Method for indirectly deriving system dependencies, diagnostic method, method for selecting a solution strategy, use of a solution strategy, cleaning method, cleaning system, and motor vehicle

Abstract

The present invention relates to a method for indirectly deriving system dependencies of the system behavior of system components of a cleaning system of a motor vehicle, wherein the cleaning system is adapted to clean at least one surface of the motor vehicle by means of a cleaning process, preferably adapted for resource-efficient cleaning, particularly preferably for resource-saving cleaning. The present invention also relates to a diagnostic method, a method for selecting a solution strategy, the use of a solution strategy, a cleaning method, a cleaning system, and a motor vehicle.

Description

[0001] The invention relates to a method for indirectly deriving system dependencies of system behaviors of system components of a cleaning system, a diagnostic method, a method for selecting a solution strategy, the use of a solution strategy, a cleaning method, a cleaning system, and a motor vehicle.

[0002] In particular, the present invention relates to a cleaning method, a method for indirectly deriving system dependencies of the system behavior of a cleaning system of a motor vehicle, particularly preferably of the system behavior of a cleaning process for a surface of a motor vehicle, a method for optimizing resource requirements for a cleaning process for a surface of a motor vehicle, a method for determining a cleaning strategy for cleaning a surface to be cleaned of a motor vehicle, a method for indirectly deriving system dependencies of the system behavior of system components of a cleaning system of a motor vehicle, a method for diagnosing deviations between actual system behavior and expected system behavior of system components of a cleaning system of a motor vehicle, a method for selecting a solution strategy, use of a selected solution strategy, a method for indirectly deriving system dependencies of the system behavior of a contamination process for a surface of a motor vehicle, use of a dependency table and / or system dependencies for determining expected availability at a distance to be covered or an operating time of a motor vehicle, a dependency table and / or system dependencies for determining expected availability at a distance to be covered or an operating time of a motor vehicle. Use of a dependency table and / or system dependencies for determining an expected distance to be covered or an operating time of a motor vehicle when an availability threshold is reached, use of a dependency table and / or system dependencies for optimizing the resource requirements of a cleaning process for a surface of a motor vehicle, use of a dependency table and / or system dependencies for determining a cleaning strategy for cleaning a surface to be cleaned of a motor vehicle, use of a dependency table and / or system dependencies for determining a necessary expected availability gain, use of system dependencies derived by a method for indirectly deriving system dependencies for resource-efficient cleaning of at least one surface of a motor vehicle, use of control quantity set points derived by a method for optimizing the resource requirements of a cleaning process for a surface of a motor vehicle for resource-efficient cleaning of at least one surface of a motor vehicle, use of a cleaning strategy derived by a method for determining a cleaning strategy for cleaning a surface to be cleaned of a motor vehicle for resource-efficient cleaning of at least one surface of a motor vehicle, a cleaning system, and a motor vehicle.

[0003] The number of sensors installed in motor vehicles has also increased due to the recent steady 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 of pedestrians, and / or within the framework of semi-autonomous or autonomous motor vehicle operation.

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

[0006] Cleaning sensor surfaces requires resources such as water, cleaning agents, and energy, which can only be stored or carried in vehicles to a limited extent. As a result, there is a growing demand for resource-saving cleaning processes.

[0007] Furthermore, the increase in the number of sensors installed in motor vehicles has led to a situation where some of the data may be collected redundantly by several sensors, but a failure of one sensor generally also leads to a failure of the driver assistance system.

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

[0009] Therefore, the decision-making process for adequate cleaning of appropriate sensors becomes more complex. There are many influences that determine adequate cleaning and how it should be achieved.

[0010] Prior art cleaning of the front and / or rear windscreen of a motor vehicle is known, in particular using windscreen wipers, wherein a cleaning fluid can also be applied to the front and / or rear windscreen.

[0011] Document EP 0 932 533 A1 discloses a device for controlling a windshield wiping and / or washing system. A sensor device detects wetting or soiling of the windshield. When wetting or soiling of the windshield is detected, as well as when the ignition key is pressed or reverse gear is engaged, the wiping and / or washing system is activated. This ensures a clear view through the vehicle windows when the vehicle is started and when reverse gear is engaged as a precautionary measure. Depending on the degree of wetting and / or soiling, a period during which the wiping and / or washing system is activated can also be specified.

[0012] DE 103 07 216 A1 discloses a process for operating a washer / wiper system for 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. The electronic control unit adaptively controls the wiper speed during the cleaning process, depending on the driving situation and / or environmental input parameters.

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

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

[0015] According to a first aspect of the invention, the object is achieved by a cleaning method for resource-efficient cleaning, preferably resource-saving cleaning, of 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 a surface, wherein the cleaning method comprises at least one cleaning process, wherein the cleaning process is adapted for cleaning a 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 distribution system, which preferably comprises at least one fluid reservoir, at least one nozzle, and at least one cleaning fluid line, wherein the sensor is adapted for detecting at least one measured quantity, preferably the availability of the sensor, a process quantity, preferably humidity and / or temperature and / or rainfall and / or snowfall in the vicinity of the motor vehicle and / or the coordinates of the motor vehicle, and / or a control quantity, and transmitting the measured quantity to the electronic control unit, wherein the nozzle is adapted for bringing the cleaning fluid into operative connection with the surface, wherein the electronic control unit is adapted for controlling and / or regulating the cleaning process by means of at least one control quantity of the cleaning process, wherein the resource requirement of the cleaning process depends on a control quantity setpoint,

[0016] It is characterized by:

[0017] The electronic control unit controls resource-efficient cleaning, preferably resource-saving cleaning, by means of 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 one another, wherein each data set comprises at least one input quantity of the cleaning system, preferably a process quantity, preferably humidity and / or temperature and / or rainfall and / or snowfall in the vicinity of the motor vehicle and / or coordinates of the motor vehicle, and / or a control quantity and / or vehicle type and / or sensor availability, and at least one output quantity of the cleaning system, preferably a resource requirement of the cleaning process and / or sensor availability,

[0018] and / or

[0019] The electronic control unit controls resource-efficient cleaning, preferably resource-saving cleaning, depending on a system dependency of the system behavior of the cleaning system, in particular of the system behavior of the cleaning process of the surface of the motor vehicle, the system dependency being a relationship between: input quantities of the cleaning system, preferably at least one controlled quantity and / or at least one process quantity of the cleaning process, preferably humidity and / or temperature and / or rainfall and / or snowfall and / or coordinates of the motor vehicle in the vicinity of the motor vehicle, and / or vehicle type and / or availability of sensors; and output quantities of the cleaning system, preferably resource requirements of the cleaning process and / or availability of sensors, specifically controlling resource-efficient cleaning, preferably resource-saving cleaning, depending on the system dependency derived by the method for indirectly deriving system dependencies of the system behavior of a cleaning system of a motor vehicle according to the second aspect of the invention.

[0020] and / or

[0021] The electronic control unit applies a control quantity setpoint, particularly preferably a control quantity setpoint derived by the method according to the third aspect of the invention, to control resource-efficient cleaning, preferably resource-saving cleaning,

[0022] and / or

[0023] The electronic control unit preferably applies a cleaning strategy, particularly preferably a cleaning strategy derived by the method according to the fourth aspect of the invention, to control the resource-efficient cleaning, preferably resource-saving cleaning.

[0024] and / or

[0025] The cleaning method comprises process steps for indirectly deriving system dependencies of system behaviors of system components of a cleaning system of a motor vehicle, preferably process steps for indirectly deriving system dependencies according to the fifth aspect of the invention,

[0026] and / or

[0027] The cleaning method comprises process steps for diagnosing the system behavior of system components of a cleaning system of a motor vehicle, preferably process steps for diagnosing the system behavior of system components of a cleaning system according to the first alternative of the sixth aspect of the invention,

[0028] and / or

[0029] The cleaning method comprises process steps for diagnosing deviations between actual and expected system behavior of system components of a cleaning system of a motor vehicle, preferably process steps for diagnosing deviations between actual and expected system behavior of system components of a cleaning system according to the second alternative of the sixth aspect of the invention,

[0030] and / or

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

[0032] and / or

[0033] The cleaning method comprises process steps for using a selected solution strategy, preferably process steps for using a selected solution strategy according to the eighth aspect of the present invention,

[0034] and / or

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

[0036] and / or

[0037] This cleaning method includes process steps for using:

[0038] a dependency table comprising at least two data sets stored in an ordered manner relative to one another, preferably comprising at least 50 data sets, particularly preferably comprising at least 200 data sets, wherein each data set comprises at least one input variable of the pollution process, particularly the distance travelled by the motor vehicle between the first availability and the second availability and / or the operating time of the motor vehicle before covering the distance travelled between the first availability and the second availability, and / or the driving speed of the motor vehicle, preferably the progression of the driving speed along the route between the first availability and the second availability, and / or a process variable, preferably the humidity, particularly preferably the progression of the humidity along the route between the first availability and the second availability, and / or the temperature in the vicinity of the motor vehicle, particularly preferably the progression of the temperature along the route between the first availability and the second availability, and / or the rainfall, particularly preferably the progression of the rainfall along the route between the first availability and the second availability, and / or the snowfall, particularly preferably the progression of the snowfall along the route between the first availability and the second availability, and / or the vehicle type and / or the coordinates of the motor vehicle, preferably the 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 a soiling process of a surface of a motor vehicle, a system dependency of resource-efficient cleaning, preferably resource-saving cleaning, of at least one surface of a motor vehicle, preferably derived by the method for indirectly deriving system dependencies according to the ninth aspect of the invention,

[0041] To / for

[0042] Preferably according to the tenth aspect of the invention, the expected availability at the distance to be covered or the operating time of the motor vehicle is determined,

[0043] and / or

[0044] Preferably according to the eleventh aspect of the invention, determining an expected distance to be covered or an expected operating time of the motor vehicle when the availability threshold is reached,

[0045] and / or

[0046] In particular, the resource requirement of a cleaning process for a surface of a motor vehicle is optimized by applying the method for optimizing the resource requirement for a cleaning process for a surface of a motor vehicle according to the third aspect of the invention,

[0047] and / or

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

[0049] and / or

[0050] Preferably according to the fourteenth aspect of the invention, a 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 to be covered or the operating time of the motor vehicle without exceeding an availability threshold.

[0051] Explain the following terms in more detail:

[0052] First of all, it should be explicitly pointed out that in the context of this patent application, indefinite articles and numbers (such as "one", "two", etc.) should generally be understood as "at least" information, that is, "at least one", "at least two", etc., unless it is clearly obvious from the corresponding context, or it is obvious to a person skilled in the art or it is technically mandatory that only "exactly one", "exactly two", etc. can be meant.

[0053] In the context of this patent application, the term "particularly" should always be understood to mean that the term introduces optional, preferred features. The expression should not be understood as "i.e.".

[0054] A “cleaning method” is a method of cleaning at least one surface or component 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 preferably select a cleaning mode in an automatic cleaning method and, if necessary, be requested to replenish the resources required for the cleaning method.

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

[0056] Particularly preferably, it is also conceivable that the cleaning method can be automatically performed during operation of the vehicle and / or outside of operating hours of the vehicle in order to clean at least one component of the surface of the vehicle and can therefore operate autonomously except for replenishing any required resources.

[0057] Cleaning should be understood as using a cleaning device such as water, air, a cleaning agent and / or a wiping element and / or a mechanical cleaning element and / or a vibration-based cleaning element and / or an ultrasonic-based cleaning element to clean a surface. Specifically, cleaning does not mean achieving an absolutely clean surface, but rather using a cleaning device to reduce contaminants on a surface.

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

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

[0060] The end time of a cleaning process should in particular also be understood to mean the end time of the evaluation phase of the cleaning process, in particular in the case where the evaluation of the cleaning process is also performed during the execution of the cleaning process, the evaluation point and the cleaning process having a common start time, but having any deviating end times, preferably the end time of the evaluation period 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 issue under consideration.

[0061] In particular, it should be taken into account 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 preferably differ only in the end time of the evaluation of the cleaning process.

[0062] A "surface" is a surface element of a motor vehicle. Preferred terms for a surface are the windshield and / or rear window and / or side windows of a motor vehicle. Furthermore, a surface is preferably understood to mean a surface element behind which a sensor is arranged. Another preferred term for a surface is a part of a surface of a motor vehicle that is visible from the outside, specifically also including hidden surfaces, such as parts of a wheel arch lining in the wheel arches of a motor vehicle.

[0063] A surface may also be understood to mean a surface element which is situated in a motor vehicle, preferably in the interior of a motor vehicle and / or in the engine compartment of a motor vehicle.

[0064] "Vehicle" or "motor vehicle" is understood to be a generally wheeled, self-propelled vehicle, which does not operate on tracks and is used for transporting persons or goods.

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

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

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

[0068] “Cleaning fluid dispensing system” means a system designed to provide cleaning fluid onto surfaces to be cleaned on a motor vehicle.

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

[0070] A "nozzle" is a device through which cleaning fluid may exit a cleaning system and which is designed to bring the cleaning fluid into interaction with, preferably operative connection with, a surface to be cleaned.

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

[0072] Preferably, the nozzle comprises an actuation means designed to influence the direction of the cleaning fluid leaving the cleaning fluid dispensing system.

[0073] Preferably, the nozzle comprises second actuation means designed to influence a property of the cleaning fluid leaving the cleaning fluid dispensing system, preferably the velocity 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" which is designed to store cleaning fluid in a motor vehicle. An electric pump is preferably integrated into the cleaning fluid reservoir.

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

[0077] The electronic components of the cleaning system may preferably include an electronic control unit and / or a data processing system. The data processing system may 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 the vehicle.

[0079] The electronic control unit described herein is preferably configured to execute a cleaning method, particularly preferably a cleaning method according to the first aspect of the invention, and / or a method for indirectly deriving system dependencies, preferably of a system behavior of a cleaning system of a motor vehicle, particularly preferably of a system dependency of a system behavior of a cleaning process of a surface of a motor vehicle, particularly preferably a method for indirectly deriving system dependencies according to the second aspect of the invention, and / or a method for indirectly deriving system dependencies of a system behavior of a system component of a cleaning system of a motor vehicle, particularly preferably a method for indirectly deriving system dependencies according to the fifth aspect of the invention, and / or a method for indirectly deriving system dependencies of a system behavior of a soiling process of a surface of a motor vehicle, particularly preferably a method for indirectly deriving system dependencies according to the ninth aspect of the invention, and / or a method for optimizing resource requirements of a cleaning process for a surface of a motor vehicle, particularly preferably a method for optimizing resource requirements according to the first alternative and / or the second alternative of the third aspect of the invention, and / or a method for determining a cleaning strategy for cleaning a surface to be cleaned of a motor vehicle, particularly preferably a method for determining a cleaning strategy according to the fourth aspect of the invention, and / or a method for diagnosing deviations between actual and expected system behaviors of system components of a cleaning system of a motor vehicle, particularly preferably according to the sixth aspect of the invention. and / or using a dependency table and / or a system dependency to determine an expected availability at a distance to be covered or an operating time of a motor vehicle, particularly preferably using a dependency table and / or a system dependency according to the tenth aspect of the invention, and / or using a dependency table and / or a system dependency to determine an expected distance to be covered or an operating time of a motor vehicle when an availability threshold is reached, particularly preferably using a dependency table and / or a system dependency according to the tenth aspect of the invention. preferably using the dependency table and / or the system dependencies according to the eleventh aspect of the invention and / or using the dependency table and / or the system dependencies for optimizing the resource requirements of a cleaning process for a surface of a motor vehicle, particularly preferably using the dependency table and / or the system dependencies according to the twelfth aspect of the invention and / or using the dependency table and / or the system dependencies for determining a cleaning strategy for cleaning the surface to be cleaned of a motor vehicle, particularly preferably using the dependency table and / or the system dependencies according to the thirteenth aspect of the invention and / or using the dependency table and / or the system dependencies for determining a necessary expected availability gain, particularly preferably using the dependency table and / or the system dependencies according to the fourteenth aspect of the invention,and / or using a system dependency derived by a method for indirectly deriving a system dependency for resource-efficient cleaning of at least one surface of a motor vehicle, particularly preferably using a system dependency according to the fifteenth aspect of the invention, and / or using a control quantity setpoint derived by a method for optimizing the resource requirement of a cleaning process for a surface of a motor vehicle, particularly preferably using a control quantity setpoint according to the fifteenth aspect of the invention, for resource-efficient cleaning of at least one surface of a motor vehicle, 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, particularly preferably using a cleaning strategy according to the fifteenth aspect of the invention, and / or as part of a cleaning system according to the sixteenth aspect of the invention, and / or as part of a motor vehicle according to the seventeenth aspect of the invention.

[0080] Furthermore, the electronic control unit is preferably equipped with all structural electronics required to carry out the cleaning method presented here, preferably the cleaning method according to the first aspect of the invention.

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

[0082] A "data processing system" is a combination of electronic components and electronic processing that produces a defined set of outputs for a set of inputs. The inputs and outputs are interpreted as data.

[0083] Preferably, a data processing system is a system that effects organized processing of amounts of data in order to achieve the goal of obtaining information about and / or changing these amounts of data.

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

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

[0086] Preferably, the sensor comprises an electronic data processing unit 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 operably connected to a sensor, preferably 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 measured quantity is the "actual or current measured quantity value" and / or the "current or actual measured quantity value".

[0091] Specifically, sensors are also understood to be virtual sensors. "Virtual sensors" utilize imaging capabilities to qualitatively or quantitatively map the data of one or more recorded measured quantities to a physical or chemical property and / or material composition of the environment. Thus, sensors can be physical or virtual sensors that qualitatively or quantitatively record quantities and / or conditions in the surrounding environment. In other words, virtual sensors use mathematical definitions to determine quantities, specifically measured quantities, controlled quantities, or process quantities.

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

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

[0094] The optical sensor may preferably determine the brightness level, or in other words the light intensity level.

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

[0096] Specifically, the sensors also include temperature sensors, pressure sensors, voltage sensors, current consumption sensors, radar sensors, ultrasonic sensors, flow rate sensors, etc.

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

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

[0099] Preferably, the measured values ​​of the measured quantities can be determined experimentally and / or numerically. In the case of experimental investigations of the measured values ​​of the measured quantities, experimental investigations of the entire motor vehicle, preferably in the laboratory or during normal motor vehicle operation, or experimental investigations of modules or components within the framework of a modular test bench can be considered. In numerical investigations, the measured values ​​of the measured quantities, numerical analyses within the framework of physical models, and / or numerical simulations should be considered, wherein the entire vehicle or modules or components can also be considered individually.

[0100] A measured quantity can also be understood as a quantity representing data, which is also referred to as "data representing the measured quantity." The data is preferably retrievable data, preferably wirelessly available data, preferably the weather in the vicinity and / or along the planned route and / or the current or actual coordinates of the motor vehicle. Furthermore, data such as sensor type, vehicle type, date of last inspection of the sensor and / or cleaning system and / or vehicle, etc. are preferably considered.

[0101] Measured values, measured quantities and measured quantity setpoints are not to be understood as pure scalars or values, but as long as this is technically reasonable, as vectors having a plurality of values ​​for the corresponding dimension of the vector.

[0102] The "vehicle type" is the specific configuration of the vehicle. Specifically, the vehicle type provides information about which surfaces the vehicle includes, how these surfaces are shaped, and which sensors are hidden behind which surfaces.

[0103] The “process value” is the current value of the “process variable”. The “process variable setpoint” is the default value of the “process variable”. Preferably, a process variable is understood to be a variable that is suitable for influencing the cleaning process and the cleaning result but is itself influenced.

[0104] Preferably, the process variable and / or the process variable setpoint and / or the process value is not a pure scalar or scalar value, but rather a vector having a plurality of values ​​for the respective dimension of the vector.

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

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

[0107] Preferably, the process variable is an ambient process variable, which relates to the surrounding environment, preferably the environment around the motor vehicle. Examples of ambient process variables are the ambient temperature near the motor vehicle, the humidity near the motor vehicle, the air pressure near the motor vehicle, the current amount of rain and / or snowfall, etc.

[0108] In this context, process variables are 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] Process variables are preferably variables which occur in or around the cleaning system and which can be influenced at least indirectly by input variables.

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

[0111] The "controlled amount set point" is a default value for the actuator, which is set to adjust the "controlled amount." The current value of the controlled amount is the "actual controlled amount value."

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

[0113] Preferably, the controlled variable and / or the controlled variable setpoint and / or the controlled value is not a pure scalar or scalar value, but a vector having a plurality of values ​​for the respective dimension of the vector.

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

[0115] Here, the controlled quantity is understood to be the type of cleaning fluid, specifically 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 when leaving 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] Particularly preferably, the control of the control variable is carried out with the goal of achieving a cleanliness of at least one surface of the motor vehicle, preferably with the goal of being resource-efficient, preferably with the goal of saving resources.

[0117] Preferably, the control of the controlled variable pursues a multi-criteria objective, wherein the Pareto-optimal objective is achieved with the aim of resource-efficient, particularly preferably resource-saving, cleaning of at least one surface of the motor vehicle, preferably under one or more boundary conditions.

[0118] The "availability" of a technical system is a measure of the extent to which the system can perform its task.

[0119] According to a conceivable variant, availability specifies whether the system can fulfill its task with the aid of two acceptable states.

[0120] Preferably, the surface in the first state is not too dirty from the point of view of the sensor and / or from the point of view of whether the driver of the motor vehicle has completed his task, whereas the surface in the second state is too dirty compared to the surface.

[0121] According to a preferred variant, the availability also specifies characteristic values ​​according to which the system can fulfill the task.

[0122] Particularly preferably, the availability can assume a value within a range that includes a certain interval, wherein reaching one interval limit indicates that the system can fully meet its requirements, while reaching another interval limit indicates that the system no longer meets its requirements.

[0123] If the availability value ranges between the interval limits, the system can still meet its requirements, but not under more difficult conditions. Specifically, the availability value reflects the degree of contamination of a surface of the motor vehicle, preferably a surface, preferably a sensor, particularly preferably an optical sensor and / or a driver of the motor vehicle.

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

[0125] The availability can also preferably have values ​​outside these interval limits. An availability above an interval limit value at which the associated sensor can fully meet its requirements indicates that the sensor can fully meet its requirements. An availability below an interval limit value at which the associated sensor can no longer meet its requirements indicates that the sensor can no longer fully meet its requirements. In other words, the surface operatively connected to the sensor must then be cleaned using a cleaning process so that the availability can be increased again, in particular to a value at which the sensor can once again perform at least part of its original task, wherein this surface can also be cleaned by passive cleaning processes (such as rain and / or snowfall).

[0126] It should be explicitly pointed out that the usability of a surface is to be understood as meaning the usability of a surface for less severe sensor-impaired operation and less severe restricted vision for the driver of the motor vehicle, preferably in particular the cleanliness of the surface of a windshield and / or rear window, etc.

[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 for the vehicle to be travelled.

[0129] An estimated availability can preferably be determined using an estimation procedure, preferably according to the tenth aspect of the invention, 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 on the driving route of the motor vehicle.

[0130] A “threshold value for availability” is to be understood as a threshold value for availability. Preferably, reaching the threshold value for availability requires that the surface in operative connection with the sensor, whose availability is considered here, be cleaned.

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

[0132] According to the fourteenth aspect of the present invention, it is preferably possible to derive an expected gain in availability, or in other words a necessary expected gain in availability.

[0133] Depending on the circumstances, a “change in availability” may be understood as an “increase in availability” and a “loss of availability.” In any case, a change in availability is understood as a change in the availability of sensors operatively connected to a surface.

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

[0135] Preferably, resources are understood herein as things that can be used to clean the vehicle surface. Specifically, cleaning fluid and / or detergent and / or energy and / or wiping elements should be considered herein, preferably wiping elements that can be replaced as needed.

[0136] “Resource requirements” are to be understood as the need for resources required for a cleaning process, in particular for a cleaning process with defined control quantity set points.

[0137] "Resource-efficient cleaning" means optimizing the cleaning of the surface to be cleaned in a way that takes into account the ratio of cleaning benefit to cleaning effort. In other words, a resource-efficient cleaning method requires selecting the control amount for the cleaning process based on the fact that the maximum cleaning success can be achieved with the minimum effort.

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

[0139] “Resource-saving cleaning” is to be understood as meaning the optimization of the cleaning of the surfaces to be cleaned according to the most important cleaning target to be achieved. Preferably, the cleaning target can be that a defined number of safety functions of the motor vehicle do not fail due to surface contamination, in particular due to contamination of sensor surfaces or impairment of sensor functionality due to contamination. A preferred cleaning target can also be that the level of autonomy of the motor vehicle does not have to be compromised due to surface contamination, in particular due to contamination of sensor surfaces or impairment of sensor functionality due to 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 invention.

[0141] “Control” is understood to mean the monitoring and possible adjustment of input variables in order to achieve a target, wherein the adjustment of the input variables takes place in particular in response to the occurrence of disturbance variables.

[0142] The "disturbance" is an output value that deviates from the expected output value.

[0143] Preferably, the interference quantity is availability.

[0144] Preferably, controlling means controlling a quantity setpoint to achieve a certain goal, in particular specification of a cleaning method for performing resource-efficient cleaning, preferably resource-saving cleaning, of at least one surface of a motor vehicle.

[0145] Preferably, controlling is understood as performing a cleaning method, preferably performing a cleaning method according to the first aspect of the invention.

[0146] The term "regulation" refers to the automatic interaction between the continuous acquisition of measured quantities and a control system that is dependent on the norms of the measured quantities. In particular, a continuous comparison of the measured quantities with the norms of the measured quantities is performed.

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

[0148] An active operating situation 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 a distance between a starting point and a planned end point.

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

[0150] A "system" is understood as an entity of connected elements forming a common whole through relationships, connections, interrelationships and / or interactions.

[0151] "System behavior" is understood as an observable change in the state or state quantity of the system. Preferably, such an observable change in the state or state quantity of the system occurs as a function of a change in an input quantity.

[0152] "Dependency," particularly "system dependency," describes the dependence of one thing on another, preferably the dependence of a system's output on its input. By changing one thing, a causal change in another can be achieved. Functional dependencies in the mathematical sense are not necessary in the context of system dependencies, but are possible.

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

[0154] It should be explicitly pointed out that system dependencies are to be understood not only as dependencies between purely scalar values ​​of input quantities and purely scalar values ​​of output quantities, but, if applicable, also as multidimensional dependencies between corresponding numbers of input quantities with corresponding associated values ​​considered for the system dependencies and output quantities with corresponding associated values ​​that depend on the input quantities.

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

[0156] Preferably, the experience about the system behavior is based on a single recorded cleaning process, which is preferably collected under laboratory conditions and / or on a real motor vehicle and / or during real motor vehicle operation and / or based on a numerical model that should represent the system behavior under consideration.

[0157] The dependency table can therefore facilitate the reuse of already recorded experience at a later point in time, in particular by selecting the associated input variables from a list of data sets within the dependency table depending on the output variable to be achieved.

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

[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 invention, the data sets contained in the dependency table can be used as data points for deriving system dependencies.

[0160] An "input quantity" is defined as a quantity that contributes to the occurrence of a targeted intervention in a control or regulation system of a system, preferably a cleaning system. Its instantaneous value is the "input quantity value".

[0161] Preferably, input quantities should not be understood as purely scalar or numerical quantities, but whenever this is technically reasonable, input quantity values ​​and input quantities should be understood as vector input quantities having a number of values ​​corresponding to the dimensions of the vector input quantity.

[0162] Controlled variables and / or data representing measured variables, particularly preferably the weather in the vicinity of the motor vehicle and / or on the planned route and / or the current coordinates, are preferably input variables.

[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 a default value of the control system.

[0164] Preferably, the input quantity comprises 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 at the corresponding position of the pre-planned route of the motor vehicle, in particular humidity and / or solar radiation and / or temperature and / or rainfall and / or snowfall.

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

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

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

[0168] Preferably, input quantities are understood to include but are not limited to properties of the spray pattern, in particular an oscillating spray pattern and / or a continuous spray pattern and / or a pulsed spray pattern and / or an alignment of the spray or spray pattern with the surface to be cleaned.

[0169] "Output" is the quantity produced by a system, especially a cleaning system. Its instantaneous value is the "output value".

[0170] Preferably, output quantities should not be understood as purely scalar or numerical values, but whenever this is technically reasonable, output quantity values ​​and output quantities should be understood as vector output quantities having a number of values ​​for the respective dimensions of the vector output quantity.

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

[0172] System-related process variables and / or resource requirements and / or availability for the cleaning process, preferably the availability of the sensor surface and / or the availability of surfaces such as windshields and / or rear windows, preferably the cleanliness of the surfaces, are preferably output variables.

[0173] A "data acquisition system" is used to record physical quantities. Depending on the sensors used, it may preferably have an analog-to-digital converter and a measured quantity memory or data memory. Preferably, the data acquisition system can be configured to simultaneously record several measured variables.

[0174] An "electronic data processing and evaluation unit" is an electronic unit that processes data in an organized manner with the goal of obtaining information about or modifying such data. Preferably, the data are recorded in a data set, processed by a human or machine according to a specified program, and output as a result.

[0175] A "database" is a system for electronic data management. The primary task of a database is to store large amounts of data efficiently, consistently, and persistently and to provide users and applications with required subsets of the stored data in different, demand-oriented representation types.

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

[0177] Preferably, the database contains system dependencies.

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

[0179] Preferably, the remotely managed database is accessible via wireless data transfer such that data can be received from the remotely managed database and data can be transferred to the remotely managed database.

[0180] Preferably, the database includes functionality that the database itself can manage.

[0181] The database is preferably part of a working memory of the electronic data processing and evaluation unit.

[0182] In particular, it is conceivable that when a new data set is entered, in particular using a dependency table, the database will delete previously existing data sets. Data sets with the largest Euclidean distance from the statistical mean of the other data sets may preferably be deleted. Data sets showing the greatest deviation from systematic dependencies between the data may preferably be deleted.

[0183] A “data set” is understood to be a set of consecutively connected data fields, wherein the data fields preferably comprise input quantity values ​​and / or output quantity values.

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

[0185] An "algorithm" is a clear instruction for solving a problem or class of problems. Preferably, the algorithm consists of a finite number of defined individual steps. The individual steps can thus be implemented in a computer program for execution, but can also be formulated in human language. Preferably, an algorithm supports problem solving because a certain input, preferably a data set, can be converted by the algorithm into a certain output.

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

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

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

[0189] Preferably, the coefficient of determination provides a measure of how well the model replicates the observed outcomes, based on the proportion of the total variation in the outcomes that is explained by the model.

[0190] "Regression analysis" is understood to be a set of statistical procedures used to estimate the relationships between variables. It encompasses several techniques for modeling and analyzing several variables, focusing on the relationship between a dependent variable and one or more independent variables. Preferably, regression analysis helps one understand how the typical value of a dependent variable changes when any one of the independent variables is changed while the others remain fixed.

[0191] Preferably, regression analysis is understood to be one of the following analysis models: linear regression, simple regression, polynomial regression, generalized linear model, binomial regression or nonlinear regression, etc.

[0192] An "optimization process" is understood as the maximization or minimization of a function by systematically selecting input values ​​from within an allowed set and computing the value of the function.

[0193] Self-learning optimization methods are a class of algorithms that can also be categorized under the general term "machine learning." These algorithms are characterized by the fact that they learn from examples and can generalize the learned knowledge. Thus, these algorithms generate knowledge based on experience.

[0194] “Optimization” means any process aimed at finding optimum values, in particular optimum values ​​of input quantities, by maximizing the achievement of an objective, in particular by minimizing or maximizing a corresponding objective function and / or by selecting values ​​of the input quantities that are known to achieve or indicate the best achievement of the objective.

[0195] In particular, it should be explicitly pointed out that optimization does not necessarily imply finding exact optimal values ​​for input quantities.

[0196] “Distance” is understood to be the distance between two points that a motor vehicle has covered, is to cover or is planned to cover.

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

[0198] Preferably, the distance is the quickest connection between the two points that can be covered by a motor vehicle.

[0199] Preferably, route planning to establish distances is performed with the aid of a navigation system.

[0200] The actual availability may be "sufficient to bridge the distance to the next cleaning process" if the actual availability can be used to cover the upcoming or planned distance before the next cleaning process without falling below a predefined availability threshold. In other words, in this case, the available availability is completely 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 associated with the corresponding availability area.

[0201] The “expected distance to be covered by the motor vehicle when the availability threshold is reached” is the expected distance that the motor vehicle can cover before reaching the predefined availability threshold.

[0202] "Operating time" is the duration of a motor vehicle's usage period, which has elapsed or is pending or planned.

[0203] The actual availability may be "sufficient to bridge the operating time to the next cleaning process" if it can be used to cover the pending or planned operating time before the next cleaning process without falling below a predefined availability threshold. In other words, in this case, the available availability is 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] The “expected operating time of the motor vehicle to be covered when the availability threshold is reached” is the expected operating time that the motor vehicle can cover before reaching the predefined availability threshold.

[0205] "Coordinates" are the geographic location of the motor vehicle on the Earth, which may be coordinates already passed, actual or current coordinates, or coordinates on a planned route.

[0206] Preferably, the coordinates can also be understood as a progression of coordinates on a completed or planned route.

[0207] A "cleaning strategy" is a plan of how a cleaning system will behave in every conceivable situation. Therefore, a cleaning strategy completely describes the behavior of a cleaning system.

[0208] Preferably, the cleaning strategy includes which surface to clean, when and with what intensity.

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

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

[0211] "Cleaning mode" or "actual cleaning mode" is the operating mode of the cleaning system. By selecting a cleaning mode, the manufacturer and / or driver of the motor vehicle can influence which driver assistance systems should not be deactivated due to sensor contamination, wherein the selected cleaning mode can also include that no cleaning should occur. This can directly influence the usability of the driver assistance systems.

[0212] Since the cleaning mode determines whether or how many driver assistance systems are to be protected from malfunctions due to excessive contamination caused by cleaning measures, the selection of the cleaning mode also determines the number of "selected sensors" for which the availability threshold should not be insufficient, so that the "selected sensors" can also be indirectly influenced.

[0213] The selected cleaning mode therefore 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 may be one or more cleaning modes, wherein one or more cleaning modes may be selected simultaneously.

[0215] Preferably, the 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 autonomous operation of the motor vehicle is not disabled by contamination of the motor vehicle's sensors.

[0216] Preferably, the second cleaning mode has the meaning "comfortable vehicle operation", which means that the cleaning system takes all necessary cleaning measures to prevent comfortable operation of the motor vehicle from being impaired due to contamination of the motor vehicle's sensors. This includes, in particular, the cleaning system maintaining the functionality of the driver assistance systems distance maintenance, lane keeping, parking assistance, park assist, and / or trailer assist by using the necessary cleaning measures.

[0217] Preferably, the third cleaning mode has the meaning "safest possible motor vehicle operation," which means that the cleaning system takes all necessary cleaning measures to ensure that safe operation of the motor vehicle is not compromised by contamination of the motor vehicle's sensors. This includes, in particular, that the cleaning system maintains the functionality of the driver assistance system 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 which are prescribed by law for the operation of the motor vehicle.

[0219] The cleaning mode “Best Possible Range” is preferably used to achieve the best possible range for the motor vehicle with the available cleaning resources.

[0220] A “system component” is understood to be any component of a cleaning system. It should be explicitly pointed out that a system component can be understood to mean a complete cleaning system as well as individual assemblies of a cleaning system and individual components of a cleaning system.

[0221] In particular, the term system component is used in the context of the diagnosis of a cleaning system. Since each physical component of a cleaning system can also be diagnosed with the aid of at least one diagnostic device, the term "system component" particularly refers to a component or components or a cleaning system that is the subject of observations and / or analyses relevant to the diagnosis.

[0222] Under certain conditions, a "current" can flow in an electrical circuit. Furthermore, an electrical circuit may have consumers, in particular consumers that perform a useful application, preferably in the form of system components. Consumers may have a "power consumption," which represents the energy demand of the consumer.

[0223] Consumers that implement electrical applications require energy to perform their work. Specifically, it is conceivable that, for the same work performed, the consumer may have varying power consumption. This may be due to different operating conditions, in particular different ambient temperatures, and / or aging effects of the consumer.

[0224] Preferably, the current signal indicates information about electric flux, electric transients, electric noise, electric noise or the like.

[0225] The “fluid pressure” is the pressure in a fluid, in particular 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 using a pressure sensor.

[0226] "Operation Time" is the individual operation time of the system components.

[0227] A “fill level signal” is understood to be information which directly describes the value of the fill level in the storage container and indirectly describes the quantity of the stored substance.

[0228] “Reaction time” is usually understood as the period between action and reaction, especially the time between measurement and measurement of effect.

[0229] "Sensing time" is the time during which a signal change can be sensed, specifically the time between the start of a tank level change and the end of a tank level change.

[0230] A “signal of the flow meter” is a piece of information provided by the flow meter, which provides information about the amount of liquid, in particular the amount of cleaning liquid, flowing through the channel within a given unit of time.

[0231] The "signal of the leak sensor" is 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 may comprise a sensor attached to a connector of two fluid channels.

[0232] The “number of actuations” is the number of times a system component has been used. Specifically, the number of pumping operations that have been performed with a pump or the number of heating operations that have been performed with a heater can be considered.

[0233] A "spray pattern" is the pattern that the cleaning fluid leaves on the surface to be cleaned after leaving the wash nozzle.

[0234] A “thermal monitoring signal” is understood to be information provided by a thermal monitoring system, which provides information about the temperature of a surface and / or the heat flow on the surface.

[0235] A “signal of the debris sensor” is understood to be information provided by the debris sensor, which provides information about the amount and / or type of foreign matter in the cleaning system.

[0236] A “check valve signal” is understood to be a piece of information provided by the check valve which indicates the check valve position.

[0237] A “signal of a drip sensor” is understood to be information provided by the drip sensor which indicates the presence of liquid and / or the amount of liquid and / or the intensity of rain and / or the intensity of snow.

[0238] A “signal of a distance sensor” is understood to be information provided by a distance sensor which indicates the distance between the sensor and an object detected by the sensor.

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

[0240] The "actual system behavior" is the observable system behavior of the system components of the cleaning system for a motor vehicle. The actual system behavior can preferably be monitored and / or determined with the aid of a measurement system. The actual system behavior can preferably be described by an actual output variable, which is preferably determined by the measurement system, preferably by a sensor.

[0241] It should be noted that actual output quantities can be understood as both scalar and vector quantities. If the actual output quantity has only one parameter, it is a scalar. If the actual output quantity has several parameters, especially a process whose parameters vary 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 components, preferably using all parameters relevant for the characterization of the system behavior.

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

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

[0245] "Deviation" is the difference between the expected output and the actual output. Therefore, the deviation can also be a scalar or vector. Preferably, the deviation includes the dimension of the actual output.

[0246] In particular, the deviation may comprise a system-typical measurement error. In particular, the magnitude of the system-typical measurement error may vary according to any dimension of the deviation, wherein the magnitude of the measurement error may in particular depend on the measurement system used to determine the output quantity.

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

[0248] The system behavior of the system components of the cleaning system for motor vehicles may be affected by measurement errors and further fluctuations and / or deviations that may lie within expected ranges. These expected non-critical deviations and / or fluctuations may be different for each dimension of the output.

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

[0250] The data series may 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 equidistant temporal distances from each other.

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

[0253] A "step response" is an output signal of a system, in particular an output signal of a system component of a cleaning system, that reacts to a planned change in an input variable. It can advantageously be used to characterize linear, time-invariant systems. The time course of the step response can advantageously be used to draw conclusions about the presence of damping in the system, which can advantageously determine, for example, whether a flow channel for the cleaning fluid is blocked.

[0254] "Drift" is a systematic deviation that varies continuously in one direction.

[0255] Preferably, the drift of the output signal of a system component can be used to indicate 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 to prevent failure of the system component.

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

[0257] It should be clearly pointed out that, like the expected output or actual output or deviation, the upper threshold value and / or the lower threshold value can be a scalar or a vector. Preferably, the upper threshold value and / or the lower threshold value include the dimension of the output.

[0258] Preferably, if the output amount exceeds an upper threshold amount in one dimension or drops below a lower threshold amount in one dimension, this is a non-tolerable deviation.

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

[0260] “Diagnostics” is generally understood as a comparison between observed system behavior and expected system behavior of system components of a cleaning system.

[0261] Specifically, "diagnosing" refers to the process of monitoring an output quantity and determining whether an observed system behavior of a system component deviates from an expected system behavior within an acceptable range, particularly by comparing the output quantity to an upper threshold quantity and / or a lower threshold quantity.

[0262] Likewise, inadmissible deviations from the actual system behavior can preferably be assessed based on percentage limit values ​​that depend on the expected output quantity.

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

[0264] A “diagnostic signal” preferably describes the result of a method for diagnosing the system behavior of a system component of a cleaning system of a motor vehicle.

[0265] The diagnostic signal may in particular indicate that the actual system behavior fully corresponds to the expected system behavior.

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

[0267] A “current diagnostic signal” is understood to be a diagnostic signal that is currently present and for which a solution strategy is being sought.

[0268] A “solving strategy” is understood to be a procedure which, based on available experimental values, is suitable for eliminating deviations between the actual system behavior of system components of the cleaning system and the expected system behavior of these system components.

[0269] A "contamination process" is understood to be the accumulation of contamination and / or pollution on a surface.

[0270] "Pollution status" is understood to mean the current state of pollution and / or apparent pollution.

[0271] A "first availability" is understood to be a first state of availability. A "second availability" is understood to be a second state of availability, wherein time has elapsed between the first availability and the second availability.

[0272] Preferably, the motor vehicle travels 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 increase in the number of driver assistance systems, the number of sensors in vehicles, in particular sensors with optical operating principles, has also increased. In particular, sensors with optically active principles rely on the fact that the surface areas of the motor vehicle to which the sensors, in particular sensors with optically active principles, are actively connected can only contain an upper limit of contamination.

[0275] If the contamination of the part of the motor vehicle surface is above this maximum contamination, the functionality of the sensor may no longer be guaranteed to a sufficiently high degree, wherein the functionality of the driver assistance system is also affected by the contamination conditions.

[0276] As a result, maintenance of the functionality of the driver assistance systems requires cleaning of surfaces that are actively connected to the corresponding sensors that supply data to the driver assistance systems, which also increases with the number of sensors.

[0277] This cleaning work requires sufficient cleaning resources, particularly cleaning fluid and electricity. Consequently, the increased demand for cleaning also increases the demand for cleaning fluid, which must be stored in motor vehicles to clean the relevant surfaces. This results in increased space requirements for the cleaning fluid reservoir and also increases the weight of the motor vehicle.

[0278] The system components require neither additional weight nor additional space.

[0279] To this end, a specific cleaning method is proposed here for resource-efficient, preferably resource-saving, cleaning of at least a portion of a surface of a motor vehicle.

[0280] Resource-efficient cleaning means optimizing the cleaning of the surface to be cleaned in a manner that takes into account the ratio of cleaning effort to cleaning costs. In other words, resource-efficient cleaning requires selecting the control variables for the cleaning process in such a way that a maximum degree of cleaning success is achieved with a minimum amount of effort, wherein the control variable setpoint at least indirectly determines the amount of resources required by the cleaning process to clean the surface.

[0281] Resource-saving cleaning is to be understood as meaning the optimization of the cleaning of the surfaces to be cleaned according to the most important cleaning target to be achieved. Preferably, the cleaning target can be that a defined number of safety functions of the motor vehicle do not fail due to surface contamination, in particular due to contamination of sensor surfaces or impairment of sensor functionality due to contamination. A preferred cleaning target can also be that the level of autonomy of the motor vehicle does not have to be compromised due to surface contamination, in particular due to contamination of sensor surfaces or impairment of sensor functionality due to contamination.

[0282] The cleaning method proposed here uses a cleaning system of a motor vehicle and plans and / or optimizes and / or executes individual cleaning processes, wherein each individual cleaning process involves cleaning an individual partial surface of the motor vehicle by using a cleaning device, in particular a cleaning fluid or the like.

[0283] Each cleaning process also includes a time span for executing the cleaning process, wherein the cleaning process includes a start time and an end time of the time span.

[0284] The cleaning system comprises an electronic control unit, a cleaning fluid distribution 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 proposed here, the cleaning success is recorded at least partially automatically, since the sensor in active connection with the surface to be cleaned is preferably capable of 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 in active connection with the sensor.

[0286] Furthermore, it is proposed that the cleaning system has access to or has available information about the availability of sensors and, therefore, about the cleaning status of the surface to be cleaned to which the sensors are in active connection.

[0287] Furthermore, the sensors can be arranged to detect process variables, 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 or be connected to additional sensors that provide measured variables, in particular process variables and / or control variables, for the cleaning system. Thus, temperature or rainfall, for example, can also be made available to the cleaning system via other sensors. This also includes transmitting the 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 may also be provided with coordinates of the motor vehicle and / or control values ​​of the control quantity.

[0290] In particular, consideration should be given to a cleaning method which uses information about the system behavior of the cleaning system and / or which itself can provide this information, in particular with the aid of a dependency table and / or system dependencies, in particular with the aid of a dependency table and / or system dependencies according to the second aspect of the invention.

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

[0292] Furthermore, a cleaning method is proposed which uses a control quantity setpoint, particularly preferably a control quantity setpoint derived by the method according to the third aspect of the invention, to control resource-efficient cleaning, preferably resource-saving cleaning.

[0293] It will be appreciated that the advantages of the controlled quantity set points according to the third aspect of the invention, as described therein, directly extend to the cleaning method according to the first aspect of the invention applying such controlled quantity set points.

[0294] Furthermore, a cleaning method is proposed, which uses a cleaning strategy, particularly preferably a cleaning strategy derived by the method according to the fourth aspect of the present invention, to control the resource-efficient cleaning, preferably the resource-saving cleaning.

[0295] It will be appreciated that the advantages of the cleaning strategy according to the fourth aspect of the invention, as described therein, directly extend to the cleaning method according to the first aspect of the invention applying such a cleaning strategy.

[0296] In particular, consideration should be given to a cleaning method which uses information about the system behavior of system components of the cleaning system and / or which itself can provide this information, in particular with the aid of a dependency table and / or system dependencies, in particular with the aid of a dependency table and / or system dependencies according to the fifth aspect of the invention.

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

[0298] In particular, consideration should also be given to a cleaning method comprising process steps for diagnosing the system behavior of system components of a cleaning system of a motor vehicle, preferably process steps for diagnosing the system behavior of system components of a cleaning system according to the first alternative of the sixth aspect of the invention.

[0299] It should be understood that the advantages of the method for diagnosing the system behavior of system components of a cleaning system according to the first alternative of the sixth aspect of the invention, as described in the first alternative of the sixth aspect of the invention, directly extend to a cleaning method comprising process steps for diagnosing the system behavior of system components of a cleaning system of a motor vehicle according to the first aspect of the invention.

[0300] In particular, consideration should also be given to a cleaning method comprising process steps for diagnosing deviations between actual system behavior and expected system behavior of system components of a cleaning system of a motor vehicle, preferably process steps for diagnosing deviations between actual system behavior and expected system behavior of system components of a cleaning system of a motor vehicle according to the second alternative of the sixth aspect of the invention.

[0301] It should be understood that the advantages of the method for diagnosing deviations between the actual system behavior and the expected system behavior of system components of a cleaning system of a motor vehicle according to the second alternative of the sixth aspect of the invention, as described in the second alternative of the sixth aspect of the invention, directly extend to a cleaning method comprising process steps for diagnosing deviations between the actual system behavior and the expected system behavior of system components of a cleaning system of a motor vehicle according to the first aspect of the invention.

[0302] A cleaning method is also proposed, which comprises a process step for selecting a solution strategy, preferably a process step for selecting a solution strategy according to the seventh aspect of the invention.

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

[0304] Furthermore, a cleaning method shall be considered, which comprises process steps for using a selected solution strategy, preferably process steps for using a selected solution strategy according to the eighth aspect of the present invention.

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

[0306] In particular, consideration should be given to a cleaning method which uses information about the system behaviour of the contamination process on the surface of a motor vehicle and / or which itself can provide this information, in particular with the aid of a dependency table and / or system dependencies, in particular with the aid of a dependency table and / or system dependencies according to the ninth aspect of the invention.

[0307] It should be understood that, as described in the ninth aspect of the present invention, the advantages of the dependency table and / or system dependencies according to the ninth aspect of the present invention directly extend to the cleaning method according to the first aspect of the present invention, which applies the dependency table and / or system dependencies according to the ninth aspect of the present invention and / or executes the program for deriving the dependency table and / or system dependencies according to the ninth aspect.

[0308] In particular, in the cleaning method proposed herein, consideration should be given to using the dependency table and / or system dependencies according to the ninth aspect of the invention to preferably determine the expected availability at the distance to be covered or the operating time of the motor vehicle according to the tenth aspect of the invention, and / or preferably determine the expected distance to be covered or the expected operating time of the motor vehicle when an availability threshold is reached according to the eleventh aspect of the invention, and / or for optimizing the resource requirements of the cleaning process for the surfaces of the motor vehicle, in particular by applying the method for optimizing the resource requirements of the cleaning process for the surfaces of the motor vehicle according to the third aspect of the invention, and / or determine the cleaning strategy for cleaning the surfaces to be cleaned of the motor vehicle, in particular by applying the method for determining a cleaning strategy for cleaning the surfaces to be cleaned of the motor vehicle according to the fourth aspect of the invention, and / or preferably determine the necessary expected availability gain according to the fourteenth aspect of the invention, wherein the sum of the actual availability and the necessary expected availability gain is sufficient to achieve the distance or operating time that the motor vehicle will still cover in a manner that does not exceed the availability threshold.

[0309] It will be appreciated that the advantages of using the dependency table and / or system dependencies according to the ninth aspect of the invention for determining, preferably according to the tenth aspect, the expected availability at the distance to be covered or the operating time of the motor vehicle and / or preferably according to the eleventh aspect, the expected distance to be covered or the expected operating time of the motor vehicle when an availability threshold is reached and / or for optimizing the resource requirements of the cleaning process for the surfaces of the motor vehicle, in particular by applying the method for optimizing the resource requirements of the cleaning process for the surfaces of the motor vehicle according to the third aspect of the invention and / or for determining, in particular by applying the method for determining a cleaning strategy for cleaning the surfaces to be cleaned of the motor vehicle according to the fourth aspect of the invention and / or for determining, preferably according to the fourteenth aspect, 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 that the motor vehicle will still cover 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 invention) extend directly to the cleaning method according to the first aspect of the invention using such dependency tables and / or such system dependencies as described above.

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

[0311] In this context, it is now specifically stated that the cleaning method should be carried out in a defined manner.

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

[0313] The cleaning method should be adjusted to the measured quantity, in particular to the availability of sensors, the surfaces of which are actively connected to the sensor and are currently being cleaned by means of a cleaning process as part of the cleaning method.

[0314] In other words, it is specifically proposed to regulate each individual cleaning process carried out within the scope of the cleaning method based on the availability of associated sensors.

[0315] The advantage is that, by means of the feedback of information about the current cleaning status, in particular by means of the availability of associated sensors, deviations in the cleaning result can be reacted to in a situation-dependent manner.

[0316] This allows the active cleaning process to be interrupted earlier than planned, thus saving additional resources and preventing over-cleaning of the surface to be cleaned.

[0317] Furthermore, it can advantageously be achieved that a cleaning process that is less efficient than expected can be carried out for longer than planned, wherein a resource-optimal cleaning result can advantageously be achieved by an overall evaluation, and even if additional resources must 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 a sensor is reached, preferably the sensor being in active connection with the respective surface to be cleaned by the cleaning process if the surface is not currently excluded from cleaning by means of the cleaning strategy.

[0319] It is proposed here that a cleaning process, in particular a cleaning process preplanned 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 value for the availability of a sensor is reached.

[0320] In this way, it is advantageously achieved that resources for cleaning can be saved, since the cleaning process is never started 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 a predefined threshold value for the availability of the sensor or is close to a predefined threshold value for the availability of the sensor.

[0322] This is particularly advantageous in that the cleaning method can initiate a 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 preferably be considered that the cleaning method described herein is applied to all surfaces that are actively connected to sensors and / or to surfaces that are actively connected to sensors required / selected according to the current cleaning mode and / or to surfaces that are actively connected to sensors required / selected according to a preselected future cleaning mode.

[0324] Advantageously, the cleaning method forces a change of cleaning mode if achieving the planned route is not practical with the currently selected cleaning mode.

[0325] If the pre-planned destination can no longer be reached using the pre-selected cleaning mode, it is proposed to change the cleaning mode in such a way that a new cleaning mode can still be used to execute the pre-planned route without having to change the cleaning mode further, wherein a cleaning mode can be selected that enables the driver to have the most comfortable possible driving experience influenced by the above-mentioned conditions.

[0326] This has the advantage of allowing the driver to reach the planned destination using available cleaning resources under conditions most comfortable for the driver, without having to replenish cleaning resources during maintenance.

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

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

[0329] A reserve strategy is proposed here as a last-minute measure, in which, in the event that achieving the planned destination without service maintenance is jeopardized and the cleaning mode is therefore not adapted to a lower level of cleaning resource consumption at an early stage, the cleaning mode is changed by the cleaning system to such an extent that only the sensors absolutely necessary for manual driving remain sufficiently available.

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

[0331] This has the advantage that the driver is only forced to intervene further 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, which are only sometimes in active connection with unnecessary sensors, with a spray of cleaning fluid.

[0333] This advantageously allows surfaces that are not actively connected to one of the necessary sensors to remain dry, thereby advantageously preventing the accumulation of contaminants present on these surfaces. This advantageously allows alternative cleaning processes, aimed at direct surface cleaning, to be implemented with fewer cleaning resources, since it is not necessary to remove encrusted layers of dirt in a short time, but rather already soaked or pre-soaked dirt.

[0334] In other words, a cleaning process is specifically not proposed here which aims to clean the surface immediately, but rather a cleaning process which makes it easier for a subsequent cleaning process which aims to clean the surface immediately to achieve better cleaning results, in particular a higher usability gain, with less resource expenditure.

[0335] A more effective cleaning process can be achieved in combination.

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

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

[0338] A cleaning method is proposed which comprises a cleaning process designed to wet the surface to be cleaned.

[0339] The cleaning method should preferably comprise two cleaning processes, wherein the first cleaning process from a time point of view is designed to wet only the surface so that any encrusted dirt on the surface to be cleaned is softened. The advantage is that the contaminants are more easily dissolved in the subsequent cleaning process.

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

[0341] Furthermore, it is specifically contemplated that a plurality of cleaning processes, each of which is intended to wet the surface to be cleaned, may be performed before the cleaning process provided for cleaning the surface to be cleaned. These cleaning processes provided for wetting the surface may occur during active and / or passive operating states of the motor vehicle.

[0342] In this way, drying of dirt on the surface to be cleaned can be advantageously prevented.

[0343] It is therefore particularly conceivable that the surface to be cleaned of the motor vehicle can also be wetted by means of a cleaning process when the vehicle is parked.

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

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

[0346] In an optional embodiment, the cleaning method comprises a cleaning process adapted to be initiated when operating conditions of the motor vehicle change.

[0347] It is proposed here that the cleaning method is adapted to start the cleaning process when the operating conditions of the motor vehicle change.

[0348] Preferably, it should be taken into account that the cleaning method starts the cleaning process when the motor vehicle is started (i.e. when transitioning from a passive operating state to an active operating state of the motor vehicle), so that the availability of the sensor at the beginning of the journey can be improved, in particular in such a way that the sensor achieves minimal availability for functional sensor operation.

[0349] Furthermore, it should also be considered that cleaning methods that change cleaning modes by initiating a cleaning process are designed to achieve minimum availability of functional sensor operation for all sensors required in the newly selected cleaning mode.

[0350] This has the advantage that the cleaning method can react in a situation-dependent manner to changes in the operating state of the motor vehicle.

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

[0352] According to a second aspect of the invention, the object is to achieve cleaning of at least one surface of a motor vehicle, preferably resource-efficient cleaning, particularly preferably resource-saving cleaning, by a method for indirectly deriving system dependencies of the system behavior of a cleaning system of a motor vehicle, in particular of a cleaning process of a surface of a motor vehicle, wherein output variables depend on input variables by means of the system behavior of the system, the method comprising the following steps:

[0353] - determining an input variable 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 parameter and the second parameter in an ordered manner relative to each other as a data set of a dependency table in a database;

[0357] - deriving a system dependency between the first parameter and the second parameter from at least two data sets of a dependency table stored in a 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 system dependency from the data sets by means of an algorithm; and

[0358] The derived system dependencies are preferably stored in a database and / or in an electronic data processing and evaluation unit and / or in an electronic control unit.

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

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

[0361] The surface superimposed on the sensor is defined in particular as the outermost surface of the motor vehicle covering the sensor, this outermost surface being in particular the windshield, the rear window, the camera lens and / or the sensor cover.

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

[0363] This brings into focus the need for new cleaning strategies that should enable resource-efficient cleaning, preferably resource-saving cleaning, such that fewer resources have to be provided for the necessary cleaning processes.

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

[0365] Preferably, the cleaning success of the cleaning process can be assessed based on the availability of the sensor before and after the cleaning process.

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

[0367] Furthermore, cleaning success is also affected by the speed at which the motor vehicle is travelling 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 relative to the direction of movement of the motor vehicle.

[0368] Furthermore, there are a large number of conceivable cleaning processes which differ in the selection of correspondingly different control variables.

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

[0370] The resource requirement of a cleaning process can be determined directly or indirectly, inter alia, depending on the control volume of the cleaning process.

[0371] When implementing resource-efficient cleaning, preferably resource-saving cleaning, specific questions arise regarding which control quantities can be used for which vehicle types, which process quantities and which cleaning successes can be achieved with which resource requirements.

[0372] As already explained above, a large number of influencing variables that influence the outcome and resource requirements of the cleaning process can be taken into account, thus increasing the complexity of the problem considered here.

[0373] Recently, it has become increasingly apparent that the multiplicity of possibilities for influencing the cleaning process, due to their complexity and the possible overlap of individual effects with one another, makes the scope within which resource-efficient cleaning lies increasingly intuitively understandable.

[0374] Resource-saving cleaning is more complex to handle in the sense of a resource-optimized cleaning strategy.

[0375] Therefore, not only has the amount of work involved in designing cleaning systems and cleaning strategies increased substantially, but also the resources required have increased, since successful cleaning must be guaranteed while maintaining a certain level of safety, and this goal can be achieved primarily through the use of extended resources.

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

[0377] Obtaining this necessary information is complex and requires a lot of work.

[0378] In contrast to 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 an input variable of the system and an output variable of the system, wherein the output variable depends on the input variable by means of the system behavior of the system.

[0379] Preferably, the input amounts comprise control amounts for the cleaning method.

[0380] Preferably, the input quantities include the pressure of the cleaning fluid and / or the temperature of the cleaning fluid and / or a 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 variable comprises a process variable.

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

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

[0384] Preferably, the proposed system dependency describes the system behavior of a cleaning process for cleaning at least one surface of a motor vehicle.

[0385] Herein a procedure is proposed wherein

[0386] - first, for a discrete cleaning process, an input quantity is determined as a first parameter and an output quantity is determined as a second parameter, a data processing system records the determined first parameter and second parameter and stores them in a database in an ordered manner relative to each other as a single data set for the discrete cleaning process,

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

[0388] It goes without saying that the first part of the procedure, in which the first parameter and the second parameter are recorded, must first be executed several times in order to obtain a large data set for deriving the system dependencies, unless existing data can be used.

[0389] During a cleaning process performed on the vehicle, in particular during normal vehicle operation, a corresponding data set may be collected directly.

[0390] Alternatively, such datasets may be determined and / or derived from experiments in the laboratory.

[0391] In a further variant, it is conceivable to determine the data set with the aid of a numerical model which represents the corresponding purification process.

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

[0393] From these experimental values, the method proposed here can be used to derive the system dependencies proposed here. 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 based on at least 2 data sets, preferably based on at least 50 data sets, further preferably based on at least 200 data sets, particularly preferably based on at least 1000 data sets.

[0395] It should be noted that the above values ​​for the number of data sets should not be understood as strict limitations, but should be able to be exceeded or reduced below them on an engineering scale without departing from the aspects of the present invention. Simply put, these values ​​are intended to provide an indication of the size of the number of data sets proposed herein.

[0396] The system dependencies thus obtained can advantageously be used not only to evaluate and reproduce previously executed cleaning processes, but also to design new cleaning processes based on a systematic analysis of this data, particularly with the goal of further reducing resource requirements. This can be achieved by interpolating between the available data sets. Furthermore, it is conceivable to generate curves from the obtained data sets, in particular using regression methods that establish a continuous and differentiable systematic relationship between the input and output variables of the cleaning process.

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

[0398] Optionally, the output quantity is 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 so 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 dependencies between input quantities and output quantities (preferably resource requirements) developed according to the proposed procedure describe the system behavior of the cleaning system.

[0402] It is therefore concretely conceivable that for each surface to be cleaned a corresponding system dependency is derived, which system dependency takes into account the portion of the control quantity that is effectively connected to the corresponding surface, and wherein the system dependency preferably describes the cleaning success and the resource requirements as a function of the portion of the control quantity and possibly also as a function of the process quantity by means of a continuous and differentiable system-determined curve, which 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, and in particular, the number of surfaces to be cleaned on the vehicle corresponds to the number of derived system dependencies.

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

[0405] This system dependency can be used in various ways. It is particularly conceivable, therefore, to use the comparison of the input variables to find a control variable that allows for particularly resource-efficient cleaning of the surface in question. Furthermore, it is conceivable to specifically look for a control variable that, when comparing the ratio of cleaning success to resource requirements, allows for particularly resource-efficient cleaning of the respective surface.

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

[0407] Preferably, the input comprises a period of applying the cleaning fluid to the surface to be cleaned.

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

[0409] Preferably, the input comprises the time the cleaning device is in use.

[0410] Preferably, the input variables include the type of motor vehicle to be considered for system dependencies.

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

[0412] Preferably, the input quantities include the amount of cleaning fluid used to clean the surface to be cleaned and / or the period during which the cleaning fluid is applied to the surface to be cleaned and / or the cleaning device, in particular a wiping element, used to treat the surface to be cleaned and / or the time during which the cleaning device is used and / or the type of motor vehicle taken into account for system dependencies and / or the amount of cleaning fluid used to soak the surface to be cleaned before it is subsequently treated with the cleaning device and / or the time during which the surface to be cleaned is soaked until it is subsequently treated with the cleaning device.

[0413] The continuous specification of system dependencies leads to the advantageous design of programs and the possibility of checking the robustness of system dependencies. Thus, it is possible to quantify whether system dependencies are regular or have trends with certain probabilities that can be controlled with continuous precision.

[0414] A further advantage of the procedure described here is that a virtually unlimited number of parameters can be stored with 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 their ability to map (n + i)-dimensional system dependencies, particularly when making decisions about the specifications of control variables within their heads. Specifically, with the increasing complexity of the corresponding cleaning systems and the increasing number of measurable influencing variables, operators are now often reaching the natural limits of their understanding. System dependencies are not subject to such limitations and are therefore advantageous.

[0416] According to this, with a suitable implementation of the proposed procedure, complex dependencies between parameters of the procedure can be mapped. This is particularly applicable to dependencies with a large number of related quantities, which can indicate various dependencies with each other.

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

[0418] In particular, it can be recorded or derived with which resource-efficient cleaning an individual surface of a vehicle type can be effectively cleaned under given environmental conditions and a given initial soiling of the respective surface.

[0419] It should be explicitly pointed out that the result of the cleaning process does not necessarily have to be complete cleaning of the surface. In particular, it should be specifically considered that the surface is cleaned to such a small degree that it remains functional for the sensor hidden behind it.

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

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

[0422] Advantageously, the input variable comprises at least one measured variable, preferably a process variable and / or a controlled variable.

[0423] It is recommended here that the input quantity includes the measured quantity.

[0424] If the input variables do not include measured variables, the system dependencies can conceivably also depend on default values ​​for the controlled variables within the control system framework.

[0425] However, by using measured quantities, the accuracy of system dependencies can be advantageously improved.

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

[0427] Furthermore, it is recommended that the input variable include a process variable so that during the cleaning process of the surface to be cleaned of the motor vehicle a system relationship between the output variable and the process variable (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 and thus also used later for optimal cleaning of the corresponding surface.

[0428] This has the advantage that the accuracy of the derived system dependencies can be increased while taking into account a plurality of influencing factors from the area of ​​the controlled and / or process variables.

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

[0430] The speed at which a motor vehicle travels 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 airflow and / or the evaporation of the cleaning fluid on the surface to be cleaned, thereby also influencing the effective exposure time during which the cleaning fluid can dissolve the contaminants.

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

[0432] In a preferred embodiment, the input quantities include humidity, in particular the current humidity in the vicinity of the motor vehicle, and / or temperature in the vicinity of the motor vehicle, in particular the current temperature in the vicinity of the motor vehicle, and / or rainfall, in particular the current rainfall in the vicinity of the motor vehicle, and / or snowfall, in particular the current snowfall in the vicinity of the motor vehicle, and / or coordinates of the motor vehicle.

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

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

[0435] It has also been shown that rain and / or snow may make the cleaning process more resource-efficient. In particular, rain and / or snow may cause the deposited dirt to separate or at least soften, thus making it easier to dissolve, 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 system dependencies, these data can also be taken into account when evaluating the purification process.

[0437] In particular, it is conceivable that current ambient conditions are also taken into account when selecting a cleaning process, in particular a cleaning process specified by a 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, in particular when statistically considering the expected temperature and / or expected humidity and / or expected rainfall and / or expected snowfall, the current coordinates of the vehicle are also taken into account. Thus, it is particularly conceivable that the expected environmental conditions are determined based on the current coordinates of the vehicle, and that an optimal resource-saving and / or resource-efficient cleaning process is selected based on the expected environmental conditions and system 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 resource-efficient, preferably resource-saving, cleaning of surfaces, thereby saving resources and increasing the operating safety of motor vehicles.

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

[0441] The vehicle type provides information about a number of different factors that influence the cleaning process of a portion of a surface of a motor vehicle. These include, in particular, the installation location of the surface to be cleaned and / or the size of the surface to be cleaned and / or the cleaning devices that can be used to clean the surface to be cleaned and / or the expected degree of soiling and / or the expected type of soiling and / or the exposure of the surface to be cleaned to airflow and / or the exposure of the surface to be cleaned to sunlight and / or the number of surfaces to be cleaned.

[0442] Furthermore, the vehicle type provides information about the respective installed functional types of sensors and / or the respective installed sensor types, in particular information about all different functional types and / or sensor types of sensors located on the motor vehicle, including an assignment of locations at which the respective sensors are installed.

[0443] It is recommended to take these influencing factors into account when exporting system dependencies.

[0444] This has the advantage that vehicle-type-dependent influencing factors can be taken into account for the system dependencies and thus can also be applied individually to each vehicle type in the future for resource-efficient recycling.

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

[0446] The usability of a sensor is the amount of information that can ultimately be provided about the degree of contamination of the sensor.

[0447] Particularly preferably, the availability can assume a value within a certain interval, wherein reaching one interval limit indicates that the system can fully meet its requirements, while reaching another interval limit indicates that the system no longer meets its requirements.

[0448] If the range of the availability value is between the interval limits, the system may still meet its requirements, but may not meet its requirements under more difficult conditions. Specifically, the availability value reflects the degree of contamination of surfaces of the motor vehicle, preferably surfaces, preferably surfaces of sensors, particularly preferably surfaces of optical sensors and / or windows through which the driver of the motor vehicle looks, in particular the windshield and / or rear window, and / or the headlights and / or rear headlights.

[0449] It was found that the availability of the sensor before the cleaning process of the surface has an impact on the cleaning success, where the amount of control is the same but the availability is different before the cleaning process.

[0450] The aspects presented here advantageously make it possible to take the availability of sensors into account as an influencing factor for the derived system dependencies.

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

[0452] The aspects of the invention presented here make it possible to determine the cleaning success of a cleaning process, in particular by comparing the availability of the sensor before and after the cleaning process (this 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 cleaning process is completed and the availability immediately before the cleaning process.

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

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

[0456] It should also be taken into account in particular that the selected cleaning process specified by the selection of the control quantity does not necessarily clean the sensor to an upper limit of the determinability of its usability, 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, which are specified by their respective control variables, can be carried out one after another in order to achieve an optimal cleaning with regard to resource efficiency and / or functionality of the sensor and / or safety of the motor vehicle.

[0458] It should be specifically taken into account that such a sequence of cleaning steps has already been defined before the first cleaning process.

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

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

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

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

[0463] In a preferred embodiment, system dependencies are determined with the aid of regression analysis.

[0464] Here, a regression algorithm is proposed as an algorithm to indirectly derive system dependencies.

[0465] Thus, algorithms can advantageously be used which have been tested in a large number of applications and which can be optimally selected and / or adapted according to the system behavior considered therein, so that high-quality system dependencies can be determined.

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

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

[0468] Preferably, the curve is continuous and differentiable, so that it is advantageously possible to determine a control quantity suitable for the requirements of the cleaning process by using the system dependencies in the control range of the control quantity, without this leading to discontinuities in the adjustment range or non-differentiable changes in the influence of changes in the control quantity.

[0469] Assuming a sufficient number of data sets are available, evaluating the coefficient of determination based on the determined data and the curve determined using the regression model provides an indication of the precision of the system dependencies. This advantageously allows for an assessment of the significance of the correlation between the input and output of the cleaning process, as well as the accuracy of the reproduction of existing or recorded data. Furthermore, with a high coefficient of determination, the curve also allows for statements to be made regarding the limits of the available data. For example, it is conceivable that the data could be numerically supplemented and / or extrapolated at the limits of the existing data.

[0470] In an optional embodiment, system dependencies are determined with the aid of an optimization process.

[0471] It is proposed to determine the parameters of the system dependencies using an optimization procedure, in particular a minimization procedure, which minimizes the cumulative deviations of the experimental values ​​considered from the data set of the system dependencies. This advantageously allows the determination of a system dependency that can be derived in an optimal manner (in particular, with the smallest cumulative deviations from the initial empirical values).

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

[0473] Preferably, the system dependencies are determined with the aid of a self-learning optimization method.

[0474] In particular, an algorithm is proposed that uses features of algorithms from the class of machine learning and is thus able to derive systematic dependencies between input and output variables.

[0475] The advantage of this is that the complex task of indirectly deriving system dependencies using self-learning optimization methods does not have to be manually adapted to new conditions. This saves time and money in the indirect derivation of system dependencies.

[0476] Since the optimizer 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] Thus, it is also conceivable to perform optimization under multiple equal objectives and / or boundary conditions (multi-criteria optimization). In particular, it is possible to minimize multiple required resources while maximizing the gain in availability. Specifically, algorithms capable of determining Pareto optima and / or Pareto fronts are considered. In particular, algorithms from the fields of simplex methods and / or evolutionary strategies and / or evolutionary optimization algorithms are proposed for deriving system dependencies.

[0478] Advantageously, data sets from an already existing database are used to derive system dependencies.

[0479] This has the advantage that data from existing databases can also be used to derive the system dependencies. This eliminates the need to first collect experimental values ​​at a specific motor vehicle, transfer them to the database data, and then transfer them to the system dependencies. In this way, existing data and experimental values ​​can be used to ensure straightforward operation of the motor vehicle's cleaning system based on the system dependencies.

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

[0481] Advantageously, it can be achieved that the number of exportable system dependencies increases over time.

[0482] Furthermore, it can advantageously be achieved that the accuracy of the system dependencies can be increased due to the larger number of experimental values ​​known with the aid of the data set.

[0483] In an advantageous embodiment, the new data set replaces the data set that deviates most from the derived system dependencies.

[0484] Specifically, the fact that the empirical value is exchanged with the maximum Euclidean distance to the system dependencies should be considered.

[0485] Advantageously, it can be achieved that the system dependencies become increasingly precise over time, which can be expressed by an increase in the coefficient of determination.

[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 may be advantageously combined with the subject matter of the first aspect of the invention in any combination, either individually or cumulatively.

[0488] According to a first alternative of the third aspect of the invention, the object is solved by a method for optimizing the resource requirement of a cleaning process for a surface of a motor vehicle, wherein a sensor is operatively connected to the surface, wherein the method uses data from a dependency table of the system behavior of a cleaning system of the motor vehicle, preferably of a cleaning process of at least one surface, preferably for resource-efficient cleaning, particularly preferably for resource-saving cleaning, 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 the dependency table of the system behavior of the cleaning system between the system behavior of the 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 for the cleaning process depends on the control quantity, the method comprising the following steps:

[0489] - accessing 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, the 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 this difference to the corresponding resource requirements for each data set of the dependency table;

[0492] - selecting the control volume of the data set that includes the highest value of the ratio; and

[0493] Preferably, the controlled variable is stored as a controlled variable setpoint in a database and / or in an electronic data processing and evaluation unit and / or in an electronic control unit.

[0494] The increasing number of vehicle assistance systems requires an increasing number of sensors to be installed in motor vehicles. Since these sensors primarily detect light signals, they rely on the surface, through which the light signals are detected, being sufficiently clean, and which is operatively connected to the sensor. Cleanliness is defined individually by the ability of each sensor to receive and / or process the corresponding light signal, at least predominantly without interference.

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

[0496] It should therefore be explicitly pointed out that this aspect of the invention may affect not only optical sensors, but all sensors on a motor vehicle, at least those sensors which are in active connection with a surface of the motor vehicle.

[0497] Each cleaning process is associated with resource requirements that the motor vehicle must provide.

[0498] It has hitherto been known to initiate the cleaning process manually, preferably by the driver of the motor vehicle.

[0499] The increase in the number of vehicle assistance systems and the increase in the number of sensors installed in motor vehicles have increased recently, which is why the need to keep resources available has also increased significantly.

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

[0501] An advantageously automatable procedure is now proposed for minimizing the resource consumption for cleaning surfaces actively connected to the relevant sensor, in particular by carrying out each individual cleaning process (which is preferably resource-efficient, in particular resource-saving) so that the resource consumption and thus the resource requirements of 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 a control quantity. The quantity of cleaning fluid applied to the surface to be cleaned can be considered as the respective input quantity or at the same time as the respective control quantity.

[0503] Attention should also preferably be paid to the fact that the cleaning liquid is applied to the surface to be cleaned in several stages, preferably in a first stage a relatively small amount of cleaning liquid is applied, with the aid of which any contaminants can be softened, and in a second stage a second amount of cleaning liquid is applied, with which the softened contaminants can be washed off the surface. The manner in which the cleaning agent is used, in particular the amount of cleaning fluid, has a direct impact on the resource requirements of a single cleaning process.

[0504] It should be noted that this aspect takes into account not only the amount of cleaning fluid required for the cleaning process, but also the amount of energy used for cleaning, the wear of the wiping elements 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 variable, particularly preferably a controlled variable, and within the framework of an output variable, statements can also be made about results of the cleaning process, particularly about the resource requirements used or used in a planned sense, and about the success of the cleaning, particularly preferably with the help of availability.

[0506] Therefore, the system behavior is 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 the input quantity, the size of the surface operatively connected to the sensor and thus to be cleaned may also be taken into account.

[0508] In the context of the input quantity, the location of the surface to be cleaned can also be preferably taken into account. Thus, a difference in resource efficiency, in particular in the preferred resource-saving cleaning method, can be determined by whether the surface to be cleaned is located at the front, side, rear, bottom, or top of the motor vehicle.

[0509] Furthermore, the input variables may also include the type of contamination, in particular whether it is a crusted deposit of dirt and / or dust, a layer of sludge, snow, etc. It should also be remembered that the operating position and operating history of the motor vehicle allow for a statistical prediction of the type of contamination on the surface, in particular in conjunction with a weather forecast. In other words, the range of input variables may also include weather conditions as well as the operating position and / or operating history, which can be assessed using the coordinates of the motor vehicle and, if necessary, other retrievable data, in particular data retrievable from a data network.

[0510] When evaluating the cleaning success of a cleaning process, it may be advantageous to keep in mind that success is considered to be the difference between the usability of the corresponding surface to be cleaned before and after the cleaning process.

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

[0512] If experimental values ​​exist for a plurality of defined cleaning processes, a resource-efficient, particularly preferably resource-saving, cleaning process can be specifically selected based on the available experimental values ​​for the respective contamination situation.

[0513] The corresponding experimental value consists of at least one input variable (in particular a control variable) and at least one output variable (in particular a gain in usability), which can be determined based on the difference between the usability before and after cleaning the surface to be cleaned.

[0514] In this context, it can be specifically considered that the optimal resource efficiency has been achieved based on existing experience, in particular the controlled quantity for the preferred resource-saving cleaning is selected based on the existing soiling situation, in particular the available availability, and the corresponding controlled quantity is reproduced within the framework of the cleaning program. During the reproduction, the controlled quantity or the controlled cleaning process can be specifically taken into account.

[0515] Possible experimental values ​​may preferably consist of experience obtained on motor vehicles, in particular specific motor vehicles, and / or from experience obtained on reference vehicles and / or experience generated on the basis of numerical models and / or experience generated on the basis of laboratory tests.

[0516] The empirical values ​​taken into account for the selection of a resource-efficient, in particular resource-saving, cleaning process preferably relate to corresponding experience gained on the basis of the surface to be cleaned, which still has to be cleaned or whose cleaning at least now has to be assessed.

[0517] When storing 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 first.

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

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

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

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

[0524] The optimal control quantity setpoint corresponds to the control quantity of the empirical value for a defined cleaning process that ensures optimal resource cleaning of the surface to be cleaned according to the proposed procedure. If the corresponding optimal empirical 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 sensor-related surfaces and to generate control quantity set points optimized for the individual surface to be cleaned.

[0526] Preferably, the program can be carried out sequentially for a plurality of surfaces to be cleaned, which has the advantage that a control quantity setpoint can be defined sequentially for each surface to be cleaned of the motor vehicle.

[0527] This can be achieved by following these 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 expected values ​​can advantageously be called up and processed in a next step;

[0529] - deriving for each data set of the dependency table the 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 the gain in availability of each stored empirical value;

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

[0531] - selecting the control volume of the data set showing the highest value of the ratio, wherein the control volume with the highest resource efficiency may be selected based on existing experimental values; and

[0532] The control quantity is preferably stored 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 this specific 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 invention, the object is solved by a method for optimizing the resource requirement of a cleaning process for 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 invention, preferably a dependency of the system behavior of a cleaning process of at least one surface, preferably for resource-efficient cleaning, particularly preferably for resource-saving cleaning, 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 the system behavior of the cleaning system between, 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 for the cleaning process depends on the control quantity,

[0534] The method comprises the following steps:

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

[0536] - deriving the 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 for the process of system dependencies;

[0537] - The difference between the processes that derive the system dependencies and the processes that generate the corresponding resource requirements;

[0538] - selecting the control quantity belonging to the point in the progression of the ratio that includes the highest value of the ratio; and

[0539] Preferably, the controlled variable is stored as a controlled variable setpoint in a database and / or in an electronic data processing and evaluation unit and / or in an electronic control unit.

[0540] According to the above-mentioned first alternative of the third aspect of the invention, discrete experimental values ​​are used for a procedure for optimizing the resource requirements of a cleaning process, preferably for resource-efficient cleaning, particularly preferably for resource-saving cleaning.

[0541] The solution of an input quantity, in particular a control quantity, within the range of possible expressions for 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 for the input quantity.

[0542] In a different manner, it is proposed here to map the system behavior of the cleaning process by means of system dependencies, preferably by means of system dependencies according to the second aspect of the invention.

[0543] Preferably, the system dependency comprises data sets, wherein each data set comprises an input quantity of the cleaning process and an output quantity of the cleaning process. In particular, it is conceivable that the system dependency is represented by a defined number of data sets and a defined distribution over a range of possible input quantities.

[0544] This advantageously allows data sets of system dependencies to be derived from experimental values ​​in such a way that the optimal number of data sets and the optimized distribution of the data sets lead to a range of possible representations of the input quantities in the sense of resource-efficient cleaning, particularly preferably for resource-saving cleaning.

[0545] In the context of system dependencies insofar as they relate to specific data sets defined by input and output quantities, these can also preferably be carried out according to the procedural steps following the first alternative of the third aspect.

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

[0547] Particularly preferably, the system dependency in the form of a curve over the complete definition range of the curve describes the dependency of the at least one input variable on the at least one output variable.

[0548] The range of definition of the curve is preferably at least as large as the range of possible expressions for the input quantities.

[0549] Likewise, in the case where the system dependency is defined by a curve, the system dependency can be considered to include data sets, each of which includes at least one input quantity and at least one output quantity of the cleaning system. In particular, each data set can be read from the curve of the individual data set, for example, by calculating the output quantity of a grid of input quantities.

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

[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 determining a gain in availability.

[0552] The use of the system dependency advantageously enables the use of mathematical methods to determine the extremes of the system behavior when searching for the optimal control variable, in particular if the system dependency is continuous and can be differentiated in the form of a curve.

[0553] Furthermore, this alternative advantageously enables a better optimal value to be determined for the controlled variable set point in comparison with the first alternative of the third aspect of the present invention, so that more resource savings can be advantageously achieved in this comparison.

[0554] This is due, on the one hand, to the fact that by the process of determining the system dependencies, in particular the determination following the second aspect of the invention, measurement inaccuracies and fluctuations in the system behavior can be smoothed, wherein preferably a continuous and therefore stable and differentiable representation of the system dependencies is generated from the discrete description with the aid of discrete experimental values, wherein a greater accuracy of the mapping of the system behavior can be achieved.

[0555] Furthermore, the optimization results can be improved by selecting the best control quantity set points in those regions that are optimal from a mathematical point of view but for which no experimental values ​​are currently available.

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

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

[0558] Preferably, the program can be carried out sequentially for a plurality of surfaces to be cleaned, which has the advantage that a control quantity setpoint can be defined sequentially for each surface to be cleaned of the motor vehicle.

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

[0560] In particular, dependency tables in a database and / or an electronic data processing and evaluation unit and / or an electronic control unit are not accessed, but corresponding system dependencies, in particular system dependencies according to the second aspect of the invention.

[0561] Furthermore, it should be understood that preferably, discrete data points are not used for calculations, but rather corresponding mathematical operations are preferably performed on the entire curve over the entire curve course. This can preferably be done analytically or by means of discretization in defined steps.

[0562] Furthermore, it should be understood that the advantages of the system dependencies are exploited and that the data set is not selected from recorded experimental values, which ensures optimal resource-saving cleaning of the surface to be cleaned, but rather the extreme points in the progression of the system dependencies, at least in the region in which the control variables can be adapted. In particular, it should be understood that by adjusting the control variables, the selected control variable setpoints can be located at the edges of the range.

[0563] It should be explicitly pointed out that the system dependency considered here is not limited to its dimensionality and can have any dimensionality of input quantities and any dimensionality of output quantities.

[0564] Preferably,

[0565] the dependency table and / or the system dependencies include dependencies on process variables, preferably humidity and / or temperature and / or rainfall and / or snowfall in the vicinity of the motor vehicle and / or the coordinates of the motor vehicle; and

[0566] -wherein, before the control variable is selected, the data set taken into account when selecting the control variable from the dependency table and / or the area of ​​the system dependency taken into account when selecting the control variable are first constrained to an area in which the deviation from the corresponding process variable, preferably the current humidity and / or the predicted humidity along the planned journey and / or the current temperature in the vicinity of the motor vehicle and / or the predicted temperature along the planned journey and / or the current rainfall and / or the predicted rainfall along the planned journey and / or the current snowfall and / or the predicted snowfall along the planned journey and / or the coordinates of the motor vehicle and / or the predicted coordinates of the motor vehicle along the planned journey, is less than 20%, preferably a low deviation of less than 10% and particularly preferably a deviation of less than 5%.

[0567] In particular, it is provided here that the optimization of the control variable setpoint, in other words the minimization of the resource requirement for cleaning the individual surfaces to be cleaned of the motor vehicle, also takes into account at least one process variable.

[0568] It goes without saying that the cleaning success of a cleaning process carried out after a long period of light rain is different from that of a cleaning process defined by the same control variables taking into account at least the same previous degree of contamination and the same type of contamination, carried out on a hot summer day with strong sunlight.

[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 when optimizing 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 variables, preferably the process variables involved. The same applies to the use of system dependencies, in particular the system dependencies according to the second aspect of the invention, which also must depend on the process variables, preferably the process variables involved, so that the suggestions here can be taken into account accordingly in the optimization.

[0571] For the purpose of taking this into account within the optimization, it is proposed that the number of empirical values ​​from the dependency table that are taken into account when selecting the optimal control variable set point and / or system dependency range is limited to a range that deviates from the currently prevailing process variable or the process variable to be expected according to the weather forecast during a planned cleaning process by no more than 20%, preferably by less than 10% and particularly preferably by less than 5%.

[0572] By this restriction, it is achieved that no experience is transferred from the cleaning process carried out in the sun to the cleaning to be carried out in the snow. In other words, it is achieved that only experience from the situation that essentially corresponds to the cleaning situation to be carried out is transferred to the corresponding situation.

[0573] In particular, the accuracy of the mapping between the desired optimal selected control variable and the result achieved during the cleaning process can be advantageously increased.

[0574] The process variable is preferably understood to be the weather along the planned route. The decision on the optimal control variable setpoint can also depend on whether weather conditions, particularly rain and / or snowfall, occur along the planned route, which require fewer resources for cleaning. This advantageously allows the total resources required for cleaning to be reduced by including the expected weather conditions in the decision on the control variable setpoint, which can also include the cleaning time. This is also particularly suggested by the inclusion of the process variable.

[0575] It should be noted that the above values ​​for the considered region of the process quantity should not be understood as strict limitations, but should be able to be exceeded or dropped below it on an engineering scale without departing from the aspects of the present invention. Simply put, these values ​​are intended to provide an indication of the magnitude of the process quantity state considered herein.

[0576] Advantageously,

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

[0578] wherein, before the control variable is selected, first the data set considered when selecting the control variable from the dependency table and / or the area of ​​the system dependencies considered when selecting the control variable is restricted to an area that deviates from the actual availability of the sensor and / or the expected availability of the sensor at a point on the planned route by less than 20%, preferably by less than 10% and particularly preferably by less than 5%, in particular by applying the following steps:

[0579] The method for determining the expected availability at a distance to be covered or an operating time of a motor vehicle is applied preferably according to a tenth aspect of the invention.

[0580] It is recommended here to include the availability of sensors in active connection with the surface to be cleaned in the optimization of the control variable setpoint.

[0581] A cleaning process defined by the control volume, as measured by the increase in availability, leads to different cleaning successes in cases of different initial surface contamination. Preferably, a better cleaning result is achieved for a more heavily soiled initial case than for a less heavily soiled surface, wherein in each case a considerable resource requirement is required since cleaning is performed in each case with the same control volume.

[0582] In this respect, contamination at the beginning of the cleaning process may affect the resource efficiency of the cleaning process.

[0583] Taking into account the initial contamination of the surface to be cleaned, in particular the contamination assessed by the availability of the sensor at the start of the cleaning process, is facilitated by the fact that the experimental values ​​stored in the dependency table are primarily dependent on the availability of the sensor at the start of the cleaning process. The same applies to the use of system dependencies, in particular those according to the second aspect of the present invention, which must also depend on the availability of the sensor at the start of the cleaning process, so that this can be taken into account accordingly in the optimization.

[0584] The same applies to the consideration of the sensor availability at the start of the process, which has already been done for the consideration of process variables. Here, too, the range of experimental values ​​and / or the range of system dependencies considered for optimization from the dependency table will be limited to a range that deviates from the actual sensor availability by less than 20%, preferably by less than 10%, and particularly preferably by less than 5%.

[0585] Due to the resulting limitations, it can advantageously be achieved that only experiences from situations that essentially correspond to the upcoming cleaning situation are transferred to these situations.

[0586] In particular, the accuracy of the mapping between the desired optimal selected control variable and the result achieved during the cleaning process can be advantageously increased.

[0587] Furthermore, it should be specifically taken into account here that, during the preliminary planning of an upcoming cleaning process, the expected availability of the sensors during the execution of the cleaning process should be estimated in advance, in particular using the procedure according to the tenth aspect of the invention.

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

[0589] Advantageously, the planning accuracy of the cleaning process can be increased, wherein the resource requirement for cleaning the surface connected to the sensor can also be advantageously reduced.

[0590] It should be noted that the above values ​​for the considered range of sensor availability at the start of the cleaning process should not be understood as strict limits, but should be able to be exceeded or lowered on an engineering scale without departing from the aspects of the present invention. In short, these values ​​are intended to provide an indication of the magnitude of the considered availability of the sensor at the start of the cleaning process proposed herein.

[0591] Optionally,

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

[0593] wherein before selecting the control variable, the data set considered when selecting the control variable from the dependency table and / or the area of ​​the system dependency considered when selecting the control variable are first constrained to an area 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 controlled variable at the start time of the cleaning process is additionally stored together with the selected controlled variable as controlled variable setpoint.

[0595] In contrast to the above, it is now proposed to optimize the cleaning process with regard to its resource efficiency in such a way that during the optimization, the conditions that must be met in order to start the cleaning process are also determined, in particular the availability of the sensors to be implemented 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 proposed here, the pre-planned cleaning process will be started by the cleaning method, in particular by the cleaning method according to the first aspect of the invention.

[0597] The proposed method is made possible by the fact that the experimental values ​​stored in the dependency table are primarily dependent 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 the system dependencies according to the second aspect of the invention, 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 set point, the optimal availability of the sensor at the start time is selected or determined based on the input quantity of the selected optimal experimental value or the optimal point of the system dependency.

[0599] After the sensor operatively connected to the surface to be cleaned already includes an actual availability value, the method can only select an optimal cleaning process, which starts immediately because the resource-optimal cleaning process within the physically possible range is already at the currently reached limit of the sensor's availability, or starts in the future at a starting time with a defined availability of the sensor, because this must first be achieved through 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] The resource requirements for the cleaning process can thus be further reduced in an advantageous manner, since the procedure proposed here selects the most resource-efficient cleaning process, within the framework of which it is still possible.

[0602] In a preferred embodiment, before the control variable is selected, the data sets taken into account when selecting the control variable from the dependency table and / or the region of the system dependencies taken into account when selecting the control variable are first restricted to a region in which the expected availability gain does not exceed 20% and / or until an availability threshold value is reached, preferably not more than 10%, particularly preferably not more than 5%, over the availability that can be used for the current range of the motor vehicle without inadvertently impairing the functionality of the sensor, in particular by the following steps:

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

[0604] In addition to active motor vehicle operation, in particular when a motor vehicle is used to cover a certain distance, a motor vehicle is also exposed to contamination in passive motor vehicle operation when the motor vehicle is parked at a certain time, in particular when the motor vehicle is exposed to the weather without protection.

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

[0606] In other words, possible over-cleaning can be prevented before the active vehicle operation is completed, so as to save advantageous and overall resources for cleaning. The procedure proposed here makes this possible.

[0607] Alternatively, a modification according to another optional embodiment is provided to wet surfaces which are only sometimes in active connection with unnecessary sensors with a spray of cleaning fluid.

[0608] This advantageously allows surfaces that are not actively connected to one of the necessary sensors to remain dry, thereby advantageously preventing the accumulation of contaminants present on these surfaces. This advantageously allows alternative cleaning processes, aimed at direct surface cleaning, to be implemented with fewer cleaning resources, since it is not necessary to remove encrusted layers of dirt in a short time, but rather already soaked or pre-soaked dirt.

[0609] In other words, a cleaning process is specifically not proposed here which aims to clean the surface immediately, but rather a cleaning process which makes it easier for a subsequent cleaning process which aims to clean the surface immediately to achieve better cleaning results, in particular a higher usability gain, with less resource expenditure.

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

[0611] To this end, the range of experimental values ​​from the dependency table or of system behavior relationships mapped by programmatically selectable system dependencies is restricted to a range such that the expected availability gain does not exceed 20% of the availability that can be used for the current range of the motor vehicle without inadvertently impairing the functionality of the sensor and / or until a threshold value of availability is reached, preferably not more than 10%, particularly preferably not more than 5%.

[0612] Preferably, the expected gain in usability of each evaluated cleaning process may be determined by applying the method according to the fourteenth aspect of the invention.

[0613] It can thus advantageously be achieved that the cleaning process selected by the method does not, on the one hand, lead to significant overcleaning of surfaces actively connected to the sensor and, on the other hand, no subsequent 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 surfaces that are actively connected to the sensor can be saved.

[0615] It should be noted that the above values ​​for the considered region of the expected gain in sensor usability due to the cleaning process should not be understood as strictly limiting, but should be able to be exceeded or lowered on an engineering scale without departing from the aspects of the present invention. Simply put, these values ​​are intended to provide an indication of the magnitude of the considered expected gain in sensor usability due to the cleaning process proposed herein.

[0616] The method for optimizing the resource requirements of cleaning processes for motor vehicle surfaces according to claim 1 , characterized in that, before the control variable is selected, the data set taken into account when selecting the control variable from the dependency table and / or the region of the system dependencies taken into account when selecting the control variable are first restricted to regions in which the expected gain in availability is sufficient to bridge the distance or operating time to the next cleaning process without falling below an availability threshold and is no more than 20%, preferably no more than 10%, and particularly preferably no more than 5%, greater than the gain in availability required to bridge the distance or operating time to the next cleaning process without falling below the availability threshold, by the following steps:

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

[0618] In particular applying the method for determining an expected gain in availability, preferably by applying the method according to the fourteenth aspect of the invention,

[0619] Wherein the sum of the current availability and the desired gain in availability is sufficient to achieve the distance to be covered or the operating time of the motor vehicle without exceeding the availability threshold.

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

[0621] In particular, it is conceivable that autonomous motor vehicle operation can be maintained until the next filling station with only minimal use of the cleaning device. Even if the minimally invasive cleaning process proposed here is not optimally resource-efficient in the sense of the highest possible increase in availability with minimal use of cleaning agent, the available resources are still used in the most efficient manner in terms 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 be achieved by first limiting the data set that is taken into account when selecting the control variable from the dependency table and / or the area of ​​the system dependencies that are taken into account when selecting the control variable to areas in which the expected gain in availability is sufficient to bridge the distance or operating time to the next cleaning process without falling below an availability threshold and does not exceed the gain in availability for bridging the distance or operating time to the next cleaning process without falling below an availability threshold by more than 20%, preferably by no more than 10% and particularly preferably by no more than 5%.

[0623] In other words, here, the solution space is limited on two sides.

[0624] It should in particular be borne in mind that before selecting the control variable setpoint, the expected distance to be covered or the expected operating time of the motor vehicle when the availability threshold is reached is preferably determined with the aid of the procedure according to the eleventh aspect of the invention.

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

[0626] This has the advantage that the cleaning process can be selected in such a way that the motor vehicle can optimally achieve the minimum goals defined by the driver using the available resources.

[0627] It should be noted that the above values ​​for the considered region of the expected gain in sensor usability due to the cleaning process should not be understood as strictly limiting, but should be able to be exceeded or lowered on an engineering scale without departing from the aspects of the present invention. Simply put, these values ​​are intended to provide an indication of the magnitude of the considered expected gain in sensor usability due to the cleaning process proposed herein.

[0628] In a preferred embodiment, a first control amount and a second control amount are selected, wherein the respective first control amount set point and the respective second control amount set point define a first cleaning process and a second cleaning process for a series of cleaning processes, the second cleaning process being performed after completion of the first cleaning process.

[0629] In particular, it is proposed here to divide the cleaning process of the surface to be cleaned into two or more individual cleaning processes of a jointly planned sequence.

[0630] The first cleaning process is defined by a first control quantity set point, and the second cleaning process is defined by a second control quantity set point.

[0631] It should also be taken into account that both control quantity setpoints contain conditions for triggering the corresponding 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 present invention. In particular, the temporal distance, spatial distance or realization of defined triggering availability between the individual cleaning processes is taken into account.

[0632] The advantage is that cleaning resources can be saved if several cleaning processes are more resource-efficient than a single cleaning process. Surprisingly, it has been found that this can occur for the corresponding input quantities or some constellations of corresponding input quantities.

[0633] Optionally, the method is performed 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] So far, the procedure has only been described to the extent that the cleaning process to be performed is optimized for only one surface at a time.

[0635] In particular, it is provided that the program is applied to a plurality of surfaces to be cleaned, in particular sequentially or in parallel.

[0636] Advantageously, the control variables are selected with the aid of a multi-criteria optimization procedure.

[0637] In particular, it is proposed here to carry out the selection of the optimal cleaning process with the aid of a multi-criteria optimization program.

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

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

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

[0641] According to the third aspect of the invention, other influencing variables can preferably be taken into account in the resource optimization, which influencing variables are in particular the device type of the sensor, 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.

[0642] Regarding 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, these may also be control quantities.

[0643] It goes without saying that the advantages of system dependencies, in particular system dependencies according to the second aspect of the invention, also apply to the use of system dependencies, in particular the use of system dependencies according to the third aspect of the invention proposed here.

[0644] It should be noted that the subject matter of the third aspect may be advantageously combined with the subject matter of the preceding aspects of the invention, either individually or cumulatively, in any combination.

[0645] According to a fourth aspect of the invention, the object 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 mode, wherein a sensor is operatively connected to the surface to be cleaned,

[0646] Wherein the sensor comprises an actual availability, and wherein the cleaning strategy comprises defining a control quantity set point for a cleaning process of the surface to be cleaned, the method comprises the steps of:

[0647] - preferably checking the actual cleaning mode;

[0648] -Select at least one sensor required for the currently selected cleaning mode;

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

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

[0651] applying a method for optimizing the resource requirements of a cleaning process for a motor vehicle surface, preferably applying a method according to the third aspect of the invention; and

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

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

[0654] A third aspect of the invention describes a procedure for optimizing a cleaning process with respect to resource consumption of a surface to be cleaned to which a sensor is operatively connected.

[0655] A third aspect of the present invention is to provide one or more resource-optimized cleaning processes for one or more surfaces to be cleaned.

[0656] However, the procedure according to the third aspect of the invention does not take into account whether a specific surface connected to the sensor must be completely cleaned, or in other words, whether the availability of the sensor should be increased for the current or planned use of the vehicle by performing a cleaning process, preferably by performing a cleaning process after the first aspect of the invention.

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

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

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

[0660] This advantageously allows saving cleaning resources, in particular because it allows the availability of sensors whose functionality is currently not required to also fall below an availability threshold.

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

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

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

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

[0665] It goes without saying that once the cleaning mode is changed, the cleaning strategy becomes invalid. Once the cleaning mode is changed, 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 invention, or a new cleaning strategy must be determined according to the proposed procedure.

[0666] It should be clearly noted that the cleaning mode may coincide with the driving mode, but this does not have to be the case, which is why these terms are used separately here.

[0667] Preferably, the assignment of the selected sensor can be obtained from an associated 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 suggested cleaning strategy may override the motor vehicle and / or driver's command as a last minute remedial measure to clean surfaces of selected sensors whose availability has reached and / or dropped below an availability threshold.

[0669] Furthermore, it is preferred that the cleaning strategy may provide that it also decides to clean sensors other than the selected sensor, in particular if one of the selected sensors is faulty.

[0670] Preferably, before determining the control quantity setpoint, first the distance and / or operating time that the motor vehicle can still cover is determined according to 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] Applying a method for determining an expected distance to be covered or an expected operating time of a motor vehicle when a threshold value of availability is reached, preferably applying a method according to the eleventh aspect of the invention.

[0672] To date, the vehicle miles achievable with available cleaning resources have not been considered when determining cleaning strategies.

[0673] This is exactly what is being proposed here.

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

[0675] Motor vehicles are contaminated both during active and passive motor vehicle operation. For reasons of resource-optimal cleaning of surfaces of motor vehicles, it is particularly proposed not to over-clean the surfaces, which is characterized by the fact that the surfaces of the motor vehicle are thoroughly cleaned shortly before reaching the target of active motor vehicle use.

[0676] Instead, it is proposed that the cleaning process can pursue the goal of cleaning the surface only to the extent that the usability achieved by the cleaning process is sufficient to achieve the goal of active vehicle operation. For this purpose, the associated control variable setpoint can be determined in particular by means of the method according to the third aspect of the invention.

[0677] Another effect is due to the fact that different cleaning modes require different amounts of cleaning resources. Specifically, 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 intended only to help the driver steer the vehicle but does not allow autonomous vehicle operation.

[0678] Therefore, it is proposed here that

[0679] • according to a step prior to determining the control variable setpoint, preferably by applying the method according to the eleventh aspect, first determining an expected distance and / or an expected operating time that the motor vehicle can still cover as a function of the actual availability of the selected sensor, until the expected availability then reaches a corresponding availability threshold;

[0680] Before determining the control quantity setpoint, according to a further step, the amount of available cleaning resources is checked, in particular using a corresponding sensor, particularly preferably a level sensor or the like;

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

[0682] ● comparing whether sufficient resources are available to meet the resource requirements of this cleaning strategy to the destination; and

[0683] ●If this is not the case, the driver is preferably offered a cleaning mode with which he can reach his destination with the available resources, and / or the driver is requested to refill the corresponding resources, the cleaning strategies offered being determined by using the optional cleaning modes in descending order according to the resource requirements for determining the cleaning strategy until a cleaning strategy is found with which the motor vehicle can still reach its destination without one of the selected sensors having an availability below an associated availability threshold.

[0684] In this way, it can advantageously be achieved that, in the event that the necessary resources according to the selected cleaning mode are insufficient to reach the destination, the driver of the motor vehicle can decide whether he wishes to perform a service stop to refill the required resources, thereby making it possible to maintain the currently selected cleaning mode, or whether he wishes to dispense with the availability of driver assistance systems and thus, if necessary, reach the destination even faster.

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

[0686] Different cleaning modes may have different error tolerances for a selected sensor.

[0687] In particular, it can be specifically envisaged that the fault tolerance of selected sensors in a cleaning mode provided for fully autonomous motor vehicle operation is lower than the fault tolerance of selected sensors in a cleaning mode provided for motor vehicle operation not allowing fully autonomous motor vehicle operation.

[0688] It is proposed that the availability threshold of each sensor may have different values ​​for different cleaning modes.

[0689] In this way, it is advantageously possible to save cleaning resources by using different availability thresholds for different cleaning modes.

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

[0691] It is proposed that the cleaning mode can be read out from the electronic control unit. This makes it advantageous to define the cleaning mode in the electronic control unit and to use it within the scope of the cleaning method, in particular within the scope of the cleaning method according to the first aspect of the invention, and within the scope of the method for determining a cleaning strategy, in particular within the scope of the method according to the fourth aspect of the invention.

[0692] Furthermore, it can advantageously be achieved that a cleaning mode 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 surface, in particular since these are safety-relevant aspects which can also fall within the scope of the manufacturer's liability in the event of a malfunction.

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

[0694] Explain the following terms in more detail:

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

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

[0697] According to a preferred variation of this embodiment, the cleaning mode is arranged to enable fully autonomous motor vehicle operation, wherein every surface operatively connected to a sensor associated with the fully autonomous motor vehicle operation is to be cleaned.

[0698] It is proposed here that this cleaning mode be provided for fully autonomous motor vehicle operation.

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

[0700] In other words, this may lead to a situation where, if such a motor vehicle falls below an availability threshold, the motor vehicle has to cease 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 sensor must be prevented from falling below an associated availability threshold. This also applies to the cleaning method, in particular the objectives of the cleaning method according to the first aspect of the invention, and therefore also to the objectives of the method proposed here for determining a cleaning strategy.

[0702] According to another preferred variation of this embodiment, the cleaning mode is set to enable a designated driver of the motor vehicle to comfortably operate the motor vehicle, wherein each surface operatively connected to a sensor associated with comfortable autonomous motor vehicle operation is to be cleaned.

[0703] The cleaning mode proposed here relates to 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 completely autonomous motor vehicle operation, but rather motor vehicle operation that is characterized by the fact that the driver of the motor vehicle largely controls the motor vehicle himself.

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

[0706] In other words, it is proposed here that the cleaning system ensures the availability of all selected sensors in connection with a cleaning mode which is arranged to enable comfortable operation of the motor vehicle with a suitable cleaning method, in particular with a cleaning method according to the first aspect of the invention.

[0707] According to another preferred variant of this embodiment, the cleaning mode is arranged to enable a designated driver of the motor vehicle to carry out the safest possible motor vehicle operation, wherein each surface operatively connected to a sensor associated with the safest possible autonomous motor vehicle operation is to be cleaned.

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

[0709] According to another preferred variant of this embodiment, the cleaning mode is arranged to enable the motor vehicle to have the best possible range, wherein each surface operatively connected to a sensor associated with autonomous motor vehicle operation with the best possible range is to be cleaned.

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

[0711] This is preferably made possible by deactivating all driver assistance systems that are not required by law for active vehicle operation, so that the associated sensors can also be used 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] The method proposed here is to create a cleaning strategy for multiple surfaces to be cleaned. This can be done serially or in parallel.

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

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

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

[0717] This enables finding a control quantity set point, preferably based on current or expected weather conditions on a pre-planned route, which provides a better relationship between the increase in availability of individually selected sensors and the cleaning resources used than a control quantity set point that does not take the measured quantity into account.

[0718] In detail, what has been accomplished under the third aspect of the present invention applies here mutatis mutandis.

[0719] Preferably, the step of determining the control variable 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 for the surface intended to be cleaned. In detail, this applies mutatis mutandis to what has been done under the second aspect of the invention.

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

[0722] Preferably, if the respective availability falls below a corresponding availability threshold, cleaning of the selected sensor by means of a predetermined reserve cleaning process is proposed as a last-minute remedial measure.

[0723] It should be noted that the subject matter of the fourth aspect may be advantageously combined with the subject matter of the preceding aspects of the invention, either individually or cumulatively, in any combination.

[0724] According to a fifth aspect of the invention, the object is achieved by a method for indirectly deriving system dependencies of a system behavior of system components of a cleaning system of a motor vehicle, wherein the cleaning system is adapted to clean at least one surface of the motor vehicle by means of a cleaning process, the cleaning process preferably being adapted for resource-efficient cleaning, particularly preferably for resource-saving cleaning, wherein output quantities depend on input quantities by means of the system behavior of the system, the method comprising the following steps:

[0725] - determining an input variable 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] - 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;

[0728] - storing the determined first parameter and the second parameter in an ordered manner relative to each other as a data set of a dependency table in a database;

[0729] - deriving the system dependency between the first parameter and the second parameter from at least two data sets of a dependency table stored in a 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 system dependency from the data sets of the dependency table by means of an algorithm; and

[0730] The derived system dependencies are preferably stored in a database and / or in an electronic data processing and evaluation unit and / or in an electronic control unit.

[0731] Also due to the increasing importance of driver assistance systems which depend on information provided by sensors, motor vehicles are increasingly being equipped with an increasing number of sensors.

[0732] Most of these sensors rely on the functionality of the surface to which the individual sensors are actively connected to avoid excessive contamination.

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

[0734] Therefore, the complexity of cleaning systems for motor vehicles is constantly increasing. Specifically, the number of nozzles and fluid connections is increasing. This is accompanied by a steady increase in the number and complexity of valve devices, cleaning fluid pumps and cleaning fluid reservoirs.

[0735] As sensors are increasing the automation of the vehicle as a whole, the degree of automation in cleaning systems for motor vehicles has also increased. This increased automation of motor vehicles also necessitates increased automation of individual cleaning processes. After all, the driver of a partially or autonomously operating motor vehicle cannot be expected to notice the soiling status of relevant surfaces in conjunction with the sensors used to monitor and / or regulate driving behavior. Therefore, automation through driver assistance systems also requires automation of cleaning systems for motor vehicles.

[0736] In addition to the complex drivers mentioned above, the networking of systems with each other plays an increasingly important role.

[0737] Overall, the number of sensors and systems involved, as well as their complexity and degree of networking, are steadily increasing.

[0738] As a result, the error susceptibility of the system components involved in the cleaning system and the associated maintenance requirements are increased. The increasing complexity of the individual system components and the increasing complexity of the cleaning system as a whole makes it difficult to identify possible errors, making maintenance work on the cleaning system increasingly time-consuming over time.

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

[0740] Despite the increasing expectations regarding the maintenance of such cleaning systems, it has recently been shown that these cannot withstand the ever-increasing system complexity and the ever-accelerating need for system changes in the area of ​​cleaning systems of motor vehicles.

[0741] A method is proposed here for deriving system dependencies that describe the system behavior of system components of a cleaning system of a motor vehicle.

[0742] The system behavior of a system component is the reaction of the system component to the specification of the system component, where 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 of a system component depends on the input via the system behavior.

[0744] It should be noted that system components of a cleaning system can be understood as individual components of the cleaning system, as well as individual assemblies and the entire cleaning system. In particular, since each of the above-mentioned variants has an individual system behavior, it can be analyzed and the knowledge about the system behavior can then be used advantageously.

[0745] In particular, it is conceivable that the known system behavior of the system component, in particular in the form of the system dependencies derived here, can be used for comparison with the observed system behavior of the system component. If there is a deviation between the known and therefore initially expected system behavior and the observed system behavior, this can indicate a significant characteristic and / or malfunction and / or defect of the system component and / or the cleaning system.

[0746] In this way, the system dependency relationship proposed here, which is derived based on experimental values, advantageously provides the possibility of comparing the observed behavior of a system component with the expected values ​​of the system behavior of the system component described by the system dependency relationship and thus verifying whether the system component and / or the cleaning system behaves as expected.

[0747] Preferably, each system component includes individual system dependencies.

[0748] For each system component to be diagnosed based on experimental values ​​translated into system dependencies, an individual system dependency may preferably be derived according to this aspect of the invention.

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

[0750] The method proposed here for deriving system dependencies from experimental values ​​can be divided into two parts. In the first part, experimental values ​​for the system behavior of system components are collected and stored in a dependency table. Input quantities that cause the activity of the system components and output quantities that describe the system components' reactions to the activity caused by the associated input quantities are stored in an ordered manner in the dependency table.

[0751] In the second part of the method, the experimental values ​​collected in the dependency table are further processed into system dependencies with the aid of an algorithm.

[0752] It should be explicitly pointed out that experimental values ​​can be collected within the framework of this procedure during the operation of the motor vehicle in which the system component is installed, in the normal operation of the system component. 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 numerical simulations using a suitable numerical model and stored in the dependency table.

[0753] It goes without saying that the system dependencies proposed here only consider those input quantities and output quantities that can be recorded and thus evaluated. Specifically, the acquisition of quantities by means of sensors based on physical and / or chemical principles of action is considered. Furthermore, the determination of quantities by means of numerical sensors that can record values ​​in numerical models or, based on measured quantities, can provide further quantities that are not measured but can be determined numerically as a function of at least one measured quantity.

[0754] Although experimental values ​​are discrete experiences of a single input quantity, the advantage of system dependencies is that they can reproduce the system behavior of system components within a range of input quantities, and in particular, can reproduce it continuously and discretely.

[0755] The system dependencies proposed here are generated by means of an algorithm based on sample points of collected discrete experimental values, wherein it is possible that the system dependencies at the sample points defined by the corresponding input variables may have different output variables compared to the recorded experience. This can preferably be caused by averaging the experience.

[0756] An input quantity is preferably understood to be a quantity that is at least indirectly suitable for influencing a system component. Direct adjustment of the input quantity is not necessary. The input quantity may also be caused by ambient conditions. In particular, it is conceivable that low temperatures may lead to ice formation in the cleaning system, which may also alter the system behavior of the system components.

[0757] It should be explicitly pointed out that neither the input quantities nor the output quantities according to the aspects presented herein need be limited to quantities that directly affect the system component under consideration or that can be determined directly at the system component under consideration. Rather, it should be taken into account that each input quantity and each output quantity that can be considered within the aspects may have an indirect effect on the system behavior of the system component under consideration or may be indirectly affected by the system component.

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

[0759] - determining an input variable as a first parameter of the method by means of at least one sensor, wherein in each case an input variable which can have multiple dimensions and is indicative of the behavior of at least one system component can advantageously be provided for further processing by means of the sensor;

[0760] - determining an 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 the 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 variables are advantageously prepared and stored for digital processing; and

[0762] - The determined first parameter and the second parameter are stored in a database as a data set of a dependency table in an ordered manner relative to one another, wherein the previously determined quantities of the method can advantageously be stored in an ordered manner relative to one another in the dependency table in the following manner: an output quantity is assigned to an input quantity, and a system row of a system component of the input quantity caused by the output quantity describes the output quantity.

[0763] In summary, the first part of the procedure advantageously enables the generation of a dependency table consisting of experimental values ​​of the system behavior of the system components under consideration.

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

[0765] - deriving a system dependency between the first parameter and the second parameter from at least two data sets of a dependency table stored in a 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 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 dependencies can then advantageously be stored so that they can be retrieved for further processing, in particular by storing the system dependencies in a non-volatile data memory. Preferably, it is conceivable to store the system dependencies in a database and / or in an electronic data processing and evaluation unit and / or in an electronic control unit.

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

[0768] It is proposed here that input variables include measured variables, in particular process variables and / or controlled variables.

[0769] While the control variable is directly suitable for influencing the cleaning system and thus at least indirectly influences system components of the cleaning system, the process variable is a variable which depends at least indirectly on the control variable or cannot be influenced by common means and only includes an influence on the system behavior of the system components.

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

[0771] Advantageously, it can be achieved that the dependency table and / or the system dependency can be based on directly determined input variables, in particular process variables and / or controlled variables, wherein variables that have a significant influence on the system behavior of the system components can be taken into account.

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

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

[0774] Because the energy demands of system components fluctuate relatively little under normal conditions, the power consumption of system components can be used relatively quickly and easily to determine whether the energy usage of the system components has changed.

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

[0776] Optionally, the output quantity and / or the input quantity comprises a process quantity, preferably a flow pressure and / or an electric current and / or an operating time and / or a temperature and / or a fill level signal and / or a reaction time and / or a sensing time and / or a signal of a leakage sensor and / or a signal of a flow meter and / or a number of actuations and / or a spray pattern and / or a thermal monitoring signal, preferably a thermal monitoring signal referenced to a certain reference area, and / or a signal of a debris sensor and / or a signal of a non-return valve and / or a signal of a drip sensor and / or a signal of a distance sensor and / or a signal of a force sensor.

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

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

[0779] In particular, the level signal of the cleaning fluid reservoir can be considered. If the cleaning system is not actively used at this time, wherein in particular no cleaning fluid pump is actively operated, and a decrease in the level signal of the cleaning fluid reservoir is still observed, this is a relatively simple indication that there is an undesired leak in the cleaning system, through which cleaning fluid escapes.

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

[0781] It should be explicitly mentioned that for other process quantities, causal relationships on the system behavior also occur.

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

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

[0784] It has been shown that in particular ambient 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 ambient conditions in the immediate vicinity of a motor vehicle.

[0785] Specifically, low temperatures may cause localized freezing within the cleaning system, resulting in localized flow blockages.

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

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

[0788] In an advantageous embodiment, the input quantity comprises vehicle type.

[0789] The type of 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 on the system behavior of a first system component may also be caused by the system behavior of a second system component. The vehicle type provides information about the constellation and / or arrangement of the system components of the cleaning system and thus represents a simple way to unambiguously record 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] The inclusion of the vehicle type therefore allows advantageously increasing the mapping accuracy of the system dependencies proposed here and thus also of the dependency table.

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

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

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

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

[0797] It has been shown that the different availability of sensors at the start of a cleaning process has an impact on the cleaning result. In other words, for cleaning processes performed in the same way, the possible gains in availability can be different.

[0798] In particular, it is proposed that the input variables include parameters of the cleaning process and / or the output variables include a gain in availability.

[0799] This makes it possible to evaluate the system behavior of the cleaning system and / or system components of the cleaning system based on the cleaning result, in particular on parameters that are dependent on the cleaning process.

[0800] This advantageously allows already installed sensors, in particular sensors for supporting driver assistance systems, to be used to evaluate the system behavior of the cleaning system.

[0801] In this way, it is advantageously possible to evaluate the system behavior of the system components of the cleaning system without having to add additional sensors which are necessary only for the evaluation of the cleaning system.

[0802] It should be clearly pointed out that this aspect particularly relates to the second, third, ninth and tenth aspects of the present invention. It goes without saying that this aspect also relates to other aspects of the present invention and there is a mutual relationship between them.

[0803] Optionally, the input comprises the current coordinates of the motor vehicle.

[0804] It has also been shown that the coordinates of the motor vehicle have 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 coordinates of the motor vehicle. In particular, it has been shown that the system behavior of the system components of the cleaning system depends on temperature and / or humidity and / or solar radiation and / or precipitation and / or snowfall.

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

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

[0808] According to a more precise approach, it is also proposed that the motor vehicle use local information about the current and / or forecasted weather at its coordinates. Thus, when determining the dependency table and / or system dependencies, influencing variables that have a valid relationship with the system behavior of the system components of the cleaning system and that can be determined directly or indirectly by the coordinates of the motor vehicle can be used to improve the accuracy of the mapping of the predicted system behavior.

[0809] It goes without saying that this aspect is related to other aspects of the present invention and there is a mutual relationship.

[0810] In a preferred embodiment, the output comprises the availability of the sensor and / or the availability achieved as a result of the cleaning process.

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

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

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

[0814] In an advantageous embodiment, the system dependencies are determined by means of regression analysis.

[0815] Here, a regression algorithm is proposed as an algorithm to indirectly derive system dependencies.

[0816] Thus, algorithms can advantageously be used which have been tested in a large number of applications and which can be optimally selected and / or adapted according to the system behavior considered therein, so that high-quality system dependencies can be determined.

[0817] Preferably, the system dependency is determined in the form of a curve, preferably a curve and a coefficient of determination 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, the curve has no gaps, so that a clear assignment between input quantities and output quantities can be achieved, in particular a continuous and differentiable dependency between input quantities and output quantities due to the system behavior of the system component, so that the system dependency is ideally adapted to any mathematical method for using the system dependency.

[0819] Assuming a sufficient number of data sets are available, evaluating the coefficient of determination based on the determined data and the curve determined using the regression model provides an indication of the accuracy of the system's dependencies. This advantageously allows for an assessment of the significance of the correlation between input and output variables and the quality of the reproduction of existing or recorded data. Furthermore, with a large coefficient of determination, the curve also allows for statements to be made regarding the boundaries of the existing data. For example, it is conceivable that data could be supplemented and / or extrapolated numerically at the boundaries of the existing data.

[0820] Advantageously, the system dependencies are determined with the aid of an optimization process.

[0821] It is proposed to determine the parameters of the system dependencies using an optimization procedure, in particular a minimization procedure, which minimizes the cumulative deviations of the experimental values ​​considered from the data set of the system dependencies. This advantageously allows the determination of a system dependency that can be derived in an optimal manner (in particular, with the smallest cumulative deviations from the initial empirical values).

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

[0823] Preferably, the system dependencies are determined with the aid of a self-learning optimization method.

[0824] In particular, an algorithm is proposed that uses features of algorithms from the class of machine learning. Thus, the algorithm is able to derive systematic dependencies between input quantities and availability differences due to contamination.

[0825] The advantage of this is that the complex task of indirectly deriving system dependencies using self-learning optimization methods does not have to be manually adapted to new conditions. This saves time and money in the indirect derivation of system dependencies.

[0826] Since the optimizer 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] Thus, it is also conceivable to perform optimization under multiple equal objectives and / or boundary conditions (multi-criteria optimization). In particular, algorithms capable of determining Pareto optima and / or Pareto fronts are considered. In particular, algorithms from the fields of the simplex method and / or evolutionary strategies and / or evolutionary optimization algorithms are proposed for deriving system dependencies.

[0828] Optionally, the system dependencies are derived using a data set from a dependency table of an already existing database, preferably a data set from which the already existing database is previously accessed.

[0829] This has the advantage that data from existing databases can also be used to derive system dependencies. This eliminates the need to first collect experimental values ​​at a specific motor vehicle, transfer them to the database data, and then transfer them to the system dependencies. In this way, existing data and experimental values ​​can be used to derive system dependencies for the pollution process without first having to collect experimental values ​​representing the system dependencies for the pollution process.

[0830] In an optional embodiment, an already existing database is continuously expanded.

[0831] Advantageously, it can be achieved that the number of exportable system dependencies increases over time.

[0832] Furthermore, it can advantageously be achieved that the accuracy of the system dependencies can be increased due to the larger number of experimental values ​​known with the aid of the data set.

[0833] Advantageously, the new data set replaces the data set in the dependency table that deviates most from the derived system dependencies.

[0834] Specifically, the fact that the empirical value is exchanged with the maximum Euclidean distance to the system dependencies should be considered.

[0835] Advantageously, it can be achieved that the system dependencies become increasingly precise over time, which can be expressed by an increase in the coefficient of determination.

[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 variable and / or the input variable include the frequency and / or the speed of the cleaning fluid pump.

[0838] This may advantageously improve the dependency table and / or system dependency accuracy, as it has been found that the frequency and / or speed of the cleaning fluid pump may affect the system behavior of the system components.

[0839] It is also proposed that the output quantity and / or the input quantity include the size of the nozzle and / or the type of washing fluid and / or the quality of the washing fluid.

[0840] Since it has been found that nozzle size and / or washing fluid type and / or washing fluid quality may influence system behavior of system components, this may advantageously improve the dependency table and / or system dependency accuracy.

[0841] Recommended output and / or input quantities include the pump diaphragm material and / or hose material.

[0842] This may advantageously improve the dependency table and / or system dependency accuracy, as it has been found that pump diaphragm material and / or hose material may affect the system behavior of system components.

[0843] It should be noted that the subject matter of the fifth aspect may be advantageously combined with the subject matter of the preceding aspects of the invention, either individually or cumulatively, in any combination.

[0844] According to a first alternative of the sixth aspect of the invention, the object is achieved by a method for diagnosing the system behavior of system components of a cleaning system of a motor vehicle,

[0845] where the output quantity depends on the input quantity by means of the system behavior of the system components of the cleaning system,

[0846] wherein the actual output amount exceeding the upper threshold amount and / or the actual output amount dropping below the lower threshold amount indicates that the actual system behavior deviates from the expected system behavior,

[0847] The method comprises the following steps:

[0848] - preferably determining the input amount;

[0849] - Determine the actual output;

[0850] - retrieving an upper threshold amount and / or a lower threshold amount, preferably depending on the input amount;

[0851] - comparing the actual output amount with an upper threshold amount and / or a lower threshold amount;

[0852] - preferably, if the actual output exceeds an upper threshold amount, calculating the deviation between the actual output and the upper threshold amount, and / or if the actual output falls below a lower threshold amount, calculating the deviation between the actual output and the lower threshold amount; and

[0853] Preferably, the diagnostic signal is stored if the actual output quantity exceeds an upper threshold quantity and / or if the actual output quantity falls below a lower threshold quantity.

[0854] A procedure for monitoring and diagnosing system components of a cleaning system of a motor vehicle is presented herein.

[0855] The number of system components of a cleaning system and the number of functions of a cleaning system are increasing 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 cleaning systems is also increasing on the market, wherein the different system components are often provided by different suppliers.

[0857] As a result, the complexity of the cleaning system also increases because of the maintenance required to maintain trouble-free system operation.

[0858] This increases the need for at least partially automated or automatable methods for early detection of possible errors in system components of a cleaning system.

[0859] It was unexpectedly discovered that electrical and mechanical anomalies in the system behavior of system components of a cleaning system are often correlated. This discovery can be used to evaluate system components based on electromechanical concepts.

[0860] While the evaluation of cleaning systems currently relies primarily on visual inspection, the evaluation of system components based on an electromechanical concept can advantageously result in the fact that already existing or easily additional electrical signals of system components of the cleaning system can also be used to evaluate possible mechanical faults. Previously, this could only be done by visual inspection by trained personnel.

[0861] In particular, mechanical anomalies in the system behavior of system components can often be advantageously identified by at least partially automatically observing the electrical behavior of the system components.Thus, a variety of different possible problems associated with the cleaning system can be detected by monitoring the electrical quantity.

[0862] In particular, it was unexpectedly determined that the time course of the inrush current of the cleaning fluid pump in the event of a mechanical blockage of the flow channel for the cleaning fluid can show characteristic differences from the time course of the inrush current in the event of a fault-free, regular activation of the cleaning fluid pump, in particular in the event of a mechanical blockage of the flow channel before the intended outlet of the cleaning fluid in the nozzle. Particularly advantageously, a distinction can be made between partial and complete blockage of the flow channel for the cleaning fluid.

[0863] While under normal circumstances the time course of the inrush flow when the cleaning fluid pump is switched on results in only a short overshoot step response, the step response in the presence of a mechanical interlock can, in particular, show a more significant time course, in which the current reaches the desired value for continuous operation of the cleaning fluid pump only with measurable damping.

[0864] The procedure proposed here can preferably be executed autonomously and can therefore preferably be executed autonomously 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 is contemplated that the diagnostic program proposed herein can preferably be activated by means of an electronic control unit and / or a cleaning system of the motor vehicle without intervention by the driver of the motor vehicle. Furthermore, it is contemplated that the diagnostic program proposed herein can preferably be activated manually by the driver of the motor vehicle.

[0866] The diagnosis proposed here compares the expected behavior of a system component of a cleaning system with the system behavior determined during monitoring of the system component using the actual output variable. The comparison is performed using at least one value of the output variable.

[0867] The expected system behavior is based in particular on experimental values ​​of evaluated system components. These experimental values ​​can be based on observations during normal operation of a motor vehicle or in a laboratory, or on the results of numerical models.

[0868] If the comparison results in 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 faulty and / or has not been damaged by external influences acting on the system component.

[0869] According to the method proposed herein, the desired system behavior is determined based on an upper threshold value and / or a lower threshold value. If the signal of the actual output variable lies within or operates within the range defined by the upper threshold value and the lower threshold value, then the system behavior of the system component under consideration is not unexpected, wherein the range can also be open-ended, provided that only the upper threshold value or the lower threshold value is specified.

[0870] Therefore, the method proposed here requires a list of 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 may also preferably depend on the input quantity and the system component considered.

[0871] Preferably, the upper threshold amount and / or the lower threshold amount depends on the process variable.

[0872] If the monitored output quantity exceeds an individually associated upper threshold value, or if the monitored output quantity falls below an 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 known empirically, in particular following the seventh and / or eighth aspects of the invention, with which specific deviations can be corrected.

[0874] If the deviation of the monitored output from the expected output and / or the characterization of the deviating system behavior leads to a known behavior pattern, this can be associated with an action recommendation. Such action recommendations are also based on experimental values, which can also be systematized to a large extent.

[0875] Regarding the systematic experimental values, it should be specifically taken into account that, depending on the type and severity of the deviation of the monitored output from the expected output, 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 is conceivable that an increase in the power consumption of the cleaning fluid pump and thus a deviation in the system behavior could lead to the conclusion that there is an error in the cleaning system. In particular, it is conceivable that the cleaning fluid pump will age, wherein it is particularly conceivable that a higher energy requirement would be required to control the pump pressure of the cleaning fluid pump.

[0877] Alternatively, in this case, it could be that there's a blockage in the flow channel downstream of the cleaning fluid pump, which results in increased backpressure and thus affects the system behavior of the cleaning fluid pump. Depending on the situation, the cause of the diagnostic deviation can be identified by comparing different output quantities. For this purpose, empirical values ​​are necessary, which can be obtained, in particular, from a table.

[0878] This also indicates that deviations between the expected and actual output quantities of the system behavior of a system component do not necessarily have to be caused by the monitored system component itself.

[0879] In the event of a blockage in front of the pump, a possible solution strategy for correcting the deviation using the onboard device may be to increase the pump pressure in a targeted manner, wherein the blockage may be released and flushed out of the cleaning system. In particular, the choice of a solution strategy according to the seventh aspect of the invention may be considered.

[0880] When implementing a solution strategy, special consideration should be given to implementing a solution strategy according to the eighth aspect of the present invention.

[0881] If the selected and implemented resolution strategy is successful, it will result in system components producing a system behavior that corresponds to the expected system behavior.

[0882] It should be explicitly noted that the diagnostic method described herein can be applied to any system component. If a sufficient number of sensors or measuring devices, a sufficient number of empirical values ​​regarding the expected system behavior of one or more system components, and a list of potentially successful resolution strategies are available, a large number of occurring deviations can be corrected using onboard devices. Deviations in system behavior that cannot be corrected using onboard resources can also be detected at an early stage and corrected within the scope of regular or early maintenance, advantageously preventing the potential spread of damage that would otherwise occur.

[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 may be a scalar quantity or a vector quantity.

[0884] Furthermore, it is optionally provided that the diagnostic signal is stored or transmitted to an electronic control unit of the motor vehicle.

[0885] Preferably, it is proposed to calculate the deviation between the actual output and the upper threshold amount if the actual output exceeds the upper threshold amount and / or to calculate the deviation between the actual output and the lower threshold amount if the actual output falls below the lower threshold amount.

[0886] If only a single parameter is evaluated without its time course, the above quantity is a scalar quantity. In all other cases, in particular when multiple parameters of the cleaning system are considered and / or when at least one time course of a parameter is considered, the above quantity should be understood as a vector quantity.

[0887] Therefore, the preferred recommended calculation of the deviation between the actual output quantity and the upper and / or lower threshold quantities also depends on whether the output quantity is a scalar or a vector quantity. It is recommended to adjust the upper and / or lower threshold quantities to the dimensional characteristics of the actual output quantity, unless this is already the case, in which case it must be ensured that the upper and / or lower threshold quantities 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 performed separately for each component, ie for the dimension of dimension.

[0889] Deviations may occur for some or all components of the actual output quantity, wherein simultaneously a component may be conceivable to have a deviation because a corresponding component of the lower threshold quantity undershoots and a component may be conceivable to have a deviation because a corresponding component of the upper threshold quantity overshoots.

[0890] If a deviation is determined for at least one component between the upper threshold value and / or the lower threshold value and the actual output variable, a further investigation of this deviation is proposed.

[0891] The diagnostic signal may include a failure to detect a deviation of actual system behavior from expected system behavior.

[0892] Furthermore, the diagnostic signal may include that a deviation of actual system behavior from expected system behavior has been detected, wherein the type and expression of the deviation may also be stored in the diagnostic signal.

[0893] Preferably, the suggested diagnostic signal comprises a deviation.

[0894] Preferably, the diagnostic signal comprises an output variable and / or a temporal progression of the output variable, wherein the temporal progression of the output variable 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 amount of values ​​that change over time should not be understood as strict limitations, but should be able to be exceeded or dropped below it on an engineering scale without departing from the aspects of the present invention. Simply put, these values ​​are intended to provide an indication of the magnitude of the amount of values ​​over the time ranges proposed herein.

[0896] In particular, it should also be remembered that the diagnostic signal comprises a plurality of time curves of the output variable over time, in particular a plurality of time curves of the output variable together with the input variable and / or the process variable over time.

[0897] This advantageously enables changes in the system behavior of system components, preferably as a function of input variables and / or process variables, to be observed and evaluated, 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 with respect to the system behavior of system components of a cleaning system of a motor vehicle can be made possible in an advantageous manner, wherein possible errors can be detected autonomously at an early stage.

[0899] This also makes it possible to identify possible subsequent error sources at an early stage, so that the propagation of errors can be advantageously limited.

[0900] In this way, it is also advantageously possible to extend the intervals at which an optical inspection by a trained specialist should be performed, 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 invention, the object is solved by a method for diagnosing deviations between actual and expected system behavior of system components of a cleaning system of a motor vehicle,

[0902] where the output quantity depends on the input quantity by means of the system behavior of the system components of the cleaning system,

[0903] where the actual system behavior depending on the input quantity is represented by the actual output quantity, and the expected system behavior depending on the input quantity is represented by the expected output quantity,

[0904] wherein the expected system behavior is represented by a dependency table or system dependencies, preferably by at least one data set of a system dependency table derived by the method according to the fifth aspect of the invention,

[0905] The method comprises the following steps:

[0906] - preferably determining the input amount;

[0907] - Determine the actual output;

[0908] - Determine the expected output by:

[0909] ○ Select the dataset that best matches the input from the dependency table, read the output stored in the selected dataset and use it as the expected output; or

[0910] ○ Selecting two data sets from the dependency table that best match the input quantity and using linear interpolation to determine the expected output quantity based on the two selected data sets; or

[0911] Calculate expected outputs by plugging inputs into system dependencies.

[0912] - Calculate the deviation between the actual output and the expected output; and

[0913] Preferably, the diagnostic signal is stored if the deviation is greater than 10%, preferably greater than 5%, particularly preferably greater than 2% of the expected output.

[0914] This second alternative of the sixth aspect of the invention, in parallel to the first alternative of the sixth aspect of the invention, also proposes a procedure for monitoring and diagnosing system components of a cleaning system of a motor vehicle.

[0915] It should be expressly pointed out that the non-limiting description of the first alternative of the sixth aspect of the present invention described above is also valid for the second alternative of the sixth aspect, and vice versa, wherein the actual output quantity is not compared with the lower threshold quantity and / or the upper threshold quantity, but is compared with the expected output quantity.

[0916] Compared to the first alternative, according to the second alternative of the sixth aspect of the present invention, it is proposed to compare the actual output quantity with the expected output quantity, thereby determining the deviation between the actual output quantity and the expected output quantity.

[0917] The diagnosis proposed here compares the expected system behavior of the system components of the cleaning system with the expected system behavior. The comparison is performed based on a comparison of at least one value of the actual output quantity with a corresponding value of the expected output quantity.

[0918] The expected system behavior is based in particular on experimental values ​​of system components diagnosed with the proposed method. These experimental values ​​can be based on observations during normal operation of a motor vehicle or in the laboratory, or on the results of a numerical model suitable for mapping the normal system behavior of the cleaning system.

[0919] Preferably, the expected system behavior, and therefore the expected output, depends on the inputs used to operate the cleaning system.

[0920] Preferably, the desired system behavior and thus the desired output quantity depends on the process quantity.

[0921] According to this second alternative of the sixth aspect of the invention, three further deviating variants are proposed in each case, with the help of which the expected output quantity can be determined based on experimental values.

[0922] According to a first and a second variant, it is conceivable that the expected system behavior of the system components is described by a dependency table, in particular a dependency table that has been created according to the first step of the method according to the fifth aspect of the invention.

[0923] It should be explicitly mentioned that the dependency table can depend on the system components, input variables and / or process variables to be diagnosed.

[0924] Such a dependency table describes discrete experimental values ​​of the expected system behavior one system component at a time, so that the experimental value must first be selected from the dependency table before comparison with the actual output quantity.

[0925] The first and second variants for determining the expected output quantity differ from one another with regard to the evaluation of the dependency table.

[0926] According to a first variant for selecting the expected output quantity, it is proposed to select the most suitable empirical value from the dependency table by comparing the actual input quantity and / or actual process quantity with the input quantity and / or process quantity of the corresponding data set, in particular the most suitable empirical value in the form of a data set defined by the shortest Euclidean distance between the data set stored in the dependency table and the actual input quantity and / or actual process quantity with respect to the input quantity and / or process quantity.

[0927] According to a second variant for selecting the expected output variable, it is proposed to select two best-fitting and adjacent experimental values ​​in the form of two data sets from a dependency table according to the description of the first variant and to interpolate between these two experimental values ​​depending on the actual input variable and / or the actual process variable.

[0928] According to a third variant for selecting expected output quantities, it is proposed to map the expected system behavior of the system components by means of system dependencies, in particular by means of system dependencies derived according to the fifth aspect of the invention.

[0929] The system dependencies can continuously describe the expected system behavior as a function of actual input variables and / or actual process variables, so that selection or interpolation between experimental values ​​as described above for the second variant is no longer necessary.

[0930] Just like the dependency tables according to the first and second variants, the system dependency may be valid only for one system component, so that in consideration of a deviating system component, a deviating system dependency or a deviating dependency table may or should be selected.

[0931] It should be understood that input variables, actual output variables, expected output variables, and / or deviations can be scalar or vector quantities. If only a single parameter describing the system behavior of a system component is evaluated without the time course of this parameter, the aforementioned variables are scalar quantities. In all other cases, in particular when multiple parameters of the cleaning system are considered and / or when at least one time course of a parameter is considered, the aforementioned variables should be understood as vector quantities.

[0932] Therefore, the calculation of the deviation between the actual output quantity and the expected output quantity also depends on whether the output quantity is a scalar or a 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 it must be ensured in each case that the expected output quantity and the actual output quantity each have corresponding quantities.

[0933] In the case of a vector actual output quantity, the calculation of the deviation is performed separately for each component, ie for the dimension of dimension.

[0934] If a deviation is determined for at least one component between the expected output variable and the actual output variable, a further investigation of this deviation is proposed.

[0935] According to the discussion already mentioned above, when determining the measured values, measurement errors and expected fluctuations of the corresponding signals also occur in normal operation.

[0936] Therefore, not every nominal deviation between the expected output quantity and the actual output quantity causes the actual system behavior of the system component to deviate from its expected system behavior.

[0937] In order to quantify when the actual system behavior of a 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 performed component by component. It should also be considered that, based on available experimental values, each component of different sizes can be assigned a limit value above which the deviation between the actual system behavior of the system component deviates from the expected system behavior.

[0939] In particular, a limit value of 10%, preferably 5%, in particular 2% is proposed for the deviation.

[0940] It should be noted that the above values ​​of the limit values ​​of deviation should not be understood as strict limits, but should be able to be exceeded or dropped below it on an engineering scale without departing from the aspects of the present invention. Simply put, these values ​​are intended to provide an indication of the size of the limit values ​​of 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 a limit value, the actual system behavior deviates from the expected system behavior of the system component under consideration.

[0943] Otherwise, the actual system behavior corresponds to the expected system behavior and it can be concluded that the system components of the cleaning system under consideration are not defective and / or not faulty and / or that the system components have not been damaged by external influences acting on the system components.

[0944] In particular, a deviation between an expected output quantity and an actual output quantity of a system behavior of a system component does not necessarily have to be caused by the monitored system component itself.

[0945] Rather, which system component of the cleaning system shows or may show a possible error can be part of a further diagnosis, depending on the deviation determined.

[0946] Please note that the diagnostic method described here can be used for any system component. If a sufficient number of sensors or measuring devices, a sufficient number of empirical values ​​regarding the expected system behavior of one or more system components, and a list of potentially successful resolution strategies are available, a large number of occurring deviations can be corrected using onboard devices. Deviations in system behavior that cannot be corrected using onboard resources can also be detected at an early stage and corrected within the scope of regular or early maintenance, advantageously preventing the potential spread of damage that would otherwise occur.

[0947] Furthermore, it is optionally provided that the diagnostic signal is stored or transmitted to an electronic control unit of the motor vehicle.

[0948] The diagnostic signal may include a failure to detect a deviation of actual system behavior from expected system behavior.

[0949] Furthermore, the diagnostic signal may include that a deviation of actual system behavior from expected system behavior has been detected, wherein the type and expression of the deviation may also be stored in the diagnostic signal.

[0950] Preferably, the diagnostic signal comprises an output variable and / or a temporal progression of the output variable, wherein the temporal progression of the output variable 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 amount of values ​​that change over time should not be understood as strict limitations, but should be able to be exceeded or dropped below it on an engineering scale without departing from the aspects of the present invention. Simply put, these values ​​are intended to provide an indication of the magnitude of the amount of values ​​over the time ranges proposed herein.

[0952] In particular, it should also be remembered that the diagnostic signal comprises a plurality of time curves of the output variable over time, in particular a plurality of time curves of the output variable together with the input variable and / or the process variable over time.

[0953] This advantageously enables changes in the system behavior of system components, preferably as a function of input variables and / or process variables, to be observed and evaluated, in particular with regard to possible aging effects and / or changes in the remaining expected service life of the system components.

[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 using the same system components or different system components.

[0955] Thus, an at least partially automated error detection with respect to the system behavior of system components of a cleaning system of a motor vehicle can be 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 be advantageously limited.

[0957] In this way, it is also advantageously possible to extend the intervals at which an optical inspection by a trained specialist should be performed, 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 in the process, preferably at least 10 time points, particularly preferably at least 20 time points.

[0959] In particular, it is proposed here that the previously discussed deviations are now also considered as a progression of deviations over time.

[0960] Preferably, the time course of the deviation can also be stored in a database.

[0961] Preferably, the time course is stored together with the diagnostic signal.

[0962] In particular, it is suggested that the time course of the deviation starts shortly before a planned change in the input quantity. Preferably, the time course of the deviation ends after the next planned time change.

[0963] Specifically, it should be remembered that the output is diagnosed over a period of at least slightly more than two planned changes in the input on both sides. Specifically, the diagnosis of the time course of the output begins before the cleaning fluid pump is turned on and ends after the cleaning fluid pump is turned off.

[0964] Based on the time course of the output variable, a systematic error of the system component can be estimated, in particular a systematic error including a dependency on the damping of the system behavior of the system component.

[0965] Furthermore, it is advantageous to take into account that the time sequence does not run continuously, but rather that a certain output variable is recorded after each activation of a system component.

[0966] In particular, it should be remembered that after each switch-on process, the fluid pressure downstream of the cleaning fluid pump and / or the current and / or the fluid velocity downstream of the cleaning fluid pump are recorded within a defined time unit after the switch-on process, and the individual values ​​recorded in each case are recorded and diagnosed as a time series.

[0967] In this way, performance degradation of the cleaning fluid pump during its useful life may advantageously be assessed so that a warning may be provided if replacement of the cleaning fluid pump is desired.

[0968] It should be noted that the above values ​​for the amount of data points should not be understood as strict limitations, but should be able to be exceeded or dropped below them on an engineering scale without departing from the aspects of the present invention. Simply put, these values ​​are intended to provide an indication of the magnitude of the amount of data points in the time ranges presented herein.

[0969] The system behavior of the system components can advantageously be evaluated based on the time course of the output variables, wherein a plurality of further analysis possibilities are provided, in particular with respect to the transmission behavior of the system components.

[0970] In particular, the time course of the deviation can be evaluated as a function of input and / or output variables, wherein data with identical or very similar input and / or process variables are compared with one another.

[0971] Preferably, the time course includes at least 30 time points. Preferably, the time course includes at least 40 time points. Preferably, the time course includes at least 50 time points.

[0972] The results of the analysis of the time course of the deviation are preferably stored together with and / or in the diagnostic signal.

[0973] Preferably, the time course of the deviation is checked against a step response.

[0974] Here, a step response is presented, in particular a step response for evaluating the time course of an output variable as a reaction to a change in an input variable.

[0975] Specifically, a change in the value of the output quantity or a change in the output quantity may be checked against a change in the input quantity.

[0976] Furthermore, it is proposed to examine the time course of the output variable, preferably with respect to the transmission behavior as part of the system behavior of the system component, wherein a damping influencing the output variable can be determined.

[0977] Preferably, it is possible to diagnose whether the nozzle is 'partially or completely clogged with cleaning fluid'. For example, a pressure spike behind the cleaning fluid pump indicates that the nozzle is clogged. The shape of the pulse spike can provide a useful indication of whether the flow path behind the pump is completely or partially clogged.

[0978] Comparison of characteristic features may entail comparing the course of the pulse spike to one or more reference courses of pressure.

[0979] If clogging of the nozzle is detected, the solution strategy according to the seventh and / or eighth aspects of the invention may be used.

[0980] Alternatively, an alert may be generated requesting manual cleaning of the nozzles.

[0981] By monitoring the inrush of the cleaning fluid pump over time, it is also possible to diagnose whether it is blocked, especially under freezing conditions.

[0982] In particular, a clogged cleaning fluid pump has a higher damping relative to surge flow.

[0983] If a clogged cleaning fluid pump is detected, it can in particular be switched off, which has the advantage of preventing the cleaning fluid pump from burning out.

[0984] The system behavior of the system components can advantageously be evaluated based on the time course of the output variables, wherein a plurality of further analysis possibilities are provided, in particular with respect to the transmission behavior of the system components.

[0985] In particular, the step response can be evaluated as a function of an input variable and / or an output variable, wherein data having identical or very similar input variables and / or process variables are compared with one another.

[0986] The results of the analysis of the time course of the deviation are preferably 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] Here, it is proposed to evaluate the time course of the output variable with respect to its drift over time.

[0989] Drift is the systematic change in output quantities as a response to input quantities during the lifetime of a system component.

[0990] The time course of the output can be compared with previously observed time courses of output over time, and particularly with multiple time courses of output over time.

[0991] Drift is present if the time-varying deviation from the expected system behavior of the system component continuously moves in one direction. Based on this characteristic, it is advantageously possible to determine how a lifetime-related change in the system behavior, in particular of the system component, develops.

[0992] Furthermore, it is advantageous to take into account that the time sequence does not run continuously, but rather that a certain output variable is recorded after each activation of a system component.

[0993] In particular, it should be remembered that after each switch-on process, the fluid pressure downstream of the cleaning fluid pump and / or the current and / or the fluid velocity downstream of the cleaning fluid pump are recorded within a defined time unit after the switch-on process, and the individual values ​​recorded in each case are recorded and diagnosed as a time series.

[0994] In this way, performance degradation of the cleaning fluid pump during its useful life may advantageously be assessed so that a warning may be provided if replacement of the cleaning fluid pump is desired.

[0995] In particular, the time course of the deviation can be evaluated based on the input and / or output variables to determine whether a drift exists, wherein data with identical or very similar input and / or process variables are compared with one another.

[0996] Preferably, at least 20 time courses of the deviation are examined to determine if there is a drift in the deviation over time. Preferably, at least 30 time courses of the deviation are examined to determine if there is a drift in the deviation over time. Preferably, at least 40 time courses of the deviation are examined to determine if there is a drift in the deviation over time.

[0997] It should be noted that the above values ​​for the time course of the deviation should not be understood as strict limitations, but should be able to be exceeded or lowered on an engineering scale without departing from the aspects of the present invention. Simply put, these values ​​are intended to provide an indication of the magnitude of the time course of the deviation ranges set forth herein.

[0998] The results of the analysis of the time course of the deviation are preferably stored together with and / or in the diagnostic signal.

[0999] The reason the actual system behavior deviates from the expected system behavior may be based on the currently diagnosed system component, or may have a reason based on the deviating system component but transferred to the actual diagnosed system component according to a system-dependent transfer function between the components.

[1000] If the corresponding transfer function is not known, further diagnosis of the system components is recommended to limit the cause.

[1001] The diagnostic signal preferably includes information about input variables which have an effect on the cleaning system and / or the system component during the diagnosis of the system component.

[1002] The diagnostic signal preferably includes information about process variables which influence the cleaning system and / or the system component during the diagnosis of the system component.

[1003] It goes without saying that the advantages of system dependencies, in particular the system dependencies according to the fifth aspect of the invention, also apply to the use of system dependencies, in particular the use of system dependencies according to the sixth aspect of the invention proposed here.

[1004] It should be noted that the subject matter of the sixth aspect may be advantageously combined with the subject matter of the preceding aspects of the invention, either individually or cumulatively, in any combination.

[1005] According to the seventh aspect of the invention, the task is solved by a method for selecting a solution strategy from a list of solution strategies contained in a database depending on a current diagnostic signal, preferably depending on a current diagnostic signal received according to the sixth aspect of the invention, wherein the list of solution strategies contains at least one solution strategy associated with the diagnostic signal, wherein the solution strategy whose associated diagnostic signal best matches the current diagnostic signal is selected from the list of solution strategies.

[1006] If the actual system behavior of system components 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 may have several causes.

[1007] Specifically, the reason why the actual system behavior deviates from the expected system behavior may be due to the currently diagnosed system component, or may be due to a deviating system component but transferred to the actually diagnosed system component according to a system-related transfer function between system components.

[1008] Preferably, the cause category of the deviation between the actual system behavior and the expected system behavior can be determined from the diagnostic signal, in particular from the current diagnostic signal according to the sixth aspect of the invention.

[1009] The current diagnostic signal represents a diagnostic signal that is affected by the solution strategy within the scope of the method. Specifically, the current diagnostic signal can be created using the method according to the sixth aspect of the present invention. Specifically, the current diagnostic signal indicates that there is a deviation between the actual system behavior and the expected system behavior.

[1010] When determining the cause of a deviation between actual and expected system behavior with the aid of the diagnostic signal, input variables and / or process variables that influence the system components and / or the cleaning system when determining the diagnostic signal are particularly preferred.

[1011] It should be taken into account in particular that the current diagnostic signal can be associated, and preferably unambiguously associated, with the cause of the deviation of the system behavior of the system component based on existing experimental values.

[1012] Furthermore, it is particularly conceivable that the 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 advantageously be achieved that, based on existing experience with different system components of different cleaning systems, in particular with different cleaning systems of different manufacturers or suppliers, a clear assignment can be made between a current diagnostic signal and the cause of a deviation from the system behavior, in particular a clear manufacturer-independent and type-independent assignment for the cleaning system and / or specific system component.

[1014] In particular, four different types of causes of deviations between actual and expected system behavior are proposed, which can preferably be distinguished by means of diagnostic signals, particularly preferably by means of current diagnostic signals according to the sixth aspect of the invention.

[1015] In particular, it is proposed here to determine the category of the cause in the presence of a current diagnostic signal.

[1016] According to the first category of causes of the deviation between the actual system behavior and the expected system behavior, there is a defect in the system component. In this respect, many different defects can be envisaged.

[1017] In particular, it is conceivable that, if a defect is present, the cleaning fluid line itself has become separated from the system components of the cleaning system.Such a defect can also be repaired by untrained personnel.

[1018] Furthermore, it is conceivable that a leak may occur in the cleaning fluid line. In this case, spare parts would be required at least in the medium term, and the defect could not be repaired by untrained personnel alone at least in the medium term.

[1019] According to the second category of causes of deviations between actual and expected system behavior, there is the aging phenomenon of system components.

[1020] Even if most system components of a motor vehicle's cleaning system are designed to survive the expected service life of the motor vehicle, system components can still age. In particular, it is conceivable that system components age more rapidly than expected, resulting in an expected service life of the system components that is shorter than the planned service life of the motor vehicle. In this case, replacement of such components becomes necessary for continued regular operation of the cleaning system.

[1021] Preferably, according to the sixth aspect of the present invention, aging phenomena can be detected and / or evaluated based on a drift of the deviation over time, in particular based on a drift of the deviation.

[1022] The progression of the deviation drift over time is a particularly preferred way of determining how high the remaining expectation of availability of a system component is.

[1023] According to the third category of causes of deviation between actual system behavior and expected system behavior, there is interference of system components.

[1024] It should be explicitly mentioned that a fault may be present in a system component that has been subjected to a diagnostic procedure, in particular a diagnostic procedure according to the sixth aspect of the present invention. Alternatively, the fault may also be caused by a deviating system component, wherein the fault is transmitted to the system component by means of a transfer function, in particular by a system behavior that is not in accordance with the diagnostic procedure.

[1025] According to the fourth category of causes of deviations between actual system behavior and expected system behavior, there are unknown causes of deviations in the system behavior of system components.

[1026] If the cause of the deviation between the actual system behavior and the expected system behavior of a system component cannot be determined based on the diagnostic signal, an unknown cause exists.

[1027] In particular, it should be borne in mind that, to date, there are not enough experimental values ​​for possible causes of the deviations, or the assignment of causes would lead to ambiguous results.

[1028] One solution strategy is a method which, when applied to a cleaning system of a motor vehicle, is designed to trace deviations between actual and expected system behavior found in system components of the cleaning system of a motor vehicle.

[1029] In other words, the solution strategy can advantageously achieve that the deviations with respect to the system components become smaller or that the actual system behavior again corresponds to the expected system behavior.

[1030] Particularly preferably, the solution strategy comprises input variables which, when the solution strategy is applied, influence the cleaning system and / or system components on the cleaning system and / or system components.

[1031] Preferably, the resolution strategy displays a notification to the driver of the motor vehicle and / or the manufacturer of the motor vehicle.

[1032] Preferably, the resolution strategy comprises measures for planning maintenance and / or repair of the motor vehicle.

[1033] The solution strategy is preferably based on operating experience of the cleaning system. This experience can be acquired during operation of the motor vehicle and / or in the laboratory and / or based on numerical models and / or can be the result of existing maintenance recommendations and / or can be based on heuristic findings.

[1034] A suitable solution strategy depends on the system behavior and / or the deviation of the current diagnostic signal, in particular on the current diagnostic signal determined according to the sixth aspect of the invention.

[1035] Preferably, the appropriate solution strategy depends on the process volume.

[1036] Preferably, the resolution strategy depends on the amount of input affecting the cleaning system and / or system components when deviations in system behavior and / or diagnostic signals are determined.

[1037] The resolution strategy advantageously enables the system components of the cleaning system to behave as expected again. This allows the functionality of the cleaning system to return to normal operation despite pre-existing deviations in system behavior.

[1038] Overall, the solution strategy can be so advantageous that, despite a diagnosed deviation in the system behavior of the system components of the cleaning system, the functionality of the driver assistance system can be maintained for a longer period of time.

[1039] In particular, it is proposed here to select a solution strategy suitable for the current diagnostic signal from a list of known solution strategies.

[1040] In particular, it is proposed to obtain a list of known resolution strategies from a database that can be accessed from the motor vehicle.The motor vehicle can also be wirelessly connected to a suitable database comprising resolution strategies.

[1041] In addition to the solution strategy, the database also includes the associated diagnostic signal, for which the solution strategy has been configured to remedy the diagnostic signal.

[1042] In addition to the solution strategy, the database preferably includes input quantities that have an impact on the system components and / or the cleaning system when determining the current diagnostic signature.

[1043] In addition to the solution strategy, the database may also preferably include process quantities that affect the system component and / or the cleaning system when determining the current diagnostic signal.

[1044] Preferably, the solution 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 present invention.

[1045] A solution strategy is selected from the database whose diagnostic signal assigned to it in the database best matches the current diagnostic signal.

[1046] Preferably, the most suitable solution strategy is selected from the database using the minimum Euclidean distance between the diagnosis signal assigned to it in the database and the current diagnosis signal.

[1047] When determining the solution strategy with the aid of the current diagnostic signal, it is particularly preferred that input variables and / or process variables that have an impact on the system component and / or the cleaning system be considered when determining the current diagnostic signal.

[1048] It is furthermore preferably proposed that the database with the solution strategy is first prefiltered with respect to the best-fit input variable and / or the best-fit process variable, in particular based on the corresponding Euclidean distance between the input variable and / or process variable stored in the diagnostic signal and the input variable and / or process variable in the database.

[1049] It is proposed to subsequently select a solution strategy based on the current diagnostic signal according to the procedure described above, according to the minimum possible Euclidean distance to the remaining solution strategies.

[1050] Thus, a solution strategy can be advantageously selected which is advantageously provided to reduce deviations in the system behavior of system components of the cleaning system and / or to notify a driver and / or manufacturer of a fault and / or to bring about upcoming maintenance and / or repair measures.

[1051] Furthermore, it should be specifically considered that the experimental values ​​on which each solution strategy is based 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.

[1052] In this way, it can advantageously be achieved that, based on existing experience with different system components of different cleaning systems, in particular different cleaning systems of different manufacturers or suppliers, a clear allocation can be made between current diagnostic signals and solution strategies, in particular a clear cross-manufacturer and cross-type allocation for cleaning systems and / or specific system components.

[1053] One conceivable solution strategy is to increase the supply voltage and / or the target speed of the cleaning fluid pump as a solution strategy if there is a deviation in the actual system behavior from the expected system behavior in the cleaning fluid pump, which in particular indicates a blockage in the flow channel between the cleaning fluid reservoir and the outlet opening at the nozzle, by an increased energy demand of the cleaning fluid pump and / or by a relatively low outlet volume of cleaning fluid at the outlet opening of the nozzle and / or by an increased static pressure of the cleaning fluid downstream of the cleaning fluid pump and / or by a low flow rate of the cleaning fluid downstream of the cleaning fluid pump. This is advantageous in terms of clearing any blockage and flushing it out of the cleaning system.

[1054] If the cleaning fluid pump shows high current, but no pulses from the existing Hall sensors, this indicates that the cleaning fluid pump motor is stalled.

[1055] If the cleaning result, in particular an increase in availability, is not achieved, and / or if activation of the cleaning fluid pump cannot be observed, it is recommended to check the controller of the cleaning system, in particular the electronic control unit of the cleaning system, to determine whether a phase open circuit fault and / or a phase ground fault and / or a short circuit fault is present. If a fault is detected, it is recommended to plan service and maintenance measures.

[1056] It is proposed to operate the cleaning fluid pump at different pressures and / or engine speeds in the event of a deviation between the actual system behavior and the expected system behavior. Since cycling through the different pressures and / or engine speeds does not again result in an actual system behavior that corresponds to the expected system behavior, it is proposed to send a corresponding warning to the driver and / or manufacturer of the motor vehicle and to signal that the cleaning fluid pump should be replaced and / or to cause the cleaning system to stop using the cleaning fluid pump and / or the entire cleaning system until the cleaning fluid pump has been replaced.

[1057] If the external temperature is above a defined temperature, in particular above 45°C, particularly preferably above 55°C, and / or if the external temperature is below a defined temperature, in particular below 0°C, particularly preferably below 15°C, it is proposed that the cleaning fluid pump is no longer operated, whereby the remaining expected service life of the cleaning fluid pump can b...

Claims

1. A method (MDSD3) for indirectly deriving system dependencies (124) of system behavior of system components of a cleaning system (16, 200) of a motor vehicle (14), wherein the cleaning system (16, 200) is adapted to clean at least one surface (20, 22, 24, 26, 28) of the motor vehicle (14) by means of a cleaning process (30, 32, 34, 36, 38, 40), wherein an output variable (204) depends on an input variable (202) by means of the system behavior of the system (16, 200), The method comprises the following steps: - determining (BDTS1) the input variable (202) as a first parameter of the method (MDSD3) by means of at least one sensor (50, 52, 54, 56, 56a, 56b, 58); - determining (BDTS2) the output quantity (204) as a second parameter of the method (MDSD3); - digitizing (BDTS3) and recording the determined first and second parameters by a data processing system (150), wherein the data processing system (150) comprises an electronic data processing and evaluation system (152) and a database (154); - storing (BDTS4) the determined first and second parameters in an ordered manner relative to one another as data sets (DP1, DP2, DP3, DP4) of a dependency table (DT) in the database (154); - by means of the electronic data processing and evaluation system (152) from at least two data sets (DP1, DP2, DP3, DP4) of the dependency table (DT) stored in the database (154), wherein the electronic data processing and evaluation system (152) accesses the data sets (DP1, DP2, DP3, DP4) of the dependency table (DT) and determines the system dependency (124) from the data sets (DP1, DP2, DP3, DP4) of the dependency table (DT) by means of an algorithm; and - storing (DSDS3) the derived system dependencies (124) in the database (154) and / or the electronic data processing and evaluation system (152) and / or the electronic control unit (18).

2. The method (MDSD3) for indirectly deriving system dependencies (124) of system behaviors of system components of a cleaning system (16, 200) of a motor vehicle (14) according to claim 1, characterized in that The input quantity (202) includes at least one measured quantity (100, 102, 104, 106, 107, 108).

3. Method (MDSD3) for indirectly deriving system dependencies (124) of system behaviors of system components of a cleaning system (16, 200) of a motor vehicle (14) according to claim 1 or 2, characterized in that The output (204) includes resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of the cleaning process (30, 32, 34, 36, 38, 40) of the surface (20, 22, 24, 26, 28) of the motor vehicle (14).

4. The method (MDSD3) for indirectly deriving system dependencies (124) of system behaviors of system components of a cleaning system (16, 200) of a motor vehicle (14) according to claim 1, characterized in that The output quantity (204) includes process quantities (140, 141, 142, 143, 144, 145, 146, 147).

5. The method (MDSD3) for indirectly deriving system dependencies (124) of system behaviors of system components of a cleaning system (16, 200) of a motor vehicle (14) according to claim 1, characterized in that The input quantities (202) include humidity and / or temperature and / or rainfall and / or snowfall in the vicinity of the motor vehicle (14).

6. Method (MDSD3) for indirectly deriving system dependencies (124) of system behaviors of system components of a cleaning system (16, 200) of a motor vehicle (14) according to claim 1, characterized in that The input (202) includes a vehicle type.

7. The method (MDSD3) for indirectly deriving system dependencies (124) of system behaviors of system components of a cleaning system (16, 200) of a motor vehicle (14) according to claim 1, characterized in that The input quantity (204) includes the availability (220, 222, 224) of the sensor (50, 52, 54, 56, 56a, 56b, 58).

8. The method (MDSD3) for indirectly deriving system dependencies (124) of system behaviors of system components of a cleaning system (16, 200) of a motor vehicle (14) according to claim 1, characterized in that The input (204) includes the current coordinates of the motor vehicle (14).

9. The method (MDSD3) for indirectly deriving system dependencies (124) of system behaviors of system components of a cleaning system (16, 200) of a motor vehicle (14) according to claim 7, characterized in that The output (204) includes the availability (220, 222, 224) of the sensor (50, 52, 54, 56, 56a, 56b, 58) and / or an availability gain (229) due to the cleaning process (30, 32, 34, 36, 38, 40).

10. The method (MDSD3) for indirectly deriving system dependencies (124) of system behaviors of system components of a cleaning system (16, 200) of a motor vehicle (14) according to claim 1, characterized in that The system dependencies (124) are determined by means of regression analysis.

11. Method (MDSD3) for indirectly deriving system dependencies (124) of system behaviors of system components of a cleaning system (16, 200) of a motor vehicle (14) according to claim 1, characterized in that The system dependency (124) is determined in the form of a curve.

12. Method (MDSD3) for indirectly deriving system dependencies (124) of system behaviors of system components of a cleaning system (16, 200) of a motor vehicle (14) according to claim 1, characterized in that The system dependencies (124) are determined by means of an optimization process.

13. The method (MDSD3) for indirectly deriving system dependencies (124) of system behaviors of system components of a cleaning system (16, 200) of a motor vehicle (14) according to claim 1, characterized in that The system dependencies (124) are derived using the data sets (DP1, DP2, DP3, DP4) of the dependency table (DT) from an already existing database (154).

14. Method (MDSD3) for indirectly deriving system dependencies (124) of system behaviors of system components of a cleaning system (16, 200) of a motor vehicle (14) according to claim 13, characterized in that The existing database (154) is continuously expanded.

15. Method (MDSD3) for indirectly deriving system dependencies (124) of system behaviors of system components of a cleaning system (16, 200) of a motor vehicle (14) according to claim 1, characterized in that The new data set (DP1, DP2, DP3, DP4) replaces the data set (DP1, DP2, DP3, DP4) in the dependency table (DT) that deviates the most from the derived system dependency (124).

16. A method for diagnosing the system behavior of system components of a cleaning system (16, 200) of a motor vehicle (14), wherein an output quantity (204) depends on an input quantity (202) by means of the system behavior of the system components of the cleaning system (16, 200), wherein the actual output quantity (204) exceeds the upper threshold quantity and / or the actual output quantity (204) drops below the lower threshold quantity indicative of a deviation of the actual system behavior from the expected system behavior, The method comprises the following steps: - determining the input quantity (202); - determining the actual output (204); - retrieving said upper threshold amount and / or said lower threshold amount; - comparing the actual output quantity (204) with the upper threshold quantity and / or the lower threshold quantity; - if the actual output exceeds the upper threshold amount, calculating the deviation between the actual output and the upper threshold amount, and / or if the actual output drops to the lower threshold amount, calculating the deviation between the actual output and the lower threshold amount; as well as - storing a diagnostic signal if the actual output quantity (204) exceeds the upper threshold quantity and / or if the actual output quantity (204) falls below the lower threshold quantity.

17. A method for diagnosing a deviation between actual and expected system behavior of a system component of a cleaning system (16, 200) of a motor vehicle (14), wherein the output quantity (204) depends on the input quantity (202) by means of the system behavior of the system components of the cleaning system (16, 200), wherein the actual system behavior depending on the input quantity (202) is represented by an actual output quantity (204), and the expected system behavior depending on the input quantity (202) is represented by an expected output quantity (204), wherein the expected system behavior is represented by a dependency table (DT) or at least one data set (DP1, DP2, DP3, DP4) of system dependencies (124), The method comprises the following steps: - determining the input quantity (202); - determining the actual output (204); - Determine the expected output (204) by the following steps: ○ Selecting the data set (DP1, DP2, DP3, DP4) that best matches the input quantity (202) from the dependency table (DT), reading the output quantity (204) stored in the selected data set (DP1, DP2, DP3, DP4) and using it as the expected output quantity (204); or ○ Selecting two data sets (DP1, DP2, DP3, DP4) that best match the input quantity (202) from the dependency table (DT), and determining the expected output quantity (204) using linear interpolation based on the two selected data sets (DP1, DP2, DP3, DP4); or ○ Calculating the expected output (204) by plugging the input (202) into the system dependencies (124); - calculating a deviation between the actual output (204) and the expected output (204); and If the deviation is greater than 10% of the expected output (204), a diagnostic signal is stored.

18. The method according to claim 16, wherein The deviation includes a time course.

19. The method according to claim 18, characterized in that The time course of the deviation is examined against the step response.

20. The method according to claim 18, wherein At least two time courses of the deviation are examined to determine the presence of a drift of the deviation over time.

21. A method for selecting a solution strategy from a list of solution strategies contained in a database (154) depending on a current diagnostic signal received according to the method of one of claims 16 to 20, wherein the list of solution strategies contains at least one solution strategy associated with the diagnostic signal, wherein the solution strategy selected from the list of solution strategies is the one whose associated diagnostic signal best matches the current diagnostic signal.

22. Use of a solution strategy selected by the method according to claim 21, by - sending a signal to the driver and / or manufacturer of the motor vehicle (14), and / or - improving the system behavior by applying said selected solution strategy to the cleaning system (16, 200), and / or - planned maintenance or repair of the cleaning system (16, 200).

23. A cleaning method (10) for resource-efficient cleaning of at least one surface (20, 22, 24, 26, 28) of a motor vehicle (14), wherein the motor vehicle (14) includes 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 a surface (20, 22, 24, 26, 28), 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 a surface (20, 22, 24, 26, 28) and comprises a cleaning cycle (38a, 40a) including a start time (38b, 40b) and an end time (38c, 40c), The cleaning system (16) includes 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 pipeline (80, 82, 84, 86, 88), wherein the sensor (50, 52, 54, 56, 56a, 56b, 58) is adapted to detect at least one measured variable (100, 102, 104, 106, 107, 108), process variable (140, 141, 142, 143, 144, 145, 146, 147), and / or controlled variable (110, 111, 112, 113, 114, 115, 116, 117, 118, 119), and transmit the measured variable (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 bring a cleaning fluid (64) into operative connection with 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 variable (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) 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 set points of the control quantities (110, 111, 112, 113, 114, 115, 116, 117, 118, 119), It is characterized by: The cleaning method comprises process steps for indirectly deriving system dependencies (124) of system behaviors of system components of a cleaning system (16, 200) of a motor vehicle (14) according to a method according to one of claims 1 to 15, and / or Process steps for diagnosing the system behavior of system components of a cleaning system (16, 200) of a motor vehicle (14) according to the method of claim 16 or one of claims 18 to 20, and / or Process step for diagnosing deviations between actual and expected system behavior of system components of a cleaning system (16, 200) of a motor vehicle (14) according to a method according to one of claims 17 to 20, and / or The process step for selecting a solution strategy according to the method of claim 21, and / or Process steps for using the selected solution strategy according to the use of claim 22.

24. 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) comprises at least one fluid reservoir (62), and / or wherein the cleaning system (16) is adapted to perform a method (MDSD3) for indirectly deriving system dependencies (124) of system behaviors of system components of a cleaning system (16, 200) of a motor vehicle (14) according to one of claims 1 to 15, and / or adapted to carry out a method according to claim 16 for diagnosing a system behavior of a system component of a cleaning system (16, 200) of a motor vehicle (14), and / or adapted to carry out a method for diagnosing deviations between actual and expected system behavior of a system component of a cleaning system (16, 200) of a motor vehicle (14) according to one of claims 17 to 20, and / or is adapted to carry out the method according to claim 21 for selecting a solution strategy from a list of solution strategies contained in a database (154) as a function of the current diagnostic signal, and / or adapted for use with a selected resolution strategy according to claim 22, and / or The cleaning system (16) is adapted to perform a cleaning method (10) for resource-efficient cleaning of at least one surface (20, 22, 24, 26, 28) of a motor vehicle (14) by means of a cleaning method according to claim 23.

25. A motor vehicle (14), wherein the motor vehicle (14) comprises a cleaning system (16) according to claim 24, and / or wherein the motor vehicle (14) is adapted to perform the cleaning method (10) for resource-efficient cleaning of at least one surface (20, 22, 24, 26, 28) of a motor vehicle (14) according to claim 23, and / or wherein the motor vehicle (14) is adapted to carry out a method (MDSD3) for indirectly deriving system dependencies (124) of system behaviors of system components of a cleaning system (16, 200) of a motor vehicle (14) according to one of claims 1 to 15, and / or adapted to carry out a method according to claim 16 for diagnosing a system behavior of a system component of a cleaning system (16, 200) of a motor vehicle (14), and / or adapted to carry out a method for diagnosing deviations between actual and expected system behavior of a system component of a cleaning system (16, 200) of a motor vehicle (14) according to one of claims 17 to 20, and / or is adapted to carry out the method according to claim 21 for selecting a solution strategy from a list of solution strategies contained in a database (154) as a function of the current diagnostic signal, and / or adapted for use with a selected resolution strategy according to claim 22 .

Images