspect of the present application,

[0030] and / or

[0031] The cleaning method comprises a process step for selecting a resolution strategy, preferably a process step for selecting a resolution strategy according to the seventh aspect of the present application.

[0032] and / or

[0033] The cleaning method comprises a process step for using the selected resolution strategy, preferably a process step for using the selected resolution strategy according to the eighth aspect of the present application,

[0034] and / or

[0035] The cleaning method comprises a process step for indirectly deriving a system dependency of a system behavior of a contamination process of a surface of the motor vehicle, preferably a process step for indirectly deriving a system dependency according to the ninth aspect of the present application,

[0036] and / or

[0037] The cleaning method comprises a process step for using:

[0038] - a dependency table comprising at least two data sets stored in an ordered manner relative to each other, preferably comprising at least 50 data sets, particularly preferably comprising at least 200 data sets, wherein each data set comprises at least one input quantity of the contamination process, in particular the distance of the motor vehicle to be covered between the first availability and the second availability and / or the operating time before covering the distance of the motor vehicle between the first availability and the second availability, and / or the driving speed of the motor vehicle, preferably a profile of the driving speed along the route between the first availability and the second availability, and / or a process quantity, preferably a humidity, particularly preferably a profile of the humidity along the route between the first availability and the second availability, and / or a temperature in the vicinity of the motor vehicle, particularly preferably a profile of the temperature along the route between the first availability and the second availability, and / or a precipitation quantity, particularly preferably a profile of the precipitation quantity along the route between the first availability and the second availability, and / or a snow quantity, particularly preferably a profile of the snow quantity along the route between the first availability and the second availability, and / or a vehicle type of the motor vehicle and / or coordinates, preferably coordinates of the motor vehicle along the route between the first availability and the second availability, and / or the first availability of the sensor, and the evaluated availability change,

[0039] and / or

[0040] - a system behavior of the contamination process of the surface of the motor vehicle, a resource-efficient cleaning, preferably a resource-saving cleaning, of at least one surface of the motor vehicle, preferably derived by the method for indirectly deriving system dependencies according to the ninth aspect of the present application,

[0041] for / for

[0042] - determining the expected availability at the distance or operating time to be covered of the motor vehicle, preferably according to the tenth aspect of the present application,

[0043] and / or

[0044] - determining the expected distance or expected operating time to be covered of the motor vehicle at the time of reaching the availability threshold, preferably according to the eleventh aspect of the present application,

[0045] and / or

[0046] - optimizing the resource requirements for the cleaning process of the surface of the motor vehicle, in particular by applying the method for optimizing the resource requirements for the cleaning process of the surface of the motor vehicle according to the third aspect of the present application,

[0047] and / or

[0048] In particular, the cleaning strategy for cleaning a surface of a motor vehicle to be cleaned is determined by applying the method for determining a cleaning strategy for cleaning a surface of a motor vehicle to be cleaned according to the fourth aspect of the present application,

[0049] and / or

[0050] Preferably according to the fourteenth aspect of the present application, the necessary expected availability gain is determined, wherein the sum of the actual availability and the necessary expected availability gain is sufficient to achieve the distance or operating time to be covered by the motor vehicle in a manner that does not exceed the availability threshold.

[0051] The following terms are explained in more detail:

[0052] First of all, it should be expressly pointed out that in the context of the present patent application, the indefinite article and the numbers (such as "one", "two", etc.) shall generally be understood as "at least" information, i.e. "at least one", "at least two", etc., unless it is expressly apparent from the respective context or it is apparent or technically mandatory for the person skilled in the art that only "exactly one", "exactly two", etc. can be meant.

[0053] In the context of the present patent application, the term "in particular" shall always be understood to mean that the term introduces an optional, preferred feature. The expression shall not be understood as "namely".

[0054] A "cleaning method" is a method of cleaning at least one surface or component of a surface of a motor vehicle, wherein impurities are to be reduced or removed. Preferably, the cleaning method is performed automatically or semi-automatically, wherein the driver of the motor vehicle can select a cleaning mode, preferably in an automatic cleaning method, and, if necessary, be requested to supplement the resources required for the cleaning method.

[0055] In particular, the cleaning program can be executed and / or initiated manually, in particular by the driver of the motor vehicle.

[0056] It is particularly preferred that it can also be envisaged that the cleaning method can be executed automatically during the operation of the vehicle and / or outside the operating time of the vehicle in order to clean at least one component of the surface of the vehicle and thus can run autonomously in addition to supplementing any required resources.

[0057] Cleaning shall be understood as cleaning a surface using cleaning means such as water, air, cleaning agents and / or wiping elements and / or mechanical cleaning elements and / or vibration-based cleaning elements and / or ultrasonic-based cleaning elements. In particular, cleaning does not mean achieving an absolutely clean surface, but rather using cleaning means to reduce the contamination of the surface.

[0058] A "cleaning fluid" is any fluid that can be used as a cleaning device, preferably water, air, cleaning agent, etc.

[0059] The cleaning method preferentially uses one or more "cleaning processes", wherein a cleaning process involves the cleaning of a surface. Each cleaning process comprises a "cleaning cycle", wherein at least one cleaning device is operatively connected with the corresponding surface, wherein the cleaning cycle comprises a "start time" and an "end time".

[0060] The end time of a cleaning process is to be understood in particular also as the end time of an evaluation phase of the cleaning process, in particular in the case where the evaluation of the cleaning process is also carried out during the execution of the cleaning process, the evaluation point and the cleaning process having a common start time, but any deviating end time, preferably the end time of the evaluation cycle ending before the end time of the cleaning process. In any case, the term "end time" refers to the end time of the cleaning process and / or the end time of the evaluation process of the cleaning process, depending on the question at hand.

[0061] It is to be considered in particular that, in the context of the evaluation of a cleaning process, a single cleaning process results in several data sets, wherein the different data sets differ preferably only in the end time of the evaluation of the cleaning process.

[0062] A "surface" is a surface element of a motor vehicle. A preferred term for a surface is a windshield and / or a rear window and / or a side window of a motor vehicle. Furthermore, a surface is preferably understood as a surface element behind which a sensor arrangement is arranged. Another preferred term for a surface is a part of a surface of a motor vehicle that is visible from the outside, in particular also including hidden surfaces, such as a part of a wheelhouse lining in a wheelhouse of a motor vehicle.

[0063] A surface can also be understood as a surface element that is located within a motor vehicle, preferably within the interior of a motor vehicle and / or within the engine compartment of a motor vehicle.

[0064] A "vehicle" or "motor vehicle" is understood to be a generally wheeled, self-propelled vehicle that does not operate on rails and is used for the transport of people or goods.

[0065] Preferably, the motor vehicle propulsion is provided by an engine or motor, typically by an internal combustion engine or an electric motor, or some combination of both, such as a hybrid electric vehicle and a plug-in hybrid vehicle.

[0066] A "cleaning system" is a system that provides all structural elements required for the cleaning method and thus also all structural elements required for the physical cleaning process.

[0067] The cleaning system preferably contains a cleaning fluid distribution system and further electrical and / or electronic components.

[0068] A "cleaning fluid dispensing system" denotes a system designed to provide a cleaning fluid on a surface to be cleaned of a motor vehicle.

[0069] Preferably, the cleaning fluid dispensing system comprises at least one "cleaning fluid line" adapted for conveying a cleaning fluid, in particular from a pump and / or a cleaning fluid reservoir to a nozzle.

[0070] A "nozzle" is a device through which a cleaning fluid can exit the cleaning system and which is designed to interact, preferably operatively connected, the cleaning fluid with the surface to be cleaned.

[0071] Preferably, the nozzle is a device designed to control the direction or the properties of the cleaning fluid when it exits the cleaning fluid dispensing system.

[0072] Preferably, the nozzle comprises an actuating device designed to influence the direction of the cleaning fluid exiting the cleaning fluid dispensing system.

[0073] Preferably, the nozzle comprises a second actuating device designed to influence the properties of the cleaning fluid exiting the cleaning fluid dispensing system, preferably the speed of the cleaning fluid.

[0074] Preferably, the cleaning fluid dispensing system is equipped with an "electric pump" designed to pump the cleaning fluid.

[0075] The cleaning fluid dispensing system comprises a "cleaning fluid reservoir" designed to store a cleaning fluid in the motor vehicle. The electric pump is preferably integrated into the cleaning fluid reservoir.

[0076] The electric pump is preferably connected to the cleaning fluid reservoir and to the nozzle, preferably by means of a "cleaning fluid line" designed to guide the cleaning fluid.

[0077] The electronic assembly of the cleaning system can preferably comprise an electronic control unit and / or a data processing system. The data processing system can also be integrated into the electronic control unit.

[0078] An "electronic control unit" (ECU) is any embedded system in automotive electronics that controls one or more electrical systems or subsystems in a vehicle.

[0079] The electronic control unit described herein is preferably configured to perform a cleaning method, in particular preferably a cleaning method according to the first aspect of the present application, and / or to perform a method for indirectly deriving a system dependency, preferably a system dependency of a system behavior of a cleaning system of a motor vehicle, in particular preferably a system dependency of a system behavior of a cleaning process of a surface of a motor vehicle, in particular preferably a method for indirectly deriving a system dependency according to the second aspect of the present application, and / or to perform a method for indirectly deriving a system dependency of a system behavior of a system component of a cleaning system of a motor vehicle, in particular preferably a method for indirectly deriving a system dependency according to the fifth aspect of the present application, and / or to perform a method for indirectly deriving a system dependency of a system behavior of a contamination process of a surface of a motor vehicle, in particular preferably to perform a method for indirectly deriving a system dependency according to the ninth aspect of the present application, and / or to perform a method for optimizing a resource requirement of a cleaning process of a surface of a motor vehicle, in particular preferably a method for optimizing a resource requirement according to the third aspect of the present application, in particular preferably according to the first alternative and / or the second alternative, and / or to perform a method for determining a cleaning strategy for cleaning a surface of a motor vehicle to be cleaned, in particular preferably a method for determining a cleaning strategy according to the fourth aspect of the present application, and / or to perform a method for diagnosing a deviation between an actual system behavior and an expected system behavior of a system component of a cleaning system of a motor vehicle, in particular preferably a method for diagnosing a deviation between an actual system behavior and an expected system behavior according to the sixth aspect of the present application, and / or to perform a method for selecting a resolution strategy, in particular preferably a method for selecting a resolution strategy according to the seventh aspect of the present application, and / or to use a selected resolution strategy, in particular preferably a selected resolution strategy according to the eighth aspect of the present application, and / or to use a dependency table and / or a system dependency for determining an expected availability at a distance to be covered or an operating time of a motor vehicle, in particular preferably a dependency table and / or a system dependency according to the tenth aspect of the present application, and / or to use a dependency table and / or a system dependency for determining an expected distance to be covered or an operating time of a motor vehicle at which an availability threshold is reached, in particular preferably a dependency table and / or a system dependency according to the eleventh aspect of the present application, and / or to use a dependency table and / or a system dependency for optimizing a resource requirement of a cleaning process of a surface of a motor vehicle, in particular preferably a dependency table and / or a system dependency according to the twelfth aspect of the present application, and / or to use a dependency table and / or a system dependency for determining a cleaning strategy for cleaning a surface of a motor vehicle to be cleaned, in particular preferably a dependency table and / or a system dependency according to the thirteenth aspect of the present application, and / or to use a dependency table and / or a system dependency for determining a necessary expected availability gain, in particular preferably a dependency table and / or a system dependency according to the fourteenth aspect of the present application.and / or using a system dependency derived by a method for indirectly deriving a resource-efficient cleaning of at least one surface of a motor vehicle, in particular preferably using a system dependency according to the fifteenth aspect of the present application, and / or using a control quantity setpoint derived by a method for optimizing resource requirements for a cleaning process of a surface of a motor vehicle for a resource-efficient cleaning of at least one surface of a motor vehicle, in particular preferably using a control quantity setpoint according to the fifteenth aspect of the present application, and / or using a cleaning strategy derived by a method for determining a cleaning strategy for cleaning a surface to be cleaned of a motor vehicle for a resource-efficient cleaning of at least one surface of a motor vehicle, in particular preferably using a cleaning strategy according to the fifteenth aspect of the present application, and / or as part of a cleaning system according to the sixteenth aspect of the present application, and / or as part of a motor vehicle according to the seventeenth aspect of the present application.

[0080] Furthermore, the electronic control unit is preferably equipped with all structural electronic components required for carrying out the cleaning method presented here, preferably the cleaning method according to the first aspect of the present application.

[0081] In particular preferably, the electronic control unit comprises a data processing system.

[0082] A "data processing system" is a combination of electronic components and electronic processes which produce a defined output set for an input set. Input and output are interpreted as data.

[0083] Preferably, a data processing system is a system which implements an organized processing of data quantities in order to achieve the goal of obtaining information about these data quantities and / or changing these data quantities.

[0084] Preferably, a data processing system comprises a "data acquisition system".

[0085] A "sensor" or "detector" is a technical component which can qualitatively or quantitatively, as a "measured quantity", determine certain physical or chemical properties and / or material compositions of its environment. These quantities are determined by means of physical or chemical effects and converted into analog or digital electrical signals.

[0086] Preferably, a sensor comprises an electronic data processing unit which is equipped to process the quantities detected by the sensor, in particular to process quantities derived from the raw measured quantities.

[0087] In particular, it should be considered that such a data processing unit can determine the contamination state of a surface operatively connected to the sensor, preferably it should be able to determine the availability of the sensor based on the measured quantities detected by the sensor, and / or the intensity of rain and / or the intensity of snowfall and / or the intensity of condensation and / or the intensity of hail.

[0088] Preferably, such an electronic data processing unit forms a unit with the sensor or is part of an electronic control unit of the motor vehicle.

[0089] Preferably, a data processing unit of this type is provided to process quantities recorded by several sensors.

[0090] The current value of a quantity is the "actual or current quantity value" and / or the "current or actual quantity value".

[0091] In particular, a sensor is also understood to be a virtual sensor. A "virtual sensor" qualitatively or quantitatively maps data of one or more recorded quantities to a certain physical or chemical property and / or material composition of the environment by means of an imaging function. Thus, a sensor can be a physical sensor or a virtual sensor which qualitatively or quantitatively records a quantity and / or a condition of the surrounding environment. In other words, a virtual sensor determines a quantity, in particular a measured quantity, a controlled quantity or a process quantity, by means of a mathematical prescription.

[0092] Preferably, a sensor is understood to be an optical sensor.

[0093] Preferably, an optical sensor is understood to be a camera and / or a lidar and / or a radar and / or an ultrasonic sensor.

[0094] An optical sensor can preferably determine a brightness level or, in other words, a light intensity level.

[0095] In particular, it should be considered that by evaluating the light intensity level, preferably in comparison with a light intensity level of a second sensor whose field of view overlaps with the field of view of the sensor, the availability of the sensor can be determined.

[0096] In particular, a sensor also comprises a temperature sensor, a pressure sensor, a voltage sensor, a current consumption sensor, a radar sensor, an ultrasonic sensor, a flow rate sensor, etc.

[0097] A "measured value" is the current value or, in other words, the actual value of a "measured quantity". A "measured quantity setpoint" is a default quantity of a measured value. Preferably, a measured quantity is any quantity which can be measured or otherwise determined in such a way that the measured value of the measured quantity can be further electronically processed. In particular, a measured quantity is understood to be a controlled quantity, a process quantity or a quantity which describes the availability of a sensor.

[0098] Preferably, a measured quantity is a vehicle speed.

[0099] The determined value of the determined quantity can preferably be determined experimentally and / or numerically. In the case of an experimental investigation of the determined value of the determined quantity, an experimental investigation of the entire motor vehicle, preferably in a laboratory or during regular motor vehicle operation, or an experimental investigation of a module or component within the framework of a module test bench can be considered. In the case of a numerical investigation, a numerical analysis and / or a numerical simulation within the framework of a physical model of the determined value of the determined quantity can be considered, wherein the entire vehicle or a module or component can also be considered individually.

[0100] The determined quantity can also be understood as a quantity of data, wherein this is also referred to as "data representing the determined quantity". The data is preferably retrievable data, preferably wirelessly available data, preferably current coordinates or actual coordinates of the weather and / or the motor vehicle on the nearby and / or planned route. Furthermore, the data is preferably considered to be the sensor type, the vehicle type, the last inspection date of the sensor and / or the cleaning system and / or the vehicle, etc.

[0101] The determined value, the determined quantity and the determined quantity setpoint are not to be understood as pure scalars or values, but the determined value, the determined quantity and the determined quantity setpoint are to be understood as vectors with multiple values for the respective dimensions of the vector as long as this is technically reasonable.

[0102] The "vehicle type" is a specific configuration of the vehicle. In particular, the vehicle type provides information about which surfaces the vehicle comprises, how these surfaces are shaped and which sensor is hidden behind which surface.

[0103] The "process value" is the current value of the "process quantity". The "process quantity setpoint" is the default value of the "process quantity". Preferably, the process quantity is to be understood as a quantity which is suitable to influence the cleaning process and the cleaning result but is itself influenced.

[0104] Preferably, the process quantity and / or the process quantity setpoint and / or the process value are not pure scalars or scalar values, but vectors with multiple values for the respective dimensions of the vector.

[0105] Preferably, the process quantity is the vehicle speed.

[0106] Preferably, the process quantity is a system-related process quantity, which relates to the behavior of the system, preferably the behavior of the cleaning system, which is preferably described by a system dependency. In other words, the system-related process quantity depends on the control quantity of the system.

[0107] Preferably, the process quantity is an environmental process quantity, which relates to the surrounding environment, preferably the environment surrounding the motor vehicle. Examples of environmental process quantities are the ambient temperature in the vicinity of the motor vehicle, the humidity in the vicinity of the motor vehicle, the air pressure in the vicinity of the motor vehicle, the current amount of rain and / or snow, etc.

[0108] wherein the process quantity is understood to be the ambient temperature in the vicinity of the motor vehicle and / or the humidity in the vicinity of the motor vehicle and / or the actual solar radiation and / or the surface temperature of the surface to be cleaned.

[0109] The process quantity is preferably a quantity that occurs in or around the cleaning system and can be influenced at least indirectly by the input quantity.

[0110] Preferably, the process quantity is the electric current, the power consumption, the flow pressure, the operating time, the fill level signal, the reaction time, the sensing time, the signal of a leakage sensor, the signal of a flow meter, the number of actuations, the spray pattern, the heat monitoring signal, the signal of a debris sensor, the signal of a check valve, the signal of a drip flow sensor, the signal of a distance sensor and / or the signal of a force sensor.

[0111] The "control quantity setpoint" is a default value for the actuator which is set to adjust the "control quantity". The current value of the control quantity is the "actual control quantity value".

[0112] Preferably, the control quantity is understood to be a quantity which is suitable to influence the cleaning process and the cleaning result and which is adjusted to control the cleaning method and / or the cleaning process, preferably to influence the cleaning method and / or the cleaning process.

[0113] Preferably, the control quantity and / or the control quantity setpoint and / or the control value is not a pure scalar or scalar value, but a vector with multiple values for the respective dimensions of the vector.

[0114] Preferably and in the case of a control system, the control quantity setpoint is understood to be a default value for the actuator which is set to adjust the control quantity.

[0115] wherein the control quantity is understood to be the type of cleaning fluid, in particular water and / or air, and / or the type of cleaning agent and / or the proportion of cleaning agent in the cleaning fluid and / or the temperature of the cleaning fluid and / or the pressure of the cleaning fluid as it leaves the nozzle and / or the flow rate of the cleaning fluid and / or the duration of the cleaning process and / or the number of cycles of the cleaning process and / or the current consumption of the fluid pump and / or the voltage of the fluid pump.

[0116] It is particularly preferred that the control of the control quantity is pursued with the goal of achieving a cleaning of at least one surface of the motor vehicle, preferably a resource-efficient goal, preferably a resource-saving goal.

[0117] Preferably, the control of the control quantity pursues a multi-criteria goal, wherein the goal of achieving a Pareto-optimal goal implementation is aimed at, preferably a resource-efficient, particularly preferably a resource-saving, cleaning of at least one surface of the motor vehicle under one or more boundary conditions.

[0118] The "availability" of a technical system is a measure of the degree to which the system can fulfill its tasks.

[0119] According to conceivable variants, the availability specification system can complete its task by means of two acceptable states.

[0120] Preferably, the surface in the first state is less soiled from the point of view of the sensor and / or from the point of view of whether the driver of the motor vehicle completes its task, whereas the surface in the second state is too soiled compared to the surface.

[0121] According to a preferred variant, the availability also specifies a characteristic value according to which the system can complete its task.

[0122] Particularly preferably, the availability can assume values in a range that comprises certain intervals, wherein one interval limit reached means that the system can completely fulfil its requirements and the other interval limit reached means that the system no longer fulfils its requirements.

[0123] If the range of the availability values is between the interval limits, the system can still fulfil its requirements, but not under more difficult conditions. In particular, the availability value reflects the degree of contamination of the surface of the motor vehicle, preferably of the surface, preferably of the surface of the sensor, particularly preferably of the optical sensor and / or of the surface of the driver of the motor vehicle.

[0124] Since it can generally be assumed that the degree of contamination of the surface increases with the operating time of the motor vehicle until cleaning, the availability, if reproduced within the intervals, can preferably be interpreted as a measure of how long the technical system, preferably the sensor, has fulfilled its requirements and / or how long the technical system, preferably the sensor, can still fulfil its requirements at least partially before it has to be cleaned in order to be able to fulfil its requirements again.

[0125] The availability can also preferably have values outside these interval limits. An availability above the interval limit value at which the associated sensor can completely fulfil its requirements indicates that the sensor can completely fulfil its requirements. An availability below the interval limit value at which the associated sensor can no longer fulfil its requirements indicates that the sensor can no longer completely fulfil its requirements. In other words, the surface in operational connection with the sensor then has to be cleaned by means of a cleaning process, so that the availability can increase again, in particular to a value at which the sensor can again complete at least part of its original task, wherein the surface can also be cleaned by passive cleaning processes, such as rain and / or snowfall.

[0126] It should be expressly pointed out that the availability of the surface is to be understood as meaning the availability of a surface for which the impaired operation of the sensor is less severe and the availability of a surface for which the restricted field of vision of the driver of the motor vehicle is less severe, preferably in particular the purity of the surface of the windscreen and / or the rear window and the like.

[0127] "actual availability" or in other words current availability is the availability prevailing at the current time.

[0128] "expected availability" is to be understood as an estimated availability, preferably at a certain distance to be covered and / or a certain operating time to be driven by the motor vehicle.

[0129] The expected availability can preferably be determined with an estimation procedure, preferably according to the tenth aspect of the present application, based on current and / or planned conditions, in particular operating conditions of the motor vehicle, wherein the expected availability represents the availability at a point to be passed of the driving route of the motor vehicle.

[0130] "availability threshold" is to be understood as a threshold value of the availability. Preferably, the achievement of the availability threshold requires that the surface operatively connected to the sensor whose availability is considered here is cleaned.

[0131] "expected availability gain" is the estimated gain of the availability of a sensor when the surface operatively connected to the corresponding sensor is cleaned, preferably with a defined cleaning procedure, especially preferably with a cleaning procedure defined by a control quantity setpoint.

[0132] According to the fourteenth aspect of the present application, the desired gain of the availability, or in other words the necessary expected availability gain, can preferably be derived.

[0133] Depending on the case, "change in availability" can be understood as "increase in availability" and "loss in availability". In any case, the change in availability is understood as a change in the availability of the sensor operatively connected to the surface.

[0134] "resource" is a source or origin of a benefit and it has a certain utility.

[0135] Preferably, a resource is understood here as something that can be used for cleaning a surface of a vehicle. In particular, cleaning fluid and / or cleaning agent and / or energy and / or wiping element, preferably a wiping element that can be replaced as needed, are to be considered here.

[0136] "resource requirement" is to be understood as the need for resources required for a cleaning procedure, in particular a cleaning procedure with a defined control quantity setpoint.

[0137] "resource-efficient cleaning" means optimizing the cleaning of a surface to be cleaned in such a way that the ratio of cleaning benefit to cleaning effort is taken into account. In other words, the resource-efficient cleaning method requires that the control quantity used for the cleaning procedure is selected in accordance with the fact that the greatest possible cleaning success can be achieved with the least possible effort.

[0138] The control quantity setpoint for resource-efficient cleaning can preferably be derived by a method for optimizing the resource requirements for a cleaning process of a motor vehicle, preferably by a method according to the third aspect of the present application.

[0139] "Resource-saving cleaning" is to be understood to mean that the cleaning of the surface to be cleaned is optimized according to the most important cleaning goals to be achieved, preferably the cleaning goals can lie in the fact that a defined number of safety functions of the motor vehicle do not fail due to surface contamination, in particular do not fail due to sensor surface contamination or due to impairment of the sensor function caused by contamination. Preferred cleaning goals can also be that the level of autonomy of the motor vehicle does not have to be abandoned due to surface contamination, in particular due to sensor surface contamination or due to impairment of the sensor function caused by contamination.

[0140] The cleaning strategy for resource-saving cleaning can preferably be derived by a method for determining a cleaning strategy for cleaning a surface to be cleaned of a motor vehicle, preferably by a method according to the fourth aspect of the present application.

[0141] "Control" is to be understood as the monitoring and possible adjustment of an input quantity in order to achieve a target, wherein the adjustment of the input quantity occurs in particular in response to the occurrence of a disturbance quantity.

[0142] "Disturbance quantity" is an output quantity value that deviates from the desired output quantity value.

[0143] Preferably, the disturbance quantity is the availability.

[0144] Preferably, the control represents the control quantity setpoint in order to achieve a certain target, in particular the execution of a specification of a cleaning method for resource-efficient cleaning, preferably resource-saving cleaning, of at least one surface of a motor vehicle.

[0145] Preferably, the control is understood as the execution of a cleaning method, preferably the execution of a cleaning method according to the first aspect of the present application.

[0146] The term "regulation" refers to the continuous acquisition of a measured quantity and the automatic interaction between the measured quantity and the specification-dependent control system. In particular, a continuous comparison of the measured quantity and the specification of the measured quantity is made.

[0147] The "operating condition" of a motor vehicle is the condition of the current use of the motor vehicle.

[0148] The active operating condition is preferably understood to mean that the motor vehicle is being used to achieve a target by means of active operation of the motor vehicle, preferably covering the distance between a starting point and a planned end point.

[0149] Preferably, passive operation means that the motor vehicle is currently parked.

[0150] A "system" is understood to be an entity of connected elements forming a common whole through relations, connections, interrelations and / or interactions.

[0151] A "system behavior" is understood to be an observable change of a state or state value of a system. Preferably, such observable change of a state or state value of a system occurs as a function of a change of an input value.

[0152] A "dependency", in particular a "system dependency", describes a dependency of one thing on another, preferably of an output quantity of a system on an input quantity of a system. By changing one thing, a causal change of the other thing can be achieved. A mathematical functional dependency is not necessarily, but possible in the context of a system dependency.

[0153] Preferably, a system dependency is understood to be a description, preferably a mathematical description, of a system behavior of a system, preferably of a cleaning system.

[0154] It should be expressly stated that a system dependency should not only be understood as a dependency between a pure scalar value of an input quantity and a pure scalar value of an output quantity, but also, if applicable, as a multi-dimensional dependency between a corresponding quantity of input quantities with corresponding associated values and an output quantity dependent on the input quantities with corresponding associated values considered for the system dependency.

[0155] A "dependency table" is understood to be a list of individual experiences about a system behavior, preferably of a cleaning system, in the form of data sets, wherein each data set comprises at least one input quantity, preferably of a cleaning system, and at least one output quantity, preferably of a cleaning system, stored in an ordered manner relative to each other.

[0156] Preferably, the experiences about the system behavior are based on single recordings of cleaning processes, which are preferably collected under laboratory conditions and / or on real motor vehicles and / or during operation of real motor vehicles and / or based on numerical models which shall represent the considered system behavior.

[0157] The dependency table can thus in particular facilitate the reapplication of already recorded experiences at a later point in time, in particular by selecting associated input quantities from the list of data sets within the dependency table depending on the output quantity to be achieved.

[0158] In other words, the dependency table makes it possible, in particular for the control of a cleaning process, to always be able to retrieve and reprocess the experience values stored there, wherein the input quantities from the dependency table are used for controlling the cleaning process at least if technically perceptible and possible in the sense of a control quantity setpoint.

[0159] On the other hand, in particular according to the second aspect and / or the fifth aspect and / or the ninth aspect of the present application, the data sets contained in the dependency table can be used as data points for deriving the system dependency.

[0160] An "input quantity" is defined as a quantity which contributes to a target intervention in a control or regulation system of a system, preferably a cleaning system. Its instantaneous value is an "input quantity value".

[0161] Preferably, the input quantity is not to be understood as a pure scalar or numerical value, but whenever this is technically reasonable, the input quantity value and the input quantity are to be understood as a vector input quantity with multiple values for the respective dimensions of the vector input quantity.

[0162] The control quantity and / or the data representing the measured quantity, in particular preferably the weather and / or the current coordinates on the planned route and / or in the vicinity of the motor vehicle are input quantities.

[0163] Preferably, in the case of a control system, the input variable is measured by a digital sensor in such a way that the measured variable corresponds to the default value of the control system.

[0164] Preferably, the input quantity contains further data, in particular data providing information about the current position of the motor vehicle and / or the planned route of the motor vehicle and / or the covered route of the motor vehicle and / or the expected weather, in particular the local weather, in particular humidity and / or solar radiation and / or temperature and / or rainfall and / or snowfall at the respective position of the pre-planned route of the motor vehicle.

[0165] Preferably, the input quantity value can be understood as the pressure of the cleaning fluid.

[0166] Preferably, the input quantity value can be understood as the temperature of the cleaning fluid.

[0167] Preferably, the input quantity value can be understood as the mixture of the cleaning fluid, in particular the amount of one or more additives.

[0168] Preferably, the input quantity value can be understood as a characteristic including, but not limited to, the spray pattern, in particular an oscillating spray pattern and / or a continuous spray pattern and / or a pulsed spray pattern and / or the alignment of the spray or the spray pattern with the surface to be cleaned.

[0169] An "output quantity" is a quantity produced by a system, in particular a cleaning system. Its instantaneous value is an "output quantity value".

[0170] Preferably, the output quantity is not to be understood as a pure scalar or numerical value, but whenever this is technically reasonable, the output quantity value and the output quantity are to be understood as a vector output quantity with multiple values for the respective dimensions of the vector output quantity.

[0171] Preferably, the output quantity value depends on the reaction of the system to the input quantity. The reaction of the system to the input quantity is determined by the system behavior and can be described by the system dependency of the system.

[0172] The system-relevant process quantity and / or the resource requirement and / or availability for the cleaning process, preferably the availability of the sensor surface and / or in particular the surface of the windshield and / or rear window and the like, preferably the purity of the surface, is preferably the output quantity.

[0173] A “data acquisition system” serves to record physical quantities. Depending on the sensors used, it can preferably have an analog-digital converter and a measured variable memory or data memory. Preferably, the data acquisition system can be set up to simultaneously acquire several measured variables.

[0174] An “electronic data processing and evaluation unit” is an electronic unit that processes data quantities in an organized manner with the aim of obtaining information about or modifying such data quantities. Preferably, the data are recorded in data sets, processed by humans or machines according to specified programs and output as a result.

[0175] A “database” is a system for electronic data management. The preferred task of a database is to efficiently, consistently and permanently store large amounts of data and to provide users and applications with the required subsets of the stored data in different, need-oriented representative types.

[0176] Preferably, the database contains a dependency table.

[0177] Preferably, the database contains system dependencies.

[0178] Preferably, the database can be local or decentralized, in particular in a data cloud.

[0179] Preferably, a remotely managed database can be accessed via wireless data transfer, so that data can be received from the remotely managed database and data can be transferred to the remotely managed database.

[0180] Preferably, the database comprises functions that the database itself can manage.

[0181] Preferably, the database is part of the working memory of the electronic data processing and evaluation unit.

[0182] It can be envisaged in particular that the database will delete previously existing data sets when new data sets are entered, in particular using the dependency table. Preferably, data sets can be deleted that include the largest Euclidean distance from the statistical average of the other data sets. Data sets that show the largest deviation from the system dependency between the data can preferably be deleted.

[0183] A "data set" is understood as a set of consecutively connected data fields, wherein the data fields preferably comprise input values and / or output values.

[0184] Preferably, the data set comprises the first and second parameters of the method according to the second and / or fifth and / or ninth aspect of the present application.

[0185] An "algorithm" is a well-defined procedure for solving a problem or a class of problems. Preferably, the algorithm comprises a finite number of defined individual steps. Thus, the individual steps can be implemented in a computer program for execution, but can also be formulated in human language. Preferably, the algorithm supports a solution of a problem in that a certain input, preferably an input of a data set, can be transformed into a certain output by means of the algorithm.

[0186] A "curve" is understood as a two-dimensional, three-dimensional or multi-dimensional relationship between variables. Preferably, the system dependency relationship can be in the form of an (n+i)-dimensional curve of order m, taking into account an n-dimensional input and an i-dimensional output.

[0187] Preferably, the curve is the image of a continuous function from an interval to a topological space.

[0188] A "determination coefficient" is understood as the proportion of the variance in the dependent variable that can be predicted from the independent variables.

[0189] Preferably, the determination coefficient provides a measure of how well a model reproduces the observed results based on the proportion of the total variation explained by the results of the model.

[0190] A "regression analysis" is understood as a collection of statistical processes for estimating relationships between variables. When the focus is on the relationship between a dependent variable and one or more independent variables, it includes several techniques for modeling and analyzing several variables. Preferably, the regression analysis helps people understand how the typical value of the dependent variable changes when any of the independent variables change while the other independent variables are held fixed.

[0191] Preferably, the regression analysis is understood as one of the following analytical models: linear regression, simple regression, polynomial regression, generalized linear models, binomial regression or non-linear regression, etc.

[0192] An "optimization process" is understood as maximizing or minimizing a function by systematically choosing input values from an allowed set and computing the value of the function.

[0193] A "self-learning optimization method" is a class of algorithms that can also be classified under the general term "machine learning". The characteristic of the corresponding algorithms lies in the fact that they learn from instances on the one hand and can generalize the learned knowledge on the other hand. Thus, such algorithms generate knowledge from experience.

[0194] "optimizing" means any process aiming at finding an optimal value, in particular an optimal value of an input quantity, by maximizing the degree of achievement of a target, in particular by minimizing or maximizing a corresponding target function and / or by selecting input quantity values known to enable or to indicate an optimal achievement of the target.

[0195] In particular, it should be made clear that optimizing does not necessarily imply finding the exact optimal value of an input quantity.

[0196] "distance" is understood as the distance between two points that the motor vehicle has already covered or will cover or is planned to cover.

[0197] Preferably, the distance is the shortest distance between two points that the motor vehicle can cover.

[0198] Preferably, the distance is the fastest connection of two points that the motor vehicle can cover.

[0199] Preferably, the route planning establishing the distance is performed with the help of a navigation system.

[0200] The actual availability can be "sufficient to bridge the distance to the next cleaning process" if it can be used to cover the upcoming or planned distance until the next cleaning process without falling below the predefined availability threshold. In other words, in this case, the available availability is fully sufficient so that the planned distance can be covered until the next cleaning process of the motor vehicle without losing the functionality of the sensors linked to the corresponding availability area.

[0201] "expected distance of the motor vehicle to be covered when reaching the availability threshold" is the expected distance that the motor vehicle can cover until reaching the predefined availability threshold.

[0202] "operating time" is the duration of the usage cycle of the motor vehicle, which has already passed or is pending or planned.

[0203] The actual availability can be "sufficient to bridge the operating time to the next cleaning process" if it can be used to cover the operating time pending or planned until the next cleaning process without falling below the predefined availability threshold. In other words, in this case, the available availability is fully sufficient so that the motor vehicle can cover the planned operating time until the next cleaning process without losing the functionality of the sensors linked to the corresponding availability area.

[0204] "expected operating time of the motor vehicle to be covered when reaching the availability threshold" is the expected operating time that the motor vehicle can cover until reaching the predefined availability threshold.

[0205] A "coordinate" is the geographical position of a motor vehicle on earth, which can be a coordinate that has already been passed, an actual or current coordinate or a coordinate on a planned route.

[0206] Preferably, a coordinate can also be understood as a progress of a coordinate on a route that has already been completed or is planned.

[0207] A "cleaning strategy" is a plan of how a cleaning system behaves in every conceivable situation. The cleaning strategy thus completely describes the behavior of the cleaning system.

[0208] Preferably, the cleaning strategy contains which surface is cleaned when and with which intensity.

[0209] Preferably, the cleaning strategy includes a control quantity setpoint for each selected sensor.

[0210] Preferably, the cleaning strategy depends on one or more influencing factors, in particular on the actual availability of the sensors.

[0211] A "cleaning mode" or "actual cleaning mode" is an operating mode of the cleaning system. By selecting a cleaning mode, the manufacturer and / or the driver of the motor vehicle can influence which driver assistance systems should not fail due to sensor contamination, wherein the selected cleaning mode can also include that no cleaning should take place. This can directly influence the availability of the driver assistance systems.

[0212] Since the cleaning mode determines whether and how many driver assistance systems are to be protected from failure due to excessive contamination as a result of cleaning measures, the selection of the cleaning mode also determines the number of "selected sensors" for which the availability threshold should not be undershot, so that the "selected sensors" can also be indirectly influenced.

[0213] The selected cleaning mode thus also determines the resource consumption of the cleaning system, or in other words, the expected remaining range of the motor vehicle with the available cleaning resources.

[0214] Preferably, there can be one or more cleaning modes, wherein one or more cleaning modes can be selected at the same time.

[0215] Preferably, a first cleaning mode has the meaning "fully autonomous motor vehicle operation", which means that the cleaning system takes all necessary cleaning measures to ensure that the autonomous operation of the motor vehicle does not fail due to contamination of the sensors of the motor vehicle.

[0216] Preferably, the second cleaning mode has the meaning "comfortable operation of the motor vehicle", which means that the cleaning system takes all necessary cleaning measures to prevent the comfortable operation of the motor vehicle from failing due to contamination of the sensors of the motor vehicle. This includes, inter alia, the cleaning system maintaining the functionality of the driver assistance systems distance maintenance, lane keeping, parking assistance, parking aid and / or trailer assistance by means of the necessary cleaning measures.

[0217] Preferably, the third cleaning mode has the meaning "as safe as possible operation of the motor vehicle", which means that the cleaning system takes all necessary cleaning measures to ensure that the safe operation of the motor vehicle does not fail due to contamination of the sensors of the motor vehicle. This includes, inter alia, the cleaning system maintaining the functionality of the driver assistance systems pedestrian recognition and / or road user recognition by means of all necessary cleaning measures.

[0218] Preferably, the fourth cleaning mode has the meaning "best possible range", which means that the cleaning system only takes those cleaning measures for the operation of the motor vehicle that are prescribed by law.

[0219] The cleaning mode "best possible range" is preferably used to achieve the best possible range of the motor vehicle with the available cleaning resources.

[0220] A "system component" is understood to be any component of the cleaning system. It should be expressly stated that a system component can be understood to be the complete cleaning system as well as individual assemblies of the cleaning system and individual components of the cleaning system.

[0221] In particular, the term system component is used in the context of the diagnosis of the cleaning system. Since each physical component of the cleaning system can also be diagnosed by means of at least one diagnostic device, the term "system component" in particular refers to a component or assembly or the cleaning system as an object of observation and / or analysis in connection with the diagnosis.

[0222] Under certain conditions, a "current" can flow in an electrical circuit. Furthermore, the electrical circuit can have a consumer, in particular a consumer which implements a useful application, preferably in the form of a system component. The consumer can have a "power consumption", which represents the demand of the consumer for energy.

[0223] A consumer which implements an electrical application requires energy for its work. In particular, it can be envisaged that a consumer can have a varying power consumption for the same work performed. The reason for this can be different operating conditions, in particular different ambient temperatures, and / or aging effects of the consumer.

[0224] Preferably, the current signal is indicative of information about the electric flux, electric transients, electric noise, electric noise, etc.

[0225] "Fluid pressure" is the pressure in a fluid, in particular the pressure in a cleaning fluid, wherein the fluid pressure consists of a static component and a dynamic component. The local fluid pressure is determined locally, in particular with a pressure sensor.

[0226] "Operation time" is the individual operation time of a system component.

[0227] "Fill level signal" is understood as information which directly describes the value of the fill level in a storage container and indirectly describes the amount of the stored substance.

[0228] "Reaction time" is generally understood as the period between action and reaction, in particular the time between a measure and the effect of the measure.

[0229] "Sensing time" is the time in which a change in a signal can be perceived, in particular the time between the beginning of a change in the tank level and the end of the change in the tank level.

[0230] "Signal of the flow meter" is the information provided by the flow meter, which provides information about the amount of liquid which has flowed through the channel in a given unit of time, in particular the amount of cleaning liquid which has flowed through the channel.

[0231] "Signal of the leak sensor" is the information provided by the leak sensor, which provides information about the presence of a leak and / or the amount of the leaking liquid flow. In particular, the leak sensor can comprise a sensor which is attached to the connectors of two fluid channels.

[0232] "Actuation number" is the number of uses of a system component. In particular, the number of pumping operations which have been performed with a pump or the number of heating operations which have been performed with a heater can be considered.

[0233] "Ejection pattern" is the pattern which the cleaning fluid leaves on the surface to be cleaned after leaving the washing nozzle.

[0234] "Thermal monitoring signal" is understood as the information provided by the thermal monitoring system, which provides information about the temperature of the surface and / or the heat flow on the surface.

[0235] "Signal of the debris sensor" is understood as the information provided by the debris sensor, which provides information about the number and / or type of foreign objects in the cleaning system.

[0236] "Signal of the check valve" is understood as the information provided by the check valve, which indicates the check valve position.

[0237] "Signal of the drip flow sensor" is understood as the information provided by the drip flow sensor, which indicates the presence and / or the amount of liquid and / or the rain intensity and / or the snow intensity.

[0238] A "signal of the distance sensor" is understood to be information provided by the distance sensor which is indicative of the distance between the sensor and an object detected by the sensor.

[0239] A "signal of the force sensor" is understood to be information provided by the force sensor which is indicative of the presence and / or magnitude of a force.

[0240] The "actual system behavior" is an observable system behavior of a system component of a cleaning system for a motor vehicle. Preferably, the actual system behavior can be monitored and / or determined by means of a measuring system. Preferably, the actual system behavior can be described by an actual output quantity which is preferably determined by the measuring system, preferably by a sensor.

[0241] It is expressly pointed out that the actual output quantity can be understood to be a scalar and a vector. If the actual output quantity has only one parameter, it is a scalar. If the actual output quantity has several parameters, in particular a course of parameters over time, the actual output quantity is a vector.

[0242] Preferably, the actual output quantity is designed to describe the system behavior of the system component, preferably with all parameters relevant to the characterization of the system behavior.

[0243] The expected system behavior is an expected system behavior of a system component of a cleaning system for a motor vehicle based on experimental values. Similar to the actual system behavior and the actual output quantity, the expected system behavior can be described by an "expected output quantity".

[0244] It is expressly pointed out that the expected output quantity can also be a scalar or a vector similar to the actual output quantity.

[0245] The "deviation" is the difference between the expected output quantity and the actual output quantity. The deviation can thus also be a scalar or a vector. Preferably, the deviation comprises the dimensionality of the actual output quantity.

[0246] In particular, the deviation can comprise a system typical measurement error. In particular, the size of this system typical measurement error can vary depending on any dimension of the deviation, wherein the size of the measurement error can in particular depend on the measuring system used to determine the output quantity.

[0247] If the deviation is within a specified measurement error, there is a numerical deviation, but in this case the actual system behavior preferably does not deviate from the expected system behavior.

[0248] The system behavior of a system component of a cleaning system for a motor vehicle can be influenced by measurement errors and further fluctuations and / or deviations which can lie within the expected range. These expected non-critical deviations and / or fluctuations can be different for each dimension of the output quantity.

[0249] A "time course", in particular a deviating time course, is a data series as a function of time, in particular a data series with deviating data.

[0250] A data series can consist of at least two, preferably at least 10 and preferably at least 20 data points distributed over time.

[0251] Preferably, the data points have an equidistant time distance from each other.

[0252] Preferably, the time intervals between the data points increase. It is particularly preferred that the time distance of the data points is proportional to the logarithm of time.

[0253] A "step response" is an output signal of a system, in particular of a system component of a cleaning system, which reacts to a planned change in the input quantity. Preferably, it can be used advantageously for the characterization of a linear time-invariant system. Preferably, the time course of the step response can be used to draw conclusions about the presence of a decay in the system, wherein it can be advantageously determined, for example, in particular whether a blockage of a flow channel for a cleaning fluid is present.

[0254] A "drift" is a system deviation which changes continuously in one direction.

[0255] Preferably, a drift of an output signal of a system component can enable statements about aging phenomena of the system component. The drift can be used in particular to determine how long the system component can still be used. Specifically, the drift can be used to analyze when the system component should be replaced in order to avoid a failure of the system component.

[0256] Overall, the system behavior of a system component preferably deviates from the permissible system behavior only if the output quantity exceeds an "upper threshold quantity" and / or falls below a "lower threshold quantity", taking into account any measurement errors and expected non-critical fluctuations.

[0257] It should be expressly stated that, like the desired output quantity or the actual output quantity or the deviation, the upper threshold quantity and / or the lower threshold quantity can be a scalar or a vector. Preferably, the upper threshold quantity and / or the lower threshold quantity comprise the dimension of the output quantity.

[0258] Preferably, it is a non-permissible deviation if the output quantity exceeds the upper threshold quantity in one dimension or falls below the lower threshold quantity in one dimension.

[0259] Preferably, the upper threshold and the lower threshold can depend on the input quantity, since the system behavior of a system component depends on the input quantity in some cases, wherein in some cases the expected system behavior of the system component and / or the reversible range of the actual output quantity can also depend on the input quantity.

[0260] "Diagnosis" is generally understood as a comparison between an observed system behavior of a system component of a cleaning system and an expected system behavior.

[0261] In particular, "diagnosis" denotes a process of monitoring an output quantity and determining whether the observed system behavior of a system component deviates from the expected system behavior within an admissible range, in particular by comparing the output quantity with an upper threshold quantity and / or a lower threshold quantity.

[0262] Likewise, an inadmissible deviation of the actual system behavior can be assessed, preferably based on a percentage limit value depending on the expected output quantity.

[0263] Diagnosis can also preferably be understood as a characterization of a possible deviation. This characterization can preferably be performed based on a time course of the output quantity.

[0264] "Diagnosis signal" preferably describes a result of a method for diagnosing a system behavior of a system component of a cleaning system of a motor vehicle.

[0265] The diagnosis signal can in particular indicate that the actual system behavior corresponds exactly to the expected system behavior.

[0266] The diagnosis signal can also indicate that the actual system behavior does not correspond to the expected system behavior, wherein the diagnosis signal preferably also contains in which form and based on which components of the output quantity the actual system behavior does not correspond to the expected system behavior.

[0267] "Current diagnosis signal" is understood as a diagnosis signal which is currently present and for which a resolution strategy is searched.

[0268] "Resolution strategy" is understood as a procedure which is adapted to eliminate a deviation between an actual system behavior of a system component of a cleaning system and an expected system behavior of this system component depending on available experimental values.

[0269] "Contamination process" is understood as an accumulation of a surface contamination and / or a pollution.

[0270] "Contamination situation" is understood as a current state of a contamination and / or a surface contamination.

[0271] "First availability" is understood as a first state of availability. "Second availability" is understood as a second state of availability, wherein a time has passed between the first availability and the second availability.

[0272] Preferably, the motor vehicle is driven between the first availability and the second availability.

[0273] Preferably, the motor vehicle increases its operating time between the first availability and the second availability.

[0274] Due to the increasing number of driver assistance systems, the number of sensors in a vehicle, in particular the number of sensors having an optical operating principle, has also increased. In particular, sensors having an optically active principle depend on the fact that the surface portion of the motor vehicle which is actively connected to the sensor, in particular to a sensor having an optically active principle, can only comprise an upper limit of contamination.

[0275] If the contamination of this portion of the surface of the motor vehicle is higher than this maximum contamination, the functionality of the sensor can no longer be guaranteed to a sufficiently high degree, wherein the functionality of the driver assistance system is also influenced by the contamination situation.

[0276] As a result, the maintenance of the functionality of the driver assistance system requires cleaning the surface which is actively connected to the respective sensor which delivers data for the driver assistance system, which also increases with the increasing number of sensors.

[0277] For this cleaning work, sufficient cleaning resources, in particular cleaning fluid and electrical power, are required. Thus, the increasing cleaning requirements also increase the demand for cleaning fluid which has to be stored in the motor vehicle for cleaning the relevant surface. This leads to an increasing space requirement for the cleaning fluid reservoir and also to an increasing weight of the motor vehicle.

[0278] The system component requires neither additional weight nor additional space.

[0279] For this purpose, a specific cleaning method is proposed herein for a resource-efficient, preferably resource-saving, cleaning of at least a portion of the surface of a motor vehicle.

[0280] Resource-efficient cleaning is to be understood as meaning that the cleaning of the surface to be cleaned is optimized in such a way that the ratio of the cleaning effort to the cleaning effort is taken into account. In other words, resource-efficient cleaning requires that the control variables for the cleaning process are selected in such a way that the greatest possible cleaning success can be achieved with the least possible effort, wherein the control variable setpoint at least indirectly determines the amount of resources required for the cleaning process to clean the surface.

[0281] Resource-saving cleaning is to be understood as meaning that the cleaning of the surface to be cleaned is optimized in accordance with the most important cleaning objectives to be achieved, preferably the cleaning objectives can lie in the fact that a defined number of safety functions of the motor vehicle do not fail due to surface contamination, in particular due to sensor surface contamination or due to impairment of the sensor functionality caused by contamination. A preferred cleaning objective can also be that the level of autonomy of the motor vehicle does not have to be abandoned due to surface contamination, in particular due to sensor surface contamination or due to impairment of the sensor functionality caused by contamination.

[0282] The cleaning method presented here uses a cleaning system of a motor vehicle and plans and / or optimizes and / or carries out individual cleaning processes, wherein each individual cleaning process involves cleaning of individual partial surfaces of the motor vehicle by using cleaning means, in particular cleaning fluid, etc.

[0283] Each cleaning process also comprises a time span in which the cleaning process is carried out, wherein the cleaning process comprises a start time and an end time of the time span.

[0284] The cleaning system comprises an electronic control unit, a cleaning fluid dispensing system, which preferably comprises at least one fluid reservoir, at least one nozzle, and at least one cleaning fluid line connecting the cleaning fluid reservoir with the washing nozzle.

[0285] Within the scope of the cleaning method presented here, the cleaning success is recorded at least partially automatically, since a sensor that is actively connected to the surface to be cleaned is preferably able or arranged to forward the availability of the sensor to the cleaning system, wherein the availability of the sensor at least indirectly represents a measure of the cleaning state of the surface that is actively connected to the sensor.

[0286] Furthermore, it is suggested that the cleaning system has access to or has available information about the availability of the sensor and thus about the cleaning state of the surface to be cleaned that is actively connected to the sensor.

[0287] Furthermore, the sensor can be arranged to detect process quantities, in particular humidity and / or temperature and / or rainfall and / or snowfall in the vicinity of the motor vehicle.

[0288] The cleaning system can have further sensors or be connected to further sensors, which can provide the cleaning system with measured quantities, in particular process quantities and / or control quantities. In this way, temperatures or rainfalls, etc. can also be made available to the cleaning system by other sensors. This also includes the transmission of corresponding data to the cleaning system, which the motor vehicle can retrieve via a wireless data connection, if necessary.

[0289] In particular, the cleaning system can also be provided with control values of the coordinates and / or control quantities of the motor vehicle.

[0290] In particular, a cleaning method is to be considered, which uses information about the system behavior of the cleaning system and / or which itself can provide this information, in particular by means of dependency tables and / or system dependencies, in particular by means of dependency tables and / or system dependencies according to the second aspect of the invention.

[0291] It is to be understood that the advantages of the dependency table and / or system dependency according to the second aspect of the present application directly extend to the cleaning method according to the first aspect of the present application which applies the dependency table and / or system dependency according to the second aspect of the present application and / or which executes the program for deriving a dependency table and / or system dependency according to the second aspect of the present application as described in the second aspect of the present application.

[0292] Further, a cleaning method is proposed which applies a control quantity setpoint, in particular a control quantity setpoint derived by the method according to the third aspect of the present application, for controlling the resource-efficient cleaning, preferably the resource-saving cleaning.

[0293] It is to be understood that the advantages of the control quantity setpoint according to the third aspect of the present application directly extend to the cleaning method according to the first aspect of the present application which applies such a control quantity setpoint as described in the third aspect of the present application.

[0294] Further, a cleaning method is proposed which applies a cleaning strategy, in particular a cleaning strategy derived by the method according to the fourth aspect of the present application, for controlling the resource-efficient cleaning, preferably the resource-saving cleaning.

[0295] It is to be understood that the advantages of the cleaning strategy according to the fourth aspect of the present application directly extend to the cleaning method according to the first aspect of the present application which applies such a cleaning strategy as described in the fourth aspect of the present application.

[0296] In particular, a cleaning method is to be considered which uses information about the system behavior of the system components of the cleaning system and / or which can provide this information itself, in particular by means of a dependency table and / or system dependency, in particular by means of a dependency table and / or system dependency according to the fifth aspect of the present application.

[0297] It is to be understood that the advantages of the dependency table and / or system dependency according to the fifth aspect of the present application directly extend to the cleaning method according to the first aspect of the present application which applies the dependency table and / or system dependency according to the fifth aspect of the present application and / or which executes the program for deriving a dependency table and / or system dependency according to the fifth aspect of the present application as described in the fifth aspect of the present application.

[0298] In particular, a cleaning method is also to be considered which comprises process steps for diagnosing the system behavior of the system components of the cleaning system of the motor vehicle, preferably process steps for diagnosing the system behavior of the system components of the cleaning system according to the first alternative of the sixth aspect of the present application.

[0299] It is to be understood that the advantages of the method of diagnosing the system behavior of a system component of a cleaning system according to the first alternative of the sixth aspect of the present application as described in the sixth aspect of the present application directly extend to a cleaning method comprising the process steps for diagnosing the system behavior of a system component of a cleaning system according to the first aspect of the present application.

[0300] In particular, it is to be considered that a cleaning method comprising process steps for diagnosing a deviation between an actual system behavior and an expected system behavior of a system component of a cleaning system of a motor vehicle, preferably for diagnosing a deviation between an actual system behavior and an expected system behavior of a system component of a cleaning system of a motor vehicle according to the second alternative of the sixth aspect of the present application is to be considered.

[0301] It is to be understood that the advantages of the method of diagnosing a deviation between an actual system behavior and an expected system behavior of a system component of a cleaning system of a motor vehicle according to the second alternative of the sixth aspect of the present application as described in the sixth aspect of the present application directly extend to a cleaning method comprising process steps for diagnosing a deviation between an actual system behavior and an expected system behavior of a system component of a cleaning system according to the first aspect of the present application.

[0302] It is to be considered that a cleaning method comprising process steps for selecting a resolution strategy, preferably according to the seventh aspect of the present application is to be considered.

[0303] It is to be understood that the advantages of the method of selecting a resolution strategy, preferably according to the seventh aspect of the present application as described in the seventh aspect of the present application directly extend to a cleaning method according to the first aspect of the present application applying such a method for selecting a resolution strategy.

[0304] Furthermore, it is to be considered that a cleaning method comprising process steps for using a selected resolution strategy, preferably according to the eighth aspect of the present application is to be considered.

[0305] It is to be understood that the advantages of the method of using a selected resolution strategy, preferably according to the eighth aspect of the present application as described in the eighth aspect of the present application directly extend to a cleaning method according to the first aspect of the present application applying such a method for using a selected resolution strategy.

[0306] In particular, a cleaning method shall be considered which uses information about the systematic behavior of the contamination process of the surface of the motor vehicle and / or which itself can provide this information, in particular by means of dependency tables and / or system dependencies, in particular by means of dependency tables and / or system dependencies according to the ninth aspect of the present application.

[0307] It shall be understood that the advantages of the dependency tables and / or system dependencies according to the ninth aspect of the present application as described in the ninth aspect of the present application directly extend to the cleaning method according to the first aspect of the present application which applies dependency tables and / or system dependencies according to the ninth aspect of the present application and / or executes a procedure according to the ninth aspect for deriving dependency tables and / or system dependencies.

[0308] In particular, in the cleaning method proposed here, the use of dependency tables and / or system dependencies according to the ninth aspect of the present application shall be considered for determining the expected availability at a distance or operating time to be covered by the motor vehicle, preferably according to the tenth aspect of the present application, and / or for determining the expected distance or expected operating time to be covered by the motor vehicle at the time of reaching the availability threshold, preferably according to the eleventh aspect of the present application, and / or for optimizing the resource requirements for cleaning the surface of the motor vehicle, in particular by applying the method for optimizing the resource requirements for a cleaning process of a surface of a motor vehicle according to the third aspect of the present application, and / or for determining a cleaning strategy for cleaning the surface to be cleaned of the motor vehicle, in particular by applying the method for determining a cleaning strategy for cleaning a surface to be cleaned of a motor vehicle according to the fourth aspect of the present application, and / or for determining a necessary expected availability gain, preferably according to the fourteenth aspect of the present application, wherein the sum of the actual availability and the necessary expected availability gain is sufficient to achieve the distance or operating time to be covered by the motor vehicle in such a way that the availability threshold is not exceeded.

[0309] It is to be understood that the advantages of using the dependency table and / or the system dependency according to the ninth aspect of the application for preferably determining the expected availability at a distance or operating time to be covered by the motor vehicle according to the tenth aspect of the application and / or for preferably determining the expected distance or expected operating time to be covered by the motor vehicle when reaching the availability threshold according to the eleventh aspect of the application and / or for optimizing the resource requirements for cleaning the surface of the motor vehicle, in particular by applying the method for optimizing the resource requirements for cleaning the surface of the motor vehicle according to the third aspect of the application and / or for determining the cleaning strategy for cleaning the surface to be cleaned of the motor vehicle, in particular by applying the method for determining the cleaning strategy for cleaning the surface to be cleaned of the motor vehicle according to the fourth aspect of the application and / or for determining the necessary expected availability gain, wherein the sum of the actual availability and the necessary expected availability gain is sufficient to achieve the distance or operating time to be covered by the motor vehicle in a manner that does not exceed the availability threshold, as described in the ninth aspect and / or the tenth aspect and / or the eleventh aspect and / or the twelfth aspect and / or the thirteenth aspect and / or the fourteenth aspect of the application, directly extend to the cleaning method according to the first aspect of the application using such a dependency table and / or such a system dependency as described above.

[0310] In an advantageous embodiment, the electronic control unit controls and / or regulates the resource-efficient cleaning, preferably the resource-saving cleaning, depending on the actually determined value of the sensor, preferably the actual availability, which is operatively connected to the surface to be cleaned.

[0311] Here, it is now specifically proposed, inter alia, that the cleaning method should be carried out in a specified manner.

[0312] In other words, the cleaning method should not only be controlled according to specifications, but also applied within the framework of regulations.

[0313] The cleaning method should be regulated according to the determined quantity, in particular according to the availability of the sensor, the surface of which is actively connected thereto and is currently being cleaned by means of the cleaning process that is part of the cleaning method.

[0314] In other words, it is specifically proposed to regulate each individual cleaning process carried out in the context of the cleaning method on the basis of the availability of the associated sensor.

[0315] The advantage is that deviations in the cleaning result can be reacted to on a case-by-case basis by feedback about the information on the current cleaning state, in particular by means of the availability of the associated sensor.

[0316] This allows an effective cleaning process to be discontinued earlier than planned, thus saving additional resources and preventing overcleaning of the surface to be cleaned.

[0317] Furthermore, it can be advantageously achieved that a cleaning process which is less efficient than expected can be performed for a longer time than planned, wherein an overall resource-optimized cleaning result can be advantageously achieved by an overall assessment, even if additional resources have to be used for such individual cleaning processes, resources can still be saved overall.

[0318] Preferably, the cleaning method starts the cleaning process as soon as a predefined threshold of availability of the sensor is reached, preferably if the surface to be cleaned by the cleaning process is not currently excluded from cleaning by means of the cleaning strategy.

[0319] It is proposed here that the cleaning process, in particular a cleaning process pre-planned by means of a control quantity setpoint, is started depending on the occurrence of a trigger condition, in particular as soon as a predefined threshold of availability of the sensor is reached.

[0320] In this way, it can be advantageously achieved that resources for cleaning can be saved, since the start of the cleaning process is never earlier than technically necessary.

[0321] Furthermore, it is proposed that the cleaning method starts the cleaning process if the availability of the sensor is less than or close to a predefined threshold of availability of the sensor.

[0322] This is particularly advantageous for the cleaning method to start the cleaning process, in particular an overdue cleaning process, even after a malfunction of the cleaning system and / or after replenishing previously insufficient cleaning resources.

[0323] In particular, it should be preferred to consider that the cleaning method described here is applied to all surfaces with which the sensor is actively connected and / or to surfaces with which the sensor is actively connected according to the current cleaning pattern requirements / selection and / or to surfaces with which the sensor is actively connected according to a preselected future cleaning pattern requirements / selection.

[0324] Advantageously, the cleaning method forces a change in the cleaning pattern if it is not realistic to achieve the planned route with the currently selected cleaning pattern.

[0325] If the pre-planned destination can no longer be reached with the pre-selected cleaning pattern, it is proposed to change the cleaning pattern in such a way that the pre-planned route can still be executed without having to change the cleaning pattern further, wherein the cleaning pattern can be selected which is affected by the above-mentioned conditions in such a way that the driver can have the most comfortable possible driving experience.

[0326] The advantage of this is that the planned destination can be reached with the available cleaning resources under conditions in which the driver can be most comfortable without having to replenish the cleaning resources during a service.

[0327] In particular, it should be preferred to consider that the cleaning method described herein is applied to all surfaces actively connected with sensors and / or to surfaces actively connected with sensors required / selected according to the current cleaning mode and / or to surfaces actively connected with sensors required / selected according to a preselected future cleaning mode.

[0328] In an advantageous embodiment, the cleaning method proceeds to keeping only sensors absolutely necessary for manual driving sufficiently available by performing a corresponding cleaning process if the cleaning resources have reached a reserve level.

[0329] A reserve strategy is proposed here as a last resort measure, in which the cleaning mode is changed by the cleaning system to such an extent that only sensors absolutely necessary for manual driving remain sufficiently available in the event that the preplanned destination is endangered in the absence of service maintenance and thus the cleaning mode is not adapted to a lower level of cleaning resource consumption at an early stage.

[0330] Optionally, it is proposed to take this measure as late as possible so that with the last available cleaning resources, the destination of the driving route can just be reached.

[0331] The advantage of this is that the driver can only be forced to intervene more in the driving of the motor vehicle as late as absolutely necessary.

[0332] Furthermore, as a modification according to a further optional embodiment, it is proposed to wet surfaces that are sometimes only actively connected with unnecessary sensors with a spray of cleaning fluid.

[0333] In this way, it can be advantageously achieved that surfaces that are not actively connected with one of the necessary sensors are not dried and thus advantageously prevent the build-up of contamination present on the surface. In this way, it can be advantageously achieved that another cleaning process aimed at the direct cleaning of the surface can be achieved with less cleaning resources, since it does not have to remove a crust of dirt in a short time, but dirt that has been soaked or pre-soaked.

[0334] In other words, a cleaning process aimed at the immediate cleaning of the surface is not specifically proposed here, but a cleaning process is proposed that makes a subsequent cleaning process aimed at the immediate cleaning of the surface easier to achieve with less resource expenditure for a better cleaning result, in particular a higher availability gain.

[0335] More effective cleaning processes can be achieved in combination.

[0336] In particular, it should be preferred to consider that the cleaning method described herein is applied to all surfaces that are actively connected with sensors and / or to surfaces that are actively connected with sensors that are required / selected according to a current cleaning pattern and / or to surfaces that are actively connected with sensors that are required / selected according to a preselected future cleaning pattern.

[0337] Optionally, the cleaning method comprises a cleaning procedure that is adapted to wet the surface to be cleaned.

[0338] It is proposed herein a cleaning method comprising a cleaning procedure that is designed to wet the surface to be cleaned.

[0339] The cleaning method should preferably comprise two cleaning procedures, wherein a first cleaning procedure from a temporal point of view is designed to wet the surface only, so that any incrustation dirt on the surface to be cleaned is softened. An advantage is that the contamination is more easily dissolved in the subsequent cleaning procedure.

[0340] A second cleaning procedure from a temporal point of view is designed to reduce or remove the previously softened dirt by using a cleaning device.

[0341] Furthermore, it should be specifically considered that a plurality of cleaning procedures is carried out before a cleaning procedure is set for cleaning the surface to be cleaned, each of the plurality of cleaning procedures being intended to wet the surface to be cleaned. These cleaning procedures that are set to humidify the surface can take place during an active and / or passive operating state of the motor vehicle.

[0342] In this way, it can be advantageously prevented that dirt on the surface to be cleaned dries.

[0343] It can thus be particularly envisaged that the surface to be cleaned of the motor vehicle can also be wetted by means of a cleaning procedure in a parked state.

[0344] An advantage is that the overall resource efficiency can be improved when cleaning the surface to be cleaned.

[0345] In particular, it should be preferred to consider that the cleaning method described herein is applied to all surfaces that are actively connected with sensors and / or to surfaces that are actively connected with sensors that are required / selected according to a current cleaning pattern and / or to surfaces that are actively connected with sensors that are required / selected according to a preselected future cleaning pattern.

[0346] In an optional embodiment, the cleaning method comprises a cleaning procedure that is adapted to be started when an operating condition of the motor vehicle changes.

[0347] It is proposed herein that the cleaning method is adapted to start a cleaning procedure when an operating condition of the motor vehicle changes.

[0348] Preferably, it should be considered that the cleaning method initiates the cleaning process at the start of the motor vehicle, i.e. at the transition from the passive operating state of the motor vehicle to the active operating state, so that the availability of the sensors at the beginning of the journey can be improved, in particular in such a way that the minimum availability of the sensor-implemented function sensors is operated.

[0349] Furthermore, it should also be considered that the cleaning method, which changes the cleaning mode by initiating the cleaning process, is designed for the minimum availability of the sensor-implemented function sensors required in the newly selected cleaning mode.

[0350] The advantage of this is that the cleaning method can react to changes in the operating state of the motor vehicle depending on the situation.

[0351] In particular, it should preferably be considered that the cleaning method described here is applied to all surfaces that are actively connected to the sensors and / or to the surfaces that are actively connected to the sensors required / selected according to the current cleaning mode and / or to the surfaces that are actively connected to the sensors required / selected according to a preselected future cleaning mode.

[0352] According to a second aspect of the application, the task is solved by a method for indirectly deriving a system dependency of a system behavior of a cleaning system of a motor vehicle, in particular of a cleaning process of a surface of a motor vehicle, wherein an output quantity depends on an input quantity by means of the system behavior of the system, for the cleaning, preferably for resource-efficient cleaning, particularly preferably for resource-saving cleaning, of at least one surface of a motor vehicle, comprising the following steps:

[0353] - determining the input quantity as a first parameter of the method by means of at least one sensor;

[0354] - determining the output quantity as a second parameter of the method, preferably by means of at least one sensor;

[0355] - digitizing, if necessary, and recording the determined first and second parameters by a data processing system, wherein the data processing system comprises an electronic data processing and evaluation system and a database;

[0356] - storing the determined first and second parameters as a data set of a dependency table in an ordered manner with respect to each other in the database;

[0357] - deriving the systematic dependency between the first parameter and the second parameter from at least two data sets of the dependency table stored in the database, preferably from at least 50 data sets of the dependency table, particularly preferably from at least 200 data sets of the dependency table, by means of an electronic data processing and evaluation system, wherein the electronic data processing and evaluation unit accesses the data sets of the dependency table and determines the systematic dependency from the data sets by means of an algorithm; and

[0358] - storing the derived systematic dependency in the database and / or in the electronic data processing and evaluation unit and / or in the electronic control unit, preferably.

[0359] Previously, it was common practice to clean the surfaces of the vehicle either on demand by the driver or automatically at predetermined intervals or when contamination was detected.

[0360] With the increasing number of sensors in motor vehicles and the resulting increase in safety through driver assistance systems by autonomous driving, the relevance of cleaning the surfaces of motor vehicles, in particular the surfaces superimposed on the sensors, has significantly increased.

[0361] The surfaces superimposed on the sensors are defined in particular as the outermost surfaces of the motor vehicle that cover the sensors, in particular the windshield, the rear window, the camera lens and / or the sensor cover.

[0362] As the demand for cleaning increases, the demand for resources to clean the corresponding surfaces also increases.

[0363] This makes the need for new cleaning strategies a focus that should enable resource-efficient cleaning, preferably resource-saving cleaning, so that less resources have to be provided for the necessary cleaning processes.

[0364] The link between the cleaning success of a cleaning process and the resulting resource requirement is therefore a focus of consideration, especially if the goal is to be able to perform cleaning as efficiently as possible or even better to save resources.

[0365] Preferably, the cleaning success of a cleaning process can be assessed on the basis of the availability of the sensors before and after the cleaning process.

[0366] The cleaning success is influenced, inter alia, by different process quantities of the cleaning process, in particular by the air humidity and / or the air temperature and / or the amount of rainfall and / or the amount of snowfall and / or the actual solar radiation and / or the temperature of the surfaces to be cleaned.

[0367] In addition, the cleaning success is also influenced by the speed at which the motor vehicle is driven during the cleaning process and the type of motor vehicle. The vehicle type provides information about how much surface is to be cleaned, where the surfaces to be cleaned are located on the motor vehicle and how they are oriented with respect to the direction of movement of the motor vehicle.

[0368] In addition, there are a large number of conceivable cleaning processes which differ in the selection of the respective different control quantities.

[0369] The control quantities determine when, how long and in which form which resource and / or which cleaning device is used to clean the respective surface.

[0370] The resource requirements of the cleaning process can be determined, inter alia, directly or indirectly by the control quantities of the cleaning process.

[0371] When implementing resource-efficient cleaning, preferably resource-saving cleaning, specific questions arise as to which control quantities can be used for which vehicle type, which process quantities and which cleaning successes are achieved at which resource requirements.

[0372] As already explained above, a large number of influencing quantities can be considered which influence the outcome and the resource requirements of the cleaning process, thus increasing the complexity of the questions to be considered here.

[0373] Recently, it has been shown more and more often that the plurality of possibilities influencing the cleaning process in terms of their complexity and due to possible overlaps between individual effects are increasingly intuitively understandable in a range (in which resource-efficient cleaning is located).

[0374] The handling of resource-saving cleaning is more complex in the sense of a resource-optimized cleaning strategy.

[0375] Thus, not only has the amount of work involved in designing the cleaning system and the cleaning strategy increased significantly, but also the resources required have increased, since successful cleaning must be ensured while guaranteeing a certain level of safety, and this goal can be achieved primarily by expanding the use of resources.

[0376] In this respect, the goal of resource-efficient cleaning, preferably resource-saving cleaning, of the surfaces to be cleaned of motor vehicles is currently a highly discussed topic, in particular because the overall system behavior between the input quantities and the output quantities is not determined.

[0377] The acquisition of this necessary information is complex and requires a large amount of effort.

[0378] Unlike the above, a method is proposed here for indirectly deriving a system dependency of the system behavior of a cleaning system of a motor vehicle between input quantities of the system and output quantities of the system, wherein the output quantities depend on the input quantities by means of the system behavior of the system.

[0379] Preferably, the input quantities comprise control quantities of the cleaning method.

[0380] Preferably, the input quantities comprise the pressure of the cleaning fluid and / or the temperature of the cleaning fluid and / or the mixture of the cleaning fluid, in particular the amount of one or more additives, and / or the characteristics of the spray pattern, in particular whether the spray pattern is an oscillating spray pattern and / or a continuous spray pattern and / or a pulsed spray pattern, and / or the alignment of the spray pattern with the surface to be cleaned.

[0381] Preferably, the input quantities comprise process quantities.

[0382] Preferably, the output quantity is the cleaning success of the cleaning method, which can in particular be assessed by the difference between the availability of the sensor before and after the corresponding surface of the cleaning coverage sensor, in particular by the gain in availability.

[0383] Furthermore, it is proposed that the output quantity should show the resource requirement of the cleaning method. The resource requirement can be determined indirectly, in particular from the control quantities or directly based on the corresponding measured values.

[0384] Preferably, the recommendation system relies on a system behavior of the surface of the motor vehicle for a cleaning process of at least one surface of the motor vehicle.

[0385] It is proposed here a procedure, wherein

[0386] - first for discrete cleaning processes, the input quantities are determined as first parameters and the output quantities are determined as second parameters, the data processing system records the determined first parameters and second parameters and stores them as individual data sets of the discrete cleaning processes in a database in an ordered manner relative to one another,

[0387] - then, in particular by means of an algorithm, a system dependency between the first parameters and the second parameters is systematically derived from the plurality of data sets using the plurality of data sets from the dependency table.

[0388] It goes without saying that the first part of the procedure in which the first parameters and the second parameters are recorded must be carried out several times first in order to obtain a large number of data sets for deriving the system dependency, unless existing data can be used.

[0389] The corresponding data sets can be collected directly during the cleaning process carried out on the vehicle, in particular during normal vehicle operation.

[0390] Furthermore, such data sets can also be determined and / or derived from experiments in a laboratory.

[0391] In a further variant, it is conceivable that the data sets are determined by means of a numerical model, which represents the corresponding cleaning process.

[0392] In particular, such data sets are stored in the dependency table and are thus collected in the form of experimental values.

[0393] From these experimental values, a system dependency as proposed herein can be derived. This system dependency can then be used to select or determine an optimal or resource-saving cleaning process.

[0394] Preferably, the system dependency is determined on the basis of at least 2 data sets, preferably on the basis of at least 50 data sets, further preferably on the basis of at least 200 data sets, especially preferably on the basis of at least 1000 data sets.

[0395] It should be noted that the above values for the number of data sets are not to be understood as strict limits, but rather it is possible to exceed it or fall below it on an engineering scale without departing from the described aspects of the application. Simply put, these values are intended to provide an indication of the magnitude of the number of data sets proposed herein.

[0396] By means of the system dependency thus obtained, it is advantageously possible not only to evaluate and reproduce a cleaning process that has already been carried out, but also to design a new cleaning process on the basis of a systematic analysis of the data, wherein, inter alia, the aim of further reducing the resource requirements can be pursued. This can be achieved by interpolation between the available data sets. Furthermore, it is conceivable, in particular using a regression method, to generate a curve from the obtained data sets, which regression method implements a continuous and differentiable system relationship between the input quantities and the output quantities of the cleaning process.

[0397] Preferably, the input quantities are determined by means of at least one sensor.

[0398] Optionally, the output quantities are determined by means of at least one sensor.

[0399] Advantageously, the data processing system comprises an electronic data processing and evaluation system and a database.

[0400] If necessary, it is proposed that the data processing system digitizes the determined first and second parameters, such that the recorded values, in particular the values determined by the sensors, can be managed in a digital database and processed electronically.

[0401] The system dependency between the input quantities and the output quantities, preferably the resource requirements, developed according to the proposed procedure describes the system behavior of the cleaning system.

[0402] Thus, it is specifically conceivable to derive, for each surface to be cleaned, a corresponding system dependency, which takes into account the part of the control quantities that is effectively connected to the corresponding surface, and wherein this system dependency describes the cleaning success and the resource requirements as a function of the part of the control quantities and possibly also as a function of the process quantities, preferably by means of a continuous and differentiable system-determined curve, which curve reflects the mutual dependencies of the quantities.

[0403] In other words, for a plurality of surfaces to be cleaned, a plurality of system dependencies can be derived, in particular the number of surfaces to be cleaned on a vehicle corresponds to the number of derived system dependencies.

[0404] Optionally, the system dependency can be in the form of an (n+i)-dimensional curve of order m, taking into account the n-dimensional input quantity and the i-dimensional output quantity.

[0405] Such a system dependency can be used in a variety of ways. Thus, it can be envisaged, inter alia, that a comparison of the input quantities can be used to find a control quantity with which the surface in question can be cleaned particularly efficiently in terms of resources. Furthermore, it can be specifically considered that, in a comparison of the cleaning success to the resource requirement, a control quantity is sought with which a particularly resource-saving cleaning of the corresponding surface can be achieved.

[0406] Preferably, the input quantity comprises the amount of cleaning fluid used for cleaning the surface to be cleaned.

[0407] Preferably, the input quantity comprises the period in which the cleaning fluid is applied to the surface to be cleaned.

[0408] Preferably, the input quantity comprises the cleaning device, in particular the wiping element, with which the surface to be cleaned is treated.

[0409] Preferably, the input quantity comprises the time in which the cleaning device is used.

[0410] Preferably, the input quantity comprises the type of motor vehicle for which the system dependency is considered.

[0411] Preferably, the input quantity comprises the amount of cleaning fluid used for soaking the surface to be cleaned before it is subsequently treated with the cleaning device. Further preferably, the input quantity also comprises the time for which the surface to be cleaned is soaked until it is subsequently treated with the cleaning device.

[0412] Preferably, the input quantity comprises the amount of cleaning fluid used for cleaning the surface to be cleaned and / or the period in which the cleaning fluid is applied to the surface to be cleaned and / or the cleaning device, in particular the wiping element, used for treating the surface to be cleaned and / or the time in which the cleaning device is used and / or the type of motor vehicle for which the system dependency is considered and / or the amount of cleaning fluid used for soaking the surface to be cleaned before it is subsequently treated with the cleaning device and / or the time for which the surface to be cleaned is soaked until it is subsequently treated with the cleaning device.

[0413] The continuous specification of the system dependency leads to the possibility of an advantageous design of the program and the checking of the robustness of the system dependency. Thus, it can be quantified whether the system dependency is regular or has a tendency with a certain probability that can be controlled by the continuous precision.

[0414] A further advantage of the procedure described herein is that an almost unlimited number of parameters can be stored in reference to one another and used to derive system dependencies, preferably (n+i)-dimensional system dependencies.

[0415] The operator of a suitable cleaning system is naturally limited in his ability to map (n+i)-dimensional system dependencies with respect to the normative decisions about the control quantities in his brain, in particular. Specifically, by constantly increasing the complexity of the corresponding cleaning system and by increasing the number of detectable influencing quantities, the operator now often reaches the limit of his understanding ability. The system dependencies are not affected by this limitation and are therefore advantageous.

[0416] Accordingly, with a suitable implementation of the proposed procedure, the complex correlations between the parameters of the procedure can be mapped. This applies in particular to dependencies with a large number of correlated quantities, which can exhibit various correlations with one another.

[0417] Advantageously, the aspects of the invention presented herein can enable that the system behavior of a cleaning system with all its relevant dependencies can be mapped, so that a rich experience about suitable and resource-efficient cleaning of surfaces of a vehicle type is created.

[0418] Specifically, it can be recorded or derived with which resource-efficient cleaning a single surface of a vehicle type can be effectively cleaned under given environmental conditions and given initial contamination of the corresponding surface.

[0419] It should be expressly pointed out that the result of the cleaning process does not have to be the complete cleaning of the surface. Specifically, it should be specifically considered that the degree of success of the cleaning of the surface is only so small that it remains functional for the sensors hidden behind it.

[0420] This applies in particular to the front and rear windows of a motor vehicle, which are cleaned to such an extent after completion of the cleaning process that at least the sensors behind the windshield, preferably the driver inside the motor vehicle, can operate in a safe driving operation through the front and rear windows in such a way that they do not fail due to contamination of the front and / or rear windows.

[0421] In this way, cleaning resources can advantageously be saved by using a cleaning method with such system dependencies, in which the motor vehicle can be driven safely with the same initial conditions as with existing cleaning resources for a greater distance and / or in which the motor vehicle weight can be reduced, since fewer resources have to be used for the same distance to be covered and / or in which the associated fluid tank of the motor vehicle can be designed to be smaller for the cleaning fluid, whereby installation space within the motor vehicle can be saved.

[0422] Advantageously, the input quantities include at least one measured quantity, preferably a process quantity and / or a control quantity.

[0423] The input quantity is preferably a control quantity.

[0424] If the input quantity does not comprise the determined quantity, the system dependency can conceivably also depend on a default value of the control quantity within the control system framework.

[0425] However, by using the determined quantity, the accuracy of the system dependency can advantageously be increased.

[0426] Preferably, such a determined quantity is a control quantity, so that a system dependency between the output quantity and the control quantity of the cleaning process of the surface to be cleaned of the motor vehicle can be derived and thus later also used for cleaning the corresponding surface, in particular for controlling and / or regulating the cleaning process of the surface to be cleaned.

[0427] Furthermore, it is proposed that the input quantity comprises a process quantity, so that a system relationship between the output quantity and the process quantity, preferably the air humidity and / or the air temperature and / or the actual solar radiation and / or the temperature of the surface to be cleaned, can be derived during the cleaning process of the surface to be cleaned of the motor vehicle and thus later also used for the optimal cleaning of the corresponding surface.

[0428] The advantage of this is that the accuracy of the derived system dependency can be increased while at the same time a plurality of influencing factors from the area of the control quantity and / or the process quantity can be taken into account.

[0429] Preferably, the input quantity comprises a driving speed of the motor vehicle.

[0430] The driving speed of the motor vehicle can influence the cleaning process of the surface to be cleaned, in particular the distribution of the cleaning fluid on the surface to be cleaned and / or the displacement of the cleaning fluid on the surface to be cleaned by the relative air flow and / or the evaporation of the cleaning fluid on the surface to be cleaned, whereby the effective exposure time of the cleaning fluid to the dissolved pollutants can also be influenced.

[0431] If the input quantity contains the driving speed, the influence of the driving speed can also be taken into account for the optimal cleaning of the surface to be cleaned using the system dependency derived here.

[0432] In a preferred embodiment, the input quantity comprises a humidity, in particular a current humidity in the vicinity of the motor vehicle, and / or a temperature in the vicinity of the motor vehicle, in particular a current temperature in the vicinity of the motor vehicle, and / or a precipitation amount, in particular a current precipitation amount in the vicinity of the motor vehicle, and / or a snowfall amount, in particular a current snowfall amount in the vicinity of the motor vehicle, and / or coordinates of the motor vehicle.

[0433] It has been shown that the air humidity and the air temperature are important factors influencing the cleaning success of the cleaning process on the surface to be cleaned.

[0434] To this end, it is proposed herein to derive systematic dependencies on these particularly relevant influencing factors for resource-efficient cleaning.

[0435] It has also been shown that rain and / or snow can make the cleaning process more resource-efficient. In particular, rain and / or snow can cause the deposited dirt to detach or at least soften, thus being more easily dissolved, thus saving cleaning fluid.

[0436] If the effective temperature and / or the effective humidity and / or the effective rainfall and / or the effective snowfall are taken into account when deriving the systematic dependencies, these data can also be taken into account when evaluating the cleaning process.

[0437] In particular, it is conceivable that the current environmental conditions are also taken into account when selecting the cleaning process, in particular the cleaning process specified by the control quantity setpoint, so that an optimal resource-saving and / or resource-efficient cleaning process can be selected and executed.

[0438] Furthermore, it is conceivable that the current coordinates of the vehicle are also taken into account, in particular when the expected temperature and / or the expected humidity and / or the expected rainfall and / or the expected snowfall are taken into account statistically. Thus, it can be specifically envisaged that the expected environmental conditions are determined on the basis of the current coordinates of the vehicle and that an optimal resource-saving and / or resource-efficient cleaning process is selected on the basis of the expected environmental conditions and the systematic dependencies and that this cleaning process is implemented to clean the surface to be cleaned.

[0439] The advantage of this is that important influencing factors can be systematically taken into account when cleaning the surface to be cleaned and thus also in the future in the resource-efficient cleaning, preferably resource-saving cleaning, of the surface, so that resources are saved and the operating safety of the motor vehicle is increased.

[0440] In an optional embodiment, the input quantity comprises a vehicle type.

[0441] The vehicle type provides information on a large number of different influencing factors that affect the cleaning process of a part of the surface of the motor vehicle. These include, inter alia, the installation location of the surface to be cleaned and / or the size of the surface to be cleaned and / or the cleaning device that can be used to clean the surface to be cleaned and / or the expected degree of contamination and / or the expected type of contamination and / or the number of surfaces to be cleaned.

[0442] Furthermore, the vehicle type provides information on the respective installation function type of the sensors and / or the respective installation sensor type, in particular on all different function types and / or sensor types of the sensors located on the motor vehicle, including the assignment to the location at which the respective sensor is installed.

[0443] It is proposed herein to take these influencing factors into account when deriving the systematic dependencies.

[0444] This has the advantage that the system dependency can take into account the influencing factor related to the vehicle type and thus can also be applied individually to each vehicle type in the future for resource-efficient cleaning.

[0445] Advantageously, the input quantity comprises the availability of the sensor.

[0446] The availability of the sensor is a quantity which can ultimately provide information about the degree of contamination of the sensor.

[0447] Particularly preferably, the availability can assume values within an interval, wherein one interval limit reached means that the system can fully meet its requirements, and the other interval limit reached means that the system no longer meets its requirements.

[0448] If the availability value ranges between the interval limits, the system can still meet its requirements, but not under more difficult conditions. In particular, the availability value reflects the degree of contamination of the surface of the motor vehicle, preferably of the surface, preferably of the surface of the sensor, particularly preferably of the surface of the optical sensor and / or of the window through which the driver of the motor vehicle looks, in particular of the windscreen and / or of the rear window, and / or of the headlamps and / or of the rear headlamps.

[0449] It was found that the availability of the sensor before a cleaning process of the surface has an influence on the cleaning success, wherein the same control quantity before the cleaning process but different availability.

[0450] It can be advantageously achieved by the aspects presented here that the availability of the sensor can be considered as an influencing factor of the derived system dependency.

[0451] Preferably, the output quantity comprises the availability of the sensor and / or the availability achieved as a result of the cleaning process.

[0452] The aspects of the application presented here make it possible to determine the cleaning success of the cleaning process, in particular by comparing the availability of the sensor before and after the cleaning process, which is referred to as the gain in availability.

[0453] In other words, the gain in availability is the difference between the availability immediately after the completion of the cleaning process and the availability immediately before the cleaning process.

[0454] Thus, the success of the cleaning process, preferably the gain in availability, can advantageously be quantified by the aspects presented here.

[0455] This enables the future cleaning process to be implemented in an advantageous manner in which the control quantity can be determined by means of a system dependency on the availability of the sensor prior to the cleaning process, by means of which system dependency, on the one hand, a resource-efficient cleaning of the surface to be cleaned can be performed and, on the other hand, a desired availability of the sensor after the cleaning process can be achieved.

[0456] It should also be specifically considered that the selected cleaning process specified by the selection of the control quantity does not necessarily clean the availability of the sensor up to the upper limit of the determinability of the availability of the sensor, but only to the extent required in terms of function-related and / or safety-related aspects.

[0457] Furthermore, it is conceivable that a plurality of cleaning processes specified by their respective control quantity can be performed one after the other in order to achieve an optimal cleaning in terms of resource efficiency and / or functionality of the sensor and / or safety of the motor vehicle.

[0458] It should be specifically considered that such a sequence of cleaning steps has already been defined prior to the first cleaning process.

[0459] Furthermore, it is conceivable that between the cleaning processes of a cleaning sequence for a surface, the availability of the respective sensor will be re-evaluated and the control quantity for the subsequent cleaning process will be determined depending on the availability of the respective sensor achieved at the same time.

[0460] Overall, it can be advantageously achieved that the cleaning of one or more surfaces of the motor vehicle can be run autonomously or at least partially autonomously.

[0461] In an advantageous embodiment, the output quantity comprises a resource requirement for the cleaning process of the surface of the motor vehicle, preferably which is determined depending on the control quantity setpoint for the cleaning process of the surface.

[0462] This can be advantageous because when using the system dependency, in particular when selecting the optimal cleaning process represented by the control quantity setpoint for the current initial conditions, the resource requirement for the cleaning process can be taken into account, from which the cleaning of the surface to be cleaned is optimized.

[0463] In a preferred embodiment, the system dependency is determined by means of a regression analysis.

[0464] Here, the use of a regression algorithm is proposed as an algorithm for indirectly deriving the system dependency.

[0465] Thus, an algorithm can be advantageously applied which has already been tested in a large number of applications and can be optimally selected and / or adapted in terms of the system behavior considered here, so that a high-quality system dependency can be determined.

[0466] Advantageously, the system dependency is determined in the form of a curve, preferably a curve and a determination coefficient of the curve.

[0467] This has the advantage that the system dependency is indicated by a curve as a function of the input quantity of the cleaning process; in particular, the curve has no gaps, so that a clear assignment between the control quantity and the output quantity, in particular a continuous and differentiable dependency between the input quantity and the output quantity, can be achieved, so that the dependency is ideally adapted for optimization, in particular optimization of the resource requirements.

[0468] Preferably, the curve is continuous and differentiable, so that it can be advantageously achieved that by using the system dependency in the control range of the control quantity, a control quantity can be determined which is suitable for the requirements of the cleaning process, without this resulting in discontinuities in the adjustment range or non-differentiable changes in the influence of the control quantity change.

[0469] Assuming that a sufficient number of data sets are available, the evaluation of the determination coefficient from the determined data and the curve determined by means of the regression model provides an indication of the accuracy of the system dependency. It can be advantageously evaluated how meaningful the correlation between the input quantity and the output quantity of the cleaning process is and how well the existing or recorded data can be reproduced. In addition, in the case of a large determination coefficient, the curve also allows statements to be made about the boundaries of the existing data. For example, it can be envisaged that the data can be supplemented and / or extrapolated numerically at the boundaries of the existing data.

[0470] In an optional embodiment, the system dependency is determined by means of an optimization process.

[0471] It is proposed here that the parameters of the system dependency are determined by means of an optimization program, in particular by means of a minimization process which minimizes the cumulative deviation of the experimental values considered from the data sets of the system dependency. In this way, it can be advantageously determined that the system dependency can be derived in an optimal manner, in particular with a minimum cumulative deviation from the initial empirical values.

[0472] Preferably, the parameters of the system dependency are determined by maximizing the resulting determination coefficient.

[0473] Preferably, the system dependency is determined by means of a self-learning optimization method.

[0474] In particular, it is proposed to use an algorithm which includes the properties of an algorithm from the machine learning class. Thus, the algorithm is able to derive a system dependency between the input quantity and the output quantity.

[0475] This has the advantage that the complex task of indirectly deriving the system dependency by using a self-learning optimization method does not have to be laboriously adapted to new conditions by humans. Thus, time and money can be saved in the indirect derivation of the system dependency.

[0476] Since the optimization procedure strives to determine the best system dependencies even in a multi-criteria environment and under various boundary conditions, the quality of the derived system dependencies can be improved by the aspects presented here.

[0477] It is thus also conceivable that the optimization can be performed under multiple equal objectives and / or boundary conditions (multi-criteria optimization). In particular, the required resources can be reduced to the greatest possible extent while the gain in availability is maximized. In particular, a class of algorithms can be considered which determine a Pareto optimum and / or a Pareto front. In particular, simplex methods and / or evolutionary strategies and / or evolutionary optimization algorithms and the like from the field are suggested here for deriving the system dependencies.

[0478] Advantageously, the data sets from already existing databases are used for deriving the system dependencies.

[0479] The advantage of this is that data from existing databases can also be used for deriving the system dependencies. It is thus possible to achieve that it is not necessary to first collect experimental values at a particular motor vehicle and to transfer them into the data of the database and subsequently into the system dependencies. In this way, existing data and experimental values can be used to ensure the direct operation of the cleaning system of the motor vehicle on the basis of the system dependencies.

[0480] In an optional embodiment, the already existing database is continuously expanded.

[0481] Advantageously, it is possible to achieve that the number of derivable system dependencies increases over time.

[0482] Furthermore, it can be advantageously achieved that the accuracy of the system dependencies can be improved since the number of experimental values known by means of the data sets is large.

[0483] In an advantageous embodiment, new data sets replace the data sets which deviate most from the derived system dependencies.

[0484] In particular, the fact that the empirical values are exchanged with the largest Euclidean distance from the system dependencies should be considered.

[0485] Advantageously, it is possible to achieve that the system dependencies become more and more precise over time, which can be expressed by an increase in the determination coefficient.

[0486] Furthermore, this can have the advantage that even weakly related system dependencies can be better identified over time.

[0487] It should be noted that the subject matter of the second aspect can advantageously be combined individually or cumulatively with the subject matter of the first aspect of the application in any combination.

[0488] According to a first alternative of the third aspect of the present application, this task is solved by a method for optimizing a resource requirement of a cleaning process of a surface of a motor vehicle, wherein a sensor is operatively connected to the surface, wherein the method uses data of a dependency table of a system behavior of a cleaning system of the motor vehicle, preferably of a cleaning process of at least one surface, preferably of a resource-efficient cleaning, particularly preferably of a resource-saving cleaning, of the system behavior, wherein the dependency table comprises a plurality of data sets, each data set comprising an input quantity of the cleaning system and an output quantity of the cleaning system, wherein the output quantity depends on the input quantity by means of a dependency table of a system behavior of the cleaning system between the system behavior of the cleaning system, preferably of at least one control quantity of the cleaning process, an availability of the sensor at a start time of the cleaning process and an availability of the sensor at an end time of the cleaning process, wherein the resource requirement of the cleaning process depends on the control quantity, the method comprising the following steps:

[0489] - accessing the data of the dependency table from a database and / or an electronic data processing and evaluation unit and / or an electronic control unit;

[0490] - deriving, for each data set of the dependency table, a difference between the availability of the sensor at the end time of the cleaning process and the availability of the sensor at the start time of the cleaning process;

[0491] - deriving a ratio of the difference to the respective resource requirement of each data set of the dependency table;

[0492] - selecting the control quantity of the data set comprising the highest value of the ratio; and

[0493] - preferably storing the control quantity as a control quantity setpoint in the database and / or the electronic data processing and evaluation unit and / or the electronic control unit.

[0494] An increasing number of vehicle assistance systems require an increasing number of sensors to be installed in a motor vehicle. Since these sensors mainly detect optical signals, they depend on the fact that the surface, which is operatively connected to the sensor, through which the optical signals are detected, is sufficiently clean. The degree of cleanliness is defined individually by the fact that the respective optical signal to be processed by the individual sensor can be received and / or at least predominantly processed without interference.

[0495] Therefore, the surface actively connected to the sensor has to be cleaned from time to time by using a cleaning device. This also applies to most sensors which do not operate with optical signals, since the signal transmission of these sensors can also be impaired by contamination.

[0496] It should therefore be expressly stated that this aspect of the application can affect not only optical sensors, but all sensors on a motor vehicle, at least those which are actively connected with a surface of the motor vehicle.

[0497] Each cleaning process is associated with a resource requirement which must be provided by the motor vehicle.

[0498] It is known hitherto that the cleaning process is initiated, preferably manually, by the driver of the motor vehicle.

[0499] The increasing number of vehicle assistance systems and the increasing number of sensors installed in motor vehicles has increased in recent times, which is why the need for keeping resources available has also significantly increased.

[0500] Due to the increasing number of sensors, the control effort for the necessary number of cleaning processes has also increased, which is why a semi-automatic or automatic cleaning of the relevant surfaces is also desirable.

[0501] It is now proposed an advantageous automatable procedure for minimizing the resource consumption for cleaning surfaces effectively connected to relevant sensors, in particular by performing each individual cleaning process, which is preferably resource-efficient, in particular resource-saving, so that the resource consumption and thus the resource requirement for at least one cleaning device can be advantageously reduced.

[0502] Each cleaning process is defined by at least one parameter, in particular an input quantity, particularly preferably by a control quantity. The quantity of cleaning fluid applied to the surface to be cleaned can be considered as the respective input quantity or as the respective control quantity at the same time.

[0503] It should also be preferably noted that the application of the cleaning liquid to the surface to be cleaned takes place in several stages, preferably a relatively small quantity of cleaning liquid is applied in a first stage, with the aid of which any contaminants can be softened, and a second quantity of cleaning liquid is applied in a second stage, with the aid of which the softened contaminants can be washed off the surface. The way in which the cleaning agent is used, in particular the quantity of cleaning fluid, has a direct influence on the resource requirement of the individual cleaning process.

[0504] It should be noted that this aspect not only considers the quantity of cleaning fluid required for the cleaning process, but also the quantity of energy used for cleaning, the wear of the wiping element and / or the considerable resources required for the cleaning process.

[0505] Each cleaning process is influenced by a system behavior, wherein the system behavior depends on at least one parameter, preferably an input quantity, particularly preferably a control quantity, and within the framework of an output quantity it is also possible to make a statement about the result of the cleaning process, in particular about the resource requirement used or used in a planning sense and about the declaration of cleaning success, particularly preferably by means of the availability.

[0506] The system behavior is therefore preferably defined by at least one input quantity and at least one output quantity, wherein the at least one output quantity depends on the at least one input quantity.

[0507] In the case of an input quantity, it is also possible to consider the size of the surface to be cleaned, which is operatively connected to a sensor.

[0508] In the context of an input quantity, it is also possible to preferably consider the location of the surface to be cleaned. The difference for the resource efficiency, in particular the preferred resource-saving cleaning method, can therefore be whether the surface to be cleaned can be found at the front or on one side or at the rear or on the bottom or on the roof of the motor vehicle.

[0509] Furthermore, the input quantity can also include the type of contamination, in particular whether it is a crust deposit of dirt and / or dust or a layer of sludge or snow, etc. It should also be remembered that the operating position and operating history of the motor vehicle allow a statistical expectation of the type of contamination of the surface, in particular in combination with a weather forecast. In other words, the range of input quantities can also include weather conditions and operating position and / or operating history, which can be evaluated by means of the coordinates of the motor vehicle and, if necessary, also other retrievable data, in particular data retrievable from a data network.

[0510] When evaluating the cleaning success of a cleaning process, it can be preferable to remember that success is considered to be the difference between the availability of the corresponding surface to be cleaned before and after the cleaning process.

[0511] Cleaning processes defined in different ways can be evaluated on the basis of their system behavior consisting of at least one input quantity and at least one output quantity.

[0512] If there are experimental values for a plurality of defined cleaning processes, a resource-efficient, particularly preferred resource-saving cleaning can be specifically selected on the basis of the existing experimental values for the respective contamination situation.

[0513] The respective experimental value consists of at least one input quantity, in particular a control quantity, and at least one output quantity, in particular a gain in availability, which can be determined from the difference between the availability before and after cleaning the surface to be cleaned.

[0514] In this context, it can be specifically considered that the optimal resource efficiency has already been generated from existing experience, in particular the preferred resource-saving clean control quantity is selected based on existing pollution conditions, in particular the availability available, and the corresponding control quantity is reproduced within the framework of the cleaning program. During the reproduction, the control quantity or the controlled cleaning process can be specifically considered.

[0515] The possible experimental values can preferably consist of experimental values obtained on motor vehicles, in particular on the specific motor vehicle, and / or from experience obtained on reference vehicles and / or generated based on numerical models and / or generated based on laboratory tests.

[0516] The experimental values considered for the selection of a resource-efficient, in particular resource-saving, cleaning process preferably relate to corresponding experience obtained based on the surface to be cleaned, which is now also to be cleaned or whose cleaning is at least now to be evaluated.

[0517] When storing the collected experimental values, the data can be stored in a dependency table.

[0518] Preferably, the dependency table can be extended by new experimental values.

[0519] The dependency table can be read out preferentially.

[0520] Preferably, the dependency table can be stored in a database and / or an electronic data processing and evaluation unit and / or an electronic control unit.

[0521] Preferably, the dependency table shows the possibility to store intermediate results for the evaluation of the cleaning process in an ordered manner.

[0522] Preferably, the dependency table allows the selection of specific experience values by means of data mining methods known in the art.

[0523] In other words, it is suggested here to optimize the resource consumption for cleaning the surfaces selected for cleaning based on the system behavior of the cleaning process, so that a better cleaning result can be achieved with a lower resource input, depending on the current initial situation.

[0524] The optimal control quantity setpoint corresponds to the control quantity of the experience value for the defined cleaning process, which guarantees the resource-optimal cleaning of the surface to be cleaned according to the proposed program. If the corresponding optimal experience value has been selected, the optimal control quantity setpoint can be obtained from the corresponding input quantity.

[0525] The method proposed here is designed to optimize the cleaning of the surface associated with the sensor and to generate a control quantity setpoint optimized for the individual surface to be cleaned.

[0526] Preferably, the procedure can be performed sequentially for a plurality of surfaces to be cleaned, which is advantageous in that the control quantity setpoint can be defined sequentially for each surface to be cleaned of the motor vehicle.

[0527] This can be achieved by the following steps:

[0528] - accessing the data of the dependency table from a database and / or an electronic data processing and evaluation unit and / or an electronic control unit, wherein the collected desired values can advantageously be called and processed in the next step;

[0529] - deriving, for each data set of the dependency table, a difference between the availability of the sensor at the end time of the cleaning process and the availability of the sensor at the start time of the cleaning process, which advantageously determines a gain in availability of each stored experience value;

[0530] - deriving a ratio of the difference to the respective resource requirement for each data set of the dependency table, wherein the efficiency of the cleaning process can advantageously be defined by the ratio of the expected resource requirement to the expected cleaning success;

[0531] - selecting the control quantity of the data set which most prominently includes the highest value of the ratio, wherein the control quantity with the highest resource efficiency can be selected on the basis of the existing experimental values; and

[0532] - preferably storing the control quantity as a control quantity setpoint in the database and / or the electronic data processing and evaluation unit and / or the electronic control unit, so that the particular control quantity setpoint can be retrieved and advantageously applied within the framework of a downstream cleaning process.

[0533] According to a second alternative of the third aspect of the present application, the task is solved by a method for optimizing the resource requirement of a cleaning process of a surface of a motor vehicle, wherein a sensor is operatively connected to the surface, wherein the method uses a system dependency of a system behavior of a cleaning system of the motor vehicle, preferably a system dependency according to the second aspect of the present application, preferably a system dependency of a system behavior of a resource-efficient cleaning, particularly preferably a resource-saving cleaning, of the cleaning process of at least one surface, wherein the system dependency comprises a plurality of data sets, each data set comprising an input quantity of the cleaning system and an output quantity of the cleaning system, wherein the output quantity depends on the input quantity by means of a system dependency of a system behavior of the cleaning system between the system behavior of the cleaning system, preferably at least one control quantity of the cleaning process, the availability of the sensor at a start time of the cleaning process and the availability of the sensor at an end time of the cleaning process, wherein the resource requirement of the cleaning process depends on the control quantity,

[0534] The method comprises the following steps:

[0535] - accessing the system dependency from a database and / or an electronic data processing and evaluation unit and / or an electronic control unit;

[0536] - deriving a difference process of the process of the system dependency between the availability of the sensor at the end time of the cleaning process and the availability of the sensor at the start time of the cleaning process;

[0537] - deriving a ratio of the difference process of the process of the system dependency to the process of the respective resource requirement;

[0538] - selecting a control quantity which belongs to the point of the process of the ratio which comprises the highest value of the ratio; and

[0539] - storing the control quantity as a control quantity setpoint in a database and / or an electronic data processing and evaluation unit and / or an electronic control unit, preferably.

[0540] According to the above first alternative of the third aspect of the present application, the discrete experimental values are used to optimize a procedure of the resource requirement of the cleaning process, preferably of a resource-efficient cleaning, particularly preferably of a resource-saving cleaning.

[0541] The solution of the input quantity, particularly the control quantity, within the range of possible expressions of the input quantity depends on the number of available experimental values and the distribution of these available experimental values within the range of possible expressions of the input quantity.

[0542] In a different way, it is proposed here to map the system behavior of the cleaning process by means of the system dependency, preferably by means of the system dependency according to the second aspect of the present application.

[0543] Preferably, the system dependency comprises a data set, wherein each data set comprises an input quantity of the cleaning process and an output quantity of the cleaning process. It can be envisaged in particular that the system dependency is represented by a defined number of data sets and a defined distribution within the possible input quantity range.

[0544] This advantageously allows the data sets of the system dependency to be derived from the experimental values in such a way that the optimum number of data sets and the optimized distribution of the data sets result in the range of possible expressions of the input quantity in the sense of the goal of a resource-efficient cleaning, particularly preferably of a resource-saving cleaning.

[0545] In the context of the system dependency in terms of its reference to a specific data set defined by the input quantity and the output quantity, these can also be carried out preferentially according to the procedure steps following the first alternative of the third aspect.

[0546] Alternatively, it can also be envisaged that the system dependency is given by its mathematical description. In this case, the system dependency consists of a curve which describes the dependency between at least one input quantity and at least one output quantity.

[0547] It is particularly preferred that the system dependency in the form of a curve describes a dependency of at least one input quantity on at least one output quantity over the entire defined range of the curve.

[0548] The preferably defined range of the curve is at least as large as the range of possible expressions of the input quantity.

[0549] Also in the case where the system dependency is defined by a curve, it can be considered that the system dependency comprises data sets, each data set comprising at least one input quantity of the cleaning system and at least one output quantity of the cleaning system. Specifically, because the output quantity can be read from the curve of the individual data sets, for example by calculating a grid of input quantities.

[0550] Preferably, the system dependency has at least one control quantity as an input quantity.

[0551] Preferably, the system dependency has a dependency between the sensor availability at the start time of the cleaning process and the sensor availability at the end time of the cleaning process, which allows to determine a gain in availability.

[0552] By using the system dependency it can be advantageously achieved that when searching for an optimal control quantity, especially if the system dependency is continuous and can be differentiated in the form of a curve, mathematical methods can be used to determine extrema of the system behavior.

[0553] Furthermore, by this alternative it can be advantageously achieved that in comparison to the first alternative of the third aspect of the present invention, better optimal values for the control quantity setpoint can be determined, so that in this comparison more resource savings can be advantageously achieved.

[0554] This aspect is due to the fact that by the process of determining the system dependency, especially after the second aspect of the present invention, a smoothing of measurement inaccuracies and fluctuations in the system behavior can be achieved, wherein preferably from a discrete description by means of discrete experimental values a continuous, thus stable and differentiable representation of the system dependency is generated, wherein a greater accuracy of the mapping of the system behavior can be achieved.

[0555] Furthermore, it is also possible to improve the optimization result by choosing the optimal control quantity setpoint in those regions which are mathematically optimal but for which currently no experimental values are available.

[0556] It is specifically proposed here to optimize the resource consumption for cleaning a surface selected for cleaning based on the system behavior of the cleaning process, so that with lower resource input a better cleaning result can be advantageously achieved, depending on the current initial situation and using the system dependency according to the second aspect of the present invention.

[0557] The method presented here is designed to optimize the cleaning of the sensor-related surface and to generate control quantity set points that are optimized for the individual surface to be cleaned.

[0558] Preferably, the procedure can be performed sequentially for a plurality of surfaces to be cleaned, which is advantageous in that the control quantity set points can be defined sequentially for each surface to be cleaned of the motor vehicle.

[0559] It should be understood that the procedure steps following the second alternative of the third aspect should be slightly modified with respect to the first alternative of the third aspect:

[0560] In particular, instead of accessing a dependency table in the database and / or the electronic data processing and evaluation unit and / or the electronic control unit, a corresponding system dependency, in particular a system dependency according to the second aspect of the application, is accessed.

[0561] Furthermore, it should also be understood that preferably no discrete data points are used for the calculation, but rather preferably the entire curve is subjected to the respective mathematical operations over the entire curve progression. This can preferably be done by means of an analysis or with the aid of a discretization in defined steps.

[0562] In addition, it should be understood that the advantage of the system dependency is utilized and that the data set is not selected from recorded experimental values, which guarantees an optimal resource-saving cleaning of the surface to be cleaned, but rather an extreme point in the progression of the system dependency, at least an extreme point in the region to which the control quantity can be adapted. In particular, it should be understood that by adjusting the control quantity, the selected control quantity set point can lie at the edge of the range.

[0563] It should be expressly stated that the system dependency considered here is not limited to its dimension and can have any dimension of the input quantity and any dimension of the output quantity.

[0564] Preferably,

[0565] - the dependency table and / or the system dependency comprises a dependency on a process quantity, preferably a humidity and / or a temperature and / or a rainfall and / or a snowfall in the vicinity of the motor vehicle and / or a coordinate of the motor vehicle; and

[0566] - wherein, prior to the selection of the control quantity, first the data set considered in the selection of the control quantity from the dependency table and / or the regional constraints of the system dependency considered in the selection of the control quantity are constrained to deviate less than 20%, preferably less than 10% and particularly preferably less than 5% from the respective process quantity, preferably from the current humidity along the planned trip and / or the forecasted humidity and / or the current temperature in the vicinity of the motor vehicle and / or the forecasted temperature along the planned trip and / or the current precipitation along the planned trip and / or the forecasted precipitation and / or the current snowfall along the planned trip and / or the forecasted snowfall and / or the coordinates of the motor vehicle and / or the forecasted coordinates of the motor vehicle along the planned trip.

[0567] It is specifically proposed here that the optimization of the control quantity setpoint, in other words the minimization of the resource requirement for the individual surfaces to be cleaned of the motor vehicle, also takes into account at least one process quantity.

[0568] It goes without saying that the cleaning success of a cleaning process performed after a long period of drizzle is different from the case in which a cleaning process defined by the same control quantity is performed in a hot summer with strong sunshine, at least taking into account the same previous degree of soiling and the same type of soiling.

[0569] In other words, the resource-optimal cleaning process also depends on at least one process quantity, which is why it can be taken into account in the optimization of the optimal control quantity setpoint.

[0570] The same result can be achieved if the experimental values stored in the dependency table initially depend on the process quantity, preferably the process quantity involved, in the same way. The same applies to the use of system dependencies, in particular system dependencies after the second aspect of the application, which must also depend on the process quantity, preferably the process quantity involved, so that what is proposed here can be taken into account accordingly in the optimization.

[0571] In order to take this into account within the optimization, it is proposed that the number of experience values from the dependency table considered in the selection of the optimal control quantity setpoint and / or the system dependency range is limited to a range in which the process quantity currently prevailing or expected according to the weather forecast at the time of the planned cleaning process deviates by no more than 20%, preferably less than 10% and particularly preferably less than 5%.

[0572] By this limitation, it can be achieved that no experience from a cleaning performed in the sunshine is transferred to a cleaning to be performed in the snow. In other words, it can be achieved that only experience from a situation which essentially corresponds to the situation to be occurring is transferred to the respective situation.

[0573] It can be particularly advantageously improved, inter alia, that the mapping accuracy between the optimally desired selected control quantity and the result achieved during the cleaning process.

[0574] The process quantity is preferably understood as the weather on the pre-planned route. The decision on the optimal control quantity setpoint can also depend on whether weather conditions are reached on the pre-planned route that require less resources for cleaning, in particular rain and / or snowfall. In this way, it can be advantageously achieved that by including the expected weather conditions in the decision on the control quantity setpoint, which can also include the cleaning time, it can be advantageously reduced the total resources required for cleaning. This is also suggested, inter alia, by including the process quantity.

[0575] It should be noted that the above values for the considered region of the process quantity should not be understood as strict limits, but rather it should be possible to exceed it or fall below it on an engineering scale without departing from the described aspects of the application. Simply put, these values are intended to provide an indication of the magnitude of the considered process quantity state proposed here.

[0576] Advantageously,

[0577] - the dependency table and / or the system dependency includes a dependency of the availability of the sensor at the start time of the cleaning process; and

[0578] - wherein, before the selection of the control quantity, the region considered when selecting the control quantity from the dependency table and / or the system dependency considered when selecting the control quantity is first constrained to a region in which the actual availability of the sensor at the points on the planned route deviates by less than 20%, preferably by less than 10% and particularly preferably by less than 5% from the expected availability of the sensor, in particular by applying the following steps:

[0579] A method for determining the expected availability at the distance or operating time to be covered of a motor vehicle is proposed, preferably in accordance with the tenth aspect of the application.

[0580] It is proposed here to include the availability of the sensor actively connected to the surface to be cleaned in the optimization of the control quantity setpoint.

[0581] By the increase in availability, the cleaning process defined by the control quantity leads to different cleaning successes in the case of different initial surface contaminations. Preferably, better cleaning results are produced for more heavily contaminated initial conditions than for less heavily contaminated surfaces, wherein in each case considerable resource requirements are required, since the cleaning is carried out with the same control quantity in each case.

[0582] In this respect, the contamination at the start of the cleaning process can influence the resource efficiency of the cleaning process.

[0583] The initial contamination of the surface to be cleaned, in particular the contamination assessed by the availability of the sensors at the beginning of the cleaning process, is taken into account by the fact that the experimental values stored in the dependency table first depend on the availability of the sensors at the start time of the cleaning process. The same applies to the use of the system dependency, in particular after the second aspect of the application, which also has to depend on the availability of the sensors at the start time of the cleaning process, so that this can be taken into account accordingly in the optimization.

[0584] The same applies when considering the availability of the sensors at the start time of the process to the cases that have already been made for considering the process quantities. Here, too, the range of experimental values considered for the optimization from the dependency table and / or the range of the system dependency will be limited to a range that deviates less than 20%, preferably less than 10%, in particular preferably less than 5% from the actual availability of the sensors.

[0585] Due to the resulting limitation, it can be advantageously achieved that only experience from cases that essentially correspond to the upcoming cleaning situation is transferred to these situations.

[0586] In particular, it can be advantageously improved the mapping accuracy between the selected control quantities expected to be optimal and the results achieved during the cleaning process.

[0587] Furthermore, it should be particularly taken into account here that in the preliminary planning of the upcoming cleaning process, in particular the expected availability of the sensors when performing the cleaning process is estimated in advance, in particular with the procedure according to the tenth aspect of the application.

[0588] Thus, depending on the distance covered by the motor vehicle before the cleaning process or depending on the operating time covered by the motor vehicle before the cleaning process, the expected availability of the sensors can first be determined, based on which a limitation of the experimental values from the area of the dependency table and / or the system dependency can be performed.

[0589] The planning accuracy of the cleaning process can be advantageously improved, wherein the resource requirement for cleaning the surfaces connected to the sensors can also be advantageously reduced.

[0590] It should be noted that the above values of the considered area of the availability of the sensors at the start time of the cleaning process should not be understood as a strict limitation, but it should be possible to exceed it or to fall below it on an engineering scale without departing from the described aspects of the application. Simply put, these values are intended to provide an indication of the size of the considered availability of the sensors at the start time of the cleaning process presented here.

[0591] Optionally,

[0592] - the dependency table and / or the system dependency comprises a dependency on the availability of the sensor at the start time of the cleaning process;

[0593] - wherein, prior to the selection of the control quantity, first the data set to be considered in the selection of the control quantity from the dependency table and / or the region of the system dependency to be considered in the selection of the control quantity is restricted to a region in which the availability of the sensor at the start time of the cleaning process is less than or equal to the actual availability of the sensor; and

[0594] - wherein the availability of the sensor associated with the selected control quantity at the start time of the cleaning process is additionally saved together with the selected control quantity as control quantity setpoint.

[0595] In contrast to the above, it is now proposed to optimize the cleaning process in terms of resource efficiency of the cleaning process in such a way that, in the optimization, a decision is also made as to the conditions that must be met in order to start the cleaning process, in particular as to the availability of the sensor to be achieved in order to start the cleaning process.

[0596] In other words, if the predetermined availability of the sensor at the start time of the cleaning process is achieved by the process presented here, the cleaning process planned in advance will be started by the cleaning method, in particular by the cleaning method according to the first aspect of the application.

[0597] The proposed method is made possible by the fact that the experimental values stored in the dependency table first depend on the availability of the sensor at the start time of the cleaning process. The same applies to the use of system dependencies, in particular system dependencies after the second aspect of the application, which must also depend on the availability of the sensor at the start time of the cleaning process, so that this can be taken into account accordingly in the optimization.

[0598] At the same time, in addition to the control quantity setpoint, the optimal availability of the sensor at the start time is selected or determined from the input quantity of the selected optimal experimental value or the optimal point of the system dependency.

[0599] After the sensor in operative connection with the surface to be cleaned already comprises the actual availability value, only the optimal cleaning process can be selected by means of the method, which immediately starts because the resource-optimal cleaning process within the physically possible range is already located on the currently achieved limit of the availability of the sensor, or starts in the future at the start time with the defined availability of the sensor, since this must first be achieved by additional contamination of the surface to be cleaned.

[0600] By storing the selected control quantity setpoint together with the availability of the sensor at the start time of the cleaning process, the cleaning method can start the cleaning process by achieving the determined optimal availability of the sensor at the start time of the cleaning process.

[0601] Thus, the resource requirements for the cleaning process can be further reduced in an advantageous manner, since the procedure presented here selects the cleaning process that is most resource-efficient within the still possible framework.

[0602] In a preferred embodiment, before the selection of the control quantity, the data sets to be considered when selecting the control quantity from the dependency table and / or the region of the system dependency to be considered when selecting the control quantity are first limited to a region in which the expected gain in availability does not exceed 20% and / or until a threshold value of availability is reached, preferably not more than 10%, particularly preferably not more than 5%, without unintentionally impairing the availability of the sensor functionality for the current trip that can be used for the motor vehicle:

[0603] The method for determining the expected gain in availability is applied, preferably the method according to the fourteenth aspect of the application, wherein the sum of the current availability and the expected gain in availability is sufficient to cover the distance or operating time to be covered by the motor vehicle in a manner that does not exceed the availability threshold value.

[0604] In addition to active motor vehicle operation, in particular when the motor vehicle is used to cover a certain distance, the motor vehicle is also contaminated in passive motor vehicle operation when the motor vehicle is parked at a certain point in time, in particular when the motor vehicle is exposed to unprotected weather.

[0605] With regard to the use of resources for cleaning the motor vehicle, it can be resource-inefficient if the motor vehicle or a part thereof is cleaned shortly before the planned operation of the motor vehicle ends, in particular if the motor vehicle will be heavily contaminated by passive operation of the motor vehicle until the next active operation is possible, so that at least one cleaning process must be started at the beginning of the next operation of the motor vehicle in order to restore the availability of the driver assistance system.

[0606] In other words, possible overcleaning can be prevented before the end of the active vehicle operation in order to save advantageous and overall resources for cleaning. The procedure presented here makes this possible.

[0607] Alternatively, a modification is provided according to a further optional embodiment to moisten surfaces that are sometimes only effectively connected with unnecessary sensors with a spray of cleaning fluid.

[0608] In this way, it can be advantageously achieved that surfaces that are not actively connected with one of the necessary sensors are not dried and thus advantageously prevent the build-up of contaminants present on the surface. In this way, it can be advantageously achieved that another cleaning process aimed at the direct cleaning of the surface can be achieved with less cleaning resources, since it does not have to remove a crust of dirt in a short time, but already soaked or pre-soaked dirt.

[0609] In other words, here specifically no cleaning process is proposed which aims at immediately cleaning the surface, but a cleaning process is proposed which makes it easier for a subsequent cleaning process aiming at immediately cleaning the surface to achieve a better cleaning result with less resource expenditure, in particular a higher availability gain.

[0610] A more effective cleaning process can be achieved in combination.

[0611] To this end, the experimental values from the dependency table or the region of the system behavior relationship mapped by the system dependency which can be selected by the program are limited to a region such that the expected availability gain does not exceed 20%, and / or until a threshold value of availability is reached, preferably not more than 10%, and in particular preferably not more than 5%, which can be used for the current trip of the motor vehicle without unintentionally impairing the availability of the sensor functionality.

[0612] Preferably, the expected gain in availability of each evaluated cleaning process can be determined by applying the method according to the fourteenth aspect of the present application.

[0613] Thus, it can be advantageously achieved that the cleaning process selected by the method does not lead to a significant over-cleaning of the surface actively connected to the sensor on the one hand, and on the other hand, no later cleaning is required to maintain the driver assistance system due to a certain degree of safety before the target is reached.

[0614] In this way, resources for cleaning the surface effectively connected to the sensor can be saved.

[0615] It should be noted that the above values of the considered region of the expected gain in availability of the sensor due to the cleaning process should not be understood as a strict limitation, but it should be possible to exceed it or fall below it on an engineering scale without departing from the described aspect of the present application. Simply put, these values are intended to provide an indication of the size of the considered expected gain in availability of the sensor due to the cleaning process proposed here.

[0616] The method for optimizing the resource requirement of a cleaning process of a surface of a motor vehicle according to the third aspect is characterized in that, before the selection of the control variable, the data set considered when selecting the control variable from the dependency table and / or the region of the system dependency considered when selecting the control variable is first limited to a region in which the expected gain in availability is sufficient to bridge the distance or operating time to the next cleaning process without falling below the threshold value of availability and does not exceed 20%, preferably not more than 10% and in particular preferably not more than 5% of the gain in availability required to bridge the distance or operating time to the next cleaning process without falling below the threshold value of availability:

[0617] In particular, the method is applied for determining the expected distance or expected operating time of the motor vehicle to be covered when the threshold of availability is reached, preferably by applying the method according to the eleventh aspect of the present application,

[0618] In particular, the method is applied for determining the expected gain of availability, preferably by applying the method according to the fourteenth aspect of the present application,

[0619] wherein the sum of the current availability and the expected gain of availability is sufficient to bridge the distance or operating time of the motor vehicle to be covered by not falling below the threshold of availability.

[0620] In some situations of the motor vehicle operation, especially if the cleaning resources still available are particularly scarce, it is advantageous to perform only the minimally invasive cleaning process so that there is a good chance that the next intermediate target and / or the next opportunity to replenish the cleaning resources can still be achieved with the existing cleaning resources.

[0621] In particular, it can be envisaged that, with only minimal use of the cleaning device, the autonomous motor vehicle operation can be maintained until the next filling station. Even if the minimally invasive cleaning process presented here is not optimally resource-efficient in the sense of the highest possible increase in availability with minimal use of the cleaning agent, the available resources are still optimally efficiently used in the sense of achieving the goals of the vehicle operator, who in particular still wishes to reach the next intermediate destination of his journey by means of autonomous driving.

[0622] This can achieve that, before the selection of the control quantity, the data set to be considered when selecting the control quantity from the dependency table and / or the region of the system dependencies to be considered when selecting the control quantity is first limited to a region in which the expected gain of availability is sufficient to bridge the distance or operating time to the next cleaning process without falling below the threshold of availability and does not exceed the gain of availability for bridging the distance or operating time to the next cleaning process without falling below the threshold of availability by more than 20%, preferably by more than 10% and particularly preferably by more than 5%.

[0623] In other words, here the solution space is limited from both sides.

[0624] It should be specifically remembered that, before the selection of the control quantity setpoint, the expected distance or expected operating time of the motor vehicle to be covered when the threshold of availability is reached is determined, preferably by means of the procedure according to the eleventh aspect of the present application.

[0625] Furthermore, it should be specifically considered that, before the selection of the control quantity setpoint, the expected gain of availability is also determined during the execution of the cleaning process by means of the procedure according to the fourteenth aspect of the present application.

[0626] The advantage of this is that the cleaning process can be selected in such a way that the motor vehicle can achieve the minimum target defined by the driver with the available resources optimally.

[0627] It should be noted that the above values for the considered region of the expected gain in availability of the sensor due to the cleaning process are not to be understood as strict limits, but rather it should be possible to exceed it or fall below it on an engineering scale without departing from the described aspect of the application. Simply put, these values are intended to provide an indication of the size of the considered expected gain in availability of the sensor due to the cleaning process presented here.

[0628] In a preferred embodiment, the first control quantity and the second control quantity are selected, wherein the respective first control quantity setpoint and the respective second control quantity setpoint define a first cleaning process and a second cleaning process for a series of cleaning processes, the second cleaning process being carried out after completion of the first cleaning process.

[0629] It is specifically proposed here to divide the cleaning process of a surface to be cleaned into two or more individual cleaning processes of a common planned sequence.

[0630] The first cleaning process is defined by a first control quantity setpoint, while the second cleaning process is defined by a second control quantity setpoint.

[0631] It should also be considered that both control quantity setpoints contain conditions that trigger the respective cleaning process within the scope of the cleaning method, in particular within the scope of the cleaning method according to the first aspect of the application. Specifically, a time distance, a spatial distance or the implementation of a defined trigger between the individual cleaning processes is considered.

[0632] The advantage is that cleaning resources can be saved if several cleaning processes are more resource-efficient than a single cleaning process. Surprisingly, this can occur in the respective input quantity or some constellation of the respective input quantities.

[0633] Optionally, the method is carried out serially or in parallel for a plurality of surfaces to be cleaned, in particular for two, three, four, five or more surfaces to be cleaned.

[0634] Hitherto, the procedure has only been described to the extent that it optimizes the cleaning process to be carried out for only one surface at a time.

[0635] It is specifically proposed here that the procedure is applied, in particular sequentially or in parallel, to a large number of surfaces to be cleaned.

[0636] Advantageously, the control quantity is selected by means of a multi-criteria optimization procedure.

[0637] It is specifically proposed here that the selection of the optimal cleaning process is carried out by means of a multi-criteria optimization procedure.

[0638] Such procedures are particularly suitable if different resources are to be optimized simultaneously and independently of one another.

[0639] Preference should be given to the fact that, in addition to the cleaning liquid, special washing liquids can also be used.

[0640] By using a multi-criteria optimization method, it can advantageously be achieved that in the decision based on the Pareto front being developed, different resources can likewise advantageously be considered as resource-efficient.

[0641] According to a third aspect of the application, other influencing variables, in particular the type of the sensor's device, the temperature of the cleaning fluid, the composition of the cleaning fluid, the movement speed of the wiping element, the amount of cleaning fluid, the orientation of the nozzle, etc., can preferably be taken into account in the resource optimization.

[0642] With regard to the temperature of the cleaning fluid, the composition of the cleaning fluid, the movement speed of the wiping element, the amount of cleaning fluid and / or the orientation of the nozzle, this can also be a control variable.

[0643] It goes without saying that the advantages of the system dependency, in particular according to the second aspect of the application, also apply to the use of the system dependency, in particular according to the third aspect of the application as presented here.

[0644] It should be noted that the subject matter of the third aspect can advantageously be combined individually or cumulatively with the subject matter of the aforementioned aspects of the application in any combination.

[0645] According to a fourth aspect of the application, this task is solved by a method for determining a cleaning strategy for cleaning a surface to be cleaned of a motor vehicle, wherein the surface to be cleaned is selected according to a cleaning pattern, wherein a sensor is operatively connected to the surface to be cleaned,

[0646] wherein the sensor comprises an actual availability, wherein the cleaning strategy comprises a control variable setpoint defining a cleaning process for the surface to be cleaned, the method comprising the following steps:

[0647] - preferably checking the actual cleaning pattern;

[0648] - selecting at least one sensor required for the currently selected cleaning pattern;

[0649] - checking the actual availability of each selected sensor;

[0650] - determining a resource-efficient, preferably resource-saving, control variable setpoint for each surface to be cleaned operatively connected to each selected sensor, in particular by the following steps:

[0651] The application of the method for optimizing the resource requirement of the cleaning process of a motor vehicle surface, preferably the application of the method according to the third aspect of the application; and

[0652] - Preferably, a determined control quantity setpoint for a resource-efficient, preferably resource-saving, cleaning of each surface to be cleaned operatively connected to each selected sensor is stored, particularly preferably the determined control quantity setpoint is stored in the cleaning strategy, preferably in a database and / or an electronic evaluation and data processing unit and / or an electronic control unit.

[0653] If the availability of a sensor falls below the availability threshold, this can result in a limited functionality of the sensor, which can indirectly impair the functionality of at least one driver assistance system.

[0654] The third aspect of the application describes a program for optimizing a cleaning process with regard to resource consumption for a surface to be cleaned operatively connected to a sensor.

[0655] The third aspect of the application is to provide one or more resource-optimal cleaning processes for one or more surfaces to be cleaned.

[0656] However, the program according to the third aspect of the application does not take into account whether the particular surface connected to the sensor has to be cleaned at all, or in other words, whether the availability of the sensor should be increased by performing a cleaning process, preferably by performing a cleaning process after the first aspect of the application, for the current or planned use of the vehicle.

[0657] The fourth aspect of the application is based on the idea that not every sensor is needed at all times for the current or planned vehicle operation.

[0658] If a surface with a sensor that is not currently needed is to be cleaned, cleaning resources are also required for this purpose.

[0659] The fourth aspect of the application uses this context to save cleaning resources and to make it possible to clean only the surfaces of a motor vehicle by a cleaning process, in particular by a cleaning method according to the first aspect of the application, which is also actively connected to at least one sensor whose functionality is desired for the current or planned vehicle operation, depending on the selected cleaning mode.

[0660] This advantageously allows the saving of cleaning resources, especially since it is also possible for the availability of a sensor whose functionality is not currently needed to fall below the availability threshold.

[0661] For this purpose, the cleaning strategy for cleaning surfaces of a motor vehicle to be cleaned is determined by means of the procedure presented here, which determines, for the entire motor vehicle, depending on the cleaning mode, whether a surface is to be cleaned and, if a surface is to be cleaned, also preferably by means of determining a corresponding control quantity, preferably using the method according to the third aspect of the application, how the surface is to be cleaned (i.e. which cleaning process is to be used to clean the surface).

[0662] Depending on the cleaning mode, the surfaces that are actively connected with the sensors required by the current use of the vehicle are selected for this purpose and are also reserved for cleaning. In this context, the corresponding sensors can also be referred to as "selected sensors".

[0663] Furthermore, by applying the method for optimizing the resource requirements of the cleaning process for the surfaces of a motor vehicle, preferably by applying the method according to the third aspect of the application, a control quantity setpoint is determined for each selected sensor, preferably for a resource-efficient, preferably for a resource-saving cleaning.

[0664] Preferably, each control quantity setpoint determined for each selected sensor is stored in the cleaning strategy.

[0665] It goes without saying that the cleaning strategy becomes invalid as soon as the cleaning mode changes. As soon as the cleaning mode changes, a different cleaning strategy must be applied within the scope of the cleaning method, preferably within the scope of the cleaning method according to the first aspect of the application, or a new cleaning strategy must be determined in accordance with the procedure presented.

[0666] It should be expressly pointed out that the cleaning mode can coincide with the driving mode, but this need not be the case, which is why these terms are used separately here.

[0667] Preferably, the assignment of the selected sensors can be obtained from a relevant list, which can preferably be obtained from a database and / or an electronic evaluation and data processing unit and / or an electronic control unit.

[0668] Preferably, the recommended cleaning strategy can override the orders of the motor vehicle and / or the driver as a last-minute remedy to clean the surfaces of the selected sensors whose availability has reached and / or fallen below an availability threshold.

[0669] Furthermore, it is preferable that the cleaning strategy can provide that it also decides to clean sensors that are not selected sensors, in particular if one of the selected sensors is faulty.

[0670] Preferably, before determining the control quantity setpoint, first of all the expected distance and / or the expected operating time that the motor vehicle can still cover is determined as a function of the actual availability of the selected sensor, in particular by the following steps, until the expected availability reaches an availability threshold, at which point the surface operatively connected to the associated sensor is to be cleaned:

[0671] The method for determining the expected distance or the expected operating time of the motor vehicle to be covered when the threshold of availability is reached is applied, preferably the method according to the eleventh aspect of the application is applied.

[0672] So far, the vehicle driving range achievable with the available cleaning resources has not been taken into account in determining the cleaning strategy.

[0673] This is what is proposed here.

[0674] When operating the motor vehicle, a distinction can be made between operating modes of the motor vehicle, for example between active motor vehicle operation, characterized by the fact that the motor vehicle covers a driving distance, and passive motor vehicle operation, in which the vehicle is parked waiting for the next active motor vehicle operation.

[0675] The motor vehicle is contaminated both in active motor vehicle operation and in passive motor vehicle operation. For reasons of resource-optimal cleaning of the surfaces of the motor vehicle, it is in particular proposed not to clean the surfaces excessively, characterized by the fact that the surfaces of the motor vehicle are cleaned thoroughly shortly before the target of active motor vehicle use is reached.

[0676] Instead, it is proposed here that the cleaning process can pursue the target of cleaning the surfaces to the extent that the availability achieved by the cleaning process is sufficient to achieve the target of active vehicle operation. For this purpose, the associated control quantity setpoint can be determined in particular by means of the method according to the third aspect of the application.

[0677] Another effect is caused by the fact that different cleaning modes require different amounts of cleaning resources. In particular, a cleaning mode designed to maintain autonomous vehicle operation requires more cleaning resources than a cleaning mode designed to maintain at least one driver assistance system that is only intended to help the driver to drive the vehicle but does not allow autonomous vehicle operation.

[0678] From this, it is proposed here,

[0679] • as a function of the steps before determining the control quantity setpoint, preferably by applying the method according to the eleventh aspect, first of all the expected distance and / or the expected operating time that the motor vehicle can still cover is determined as a function of the actual availability of the selected sensor, until the expected availability then reaches the respective availability threshold;

[0680] • checking the amount of available cleaning resources according to a further step, in particular using a corresponding sensor, in particular a liquid level sensor or the like, before determining the control quantity setpoint;

[0681] • determining a cleaning strategy with a corresponding control quantity setpoint depending on the currently selected cleaning mode, and in conjunction therewith also determining the resource requirement for cleaning;

[0682] • comparing whether there are sufficient resources available to meet the resource requirement of this cleaning strategy to reach the destination; and

[0683] • if this is not the case, preferably providing the driver with a cleaning mode with which the driver can reach his destination with the available resources and / or requesting the driver to refill the corresponding resources, the cleaning strategy provided being determined by using the alternative cleaning modes in descending order according to the resource requirement for determining the cleaning strategy until a cleaning strategy is found with which the motor vehicle can still be used to reach its destination without one of the selected sensors reaching an availability below the associated availability threshold.

[0684] In this way, it can be advantageously achieved that in the event of insufficient necessary resources according to the selected cleaning mode to reach the destination, the driver of the motor vehicle can decide whether he wishes to execute a service stop to refill the required resources, whereby the currently selected cleaning mode can be maintained, or whether he wishes to dispense with the availability of the driver assistance system and thus possibly reach the destination more quickly if necessary.

[0685] Optionally, the availability threshold depends on the selected cleaning mode.

[0686] For the selected sensors, different cleaning modes can have different error tolerances.

[0687] In particular, it can be taken into account that the fault tolerance of the selected sensors in a cleaning mode set for fully autonomous motor vehicle operation is lower than the fault tolerance of the selected sensors in a cleaning mode set for motor vehicle operation which does not allow fully autonomous motor vehicle operation.

[0688] It is proposed here that the availability threshold for each sensor can have different values for different cleaning modes.

[0689] In this way, it can be advantageously achieved that cleaning resources are saved by different availability thresholds for different cleaning modes.

[0690] Advantageously, the cleaning mode is read from an electronic control unit.

[0691] It is proposed here that the cleaning pattern can be read from the electronic control unit. This makes it advantageous that the cleaning pattern can be defined in the electronic control unit and used in the context of the cleaning method, in particular in the context of the cleaning method according to the first aspect of the application and in the context of the method for determining a cleaning strategy, in particular in the context of the method according to the fourth aspect of the application.

[0692] Furthermore, it can be advantageously achieved that the cleaning pattern can be defined in the electronic control unit, in particular by the manufacturer of the motor vehicle, so that the manufacturer of the motor vehicle can also influence the cleaning of the sensor surfaces, in particular since these are safety-relevant aspects, which can also reach the scope of the manufacturer's liability in the event of a malfunction.

[0693] Optionally, the cleaning pattern is acquired from a selection device.

[0694] The following terms are explained in more detail:

[0695] A "selection device" is to be understood as a device which can be used to select a cleaning pattern. Preferably, a rotary switch or a selector slide or an electronic input unit or the like can be considered here.

[0696] It is proposed here in particular that the cleaning pattern can be obtained from a selection device, in particular a selection device which is located in the direct sphere of influence of the driver of the vehicle, so that the driver can influence the cleaning pattern and thus indirectly the cleaning strategy by adjusting the selection device according to his needs.

[0697] According to a preferred variant of this embodiment, the cleaning pattern is set in such a way that a fully autonomous motor vehicle operation is enabled, in which every surface operatively connected to a sensor relevant to the fully autonomous motor vehicle operation is to be cleaned.

[0698] It is proposed here that the cleaning pattern is set for a fully autonomous motor vehicle operation.

[0699] If the motor vehicle is set up and registered for a fully autonomous motor vehicle operation, this can preferably mean that all sensors installed on the motor vehicle are selected and thus the availability of all sensors must be guaranteed.

[0700] In other words, this can result in the case that if such a motor vehicle falls below the availability threshold, the motor vehicle must stop the fully autonomous motor vehicle operation at least until the corresponding availability is again above the availability threshold.

[0701] For the cleaning system, this means that the availability of the sensors must be prevented from falling below the associated availability threshold. This applies equally to the object of the cleaning method, in particular the cleaning method according to the first aspect of the application, and thus also to the object of the method presented here for determining a cleaning strategy.

[0702] According to a further preferred variant of this embodiment, the cleaning pattern is set such that a specified driver of the motor vehicle is able to operate the motor vehicle comfortably, wherein each surface operatively connected to a sensor relevant to a comfortable autonomous motor vehicle operation is to be cleaned.

[0703] The cleaning pattern presented here relates to a comfortable operation of the motor vehicle.

[0704] Preferably, this means that the operation is comfortable for the driver of the motor vehicle. Comfortable here does not mean a fully autonomous motor vehicle operation, but rather a motor vehicle operation characterized by the fact that the driver of the motor vehicle controls the motor vehicle primarily himself.

[0705] However, a comfortable vehicle operation is understood to mean the functionality of several driver assistance systems (in particular a lane departure warning system or a distance warning system or the like) which can make the driving of the driver more comfortable.

[0706] In other words, it is presented here that the cleaning system ensures the availability of all selected sensors relevant to the cleaning pattern, which is set such that the motor vehicle is able to be operated comfortably with an appropriate cleaning method, in particular with a cleaning method according to the first aspect of the application.

[0707] According to a further preferred variant of this embodiment, the cleaning pattern is set such that a specified driver of the motor vehicle is able to operate the motor vehicle as safely as possible, wherein each surface operatively connected to a sensor relevant to an autonomous motor vehicle operation as safely as possible is to be cleaned.

[0708] It is presented here that the availability of all sensors required for a safety-relevant driver assistance system is monitored, wherein the method presented here is set to ensure that the respective availability does not fall below the relevant threshold value for the availability.

[0709] According to a further preferred variant of this embodiment, the cleaning pattern is set such that the motor vehicle is able to have the best possible range, wherein each surface operatively connected to a sensor relevant to an autonomous motor vehicle operation with the best possible range is to be cleaned.

[0710] The cleaning pattern presented here enables the motor vehicle to achieve the maximum range with its remaining cleaning resources.

[0711] This is preferably possible by deactivating all driver assistance systems for active vehicle operation not prescribed by law, so that the associated sensors can also be available below any relevant availability threshold.

[0712] In an advantageous embodiment, the method is performed for a plurality of surfaces to be cleaned, in particular for two, three, four, five or more surfaces to be cleaned.

[0713] It is proposed here to establish a cleaning strategy for a plurality of surfaces to be cleaned. This can be done serially or in parallel.

[0714] This applies in particular to all surfaces of the motor vehicle which are actively connected with the (selected) sensors.

[0715] Optionally, the step of determining the control quantity setpoint takes into account a measured quantity, preferably a process quantity, particularly preferably a current humidity along the planned route and / or a predicted humidity and / or a current temperature in the vicinity of the motor vehicle and / or a predicted temperature along the planned route and / or a current rainfall along the planned route and / or a predicted rainfall and / or a current snowfall along the planned route and / or a predicted snowfall.

[0716] It is provided here that a measured quantity is taken into account when determining the cleaning strategy.

[0717] This makes it possible to find a control quantity setpoint, preferably on the basis of current or expected weather conditions on a pre-planned route, which provides a better relationship between the increase in availability of the individually selected sensors and the cleaning resources used compared to a control quantity setpoint which does not take into account a measured quantity.

[0718] In detail, by necessary adaptations, this applies to what has already been done under the third aspect of the application.

[0719] Preferably, the step of determining the control quantity setpoint takes into account the vehicle type.

[0720] In particular, in this context, the type of motor vehicle provides information about the built-in cleaning system and the position and orientation of the surfaces intended to be cleaned. In detail, by necessary adaptations, this applies to what has already been done under the second aspect of the application.

[0721] It is understood that the determination of the control strategy can take into account any resources for cleaning one or more surfaces. In particular, it is important to take into account that the cleaning system can also cause resource constraints, which can also be taken into account when determining the cleaning strategy. Preferably, the flow rate of the fluid pump can be considered as a possible boundary condition, which can require that only a certain number of cleaning processes can be executed in parallel.

[0722] Preferably, if the corresponding availability falls below a corresponding availability threshold, it is suggested to clean the selected sensor by means of a predetermined reserve cleaning procedure as a last-minute remedy.

[0723] It should be noted that the subject matter of the fourth aspect can advantageously be combined individually or cumulatively with the subject matter of the preceding aspects of the present application in any combination.

[0724] According to a fifth aspect of the present application, the task is solved by a method for indirectly deriving a system dependency of a system behavior of a system component of a cleaning system of a motor vehicle, wherein the cleaning system is adapted for cleaning at least one surface of the motor vehicle by means of a cleaning procedure, which is preferably adapted for resource-efficient cleaning, particularly preferably for resource-saving cleaning, wherein an output quantity depends on an input quantity by means of the system behavior of the system, the method comprising the following steps:

[0725] - determining the input quantity as a first parameter of the method by means of at least one sensor;

[0726] - determining the output quantity as a second parameter of the method, preferably by means of at least one sensor;

[0727] - if necessary, digitizing and recording the determined first and second parameters by a data processing system, wherein the data processing system comprises an electronic data processing and evaluation system and a database;

[0728] - storing the determined first and second parameters in the database as data sets of a dependency table in an ordered manner with respect to each other;

[0729] - deriving the system dependency between the first and second parameters by means of the electronic data processing and evaluation system from at least two data sets of the dependency table stored in the database, preferably from at least 50 data sets of the dependency table, particularly preferably from at least 200 data sets of the dependency table, wherein the electronic data processing and evaluation unit accesses the data sets of the dependency table and determines the system dependency from the data sets of the dependency table by means of an algorithm; and

[0730] - preferably storing the derived system dependency in the database and / or the electronic data processing and evaluation unit and / or the electronic control unit.

[0731] Due to the increasing importance of driver assistance systems depending on the information provided by the sensors, motor vehicles are increasingly equipped with an increasing number of sensors.

[0732] Most of these sensors depend on the functionality of the surface actively connected to the individual sensor to avoid excessive contamination.

[0733] In addition to the number of sensors, the number of installation positions of the sensors on the vehicle is also increasing, as is the number of surfaces operatively connected to at least one of the sensors that are to be cleaned by the cleaning system.

[0734] Thus, the complexity of the cleaning system for a motor vehicle is constantly increasing. In particular, the number of nozzles and fluid connections is increasing. This is accompanied by a steady increase in the number of and complexity of valve devices, cleaning fluid pumps and cleaning fluid reservoirs.

[0735] In the same measure in which the automation of the entire vehicle is increased by sensors, the degree of automation of the cleaning system for a motor vehicle has also risen, since an increase in the automation of a motor vehicle also requires an increase in the automation of the individual cleaning processes. After all, it cannot be expected that a driver of a partially autonomous or autonomous motor vehicle will pay attention to the contamination status of the relevant surfaces in connection with the sensors for monitoring and / or regulating the driving operation. Thus, the automation by means of driver assistance systems also requires automation of the cleaning system for a motor vehicle.

[0736] In addition to the above-mentioned complex drivers, the networking of the systems with one another is playing an increasingly important role.

[0737] In summary, the number of sensors and systems involved and their complexity and degree of networking are steadily increasing.

[0738] As a result, the susceptibility to errors of the system components involved in the cleaning system and the associated maintenance requirements are increasing. The increasing complexity of the individual system components and the increasing complexity of the entire cleaning system make it difficult to identify possible errors, so that the maintenance work on the cleaning system becomes more and more time-consuming over time.

[0739] Since the different system components of a defined cleaning system for a defined motor vehicle can also come from different suppliers, the search for possible errors becomes more difficult.

[0740] Despite the increasing expectations for the maintenance of such cleaning systems, it has recently become apparent that these cannot withstand the constantly increasing system complexity and the constantly accelerating need for system changes in the area of the cleaning system for a motor vehicle.

[0741] It is proposed here a method for deriving a system dependency for a description of a system behavior of a system component of a cleaning system for a motor vehicle.

[0742] The system behavior of a system component is the reaction of the system component to a specification of the system component, wherein the specification of the system component can be described by input quantities and the reaction of the system component can be described by output quantities.

[0743] In other words, the output quantity of a system component depends on the input quantity by means of the system behavior.

[0744] It should be noted that a system component of a cleaning system can be understood as a single component of the cleaning system, as well as a single assembly and the entire cleaning system. Especially since each of the above-mentioned variants has an individual system behavior, which can be analyzed and the knowledge about the system behavior can subsequently be advantageously used.

[0745] Especially it can be envisaged that the known system behavior of a system component, especially the known system behavior in the form of the system dependency derived here, can be used for comparison with the observed system behavior of this system component. If there is a deviation between the known and thus initially expected system behavior and the observed system behavior, this can indicate that the system component and / or the cleaning system has a significant feature and / or a fault and / or a defect.

[0746] In this way, the system dependency derived here on the basis of experimental values offers in an advantageous manner the possibility to compare the observed behavior of a system component with the expected value of the system behavior of the system component described by the system dependency and thus to verify whether the system component and / or the cleaning system behaves as expected.

[0747] Preferably, each system component comprises an individual system dependency.

[0748] For each system component to be diagnosed on the basis of experimental values translated into a system dependency, an individual system dependency can preferably be derived according to this aspect of the application.

[0749] The method presented here can be used to derive system dependencies of different system components serially and / or in parallel.

[0750] The method presented here for deriving a system dependency from experimental values can be divided into two parts. In the first part, experimental values about the system behavior of a system component are collected and stored in a dependency table. The input quantity that leads to an activity of the system component and the output quantity that describes the reaction of the system component to the activity caused by the associated input quantity are stored in the dependency table in an ordered manner.

[0751] In the second part of the method, the experimental values collected in the dependency table are further processed into a system dependency by means of an algorithm.

[0752] It should be expressly pointed out that experimental values can be collected within the framework of this procedure in the course of the regular operation of the system component during the operation of the motor vehicle in which the system component is installed. Furthermore, it is also conceivable that corresponding experimental values can be collected during the operation of the system component in the laboratory or by means of a numerical simulation using a suitable numerical model and stored in the dependency table.

[0753] It goes without saying that the system dependency presented here can only take into account those quantities of the input quantities and those quantities of the output quantities which can be recorded and thus evaluated. In particular, quantities which are acquired by means of sensors based on physical and / or chemical action principles should be taken into account. Furthermore, it is also conceivable that quantities are determined by means of numerical sensors which can record values in a numerical model or which, based on measured quantities, can provide further quantities which are not measured but can be determined in numerical form depending on at least one measured quantity.

[0754] While the experimental values are discrete experiences of the individual input quantities, the advantage of the system dependency is that the system dependency can reproduce the system behavior of the system component in the range of the input quantities, in particular continuously and discretely.

[0755] The system dependency presented here is generated by means of an algorithm based on the sampling points of the collected discrete experimental values, it is possible that the system dependency at the sampling points defined by the corresponding input quantities can have different output quantities compared to the recorded experiences. This can preferably be caused by an averaging of the experiences.

[0756] Preferably, the input quantities are understood to be quantities which are at least indirectly suitable for influencing the system component. The input quantities do not have to be adjusted directly. The input quantities can also result from environmental conditions. It is especially conceivable that low temperatures lead to the formation of ice in a cleaning system, which can also change the system behavior of the system component.

[0757] It should be expressly pointed out that neither the input quantities nor the output quantities according to the aspects presented here have to be limited to quantities which directly influence the system component considered or which can be determined directly at the system component considered. Rather, it should be taken into account that each input quantity and each output quantity can be considered within the aspect which can have an indirect influence on the system behavior of the system component considered or which can be indirectly influenced by the system component.

[0758] The first part of the procedure presented here shows the following steps:

[0759] - determining the input quantities as a first parameter of the method by means of at least one sensor, wherein in each case it can be advantageous to provide input quantities which can have multiple dimensions and which are indicative of the behavior of at least one system component for further processing by means of the sensors;

[0760] - determining the output quantity as a second parameter of the method, preferably by means of at least one sensor, wherein in each case the output quantity, which can have multiple dimensions and describes the system behavior of the system component as a function of the input quantity determined by means of the above-mentioned process steps, can advantageously be provided by means of a sensor for further processing;

[0761] - digitizing, if necessary, and recording the determined first and second parameters by a data processing system, wherein the data processing system comprises an electronic data processing and evaluation system and a database, wherein the input and output quantities are advantageously prepared and stored for digital processing; and

[0762] - storing the determined first and second parameters as data sets of a dependency table in an ordered manner with respect to one another in the database, wherein the previously determined quantities of the method can advantageously be stored in an ordered manner with respect to one another in the dependency table in such a way that the output quantity is assigned to the input quantity, the system behavior of the system component caused by the output quantity describing the output quantity.

[0763] In summary, the first part of the procedure advantageously makes it possible to generate a dependency table consisting of experimentally determined values of the system behavior of the system component considered.

[0764] The second part of the procedure presented here shows the following steps:

[0765] - deriving a system dependency between the first and second parameters by means of the electronic data processing and evaluation system from at least two data sets of the dependency table stored in the database, preferably from at least 50 data sets of the dependency table, particularly preferably from at least 200 data sets of the dependency table, wherein the electronic data processing and evaluation unit accesses the data sets of the dependency table and determines the system dependency from the data sets of the dependency table by means of an algorithm, wherein in this step the system dependency is advantageously derived mathematically by means of a suitable algorithm.

[0766] The derived system dependency can then advantageously be stored, so that it can be called up for further processing, in particular stored in a non-volatile data memory. Preferably, it can be envisaged that the system dependency is stored in the database and / or in the electronic data processing and evaluation unit and / or in the electronic control unit.

[0767] Preferably, the input quantity comprises at least one measured quantity, preferably a process quantity and / or a control quantity.

[0768] It is proposed here that the input quantity comprises a measured quantity, in particular a process quantity and / or a control quantity.

[0769] While the control quantities directly apply to influence the cleaning system and thus at least indirectly the system components of the cleaning system, the process quantities are quantities which at least indirectly depend on the control quantities or which cannot be influenced by common means and which only comprise an influence on the system behavior of the system components.

[0770] The process quantities are preferably quantities which are present in or around the cleaning system and which can at least indirectly be influenced by the input quantities.

[0771] It can be advantageously implemented that the dependency table and / or the system dependency can depend on directly determined input quantities, in particular process quantities and / or control quantities, wherein important influencing quantities of the system behavior of the system components can be taken into account.

[0772] In a preferred embodiment, the output quantities and / or the input quantities comprise a cleaning process of a surface of a motor vehicle, preferably a resource requirement of the power consumption, preferably the resource requirement is determined depending on a control quantity setpoint for the cleaning process of the surface.

[0773] In connection with the system components of the cleaning system, the power consumption is a relatively easy to determine quantity.

[0774] Since the energy demand of the system components fluctuates relatively little under normal conditions, the power consumption of the system components can be used relatively quickly and easily to determine whether a change in the energy using system components has occurred.

[0775] Thus, it can be advantageously implemented that the power consumption can also be taken into account to describe the system behavior of the system components, wherein the power consumption required by the system components can advantageously be used for a comparison between the expected system behavior and the actual system behavior, also in the context of a diagnosis of the system components, in particular a diagnosis according to the sixth aspect of the present application.

[0776] Optionally, the output quantities and / or the input quantities comprise process quantities, preferably flow pressure and / or current and / or operating time and / or temperature and / or fill level signal and / or reaction time and / or sensing time and / or signal of a leakage sensor and / or signal of a flow meter and / or number of actuations and / or spray pattern and / or thermal monitoring signal, preferably a thermal monitoring signal with reference to a certain reference area, and / or signal of a debris sensor and / or signal of a check valve and / or signal of a drip flow sensor and / or signal of a distance sensor and / or signal of a force sensor.

[0777] In the context of the output quantities and / or the input quantities, the process quantities are also valuable indicators for assessing the system behavior of the system components of the cleaning system of the motor vehicle.

[0778] In particular, any process quantity which is preferably easy to determine or particularly meaningful should be taken into account in this context.

[0779] In particular, the level signal of the cleaning fluid reservoir can be considered. If the cleaning system is not in active use at this time, in which in particular no cleaning fluid pump is in active operation, and a decrease in the level signal of the cleaning fluid reservoir can still be observed, this relatively simply indicates an undesired leak in the cleaning system, through which cleaning fluid escapes.

[0780] Alternatively, the signal of the flow rate sensor in the flow channel for cleaning fluid can also be considered, in particular by determining the static pressure on the wall of the flow channel for cleaning fluid. For example, if the cleaning fluid pump is in active operation and all possible valves in the cleaning system are set such that cleaning fluid should flow through the flow channel for cleaning fluid, and if the signal of the flow rate sensor does not indicate this, there is a deviation between the expected system behavior and the actual system behavior. This can have several reasons, such as a leak in the cleaning fluid system or an empty cleaning fluid reservoir.

[0781] It should be expressly mentioned that for other process quantities, too, a causal relationship to the system behavior occurs.

[0782] It can thus be advantageously achieved that process quantities in the form of output quantities can be included in the dependency table and / or in the system dependencies for evaluating the system behavior, wherein the diagnosis of the cleaning system can be advantageously improved in downstream steps.

[0783] In an optional embodiment, the input quantities include the humidity and / or the temperature and / or the amount of rainfall and / or the amount of snowfall in the vicinity of the motor vehicle.

[0784] It has been shown that in particular environmental conditions, such as preferably humidity and / or temperature and / or rain and / or snow, can have an influence on the system behavior of the cleaning system, in particular the environmental conditions in the immediate vicinity of the motor vehicle.

[0785] In particular, low temperatures can lead to local freezing within the cleaning system, causing local flow blockages.

[0786] In addition, dependencies and influences between the quantities can also be considered.

[0787] By including the above-mentioned quantities in the input quantities, the accuracy of the system dependencies can advantageously be increased.

[0788] In an advantageous embodiment, the input quantities include the vehicle type.

[0789] The type of the motor vehicle determines the specific design and arrangement of the individual system components of the cleaning system.

[0790] Thus, in different constellations and / or arrangements of system components, different influences of the system behavior of a first system component can also be caused by the system behavior of a second system component. The vehicle type provides information about the constellation and / or arrangement of system components of the cleaning system and thus represents a simple possibility to explicitly record the corresponding interactions.

[0791] In this respect, the interaction between the first system component and the second system component is also determined by the vehicle type.

[0792] Thus, the inclusion of the vehicle type allows to advantageously increase the mapping accuracy of the system dependencies presented here and thus also of the dependency table.

[0793] Preferably, the input quantity comprises the availability of the sensor.

[0794] If it is suggested here that the input quantity comprises the availability, this preferably means the availability before the cleaning process is started using the cleaning system.

[0795] The effectiveness of the cleaning process carried out by means of the cleaning system depends not only on other influencing variables, but also on the availability of the sensor whose surface is to be cleaned which is actively connected thereto.

[0796] The availability of the sensor is a measure of the degree of contamination of the surface connected to the sensor.

[0797] It has been shown that different availabilities of the sensor at the beginning of the cleaning process include an influence on the cleaning result. In other words, the possible gain in availability can be different for a cleaning process carried out in the same way.

[0798] It is especially suggested that the input quantity comprises the parameter of the cleaning process and / or the output quantity comprises the gain in availability.

[0799] This makes it possible to evaluate the system behavior of the cleaning system and / or of the system components of the cleaning system on the basis of the cleaning result, especially depending on the parameter of the cleaning process.

[0800] This advantageously allows the system behavior of the cleaning system to be evaluated using already installed sensors, especially using sensors for supporting driver assistance systems.

[0801] In this way, it can advantageously be achieved that the evaluation of the system behavior of the system components of the cleaning system does not necessarily have to add additional sensors necessary only for the evaluation of the cleaning system.

[0802] It should be expressly pointed out that this aspect in particular relates to the second, third, ninth and tenth aspects of the present application. It goes without saying that this aspect also relates to the other aspects of the present application and there are interrelationships.

[0803] Optionally, the input quantity comprises a current coordinate of the motor vehicle.

[0804] It has also been shown that the coordinate of the motor vehicle comprises an influence on the system behavior of the system components of the cleaning system.

[0805] Preferably, weather conditions can be taken into account, which depend on the coordinate of the motor vehicle. In particular, it has been shown that the system behavior of the system components of the cleaning system depends on the temperature and / or the humidity and / or the solar radiation and / or the precipitation and / or the snowfall.

[0806] According to a relatively simple procedure, the weather conditions at the coordinate of the motor vehicle are related to the current latitude on the planet, which can be determined from the coordinate of the motor vehicle.

[0807] Thus, it can be advantageously achieved that, based on the coordinate of the motor vehicle and based on the correlation with the weather conditions, relevant influencing variables on the system behavior of the system components of the cleaning system can be taken into account, wherein the dependency table and / or the accuracy of the system dependency can be advantageously improved for the system behavior.

[0808] According to a more precise method, it is also recommended that the motor vehicle uses local information about the current and / or predicted weather at its coordinate. Thus, when determining the dependency table and / or the system dependency, influencing variables that have an effective relationship with the system behavior of the system components of the cleaning system and can be determined directly or indirectly from the coordinate of the motor vehicle can be used to increase the mapping accuracy of the predicted system behavior.

[0809] It goes without saying that this aspect relates to the other aspects of the invention and that there are interrelationships.

[0810] In a preferred embodiment, the output quantity comprises the availability of the sensor and / or the availability gained due to the cleaning process.

[0811] It is here recommended that the output quantity comprises the availability of the sensor and / or the gain in availability due to the use of the cleaning system.

[0812] If it is here recommended that the output quantity comprises the availability, this preferably means the availability after the completion of the cleaning process using the cleaning system.

[0813] In this way, it can be advantageously determined how the system behavior of the system components of the cleaning system depends on the cleaning success of the cleaning process carried out by the cleaning system. The gain in availability is due to the difference between the availability after the cleaning process and the availability before the cleaning process.

[0814] In an advantageous embodiment, the system dependency is determined by means of a regression analysis.

[0815] It is here recommended to use a regression algorithm as an algorithm for indirectly deriving the system dependency.

[0816] Thus, algorithms can be advantageously applied which have already been tested in a large number of applications and which can be optimally selected and / or adapted in terms of the system behavior considered here, so that a high-quality system dependency can be determined.

[0817] Preferably, the system dependency is determined in the form of a curve, preferably a curve and a determination coefficient of the curve.

[0818] The advantage of this is that the system dependency is indicated by a curve which is a function of at least one input quantity of the system behavior of the system component; in particular, this curve has no gaps, so that a clear assignment between the input quantity and the output quantity, in particular a continuous and differentiable dependency between the input quantity and the output quantity due to the system behavior of the system component, can be realized, so that the system dependency is ideally adapted for any mathematical method using the system dependency.

[0819] Assuming that a sufficient number of data sets are available, the evaluation of the determination coefficient from the determined data and the curve determined by means of the regression model provides an indication of the accuracy of the system dependency. It can be advantageously evaluated how meaningful the correlation between the input quantity and the output quantity is and how well the existing or recorded data can be reproduced. In addition, in the case of a large determination coefficient, the curve also allows statements to be made about the boundaries of the existing data. For example, it can be envisaged that the data can be supplemented and / or extrapolated in numerical form at the boundaries of the existing data.

[0820] Advantageously, the system dependency is determined by means of an optimization process.

[0821] It is proposed here that the parameters of the system dependency are determined by means of an optimization procedure, in particular by means of a minimization procedure which minimizes the cumulative deviation of the experimental values considered from the data sets of the system dependency. In this way, it is advantageously possible to determine a system dependency which can be derived in the best possible way, in particular with the smallest cumulative deviation from the initial empirical values.

[0822] Preferably, the parameters of the system dependency are determined by maximizing the resulting determination coefficient.

[0823] Preferably, the system dependency is determined by means of a self-learning optimization method.

[0824] In particular, it is proposed to use an algorithm which includes the properties of an algorithm from the class of machine learning. Thus, the algorithm is able to derive a system dependency between the input quantity and the availability difference due to the contamination.

[0825] The advantage of this is that the complex task of indirectly deriving the system dependencies by using a self-learning optimization method does not have to be laboriously adapted to new conditions by hand. Thus, time and money can be saved in the indirect derivation of the system dependencies.

[0826] Since the optimization program strives to determine the best system dependencies even in a multi-criteria environment and under various boundary conditions, the quality of the derived system dependencies can be improved by the aspects presented here.

[0827] It is also conceivable that the optimization can be performed under multiple equal objectives and / or boundary conditions (multi-criteria optimization). In particular, a class of algorithms that can determine a Pareto optimum and / or a Pareto front is considered. In particular, simplex methods and / or evolutionary strategies and / or evolutionary optimization algorithms and the like from the field are suggested here for deriving the system dependencies.

[0828] Optionally, the data sets of the dependency table from an already existing database are used to derive the system dependencies, preferably the data sets of the already existing database are accessed previously.

[0829] The advantage of this is that data from existing databases can also be used to derive the system dependencies. Thus, it can be achieved that it is not necessary to first collect experimental values at a particular motor vehicle and to transfer them into the data of the database and subsequently into the system dependencies. In this way, existing data and experimental values can be used to derive the system dependencies of a pollution process without first collecting experimental values representing the system dependencies of the pollution process.

[0830] In an optional embodiment, the already existing database is continuously expanded.

[0831] Advantageously, it can be achieved that the number of derivable system dependencies increases over time.

[0832] Furthermore, it can be advantageously achieved that the accuracy of the system dependencies can be improved since the number of experimental values known by means of the data sets is large.

[0833] Advantageously, the new data sets replace the data sets in the dependency table that deviate most from the derived system dependencies.

[0834] In particular, the fact that the empirical values are exchanged with the largest Euclidean distance from the system dependencies should be considered.

[0835] Advantageously, it can be achieved that the system dependencies become more and more accurate over time, which can be expressed by an increase in the determination coefficient.

[0836] Furthermore, this can have the advantage that even weakly related system dependencies can be better identified over time.

[0837] It is further proposed that the output quantity and / or the input quantity comprises a frequency and / or a speed of the cleaning fluid pump.

[0838] This can advantageously improve the dependency table and / or the system dependency accuracy, since it has been found that the frequency and / or the speed of the cleaning fluid pump can influence the system behavior of the system components.

[0839] It is further proposed that the output quantity and / or the input quantity comprises a size of the nozzle and / or a type of the washing fluid and / or a quality of the washing fluid.

[0840] Since it has been found that the size of the nozzle and / or the type of the washing fluid and / or the quality of the washing fluid can influence the system behavior of the system components, this can advantageously improve the dependency table and / or the system dependency accuracy.

[0841] It is proposed that the output quantity and / or the input quantity comprises a pump diaphragm material and / or a hose material.

[0842] This can advantageously improve the dependency table and / or the system dependency accuracy, since it has been found that the pump diaphragm material and / or the hose material can influence the system behavior of the system components.

[0843] It should be noted that the subject matter of the fifth aspect can advantageously be combined individually or cumulatively with the subject matter of the preceding aspects of the present application in any combination.

[0844] According to a first alternative of the sixth aspect of the present application, this task is solved by a method for diagnosing a system behavior of a system component of a cleaning system of a motor vehicle,

[0845] wherein the output quantity depends on the input quantity by means of the system behavior of the system component of the cleaning system,

[0846] wherein an actual output quantity exceeding an upper threshold quantity and / or an actual output quantity falling below a lower threshold quantity indicates that the actual system behavior deviates from the expected system behavior,

[0847] The method comprises the following steps:

[0848] - preferably determining the input quantity;

[0849] - determining the actual output quantity;

[0850] - preferably retrieving the upper threshold quantity and / or the lower threshold quantity depending on the input quantity;

[0851] - comparing the actual output quantity with the upper threshold quantity and / or the lower threshold quantity;

[0852] - preferably, if the actual output quantity exceeds the upper threshold quantity and / or if the actual output quantity falls below the lower threshold quantity, a deviation between the actual output quantity and the upper threshold quantity is calculated, and / or a deviation between the actual output quantity and the lower threshold quantity is calculated; and

[0853] - preferably, if the actual output quantity exceeds the upper threshold quantity and / or if the actual output quantity falls below the lower threshold quantity, a diagnostic signal is stored.

[0854] It is proposed here a procedure for monitoring and diagnosing system components of a cleaning system of a motor vehicle.

[0855] The number of system components of the cleaning system and the number of functions of the cleaning system increase due to the increasing number of driver assistance systems in motor vehicles.

[0856] At the same time, the number of different combinations of different system components for forming the cleaning system also increases on the market, wherein the different system components are usually provided by different suppliers.

[0857] As a result, the complexity of the cleaning system also increases, since maintenance is required to maintain fault-free system operation.

[0858] This increases the need for at least partially automated or automatable methods for early detection of possible errors in the system components of the cleaning system.

[0859] It has been surprisingly found that electrical and mechanical anomalies in the system behavior of the system components of the cleaning system are usually related. This finding can be used to evaluate the system components based on mechatronic concepts.

[0860] If the evaluation of the cleaning system currently mainly depends on visual observation, the evaluation of the system components based on mechatronic concepts can advantageously lead to the fact that already existing or effortless additional electrical signals of the system components of the cleaning system can also be used to evaluate possible mechanical malfunctions. Previously, this could only be visually observed by trained personnel.

[0861] In particular, mechanical anomalies in the system behavior of the system components can usually be advantageously identified by at least partially automatically observing the electrical behavior of the system components. Thus, a variety of different possible problems related to the cleaning system can be detected by monitoring electrical quantities.

[0862] In particular, it is surprisingly determined that the time course of the surge of the cleaning fluid pump in the presence of a mechanical blockage of the flow channel for the cleaning fluid can indicate a characteristic difference from the time course of the surge current in the presence of an error-free regular switching on of the cleaning fluid pump, in particular in the case of a mechanical blockage of the flow channel until the specified outlet of the cleaning fluid in the nozzle. It is particularly advantageous that a partial blockage and a complete blockage of the flow channel for the cleaning fluid can be distinguished.

[0863] While the time course of the surge in the case of a regular switching on of the cleaning fluid pump only leads to a short overshoot step response in the normal case, the step response in the presence of a mechanical interlock can in particular indicate a temporally more pronounced course, in which the current only reaches the desired value for the continuous operation of the cleaning fluid pump with determinable damping.

[0864] The procedure presented here can preferably be carried out autonomously and thus preferably within the framework of a self-diagnosis of the cleaning system and report whether an abnormal system behavior of a system component of the cleaning system has been diagnosed.

[0865] In particular, it should also be considered that the diagnostic procedure presented here can preferably be activated without intervention by the driver of the motor vehicle by means of the electronic control unit of the motor vehicle and / or the cleaning system. Furthermore, it should also be considered that the diagnostic procedure presented here can preferably be activated manually by the driver of the motor vehicle.

[0866] The diagnosis presented here compares the expected behavior of a system component of the cleaning system with the system behavior determined during the monitoring of this system component by means of the actual output quantity. The comparison is carried out using at least one value of the output quantity.

[0867] The expected system behavior is in particular based on experimental values of the system component evaluated. These experimental values can be based on observations in the regular operation of the motor vehicle or in the laboratory or be the result of a numerical model.

[0868] If the comparison leads to the result that the system behavior of the monitored system component corresponds to the expected system behavior, it is concluded that the system component is not defective and / or not malfunctioning and / or that the system component is not damaged by external influences acting on the system component.

[0869] According to the method presented here, the expected system behavior is determined on the basis of an upper threshold quantity and / or a lower threshold quantity. If the signal of the actual output quantity lies in or runs in a range defined by the upper threshold quantity and the lower threshold quantity, the system behavior of the system component considered is not unexpected, wherein the range can also be open on one side, provided that only the upper threshold quantity or the lower threshold quantity is specified.

[0870] The method presented here thus requires a list with at least one upper threshold value or at least one lower threshold value for the output quantity. Each threshold value is an individual value for each output quantity and can also preferably depend on the input quantity and the system component considered.

[0871] Preferably, the upper threshold quantity and / or the lower threshold quantity depend on the process quantity.

[0872] If the monitored output quantity exceeds the individually associated upper threshold value or if the monitored output quantity falls below the individually associated lower threshold value, there is a deviation which can be characterized by another output quantity if necessary.

[0873] Furthermore, it is conceivable that a solution strategy is empirically learned with which a particular deviation can be corrected, in particular after the seventh aspect and / or the eighth aspect of the application.

[0874] If the deviation of the monitored output quantity from the expected output quantity and / or the characterization of the deviating system behavior leads to a known behavior pattern, this can be associated with a recommendation for action. This recommendation for action on the action is also based on empirical values, which can also be largely systematized.

[0875] With regard to the systematized empirical values, it should be specifically considered that depending on the type and severity of the deviation of the monitored output quantity from the expected output quantity, a certain error can be inferred. Preferably, this inference is valid or at least transferable for a plurality of different system components and a plurality of different cleaning systems.

[0876] For example, it should be considered here that an increase in the power consumption of the cleaning fluid pump and thus a deviation in the system behavior leads to the conclusion that there is an error in the cleaning system. It can be envisaged here in particular that the cleaning fluid pump will age, wherein it can be specifically envisaged in particular that a higher energy requirement will have to be used for the controlled pump pressure of the cleaning fluid pump.

[0877] Alternatively, it can be envisaged in this case that there is a blockage in the flow channel downstream of the cleaning fluid pump, which leads to an increased back pressure and thus influences the system behavior of the cleaning fluid pump. Depending on the case, it is possible to distinguish between the cause of the localization diagnostic deviation by comparing different output quantities. For this purpose, empirical values are necessary, which can be obtained in particular in a list.

[0878] This also shows that a deviation between the expected output quantity and the actual output quantity of the system behavior of a system component does not necessarily result from the monitored system component itself.

[0879] In case of a blockage in front of the pump, a possible solution strategy to correct the deviation with the on-board device can be to increase the pump pressure in a targeted manner, wherein the blockage can be released and flushed out of the cleaning system. In particular, the selection of a solution strategy according to the seventh aspect of the application can be considered.

[0880] When implementing a solution strategy, particular consideration should be given to implementing a solution strategy according to the eighth aspect of the application.

[0881] If the selected and implemented solution strategy is successful, it will result in a system behavior of the system components corresponding to the expected system behavior.

[0882] It should be expressly stated that the diagnostic method described here can be applied to any system component. If a sufficient number of sensors or measuring devices, a sufficient number of empirical values on the expected system behavior of one or more system components and a list of possible successful solution strategies are available, a large number of deviations can be corrected with the on-board device. Deviations in the system behavior that cannot be repaired with on-board resources can also be detected at an early stage and repaired within the scope of regular or early maintenance, wherein possible extensions that could otherwise be damaged can advantageously be prevented.

[0883] It goes without saying that the input quantity, the output quantity, the lower threshold quantity and / or the upper threshold quantity and / or the deviation can be a scalar or a vector.

[0884] Furthermore, it is optionally proposed to store or transmit the diagnostic signal to an electronic control unit of the motor vehicle.

[0885] Preferably, it is proposed to calculate the deviation between the actual output quantity and the upper threshold quantity if the actual output quantity exceeds the upper threshold quantity and / or to calculate the deviation between the actual output quantity and the lower threshold quantity if the actual output quantity falls below the lower threshold quantity.

[0886] The above-mentioned quantities are scalar quantities if only a single parameter is evaluated without a time progression of this parameter. In all other cases, in particular when considering a plurality of parameters of the cleaning system and / or when considering at least one time progression of a parameter, the above-mentioned quantities should be understood as vectors.

[0887] The preferred proposed calculation of the deviation between the actual output quantity and the upper threshold quantity and / or the lower threshold quantity therefore also depends on whether the output quantity is a scalar or a vector. It is proposed to adjust the upper threshold quantity and / or the lower threshold quantity to the dimensional properties of the actual output quantity, unless this is already the case, wherein it must be ensured that the upper threshold quantity and / or the lower threshold quantity and the actual output quantity each have corresponding values.

[0888] In the case of a vector actual output quantity, the calculation of the deviation is carried out individually for each component, i.e. for the dimension of the dimension.

[0889] A deviation can occur for some or all components of the actual output quantity, wherein a component can be assumed to be deviating both because the corresponding component of the lower threshold quantity is undershot and because the corresponding component of the upper threshold quantity is overshot.

[0890] If a deviation is determined for at least one component between the upper threshold quantity and / or the lower threshold quantity and the actual output quantity, a further investigation of the deviation is proposed.

[0891] The diagnostic signal can comprise that no deviation of the actual system behavior from the expected system behavior has been detected.

[0892] Furthermore, the diagnostic signal can comprise that a deviation of the actual system behavior from the expected system behavior has been detected, wherein the type and expression of the deviation can also be stored in the diagnostic signal.

[0893] Preferably, the proposed diagnostic signal comprises the deviation.

[0894] Preferably, the diagnostic signal comprises the output quantity and / or a course of the output quantity over time, wherein the course of the output quantity over time comprises at least two time points, preferably at least 10 time points, particularly preferably at least 20 time points.

[0895] It should be noted that the above values for the quantity of values over time are not to be understood as strict limits, but rather it should be possible to exceed it or fall below it on an engineering scale without departing from the described aspects of the application. Simply put, these values are intended to provide an indication of the magnitude of the quantity of values over the time range proposed here.

[0896] In particular, it should also be remembered that the diagnostic signal comprises a plurality of time curves of the output quantity over time, in particular a plurality of time curves of the output quantity over time together with the input quantity and / or the process quantity.

[0897] This enables a favorable observation and evaluation of changes in the system behavior of the system components, preferably depending on the input quantity and / or the process quantity, in particular with regard to possible aging effects and / or changes in the remaining expected service life of the system components.

[0898] Thus, an at least partially automated error detection of the system behavior of the system components of the cleaning system of the motor vehicle can be made possible in an advantageous manner, wherein possible errors can be detected autonomously at an early stage.

[0899] This also enables possible subsequent sources of error to be identified at an early stage, so that the propagation of errors can be advantageously limited.

[0900] In this way, it is also possible to advantageously extend the interval at which optical checks are to be performed by trained experts, thus reducing the overall maintenance costs of the cleaning system and the expected availability of the cleaning system.

[0901] According to a second alternative of the sixth aspect of the present invention, the task is solved by a method for diagnosing a deviation between an actual system behavior and an expected system behavior of a system component of a cleaning system of a motor vehicle,

[0902] wherein the output quantity depends on the input quantity by means of the system behavior of the system component of the cleaning system,

[0903] wherein the actual system behavior depending on the input quantity is represented by an actual output quantity and the expected system behavior depending on the input quantity is represented by an expected output quantity,

[0904] wherein the expected system behavior is represented by at least one data set of a dependency table or system dependency table, preferably a system dependency table derived according to the method of the fifth aspect of the present invention,

[0905] The method comprises the following steps:

[0906] - preferably determining the input quantity;

[0907] - determining the actual output quantity;

[0908] - determining the expected output quantity by:

[0909] o selecting from the dependency table the data set that best matches the input quantity, reading the output quantity stored in the selected data set and using it as the expected output quantity; or

[0910] o selecting from the dependency table the two data sets that best match the input quantity and determining the expected output quantity using linear interpolation based on the two selected data sets; or

[0911] o calculating the expected output quantity by inserting the input quantity into the system dependency;

[0912] - calculating a deviation between the actual output quantity and the expected output quantity; and

[0913] - preferably storing a diagnostic signal if the deviation is greater than 10% of the expected output quantity, preferably greater than 5% of the expected output quantity, particularly preferably greater than 2% of the expected output quantity.

[0914] The second alternative of the sixth aspect of the present invention also proposes, in parallel with the first alternative of the sixth aspect of the present invention, a program for monitoring and diagnosing a system component of a cleaning system of a motor vehicle.

[0915] It should be expressly mentioned that the non-limiting description of the first alternative of the sixth aspect of the application is also valid for the second alternative of the sixth aspect, and vice versa, wherein the actual output quantity is not compared to a lower threshold quantity and / or an upper threshold quantity, but to an expected output quantity.

[0916] In contrast to the first alternative, according to the second alternative of the sixth aspect of the application, it is proposed to compare the actual output quantity to an expected output quantity, whereby a deviation between the actual output quantity and the expected output quantity is determined.

[0917] The diagnosis proposed here compares the expected system behavior of a system component of the cleaning system to an expected system behavior. The comparison is performed on the basis of a comparison of at least one value of the actual output quantity to a corresponding value of the expected output quantity.

[0918] The expected system behavior is in particular based on experimental values of the system component diagnosed with the proposed method. These experimental values can be based on observations in regular operation of the motor vehicle or in a laboratory, or are results of a numerical model suitable for mapping regular system behavior of the cleaning system.

[0919] Preferably, the expected system behavior and thus the expected output quantity depend on the input quantity used for operating the cleaning system.

[0920] Preferably, the expected system behavior and thus the expected output quantity depend on the process quantity.

[0921] According to this second alternative of the sixth aspect of the application, in each case three further deviation variants are proposed by means of which the expected output quantity can be determined on the basis of experimental values.

[0922] According to the first variant and the second variant, it is conceivable that the expected system behavior of the system component is described by a dependency table, in particular a dependency table that has been created according to the first step of the method of the fifth aspect of the application.

[0923] It should be expressly mentioned that the dependency table can depend on the system component to be diagnosed, the input quantity and / or the process quantity.

[0924] Such a dependency table describes discrete experimental values of the expected system behavior of the system component one at a time, so that before the comparison to the actual output quantity must first be selected from the dependency table.

[0925] With regard to the evaluation of the dependency table, the first variant and the second variant for determining the expected output quantity differ from one another.

[0926] According to a first variant for selecting the expected output quantity, it is proposed to select from the dependency table in the form of an empirical value by comparing the actual input quantity and / or the actual process quantity with the input quantity and / or the process quantity of the respective data set and the shortest Euclidean distance with respect to the input quantity and / or the process quantity between the data set stored in the dependency table and the actual input quantity and / or the actual process quantity, in particular the data set best suited.

[0927] According to a second variant for selecting the expected output quantity, it is proposed to select two best fits and adjacent experimental values from the two data sets of the dependency table according to the description of the first variant and to interpolate between these two experimental values according to the actual input quantity and / or the actual process quantity.

[0928] According to a third variant for selecting the expected output quantity, it is proposed to map the expected system behavior of a system component by means of a system dependency, in particular a system dependency derived according to the fifth aspect of the present application.

[0929] The system dependency can continuously describe the expected system behavior as a function of the actual input quantity and / or the actual process quantity, so that a selection or interpolation between experimental values as described above for the second variant is no longer required.

[0930] Just like the dependency table according to the first variant and the second variant, the system dependency can only be valid for one system component, so that a deviation system dependency or a deviation dependency table can or should be selected in view of a deviating system component.

[0931] It is to be understood that the input quantity, the actual output quantity, the expected output quantity and / or the deviation can be scalar or vector. The above-mentioned quantities are scalar if only a single parameter describing the system behavior of the system component is evaluated without a time progression of this parameter. In all other cases, in particular when considering a plurality of parameters of the cleaning system and / or when considering at least one time progression of one parameter, the above-mentioned variables are to be understood as vectors.

[0932] The calculation of the deviation between the actual output quantity and the expected output quantity thus also depends on whether the output quantity is scalar or vector. If this is not the case, it is preferably recommended to adjust the expected output quantity to the dimensional properties of the actual output quantity, wherein in each case it must be ensured that the expected output quantity and the actual output quantity each have quantities that correspond to each other.

[0933] In the case of a vector actual output quantity, the calculation of the deviation is carried out separately for each component, i.e. for the dimension of the dimension.

[0934] If a deviation is determined for at least one component between the expected output quantity and the actual output quantity, a further investigation of this deviation is proposed.

[0935] According to the discussion already mentioned above, when determining the measured values, a determination error and an expected fluctuation of the corresponding signals also occur in the routine operation.

[0936] Therefore, not every nominal deviation between the expected output quantity and the actual output quantity leads to a deviation of the actual system behavior of the system component from its expected system behavior.

[0937] In order to quantify when the actual system behavior of the system component deviates from the expected system behavior, it is proposed here to use the relative deviation between the actual output quantity and the expected output quantity.

[0938] This relative comparison is also carried out component by component. It should also be considered that a limit value can be specified for each component of different size depending on the available experimental values, above which a deviation between the actual system behavior of the system component and the expected system behavior deviates.

[0939] In particular, a limit value of the deviation of 10%, preferably 5%, in particular 2%, is proposed.

[0940] It should be noted that the above values for the limit value of the deviation should not be understood as a strict limitation, but rather it should be possible to exceed it or fall below it on an engineering scale without departing from the described aspects of the application. Simply put, these values are intended to provide an indication of the size of the limit value of the deviation proposed here.

[0941] Preferably, the limit value of the deviation is 15%. Furthermore, preferably, the limit value of the deviation is 20%. Furthermore, preferably, the limit value of the deviation is 25%. Furthermore, preferably, the limit value of the deviation is 30%.

[0942] If the ratio between the actual output quantity and the expected output quantity in at least one component exceeds the limit value, the actual system behavior deviates from the expected system behavior of the system component considered.

[0943] Otherwise, the actual system behavior corresponds to the expected system behavior and it can be concluded that the system component of the cleaning system considered is not defective and / or not faulty and / or the system component is not damaged by external influences acting on the system component.

[0944] In particular, the deviation between the expected output quantity and the actual output quantity of the system behavior of the system component does not necessarily result from the monitored system component itself.

[0945] Rather, depending on the determined deviation, which system component of the cleaning system shows or can show a possible error can be part of a further diagnosis.

[0946] It is noted that the diagnostic method described herein can be used for any system component. If a sufficient number of sensors or measuring devices, a sufficient number of empirical values on the expected system behavior of one or more system components and a list of possibly successful solution strategies are available, a large number of occurring deviations can be corrected with on-board means. Deviations of system behavior that cannot be repaired with on-board resources can also be detected at an early stage and repaired within the scope of regular or early maintenance, wherein possible extensions that might otherwise be damaged can advantageously be prevented.

[0947] Furthermore, it is optionally proposed to store or transmit the diagnostic signal to an electronic control unit of the motor vehicle.

[0948] The diagnostic signal can comprise that no deviation of the actual system behavior from the expected system behavior has been detected.

[0949] Furthermore, the diagnostic signal can comprise that a deviation of the actual system behavior from the expected system behavior has been detected, wherein the type and expression of the deviation can also be stored in the diagnostic signal.

[0950] Preferably, the diagnostic signal comprises an output quantity and / or a course of the output quantity over time, wherein the course of the output quantity over time comprises at least two time points, preferably at least 10 time points, particularly preferably at least 20 time points.

[0951] It should be noted that the above values for the quantity of values over time are not to be understood as strict limits, but it should be possible to exceed it or fall below it on an engineering scale without departing from the described aspect of the application. Simply put, these values are intended to provide an indication of the size of the quantity of values over the time range proposed herein.

[0952] In particular, it should also be remembered that the diagnostic signal comprises a plurality of time curves of the output quantity over time, in particular a plurality of time curves of the output quantity over time together with the input quantity and / or the process quantity.

[0953] This enables a favorable observation and evaluation of changes in the system behavior of the system component, preferably depending on the input quantity and / or the process quantity, in particular with regard to possible aging effects and / or changes in the remaining expected service life of the system component.

[0954] If the comparison between the actual output quantity and the expected output quantity is completed, the diagnostic method can be stopped, or alternatively continued with the same system component or a different system component.

[0955] Thus, an at least partially automated error detection of the system behavior of the system component with regard to the cleaning system of the motor vehicle is made possible in an advantageous manner, wherein possible errors can be detected autonomously at an early stage.

[0956] This also makes it possible to detect possible subsequent error sources at an early stage, so that the propagation of errors can advantageously be limited.

[0957] In this way, it is also possible to advantageously extend the intervals at which optical checks by trained specialists are to be carried out, thus reducing the overall maintenance costs of the cleaning system.

[0958] In a preferred embodiment, the deviation comprises a time course, preferably a time course comprising at least two time points, preferably at least 10 time points, particularly preferably at least 20 time points, in the course.

[0959] It is proposed here in particular to regard the previously discussed deviation now also as a course of the deviation over time.

[0960] Preferably, the course of the deviation over time can also be stored, preferably in a database.

[0961] Preferably, the time course is stored together with the diagnostic signal.

[0962] In particular, it is proposed that the time course of the deviation begins shortly before a planned change in the input quantity. Preferably, the time course of the deviation ends after the next planned change in time.

[0963] In particular, it should be borne in mind that the output quantity is diagnosed over a period of at least slightly more than two planned changes in the input quantity on both sides. In particular, the diagnosis of the time course of the output quantity begins before the cleaning fluid pump is switched on and ends after the cleaning fluid pump is switched off.

[0964] On the basis of the time course of the output quantity, it is possible to assess the systematic error of the system component, in particular a systematic error which includes a dependency on the damping of the system behavior of the system component.

[0965] Furthermore, it is advantageous to consider that the time course is not continuously run, but rather that a certain output quantity is recorded after each activation of the system component.

[0966] In particular, it should be borne in mind that, after each activation process, the fluid pressure downstream of the cleaning fluid pump and / or the current downstream of the cleaning fluid pump and / or the fluid velocity downstream of the cleaning fluid pump are recorded within a defined time unit after the activation process, and the individual values recorded in each case are recorded and diagnosed as a time sequence.

[0967] In this way, it is possible to advantageously assess the performance degradation of the cleaning fluid pump over the service life, so that a warning can be provided if it is expected that the cleaning fluid pump is to be replaced.

[0968] It should be noted that the above values for the amount of data points should not be understood as strict limitations, but rather it should be possible to exceed it or fall below it on an engineering scale without departing from the described aspects of the application. Simply put, the values are intended to provide an indication of the size of the amount of data points in the time frame presented here.

[0969] The system behavior of the system component can advantageously be evaluated on the basis of the time course of the output quantity, wherein a plurality of further analysis possibilities are provided, in particular analysis possibilities related to the transport behavior of the system component.

[0970] In particular, the time course of the deviation can be evaluated as a function of the input quantity and / or the output quantity, wherein data with the same or very similar input quantity and / or process quantity are compared with each other.

[0971] Preferably, the time course comprises at least 30 time points. Preferably, the time course comprises at least 40 time points. Preferably, the time course comprises at least 50 time points.

[0972] Preferably, the analysis result of the time course of the deviation is stored together with and / or in the diagnostic signal.

[0973] Preferably, the time course of the deviation is checked for a step response.

[0974] It is presented here to evaluate the time course of the output quantity with regard to the step response, in particular with regard to the step response as a reaction to a change in the input quantity.

[0975] In particular, the value of the output quantity or the change in the change of the output quantity can be checked for a change in the input quantity.

[0976] Furthermore, it is presented to check the time course of the output quantity, preferably with regard to the transport behavior as part of the system behavior of the system component, wherein a damping influencing the output quantity can be determined.

[0977] Preferably, it can be diagnosed whether the nozzle is 'partially or completely clogged by cleaning fluid'. For example, a pressure peak behind the cleaning fluid pump indicates that the nozzle is clogged. The shape of the pulse spike can provide an advantageous indication of whether the flow channel behind the pump is completely clogged or partially clogged.

[0978] The comparison of the characteristic properties can require a comparison of the course of the pulse spike with one or more reference courses of the pressure.

[0979] If a clogging of the nozzle is detected, a resolution strategy according to the seventh and / or eighth aspect of the application can be used.

[0980] Alternatively, a warning can be generated requesting a manual cleaning of the nozzle.

[0981] By monitoring the surge of the cleaning fluid pump over time, it is also possible to diagnose whether it is clogged, especially in frozen conditions.

[0982] In particular, a clogged cleaning fluid pump has a higher damping with respect to the surge.

[0983] If a clogged cleaning fluid pump is detected, it can be particularly shut down, which has the advantage of preventing the cleaning fluid pump from burning out.

[0984] The system behavior of the system component can advantageously be evaluated on the basis of the time course of the output quantity, wherein a plurality of further analysis possibilities are provided, in particular analysis possibilities related to the transmission behavior of the system component.

[0985] In particular, the step response can be evaluated as a function of the input quantity and / or the output quantity, wherein data with the same or very similar input quantity and / or process quantity are compared with one another.

[0986] Preferably, the analysis results of the time course of the deviation are stored together with and / or in the diagnostic signal.

[0987] Advantageously, at least two time courses of the deviation are examined to determine the presence of a drift of the deviation over time, preferably at least five courses of the deviation, preferably at least 10 courses of the deviation.

[0988] It is proposed here to evaluate the time course of the output quantity with regard to a drift of the output quantity over time.

[0989] The drift is a systematic change in the output quantity as a reaction to the input quantity over the lifetime of the system component.

[0990] The time course of the output quantity can be compared with previously observed time courses of the change in the output quantity over time, in particular with a plurality of time courses of the change in the output quantity over time.

[0991] If the deviation over time continuously moves in one direction from the expected system behavior of the system component, a drift is present. According to this property, it can advantageously be determined how, in particular, a lifetime-related change in the system behavior of the system component develops.

[0992] Furthermore, it is advantageous to consider that the time course does not run continuously, but that a certain output quantity is recorded after each activation of the system component.

[0993] In particular, it should be remembered that after each activation process, the fluid pressure downstream of the cleaning fluid pump and / or the current downstream of the cleaning fluid pump and / or the fluid velocity are recorded within a defined time unit after the activation process, and the individual values recorded in each case are recorded and diagnosed as a time series.

[0994] In this way, a performance deterioration of the cleaning fluid pump during the service life can advantageously be assessed, such that a warning can be provided if a replacement of the cleaning fluid pump is desired.

[0995] In particular, the time courses of the deviations can be assessed in terms of the input quantities and / or the output quantities to determine whether a drift exists, wherein data with the same or very similar input quantities and / or process quantities are compared with each other.

[0996] Preferably, at least 20 time courses of the deviations are checked to determine whether a drift of the deviations over time exists. Preferably, at least 30 time courses of the deviations are checked to determine whether a drift of the deviations over time exists. Preferably, at least 40 time courses of the deviations are checked to determine whether a drift of the deviations over time exists.

[0997] It should be noted that the above values for the number of time courses of the deviations should not be understood as strict limitations, but it should be possible to exceed it or fall below it on an engineering scale without departing from the described aspects of the application. Simply put, these values are intended to provide an indication of the size of the number of time courses of the deviation ranges proposed here.

[0998] Preferably, the results of the analysis of the time courses of the deviations are stored together with and / or in the diagnostic signals.

[0999] The cause of the actual system behavior deviating from the expected system behavior can be based on the currently diagnosed system component or can have a cause based on a system component deviating from the system component but being transferred to the actually diagnosed system component according to a system-related transfer function between the components.

[1000] If the corresponding transfer function is not known, it is advisable to further diagnose the system component to limit the cause.

[1001] The diagnostic signals preferably include information about input quantities, which have an influence on the cleaning system and / or the system component during the diagnosis of the system component.

[1002] The diagnostic signals preferably include information about process quantities, which have an influence on the cleaning system and / or the system component during the diagnosis of the system component.

[1003] It goes without saying that the advantages of the system dependency, in particular according to the fifth aspect of the application, also apply to the use of the system dependency, in particular the use of the system dependency according to the sixth aspect of the application proposed here.

[1004] It should be noted that the subject matter of the sixth aspect can advantageously be combined individually or cumulatively with the subject matter of the aforementioned aspects of the application in any combination.

[1005] According to a seventh aspect of the present application, this task is solved by a method for selecting a resolution strategy from a list of resolution strategies contained in a database depending on a current diagnostic signal, preferably a current diagnostic signal received according to the sixth aspect of the present application, wherein the list of resolution strategies contains at least one resolution strategy associated with a diagnostic signal, wherein the resolution strategy is selected from the list of resolution strategies whose associated diagnostic signal best matches the current diagnostic signal.

[1006] If the actual system behavior of a system component of a cleaning system of a motor vehicle does not correspond to the expected system behavior, the deviation between the actual system behavior and the expected system behavior can have several reasons.

[1007] In particular, the reason for the deviation of the actual system behavior from the expected system behavior can be due to the currently diagnosed system component or can be due to a deviation of a system component but is transmitted to the actually diagnosed system component according to a system-related transfer function between the system components.

[1008] Preferably, the reason for the deviation between the actual system behavior and the expected system behavior can be determined by the diagnostic signal, in particular by the current diagnostic signal according to the sixth aspect of the present application.

[1009] The current diagnostic signal represents a diagnostic signal which is influenced by the resolution strategy within the scope of the method. In particular, the current diagnostic signal can be created using the method according to the sixth aspect of the present application. In particular, the current diagnostic signal indicates that there is a deviation between the actual system behavior and the expected system behavior.

[1010] When determining the reason for the deviation between the actual system behavior and the expected system behavior by means of the diagnostic signal, input quantities and / or process quantities which have an influence on the system component and / or the cleaning system when determining the diagnostic signal are particularly preferred.

[1011] It should be particularly considered that the current diagnostic signal can be associated, and preferably can be explicitly associated, with the reason for the deviation of the system behavior of the system component based on existing experimental values.

[1012] Furthermore, it can be specifically considered that these experimental values are systematized to such an extent that they are valid or at least transferable for a plurality of different system components and / or a plurality of different cleaning systems.

[1013] In this way, it can be advantageously achieved that based on existing experience of different system components of different cleaning systems, in particular of different cleaning systems of different manufacturers or suppliers, an explicit assignment between the current diagnostic signal and the reason for the deviation of the system behavior can be made, in particular an explicit manufacturer-independent and type-independent assignment for the cleaning system and / or the particular system component.

[1014] In particular, four different types of reasons for a deviation between the actual system behavior and the expected system behavior are proposed, which preferably can be distinguished by means of the diagnostic signal, in particular preferably by means of the current diagnostic signal according to the sixth aspect of the application.

[1015] In particular, it is proposed here to determine the class of the reason in the presence of the current diagnostic signal.

[1016] According to a first class of reasons for a deviation between the actual system behavior and the expected system behavior, there is a defect of a system component. In this respect, many different defects can be envisaged.

[1017] In particular, it can be envisaged that, if there is a defect, the cleaning fluid line itself has been separated from the system components of the cleaning system. Such a defect can also be repaired by untrained persons.

[1018] Furthermore, it can be envisaged that there is a leak in the cleaning fluid line. In this case, spare parts are required at least in the medium term and the defect cannot be repaired by untrained personnel alone at least in the medium term.

[1019] According to a second class of reasons for a deviation between the actual system behavior and the expected system behavior, there is an aging phenomenon of a system component.

[1020] Even if most of the system components of the cleaning system of a motor vehicle are designed in such a way that they survive in the expected service life of the motor vehicle, the system components nevertheless age. In particular, it can also be envisaged that a system component ages faster than expected, so that the expected service life of this system component is shorter than the planned service life of the motor vehicle. In this case, the replacement of such a component is unavoidable for further regular operation of the cleaning system.

[1021] Preferably, according to the sixth aspect of the application, an aging phenomenon can be detected and / or evaluated on the basis of a drift of the deviation over time, in particular on the basis of a drift of the deviation.

[1022] The course of the drift of the deviation over time is a particularly preferred way of determining how much of the expected availability of a system component remains.

[1023] According to a third class of reasons for a deviation between the actual system behavior and the expected system behavior, there is an interference of a system component.

[1024] It should be expressly mentioned that a fault can be present in a system component for which a diagnostic procedure has already been carried out, in particular a diagnostic procedure according to the sixth aspect of the application. Alternatively, the fault can also be caused by a deviating system component, wherein the fault is in particular transmitted to the system behavior of the diagnostic procedure by means of a transfer function.

[1025] According to a fourth category of reasons for a deviation between an actual system behavior and an expected system behavior of a system component, there is an unknown reason for a deviation of a system behavior of a system component.

[1026] If the reason for a deviation between an actual system behavior and an expected system behavior of a system component cannot be determined based on the diagnostic signal, there is an unknown reason.

[1027] It should be especially kept in mind that so far, there are not enough experimental values for possible reasons for a deviation or that the assignment of reasons would lead to ambiguous results.

[1028] A solution strategy is a method designed to backtrack a deviation between an actual system behavior and an expected system behavior found in a system component of a cleaning system applied to a motor vehicle.

[1029] In other words, the solution strategy can advantageously achieve that the deviation regarding the system component becomes smaller or that the actual system behavior corresponds to the expected system behavior again.

[1030] Particularly preferably, the solution strategy comprises an input quantity, which, when the solution strategy is applied, influences the cleaning system and / or and / or the system component on the cleaning system and / or the system component.

[1031] Preferably, the solution strategy displays a notification to a driver of the motor vehicle and / or to a manufacturer of the motor vehicle.

[1032] Preferably, the solution strategy comprises measures to plan a maintenance and / or repair of the motor vehicle.

[1033] The solution strategy is preferably based on an operational experience of the cleaning system. Such an experience can be obtained during operation of the motor vehicle and / or in a laboratory and / or based on a numerical model and / or can be a result of an existing maintenance recommendation and / or can be based on heuristics.

[1034] A suitable solution strategy depends on the deviation of the system behavior and / or the current diagnostic signal, in particular on the current diagnostic signal determined according to the sixth aspect of the present invention.

[1035] Preferably, the suitable solution strategy depends on a process quantity.

[1036] Preferably, the solution strategy depends on an input quantity influencing the cleaning system and / or the system component when the deviation of the system behavior and / or the diagnostic signal is determined.

[1037] By the solution strategy, it can advantageously be achieved that the system component of the cleaning system behaves again as expected. This allows the functionality of the cleaning system to return to normal operation, regardless of the previously existing deviation of the system behavior.

[1038] Overall, the resolution strategy can be so advantageous that, despite the system behavior of the system components of the cleaning system being diagnosed as deviating, the functionality of the driver assistance system can be maintained for a longer period of time.

[1039] It is proposed here in particular to select a resolution strategy from a list of known resolution strategies that is suitable for the current diagnostic signal.

[1040] In particular, it is proposed to obtain the list of known resolution strategies from a database that is accessible to the motor vehicle. The motor vehicle can also be connected wirelessly to a suitable database that includes resolution strategies.

[1041] In addition to the resolution strategy, the database also includes the associated diagnostic signal for which the resolution strategy has been set up to remedy.

[1042] In addition to the resolution strategy, the database preferably includes input quantities that have an influence on the system components and / or the cleaning system when determining the current diagnostic signal.

[1043] In addition to the resolution strategy, the database can also preferably include process quantities that have an influence on the system components and / or the cleaning system when determining the current diagnostic signal.

[1044] Preferably, the resolution strategy can be determined with the aid of the current diagnostic signal, in particular with the aid of the current diagnostic signal obtained according to the sixth aspect of the application.

[1045] The resolution strategy that is best matched to the current diagnostic signal from the diagnostic signals assigned to it in the database is selected from the database.

[1046] Preferably, the most suitable resolution strategy is selected from the database using the smallest Euclidean distance between the diagnostic signals assigned to it in the database and the current diagnostic signal.

[1047] When determining the resolution strategy with the aid of the current diagnostic signal, particular preference is given to focusing on input quantities and / or process quantities that have an influence on the system components and / or the cleaning system when determining the current diagnostic signal.

[1048] It is furthermore proposed with preference that the database with resolution strategies is pre-filtered first with respect to the best-fitting input quantities and / or the best-fitting process quantities, in particular on the basis of the corresponding Euclidean distances between the input quantities and / or process quantities stored in the diagnostic signals and the input quantities and / or process quantities in the database.

[1049] It is proposed to subsequently select a resolution strategy on the basis of the current diagnostic signal according to the above procedure according to the smallest possible Euclidean distance to the remaining resolution strategi...

Claims

1. A method for optimizing resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of a cleaning process (30, 32, 34, 36, 38, 40) of a surface (20, 22, 24, 26, 28) of a motor vehicle (14), wherein sensors (50, 52, 54, 56, 56a, 56b, 58) are operatively connected to the surface (20, 22, 24, 26, 28), wherein the method uses data from a dependency table of a system behavior of a cleaning system (16, 200) of the motor vehicle (14), wherein the dependency table comprises data sets (DP1, DP2, DP3, DP4), each data set comprising input quantities (202) of the cleaning system (16, 200) and output quantities (204) of the cleaning system (16, 200), wherein the output quantities (204) depend on the input quantities (202) by means of the system behavior of the system (16, 200), wherein the dependency table comprises data sets (DP1, DP2, DP3, DP4) of the system behavior of the cleaning system (16, 200) between at least one control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) of the cleaning process (30, 32, 34, 36, 38, 40), an availability (220, 222, 224) of the sensors (50, 52, 54, 56, 56a, 56b, 58) at a start time (38b, 40b) of the cleaning process (30, 32, 34, 36, 38, 40) and an availability (220, 222, 224) of the sensors (50, 52, 54, 56, 56a, 56b, 58) at an end time (38c, 40c) of the cleaning process (30, 32, 34, 36, 38, 40), wherein the resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of the cleaning process (30, 32, 34, 36, 38, 40) depend on the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119), the method comprising the following steps: - accessing the data of the dependency table from a database (154) and / or an electronic data processing and evaluation unit (152) and / or an electronic control unit (18); deriving, for each data set (DP1, DP2, DP3, DP4) of the dependency table, a difference between the availability (220, 222, 224) of the sensor (50, 52, 54, 56, 56a, 56b, 58) at an end time (38c, 40c) of the cleaning process (30, 32, 34, 36, 38, 40) and the availability (220, 222, 224) of the sensor (50, 52, 54, 56, 56a, 56b, 58) at a start time (38b, 40b) of the cleaning process (30, 32, 34, 36, 38, 40); deriving a ratio of the difference to a respective resource requirement (30d, 32d, 34d, 36d, 38d, 40d) of each data set (DP1, DP2, DP3, DP4) of the dependency table; selecting the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) of the data set (DP1, DP2, DP3, DP4) comprising the highest value of the ratio; and storing the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) as a control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) setpoint in the database (154) and / or the electronic data processing and evaluation unit (152) and / or the electronic control unit (18).

2. A method for optimizing a resource requirement (30d, 32d, 34d, 36d, 38d, 40d) of a cleaning process (30, 32, 34, 36, 38, 40) of a surface (20, 22, 24, 26, 28) of a motor vehicle (14), wherein a sensor (50, 52, 54, 56, 56a, 56b, 58) is operatively connected to the surface (20, 22, 24, 26, 28), wherein the method uses a system dependency (120, 120D, 120R) of a system behavior of a cleaning system (16, 200) of the motor vehicle (14), wherein the system dependency (120, 120D, 120R) comprises data sets (DP1, DP2, DP3, DP4), each data set comprising an input quantity (202) of the cleaning system (16, 200) and an output quantity (204) of the cleaning system (16, 200), wherein the output quantity (204) depends on the input quantity (202) by means of the system behavior of the system (16, 200), wherein the system dependency (120, 120D, 120R) comprises a data set (DP1, DP2, DP3, DP4) of the system behavior of the cleaning system (16, 200) between the availability (220, 222, 224) of the sensor (50, 52, 54, 56, 56a, 56b, 58) at a start time (38b, 40b) of the cleaning process (30, 32, 34, 36, 38, 40) and the availability (220, 222, 224) of the sensor (50, 52, 54, 56, 56a, 56b, 58) at an end time (38c, 40c) of the cleaning process (30, 32, 34, 36, 38, 40) of at least one control variable (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) of the cleaning process (30, 32, 34, 36, 38, 40), wherein the resource requirement (30d, 32d, 34d, 36d, 38d, 40d) of the cleaning process (30, 32, 34, 36, 38, 40) depends on the control variable (110, 111, 112, 113, 114, 115, 116, 117, 118, 119), the method comprising the following steps: - accessing the system dependency (120, 120D, 120R) from a database (154) and / or an electronic data processing and evaluation unit (152) and / or an electronic control unit (18); - deriving, for a course of the system dependency (120, 120D, 120R), a course of a difference between the availability (220, 222, 224) of the sensor (50, 52, 54, 56, 56a, 56b, 58) at an end time (38c, 40c) of the cleaning process (30, 32, 34, 36, 38, 40) and the availability (220, 222, 224) of the sensor (50, 52, 54, 56, 56a, 56b, 58) at a start time (38b, 40b) of the cleaning process (30, 32, 34, 36, 38, 40); - deriving a course of a ratio of the course of the difference of the system dependency (120, 120D, 120R) to a course of a respective resource requirement (30d, 32d, 34d, 36d, 38d, 40d); - selecting the control variable (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) belonging to the point of the course of the ratio comprising the highest value of the ratio; and - selecting the control variable (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) belonging to the point of the course of the ratio comprising the highest value of the ratio; and - storing the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) as a control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) setpoint in the database (154) and / or the electronic data processing and evaluation unit (152) and / or the electronic control unit (18).

3. The method for optimizing the resource requirement (30d, 32d, 34d, 36d, 38d, 40d) of a cleaning process (30, 32, 34, 36, 38, 40) of a surface (20, 22, 24, 26, 28) of a motor vehicle (14) according to one of claims 1 to 2, characterized in that the system behavior is a cleaning process (30, 32, 34, 36, 38, 40) of at least one surface (20, 22, 24, 26, 28).

4. The method for optimizing the resource requirement (30d, 32d, 34d, 36d, 38d, 40d) of a cleaning process (30, 32, 34, 36, 38, 40) of a surface (20, 22, 24, 26, 28) of a motor vehicle (14) according to one of claims 1 to 2, characterized in that - the dependency table or system dependency (120, 120D, 120R) comprises a dependency on a process quantity (140, 141, 142, 143, 144, 145, 146, 147); and - wherein, prior to the selection of the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119), first the data set (DP1, DP2, DP3, DP4) considered in the selection of the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) from the dependency table and / or the regional constraint of the system dependency (120, 120D, 120R) considered in the selection of the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) is a region in which the deviation from the respective process quantity (140, 141, 142, 143, 144, 145, 146, 147) is less than 20%.

5. The method for optimizing the resource requirement (30d, 32d, 34d, 36d, 38d, 40d) of a cleaning process (30, 32, 34, 36, 38, 40) of a surface (20, 22, 24, 26, 28) of a motor vehicle (14) according to claim 4, characterized in that the process quantity (140, 141, 142, 143, 144, 145, 146, 147) is a humidity and / or a temperature and / or a rainfall amount and / or a snowfall amount in the vicinity of the motor vehicle (14) and / or a coordinate of the motor vehicle (14).

6. The method for optimizing resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of a cleaning process (30, 32, 34, 36, 38, 40) of a surface (20, 22, 24, 26, 28) of a motor vehicle (14) according to claim 4, characterized in that the respective process quantity (140, 141, 142, 143, 144, 145, 146, 147) is a current humidity and / or a forecast humidity along the planned route and / or a current temperature in the vicinity of the motor vehicle (14) and / or a forecast temperature along the planned route and / or a current rainfall along the planned route and / or a forecast rainfall along the planned route and / or a current snowfall along the planned route and / or a forecast snowfall along the planned route and / or coordinates of the motor vehicle (14) and / or forecast coordinates of the motor vehicle (14) along the planned route.

7. The method for optimizing resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of a cleaning process (30, 32, 34, 36, 38, 40) of a surface (20, 22, 24, 26, 28) of a motor vehicle (14) according to one of claims 1 to 2, characterized in that - the dependency table or the system dependency (120, 120D, 120R) comprises a dependency of the availability (220, 222, 224) of the sensor (50, 52, 54, 56, 56a, 56b, 58) at the start time (38b, 40b) of the cleaning process (30, 32, 34, 36, 38, 40); and - wherein, prior to the selection of the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119), first the data set (DP1, DP2, DP3, DP4) considered in the selection of the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) from the dependency table and / or the regional constraint of the system dependency (120, 120D, 120R) considered in the selection of the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) is offset by less than 20% from the actual availability (221) of the sensor (50, 52, 54, 56, 56a, 56b, 58) and / or the expected availability (223) of the sensor (50, 52, 54, 56, 56a, 56b, 58) at the point on the planned route, a method for determining the expected availability (223) at the distance or operating time of the motor vehicle (14) that is still to be covered is applied.

8. Method for optimizing resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of a cleaning process (30, 32, 34, 36, 38, 40) of a surface (20, 22, 24, 26, 28) of a motor vehicle (14) according to one of claims 1 to 2, characterized in that - the dependency table or the system dependency (120, 120D, 120R) comprises a dependency of the availability (220, 222, 224) of the sensors (50, 52, 54, 56, 56a, 56b, 58) at the start time (38b, 40b) of the cleaning process (30, 32, 34, 36, 38, 40) on the availability (220, 222, 224) of the sensors (50, 52, 54, 56, 56a, 56b, 58) at the start time (38b, 40b) of the cleaning process (30, 32, 34, 36, 38, 40); - wherein before the selecting the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) first the data set (DP1, DP2, DP3, DP4) considered in the selecting the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) from the dependency table and / or the regional constraint of the system dependency (120, 120D, 120R) considered in the selecting the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) is a region in which the availability (220, 222, 224) of the sensors (50, 52, 54, 56, 56a, 56b, 58) at the start time (38b, 40b) of the cleaning process (30, 32, 34, 36, 38, 40) is less than or equal to the actual availability (220, 222, 224) of the sensors (50, 52, 54, 56, 56a, 56b, 58); and - wherein the availability (220, 222, 224) of the sensors (50, 52, 54, 56, 56a, 56b, 58) at the start time (38b, 40b) of the cleaning process (30, 32, 34, 36, 38, 40) associated with the selected control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) is additionally saved together with the selected control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) as control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) setpoint.

9. Method for optimizing resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of a cleaning process (30, 32, 34, 36, 38, 40) of a surface (20, 22, 24, 26, 28) of a motor vehicle (14) according to one of claims 1 to 2, characterized in that, Before the selection of the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119), the data set (DP1, DP2, DP3, DP4) to be considered in the selection of the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) from the dependency table and / or the region of the system dependency (120, 120D, 120R) to be considered in the selection of the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) is first limited to a region in which the expected availability gain (229) does not exceed 20% and / or until a threshold of availability (227, 228) is reached, the availability that can be used for the current trip of the motor vehicle (14) without unintentionally impairing the functionality of the sensors, a method for determining an expected availability gain (229) is applied, wherein the sum of the current availability and the expected availability gain is sufficient to achieve the distance or operating time to be covered by the motor vehicle (14) in such a way that the threshold of availability (227, 228) is not exceeded.

10. Method for optimizing resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of a cleaning process (30, 32, 34, 36, 38, 40) of a surface (20, 22, 24, 26, 28) of a motor vehicle (14) according to one of claims 1 to 2, characterized in that, Before the selection of the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119), the data set (DP1, DP2, DP3, DP4) to be considered in the selection of the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) from the dependency table and / or the region of the system dependency (120, 120D, 120R) to be considered in the selection of the control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) is first limited to a region in which the expected availability gain (229) is sufficient to achieve the distance or operating time to the next cleaning process without falling below the threshold of availability (227, 228) and does not exceed 20% of the availability gain (229) required to achieve the distance or the operating time to the next cleaning process without falling below the threshold of availability (227, 228), a method for determining the expected distance or expected operating time of the motor vehicle (14) to be covered when the threshold of availability (227, 228) is reached is applied, a method for determining an expected availability gain (229) is applied, wherein the sum of the current availability and the expected availability gain is sufficient to achieve the distance or operating time to be covered by the motor vehicle (14) in such a way that the threshold of availability (227, 228) is not exceeded.

11. Method for optimizing resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of a cleaning process (30, 32, 34, 36, 38, 40) of a surface (20, 22, 24, 26, 28) of a motor vehicle (14) according to one of claims 1 to 2, characterized in that, selecting a first control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) and a second control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119), wherein a respective first control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) setpoint and a respective second control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) setpoint define a first cleaning process (30, 32, 34, 36, 38, 40) and a second cleaning process (30, 32, 34, 36, 38, 40) of a series of cleaning processes (30, 32, 34, 36, 38, 40), the second cleaning process (30, 32, 34, 36, 38, 40) being executed after completion of the first cleaning process (30, 32, 34, 36, 38, 40).

12. Method for optimizing resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of a cleaning process (30, 32, 34, 36, 38, 40) of a surface (20, 22, 24, 26, 28) of a motor vehicle (14) according to one of claims 1 to 2, characterized in that The method is executed serially or in parallel for a plurality of surfaces (20, 22, 24, 26, 28) to be cleaned.

13. Method for optimizing resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of a cleaning process (30, 32, 34, 36, 38, 40) of a surface (20, 22, 24, 26, 28) of a motor vehicle (14) according to one of claims 1 to 2, characterized in that, The control quantities (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) are selected by means of a multi-criteria optimization program.

14. A cleaning method (10) for a resource-efficient cleaning of at least one surface (20, 22, 24, 26, 28) of a motor vehicle (14), wherein the motor vehicle (14) comprises a cleaning system (16) and at least one sensor (50, 52, 54, 56, 56a, 56b, 58), wherein the sensor (50, 52, 54, 56, 56a, 56b, 58) is operatively connected to one surface (20, 22, 24, 26, 28), wherein the cleaning method comprises at least one cleaning process (30, 32, 34, 36, 38, 40), wherein the cleaning process (30, 32, 34, 36, 38, 40) is adapted for cleaning one surface (20, 22, 24, 26, 28) and comprises a cleaning cycle (38a, 40a) comprising a start time (38b, 40b) and an end time (38c, 40c), wherein the cleaning system (16) comprises an electronic control unit (18), a cleaning fluid distribution system (60), at least one nozzle (70, 72, 74, 76, 76a, 76b, 78, 78a, 78b), and at least one cleaning fluid line (80, 82, 84, 86, 88), wherein the sensors (50, 52, 54, 56, 56a, 56b, 58) are adapted to detect at least one measured quantity (100, 102, 104, 106, 107, 108), a process quantity (140, 141, 142, 143, 144, 145, 146, 147), and / or a control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) and to transmit the measured quantity (100, 102, 104, 106, 107, 108) to the electronic control unit (18), wherein the nozzles (70, 72, 74, 76, 76a, 76b, 78, 78a, 78b) are adapted to operatively connect a cleaning fluid (64) to the surface (20, 22, 24, 26, 28), wherein the electronic control unit (18) is adapted to control and / or regulate the cleaning process (30, 32, 34, 36, 38, 40) by means of at least one control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) of the cleaning process (30, 32, 34, 36, 38, 40), wherein the resource requirement (30d, 32d, 34d, 36d, 38d, 40d) of the cleaning process (30, 32, 34, 36, 38, 40) depends on a control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) setpoint, characterized in that the electronic control unit (18) controls and / or regulates the resource-efficient cleaning by applying a control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) setpoint derived by the method according to one of claims 1 to 13.

15. The cleaning method (10) according to claim 14, characterized in that The cleaning fluid distribution system comprises at least one fluid reservoir (62).

16. The cleaning method (10) according to claim 14, characterized in that The measured quantity (100, 102, 104, 106, 107, 108) is an availability (220, 222, 224) of the sensor (50, 52, 54, 56, 56a, 56b, 58).

17. The cleaning method (10) according to claim 14, characterized in that The process quantity (140, 141, 142, 143, 144, 145, 146, 147) is a humidity and / or a temperature and / or a rainfall and / or a snowfall in the vicinity of the motor vehicle (14) and / or coordinates of the motor vehicle (14).

18. The cleaning method (10) according to claim 14, characterized in that The electronic control unit (18) controls and / or regulates the resource-efficient cleaning depending on an actual measured quantity value of the sensor (50, 52, 54, 56, 56a, 56b, 58) operatively connected to the surface (20, 22, 24, 26, 28) to be cleaned.

19. The cleaning method (10) according to claim 18, characterized in that The actual measured quantity value is an actual availability (221).

20. Use of a control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) set point derived by a method according to one of claims 1 to 13 for optimizing resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of a cleaning process (30, 32, 34, 36, 38, 40) of a surface (20, 22, 24, 26, 28) of a motor vehicle (14) for a resource-efficient cleaning of at least one surface (20, 22, 24, 26, 28) of a motor vehicle (14).

21. A cleaning system (16) comprising an electronic control unit (18), a cleaning fluid distribution system (60), at least one nozzle (70, 72, 74, 76, 76a, 76b, 78, 78a, 78b), and at least one cleaning fluid line (80, 82, 84, 86, 88), wherein the cleaning fluid distribution system (60) contains at least one fluid reservoir (62), wherein the cleaning system (16) is adapted to perform a method according to one of claims 1 to 13 for optimizing resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of a cleaning process (30, 32, 34, 36, 38, 40) of a surface (20, 22, 24, 26, 28) of a motor vehicle (14), wherein sensors (50, 52, 54, 56, 56a, 56b, 58) are operably connected to the surface (20, 22, 24, 26, 28), and / or wherein the cleaning system (16) is adapted to perform a cleaning method (10) according to one of claims 14 to 19 for a resource-efficient cleaning of at least one surface (20, 22, 24, 26, 28) of a motor vehicle (14).

22. A motor vehicle (14), wherein the motor vehicle (14) comprises a cleaning system (16) according to claim 21, and / or wherein the motor vehicle (14) is adapted to perform a cleaning method (10) according to one of claims 14 to 19 for a resource-efficient cleaning of at least one surface (20, 22, 24, 26, 28) of a motor vehicle (14), and / or wherein the motor vehicle (14) is adapted to perform a method according to one of claims 1 to 13 for optimizing resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of a cleaning process (30, 32, 34, 36, 38, 40) of a surface (20, 22, 24, 26, 28) of a motor vehicle (14), and / or wherein the motor vehicle (14) is adapted to perform a method according to one of claims 1 to 13 for optimizing resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of a cleaning process (30, 32, 34, 36, 38, 40) of a surface (20, 22, 24, 26, 28) of a motor vehicle (14), The control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) setpoint derived by the method for optimizing the resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of the cleaning process (30, 32, 34, 36, 38, 40) of the surfaces (20, 22, 24, 26, 28) of the motor vehicle (14) according to one of claims 1 to 13 is adapted for resource-efficient cleaning of at least one surface (20, 22, 24, 26, 28) of the motor vehicle (14).

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