Method for indirectly deriving systematic dependencies of system behavior of system components of a cleaning system, diagnostic method, method for selecting a solution strategy, use of the solution strategy, cleaning method, cleaning system, automobile

Abstract

The present invention relates to a method for indirectly deriving systematic dependencies of the system behavior of system components of a washing system of a motor vehicle, the washing system being adapted for washing at least one surface of the motor vehicle by a washing process, preferably adapted for resource-efficient washing, particularly preferably adapted for resource-saving washing. Furthermore, the present invention relates to a diagnostic method, a method for selecting a solution strategy, use of the solution strategy, a washing method, a washing system and a motor vehicle.

Description

[Technical Field]

[0001] The present invention relates to a method for indirectly deriving systematic dependencies of the system behavior of system components of a washing system, a diagnostic method, a method for selecting a solution strategy, use of the solution strategy, a washing method, a washing system and a vehicle.

[0002] In particular, the present invention relates to a cleaning method, a method for indirectly deriving systematic dependencies of the system behavior of a cleaning system of a vehicle, particularly preferably of the system behavior of a cleaning process of a vehicle surface, a method for optimizing resource requirements for a cleaning process of a vehicle surface, a method for determining a cleaning strategy for cleaning a surface to be cleaned of a vehicle, a method for indirectly deriving systematic dependencies of the system behavior of system components of a vehicle cleaning system, a method for diagnosing deviations between actual and expected system behavior of system components of a vehicle cleaning system, a method for selecting a solution strategy, use of the selected solution strategy, a method for indirectly deriving systematic dependencies of the system behavior of a fouling process of a vehicle surface, use of dependency tables and / or systematic dependencies for determining the expected availability of vehicles not yet covered at a distance or operating time, determining the expected distance or operating time of vehicles not yet covered when an availability threshold is reached. use of dependency tables and / or systematic dependencies for optimizing resource requirements for a cleaning process of a surface of a vehicle, use of dependency tables and / or systematic dependencies for determining a cleaning strategy for cleaning a surface to be cleaned of a vehicle, use of dependency tables and / or systematic dependencies for determining a required expected increase in availability, use of systematic dependencies derived by a method for indirectly deriving systematic dependencies for resource-efficient cleaning of at least one surface of a vehicle, use of control quantity setpoints derived by a method for optimizing resource requirements for a cleaning process of a surface of a vehicle for resource-efficient cleaning of at least one surface of a vehicle, use of a cleaning strategy derived by a method for determining a cleaning strategy for resource-efficient cleaning of at least one surface of a vehicle for cleaning a surface to be cleaned of a vehicle, a cleaning system, and a vehicle.

[0003] The steady expansion of driver assistance systems in recent years has led to an increase in the number of sensors installed in automobiles.

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

[0005] The increase in the number of sensors has also been accompanied by an increase in the need for cleaning, as these sensors rely on unexcessively clean surfaces for functional sensor operation and therefore the continued operation of these safety features and / or the operation of (partially) autonomous vehicles.

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

[0007] Furthermore, as the number of sensors installed in cars increases, the failure of one sensor usually leads to the failure of the driver assistance system, but multiple sensors make it possible to obtain some data redundantly.

[0008] When saving resources, the question arises as to which cleaning strategy can maintain the functionality of the driver assistance systems for as long as possible without the need to replenish cleaning resources and / or which sensors can be ignored during cleaning or can be cleaned with fewer resources.

[0009] Therefore, the decision-making process for properly cleaning a sensor has become more complex. There are many influences that determine proper cleaning and how this is achieved.

[0010] State-of-the-art washing of the front and / or rear windscreen of a motor vehicle is known in particular by means of windscreen wipers, whereby washing liquid can also be applied to the front and / or rear windscreen.

[0011] A device for controlling a wiping and / or rinsing system for a windshield is already known from document EP 0 932 533 A1. A sensor device measures the wetness or contamination of the windshield. When wetness or contamination of the windshield is detected and the ignition key is pressed or reverse gear is engaged, the wiping and / or rinsing system is switched on. This ensures, as a preventative measure, a clear view through the vehicle window when the vehicle is started and reverse gear is engaged. Depending on the degree of wetness and / or contamination, it is also possible to specify the period for which the wiping and / or rinsing system is switched on.

[0012] DE 103 07 216 A1 discloses a process for operating a windshield washer / wiper system for a motor vehicle 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 washer fluid. The wiper speed during the washing process is adaptively controlled by the electronic control unit depending on driving conditions and / or environmental input parameters.

[0013] DE 10 2009 040 993 A1 reveals a device for operating a wiping and / or rinsing system for a vehicle windscreen, having a control device for controlling a cleaning process of the wiping and / or rinsing system, wherein the windscreen of the vehicle can be exposed to a cleaning fluid of the rinsing system and / or the wipers of the wiper system can be moved in contact with the windscreen accordingly, the control means is adapted to determine a degree of contamination and / or a degree of wetting of the disk in response to the at least one detected information and to set at least one specific parameter of the cleaning process in response to the determined degree of contamination and / or degree of wetting, the control means is adapted to determine a degree of contamination and / or a degree of wetting of the disk during the cleaning process and to adjust the at least one specific parameter in response to the degree of contamination and / or degree of wetting during the cleaning process, predetermined multiple value combinations for at least two specific parameters of the cleaning process are stored in the control means, and the control means is adapted to select a value combination from the multiple value combinations in response to the degree of contamination and / or degree of wetting and to adjust the at least two specific parameters in response to the selected value combination.

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

[0015] According to a first aspect of the present invention, a task is a washing method for resource-efficient washing, preferably resource-saving washing, of at least one surface of a motor vehicle, wherein the motor vehicle exhibits a washing system and at least one sensor, the sensor being operatively connected to the one surface, the washing method exhibiting at least one washing process, the washing process being adapted to wash the one surface and exhibiting a washing duration comprising a start time and an end time, the washing system exhibiting an electronic control unit, preferably a washing fluid distribution system comprising at least one fluid reservoir, at least one nozzle, and at least one washing fluid line. 1. A washing method according to claim 1, wherein a sensor is adapted to detect at least one measured quantity, preferably sensor availability, a throughput, preferably humidity and / or temperature in the vicinity of the motor vehicle, and / or an amount of rainfall and / or snowfall, and / or coordinates of the motor vehicle, and / or a control quantity, and to transmit the measured quantity to an electronic control unit, a nozzle is adapted to operatively connect a washing liquid with a surface, and the electronic control unit is adapted to control and / or regulate the washing process by at least one control quantity of the washing process, and a resource requirement of the washing process depends on a control quantity setpoint, the electronic control unit controls the resource-efficient, preferably resource-saving, washing in response to a dependency table representing at least two data sets, preferably representing at least 50 data sets, particularly preferably representing at least 200 data sets, each data set representing at least one input quantity of the washing system, preferably a processing quantity, preferably humidity and / or temperature in the vicinity of the motor vehicle, and / or rainfall and / or snowfall amount, and / or coordinates of the motor vehicle, and / or control quantity, and / or vehicle type, and / or sensor availability, stored in an ordered manner relative to one another, and at least one output quantity of the washing system, preferably resource requirements of the washing process and / or sensor availability, and / or the electronic control unit controls resource-efficient washing, preferably resource-saving washing, depending on a systematic dependency of the system behavior of the washing system, in particular of the system behavior of the washing process of the surface of a vehicle, between an input quantity of the washing system, preferably at least one control quantity of the washing process and / or at least one processing quantity, preferably humidity and / or temperature in the vicinity of the vehicle, and / or the amount of rainfall and / or snowfall, and / or the coordinates of the vehicle, and / or the vehicle type, and / or sensor availability, and an output quantity of the washing system, preferably resource requirements of the washing process and / or sensor availability, in particular depending on a systematic dependency derived by the method for indirectly deriving a systematic dependency of the system behavior of a washing system of a vehicle according to the second aspect of the present specification, and / or an electronic control unit controls a resource-efficient cleaning, preferably a resource-saving cleaning applying a control quantity setpoint, particularly preferably a control quantity setpoint derived by the method according to the third aspect of the invention, and / or an electronic control unit controls resource-efficient cleaning, preferably resource-saving cleaning applying a cleaning strategy, particularly preferably applying a cleaning strategy derived by the method according to the fourth aspect of the present invention, and / or a washing method comprising process steps for indirectly deriving systematic dependencies of the system behavior of system components of a washing system of a motor vehicle, preferably process steps for indirectly deriving systematic dependencies according to the fifth aspect of the present invention, and / or a washing method comprising process steps for diagnosing the system behavior of a system component of a washing system of a motor vehicle, preferably a process step for diagnosing the system behavior of a system component of a washing system according to the first alternative of the sixth aspect of the present invention, and / or a washing method comprising a process step for diagnosing deviations between actual and expected system behavior of a system component of a washing system of a motor vehicle, preferably a process step for diagnosing deviations between actual and expected system behavior of a system component of a washing system according to the second alternative of the sixth aspect of the present invention, and / or 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, and / or the cleaning method comprises process steps for using a selected solution strategy, preferably for using a selected solution strategy according to the eighth aspect of the present invention, and / or a cleaning method comprising process steps for indirectly deriving a systematic dependency of the system behavior of a fouling process on a surface of a motor vehicle, preferably a process step for indirectly deriving a systematic dependency according to the ninth aspect of the present invention, and / or The cleaning method is a dependency table representing at least two data sets, preferably representing at least 50 data sets, particularly preferably representing at least 200 data sets, each data set being stored in an ordered manner relative to one another, representing at least one input quantity of the fouling process, in particular the vehicle distance traveled between the first availability and the second availability and / or the operating time covering the vehicle distance traveled between the first availability and the second availability and / or the driving speed of the vehicle, preferably the driving speed along the path between the first availability and the second availability, and / or the throughput, preferably humidity, particularly preferably the first availability a dependency table showing the course of humidity along the path between the first availability and the second availability and / or the temperature in the vicinity of the vehicle, particularly preferably the course of temperature along the path between the first availability and the second availability and / or the amount of rainfall, particularly preferably the course of rainfall along the path between the first availability and the second availability and / or the amount of snowfall, particularly preferably the course of snowfall along the path between the first availability and the second availability, and / or the coordinates of the vehicle, particularly preferably the coordinates of the vehicle along the path between the first availability and the second availability, and / or the first availability and the evaluated change in the availability of the sensor, and / or - process steps for using the systematic dependence of a fouling process of a surface of a motor vehicle on a system behavior, preferably derived by the method for indirectly deriving systematic dependence according to the ninth aspect of the present invention, for a resource-efficient, preferably resource-saving, cleaning of at least one surface of a motor vehicle, Preferably, determining the expected availability of a vehicle over a distance or operating time that has not yet been covered according to the tenth aspect of the present invention; and / or When an availability threshold is reached, preferably determining the expected distance or expected operating time of the not yet covered vehicle according to the eleventh aspect of the invention, and / or Optimizing the resource requirements for a cleaning process of an automotive surface, in particular by applying the method for optimizing the resource requirements for a cleaning process of an automotive surface according to the third aspect of the present invention, and / or determining a cleaning strategy for cleaning a surface to be cleaned of a motor vehicle, in particular 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 present invention, and / or Preferably, the problem is solved by a cleaning method according to a fourteenth aspect of the present invention, characterized in that it comprises a process step for determining an expected increase in availability, wherein the sum of the actual availability and the required expected increase in availability is sufficient to achieve the distance or operating time not yet covered by the vehicle, so that the availability threshold is not exceeded.

[0016] Let's explain the terminology in detail. First of all, it should be clearly pointed out that in the context of this patent application, indefinite articles and numerals such as "1", "2", etc. should normally be understood as "at least" information, i.e. "at least one...", "at least two...", etc., unless this is clearly evident from the respective context or it is obvious to a person skilled in the art that they can only mean "exactly one...", "exactly two...", etc., or it is technically necessary.

[0017] In the context of this patent application, the term "in particular" should always be understood as meaning that this term introduces an optional preferential feature. This expression should not be understood as "i.e."

[0018] A "washing method" is a method for cleaning at least one surface or surface component of a vehicle surface, in which impurities are reduced or removed. Preferably, the driver of the vehicle can select a washing mode in the automatic washing method, and the washing method is performed automatically or semi-automatically, as required to replenish resources required for the washing method.

[0019] In particular, the washing process may be performed and / or initiated manually, in particular by the driver of the vehicle.

[0020] Particular preference is given to the possibility that the cleaning method for cleaning at least one component of the surface of the vehicle may be carried out automatically during operation of the vehicle and / or outside of the vehicle's operating hours and therefore may be carried out autonomously, apart from replenishing the necessary resources.

[0021] Cleaning is understood as the use of cleaning means such as water, air, detergents and / or wiping elements and / or mechanical cleaning elements and / or vibration-based cleaning elements and / or ultrasonic-based cleaning elements for cleaning. In particular, cleaning does not mean achieving a completely clean surface, but the use of cleaning means means reducing contamination of the surface.

[0022] The "cleaning fluid" can be any fluid that can be used as a cleaning means, preferably water, air, cleaning agent, etc.

[0023] The cleaning method preferentially uses one or more "cleaning processes", where the cleaning process relates to cleaning one surface. Each cleaning process indicates a "cleaning period" during which at least one cleaning means is operatively connected to the corresponding surface, and the cleaning period indicates a "start time" and an "end time".

[0024] In particular, the end time of the cleaning process should also be understood as the end time of the evaluation phase of the cleaning process, especially if the evaluation of the cleaning process is also carried out during the execution of the cleaning process, and the evaluation point and the cleaning process have a common start time, but any deviating end time, preferably the end time of the evaluation period, ends before the end time of the cleaning process. In both cases, the term end time refers to the end time of the cleaning process and / or the end time of the evaluation process of the cleaning process, depending on the question under consideration.

[0025] It should be considered in particular that a single cleaning process, in the context of the evaluation of a cleaning process, leads to several data sets, the different data sets preferably differing only by the end time of the evaluation of the cleaning process.

[0026] "Surface" is a surface element of the motor vehicle. A preferred term for surface is the windshield and / or rear window and / or side window of the motor vehicle. Furthermore, a surface is preferably understood as a surface element behind which a sensor is arranged. Another preferred term for surface is a part of the surface of the motor vehicle that is visible from the outside, which also includes hidden surfaces, such as in particular parts of the wheel arch liner in the wheel arch of the motor vehicle.

[0027] Surfaces may also be understood as surface elements that are located inside the motor vehicle, preferably in the interior of the motor vehicle and / or in the engine compartment of the motor vehicle.

[0028] A "vehicle" or "motor vehicle" is generally understood as a self-propelled vehicle, generally wheeled, not operating on rails, used for the transport of people or goods.

[0029] Preferably, propulsion in a vehicle is provided by an engine or motor, typically an internal combustion engine or an electric motor, or some combination of the two, such as hybrid electric vehicles and plug-in hybrids.

[0030] A "cleaning system" is a system that provides all the structural elements necessary for a cleaning method and therefore also for a physical cleaning process.

[0031] The cleaning system preferably includes a cleaning fluid dispensing system and other electrical and / or electronic components.

[0032] "Washing fluid distribution system" means a system designed to provide washing fluid to the surface of an automobile being washed.

[0033] Preferably, the cleaning fluid distribution system exhibits at least one "cleaning fluid line" particularly adapted to convey cleaning fluid from a pump and / or a cleaning fluid reservoir to the nozzles.

[0034] A "nozzle" is a device through which cleaning fluid can leave the cleaning system and is designed to bring the cleaning fluid into interaction with, and preferably into operative connection with, the surface to be cleaned.

[0035] Preferably, the nozzle is a device designed to control the direction or characteristics of the cleaning fluid as it exits the cleaning fluid dispensing system.

[0036] Preferably, the nozzle exhibits actuation means designed to influence the direction in which the cleaning fluid leaves the cleaning fluid distribution system.

[0037] Preferably, the nozzle exhibits second actuation means designed to influence the characteristics, preferably the velocity, at which the cleaning fluid leaves the cleaning fluid dispensing system.

[0038] Preferably, the cleaning fluid dispensing system comprises an "electric pump" designed to pump the cleaning fluid.

[0039] The washer fluid distribution system includes a "washing fluid reservoir" designed to store the washer fluid on the vehicle. An electric pump is preferably integrated into the washer fluid reservoir.

[0040] The electric pump is preferably connected to the cleaning fluid reservoir and the nozzle by a "cleaning fluid line" which is preferably designed to guide the cleaning fluid.

[0041] The electronic components of the cleaning system may preferably include an electronic control unit and / or a data processing system, which may also be integrated into the electronic control unit.

[0042] An "electronic control unit" (ECU) is any system embedded in automotive electronics that controls one or more electrical systems or subsystems in a vehicle.

[0043] The electronic control unit is preferably adapted to execute a washing method, particularly preferably a washing method according to the first aspect of the invention, and / or to execute a method for indirectly deriving systematic dependencies, preferably the system behavior of a washing system of a motor vehicle, particularly preferably the systematic dependencies of the system behavior of a washing process of a surface of a motor vehicle, particularly preferably the method for indirectly deriving systematic dependencies according to the second aspect of the invention, and / or to execute a method for indirectly deriving systematic dependencies of the system behavior of system components of a washing system of a motor vehicle, particularly preferably the method for indirectly deriving systematic dependencies according to the fifth aspect of the invention, and / or to execute a method for indirectly deriving systematic dependencies of the system behavior of a fouling process of a surface of a motor vehicle, particularly preferably the method for indirectly deriving systematic dependencies according to the ninth aspect of the invention, and / or to execute a method for optimizing resource requirements for a washing process of a surface of a motor vehicle, particularly preferably the method for optimizing resource requirements according to the first and / or second alternative of the third aspect of the invention, and / or to execute a washing strategy for washing surfaces to be washed of a motor vehicle. a method for determining a solution strategy, particularly preferably by implementing a method for determining a washing strategy according to the fourth aspect of the invention and / or a method for diagnosing deviations between actual and expected system behavior of system components of a washing system of a vehicle, particularly preferably by implementing a method for diagnosing deviations between actual and expected system behavior according to the sixth aspect of the invention and / or a method for selecting a solution strategy, particularly preferably by implementing a method for selecting a solution strategy according to the seventh aspect of the invention and / or using a selected solution strategy, particularly preferably by using a selected solution strategy according to the eighth aspect of the invention and / or using dependency tables and / or systematic dependencies to determine the expected availability of vehicles not yet covered in distance or operating time, particularly preferably by using dependency tables and / or systematic dependencies according to the tenth aspect of the invention and / or using dependency tables and / or systematic dependencies to determine the expected distance or operating time of vehicles not yet covered when an availability threshold is reached, particularly preferablyUsing dependency tables and / or systematic dependencies according to an eleventh aspect of the present invention and / or using dependency tables and / or systematic dependencies for optimizing resource requirements for a cleaning process of a surface of a motor vehicle, particularly preferred using dependency tables and / or systematic dependencies according to a twelfth aspect of the present invention and / or using dependency tables and / or systematic dependencies to determine a cleaning strategy for cleaning a surface of a motor vehicle to be cleaned, particularly preferred using dependency tables and / or systematic dependencies according to a thirteenth aspect of the present invention and / or using dependency tables and / or systematic dependencies to determine a required expected increase in availability, particularly preferred using dependency tables and / or systematic dependencies according to a fourteenth aspect of the present invention and / or using dependency tables and / or systematic dependencies to determine a required expected increase in availability of resources of at least one surface of a motor vehicle. using systematic dependencies derived by a method for indirectly deriving systematic dependencies for efficient cleaning, particularly preferably using systematic dependencies as defined in the fifteenth aspect of the present invention, and / or using control quantity setpoints derived by a method for optimizing the resource requirements of a cleaning process for a surface of a vehicle for resource-efficient cleaning of at least one surface of a vehicle, particularly preferably using control quantity setpoints as defined in the fifteenth aspect of the present invention, and / or using a cleaning strategy for cleaning a surface to be cleaned of the vehicle derived by a method for determining a cleaning strategy for resource-efficient cleaning of at least one surface of a vehicle, particularly preferably using a cleaning strategy as defined in the fifteenth aspect of the present invention, and / or being part of a cleaning system as defined in the sixteenth aspect of the present invention and / or being configured to be part of a vehicle as defined in the seventeenth aspect of the present invention,

[0044] Furthermore, the electronic control unit preferably comprises all structural electronic elements necessary for carrying out the cleaning method presented herein, preferably the cleaning method according to the first aspect of the invention.

[0045] Particular preference is given to the electronic control unit including a data processing system.

[0046] A "data processing system" is a combination of electronic components and processes that produces a defined set of outputs for a set of inputs, where the inputs and outputs are interpreted as data.

[0047] Preferably, the data processing system is a system that allows for an organized processing of data volumes with a view to obtaining information about these data volumes and / or changing these data volumes.

[0048] Preferably, the data processing system refers to a "data acquisition system."

[0049] A "sensor" or "detector" is a technological component that can measure specific physical or chemical properties and / or material compositions of its environment either qualitatively or quantitatively as "measurands." These quantities are measured by physical or chemical effects and converted into analog or digital electrical signals.

[0050] Preferably, the sensor exhibits an electronic data processing unit equipped to process the quantities detected by the sensor, in particular quantities derived from the original measured quantities.

[0051] In particular, it should be considered that such a data processing unit is capable of determining the contamination state of a surface operatively connected to the sensor, and preferably should be capable of determining the availability of 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 based on the measured quantities detected by the sensor.

[0052] Preferably, such an electronic data processing unit forms a unit with the sensor or is part of the electronic control unit of the motor vehicle.

[0053] A data processing unit of this type is preferably set up to process quantities recorded by several sensors.

[0054] The current value of a measurand is the "actual or current measurand value" and / or the "current or actual measurand value."

[0055] In particular, sensors should also be understood as virtual sensors. A "virtual sensor" qualitatively or quantitatively maps data of one or more measured quantities recorded by an imaging function to specific physical or chemical properties and / or material compositions of the environment. Thus, sensors can be both physical sensors or virtual sensors that qualitatively or quantitatively record quantities and / or conditions in the surrounding environment. In other words, virtual sensors determine quantities, particularly measured, controlled, or processed quantities, through mathematical definition.

[0056] Preferably, the sensor is understood to be an optical sensor.

[0057] Preferably, optical sensors are understood as cameras and / or lidar and / or radar and / or ultrasonic sensors.

[0058] The light sensor is preferably capable of determining the brightness level, ie the light intensity level.

[0059] In particular, it should be considered that the availability of a sensor can be determined by evaluating the light intensity level, preferably in comparison with the light intensity level of a second sensor whose field of view overlaps with that of the sensor.

[0060] In particular, the sensors include temperature sensors, pressure sensors, voltage sensors, current consumption sensors, radar sensors, ultrasonic sensors, and flow rate sensors.

[0061] A "measured value" is the current, i.e., actual, value of a "measurand". A "measurand setpoint" is a default value of the measurand. Preferably, a measurand is any quantity that can be measured or otherwise determined in such a way that the measured value of the measurand can be further processed electronically. In particular, a measurand is understood to be a quantity that represents a controlled quantity, a processed quantity, or the availability of a sensor.

[0062] Preferably, the measured quantity is vehicle speed.

[0063] Preferably, the measured values ​​of the measurands can be determined experimentally and / or numerically. In the case of an experimental investigation of the measured values ​​of the measurands, preferably, an experimental investigation of the entire vehicle in a laboratory or during normal vehicle operation, or of a module or component within the framework of a modular test bench, can be considered. Numerical investigations involve the measurement of the measured values, numerical analysis and / or numerical simulation within the framework of a physical model, and can also consider the entire vehicle or a module or component individually.

[0064] A measurement can also be understood as a quantity representing data, also referred to as "data representing a measurement." The data is preferably searchable data, preferably wirelessly available data, preferably weather in the vicinity of the vehicle and / or on the planned route, and / or current or actual coordinates of the vehicle. Furthermore, it is preferable to consider the data as sensor type, vehicle type, date of latest inspection of the sensor and / or washing system and / or vehicle, etc.

[0065] Measurements, measurands, and measurand-set values ​​should not be understood as pure scalar quantities or values, but whenever this is deemed technically reasonable, measurements, measurands, and measurand-set values ​​should be understood as vector quantities having multiple values ​​for each dimension of the vector quantity.

[0066] A "vehicle type" is a specific configuration of a vehicle. In particular, a vehicle type provides information about which surfaces a vehicle exhibits, how these surfaces are formed, and which sensors are hidden behind which surfaces.

[0067] The "Throughput Value" is the current value of the "Throughput Amount". The "Throughput Setpoint" is the default value of the "Throughput Amount". Preferably, the throughput should be understood as an amount that is suitable for influencing the cleaning process and the cleaning result, but cannot itself be influenced.

[0068] Preferably, the processing quantities and / or processing quantity settings and / or processing values ​​are not purely scalar quantities or values, but are vector quantities having multiple values ​​for each dimension of the vector quantity.

[0069] Preferably, the throughput is vehicle speed.

[0070] Preferably, the throughput is a system-related throughput related to the behavior of the system, preferably the behavior of a cleaning system, which is preferably exhibited by a systematic dependency, in other words, the system-related throughput depends on the controlled quantities of the system.

[0071] Preferably, the process quantity is an environmental process quantity related to the surrounding environment, preferably the environment surrounding the vehicle. Examples of environmental process quantities are the ambient temperature near the vehicle, the humidity near the vehicle, the air pressure near the vehicle, the current amount of rain and / or snow, etc.

[0072] In particular, the treatment amount is understood as the ambient temperature in the vicinity of the vehicle and / or the humidity in the vicinity of the vehicle and / or the actual solar radiation and / or the surface temperature of the surface to be cleaned.

[0073] The throughput quantities are preferably quantities that occur in or around the washing system and that can be influenced, at least indirectly, by the input quantities.

[0074] Preferably, the processing quantities are current, power consumption, flow pressure, operating time, fill level signal, reaction time, sensing time, leakage signal via sensor, flow meter signal, number of actuations, spray pattern, thermal monitoring signal, debris sensor signal, check valve signal, drip sensor signal, distance sensor signal, and / or force signal sensor.

[0075] The "controlled variable set value" is the default value of the actuator that is set to adjust the "controlled variable." The current value of the controlled variable is the "actual controlled variable value."

[0076] Preferably, a control quantity is to be understood as a quantity which is suitable for influencing the cleaning process and the cleaning result, which is adjusted to control the cleaning method and / or cleaning process, and preferably which is controlled to influence the cleaning method and / or cleaning process.

[0077] Preferably, the controlled variables and / or controlled variable setpoints and / or controlled values ​​are not purely scalar quantities or values, but are vector quantities having multiple values ​​for each dimension of the vector quantity.

[0078] Preferably, and in the case of a control system, a controlled variable setpoint is understood as a default value of the actuator that is set to adjust the controlled variable.

[0079] In particular, controlled variables are understood as the type of cleaning liquid, in particular water and / or air, and / or the type of cleaning agent and / or the proportion of cleaning agent in the cleaning liquid and / or the temperature of the cleaning liquid and / or the pressure of the cleaning liquid when it leaves the nozzle and / or the flow rate of the cleaning liquid 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.

[0080] Particular preference is given to the control amount being aimed at a desired, preferably resource-efficient, preferably resource-saving, cleaning objective of at least one surface of the motor vehicle.

[0081] Preferably, the control of the controlled variable pursues a multi-criteria objective, and the Pareto-optimal goal achievement aims at preferably resource-efficient, particularly preferably resource-saving, cleaning of at least one surface of the motor vehicle under one or more boundary conditions.

[0082] The "availability" of a technical system is a measure of the degree to which the system is able to perform its task.

[0083] According to a possible variant, availability specifies whether the system is able to perform its task in two permissible states.

[0084] Preferably, the surface in the first state is less dirty than the surface from the point of view of the sensor and / or from the point of view of the driver of the vehicle, and in the second state is less dirty.

[0085] According to a preferred variant, the availability also specifies the property values ​​that allow the system to perform its task.

[0086] A particular preference is that availability can assume a range of values ​​indicating intervals, where one interval limit of arrival means that the system can fully meet that requirement, and another interval limit of arrival means that the system will no longer be able to meet that requirement.

[0087] If the availability value is in the range between the interval limits, the system can still meet the requirements, but under more difficult conditions. In particular, the availability value reflects the degree of contamination of the surface of the vehicle, preferably the degree of contamination of the surface, preferably the surface of the sensor, particularly preferably the degree of contamination of the optical sensor and / or the surface of the vehicle driver.

[0088] Since in principle it can be assumed that the degree of contamination of the surface increases with the operating time of the vehicle until cleaning, when reproduced within an interval, the availability can preferably be interpreted as a measure of the period during which the technical system, preferably the sensor, already meets its requirements and / or can still meet its requirements, at least in part, until the technical system, preferably the sensor, has to be cleaned in order to be able to meet its requirements.

[0089] The availability may preferably have values ​​outside these spacing limits. An availability higher than the value of the spacing limit at which the associated sensor can fully meet its requirements indicates that the sensor can fully meet its requirements. An availability lower than the value of the spacing limit at which the associated sensor can no longer meet its requirements indicates that the sensor can no longer meet its requirements. In other words, the surface in operative connection with the sensor needs to be cleaned by a cleaning process so that the availability is improved again, in particular to a value at which the sensor can again perform at least part of its original task, and so that the surface can also be cleaned by passive cleaning processes such as rain and / or snowfall.

[0090] It is expressly pointed out that surface availability should be understood to mean both the availability of the surface for less severely impaired operation of the sensor and the availability of the surface, preferably the degree of purity of the surface, in particular the windshield and / or rear window, for less severely restricted visibility for the driver of the vehicle.

[0091] "Actual availability", i.e., current availability, is the availability that prevails at the present time.

[0092] "Expected availability" should preferably be understood as the estimated availability for a particular distance not yet covered and / or a particular operating time of a vehicle not yet driven.

[0093] The predicted availability can preferably be determined based on current and / or planned conditions, in particular the operating conditions of the vehicle, preferably by an estimation procedure as described in the tenth aspect of the present invention, and the predicted availability represents the availability at points in the vehicle's travel route that have not yet been traversed.

[0094] "Availability threshold" is understood as the threshold of availability, preferably requiring cleaning of the surface operatively connected to the sensor whose availability is considered here.

[0095] The "expected increase in availability" is the estimated increase in availability of the 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.

[0096] The expected increase in availability, i.e. the required expected increase in availability, can preferably be derived according to the fourteenth aspect of the present invention.

[0097] Depending on the context, a "change in availability" may be understood as an "increase in availability" or a "loss of availability." In either case, a change in availability should be understood as a change in the availability of a sensor operably connected to the surface.

[0098] A "resource" is a source or supply from which benefits are generated and has some degree of utility.

[0099] Preferably, a resource is understood here as something that can be used to clean the surfaces of the vehicle. In particular, this involves a cleaning liquid and / or a cleaning agent and / or energy and / or wiping elements, preferably wiping elements that can be replaced as needed.

[0100] "Resource requirements" is understood as the need for resources that are required for a cleaning process, in particular a cleaning process with defined control quantity setpoints.

[0101] "Resource-efficient cleaning" means that the cleaning of the surface being cleaned is optimized so that the ratio between cleaning effectiveness and cleaning power is taken into account. In other words, a resource-efficient cleaning method requires that the amount of control over the cleaning process be selected according to the fact that maximum cleaning success can be achieved with minimum effort.

[0102] The control quantity set points for resource-efficient washing may preferably be derived by a method for optimizing resource requirements for a vehicle washing process, preferably by a method according to the third aspect of the present invention.

[0103] "Resource-saving cleaning" is understood to mean that the cleaning of the surface to be cleaned is optimized with a priority cleaning objective to be achieved, which may preferably be based on the fact that the vehicle will not break down due to contamination of the surface, in particular due to contamination of the sensor surface, or due to a failure of the sensor function caused by the contamination. The priority cleaning objective may also be that the level of autonomy of the vehicle does not have to be given up due to contamination of the surface, in particular due to contamination of the sensor surface, or due to a failure of the sensor function caused by the contamination.

[0104] A washing strategy for resource-saving washing can preferably be derived by a method for determining a washing strategy for washing a surface to be washed of a motor vehicle, preferably by a method according to the fourth aspect of the present invention.

[0105] "Control" is understood as the monitoring and possible adjustment of input quantities to achieve an objective, in particular in response to the occurrence of a disturbance quantity.

[0106] A "disturbance amount" is an output amount in which the output amount value deviates from the desired output amount value.

[0107] Preferably, the disturbance quantity is availability.

[0108] Preferably, controlling means specifying control quantity setpoints for achieving a particular objective, in particular for carrying out a cleaning method for resource-efficient cleaning, preferably resource-saving cleaning, of at least one surface of a motor vehicle.

[0109] Preferably, controlling is understood as carrying out a cleaning method, preferably a cleaning method according to the first aspect of the present invention.

[0110] The term "regulating" refers to the automated interaction between the continuous acquisition of a measurand and the control of a system in response to a specified measurand. In particular, there is a continuous comparison of the measurand with the specified measurand.

[0111] The "operating conditions" of a vehicle are the conditions under which the vehicle is currently used.

[0112] Active operating conditions are preferably understood to mean that the vehicle is being used to achieve a target, preferably by active operation of the vehicle, to cover the distance between the start point and the planned end point.

[0113] Preferably, passive operation means that the vehicle is currently parked.

[0114] A "system" is understood as an entity of connected elements that form a common whole through relationships, connections, interrelationships, and / or interactions.

[0115] "System behavior" is understood as an observable change in the state of a system or the value of a state quantity. Preferably, such observable change in the state of a system or the value of a state quantity occurs as a function of changes in the values ​​of input quantities.

[0116] "Dependence," especially "systematic dependence," refers to a relationship of dependence of one thing on another, preferably a dependence between an output quantity of a system and an input quantity of the system. By changing one, a causal change in the other can be achieved. Functional dependence in the mathematical sense is not necessary in this context of systematic dependence, but is possible.

[0117] Preferably, a systematic dependency is understood as a description of the system behavior of a system, preferably a mathematical description, preferably a description of the system behavior of a cleaning system.

[0118] It should be clearly pointed out that systematic dependence is to be understood not only as a dependence between the pure scalar values ​​of the input quantities and the pure scalar values ​​of the output quantities, but also, if applicable, as a multidimensional dependence between the number of corresponding input quantities considered for systematic dependence with their respective associated values ​​and the output quantities dependent thereon with their respective associated values.

[0119] A "dependency table" is understood as a list of individual experiences regarding system behavior, preferably of a washing system, in the form of data sets, each data set indicating at least one input quantity, preferably an input quantity of the washing system, and at least one output quantity, preferably an output quantity of the washing system, stored in an ordered manner relative to each other.

[0120] Preferably, the experience regarding system behavior is preferably based on a single documented cleaning process collected under laboratory conditions and / or on a real vehicle and / or during real vehicle operation and / or based on a numerical model and represents the system operation being considered.

[0121] Thus, among other things, the dependency table can be advantageous for already documented experiences to be applied again later on, in particular by selecting the associated input quantity from a list of data sets in the dependency table depending on the output quantity to be achieved.

[0122] In other words, the dependency table, on the one hand, enables the empirical values ​​stored therein, in particular for the control of the cleaning process, to be constantly retrieved and reprocessed, and, at least where technically reasonable and possible in the sense of control variable set values, input quantities from the dependency table are used to control the cleaning process.

[0123] On the other hand, the data sets contained in the dependency tables may in particular be used as data points for deriving systematic dependencies according to the second and / or fifth and / or ninth aspects of the present invention.

[0124] An "input quantity" is defined as a quantity with the help of which a targeted intervention into a system, preferably a control or regulation system of a cleaning system, is carried out. Its instantaneous value is the "input quantity value".

[0125] Preferably, input quantities should not be understood as pure scalar quantities or values, but whenever this is deemed technically reasonable, input quantity values ​​and input quantities should be understood as vector input quantities having multiple values ​​for each dimension of the vector input quantity.

[0126] Preference is given to data representing input, controlled and / or measured quantities, in particular the weather in the vicinity of the vehicle and / or on the planned route and / or the current coordinates of the vehicle.

[0127] Preferably, in the case of a control system, the input variables are measured by numerical sensors so that the measured variables correspond to default values ​​of the control system.

[0128] Preferably, the input quantities comprise further data, in particular data providing information about the current position of the vehicle and / or the planned route of the vehicle and / or the route covered by the vehicle and / or the expected weather, in particular the local weather at each location of the vehicle's pre-planned route, in particular humidity and / or solar radiation and / or temperature and / or rainfall and / or snowfall.

[0129] Preferably, the value of the input quantity can be understood as the pressure of the cleaning liquid.

[0130] Preferably, the value of the input quantity can be understood as the temperature of the cleaning liquid.

[0131] Preferably, the input amount value can be understood as the amount of the mixture of the cleaning liquid, in particular of one or more additives.

[0132] Preferably, the input quantity values ​​may include, but are not limited to, the spray pattern, in particular an oscillating spray pattern and / or a continuous spray pattern and / or a pulsed spray pattern and / or the alignment of the spray to the surface to be cleaned or the characteristics of the spray pattern.

[0133] An "output quantity" is a quantity that comes from a system, in particular a cleaning system. Its instantaneous value is the "output quantity value."

[0134] Preferably, the output quantity should not be understood as a pure scalar quantity or value, but whenever this is deemed technically reasonable, the output quantity value and the output should be understood as a vector output quantity having multiple values ​​for each dimension of the vector output quantity.

[0135] Preferably, the value of the output quantity depends on the response of the system to the input quantities. The response of the system to the input quantities is determined by the system behavior and can be described by the systematic dependencies of the system.

[0136] Priority is given to the system-related throughput and / or resource requirements and / or availability of the cleaning process, preferably the availability of the sensor surface and / or the availability of the surface, preferably the purity of the surface, particularly the windshield and / or rear window, etc.

[0137] A "data acquisition system" is used to record physical quantities. Depending on the sensor used, it may be preferable to have an analog-to-digital converter and a measured quantity memory or data memory. The data acquisition system can preferably be set up to acquire multiple measured variables simultaneously.

[0138] An "electronic data processing and evaluation unit" is an electronic unit that processes data volumes in a systematic manner in order to obtain or modify information about such data volumes. Preferably, the data is recorded in a data set, processed by a person or machine according to a specified procedure, and the results are output.

[0139] 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 necessary subsets of the stored data in different, demand-oriented representation types for users and application programs.

[0140] Preferably, the database includes a dependency table.

[0141] Preferably, the database includes phylogenetic dependencies.

[0142] Preferably, the database may be local or distributed, especially in a data cloud.

[0143] Preferably, the remotely managed database may be accessed via wireless data transfer so that data may be received from the remotely managed database and data may be transferred to the remotely managed database.

[0144] Preferably, the database exhibits functions that allow the database to manage itself.

[0145] Preferably, the database is part of the working memory of the electronic data processing and evaluation unit.

[0146] Among other things, it is conceivable that the database will remove existing datasets as new datasets are entered, particularly using the dependency table. Priority can be given to removing datasets that show the greatest Euclidean distance to the statistical mean of the other datasets. Priority can be given to removing datasets that show the greatest deviation from systematic dependencies between the data.

[0147] A "dataset" is understood as a group of consecutively connected data fields, the data fields preferably representing values ​​of input quantities and / or values ​​of output quantities.

[0148] Preferably, the data set represents the first and second parameters of the method according to the second and / or fifth and / or ninth aspect of the present invention.

[0149] An "algorithm" is a clear set of instructions for solving a problem or class of problems. Preferably, an algorithm consists of a finite number of defined individual steps. The individual steps can therefore be implemented in a computer program for execution, but can also be formulated in human language. Preferably, an algorithm supports problem solving because a particular input, preferably a data set of input, can be transformed by the algorithm into a particular output.

[0150] A "curve" is understood as a two-dimensional, three-dimensional or multidimensional relationship between variables. Preferably, the systematic dependence can take the form of an m-th order (n+i)-dimensional curve, taking into account n-dimensional input quantities and i-dimensional output quantities.

[0151] Preferably, the curve is the image of a continuous function from the interval to the phase space.

[0152] The "coefficient of determination" is understood as the proportion of the variance in the dependent variable that can be predicted from the independent variables.

[0153] Preferably, the coefficient of determination provides a measure of how well the observed outcome is replicated by the model, based on the proportion of the total variation in the outcome that is explained by the model.

[0154] "Regression analysis" is understood as a set of statistical processes for estimating the relationship between variables. It includes many 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 understand how the typical value of a dependent variable changes when any one of the independent variables changes while the other independent variables are fixed.

[0155] Preferably, regression analysis is understood as one of the following analytical models: linear regression, simple regression, polynomial regression, generalized linear model, binomial regression or non-linear regression, etc.

[0156] An "optimization process" is understood as maximizing or minimizing a function by systematically selecting input values ​​from within a permitted set and calculating the value of the function.

[0157] "Self-learning optimization methods" is a category of algorithms that can also be classified under the general term "machine learning." The corresponding algorithms are characterized by the fact that, on the one hand, they learn from examples and, on the other hand, they are able to generalize the learned knowledge. Thus, such algorithms generate knowledge from experience.

[0158] "Optimization" means a process aimed at finding optimum values, in particular optimal values ​​of input quantities, by maximizing the achievement of a goal, in particular by minimizing or maximizing a corresponding objective function and / or by selecting values ​​of the input quantities that are known to allow or indicate the best achievement of the goal.

[0159] In particular, it should be explicitly noted that optimization does not necessarily mean that exact optimum values ​​of the input quantities are found.

[0160] "Distance" is understood as the distance between two points that have been, will be, or are to be covered by the vehicle.

[0161] Preferably, the distance is the shortest distance between two points that the vehicle can cover.

[0162] Preferably, the distance is the fastest connection between two points that the vehicle can cover.

[0163] Preferably, route planning to establish distances is performed with the aid of a navigation system.

[0164] The actual availability may be "sufficient to cover the distance to the next washing process" if it can be used to cover the next or planned distance before the next washing process without dropping below a predefined availability threshold. In other words, the available availability in this case is likely sufficient to be able to cover the planned distance to the next washing process in the car without losing the functionality of the sensors linked to the corresponding available area.

[0165] The "expected distance of the vehicle to be covered when the availability threshold is reached" is the expected distance that the vehicle can cover before reaching a predefined availability threshold.

[0166] "Operational time" is the period of vehicle use already elapsed, pending, or planned.

[0167] The actual availability may be "sufficient to fill the operating time until the next wash process" if it can be used to cover the pending or planned operating time before the next wash process without falling below a predefined availability threshold. In other words, the available availability in this case is likely sufficient to allow the car to cover the planned operating time until the next wash process without losing the functionality of the sensors linked to the corresponding available area.

[0168] The "expected operating time of the vehicle covered when the availability threshold is reached" is the expected operating time that the vehicle can cover until the predefined availability threshold is reached.

[0169] "Coordinates" are the geographic location of the vehicle on the Earth, and can be coordinates already traversed, actual or current coordinates, or coordinates on a planned route.

[0170] Preferably, the coordinates can also be understood as the course of coordinates on an already completed or planned route.

[0171] A "cleaning strategy" is a plan for how a cleaning system will behave in all possible situations. Thus, a cleaning strategy completely describes the behavior of a cleaning system.

[0172] Preferably, the cleaning strategy includes which surfaces to clean, when, and with what intensity.

[0173] Preferably, the cleaning strategy indicates a control variable set point for each selected sensor.

[0174] Preferably, the cleaning strategy depends on one or more influencing factors, in particular the actual availability of sensors.

[0175] The "wash mode" or "actual wash mode" is the operating mode of the wash system. By selecting a wash mode, the vehicle manufacturer and / or driver can influence which driver assistance systems must not fail due to sensor contamination, and the selected wash mode can also imply that no washes must be performed. This can have a direct impact on the availability of the driver assistance systems.

[0176] Since the cleaning mode determines whether or how many driver assistance systems are protected from failure due to excessive fouling caused by the cleaning measures, the choice of cleaning mode may also indirectly affect the "selected sensors" and therefore determine the number of "selected sensors" that should not undershoot the availability threshold.

[0177] The selected washing mode therefore also determines the resource consumption of the washing system, i.e. the expected remaining range of the vehicle with available washing resources.

[0178] Preferably, there may be more than one cleaning mode, and more than one cleaning mode may be selected simultaneously.

[0179] Preferably, the first cleaning mode has the meaning of "fully autonomous vehicle operation", which means that the cleaning system takes all necessary cleaning measures to ensure that the autonomous operation of the vehicle does not fail due to contamination of the vehicle's sensors.

[0180] Preferably, the second cleaning mode has the meaning "comfortable vehicle operation", which means that the cleaning system takes all necessary cleaning measures to ensure that the comfortable operation of the vehicle does not fail due to contamination of the vehicle's sensors. This includes, inter alia, the cleaning system maintaining the distance keeping, lane keeping, parking assistant, parking assistant and / or trailer assistant functions of the driver assistance systems by all necessary cleaning measures.

[0181] Preferably, the third cleaning mode has the meaning "safest possible vehicle operation", which means that the cleaning system takes all necessary cleaning measures to ensure that the safe operation of the vehicle does not fail due to contamination of the vehicle's sensors, which includes, among other things, that the cleaning system maintains the pedestrian recognition and / or road user recognition functions of the driver assistance systems by all necessary cleaning measures.

[0182] Preferably, the fourth washing mode has the meaning "to the best possible extent", which means that the washing system only carries out washing measures prescribed by law for the operation of the vehicle.

[0183] The cleaning mode "best possible coverage" is preferably used to achieve the best possible coverage of the vehicle with the available cleaning resources.

[0184] A "system component" is understood as any component of a cleaning system. It should be clearly pointed out that a system component can be understood as a complete cleaning system, as well as a single assembly of a cleaning system and a single component of a cleaning system.

[0185] In particular, the term system component is used in the context of diagnosing a cleaning system. Because all physical components of a cleaning system can also be diagnosed by at least one diagnostic means, the term system component specifically refers to a component or assembly or cleaning system that is the subject of observation and / or analysis related to the diagnosis.

[0186] "Current" may flow in an electric circuit under certain conditions. Furthermore, an electric circuit may have consumers, particularly, preferably consumers that enable useful applications in the form of system components. Consumers may have "power consumption" that represents the demand for energy by the consumer.

[0187] Consumers that enable electrical applications require energy to perform their work. Specifically, it is considered that the power consumption of a consumer performing the same task may vary. The reasons for this may be different operating conditions, in particular different ambient temperatures, and / or the effects of consumer aging.

[0188] Preferably, the current signal indicates information about magnetic flux, electrical transients, electrical noise, electrical noise, or the like.

[0189] "Fluid pressure" is the pressure of a fluid, in particular a cleaning liquid, and the fluid pressure consists of a static and a dynamic component. The local fluid pressure can be measured locally, in particular with a pressure sensor.

[0190] "Operating time" is the individual operating time of a system component.

[0191] A "filling level signal" is understood as information that directly indicates the value of the filling level in the storage container and indirectly indicates the amount of stored substance.

[0192] "Response time" is generally understood to be the time between action and reaction, and in particular the time between measurement and the effect of the measurement.

[0193] The "sensing time" is the time during which a change in signal can be perceived, specifically the time between the start of the change in the storage tank level and the end of the change in the storage tank level.

[0194] A "flow meter signal" is part of the information provided by a flow meter, which provides information about the amount of liquid flowing through a channel in a given unit of time, in particular the amount of cleaning liquid flowing through the channel.

[0195] A "leak sensor signal" is information provided by a leak sensor that provides information regarding the presence of a leak and / or the flow rate of a leaking liquid. In particular, a leak sensor may include a sensor attached to the junction of two fluid channels.

[0196] "Number of operations" is the number of times a system component has been used. In particular, it can take into account the number of pumping operations already performed by a pump or the number of heating operations already performed by a heater.

[0197] "Spray pattern" is the pattern that cleaning fluid leaves on the surface being cleaned after leaving the cleaning nozzle.

[0198] "Thermal monitoring signal" is understood as information provided by a thermal monitoring system that provides information about the temperature of a surface and / or the heat flow over a surface.

[0199] A "debris sensor signal" is understood as information provided by a debris sensor that provides information regarding the amount and / or type of foreign matter in the cleaning system.

[0200] A "check valve signal" is understood to be a piece of information provided by a check valve that indicates its position.

[0201] "Drip sensor signal" is understood as information provided by the drip sensor indicating the presence of liquid and / or the amount of liquid and / or the intensity of rain and / or snow.

[0202] "Distance sensor signal" is understood as information provided by a distance sensor that indicates the distance between the sensor and an object detected by the sensor.

[0203] A "force sensor signal" is understood as information provided by a force sensor that indicates the presence and / or magnitude of an existing force.

[0204] "Actual system behavior" is the observable system behavior of the system components of a washing system for a motor vehicle. Preferably, the actual system behavior can be monitored and / or determined by a measurement system. Preferably, the actual system behavior can be described by actual output quantities, preferably determined by the measurement system, preferably by sensors.

[0205] It should be clearly pointed out that the actual output quantity can be understood as a scalar or a vector quantity. If the actual output quantity has only one parameter, it is a scalar quantity. If the actual output quantity has multiple parameters, especially the course of the parameters over time, it is a vector quantity.

[0206] Preferably, the actual output quantities are designed to represent the system behavior of the system components, preferably in all parameters relevant to characterizing the system behavior.

[0207] The expected system behavior is the system behavior of the system components for the car wash system, and is predicted based on empirical values. Similar to the actual system behavior and actual output, the expected system behavior can be expressed as a "predicted output."

[0208] It should be explicitly pointed out that the expected output quantities can also be scalar or vector quantities similar to the actual output quantities.

[0209] "Deviation" is the difference between the expected output quantity and the actual output quantity. Therefore, deviation can also be a scalar or vector quantity. Preferably, deviation indicates the dimension of the actual output quantity.

[0210] In particular, the deviation may represent a typical measurement error of the system, which may vary in size depending on any dimension of the deviation, and the size of the measurement error may depend, in particular, on the measurement system used to determine the output quantity.

[0211] Numerical deviation exists if the deviation is within a specified measurement error, but in this case the actual system behavior preferably does not deviate from the expected system behavior.

[0212] The system behavior of the system components of the washing system for automobiles may be subject to measurement errors as well as additional variations and / or deviations that may be within expected ranges. These expected insignificant deviations and / or variations may be different for each dimension of the output quantity.

[0213] A "time process", in particular a deviation time process, is a data series as a function of time, in particular a data series involving deviation data.

[0214] A data series may consist of at least two, preferably at least 10, preferably at least 20 data points distributed over time.

[0215] Preferably, the data points are equidistant from each other in time.

[0216] Preferably, the time interval between the data points increases. Particular preference is given to the time distance of the data points being proportional to the logarithm of 1 from time.

[0217] 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 quantity. It can be advantageously used to characterize linear time-invariant systems. The time course of the step response can be used to draw conclusions about the damping present in the system, for example, to advantageously determine whether there is a blockage of a flow channel for the cleaning liquid, in particular.

[0218] A "drift" is a systematic deviation that varies continuously in one direction.

[0219] Preferably, the drift of the output signal of a system component can make it possible to make statements about the aging phenomenon of the system component. The drift can in particular be used to determine how long a system component can still be used. In particular, the drift can be used to analyze when a system component needs to be replaced in order to avoid failure of the system component.

[0220] Overall, the system behavior of the system components preferably deviates from the acceptable system behavior only when the output quantity exceeds an "upper threshold quantity" and / or falls below a "lower threshold quantity," taking into account measurement error and expected minor variations.

[0221] It should be clearly pointed out that the upper and / or lower threshold amounts may be scalar or vector quantities, as well as expected or actual output quantities or deviations. Preferably, the upper and / or lower threshold amounts indicate the dimension of the output quantity.

[0222] Preferably, this is an unacceptable deviation if the output amount exceeds an upper threshold amount in one dimension or falls below a lower threshold amount in one dimension.

[0223] Preferably, the upper and lower thresholds may depend on the input quantity, since the system behavior of the system component may in some cases depend on the input quantity, and in some cases the reversible range of the expected system behavior and / or actual output quantity of the system component may depend on the input quantity.

[0224] By "diagnose" it is generally understood to compare observed system behavior of system components of a cleaning system with expected system behavior.

[0225] In particular, "diagnosing" refers to the process of monitoring an output quantity and determining whether the observed system behavior of a system component deviates from the expected system behavior within acceptable limits, particularly by comparing the output quantity to an upper threshold quantity and / or a lower threshold quantity.

[0226] Similarly, unacceptable deviations in actual system behavior may preferably be assessed based on percentage limits depending on the expected output amount.

[0227] Diagnosis can preferably also be understood as a characterization of possible deviations, which characterization can preferably be performed based on the time course of the output quantity.

[0228] The "diagnostic signal" preferably describes the result of a method for diagnosing the system behavior of a system component of a washing system of a motor vehicle.

[0229] In particular, the diagnostic signal can indicate that the actual system behavior corresponds perfectly to the expected system behavior.

[0230] The diagnostic signal may also indicate that the actual system behavior does not correspond to the expected system behavior, and the diagnostic signal preferably includes in what form and based on what components of the output quantities the actual system behavior does not correspond to the expected system behavior.

[0231] "Current diagnostic signal" is understood as the diagnostic signal that currently exists and for which a solution strategy is sought.

[0232] A "solution strategy" is understood as a procedure that is suitable to eliminate deviations between the actual system behavior of a system component and the expected system behavior of this system component of the cleaning system, according to available experience.

[0233] "Fouling process" is understood as the accumulation of contamination and / or soiling on a surface.

[0234] "Fouling conditions" are understood as the current condition of contamination and / or fouling of a surface.

[0235] A "first availability" is understood to be a first state of availability. A "second availability" is understood to be a second state of availability after time has elapsed between the first availability and the second availability.

[0236] Preferably, the vehicle traveled between the first availability and the second availability.

[0237] Preferably, the vehicle has increased its operating time between the first availability and the second availability.

[0238] The increase in the number of driver assistance systems also leads to an increase in the number of sensors in vehicles, in particular sensors with optical operating principles, particularly sensors with optically active components relying on the fact that the part of the surface of the vehicle that is actively connected to the sensor, in particular the sensor with optically active components, may only show an upper limit of soiling.

[0239] If the contamination of this part of the vehicle's surface exceeds this maximum contamination, the function of the sensors cannot be guaranteed to a sufficiently high degree and the function of the driver assistance systems is also affected by the contamination state.

[0240] As a result, maintaining the functionality of driver assistance systems requires cleaning of the surfaces actively connected to each sensor that provides data for the driver assistance systems, which increases as the number of sensors increases.

[0241] This cleaning operation requires sufficient cleaning resources, particularly cleaning fluid and electricity. Therefore, as the need for cleaning increases, so does the need for cleaning fluid that must be stored in the vehicle to clean the relevant surfaces. This leads to an increase in the space required for the cleaning fluid reservoir, which in turn leads to an increase in the weight of the vehicle.

[0242] Neither the additional weight nor the additional space requirements of the system components are desirable.

[0243] For this reason, a particular cleaning method is proposed here for the resource-efficient, preferably resource-saving, cleaning of at least a portion of a surface of a motor vehicle.

[0244] Resource-efficient cleaning means that the cleaning of the surface being cleaned is optimized so that the ratio between cleaning effectiveness and cleaning cost is taken into account. In other words, resource-efficient cleaning requires that the control variables of the cleaning process be selected to achieve maximum cleaning success with minimum effort, and the control variable setpoints at least indirectly determine the amount of resources the process requires to clean a surface.

[0245] "Resource-saving cleaning" is understood to mean that the cleaning of the surface to be cleaned is optimized with a priority cleaning objective to be achieved, which may preferably be based on the fact that the vehicle will not break down due to contamination of the surface, in particular due to contamination of the sensor surface, or due to a failure of the sensor function caused by the contamination. The priority cleaning objective may also be that the level of autonomy of the vehicle does not have to be given up due to contamination of the surface, in particular due to contamination of the sensor surface, or due to a failure of the sensor function caused by the contamination.

[0246] The proposed cleaning method uses a vehicle washing system to plan and / or optimize and / or execute individual cleaning processes, each of which involves the cleaning of individual partial surfaces of the vehicle by the use of cleaning means, in particular cleaning fluids.

[0247] Each cleaning process also indicates the period during which the cleaning process is performed, and the cleaning process indicates the start and end times of this period.

[0248] The cleaning system refers to an electronic control unit, a cleaning fluid dispensing system, and preferably includes at least one fluid reservoir, at least one nozzle, and at least one cleaning fluid line connecting the cleaning fluid reservoir and the cleaning nozzle.

[0249] The success of the cleaning is recorded at least partly automatically within the scope of the cleaning method proposed here, and sensors that are actively connected to the surface to be cleaned are preferably capable of or arranged to transfer sensor availability to the cleaning system, whereby sensor availability at least indirectly represents a measure of the cleaning status of the surface that is actively connected to the sensor.

[0250] It is further suggested that the cleaning system may have access to or have available information regarding the availability of sensors and therefore the cleaning status of the surfaces being cleaned in active connection with the sensors.

[0251] Furthermore, sensors may be arranged to detect process quantities, in particular humidity and / or temperature in the vicinity of the vehicle, and / or the amount of rainfall and / or snowfall.

[0252] The washing system may have or be connected to further sensors that can provide the washing system with measured quantities, in particular process and / or control quantities. In this way, temperature, rainfall, etc. may also be made available to the washing system by other sensors. This also includes transmitting corresponding data to the washing system that the vehicle can retrieve as needed via a wireless data connection.

[0253] In particular, the washing system may also provide control values ​​for the coordinates and / or control quantities of the vehicle.

[0254] In particular, it is necessary to consider cleaning methods that use information about the system behavior of the cleaning system and / or that can provide this information themselves, in particular by means of dependency tables and / or systematic dependencies, in particular by means of dependency tables and / or systematic dependencies as described in the second aspect of the present invention.

[0255] As described in the second aspect of the invention, it will be appreciated that the benefits of the dependency tables and / or systematic dependencies described in the second aspect of the invention extend directly to the cleaning method described in the first aspect of the invention, which applies the dependency tables and / or systematic dependencies described in the second aspect of the invention and / or carries out a procedure for deriving the dependency tables and / or systematic dependencies described in the second aspect of the invention.

[0256] Furthermore, a cleaning method is proposed for controlling resource-efficient cleaning, preferably resource-saving cleaning applying control quantity setpoints, particularly preferably applying control quantity setpoints derived by the method according to the third aspect of the present invention.

[0257] As described in the third aspect of the invention, it will be appreciated that the benefits of the control quantity set points described in the third aspect of the invention extend directly to cleaning methods applying such control quantity set points as described in the first aspect of the invention.

[0258] Furthermore, a cleaning method is proposed that controls resource-efficient cleaning, preferably resource-saving cleaning, applying a cleaning strategy, particularly preferably applying a cleaning strategy derived by the method according to the fourth aspect of the present invention.

[0259] As described in the fourth aspect of the invention, it will be appreciated that the benefits of the cleaning strategy described in the fourth aspect of the invention extend directly to cleaning methods applying such a cleaning strategy as described in the first aspect of the invention.

[0260] In particular, it is necessary to consider cleaning methods that use information about the system behavior of the system components of the cleaning system and / or that can provide this information themselves, in particular by means of dependency tables and / or systematic dependencies, in particular by means of dependency tables and / or systematic dependencies as described in the fifth aspect of the present invention.

[0261] As described in the fifth aspect of the invention, it will be appreciated that the benefits of the dependency tables and / or systematic dependencies described in the fifth aspect of the invention extend directly to the cleaning method according to the first aspect of the invention, which applies the dependency tables and / or systematic dependencies described in the fifth aspect of the invention and / or carries out a procedure for deriving the dependency tables and / or systematic dependencies described in the fifth aspect of the invention.

[0262] In particular, a cleaning method should also be considered that includes process steps for diagnosing the system behavior of a system component of a cleaning system of a motor vehicle, preferably process steps for diagnosing the system behavior of a system component of a cleaning system according to the first alternative example of the sixth aspect of the present invention.

[0263] It will be understood that the advantages of the method for diagnosing the system behavior of a system component of a washing system according to the first alternative example of the sixth aspect of the present invention as described in the first alternative example of the sixth aspect of the present invention extend directly to the washing method comprising such process steps for diagnosing the system behavior of a system component of a washing system of a motor vehicle as described in the first aspect of the present invention.

[0264] In particular, a cleaning method should also be considered that includes 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 example of the sixth aspect of the present invention.

[0265] It will be understood that the advantages of the method for diagnosing deviations between actual and expected system behavior of system components of a washing system of a motor vehicle according to the second alternative example of the sixth aspect of the present invention, as described in the second alternative example of the sixth aspect of the present invention, directly extend to the washing method described in the first aspect of the present invention, which includes such process steps for diagnosing deviations between actual and expected system behavior of system components of a washing system of a motor vehicle.

[0266] Also proposed is a cleaning method comprising process steps for selecting a solution strategy, preferably process steps for selecting a solution strategy according to the seventh aspect of the present invention.

[0267] It will be appreciated 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 as described in the seventh aspect of the present invention, extend directly to a cleaning method applying such a method for selecting a solution strategy as described in the first aspect of the present invention.

[0268] Furthermore, cleaning methods are to be considered that include 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.

[0269] It will be appreciated that the advantages of the method using the selected resolution strategy, preferably as described in the eighth aspect of the invention, and the process steps for using the selected resolution strategy as described in the eighth aspect of the invention, extend directly to the cleaning method applying such a method using the selected resolution strategy as described in the first aspect of the invention.

[0270] In particular, it is necessary to consider cleaning methods that use information about the system behavior of the fouling process of the surface of the motor vehicle and / or that are able to provide this information themselves, in particular by means of dependency tables and / or systematic dependencies, in particular by means of dependency tables and / or systematic dependencies as described in the ninth aspect of the present invention.

[0271] As described in the ninth aspect of the present invention, it will be appreciated that the benefits of the dependency tables and / or systematic dependencies described in the ninth aspect of the present invention extend directly to the cleaning method according to the first aspect of the present invention, which applies the dependency tables and / or systematic dependencies described in the ninth aspect of the present invention and / or carries out a procedure for deriving the dependency tables and / or systematic dependencies described in the ninth aspect of the present invention.

[0272] In particular, within the scope of the cleaning method proposed herein, it is necessary to consider determining the expected availability of the vehicle for distances or operating times not yet covered, preferably using the dependency tables and / or systematic dependencies described in the ninth aspect of the present invention, and / or determining the expected distances or expected operating times of the vehicle for distances not yet covered when an availability threshold is reached, preferably by applying a method for optimizing the resource requirements for the cleaning process of the vehicle's surfaces, in particular the method for optimizing the resource requirements for the cleaning process of the vehicle's surfaces, in particular the method for optimizing the resource requirements for the cleaning process of the vehicle's surfaces, in particular the method for optimizing the resource requirements for the cleaning process of the vehicle's surfaces, in particular the method for determining a cleaning strategy for cleaning the vehicle's surfaces to be cleaned ...

[0273] Preferably, the dependency table and / or systematic dependency as described in the ninth aspect of the present invention is used to determine the expected availability in distance or operating time of the vehicles not yet covered, as described in the tenth aspect of the present invention, and / or preferably, the expected distance or expected operating time of the vehicles not yet covered when an availability threshold is reached is determined, as described in the eleventh aspect of the present invention, and / or by applying a method for optimizing resource requirements for a cleaning process of a vehicle surface, in particular as described in the third aspect of the present invention, for optimizing resource requirements for a cleaning process of a vehicle surface, in particular as described in the fourth aspect of the present invention, and / or a cleaning strategy for cleaning the surfaces to be cleaned of the vehicle, in particular as described in the fourth aspect of the present invention. By applying the method, the advantages of determining a cleaning strategy for cleaning surfaces to be cleaned of a motor vehicle and / or preferably determining a required expected increase in availability as described in the fourteenth aspect of the present invention as described in the ninth and / or tenth and / or eleventh and / or twelfth and / or thirteenth and / or fourteenth correspondences of the present invention, wherein the sum of the actual availability and the required expected increase in availability is sufficient to achieve the distance or operating time not yet covered by the motor vehicle so that the availability threshold is not exceeded, and directly extend to a cleaning method using such dependency tables and / or such systematic dependencies as described in the first aspect of the present invention above, are realized.

[0274] In an advantageous embodiment, the electronic control unit controls and / or regulates the resource-efficient cleaning, preferably resource-saving cleaning, depending on the actual measured quantity values, preferably the actual availability of sensors operably connected to the surface to be cleaned.

[0275] It is specifically proposed here, inter alia, to carry out the cleaning method in a coordinated manner.

[0276] In other words, cleaning methods need not only to be controlled by specification, but also to be applied within a coordinated framework.

[0277] The cleaning method needs to be adjusted as a function of the measurand, in particular as a function of the availability of sensors whose surfaces are in active connection with the sensors and are currently being cleaned by the cleaning process as part of the cleaning method.

[0278] In other words, it is specifically proposed to adjust each individual cleaning process carried out within the cleaning recipe based on the availability of the associated sensor.

[0279] This is advantageous in particular in that the availability of associated sensors allows for the feedback of information about the current cleaning state to react to deviations in the cleaning result according to the situation.

[0280] This allows the effective cleaning process to be stopped earlier than planned, saving additional resources and preventing over-cleaning of the surfaces being cleaned.

[0281] Furthermore, it can be advantageously achieved that a less effective cleaning process than expected can be run for longer than planned, advantageously achieving a resource-optimal cleaning result in the overall assessment, and even if additional resources need to be used for this individual cleaning process, resources can still be saved in total.

[0282] Preferably, the cleaning method initiates the cleaning process as soon as a predefined threshold of sensor availability is reached, which is preferably actively connected with the surfaces to be cleaned by the cleaning process if the respective surfaces are not currently excluded from cleaning by the cleaning strategy.

[0283] It is proposed here to start a cleaning process, in particular a cleaning process that has been pre-planned by a control variable setpoint, upon the occurrence of a trigger condition, in particular as soon as a pre-defined threshold of sensor availability is reached.

[0284] In this way, it can be advantageously achieved that resources for cleaning can be saved, since the cleaning process never starts earlier than technically required.

[0285] Furthermore, if the availability of the sensor is less than or close to a predefined threshold of sensor availability, the cleaning method is proposed to start the cleaning process.

[0286] In particular, this may be advantageous for the cleaning method to start the cleaning process even after a malfunction of the cleaning system and / or after a previous replenishment of insufficient cleaning resources, in particular after starting an extensive cleaning process.

[0287] In particular, it should be considered that the cleaning methods described herein are applied to all surfaces that are actively connected to sensors and / or to surfaces that are actively connected to sensors required / selected by the current cleaning mode and / or to surfaces that are actively connected to sensors required / selected by a pre-selected future cleaning mode.

[0288] Suitably, the cleaning method forces a change in cleaning mode if it is not practical to accomplish the planned path in the currently selected cleaning mode.

[0289] If the pre-selected washing mode makes it impossible to reach the pre-planned destination, it is proposed to change the washing mode so that a washing mode is reselected that still allows the pre-planned route to be carried out without further necessary changes to the washing mode, and subject to compliance with the above conditions, a washing mode can be selected that allows the driver to have the most comfortable driving experience possible.

[0290] The advantage of this is that the planned destination can be reached using the resources available for washing under the most comfortable conditions possible for the driver, without having to replenish washing resources during the service stay.

[0291] In particular, it should be considered that the cleaning methods described herein are applied to all surfaces that are actively connected to sensors and / or to surfaces that are actively connected to sensors required / selected by the current cleaning mode and / or to surfaces that are actively connected to sensors required / selected by a pre-selected future cleaning mode.

[0292] In an advantageous embodiment, the cleaning method transitions to keeping only those sensors absolutely necessary for manual operation fully available by executing a corresponding cleaning process when the cleaning resources reach a reserve level.

[0293] Here, a kind of backup strategy is proposed in which the cleaning system changes the cleaning mode to such an extent that only the sensors absolutely necessary for manual operation remain sufficiently available, as a measure of the last moment in case reaching a pre-planned destination without service maintenance is at risk and in an early stage the cleaning mode has not been adapted to a lower level of cleaning resource consumption.

[0294] Optionally, it is proposed to take this measure as late as possible so as to be able to reach the destination of the travel route with the last available cleaning resource.

[0295] The advantage of this is that the driver is forced to intervene further in the operation of the vehicle only if absolutely necessary.

[0296] Furthermore, as a modification according to a further optional embodiment, it is proposed to occasionally wet surfaces that are only effectively connected to unnecessary sensors with a spray of cleaning liquid.

[0297] In this way, it can be advantageously achieved that surfaces that are not actively connected to one of the required sensors do not dry out, and thus advantageously prevent the adhesion of contamination present on these surfaces.In this way, it can be advantageously achieved that a separate cleaning process aimed at directly cleaning the surface can work with fewer cleaning resources, since it does not need to quickly remove the layer of covered dirt, but rather removes already soaked or pre-soaked dirt.

[0298] In other words, no cleaning process is proposed here that is specifically aimed at the immediate cleaning of surfaces, but rather a cleaning process that makes it easier for subsequent cleaning processes aimed at the immediate cleaning of surfaces to achieve better cleaning results, in particular with less resource consumption and improved availability.

[0299] Thus, in combination, they can enable a more efficient cleaning process.

[0300] In particular, it should be considered that the cleaning methods described herein are applied to all surfaces that are actively connected to sensors and / or to surfaces that are actively connected to sensors required / selected by the current cleaning mode and / or to surfaces that are actively connected to sensors required / selected by a pre-selected future cleaning mode.

[0301] Optionally, the cleaning method refers to a cleaning process adapted to wet the surface to be cleaned.

[0302] A cleaning method is presented herein that describes a cleaning process designed to wet the surface to be cleaned.

[0303] The cleaning method should preferably include two cleaning processes, the first of which is designed to wet only the surface to be cleaned so that the covered dirt on the surface to be cleaned is softened, which is an advantage in that it is easy to dissolve the dirt in the subsequent cleaning process.

[0304] The second cleaning process in terms of time is designed to reduce or remove previously softened soils by using cleaning means.

[0305] Furthermore, it should be taken into account that a cleaning process designed to clean a surface to be cleaned is preceded by several cleaning processes each designed to moisten the surface to be cleaned. These cleaning processes designed to moisten the surface may be carried out during active and / or passive operating conditions of the vehicle.

[0306] In this way, soiling on the surface being cleaned can be advantageously prevented.

[0307] It is therefore particularly contemplated that the surface of the vehicle being washed may also be moistened in parked conditions by the washing process.

[0308] The advantage is that overall resource efficiency can be improved when cleaning the surfaces being cleaned.

[0309] In particular, it should be considered that the cleaning methods described herein are applied to all surfaces that are actively connected to sensors and / or to surfaces that are actively connected to sensors required / selected by the current cleaning mode and / or to surfaces that are actively connected to sensors required / selected by a pre-selected future cleaning mode.

[0310] In an optional embodiment, the cleaning method describes a cleaning process that is adapted to be initiated upon a change in the operating conditions of the vehicle.

[0311] Here, it is suggested to adapt the washing method so as to initiate the washing process when the operating conditions of the vehicle change.

[0312] Preferably, the cleaning method should take into account that the cleaning process begins when the vehicle is started, i.e., at the transition of the vehicle from a passive operating state to an active operating state, so that the availability of the sensors can be improved at the start of the journey, in particular in such a way that the sensors achieve a minimum availability for functional sensor operation.

[0313] Furthermore, it should also be considered that cleaning methods that change cleaning modes by initiating a cleaning process are designed to achieve a minimum availability of functional sensor operation of all sensors required for the newly selected cleaning mode.

[0314] The advantage of this is that the cleaning method can react adaptively to changes in the operating conditions of the vehicle.

[0315] In particular, it should be considered that the cleaning methods described herein are applied to all surfaces that are actively connected to sensors and / or to surfaces that are actively connected to sensors required / selected by the current cleaning mode and / or to surfaces that are actively connected to sensors required / selected by a pre-selected future cleaning mode.

[0316] According to a second aspect of the invention, there is provided a method for indirectly deriving systematic dependencies of a system behavior of a washing system, particularly preferably a washing process of a surface of a vehicle, for washing at least one surface of a vehicle, preferably for resource-efficient washing, particularly preferably for resource-saving washing, wherein output quantities depend on input quantities due to the system behavior of the system, - determining an input quantity as a first parameter of the method by means of at least one sensor; - determining, preferably by means of at least one sensor, a quantity of power output as a second parameter of the method; - digitizing and recording, if necessary, the determined first and second parameters by a data processing system, which data processing system represents an electronic data processing and evaluation system and database; - storing the determined first and second parameters in a database in an ordered manner relative to one another as a data set of a dependency table; - deriving systematic dependencies between first and second parameters by means of an electronic data processing and evaluation system from at least two datasets of dependency tables stored in a database, preferably from at least 50 datasets of dependency tables, particularly preferably from at least 200 datasets of dependency tables, wherein the electronic data processing and evaluation unit accesses the datasets of the dependency tables and determines the systematic dependencies from the datasets by means of an algorithm; - Preferably, storing the derived systematic dependencies in a database and / or an electronic data processing and evaluation unit and / or an electronic control unit.

[0317] Previously, vehicle surfaces to be cleaned were typically cleaned automatically at the driver's request, at predetermined intervals, or when contamination was detected.

[0318] With the increasing number of sensors in automobiles and the increasing safety aspects resulting from the possibilities offered by driver assistance systems up to autonomous driving, the relevance of cleaning automobile surfaces, in particular surfaces overlaid with sensors, has increased significantly.

[0319] The surface overlying the sensor is defined in particular as the outermost surface of the vehicle that covers the sensor, in particular the windshield, rear window, camera lens and / or sensor cover.

[0320] The increased need for cleaning also increases the need for resources to clean the corresponding surfaces.

[0321] This brings into focus the need for new cleaning strategies to achieve resource-efficient cleaning, preferably resource-saving cleaning, so that fewer resources need to be provided for the required cleaning process.

[0322] The relationship between the cleaning success of a cleaning process and the resulting resource requirements is therefore a point of attention for consideration, particularly with the aim of being able to carry out the process as efficiently as possible or even with greater resource conservation.

[0323] Preferably, the cleaning success of the cleaning process can be assessed based on the availability of sensors before and after the cleaning process.

[0324] The success of the cleaning is influenced, inter alia, by different throughputs of the cleaning process, inter alia by air humidity and / or air temperature, and / or the amount of rainfall and / or snowfall, and / or the amount of actual solar radiation, and / or the temperature of the surface to be cleaned.

[0325] Additionally, the success of the cleaning is also affected by the speed at which the vehicle is traveling during the cleaning process and the type of vehicle, which provides information about the number of surfaces to be cleaned, where they are located on the vehicle, and how they are oriented relative to the direction of vehicle movement.

[0326] Furthermore, there are many possible cleaning processes, each with different control variable selections.

[0327] The amount of control determines when, for how long, and in what manner which resources and / or cleaning means are used to clean each surface.

[0328] The resource requirements of a cleaning process can be determined directly or indirectly depending on, among other things, the amount of control over the cleaning process.

[0329] When implementing resource-efficient, preferably resource-saving, washes, specific questions arise about which control amounts can be used for which vehicle types, what treatment amounts, and under what resource requirements will make which washes successful.

[0330] As already explained above, the complexity of the question considered here increases as a large number of influencing quantities may be taken into account that affect the outcome and resource requirements of the cleaning process.

[0331] In recent years, resource-efficient cleaning has become less intuitive due to the complexity of the many different possibilities that can affect cleaning processes, and the potential for individual effects to compound on one another.

[0332] Resource-saving cleaning in the sense of a resource-optimized cleaning strategy is an even more complex process.

[0333] As a result, not only has the effort involved in designing cleaning systems and cleaning strategies increased significantly, but the resources required have also increased significantly, as they must ensure successful cleaning while guaranteeing a certain level of safety, a goal that can be achieved primarily by expanding the use of resources.

[0334] In this respect, the objective of resource-efficient cleaning, preferably resource-saving cleaning, of the surfaces to be cleaned of motor vehicles is currently a highly debated topic, especially since the comprehensive system behavior between input and output quantities is not determined.

[0335] This type of necessary information is complex to obtain and requires a great deal of effort to obtain.

[0336] Deviating from the above, a method is proposed here to indirectly derive the systematic dependence of the system behavior of a car washing system between the input quantities of the system and the output quantities of the system, where the output quantities depend on the input quantities due to the system behavior of the system.

[0337] Preferably, the input quantity represents a control quantity for the cleaning method.

[0338] Preferably, the input quantities indicate the pressure of the cleaning liquid and / or the temperature of the cleaning liquid and / or the mixture of the cleaning liquid, 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 alignment of the spray pattern to the surface to be cleaned.

[0339] Preferably, the input amount indicates a processing amount.

[0340] Preferably, the output quantity is the cleaning success of the cleaning method, which can be assessed in particular by the difference in availability of the sensor before and after cleaning the corresponding surface covering the sensor, in particular by an increase in availability.

[0341] It is further suggested that the output quantity should be indicative of the resource requirements of the cleaning method, which can be determined indirectly, in particular as a function of the control quantity, or directly on the basis of corresponding measured values.

[0342] Preferably, the systematic dependency is suggested to describe the system behavior of a cleaning process for a surface of a motor vehicle for cleaning at least one surface of the motor vehicle.

[0343] In the procedure proposed here, - first, for each individual cleaning process, an input quantity is determined as a first parameter and an output quantity is determined as a second parameter, and the data processing system records the determined first and second parameters and stores them in a database in an ordered manner relative to each other as a single data set for the individual cleaning process; A systematic dependency between the first parameter and the second parameter is then systematically derived from the plurality of data sets, in particular by an algorithm, using the plurality of data sets from the dependency table.

[0344] Needless to say, unless existing data is available, obtaining a larger data set from which to derive the systematic dependence will require initially running the first part of the procedure, in which the first and second parameters are recorded, several times.

[0345] The corresponding data sets can be collected directly during the cleaning process carried out on the vehicle, in particular during normal vehicle operation.

[0346] Furthermore, such data sets may also be determined and / or derived from laboratory experiments.

[0347] In a further variant, it is conceivable that the data set is determined by a numerical model representing the corresponding refinery process.

[0348] In particular, such data sets are collected in the form of empirical values, as they are stored in dependency tables.

[0349] From these empirical values, the systematic dependencies proposed herein can be derived in the manner proposed herein, which can be used to select or determine an optimal or resource-saving cleaning process.

[0350] Preferably, the systematic dependence is determined on the basis of at least two datasets, preferably on the basis of at least 50 datasets, more preferably on the basis of at least 200 datasets, and especially preferably on the basis of at least 1000 datasets.

[0351] It should be pointed out that the above values ​​for the number of data sets should not be understood as hard limits, but rather should be able to be exceeded or fallen short on an engineering scale without departing from the described aspects of the invention. In simple terms, the values ​​are intended to indicate the size of the number of data sets proposed here.

[0352] The systematic dependencies thus obtained advantageously make it possible not only to evaluate and reproduce previously performed cleaning processes, but also to devise new cleaning processes based on a systematic analysis of the data, with the aim, inter alia, of further reducing resource requirements. This can be achieved by interpolation between the available data sets. Furthermore, it is conceivable, in particular, to use regression methods to generate curves from the obtained data sets, which allow for continuous and differentiable systematic relationships between input and output quantities of the cleaning process.

[0353] Preferably, the input quantity is determined by at least one sensor.

[0354] Optionally, the output quantity is determined by at least one sensor.

[0355] Advantageously, a data processing system refers to an electronic data processing and evaluation system and database.

[0356] It is suggested that, if necessary, 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 maintained in a digital database and processed electronically.

[0357] The systematic dependencies between input and output quantities, preferably resource requirements, developed according to the proposed procedure describe the system behavior of the washing system.

[0358] It is therefore specifically conceivable that for each surface to be cleaned, a respective systematic dependency is derived that takes into account the portion of the controlled quantity that is effectively associated with the corresponding surface, and that the systematic dependency represents the resource requirements as a function of this portion of the controlled quantity, and possibly as a function of the processing volume, by means of a continuous, differentiable, systematically determined curve that reflects the cleaning success as well as, preferably, the interdependence of the quantities.

[0359] In other words, multiple systematic dependencies can be derived for multiple surfaces to be washed, and in particular the number of surfaces to be washed on the vehicle corresponds to the number of systematic dependencies derived.

[0360] Optionally, the systematic dependence may take the form of an (n+i)-dimensional curve of order m, taking into account n-dimensional input quantities and i-dimensional output quantities.

[0361] Such systematic dependencies can be used in various ways. It is therefore conceivable that, among other things, the comparison of input quantities can be used to find control quantities that allow the surfaces in question to be cleaned particularly efficiently from a resource perspective. Furthermore, it is specifically conceivable to find control quantities that allow a particular resource-saving cleaning of the corresponding surfaces in a comparison of cleaning success rate and resource requirements.

[0362] Preferably, the input amount indicates the amount of cleaning liquid to be used to clean the surface to be cleaned.

[0363] Preferably, the input amount indicates the period of time for which the cleaning solution is to be applied to the surface to be cleaned.

[0364] Preferably, the input amount refers to the cleaning means, in particular the wiping elements with which the surface to be cleaned is treated.

[0365] Preferably, the input amount indicates the time for which the cleaning means is to be used.

[0366] Preferably, the input quantity indicates the type of vehicle that is considered for the systematic dependency.

[0367] Preferably, the input amount indicates the amount of cleaning liquid the surface to be cleaned is immersed in before it is subsequently treated with the cleaning means, and more preferably, the input amount also indicates the time the surface to be cleaned is immersed for before it is subsequently treated with the cleaning means.

[0368] Preferably, the input amount indicates the amount of cleaning liquid used to clean the surface to be cleaned and / or the period for which the cleaning liquid is applied to the surface to be cleaned and / or the cleaning means, in particular the time for which the surface to be cleaned is treated and the wiping element and / or the cleaning means is used and / or the type of vehicle for which systematic dependencies are taken into account and / or the amount of cleaning liquid in which the surface to be cleaned is immersed before it is subsequently treated with the cleaning means and / or the time for which the surface to be cleaned is immersed before it is subsequently treated with the cleaning means.

[0369] Specifying systematic dependence continuously gives advantages to the design of procedures and allows checking the robustness of the systematic dependence, thus quantifying whether the systematic dependence is a regularity or a trend with a certain probability that can be captured with continuous precision.

[0370] Another advantage of the procedure described here is that it can be used to store an almost unlimited number of parameters relative to one another and derive systematic dependencies, preferably systematic dependencies in (n+i) dimensions.

[0371] Operators of suitable cleaning systems are naturally limited in their ability to map (n+i)-dimensional systematic dependencies, especially when it comes to decisions regarding the assignment of control quantities in the brain. In particular, due to the ever-increasing complexity of the corresponding cleaning systems and the increasing number of detectable influence quantities, today's operators are often already at the limit of the natural limits of their comprehension abilities. Systematic dependencies are advantageous because they are not subject to such limitations.

[0372] It is stated that a suitable implementation of the proposed procedure allows mapping complex correlations between the parameters of the procedure, which applies in particular to dependencies where there are many related quantities that may exhibit various correlations with each other.

[0373] Advantageously, aspects of the invention presented herein can achieve the ability to map the system behavior of a cleaning system with all relevant interdependencies, resulting in a wealth of experience with proper and resource-efficient cleaning of vehicle-type surfaces.

[0374] In particular, resource-efficient cleaning of single surfaces of a vehicle type can be recorded or derived that can be efficiently cleaned under given environmental conditions and given initial contamination of the respective surface.

[0375] It should be clearly pointed out that the result of the cleaning process does not necessarily have to be a complete cleaning of the surface, especially since the success of cleaning the surface is very small, so it is necessary to consider in particular that the sensors hidden behind it continue to function.

[0376] This applies in particular to the front and rear windows of a motor vehicle, which are cleaned to such an extent that after the completion of the cleaning process, at least the windshield, and preferably sensors behind the driver of the motor vehicle inside the windshield, can operate through the front and rear windows so that safe driving operation is not impaired by soiling of the front and / or rear windows.

[0377] Thus, by using a cleaning method that takes advantage of such systematic dependencies, cleaning resources can be advantageously saved, allowing the vehicle to be safely driven further distances under the same initial conditions as existing cleaning resources, and / or the weight of the vehicle can be reduced as fewer resources need to be used to cover the same distance, and / or the vehicle's associated fluid tank can be designed to be smaller for the cleaning fluid, saving installation space within the vehicle.

[0378] Advantageously, the input quantity represents at least one measured quantity, preferably a processed and / or controlled quantity.

[0379] Here, it is implied that the input quantity denotes a measured quantity.

[0380] If the input quantities lack the ability to represent the measured quantities, the systematic dependence may possibly also depend on the default values ​​of the controlled quantities within the framework of the control system.

[0381] However, the use of measurands can advantageously increase the accuracy of systematic dependencies.

[0382] Preferably, such measured quantities are control quantities, so that a systematic dependency between the output quantity of the cleaning process of the surface of the vehicle to be cleaned and the control quantity can be derived and thus can be used later for cleaning the corresponding surface, in particular also for controlling and / or adjusting the cleaning process of the surface to be cleaned.

[0383] Furthermore, it is suggested that the input quantities indicate the throughput quantities, so that a systematic relationship between the output quantities and the throughput quantities, preferably air humidity and / or air temperature, and / or actual solar radiation, and / or temperature of the surface to be cleaned, can be derived during the cleaning process of the surfaces of the vehicle to be cleaned and can therefore also be used later for optimal cleaning of the corresponding surfaces.

[0384] The advantage of this is that the accuracy of the derived systematic dependence can be increased and at the same time a large number of influencing factors from the domain of the controlled and / or processed quantities can be taken into account.

[0385] Preferably, the input quantity is indicative of the driving speed of the vehicle.

[0386] The travel speed of the vehicle may affect the cleaning process of the surface being cleaned, in particular the distribution of the cleaning liquid on the surface being cleaned and / or the displacement of the cleaning liquid on the surface being cleaned due to relative airflow and / or evaporation of the cleaning liquid on the surface being cleaned, and the effective exposure time during which the cleaning liquid may dissolve contamination may also be affected.

[0387] If the input quantities include operating speed, the systematic dependencies derived here can also be used to take into account the effect of operating speed for optimal cleaning of the surface being cleaned.

[0388] In a preferred embodiment, the input quantity indicates humidity, in particular the current humidity in the vicinity of the vehicle and / or temperature in the vicinity of the vehicle, in particular the current temperature in the vicinity of the vehicle and / or rainfall, in particular the current rainfall and / or snowfall in the vicinity of the vehicle, in particular the current snowfall in the vicinity of the vehicle and / or coordinates of the vehicle.

[0389] Air humidity and temperature have been shown to be important factors that affect the cleaning success of the cleaning process on the surface being cleaned.

[0390] For this reason, it is proposed here to derive a systematic dependency on these particularly relevant influencing factors for resource-efficient cleaning.

[0391] It has also been shown that rain and / or snow can make the cleaning process more resource-efficient: in particular, rain and / or snow can loosen or at least soften accumulated dirt, making it easier to dissolve, thus potentially saving cleaning fluids.

[0392] If the effective temperature and / or effective humidity and / or effective rainfall and / or effective snowfall are taken into account when deriving the systematic dependencies, these data can also be taken into account when evaluating the refining process.

[0393] In particular, it is conceivable that when selecting a cleaning process, in particular a cleaning process specified by a control variable setpoint, the current environmental conditions are also taken into account, so that an optimally resource-saving and / or resource-efficient cleaning process can be selected and executed.

[0394] It is further conceivable that the current coordinates of the vehicle are also taken into account, in particular when statistically considering the expected temperature and / or the expected humidity and / or the expected amount of rain and / or the expected amount of snow. Thus, it is specifically conceivable that based on the current coordinates of the vehicle, expected environmental conditions are determined and, based on the expected environmental conditions and systematic dependencies, an optimal resource-saving and / or resource-efficient cleaning process is selected and implemented for cleaning the surface to be cleaned.

[0395] The advantage of this is that important influencing factors can be systematically taken into account when cleaning the surfaces to be cleaned and can therefore also be taken into account in future resource-efficient, preferably resource-saving, cleaning of surfaces, saving resources and improving the operational safety of the vehicle.

[0396] In an optional embodiment, the input quantity indicates a vehicle type.

[0397] The vehicle type provides information on a number of different influencing factors that affect the cleaning process of some of the surfaces of the vehicle, including, inter alia, the location where the surfaces to be cleaned are located and / or the size of the surfaces to be cleaned and / or the cleaning means capable of cleaning the surfaces to be cleaned and / or the expected degree of contamination and / or the expected type of contamination and / or the exposure of the surfaces to be cleaned to air currents and / or the exposure of the surfaces to be cleaned to sunlight and / or the number of surfaces to be cleaned.

[0398] Furthermore, the vehicle type provides information about all different functional types of sensors and / or sensor types located in the vehicle, including in particular the assignment of each installed functional type of sensor and / or each installed sensor type to the location where each sensor is installed.

[0399] Here, we propose to consider these influencing factors when deriving systematic dependencies.

[0400] The advantage of this is that influencing factors associated with vehicle type can be taken into account with respect to systematic dependencies and can therefore be applied individually to each vehicle type in the future for resource-efficient cleaning.

[0401] Advantageously, the input quantity indicates the availability of the sensor.

[0402] Sensor availability is the quantity that can ultimately provide information about how badly the sensor is polluted.

[0403] A particular priority is that availability can assume values ​​within an interval, with one interval limit of arrival meaning that the system can fully meet that requirement, and another interval limit of arrival meaning that the system will no longer be able to meet that requirement.

[0404] If the availability value is in the range between the interval limits, the system will still be able to meet its requirements, but under more difficult conditions. In particular, the availability value reflects the degree of contamination of the surfaces of the vehicle, preferably the degree of contamination of the surfaces, preferably of the sensors, particularly preferably the degree of soiling of the surfaces of the optical sensors, and / or the degree of soiling of the windows seen by the driver of the vehicle, in particular the degree of soiling of the windshield and / or rear window, and / or the degree of soiling of the headlamps and / or rear headlamps.

[0405] The availability of the sensor before the cleaning process of the surface is the same control quantity, but different availability before the cleaning process was found to affect the cleaning success.

[0406] By means of the aspects proposed here, it may be advantageously achieved that sensor availability can be taken into account as an influencing factor of the derived systematic dependency.

[0407] Preferably, the output quantity indicates the availability of the sensor and / or an increase in availability due to the cleaning process.

[0408] The aspects of the invention proposed here make it possible, in particular, to determine the cleaning success of a cleaning process by comparing the availability of the sensor before and after the cleaning process, referred to as the increase in availability.

[0409] In other words, the increase in availability is the difference between the availability immediately after the completion of the cleaning process and the availability immediately before the cleaning process.

[0410] Thus, the success of the cleaning process, preferably increased availability, can be advantageously quantified by the embodiments proposed herein.

[0411] This advantageously enables future cleaning processes in which the control quantities can be determined by systematic dependence on the availability of sensors before the cleaning process, making it possible, on the one hand, to carry out resource-efficient cleaning of the surfaces to be cleaned, but, on the other hand, to achieve the desired availability of sensors after the cleaning process has been achieved.

[0412] The selected cleaning process specified by the selection of the control quantity does not necessarily remove the availability of the sensor up to the upper limit of the determinability of the availability of the sensor, but only if it is necessary in a functionally and / or safety-related manner.

[0413] Furthermore, it is conceivable that several cleaning processes, specified by respective control variables, can be carried out one after the other in order to achieve optimal cleaning in terms of resource efficiency and / or sensor functionality and / or vehicle safety aspects.

[0414] It should be particularly taken into consideration that the sequence of such cleaning steps is already defined before the first cleaning process.

[0415] It is further conceivable that during the cleaning process of a surface cleaning sequence the availability of each sensor is re-evaluated and the amount of control of the subsequent cleaning process is determined depending on the availability of each sensor achieved during that time.

[0416] Overall, it can be advantageously achieved that cleaning of one or more surfaces of a motor vehicle can be carried out autonomously, or at least partially autonomously.

[0417] In an advantageous embodiment, the output amount is indicative of a resource requirement of the cleaning process of the surface of the motor vehicle, and preferably the resource requirement is determined as a function of a control amount setpoint of the cleaning process of the surface.

[0418] This is advantageous in that when using systematic dependencies, the resource requirements of the cleaning process can be taken into account, inter alia, when selecting the optimal cleaning process, represented by the control variable setpoints of the current initial conditions for which the cleaning of the surface is optimized.

[0419] In a preferred embodiment, the systematic dependence is determined by regression analysis.

[0420] Here, it is suggested to use a regression algorithm as an algorithm for indirectly deriving the systematic dependence.

[0421] Therefore, algorithms that have already been tested in numerous applications and that can be optimally selected and / or adapted according to the system behavior considered here can be advantageously applied to determine high-quality systematic dependencies.

[0422] Advantageously, the systematic dependence is determined in the form of a curve, preferably a curve and a coefficient of determination of the curve.

[0423] The advantage of this is that the systematic dependence is shown by a curve as a function of the input quantities of the cleaning process, in particular this curve has no gaps, so that a clear allocation between the controlled quantities and the output quantities can be achieved, in particular a continuous and differentiable dependence between the input quantities and the output quantities, so that the dependence is ideally suited for optimization, in particular for optimization of resource requirements.

[0424] Preferably, the curve is continuous and differentiable, so that the systematic dependence in the control range of the controlled variable can be used to determine the controlled variable suitable for the requirements of the cleaning process, which would otherwise lead to discontinuities in the adjustment range or non-differentiable changes in the effect of fluctuations in the controlled variable.

[0425] Evaluating the coefficient of determination from the determined data and the curve determined by the regression model provides an indication of the accuracy of the systematic dependence, assuming a sufficient number of data sets are available. It is advantageous to evaluate how meaningful the correlation between input and output quantities of the cleaning process is and how well it can reproduce existing or recorded data. Furthermore, if the coefficient of determination is large, the curve can also be used to make statements about the margins of existing data. For example, it is considered that the data can be numerically supplemented and / or estimated at the margins of existing data.

[0426] In an optional embodiment, the systematic dependencies are determined by an optimization process.

[0427] It is suggested here that the parameters of the systematic dependence are determined by an optimization procedure, in particular by a minimization procedure that minimizes the cumulative deviation of the empirical values ​​taken into account by the data set from the systematic dependence. In this way, it is advantageously possible to determine a systematic dependence that can be derived in an optimal way, in particular with a minimum cumulative deviation from the initial empirical values.

[0428] Preferably, the parameters of the systematic dependence are determined by maximizing the resulting coefficient of determination.

[0429] Preferably, the systematic dependencies are determined by a self-learning optimization method.

[0430] In particular, it is proposed to use algorithms that exhibit the properties of algorithms from the machine learning class, thus being able to derive systematic dependencies between input and output quantities.

[0431] The advantage of this is that by using a self-learning optimization method, the complex task of indirectly deriving systematic dependencies does not require a human to painstakingly adapt to new conditions, thus saving time and money by indirectly deriving systematic dependencies.

[0432] Since the optimization procedure seeks to determine the optimal systematic dependence even in a multi-criteria environment and under various boundary conditions, the quality of the derived systematic dependence can be improved by the aspects proposed herein.

[0433] In this way, it is conceivable that optimization can be performed under multiple equal objectives and / or boundary conditions (multi-criteria optimization). In particular, it is possible to minimize multiple required resources while maximizing the increase in availability. In particular, classifications of algorithms that can determine Pareto optimality and / or the Pareto front are considered. In particular, classifications of algorithms in fields such as simplex methods and / or evolutionary strategies and / or evolutionary optimization algorithms are proposed here in order to derive systematic dependencies.

[0434] Advantageously, the systematic dependencies are derived using data sets from an existing database.

[0435] The advantage of this is that the systematic dependencies can also be derived using data from the existing database. Thus, it is possible to avoid the need to first collect empirical values ​​for a particular vehicle, transfer them to the database data, and then transfer them to the systematic dependencies. In this way, the existing data and empirical values ​​can be used to ensure the direct operation of the vehicle's washing system based on the systematic dependencies.

[0436] In an optional embodiment, the existing database is continually expanded.

[0437] Advantageously, an increase in the number of derivable systematic dependencies over time can be achieved.

[0438] Furthermore, due to the large number of empirical values ​​known from the data set, it is advantageously achieved that the accuracy of the systematic dependence can be increased.

[0439] In an advantageous embodiment, the new data set replaces the data set that deviates most from the derived systematic dependencies.

[0440] In particular, one must take into account the fact that empirical values ​​are traded off for the maximum Euclidean distance to systematic dependencies.

[0441] Advantageously, the systematic dependence becomes more and more precise over time, which can be expressed by an increase in the coefficient of determination.

[0442] Furthermore, this has the advantage that even weakly correlated systematic dependencies can be better identified over time.

[0443] 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 individually or cumulatively in any combination.

[0444] According to a first alternative of the third aspect of the present invention, the task is a method for optimizing resource requirements for a washing process of a surface of a motor vehicle, wherein a sensor is operatively connected to the surface, the method using data from dependency tables for a system behavior of a washing system of the motor vehicle, preferably for a system behavior of a washing process of at least one surface, preferably for resource-efficient washing, particularly preferably for resource-saving washing, the dependency tables representing data sets each representing an input quantity of the washing system and an output quantity of the washing system, the output quantity depending on the input quantity by means of the dependency table of the washing system behavior between at least one control quantity of the washing process and the availability of the sensor at the start time of the washing process and the availability of the sensor at the end time of the washing process, and the resource requirements of the washing process depending on the control quantity, - 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; - deriving, for each data set of the dependency table, the difference between the availability of the sensor at the end of the cleaning process and the availability of the sensor at the start of the cleaning process; - deriving, for each dataset of the dependency table, the respective resource requirements and the ratio of the difference; - selecting the control quantity of the data set that exhibits the maximum value of the ratio; -preferably storing the control quantity as a control quantity setpoint in a database and / or an electronic data processing and evaluation unit and / or an electronic control unit.

[0445] As the number of vehicle assistance systems increases, the number of sensors installed in engine vehicles also increases. These sensors primarily detect optical signals and therefore rely on the fact that the surfaces on which the optical signals are detected and operably connected to the sensors are sufficiently clean. Cleanliness is defined individually for each sensor by the fact that each optical signal to be processed can be received and / or processed at least primarily without interference.

[0446] Therefore, surfaces that are actively connected to sensors must be cleaned from time to time by using cleaning means. This also applies to the majority of sensors that do not operate with optical signals, since their signal transmission can be impaired by contamination.

[0447] It should therefore be clearly pointed out that this aspect of the invention may affect not only optical sensors, but all sensors in a vehicle, at least sensors that are actively connected to the surface of the vehicle.

[0448] Each washing process is linked to the resource requirements that the vehicle must provide.

[0449] So far, it is known that the cleaning process is initiated manually, preferably by the driver of the vehicle.

[0450] The recent increase in the number of vehicle assistance systems, and therefore the number of sensors installed in automobiles, has also significantly increased the need to keep resources available.

[0451] The increase in sensors also increases the number of controls required for the cleaning process, so semi-automatic or automatic cleaning of the surfaces involved is also desirable.

[0452] In particular, an advantageously automatable procedure is now proposed for minimizing the consumption of resources for cleaning surfaces that are effectively connected to associated sensors, preferably by performing resource-efficient and in particular resource-saving individual cleaning processes, so that the resource consumption and therefore also the resource requirements of at least one cleaning means can be advantageously reduced.

[0453] Each cleaning process is defined by at least one parameter, in particular an input quantity, particularly preferably a control quantity. The amount of cleaning liquid applied to the surface to be cleaned can be considered as the respective input quantity or simultaneously as the respective control quantity.

[0454] Priority should also be given to the fact that the cleaning fluid is applied to the surface to be cleaned in several stages, preferably in a relatively small amount in the first stage to soften the contamination, and in a second stage to wash the softened contamination off the surface. The method of application of the cleaning agent, and in particular the amount of cleaning fluid, directly affects the resource requirements of a single cleaning process.

[0455] It should be noted that this aspect considers not only the amount of cleaning fluid required for the cleaning process, but also the amount of energy used for cleaning, wear on the wiping elements, and / or equivalent resources required for the cleaning process.

[0456] Each cleaning process is influenced by system behavior, which depends on at least one parameter, preferably an input quantity, particularly preferably a control quantity, and within the framework of output quantities, particularly preferably by availability, statements can also be made regarding the result of the cleaning process, in particular the resource requirements used or to be used in a planning sense, and the success of the cleaning.

[0457] Thus, the system behavior is preferably defined by at least one input quantity and at least one output quantity, where the at least one output quantity depends on the at least one input quantity.

[0458] In the case of an input quantity, the size of the surface to be cleaned can also be considered as it is operably connected to a sensor.

[0459] In the context of input volume, the location of the surface to be cleaned can also be prioritized. Thus, differences in resource-efficient, and especially resource-saving, cleaning methods can be attributed to whether the surface to be cleaned is on the front or one side or the back or the bottom or the top of the car.

[0460] Furthermore, the input quantities may also include the type of contamination, in particular whether it is dirt and / or dust or a covered deposit of a layer such as mud or snow. It should also be noted that the operating location and operating history of the vehicle may statistically predict the type of surface contamination, in particular in combination with a weather forecast. In other words, the range of input quantities may also include weather conditions and the operating location and / or operating history. These may be evaluated by the vehicle's coordinates and, if necessary, other searchable data, in particular data searchable from a data network.

[0461] When assessing the cleaning success of a cleaning process, it can be preferably remembered that success is considered as the difference in availability of the corresponding surface to be cleaned before and after the cleaning process.

[0462] Different definitions of cleaning processes can be evaluated based on system behavior that is comprised of at least one input quantity and at least one output quantity.

[0463] If there are empirical values ​​for several defined cleaning processes, a resource-efficient and especially preferred resource-saving cleaning can be selected based in particular on the existing empirical values ​​for the respective contamination situation.

[0464] Each empirical value consists of at least one input quantity, in particular a control quantity, and at least one output quantity, in particular an increase in availability determinable from the difference between the availability before and after cleaning the surface to be cleaned.

[0465] In this context, it may be considered in particular that, based on the existing contamination situation, in particular available availability, control variables that have resulted in optimal resource-efficient, in particular resource-saving, cleaning according to existing experience are selected and that the corresponding control variables are reproduced within the framework of the cleaning procedure. During regeneration, it may be considered in particular that the control variables or controlled cleaning processes are selected.

[0466] The possible empirical values ​​may preferably consist of empirical values ​​derived from experience gained with a motor vehicle, in particular a specific motor vehicle, and / or experience gained with a reference vehicle and / or experience generated on the basis of a numerical model and / or experience generated on the basis of laboratory tests.

[0467] The experience values ​​taken into account for the selection of a resource-efficient, in particular resource-saving, cleaning process are preferably related to the respective experiences gained on the basis of surfaces to be cleaned that are currently being cleaned or at least whose cleaning is to be evaluated.

[0468] When storing collected experience values, the data can be stored in a dependency table.

[0469] Preferably, the dependency table can be extended with new experience values.

[0470] The dependency table can be read preferentially.

[0471] 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.

[0472] Preferably, the dependency table offers the possibility of storing intermediate results for the evaluation of the cleaning process in an ordered manner.

[0473] Preferably, the dependency table allows the selection of specific experience values ​​by data mining methods known in the state of the art.

[0474] In other words, it is suggested here that the resource consumption for cleaning of the surfaces selected for cleaning is optimized based on the system behavior of the cleaning process, so that better cleaning results can be advantageously achieved with less resource input, especially depending on the current initial situation.

[0475] The optimal control quantity setpoints correspond to the empirical control quantities of the defined cleaning process that guarantee resource-optimal cleaning of the surfaces to be cleaned according to the proposed procedure. If the corresponding optimal empirical quantities are selected, the optimal control quantity setpoints can be obtained from the corresponding input quantities.

[0476] The method proposed here is designed to optimize cleaning of surfaces relative to the sensors and generate control variable set points that are optimized for each individual surface being cleaned.

[0477] Preferably, the procedure can be carried out sequentially for several surfaces to be washed, which is advantageous in that the control quantity setpoints can be defined successively for each surface of the vehicle to be washed.

[0478] this is, - 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, in which the collected prediction values ​​can be advantageously called up and processed in a subsequent step; - deriving, for each data set of the dependency table, the difference between the availability of the sensor at the end of the washing process and the availability of the sensor at the start of the washing process, in which an increase in the availability for each stored experience value is advantageously determined; - deriving, for each data set of the dependency table, the respective resource requirements and the ratio of the difference, wherein the efficiency of the cleaning process can be advantageously defined by the ratio of the expected resource requirements and the expected cleaning success; - selecting the control amount of the data set that exhibits the highest value of the ratio, whereby the most resource-efficient control amount may be selected based on existing experience; - Preferably, this can be achieved by a step of storing the control quantity as a control quantity set value in a database and / or an electronic data processing and evaluation unit and / or an electronic control unit, wherein the specific control quantity set value can be retrieved and advantageously applied within the framework of a downstream cleaning process.

[0479] According to a second alternative of the third aspect of the present invention, the task is a method for optimizing resource requirements for a washing process of a surface of a motor vehicle, wherein a sensor is operatively connected to the surface, the method using systematic dependencies, preferably systematic dependencies as described in the second aspect of the present invention, of a system behavior of a washing system of a motor vehicle, preferably of a washing process of at least one surface, preferably for resource-efficient washing, particularly preferably for resource-saving washing, the systematic dependencies representing data sets each representing input quantities of the washing system and output quantities of the washing system, the output quantities depending on the system behavior of the system, preferably at least one control quantity of the washing process and a systematic dependency of the washing system behavior between the availability of the sensor at the start time of the washing process and the availability of the sensor at the end time of the washing process, and the resource requirements of the washing process depending on the control quantity, - accessing the systematic dependencies from a database and / or an electronic data processing and evaluation unit and / or an electronic control unit; - deriving, for a systematic dependency process, a process of the difference between the availability of the sensor at the end of the cleaning process and the availability of the sensor at the start of the cleaning process; - deriving, for the systematic dependency processes, the difference processes and the ratio processes of the respective resource requirement processes; - selecting the control quantity that belongs to the point in the course of the ratio that exhibits the highest value of the ratio; -preferably storing the control quantity as a control quantity setpoint in a database and / or an electronic data processing and evaluation unit and / or an electronic control unit.

[0480] According to the above-mentioned first alternative of the third aspect of the present invention, discrete empirical values ​​are used in a procedure for optimizing the resource requirements of a cleaning process, preferably for resource-efficient cleaning, particularly preferably for resource-saving cleaning.

[0481] The resolution of the input quantities, in particular the control quantities, over the range of possible representations of the input quantities depends on the number of available empirical values ​​and the distribution of these available empirical values ​​over the range of possible representations of the input quantities.

[0482] Alternatively, it is now proposed to map the system behavior of the cleaning process by systematic dependencies, preferably by systematic dependencies according to the second aspect of the present invention.

[0483] Preferably, the systematic dependence is represented by data sets, each data set representing an input quantity of a cleaning process and an output quantity of a cleaning process. In particular, it is believed that the systematic dependence is represented by a defined number of data sets and a defined distribution over the range of possible input quantities.

[0484] This advantageously enables the systematically dependent datasets to be derived from empirical values ​​so that an optimal number of datasets and an optimized distribution of datasets are obtained in the range of possible representations of the input quantities, in the sense of resource-efficient cleaning, particularly preferably resource-saving cleaning.

[0485] As far as specific data sets in the context of systematic dependencies defined by input and output quantities are concerned, these can also preferentially be proceeded with following the procedural steps of the first alternative of the third aspect.

[0486] Alternatively, the systematic dependence may be given by its mathematical description, which consists of a curve representing the dependence between at least one input quantity and at least one output quantity.

[0487] Particularly preferably, the systematic dependence in the form of a curve over the complete defined range of the curve represents the dependence of at least one output quantity on at least one input quantity.

[0488] The preferred definition range of the curve is at least as large as the range of possible representations of the input quantity.

[0489] Also, when a systematic dependency is defined by a curve, the systematic dependency can be said to represent data sets each representing at least one input quantity of the cleaning system and at least one output quantity of the cleaning system, particularly since the individual data sets can be read from the curve, for example, by calculating the output quantity of a grid of input quantities.

[0490] Preferably, the systematic dependence has at least one control variable as an input variable.

[0491] Preferably, the systematic dependency comprises a dependency between the availability of the sensor at the start time of the cleaning process and the availability of the sensor at the end time of the cleaning process, whereby an increase in availability can be determined.

[0492] By using systematic dependencies, it is advantageously achieved that mathematical methods can be used to determine the extrema of the system behavior when searching for optimal control variables, especially if the systematic dependencies are continuous and differentiable in the form of a curve.

[0493] Furthermore, this alternative can advantageously be achieved to determine a better optimality for the control variable setpoints compared to the first alternative of the third aspect of the present invention, thereby enabling a more advantageous comparison and enabling even more resource savings.

[0494] This means that on the one hand, the process of determining the systematic dependence, in particular the determination after the second aspect of the present invention, smooths out measurement inaccuracies and fluctuations in the system behavior, and preferably allows for the formation of a discrete description by means of discrete empirical values, generating a continuous, stable and differentiable representation of the systematic dependence and achieving greater accuracy in mapping the system behavior.

[0495] Furthermore, the optimization results can be improved by selecting optimal control variable setpoints from those regions that are optimal from a mathematical point of view, but for which no empirical data is currently available.

[0496] It is specifically proposed here that the resource consumption for cleaning of the surfaces selected for cleaning is optimized based on the system behavior of the cleaning process, so that, depending in particular on the current initial situation and using the systematic dependencies described in the second aspect of the present invention, better cleaning results can be advantageously achieved with less resource input.

[0497] The method proposed here is designed to optimize cleaning of surfaces relative to the sensors and generate control variable set points that are optimized for each individual surface being cleaned.

[0498] Preferably, the procedure can be carried out sequentially for several surfaces to be washed, which is advantageous in that the control quantity setpoints can be defined successively for each surface of the vehicle to be washed.

[0499] It is understood that the procedural steps following the second alternative of the third embodiment should be slightly modified from the first alternative of the third embodiment.

[0500] In particular, the database and / or dependency tables in the electronic data processing and evaluation unit and / or electronic control unit are not accessed, but rather the corresponding systematic dependencies, in particular the systematic dependencies according to the second aspect of the invention, are accessed.

[0501] It is further understood that preferably, discrete data points are not used in the calculation, but the respective mathematical operations are preferably performed on the entire curve over its entire course, which can preferably be performed in defined steps either analytically or by discretization.

[0502] Furthermore, the advantage of the systematic dependence is exploited, and it is understood that the data set is not selected from documented empirical values ​​(which would ensure optimal resource-saving cleaning of the surface to be cleaned), but is an extreme point of the process of the systematic dependence, or at least an extreme point of a region to which the control variable can be adapted. In particular, it is understood that by adjusting the control variable, the selected control variable set point can be placed at the edge of a range.

[0503] It should be clearly pointed out that the systematic dependencies considered here are not limited to that dimension, but can have any number of dimensions of the input quantities and any number of dimensions of the output quantities.

[0504] Preferably, the dependency table and / or the systematic dependency indicates a dependency on the processing quantity, preferably on the humidity and / or temperature in the vicinity of the vehicle and / or on the amount and / or quantity of precipitation and / or on the coordinates of the vehicle, - Before selecting the control quantity, the datasets taken into account in selecting the control quantity from the dependency table and / or the areas of systematic dependency taken into account in selecting the control quantity are first limited to areas that deviate from the respective processing quantities, preferably the current and / or predicted humidity along the planned journey, and / or the current and / or predicted temperature in the vicinity of the vehicle along the planned journey, and / or the current and / or predicted rainfall along the planned journey, and / or the current and / or predicted snowfall along the planned journey, and / or the coordinates of the vehicle and / or the predicted coordinates of the vehicle along the planned journey, by less than 20%, preferably by less than 10%, particularly preferably by less than 5%.

[0505] It is here particularly proposed that the optimization of the control quantity setpoints, in other words the minimization of the resource requirements for washing a single surface of the vehicle to be washed, also takes into account at least one throughput quantity.

[0506] Needless to say, the cleaning success of a cleaning process carried out after a prolonged period of drizzle will be different from when a cleaning process defined with the same amount of control is carried out on a hot summer day with strong sunlight, taking into account at least the same degree of previous soiling and the same type of soiling.

[0507] In other words, a resource-optimal cleaning process also depends on at least one throughput variable, which can then be taken into account when optimizing the optimal control variable setpoint.

[0508] The same can be achieved if the empirical values ​​stored in the dependency table are initially dependent on the throughput, preferably on the relevant throughput. The same applies when using systematic dependencies, in particular the systematic dependencies according to the second aspect of the invention, which must also have a dependency on the throughput, preferably on the relevant throughput, so that the optimization can take into account what is proposed here.

[0509] It is proposed that the number of empirical values ​​from the dependency table taken into account when selecting the optimal control quantity setpoint and / or systematic dependency range for consideration during optimization be limited to a range that does not deviate by more than 20% from the currently prevailing throughput or the throughput expected according to weather forecasts at the time of the planned cleaning process, preferably by less than 10%, and particularly preferably by less than 5%.

[0510] Such a restriction ensures that the experience of a cleaning process carried out in sunlight is not transferred to a pending cleaning during snowfall. In other words, only the experience from a situation that essentially corresponds to the impending cleaning situation is transferred to the respective situation.

[0511] In particular, the accuracy of the mapping between selected control variables that are expected to be optimal and the results achieved during the cleaning process can be advantageously improved.

[0512] The throughput is preferably understood as the weather of the pre-planned route. The determination of the optimal control quantity setpoint may also depend on whether the pre-planned route reaches weather conditions that require fewer resources for cleaning, in particular during rain and / or snowfall. In this way, by including the expected weather conditions in the determination of the control quantity setpoint, which may also include the cleaning time, it may be advantageously achieved that the total resources required for cleaning can be advantageously reduced. This is also implied, inter alia, by the inclusion of the throughput.

[0513] It should be pointed out that the above values ​​for the considered range of throughput should not be understood as hard limits, but rather should be able to be exceeded or fallen below on an engineering scale without departing from the described aspects of the invention. In short, the values ​​are intended to indicate the size of the considered throughput regime proposed here.

[0514] Conveniently, - dependency tables and / or systematic dependencies showing the dependency of the start time of the cleaning process on the availability of sensors, In particular, preferably by applying the method for determining the expected availability of a vehicle for a distance or operating time not yet covered according to the tenth aspect of the present invention, before the selection of the control quantity, the data sets taken into account in the selection of the control quantity from the dependency table and / or the region of systematic dependency taken into account in the selection of the control quantity are first limited to a region 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%, particularly preferably by less than 5%.

[0515] It is suggested here that optimization of the control variable set points involves the availability of sensors that are actively connected to the surface being cleaned.

[0516] A cleaning process defined by a control amount, measured by increased availability, will result in different cleaning successes for surfaces with different initial soiling. Preferably, better cleaning results are obtained for heavily soiled initial situations than for more heavily soiled surfaces, and since cleaning is performed with the same control amount in each case, equivalent resource requirements are required in each case.

[0517] In this regard, contamination at the start of the cleaning process can affect the resource efficiency of the cleaning process.

[0518] In particular, consideration of the initial contamination status of the surface to be cleaned, assessed by the availability of sensors at the start time of the cleaning process, is made possible by the fact that the empirical values ​​stored in the dependency table initially have a dependency on the availability of sensors at the start time of the cleaning process. The same applies when using systematic dependencies, in particular the systematic dependencies according to the second aspect of the invention, which must also depend on the availability of sensors at the start time of the cleaning process, and which can therefore be taken into account in the optimization.

[0519] When considering the availability of sensors at the start of the cleaning process, the same applies as already done for the throughput consideration: here too, the range of empirical values ​​and / or the range of systematic dependencies taken into account for optimization from the dependency table is limited to a range that deviates from the actual availability of sensors by less than 20%, preferably by less than 10%, particularly preferably by less than 5%.

[0520] Due to the resulting restriction, it can be advantageously achieved that only experience from situations that essentially coincide with the next cleaning situation is transferred to these situations.

[0521] In particular, the accuracy of the mapping between selected control variables that are expected to be optimal and the results achieved during the cleaning process can be advantageously improved.

[0522] Furthermore, it is particularly important here to consider that in the preliminary planning of the next cleaning process, in particular in the procedure described in the tenth aspect of the present invention, the expected availability of sensors when carrying out the cleaning process is estimated in advance.

[0523] Thus, depending on the distance covered by the vehicle to the cleaning process or the operating time covered by the vehicle to the cleaning process, the expected availability of the sensors can first be determined, and based on this, the limitation of empirical values ​​from the dependency table and / or the area of ​​systematic dependency can be carried out.

[0524] The planning accuracy of the cleaning process can be advantageously improved and the resource requirements for cleaning the surfaces connected to the sensors can also be advantageously reduced.

[0525] It should be pointed out that the above values ​​for the considered range of availability of sensors for the start time of the cleaning process should not be understood as hard limits, but rather should be able to be exceeded or fallen short on an engineering scale without departing from the described aspects of the invention. In short, the values ​​are intended to indicate the size of the considered availability of sensors for the start time of the cleaning process proposed here.

[0526] Optionally, - dependency tables and / or systematic dependencies showing the dependency of the start time of the cleaning process on the availability of sensors, - before the selection of the controlled variable, the data sets taken into account in the selection of the controlled variable from the dependency table and / or the region of systematic dependency taken into account in the selection of the controlled variable are first limited to a region in which the availability of the sensor at the start time of the cleaning process is less than or equal to the actual availability of the sensor, The availability of the sensor at the start time of the cleaning process associated with the selected controlled variable is further saved together with the selected controlled variable as a controlled variable setpoint.

[0527] Contrary to the above, it is now proposed to optimize the cleaning process with respect to its resource efficiency, so that at the time of optimization a decision is also made as to the conditions that must be met in order to start the cleaning process, and in particular the availability of sensors that is achieved in order to start the cleaning process.

[0528] In other words, the pre-planned cleaning process must be initiated by the cleaning method, in particular by the cleaning method according to the first aspect of the invention, if a predetermined availability of the sensor at the start time of the cleaning process is achieved by the process proposed here.

[0529] The proposed method is made possible by the fact that the empirical values ​​stored in the dependency table depend primarily on the availability of sensors at the start time of the cleaning process. The same applies when using systematic dependencies, in particular the systematic dependencies according to the second aspect of the invention, which must also depend on the availability of sensors at the start time of the cleaning process, and this can therefore be taken into account in the optimization.

[0530] At the same time, in addition to the control variable setpoint, the optimum availability of the sensor at the start is also selected or determined from the input variables of the selected optimum empirical value or optimum point of systematic dependence.

[0531] After the sensor that is effectively connected to the surface to be cleaned already indicates an actual availability value, this method allows only the optimal cleaning process to be selected, within the physically possible range of resources, to either start immediately, since it is already at the limit of the sensor's currently reached availability, or to start in the future, at the defined availability of the sensor at the start time, since this must first be achieved by additional contamination of the surface to be cleaned.

[0532] By storing the selected control variable setpoint along with the sensor availability at the start time of the cleaning process, the cleaning method can start the cleaning process by reaching the determined optimal availability of the sensor at the start time of the cleaning process.

[0533] Therefore, the resource requirements of the cleaning process can be further reduced in an advantageous way, since the procedure proposed here selects the most resource-efficient cleaning process within the framework of what is still possible.

[0534] In a preferred embodiment, before the selection of the control variable, the data sets taken into account in the selection of the control variable from the dependency table and / or the areas of systematic dependency taken into account in the selection of the control variable are initially limited to areas in which the expected increase in availability does not exceed the availability that would allow the current journey of the vehicle to be carried out without unintended failure of the sensor function by 20% and / or until an availability threshold is reached, preferably by not exceeding 10%, particularly preferably by not exceeding 5%; In particular, preferably by applying the method for determining the expected increase in availability according to the fourteenth aspect of the present invention, the sum of the current availability and the expected increase in availability is sufficient to achieve the distance covered or operating time of the vehicle such that the availability threshold is not exceeded.

[0535] Motor vehicles pollute not only during active vehicle operation, especially when the vehicle is used to cover distances, but also during passive vehicle operation when the vehicle is parked at a point, especially when the vehicle is unprotected and exposed to the weather.

[0536] With regard to the use of resources for washing a vehicle, if a vehicle or part thereof is washed shortly before the end of the vehicle's planned operation, particularly if this is likely to be before the next active operation in which the vehicle will be heavily contaminated by the vehicle's passive operation, it may be less resource efficient, and therefore at the start of the vehicle's next operation, at least one washing process must be initiated to restore the availability of the driver assistance systems.

[0537] In other words, possible over-cleaning can be prevented before the end of active vehicle operation, in order to save both cleaning benefits and overall resources. The procedure proposed here makes this possible.

[0538] Alternatively, there is provision for a further optional embodiment modification to occasionally wet surfaces that are only effectively connected to unnecessary sensors with a spray of cleaning fluid.

[0539] In this way, it can be advantageously achieved that surfaces that are not actively connected to one of the required sensors do not dry out, and thus advantageously prevent the adhesion of contamination present on these surfaces.In this way, it can be advantageously achieved that a separate cleaning process aimed at directly cleaning the surface can work with fewer cleaning resources, since it does not need to quickly remove a layer of covered dirt, but rather removes already soaked or pre-soaked dirt.

[0540] In other words, no cleaning process is proposed here that is specifically aimed at the immediate cleaning of surfaces, but rather a cleaning process that makes it easier for subsequent cleaning processes aimed at the immediate cleaning of surfaces to achieve better cleaning results, in particular with less resource consumption and improved availability.

[0541] Thus, in combination, they can enable a more efficient cleaning process.

[0542] For this purpose, the region of system behavior mapped by empirical values ​​from the dependency table or by systematic dependencies that can be selected by the procedure is limited to a region so that the expected increase in availability does not exceed the availability that would allow the vehicle's current journey to be carried out without unintentional failure of the sensor function by 20% and / or until an availability threshold is reached, preferably by no more than 10%, particularly preferably by no more than 5%.

[0543] Preferably, the expected increase in availability of each evaluated cleaning process can be determined by applying the method described in the fourteenth aspect of the present invention.

[0544] Therefore, the cleaning process selected by this method, on the one hand, does not result in significant over-cleaning of the surface in active connection with the sensor, and on the other hand, it can be advantageously achieved that no post-cleaning is required to maintain the driver assistance system before reaching the target, with a certain degree of safety.

[0545] In this way, resources can be saved for cleaning surfaces that are effectively connected to the sensor.

[0546] It should be pointed out that the above values ​​of the contemplated region of expected increase in sensor availability due to the cleaning process should not be understood as hard limits, but rather should be able to be exceeded or fallen short on an engineering scale without departing from the described aspects of the invention. In simple terms, the values ​​are intended to indicate the size of the contemplated expected increase in sensor availability due to the cleaning process proposed herein.

[0547] A method for optimizing resource requirements for a cleaning process of a surface of a motor vehicle, wherein before the selection of the control variable, the datasets taken into account in the selection of the control variable from the dependency table and / or the areas of systematic dependency taken into account in the selection of the control variable are first limited to areas in which the expected increase in availability is sufficient to cover the distance or the operating time to the next cleaning process without falling below an availability threshold, in particular by applying a method for determining the expected distance or the expected operating time of the motor vehicle not yet covered when the availability threshold is reached, preferably by applying the method according to the eleventh aspect of the present invention, in particular by applying the method for determining the expected increase in availability, preferably by applying the method according to the fourteenth aspect of the present invention, in which the increase in availability is not more than 20%, preferably not more than 10%, particularly preferably not more than 5% of the increase in availability necessary to cover the distance or the operating time to the next cleaning process without falling below the availability threshold, 7. The method according to claim 1, wherein the sum of the current availability and the expected increase in availability is sufficient to achieve the distance covered or the operating time of the vehicle such that the availability threshold is not exceeded.

[0548] In some situations of vehicle operation, particularly when the currently still available cleaning resources are particularly scarce, it is advantageous if only minimally invasive cleaning processes are performed so that the next intermediate goal and / or the next opportunity to replenish cleaning resources can still be achieved using the existing cleaning resources.

[0549] In particular, it is believed that autonomous vehicle operation can be maintained until the next gas station with a minimum of cleaning measures required. Although the minimally invasive cleaning process proposed here is not optimally resource efficient in the sense of minimizing the use of cleaning agents and maximizing their availability, the available resources are used optimally and efficiently, in particular in the sense of achieving the operational goals of the vehicle operator, who wants to reach the next intermediate destination autonomously.

[0550] This can be achieved by the following: prior to the selection of the control quantity, the data sets taken into account in the selection of the control quantity from the dependency table and / or the region of systematic dependency taken into account in the selection of the control quantity are first limited to regions in which the expected increase in availability is sufficient to fill the distance or operating time to the next cleaning process without falling below the availability threshold, in particular when the availability threshold is reached, and not exceeding by 20%, preferably not exceeding by 10%, particularly preferably not exceeding by 5% the increase in availability required to fill the distance or operating time to the next cleaning process without falling below the availability threshold.

[0551] In other words, here the solution space is limited by two aspects.

[0552] It should be noted in particular that before selecting the control quantity setpoint, the expected distance or expected operating time of the vehicle not yet covered when the availability threshold is reached is determined, preferably by the procedure described in the eleventh aspect of the present invention.

[0553] Furthermore, it should be particularly considered that before the control quantity set point is selected, the expected increase in availability during the execution of the cleaning process is also determined by the procedure described in the fourteenth aspect of the present invention.

[0554] The advantage of this is that the vehicle can make a selection of the cleaning process in such a way that it can optimally achieve the minimum targets defined by the driver with the available resources.

[0555] It should be pointed out that the above values ​​of the contemplated region of expected increase in sensor availability due to the cleaning process should not be understood as hard limits, but rather should be able to be exceeded or fallen short on an engineering scale without departing from the described aspects of the present invention. In simple terms, the values ​​are intended to indicate the size of the contemplated expected increase in sensor availability due to the cleaning process proposed herein.

[0556] In a preferred embodiment, a first control quantity and a second control quantity are selected, and the respective first control quantity set values ​​and the respective second control quantity set values ​​define first and second cleaning processes for a sequence of cleaning processes, and the second cleaning process is performed after completion of the first cleaning process.

[0557] Here, it is specifically proposed to divide the cleaning process of the surface to be cleaned into two or more individual cleaning processes of a jointly planned sequence.

[0558] The first cleaning process is defined by a first controlled variable setpoint, and the second cleaning process is defined by a second controlled variable setpoint.

[0559] Both control quantity setpoints should also be considered to include conditions for triggering the respective cleaning processes within the cleaning method, in particular within the cleaning method according to the first aspect of the invention, in particular the achievement of a time distance, a spatial distance or a defined triggering availability between the individual cleaning processes.

[0560] The advantage is that resources for cleaning can be saved when multiple cleaning processes are more resource efficient than a single cleaning process. Surprisingly, it turns out that this can manifest itself for each input quantity or several constellations of each input quantity.

[0561] Optionally, the method is performed in series or parallel for multiple surfaces to be cleaned, particularly for two, three, four, five or more surfaces to be cleaned.

[0562] So far, procedures have only been described to the extent that the cleaning process carried out is optimized for only one surface at a time.

[0563] It is specifically proposed here to apply this procedure to multiple surfaces to be cleaned, in particular sequentially or in parallel.

[0564] Advantageously, the control variables are selected by a multi-criteria optimization procedure.

[0565] Here, it is specifically proposed that the selection of the optimal cleaning process is carried out with the help of a multi-criteria optimization procedure.

[0566] Such a procedure is particularly suitable for optimizing different resources simultaneously and independently of each other.

[0567] In addition to the cleaning solution, it should be a priority to be able to use a special cleaning lotion.

[0568] By using a multi-criteria optimization approach, the advantage can be advantageously achieved that different resources can be considered equally advantageously resource efficient in decisions based on the Pareto front being developed.

[0569] According to the third aspect of the invention, it is preferably possible to take into account other influencing variables for resource optimization, in particular the device type of the sensor, the temperature of the cleaning liquid, the composition of the cleaning liquid, the movement speed of the wiping element, the amount of cleaning liquid, the orientation of the nozzles, etc.

[0570] Control variables may also be the temperature of the cleaning fluid, the composition of the cleaning fluid, the speed of movement of the wiping element, the amount of cleaning fluid, and / or the orientation of the nozzle.

[0571] Needless to say, the advantages of systematic dependence, in particular the systematic dependence described in the second aspect of the invention, also apply to the use of systematic dependence, in particular the use of systematic dependence proposed here according to the third aspect of the invention.

[0572] 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 individually or cumulatively in any combination.

[0573] According to a fourth aspect of the present invention, the task is a method for determining a washing strategy for washing a surface to be washed of a motor vehicle, the surface to be washed being selected depending on a washing mode, and a sensor being operatively connected to the surface to be washed; The sensor indicates the actual availability and the cleaning strategy indicates the control variable set points that define the cleaning process of the surface to be cleaned; - preferably checking the actual cleaning mode; - selecting at least one sensor required for the currently selected cleaning mode; - checking the actual availability of each selected sensor; - determining resource-efficient, preferably resource-saving, control variable setpoints for the cleaning of each surface to be cleaned operatively connected to each selected sensor, in particular by applying a method for optimizing resource requirements for the cleaning process of a surface of a motor vehicle, preferably by applying the method described in the third aspect of the invention; -preferably operatively connected to each selected sensor for storing determined control variable setpoints for resource-efficient, preferably resource-saving, cleaning of each surface to be cleaned, and particularly preferably storing the determined control variable setpoints in a cleaning strategy, preferably in a database and / or an electronic data processing and evaluation unit and / or an electronic control unit.

[0574] If the availability of the 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.

[0575] A third aspect of the invention describes a procedure for optimizing a cleaning process in terms of resource consumption for the surface to be cleaned, operatively connected to a sensor.

[0576] 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.

[0577] However, the procedure described in the third aspect of the invention does not take into account whether the particular surface connected to the sensor needs to be thoroughly cleaned, in other words whether it is necessary to increase the availability of the sensor by performing a cleaning process, preferably for the current or planned use of the vehicle, by performing a cleaning process after the first aspect of the invention.

[0578] A fourth aspect of the present invention is based on the idea that not all sensors are required at all times for current or planned vehicle operation.

[0579] If cleaning surfaces with sensors that are not currently needed, cleaning resources are also needed for this purpose.

[0580] A fourth aspect of the present invention takes advantage of this context to save washing resources and allows only the surfaces of the vehicle to be washed by the washing process, in particular by a washing method according to the first aspect of the present invention, which also has an active connection to at least one sensor whose function is desired for current or planned vehicle operation according to the selected washing mode.

[0581] This advantageously allows for savings in cleaning resources, particularly since the availability of sensors whose functionality is not currently required can also fall below the availability threshold.

[0582] For this purpose, the cleaning strategy for cleaning the surfaces to be cleaned of the vehicle is determined by the procedure proposed here and, depending on the cleaning mode, for the entire vehicle, it is also determined whether the surface is to be cleaned, if so, how, i.e. with which cleaning process this surface is to be cleaned, preferably by determining corresponding control variables, preferably using the procedure described in the third aspect of the invention.

[0583] 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 reserved for cleaning. In this context, the corresponding sensors may also be referred to as "selected sensors".

[0584] Furthermore, the control quantity setpoints, preferably resource-efficient, particularly preferably resource-saving, control quantity setpoints for cleaning, are preferably determined for each selected sensor by applying a method for optimizing resource requirements for a cleaning process of a surface of a motor vehicle, particularly preferably by applying the method according to the third aspect of the present invention.

[0585] Preferably, each control variable set point thus determined for each selected sensor is stored in a cleaning strategy.

[0586] Needless to say, as soon as the cleaning mode is changed, the cleaning strategy becomes invalid: as soon as the cleaning mode is changed, a different cleaning strategy must be applied within the cleaning method, preferably within the cleaning method according to the first aspect of the invention, or a new cleaning strategy must be determined according to the proposed procedure.

[0587] It is expressly noted that cleaning mode may coincide with operating mode, but this is not necessarily the case, and therefore these terms are used separately herein.

[0588] 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.

[0589] Preferably, it is suggested that the cleaning strategy can override vehicle and / or driver commands as a last-ditch rescue measure to clean surfaces of selected sensors whose availability has reached and / or fallen below an availability threshold.

[0590] Furthermore, it is preferred that the cleaning strategy also provides for determining the cleaning of sensors other than the selected sensors, especially if one of the selected sensors is malfunctioning.

[0591] Preferably, before the control quantity setpoint is determined, the distance and / or operating time that the vehicle can still cover is first determined as a function of the actual availability of the selected sensor until the expected availability reaches an availability threshold at which the surfaces operatively connected to the associated sensor need to be cleaned, in particular by applying a method for determining the expected distance or expected operating time of the vehicle not yet covered when an availability threshold is reached, preferably by applying the method described in the eleventh aspect of the present invention.

[0592] To date, the vehicle coverage achievable with available cleaning resources has not been considered when determining cleaning strategies.

[0593] This is exactly what is being proposed here.

[0594] When operating a vehicle, a distinction can be made between vehicle operation modes, for example, active vehicle operation, characterized by the fact that the vehicle completes a driving distance, and passive vehicle operation, where the vehicle is parked and awaits the next active vehicle operation.

[0595] Vehicles are contaminated during both active and passive vehicle operation. For reasons of optimal cleaning of vehicle surface resources, it is particularly proposed that the surfaces are not over-cleaned, which is characterized by the fact that the surfaces are thoroughly cleaned just before reaching the end of active vehicle use.

[0596] Instead, it is proposed here that the cleaning process can pursue the goal of cleaning the surface only to the extent that the availability provided by the cleaning process is sufficient to achieve the goal of active vehicle operation, and to this end the associated control variable setpoints can be determined in particular by the method described in the third aspect of the present invention.

[0597] Further effects arise from the fact that different cleaning modes require different amounts of cleaning resources: in particular, a cleaning mode designed to maintain autonomous vehicle operation will require more cleaning resources than a cleaning mode designed to maintain at least one driver assistance system that is intended merely to assist the driver in operating the vehicle, but is not permitted for autonomous vehicle operation.

[0598] As a result of this, here, following the previous step of determining the control variable setpoints, first determine the expected distance that the vehicle can still cover and / or the expected operating time as a function of the actual availability of the selected sensors, preferably by applying the method according to the eleventh aspect, until the expected availability reaches a respective threshold of availability, before determining the control quantity setpoint, in particular by following a further step of checking the quantity of available cleaning resources, which is given priority by a corresponding sensor, in particular a level sensor, etc., Depending on the currently selected cleaning mode, the corresponding control variable setpoints are used to determine the cleaning strategy and, in this connection, the resource requirements for cleaning; Compare whether sufficient resources are available to meet the resource requirements of this cleaning strategy to reach the destination, If this is not the case, it is preferable to offer the driver a washing mode that allows the destination to be reached with the available resources and / or to request the driver to replenish the corresponding resources, and it is proposed that the washing strategies offered be achieved in descending order according to the resource requirements in order to determine the washing strategy until a washing strategy is found that allows the vehicle to reach the destination without one of the selected sensors reaching an availability below the associated availability threshold by using the selectable washing modes.

[0599] In this way, it can be advantageously achieved that a driver of a vehicle in a situation where the required resources according to the selected washing mode are not sufficient to reach the destination can decide whether he wants to perform a service stop to replenish the required resources that can maintain the currently selected washing mode, or whether he wants to eliminate the availability of the driver assistance system and, if necessary, reach the destination faster.

[0600] Optionally, the availability threshold varies depending on the cleaning mode selected.

[0601] Different cleaning modes may require different tolerances for the selected sensors.

[0602] In particular, the fault tolerance of selected sensors in a wash mode configured for fully autonomous vehicle operation may be considered to be lower than a wash mode configured for vehicle operation that does not allow fully autonomous vehicle operation.

[0603] It is proposed here that the availability threshold of each sensor may have different values ​​for different cleaning modes.

[0604] In this way it can be advantageously achieved that resources for cleaning can be saved by different thresholds of availability of different cleaning modes.

[0605] Conveniently, the cleaning mode is read from the electronic control unit.

[0606] It is suggested here that the cleaning mode can be read from the electronic control unit, which allows the cleaning mode to be defined in the electronic control unit and used therefrom advantageously in a range of cleaning methods, in particular in a range of methods for determining the cleaning method and cleaning strategy according to the first aspect of the invention, in particular the method according to the fourth aspect of the invention.

[0607] Furthermore, it can be advantageously achieved that the cleaning mode can be defined in the electronic control unit, in particular by the manufacturer of the vehicle, so that the manufacturer of the vehicle can also influence the cleaning of the sensor surface, in particular since these are safety-related aspects that may also fall within the manufacturer's area of ​​responsibility in the event of a malfunction.

[0608] Optionally, the cleaning mode is obtained from a selection means.

[0609] Let's explain the terminology in detail.

[0610] "Selection means" is to be understood as a device by which a cleaning mode can be selected. Preferably, a rotary switch or a selector slide or an electronic input unit or the like may be considered here.

[0611] Here, it is specifically proposed that the cleaning mode can be obtained from a selection means, in particular a selection means that is within the direct influence of the vehicle driver, so that the driver can influence the cleaning mode and thus indirectly influence the cleaning strategy according to his needs by adjusting the selection means.

[0612] According to a preferred variant of the embodiment, the cleaning mode is set to enable fully autonomous vehicle operation, and each surface operably connected to a sensor associated with fully autonomous vehicle operation should be cleaned.

[0613] Here, we propose to set up a cleaning mode for fully autonomous vehicle operation.

[0614] If a vehicle is being configured and registered for fully autonomous vehicle operation, this preferably means that all sensors installed in the vehicle must be selected and therefore the availability of all sensors must be guaranteed.

[0615] In other words, this could lead to a situation where fully autonomous vehicle operation would have to be halted if such a vehicle fell below an availability threshold, at least until the corresponding availability was again above the availability threshold.

[0616] In the case of a cleaning system, this means that the availability of the sensor must not fall below the associated availability threshold. The same applies as the object of cleaning methods, in particular the cleaning method according to the first aspect of the invention, and consequently also to the method proposed here for determining a cleaning strategy.

[0617] According to another preferred variant of the embodiment, the cleaning mode is set to enable comfortable vehicle operation for the designated driver of the vehicle, and each surface operably connected to a sensor associated with comfortable vehicle operation should be cleaned.

[0618] The cleaning mode proposed here is related to the comfortable operation of the vehicle.

[0619] Preferably, this means that operation is comfortable for the driver of the vehicle, where comfortable does not mean fully autonomous vehicle operation, but rather vehicle operation that is characterized by the fact that the driver of the vehicle is primarily in control of the vehicle himself.

[0620] However, comfortable vehicle operation is understood to mean some driver assistance systems that can make driving more comfortable for the driver, in particular functions such as lane departure warning systems or distance warning systems.

[0621] In other words, what is proposed here is for the washing system to ensure the availability of all selected sensors associated with the washing mode set to allow comfortable vehicle operation in an appropriate washing method, in particular the washing method described in the first aspect of the present invention.

[0622] According to another preferred variant of the embodiment, the cleaning mode is set to enable vehicle operation that is as safe as possible for the designated driver of the vehicle, and each surface that is operably connected to a sensor associated with vehicle operation that is as safe as possible should be cleaned.

[0623] It is proposed here that the availability of all sensors required for a safety-related driver assistance system is monitored, and the method proposed here is configured to ensure that the availability of each does not fall below the associated value of the associated availability threshold.

[0624] According to another preferred variant of the embodiment, the cleaning mode is set to enable the vehicle to have the best possible range, and each surface operably connected to a sensor associated with the vehicle operation that has the best possible range should be cleaned.

[0625] The washing mode proposed here allows the vehicle to achieve maximum coverage with the remaining washing resources.

[0626] This is preferably made possible by deactivating all driver assistance systems for active vehicle operation not prescribed by law, so that associated sensors are also available below any relevant availability thresholds.

[0627] In an advantageous embodiment, the method is carried out for multiple surfaces to be cleaned, in particular for two, three, four, five or more surfaces to be cleaned.

[0628] Here, a method is proposed to establish a cleaning strategy for multiple surfaces to be cleaned, which can be performed in series or in parallel.

[0629] This applies preferentially to all surfaces of the vehicle that are actively connected to (selected) sensors.

[0630] Optionally, the step of determining the control quantity setpoint takes into account measured quantities, preferably process quantities, particularly preferably current and / or predicted humidity along the planned journey, and / or current and / or predicted temperature in the vicinity of the vehicle along the planned journey, and / or current and / or predicted rainfall along the planned journey, and / or current and / or predicted snowfall along the planned journey.

[0631] It is provided here that the measured quantity is taken into account when determining the cleaning strategy.

[0632] This preferably allows for control quantity setpoints to be found based on current or forecasted weather conditions along the pre-planned route, thereby providing a better relationship between increased availability of individual selected sensors and the cleaning resources used than control quantity setpoints that do not take into account the measured quantities.

[0633] In particular, what has already been done under the third aspect of the invention applies here, with the necessary adjustments.

[0634] Preferably, the step of determining the control variable set point takes into account the vehicle type.

[0635] In particular, the type of vehicle provides information about the built-in washing system and, in this context, the location and orientation of the surface intended to be washed. In particular, this applies to the necessary adjustments already made under the second aspect of the invention.

[0636] It is understood that the determination of the control strategy can take into account any resources for cleaning one or more surfaces. In particular, it is important to consider that the cleaning system may have resource limitations, which can also be taken into account when determining the cleaning strategy. Preferably, the flow rate of the fluid pump can be considered as a possible boundary condition, which may require that only a certain number of cleaning processes can be performed in parallel.

[0637] Preferably, selected sensors are proposed to be cleaned as a last-ditch rescue measure by a predetermined pre-cleaning process when their respective availability falls below a corresponding availability threshold.

[0638] 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 individually or cumulatively in any combination.

[0639] According to a fifth aspect of the present invention, there is provided a method for indirectly deriving systematic dependencies of the system behavior of system components of a washing system of a motor vehicle, the washing system being adapted to at least one surface of the motor vehicle by a washing process, preferably adapted for resource-efficient washing, particularly preferably adapted for resource-saving washing, wherein output quantities depend on input quantities due to the system behavior of the system, - determining an input quantity as a first parameter of the method by means of at least one sensor; - determining an output quantity as a second parameter of the method, preferably determined by at least one sensor; - digitizing and recording, if necessary, the determined first and second parameters by a data processing system, which data processing system represents an electronic data processing and evaluation system and database; - storing the determined first and second parameters in a database in an ordered manner relative to one another as a data set of a dependency table; - deriving systematic dependencies between first and second parameters by means of an electronic data processing and evaluation system from at least two datasets of dependency tables stored in a database, preferably from at least 50 datasets of dependency tables, particularly preferably from at least 200 datasets of dependency tables, wherein the electronic data processing and evaluation unit accesses the datasets of the dependency tables and determines the systematic dependencies from the datasets of the dependency tables by means of an algorithm; - Preferably, storing the derived systematic dependencies in a database and / or an electronic data processing and evaluation unit and / or an electronic control unit. Additionally, due to the growing importance of driver assistance systems that rely on information provided by sensors, automobiles are being equipped with an increasing number of sensors.

[0640] Most of these sensors rely on the ability of a surface to be actively connected to the individual sensors to avoid excessive contamination.

[0641] In addition to the number of sensors, the number of sensor locations on a vehicle is also increasing, as is the number of surfaces cleaned by a cleaning system operatively connected to at least one of these sensors.

[0642] As a result, the complexity of automotive wash systems is constantly increasing, particularly the number of nozzles and fluid connections, which has been accompanied by a steady increase in the number and complexity of valve devices, wash fluid pumps and wash fluid reservoirs.

[0643] Just as the automation of the entire vehicle through sensors is increasing, the increased automation of the vehicle also requires the increased automation of individual cleaning processes, and therefore the degree of automation of the vehicle's washing system is also increasing. After all, the driver of a partially autonomous or autonomously operating vehicle cannot be expected to monitor the soiling state of relevant surfaces in correlation with sensors to monitor and / or adjust their driving behavior. Therefore, automation through driver assistance systems also requires the automation of the vehicle's washing system.

[0644] In addition to these complexities mentioned above, the networking of systems with each other plays an increasingly important role.

[0645] Overall, both the number of sensors and systems involved and their complexity and degree of networking are steadily increasing.

[0646] This has resulted in increased susceptibility to errors and associated maintenance requirements for system components associated with the cleaning system. The increased complexity of the individual system components, as well as the overall complexity of the cleaning system, makes it difficult to identify possible errors and makes maintenance of the cleaning system increasingly time-consuming over time.

[0647] The detection of possible errors becomes even more difficult because different system components of a defined washing system of a defined vehicle may also come from different suppliers.

[0648] Although the maintenance expectations for such wash systems are increasing, they have recently been shown to be unable to withstand the ever-increasing system complexity and the need for ever-accelerating system change in the area of ​​automotive wash systems.

[0649] Here, we propose a method to derive systematic dependencies for describing the system behavior of system components in an automobile washing system.

[0650] The system behavior of a system component is the reaction of the system component to its specifications, where the specifications are described by input quantities and the reactions of the system component are described by output quantities.

[0651] In other words, the output quantities of the system components depend on the input quantities, depending on the system behavior.

[0652] It is noted that the system components of the cleaning system can be understood as single parts of the cleaning system, as well as single assemblies and the entire cleaning system. In particular, each of the above variations has an individual system behavior that can be analyzed so that knowledge of the system behavior can be used advantageously later.

[0653] In particular, it is conceivable that the known system behavior of a system component, especially in the form of the systematic dependencies derived herein, can be used to compare with the observed system behavior of this system component. If there is a deviation between the known, and therefore initially expected, system behavior and the observed system behavior, this may indicate a notable feature and / or malfunction and / or defect in the system component and / or cleaning system.

[0654] Thus, the systematic dependencies proposed here are derived on the basis of empirical values ​​and advantageously provide the possibility to compare the observed behavior of the system components with the expected system behavior of the system components described by the systematic dependencies and thus to verify whether the system components and / or the cleaning system behave as expected.

[0655] Preferably, each system component exhibits an individual system dependency.

[0656] For each system component to be diagnosed based on empirical values ​​converted into systematic dependencies, individual systematic dependencies can preferably be derived in accordance with this aspect of the invention.

[0657] The method proposed here can be used to derive systematic dependencies of different system components in series and / or parallel.

[0658] The method proposed here for deriving systematic dependencies from empirical values ​​can be divided into two sections: In the first section, empirical values ​​regarding the system behavior of the system components are collected and stored in a dependency table; input quantities leading to the activity of the system components and output quantities representing the system component's response to the activity caused by the associated input quantities are stored in an ordered manner in the dependency table.

[0659] In the second section of the method, the empirical values ​​collected in the dependency table are further processed by an algorithm into systematic dependencies.

[0660] It should be clearly pointed out that within the framework of this procedure, empirical values ​​can be collected during normal operation of the system components during operation of the vehicle in which they are installed. Furthermore, it is also conceivable that corresponding empirical values ​​can be collected and stored in the dependency table during operation of the system components in a laboratory or in a numerical simulation using a suitable numerical model.

[0661] Of course, the proposed systematic dependence can only take into account the amounts of input and output quantities that can be recorded and therefore evaluated. In particular, the acquisition of quantities by sensors based on physical and / or chemical principles of action must be considered. Furthermore, the determination of quantities by numerical sensors, whose values ​​can be recorded in a numerical model or which, based on the measured quantities, can provide further quantities that are not measured but can be determined numerically depending on at least one measured quantity, is also considered.

[0662] While empirical values ​​are individual experiences with a single input quantity, the advantage of systematic dependence is that it can reproduce the system behavior of system components over a range of input quantities, and in particular, it can reproduce it continuously and discretely.

[0663] The proposed systematic dependence is generated based on discrete empirical sampling points collected by an algorithm, and the systematic dependence at sampling points defined by corresponding input quantities may have different output quantities compared to documented experience, preferably caused by empirical averaging.

[0664] Preferably, an input quantity is understood to be a quantity that is at least indirectly suitable for influencing a system component. It is not necessary that the input quantity can be directly adjusted. The input quantity can also result from environmental conditions. It is particularly considered that low temperatures can lead to ice formation in the washing system, which can also change the system behavior of the system components.

[0665] It should be clearly pointed out that the input and output quantities described in the proposed embodiment are not necessarily limited to quantities that directly affect the system component under consideration, nor are they limited to quantities that can be directly determined by the system component under consideration. Rather, it should be considered that all input and output quantities may be considered in this embodiment, which may indirectly affect the system behavior of the system component under consideration or may be indirectly affected by the system component.

[0666] The first section of the proposed procedure is: - determining, using at least one sensor, an input quantity as a first parameter of the method, which in each case may have several dimensions and which is indicative of the behavior of at least one system component and which can advantageously be provided for further processing by the sensor; - determining an output quantity as a second parameter of the method, preferably determined by at least one sensor, which may in each case have several dimensions, and which output quantity describing the system behavior of the system components as a function of their input quantities determined by the process steps described above, can advantageously be provided by the sensor for further processing; - optionally digitizing and recording the determined first and second parameters by a data processing system, which represents an electronic data processing and evaluation system and database, in which the input and output quantities are advantageously prepared for digital processing and stored; - storing the determined first and second parameters in a database in a mutually related and ordered manner as a data set in a dependency table, in which the previously determined method quantities can be stored in a mutually advantageous ordered manner so that an output quantity is assigned to the input quantity describing the system behavior of the system component caused by the input quantity.

[0667] In summary, the first section of the procedure advantageously enables the generation of a dependency table consisting of empirical values ​​of the system behavior of the system components considered.

[0668] The second section of the proposed procedure is: - deriving by an electronic data processing and evaluation system a systematic dependency between a first parameter and a second parameter from at least two datasets of dependency tables stored in a database, preferably from at least 50 datasets of dependency tables, particularly preferably from at least 200 datasets of dependency tables, wherein the electronic data processing and evaluation unit accesses the datasets of the dependency tables and determines the systematic dependency from the datasets of the dependency tables by means of an algorithm, the systematic dependency being advantageously derived in a mathematical manner by means of a suitable algorithm.

[0669] The derived systematic dependencies can then be advantageously stored so that they can be called up again for further processing, in particular the systematic dependencies are stored in a non-volatile data memory, and it is preferable that the systematic dependencies are stored in a database and / or an electronic data processing and evaluation unit and / or an electronic control unit.

[0670] Preferably, the input quantity represents at least one measured quantity, preferably a processed and / or controlled quantity.

[0671] It is suggested here that the input quantities denote measured quantities, in particular processed and / or controlled quantities.

[0672] A controlled quantity is suitable for directly influencing the cleaning system and therefore, at least indirectly, for influencing the system components of the cleaning system, whereas a processed quantity is a quantity that, at least indirectly, depends on the controlled quantity or cannot be influenced by normal means and only has an effect on the system behavior of the system components.

[0673] The throughput volume is preferably a volume present in or around the washing system that can be influenced, at least indirectly, by the input volume.

[0674] The dependency tables and / or systematic dependencies may have dependencies on directly measured input quantities, in particular process and / or control quantities, which can advantageously achieve taking into account important influence quantities of system components on system behavior.

[0675] In a preferred embodiment, the output quantity and / or the input quantity indicate the resource requirements, preferably the power consumption, of the cleaning process of the surface of the motor vehicle, and preferably the resource requirements are determined depending on the control quantity setpoints for the cleaning process of the surface.

[0676] The power consumption can be relatively easily determined in combination with the system components of the cleaning system.

[0677] The power consumption of a system component can be used relatively quickly and easily to determine whether a change has occurred in a system component that uses energy, since under normal conditions there is relatively little fluctuation in the energy requirements of the system component.

[0678] Thus, power consumption can also be taken into account in describing the system behavior of a system component, and it can be advantageously achieved that also in the context of diagnosing a system component, in particular a diagnosis as described in the sixth aspect of the present invention, the power consumption required by a system component can be advantageously used for comparison between expected and actual system behavior.

[0679] Optionally, the output quantity and / or the input quantity represent a process quantity, preferably a flow rate and / or a 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 leak sensor signal and / or a flow meter signal and / or several actuations and / or spray patterns and / or thermal monitoring signals, preferably signals referenced to a thermal monitoring reference area and / or a debris sensor signal and / or a check valve signal and / or a drip sensor signal and / or a distance sensor signal and / or a force sensor signal.

[0680] In the context of output and / or input quantities, throughput is also a valuable indicator for assessing the system behavior of the system components of an automobile wash system.

[0681] In particular, in this context, it is necessary to consider the amount of processing that is easy to determine or particularly meaningful.

[0682] Specifically, the level signal of the cleaning fluid reservoir can be considered: if a drop in the level signal of the cleaning fluid reservoir is observed even though the cleaning system is not currently being actively used, and in particular the cleaning fluid pump is not actively running, this relatively simply indicates an unwanted leak in the cleaning system through which cleaning fluid is escaping.

[0683] Alternatively, the signal of the flow sensor in the flow channel for the cleaning fluid can also be considered, particularly 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 flows through the flow channel for the cleaning fluid, and if the signal of the flow 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.

[0684] It is necessary to explicitly mention that other processing quantities also have causal correlations to system behavior.

[0685] It can therefore be advantageously achieved that process quantities in the form of output quantities can be included in dependency tables and / or systematic dependencies for assessment of system behavior, and that diagnostics of the cleaning system can be advantageously improved in downstream steps.

[0686] In an optional embodiment, the input quantities indicate humidity and / or temperature and / or amount of rainfall and / or snowfall in the vicinity of the vehicle.

[0687] In particular, it has been shown that certain environmental conditions, such as humidity and / or temperature, and / or rain and / or snow, can affect the system behavior of the washing system, especially the environmental conditions in the immediate vicinity of the vehicle.

[0688] In particular, low temperatures can cause localized freezing within the cleaning system, causing localized flow blockages.

[0689] Furthermore, further dependencies and influences of the quantities on each other can be taken into account.

[0690] By including these quantities in the input quantities, the accuracy of the systematic dependence can be advantageously increased.

[0691] In an advantageous embodiment, the input quantity is indicative of a vehicle type.

[0692] The type of vehicle will determine the specific design and arrangement of the individual system components of the washing system.

[0693] Thus, in different constellations and / or arrangements of the system components, different effects of 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 washing system and therefore represents a simple possibility for unambiguously recording the corresponding interactions.

[0694] In this regard, the interaction between the first system component and the second system component is also determined by the vehicle type.

[0695] Therefore, including vehicle type can advantageously improve the systematic dependencies proposed here, and therefore the mapping accuracy of the dependency table.

[0696] Preferably, the input quantity indicates the availability of the sensor.

[0697] Here, when it is suggested that an input quantity indicates availability, this preferably means availability before starting a cleaning process using the cleaning system.

[0698] The effectiveness of the cleaning process implemented by the cleaning system depends not only on other influencing variables but also on the availability of sensors with which the surfaces to be cleaned are in active connection.

[0699] The availability of a sensor is a measure of the degree of contamination of the surface connected to the sensor.

[0700] It has been shown that different availability of sensors at the start of a cleaning process has an impact on the cleaning result, in other words, cleaning processes carried out in the same way may have different possibilities for increasing availability.

[0701] It is suggested, inter alia, that the input quantities are indicative of the parameters of the cleaning process and / or that the output quantities are indicative of increased availability.

[0702] 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 results, in particular as a function of the parameters of the cleaning process.

[0703] This advantageously makes it possible to evaluate the system behavior of the washing system already with sensors that are already installed, in particular sensors for supporting driver assistance systems.

[0704] In this way, it can be advantageously achieved that for the evaluation of the system behavior of the system components of the washing system, no additional sensors that are required solely for the evaluation of the washing system need to be added.

[0705] It should be clearly pointed out that this aspect is particularly relevant to the second, third, ninth and tenth aspects of the invention, and of course this aspect is also relevant to the other aspects of the invention, and interrelationships exist.

[0706] Optionally, the input quantity indicates the current coordinates of the vehicle.

[0707] It has also been shown that the coordinates of the vehicle affect the system behavior of the system components of the washing system.

[0708] Preferably, weather conditions that depend on the coordinates of the vehicle can be taken into account, in particular the system behavior of the system components of the washing system has been shown to depend on temperature and / or humidity and / or solar radiation and / or precipitation and / or snowfall.

[0709] According to a relatively simple procedure, the weather conditions at the coordinates of the car are correlated with the current latitude on the planet, which can be determined by the coordinates of the car.

[0710] Thus, based on the coordinates of the vehicle and based on correlation with weather conditions, it is possible to take into account relevant influencing variables of the system components of the washing system on the system behavior, and it can be advantageously achieved that the accuracy of the dependency table and / or systematic dependency can be advantageously improved for the system behavior.

[0711] According to a more accurate approach, it is also proposed that the vehicle uses local information about the current and / or predicted weather at its coordinates. Thus, when determining the dependency tables and / or systematic dependencies, influencing variables that are in an effective relationship with the system behavior of the system components of the washing system and that can be determined directly or indirectly by the vehicle's coordinates can be used to improve the mapping accuracy of the predicted system behavior.

[0712] Of course, this aspect is related to other aspects of the invention and interrelationships exist.

[0713] In a preferred embodiment, the output quantity indicates the availability of the sensor and / or an increase in availability due to the cleaning process.

[0714] Here, it is suggested that the output quantity indicates the availability of the sensor and / or increased availability due to use of the cleaning system.

[0715] Here, when it is suggested that the output amount indicates availability, this preferably means availability after completion of a cleaning process using the cleaning system.

[0716] In this manner, it is possible to advantageously determine 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, where the increase in availability is due to the difference between the availability after the cleaning process and the availability before the cleaning process.

[0717] In an advantageous embodiment, the systematic dependence is determined by regression analysis.

[0718] Here, it is suggested to use a regression algorithm as an algorithm for indirectly deriving the systematic dependence.

[0719] Therefore, algorithms that have already been tested in numerous applications and that can be optimally selected and / or adapted according to the system behavior considered here can be advantageously applied to determine high-quality systematic dependencies.

[0720] Preferably, the systematic dependence is determined in the form of a curve, preferably a curve and a coefficient of determination of the curve.

[0721] The advantage of this is that the systematic dependence is shown as a curve as a function of at least one input quantity of the system behavior of the system components, in particular this curve is gap-free, so that a clear assignment between the input quantities and the output quantities can be achieved, in particular a continuous and differentiable dependence between the input quantities and the output quantities due to the system behavior of the system components, so that the systematic dependence is ideally suited to any mathematical method for using the same.

[0722] Evaluating the coefficient of determination from the determined data and the curve determined by the regression model provides an indication of the accuracy of the systematic dependence, assuming a sufficient number of data sets are available. It can be advantageously used to evaluate how meaningful the correlation between input and output quantities is and how well it can reproduce existing or recorded data. Furthermore, if the coefficient of determination is large, the curve can also be used to make statements about the margins of existing data. For example, it is considered that the data can be numerically supplemented and / or estimated at the margins of existing data.

[0723] Advantageously, the systematic dependencies are determined by an optimization process.

[0724] It is suggested here that the parameters of the systematic dependence are determined by an optimization procedure, in particular by a minimization procedure, which minimizes the cumulative deviation of the empirical values ​​considered by the data set from the systematic dependence. In this way, it is advantageously possible to determine a systematic dependence that can be derived in an optimal way, in particular with a minimum cumulative deviation from the initial empirical values.

[0725] Preferably, the parameters of the systematic dependence are determined by maximizing the resulting coefficient of determination.

[0726] Preferably, the systematic dependencies are determined by a self-learning optimization method.

[0727] In particular, it is proposed to use algorithms that exhibit the characteristics of algorithms from the machine learning classification, so that the algorithm can derive a systematic dependency between the amount of input and the difference in availability due to contamination.

[0728] The advantage of this is that by using a self-learning optimization method, the complex task of indirectly deriving systematic dependencies does not require a human to painstakingly adapt to new conditions, thus saving time and money by indirectly deriving systematic dependencies.

[0729] Since the optimization procedure seeks to determine the optimal systematic dependence even in a multi-criteria environment and under various boundary conditions, the quality of the derived systematic dependence can be improved by the aspects proposed herein.

[0730] In this way, it is conceivable that optimization can be performed under multiple equal objectives and / or boundary conditions (multi-criteria optimization). In particular, classifications of algorithms that can determine Pareto optimality and / or the Pareto front are considered. In particular, classifications of algorithms in fields such as simplex methods and / or evolutionary strategies and / or evolutionary optimization algorithms are proposed here in order to derive systematic dependencies.

[0731] Optionally, the systematic dependencies are derived using a data set of dependency tables from an existing database, preferably a data set of an existing database that has been previously accessed.

[0732] The advantage of this is that data from an existing database can also be used to derive the systematic dependencies. Thus, it is possible to achieve that empirical values ​​do not first need to be collected for a particular vehicle, transferred to the data in the database, and then later transferred to the systematic dependencies. In this way, existing data and empirical values ​​can be used to derive the systematic dependencies on the fouling process without first needing to collect empirical values ​​that represent the systematic dependencies of the fouling process.

[0733] In an optional embodiment, the existing database is continually expanded.

[0734] Advantageously, an increase in the number of derivable systematic dependencies over time can be achieved.

[0735] Furthermore, due to the large number of empirical values ​​known from the data set, it can be advantageously achieved that the accuracy of the systematic dependence can be increased.

[0736] Advantageously, the new data set replaces the data set in the dependency table that deviates most from the derived systematic dependencies.

[0737] In particular, one must take into account the fact that empirical values ​​are traded off for the maximum Euclidean distance to systematic dependencies.

[0738] Advantageously, the systematic dependence becomes more and more precise over time, which can be expressed by an increase in the coefficient of determination.

[0739] Furthermore, this has the advantage that even weakly correlated systematic dependencies can be better identified over time.

[0740] It is also proposed that the output and / or input amounts refer to the frequency and / or speed of the irrigation pump.

[0741] This can advantageously improve dependency table and / or systematic dependency accuracy, as it has been found that the frequency and / or speed of the wash fluid pump can affect the system behavior of the system components.

[0742] It is further suggested that the output amount and / or input amount are indicative of the nozzle size and / or the type of cleaning fluid and / or the quality of the cleaning fluid.

[0743] This can advantageously improve the dependency table and / or systematic dependency accuracy, as it has been found that nozzle dimensions and / or cleaning fluid type and / or cleaning fluid quality can affect the system behavior of system components.

[0744] It is suggested that the output quantity and / or input quantity refer to the pump diaphragm material and / or the hose material.

[0745] This can advantageously improve dependency table and / or systematic dependency accuracy, as it has been found that pump diaphragm material and / or hose material can affect the system behavior of the system components.

[0746] 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 individually or cumulatively in any combination.

[0747] According to a first alternative of the sixth aspect of the present invention, the task is a method for diagnosing system behavior of a system component of a washing system of a motor vehicle, comprising: The output amount depends on the input amount due to the system behavior of the system components of the cleaning system, an actual output amount exceeding an upper threshold and / or an actual output amount falling below a lower threshold indicates that the actual system behavior deviates from the expected system behavior; Preferably, a step of determining an input amount; determining the actual output amount; - preferably searching for an upper threshold amount and / or a lower threshold amount depending on the input amount; - comparing the actual output amount with an upper threshold amount and / or a lower threshold amount; - preferably calculating the deviation between the actual output quantity and the upper threshold quantity if the actual output quantity is above the upper threshold quantity and / or calculating the deviation between the actual output quantity and the lower threshold quantity if the actual output quantity is below the lower threshold quantity; -preferably, storing a diagnostic signal when the actual output amount exceeds an upper threshold and / or when the actual output amount falls below a lower threshold.

[0748] A procedure for monitoring and diagnosing system components of an automotive washing system is proposed herein.

[0749] As the number of driver assistance systems in motor vehicles increases, the number of system components in washing systems and the number of functions in washing systems also increases.

[0750] At the same time, there is an increasing number of different combinations of different system components on the market to form cleaning systems, with the different system components typically being provided by different suppliers.

[0751] As a result, the complexity of cleaning systems has increased, as has the need for maintenance to maintain trouble-free system operation.

[0752] This has created an increasing need for a systematic, at least partially automated, or automatable, approach for the early detection of errors that may occur in system components of a cleaning system.

[0753] Unexpectedly, it was discovered that electrical and mechanical anomalies in the system behavior of system components in cleaning systems are often related. This finding can be used to evaluate system components based on mechatronic concepts.

[0754] If the assessment of cleaning systems currently relies mainly on visual observation, the assessment of system components based on mechatronic concepts can advantageously lead to the fact that the existing, or with little effort additional, electrical signals of the system components of a cleaning system can also be used to assess possible mechanical faults. Previously, this was only possible by visual inspection by trained personnel.

[0755] In particular, mechanical anomalies in the system behavior of system components can often be advantageously identified by at least partially automated observation of the electrical behavior of the system components. Thus, by monitoring electrical quantities, different possible problems associated with the cleaning system can be detected.

[0756] In particular, it has been unexpectedly determined that the time course of the inrush current of the cleaning liquid pump in the presence of a mechanical blockage of the flow channel of the cleaning liquid, in particular in the case of a mechanical blockage of the flow channel up to the designated outlet of the cleaning liquid at the nozzle, can show characteristic differences from the time course in the presence of an error-free normal switching on of the cleaning liquid pump. It can be particularly advantageous to distinguish between a partial blockage and a complete blockage of the flow channel of the cleaning liquid.

[0757] Normally, the time course of the inrush current when the cleaning solution pump is switched on results in only a short overshoot step response, but in the presence of a mechanical interlock the step response can show a more pronounced time course, in particular where the current reaches the expected value for continuous operation of the cleaning solution pump with only a measurable decay.

[0758] The procedure proposed here can preferably be executed autonomously and therefore preferably executes autonomously within the framework of self-diagnosis of the cleaning system and can report if abnormal system behavior of a system component of the cleaning system is diagnosed.

[0759] In particular, it should be considered that the diagnostic procedure proposed here can preferably be initiated by the electronic control unit and / or the washing system of the vehicle without the intervention of the driver of the vehicle. Furthermore, it should be considered that the diagnostic procedure proposed here can preferably be initiated manually by the driver of the vehicle.

[0760] The proposed diagnosis involves comparing the expected behavior of a system component of a cleaning system with the system behavior determined during monitoring of this system component by an actual output quantity, the comparison being performed using at least one value of the output quantity.

[0761] The expected system behavior is based on empirical values ​​of specifically evaluated system components. These empirical values ​​may be based on normal operation of the vehicle or laboratory observations, or may be the result of a numerical model.

[0762] If the comparison results in the monitored system behavior of the system component corresponding to the expected system behavior, it is concluded that the system component does not have defects and / or failures and / or that the system component is not impaired by external influences acting on the system component.

[0763] The expected system behavior is determined according to the method proposed herein based on the upper and / or lower threshold quantities. If the actual output quantity signal is within or performs within the range defined by the upper and lower threshold quantities, then the system behavior of the considered system component is not unexpected, and this range can also be opened if only the upper or lower threshold quantities are specified.

[0764] Therefore, the proposed method requires a list with at least one upper threshold or at least one lower threshold for the output quantity, each threshold being a separate value for each output quantity and preferably also depending on the input quantity and the system component under consideration.

[0765] Preferably, the upper and / or lower threshold amounts are dependent on the throughput.

[0766] If the monitored output quantity exceeds an individually associated upper threshold, or if the monitored output quantity falls below an individually associated lower threshold, then a deviation exists which may be characterized by another output quantity, if desired.

[0767] Furthermore, it is believed that solution strategies are known from experience that can correct certain deviations, especially following the seventh and / or eighth aspects of the invention.

[0768] If the deviation of monitored output quantities from expected output quantities and / or the characterization of deviating system behavior results in a known behavioral pattern, this can be associated with a recommendation for action. Such recommendation for action is also based on empirical values, which can also be largely systematized.

[0769] With respect to systematic empirical values, it is particularly important to consider that certain errors may be inferred depending on the type and severity of deviation of the monitored output from the expected output, and preferably, the conclusions are valid or at least transferable to a number of different system components and a number of different cleaning systems.

[0770] For example, it is necessary to consider here that an increased power consumption of the cleaning liquid pump and therefore a deviation in the system behavior leads to the conclusion that an error exists in the cleaning system, particularly in the case of an aging cleaning liquid pump, which in particular requires the use of higher energy requirements for the controlled pump pressure of the cleaning liquid pump.

[0771] Alternatively, in this case, there may be a blockage in the flow channel downstream of the wash pump, which may cause an increase in back pressure, which in turn may affect the system behavior of the wash pump. Depending on the situation, a distinction can be made to identify the cause of the diagnosed deviation by comparing different output quantities. For this, empirical values, which may be available in a list, are required.

[0772] This also indicates that deviations between expected and actual output quantities of the system behavior of a system component need not be caused by the monitored system component itself.

[0773] If there is a blockage before the pump, a possible solution strategy to correct the deviation with on-board means is to increase the pump pressure in a targeted manner, so that the blockage can be released and flushed out of the cleaning system. In particular, the choice of solution strategy described in the seventh aspect of the present invention can be considered.

[0774] When implementing a solution strategy, particular consideration should be given to implementing the solution strategy described in the eighth aspect of the present invention.

[0775] If the solution strategy selected and implemented is successful, the resulting system behavior of the system components corresponds to the expected system behavior.

[0776] It should be clearly pointed out that the diagnostic method described here can be applied to any system component. If a sufficient number of sensors or measurement devices, a sufficient number of empirical values ​​regarding the expected system behavior of one or more system components, and a list of potentially successful solution strategies are available, many deviations that occur can be corrected by on-board devices. Deviations in system behavior that cannot be repaired by on-board resources can also be detected early and repaired within the scope of normal or early maintenance, advantageously preventing the expansion of damage that might otherwise occur.

[0777] Of course, the input quantity, output quantity, lower and / or upper threshold quantity, and / or deviation can be scalar or vector quantities.

[0778] Furthermore, it is suggested that the diagnostic signal is optionally stored or passed to an electronic control unit of the motor vehicle.

[0779] Preferably, it is proposed to calculate the deviation between the actual output quantity and the upper threshold quantity if the actual output quantity exceeds the upper threshold quantity, and / or to calculate the deviation between the actual output quantity and the lower threshold quantity if the actual output quantity is below the lower threshold quantity.

[0780] The above quantities are scalars when only a single parameter is evaluated without the time course of this parameter. In all other cases, especially when considering several parameters of the cleaning system and / or when considering the time course of at least one of the parameters, the above quantities are understood as vector quantities.

[0781] Therefore, the preferably proposed calculation of the deviation between the actual output quantity and the upper and / or lower threshold quantity also depends on whether the output quantity is a scalar or a vector. Unless already the case, it is proposed to adjust the upper and / or lower threshold quantity to the dimensional characteristics of the actual output quantity, and it must be ensured that the upper and / or lower threshold quantity each have a corresponding value.

[0782] For vector actual output quantities, the calculation of the deviation is done component by component, i.e., dimension by dimension, separately.

[0783] Deviations may occur in some or all components of the actual output quantity, and at the same time, components are considered to be deviating because the corresponding components of the lower threshold quantity are undershooting, and components are considered to be deviating because the corresponding components of the upper threshold quantity are overshooting.

[0784] If a deviation is determined for at least one component between the upper and / or lower threshold amount and the actual output amount, further investigation of this deviation is suggested.

[0785] The diagnostic signal may include a failure to detect deviations in actual system behavior from expected system behavior.

[0786] Additionally, the diagnostic signal may include that a deviation of the actual system behavior from the expected system behavior has been detected, and the type and description of the deviation may also be stored in the diagnostic signal.

[0787] Preferably, the diagnostic signal is indicated to be indicative of a deviation.

[0788] Preferably, the diagnostic signal indicates the output quantity and / or the course of the output quantity over time, and the course of the output quantity over time indicates at least two time points, preferably at least 10 time points, particularly preferably at least 20 time points.

[0789] It should be pointed out that the above values ​​for the amount of value over time should not be understood as hard limits, but rather should be able to be exceeded or fallen below on an engineering scale without departing from the described aspects of the invention. Simply put, these values ​​are intended to indicate the size of the amount of value over the time ranges suggested herein.

[0790] It is also noted that the diagnostic signal may in particular show multiple time curves of output quantities over time, in particular input quantities and / or processing quantities.

[0791] This advantageously makes it possible to observe and evaluate changes in the system behavior of the system components, in particular with regard to possible aging and / or remaining life of the system components as a function of input and / or processing volume.

[0792] Thus, at least partially automated error detection regarding the system behavior of system components of a washing system for a motor vehicle can be made possible in an advantageous manner, and possible errors can be detected autonomously at an early stage.

[0793] This also allows early identification of possible causes of follow-up errors, advantageously limiting the propagation of errors.

[0794] In this way, the intervals at which trained professionals should perform optical inspections can also be advantageously extended, thus reducing the overall maintenance costs of the cleaning system and the expected availability of the cleaning system.

[0795] According to a second alternative of the sixth aspect of the present invention, the task is to provide a method for diagnosing deviations between actual and expected system behavior of system components of a washing system of a motor vehicle, comprising: The output amount depends on the input amount due to the system behavior of the system components of the cleaning system, Actual system behavior as a function of input quantities is represented by actual output quantities, and expected system behavior as a function of input quantities is represented by expected output quantities; the expected system behavior is represented by at least one data set of dependency tables or systematic dependencies, preferably systematic dependencies derived by the method according to the fifth aspect of the present invention, Preferably, a step of determining an input amount; determining the actual output amount; - determining an expected output amount, Selecting the dataset from the dependency table that best matches the input quantity, reading the output quantity stored in the selected dataset and taking it as the expected output quantity; Selecting two data sets from the dependency table that best match the input quantities, and determining the expected output quantities using linear interpolation based on the two selected data sets; or determining by calculating the expected output quantities by inserting the input quantities into the systematic dependencies; - calculating the deviation between the actual output amount and the expected output amount; - Preferably, the deviation is resolved by a method including a step of storing a diagnostic signal when the deviation is greater than 10% of the expected output amount, preferably greater than 5% of the expected output amount, and particularly preferably greater than 2% of the expected output amount.

[0796] In parallel with the first alternative of the sixth aspect of the invention, this second alternative of the sixth aspect of the invention also proposes a procedure for monitoring and diagnosing system components of a washing system of a motor vehicle.

[0797] It should be clearly pointed out that the open-ended description of the first alternative of the sixth aspect of the present invention above is also valid for the second alternative of the sixth aspect, and vice versa, where the actual output amount is differently compared to the expected output amount, rather than to a lower threshold amount and / or an upper threshold amount.

[0798] In contrast to the first alternative, according to a second alternative of the sixth aspect of the present invention, the actual output quantity is compared with the expected output quantity and a deviation between the actual output quantity and the expected output quantity is determined.

[0799] The proposed diagnosis compares the expected system behavior of the system components of the cleaning system with the expected system behavior, the comparison being performed based on at least one value of an actual output quantity compared to a corresponding value of the expected output quantity.

[0800] The expected system behavior is based in particular on empirical values ​​of the system components diagnosed with the proposed method, which may be based on normal operation of a vehicle or on laboratory observations, or may be the result of a numerical model suitable for mapping the normal system behavior of a washing system.

[0801] Preferably, the expected system behavior, and therefore the expected output amount, also depends on the input amount at which the washing system operates.

[0802] Preferably, the expected system behavior, and therefore the expected output volume, depends on the throughput.

[0803] According to this second alternative of the sixth aspect of the invention, three further variants are proposed in each case, by means of which the expected output quantity can be determined on the basis of empirical values.

[0804] According to the first and second variants, the expected system behavior of the system components is considered to be described by a dependency table, in particular a dependency table created according to the first step of the method according to the fifth aspect of the invention.

[0805] It should be explicitly mentioned that the dependency table may depend on the system components, input quantities and / or processing quantities being diagnosed.

[0806] Such dependency tables describe discrete empirical values ​​of expected system behavior, one system component at a time, and as a result, it is necessary to first select an empirical value from the dependency table before comparison with the actual output quantity.

[0807] With regard to the evaluation of the dependency table, the first and second variants for determining the expected output amount differ from each other.

[0808] According to a first variant for selecting the expected output quantities, it is proposed to select from the dependency table empirical values ​​in the form of the best suited dataset, in particular the best suited dataset defined by the shortest Euclidean distance in terms of input quantities and / or processing quantities between the dataset stored in the dependency table and the actual input quantities and / or actual processing quantities, by comparing the actual input quantities and / or actual processing quantities with the input quantities and / or processing quantities of the respective dataset.

[0809] According to a second variant for the selection of the expected output quantity, it is proposed to select two optimal adjacent empirical values ​​in accordance with the description of the first variant from the dependency table in the form of two data sets and to interpolate between these two empirical values ​​according to the actual input quantities and / or the actual processing quantities.

[0810] According to a third variant for selecting expected output quantities, the expected system behavior of the system components is mapped by systematic dependencies, in particular by systematic dependencies derived according to the fifth aspect of the invention.

[0811] The systematic dependence can continuously describe the expected system behavior as a function of actual input quantities and / or actual processing quantities, so that selection or interpolation between empirical values ​​is not necessary, as described above for the second variant.

[0812] Similar to the dependency tables according to variants 1 and 2, a systematic dependency is only valid for one system component, and as a result, a deviating systematic dependency or a deviating dependency table can or should be selected to consider a deviating system component.

[0813] It is understood that the input quantities, actual output quantities, expected output quantities and / or deviations can be scalar or vector quantities. The above quantities are scalar when only a single parameter describing the system behavior of the system components is evaluated without the time course of this parameter. In all other cases, especially when considering several parameters of the cleaning system and / or when considering the time course of at least one of the parameters, the above variables are understood as vector quantities.

[0814] 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 not already the case, it is preferably suggested to adjust the expected output quantity to the dimensional characteristics of the actual output quantity, and in any case, it must be ensured that the expected output quantity and the actual output quantity each have a corresponding quantity.

[0815] For vector actual output quantities, the calculation of the deviation is done component by component, i.e., dimension by dimension, separately.

[0816] If a deviation is determined for at least one component between the expected output amount and the actual output amount, further investigation of this deviation is suggested.

[0817] According to the discussion above, measurement errors and expected variations in the respective signals may occur during normal operation when determining the measurements.

[0818] Thus, not all nominal deviations between expected and actual output quantities will result in deviations of the actual system behavior of the system components from the expected system behavior.

[0819] To quantify the cases of deviation of the actual system behavior of the system components from the expected system behavior, it is suggested here to use the relative deviation between the actual output quantity and the expected output quantity.

[0820] This relative comparison is performed for each component. It should also be considered that limits beyond which the deviation between the actual and expected system behavior of a system component may be specified for components of different sizes, depending on available experience.

[0821] In particular, deviation limits of 10%, preferably 5%, and especially 2% are proposed.

[0822] It should be pointed out that the above values ​​for deviation limits should not be understood as hard limits, but rather should be able to be exceeded or fallen below on an engineering scale without departing from the described aspects of the invention. In simple terms, the values ​​are intended to indicate the size of the deviation limits proposed here.

[0823] Preferably, the deviation limit is 15%, more preferably, the deviation limit is 20%, more preferably, the deviation limit is 25%, and even more preferably, the deviation limit is 30%.

[0824] If the ratio of the actual output quantity to the expected output quantity exceeds a limit value for at least one component, the actual system behavior differs from the expected system behavior for the system component being considered.

[0825] Otherwise, it is concluded that the actual system behavior corresponds to the expected system behavior and that the considered system components of the cleaning system do not have defects and / or malfunctions and / or that the system components are not impaired by external influences acting on the system components.

[0826] In particular, deviations between expected and actual output quantities of the system behavior of a system component need not be caused by the monitored system component itself.

[0827] Rather, it may be part of further diagnostics that indicate which system components of the cleaning system are or may be indicative of possible errors that may occur depending on the determined deviation.

[0828] It should be noted that the diagnostic methods described herein can be used with any system component. Given the availability of a sufficient number of sensors or measurement 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, many deviations that occur can be corrected with on-board devices. Deviations in system behavior that cannot be repaired with on-board resources can also be detected early and repaired within the scope of normal or early maintenance, advantageously preventing further damage that might otherwise occur.

[0829] Furthermore, it is suggested that the diagnostic signal is optionally stored or passed to an electronic control unit of the motor vehicle.

[0830] The diagnostic signal may include a failure to detect deviations in actual system behavior from expected system behavior.

[0831] Additionally, the diagnostic signal may include that a deviation of the actual system behavior from the expected system behavior has been detected, and the type and description of the deviation may also be stored in the diagnostic signal.

[0832] Preferably, the diagnostic signal indicates the output quantity and / or the course of the output quantity over time, and the course of the output quantity over time indicates at least two time points, preferably at least 10 time points, particularly preferably at least 20 time points.

[0833] It should be pointed out that the above values ​​for the amount of value over time should not be understood as hard limits, but rather should be able to be exceeded or fallen below on an engineering scale without departing from the described aspects of the invention. Simply stated, the values ​​are intended to indicate the size of the amount of value over the time ranges proposed herein.

[0834] It is also noted that the diagnostic signal may in particular show multiple time curves of output quantities over time, in particular input quantities and / or processing quantities.

[0835] This advantageously makes it possible to observe and evaluate changes in the system behavior of the system components, in particular with regard to their possible ageing and / or remaining lifespan as a function of input and / or processing volumes.

[0836] Once the comparison of the actual output amount to the expected output amount is complete, the diagnostic method can be stopped or can be continued again with the same system component or with a different system component.

[0837] Thus, at least partially automated error detection regarding the system behavior of system components of a washing system for a motor vehicle can be made possible in an advantageous manner, and possible errors can be detected autonomously at an early stage.

[0838] This also allows for early detection of possible causes of follow-up errors, advantageously limiting the propagation of errors.

[0839] In this manner, the intervals at which optical inspections should be performed by trained professionals can also be advantageously extended, thus reducing the overall maintenance costs of the cleaning system.

[0840] In a preferred embodiment, the deviation represents a time course, preferably the time course represents at least two time points of the process, preferably at least 10 time points, particularly preferably at least 20 time points.

[0841] Here, it is specifically proposed to consider said deviations as deviations over time as well.

[0842] Preferably, the course of deviations over time can also be preferably stored in a database.

[0843] Preferably, the time course is stored with the diagnostic signal.

[0844] In particular, it is suggested that the deviation time course starts just before a scheduled change in the input quantity. Preferably, the deviation time course ends after the next scheduled time change.

[0845] In particular, it should be noted that the output quantity is diagnosed over a period that at least slightly exceeds the two planned changes in the input quantities on both sides. In particular, the time course diagnosis of the output quantity starts before switching on the cleaning fluid pump and ends after switching off the cleaning fluid pump.

[0846] Based on the time course of the output quantities, systematic errors of the system components can be evaluated, in particular systematic errors that indicate the dependence of the system components on the damping of the system behavior.

[0847] Furthermore, rather than running the time course continuously, it may be advantageous to consider recording certain output quantities after each activation of a system component.

[0848] In particular, it should be noted that the fluid pressure downstream of the cleaning fluid pump and / or the current and / or fluid velocity downstream of the cleaning fluid pump are recorded after each on-switching process at defined time units after the switch-on process, and the individual values ​​recorded in each case are recorded and diagnosed as a time series.

[0849] In this way, degradation of the wash pump's performance over its life can be advantageously assessed and a warning can be provided when the wash pump is expected to be replaced.

[0850] It should be pointed out that the above values ​​for the amount of data points in time should not be understood as hard limits, but rather should be able to be exceeded or fallen short on an engineering scale without departing from the described aspects of the invention. Simply put, the values ​​are intended to indicate the size of the amount of data points within the time ranges proposed herein.

[0851] The system behavior of the system components can be advantageously evaluated based on the time course of the output quantities, providing further analytical possibilities supporting the transmission behavior of the system components in relation to one another, and in particular a variety of such analytical possibilities.

[0852] In particular, the time course of deviations can be evaluated as a function of input and / or output quantities, and data having the same or very similar input and / or output quantities are compared with each other.

[0853] Preferably, the time course represents at least 30 time points. Preferably, the time course represents at least 40 time points. Preferably, the time course represents at least 50 time points.

[0854] Preferably, the results of the analysis of the time course of the deviation are stored together with and / or in the diagnostic signal.

[0855] Preferably, the time course of the deviation is examined for a step response.

[0856] Here, it is proposed to evaluate the time course of an output quantity in terms of a step response, in particular in terms of a step response as a reaction to a change in an input quantity.

[0857] In particular, it is possible to examine the value of an output quantity or the change in the output quantity for a change in an input quantity.

[0858] It is further proposed that the time course of the power quantity can be examined, preferably with respect to the transmission behavior as part of the system behavior of the system components, to determine the attenuation that affects the power quantity.

[0859] Preferably, it can be diagnosed whether a nozzle is "partially or completely clogged with cleaning fluid." For example, a spike in pressure behind the cleaning fluid pump indicates that the nozzle is blocked. The shape of the spike can advantageously indicate whether the flow channel behind the pump is completely or partially blocked.

[0860] Comparison of characteristic properties may involve comparing the spike process with one or more benchmark processes of pressure.

[0861] If a blocked nozzle is detected, a resolution strategy may be used in accordance with the seventh and / or eighth aspects of the invention.

[0862] Alternatively, a warning can be generated requesting manual cleaning of the nozzle.

[0863] Monitoring the inrush current of the solution pump over time can also be used to diagnose whether the solution pump is blocked, especially in icy conditions.

[0864] In particular, a blocked irrigation pump exhibits higher damping with respect to inrush current.

[0865] If a blocked 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.

[0866] The system behavior of the system components can be advantageously evaluated based on the time course of the output quantities, providing further analytical possibilities supporting the transmission behavior of the system components in relation to one another, and in particular a variety of such analytical possibilities.

[0867] In particular, the step response can be evaluated as a function of input and / or output quantities, and data having the same or very similar input and / or output quantities are compared with each other.

[0868] Preferably, the results of the analysis of the time course of the deviation are stored together with and / or in the diagnostic signal.

[0869] Advantageously, at least two time courses of deviation are examined for the presence of deviation drift over time, preferably at least five deviation courses, preferably at least ten deviation courses.

[0870] Here, it is suggested to evaluate the time course of the output quantity in terms of the drift of the output quantity over time.

[0871] Drift is the systematic change in an output quantity in response to an input quantity over the life of a system component.

[0872] The time course of the output magnitude can be compared to previously observed time courses of the output magnitude over time, particularly to multiple time courses of the output magnitude over time.

[0873] Drift exists when the deviation over time starts from the expected system behavior of the system components and moves continuously in one direction. The characteristics can advantageously determine how changes occur in the system behavior of the system components, particularly with respect to aging.

[0874] Furthermore, rather than running the time course continuously, it may be advantageous to consider recording certain output quantities after each activation of a system component.

[0875] In particular, it should be noted that the fluid pressure downstream of the cleaning fluid pump and / or the current and / or fluid velocity downstream of the cleaning fluid pump are recorded after each switch-on process at defined time intervals after the switch-on process, and the individual values ​​recorded in each case are recorded and diagnosed as a time series.

[0876] In this way, degradation of the wash pump's performance over its life can be advantageously assessed and a warning can be provided when the wash pump is expected to be replaced.

[0877] In particular, the time course of deviation can be assessed for the presence of drift as a function of input and / or output quantities, whereby data having the same or very similar input and / or output quantities are compared to each other.

[0878] Preferably, at least 20 time courses of the deviation are examined for the presence of drift in the deviation over time, preferably at least 30 time courses of the deviation are examined for the presence of drift in the deviation over time, preferably at least 40 time courses of the deviation are examined for the presence of drift in the deviation over time.

[0879] It should be pointed out that the above values ​​for the amount of deviation time course should not be understood as hard limits, but rather should be able to be exceeded or fallen below on an engineering scale without departing from the described aspects of the invention. In simple terms, the values ​​are intended to indicate the size of the amount of deviation time course within the proposed range.

[0880] Preferably, the results of the analysis of the time course of the deviation are stored together with and / or in the diagnostic signal.

[0881] The cause of actual system behavior deviating from expected system behavior may be based on the system component currently being diagnosed, or may be based on the deviating system component but have the cause transferred to the actual diagnosed system component according to a system-dependent transmission function between the components.

[0882] If the corresponding transfer function is unknown, diagnosing further system components is suggested to narrow down the cause.

[0883] The diagnostic signal preferentially indicates information about an input quantity that has an impact on the cleaning system and / or system components during diagnostics of the system components.

[0884] The diagnostic signal preferentially indicates information regarding throughput, which is affecting the cleaning system and / or system components during system component diagnostics.

[0885] Needless to say, the advantages of systematic dependence, in particular the systematic dependence described in the fifth aspect of the invention, also apply to the use of systematic dependence, in particular the use of systematic dependence proposed here according to the sixth aspect of the invention.

[0886] 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 individually or cumulatively in any combination.

[0887] According to a seventh aspect of the present invention, the task is solved by a method of selecting a solution strategy from a list of solution strategies contained in a database in response to a current diagnostic signal, preferably in response to a current diagnostic signal received in accordance with the sixth aspect of the present invention, wherein the list of solution strategies comprises at least one solution strategy associated with the diagnostic signal, and wherein the solution strategy is selected from the list of solution strategies whose associated diagnostic signal best matches the current diagnostic signal.

[0888] When the actual system behavior of the system components of a car wash system does not correspond to the expected system behavior, the deviation between the actual system behavior and the expected system behavior may have several causes.

[0889] In particular, the cause of actual system behavior that deviates from expected system behavior may be attributable to the system component currently being diagnosed, or may be attributable to the deviating system component but have a cause that is transferred to the actually diagnosed system component according to a system-dependent transmission function between the system components.

[0890] Preferably, the category of cause of the deviation between the actual system behavior and the expected system behavior can be determined by the diagnostic signal, in particular by the current diagnostic signal according to the sixth aspect of the present invention.

[0891] A current diagnostic signal refers to a diagnostic signal that is the subject of a solution strategy within the scope of this method. In particular, the current diagnostic signal may have been created using the method according to the sixth aspect of the present invention. In particular, the current diagnostic signal indicates that there is a deviation between the actual system behavior and the expected system behavior.

[0892] When determining the cause of deviation between actual and expected system behavior by means of a diagnostic signal, particular priority is given to input and / or process quantities that have an impact on the system components and / or the cleaning system when determining the diagnostic signal.

[0893] It is particularly important to consider that the current diagnostic signals can be correlated, preferably unambiguously, with the causes of deviations in the system behavior of the system components based on existing empirical values.

[0894] Furthermore, these empirical values ​​can be specifically considered to be organized to the extent that they are valid or at least transferable to multiple different system components and / or multiple different cleaning systems.

[0895] In this way, it can be advantageously achieved that, based on existing experience with different system components of different cleaning systems, in particular different cleaning systems from different manufacturers or suppliers, a clear assignment can be made between the current diagnostic signal and the cause of deviations in system behavior, in particular a clear manufacturer-independent and type-independent assignment for the cleaning system and / or specific system component.

[0896] In particular, four different categories of causes of deviations between actual and expected system behavior are proposed, which can preferably be distinguished by diagnostic signals, and in particular are given particular priority by the current diagnostic signal according to the sixth aspect of the invention.

[0897] Specifically, it is proposed here to determine the category of cause in the presence of the current diagnostic signal.

[0898] According to the first category of causes of deviations between actual and expected system behavior, there are defects in the system components. In this regard, a number of different defects are possible:

[0899] In particular, if a defect exists, it is believed that the cleaning solution line has isolated itself from the system components of the cleaning system, and such a defect can be repaired even by untrained personnel.

[0900] In addition, there is likely to be a leak in the cleaning fluid line, which will require spare parts, at least in the medium term, and the defect cannot be repaired by untrained personnel alone, at least in the medium term.

[0901] According to a second category of causes of deviations between actual and expected system behavior, there exists the phenomenon of aging of system components.

[0902] Even if most of the system components of a car's washing system are designed to last the expected life of the car, the system components still deteriorate over time. Specifically, it is possible that a system component may age faster than intended, resulting in the expected life of the system component being shorter than the planned life of the car. In this case, replacement of such components is unavoidable for further normal operation of the washing system.

[0903] Preferably, ageing phenomena can be detected and / or assessed based on the drift of deviations over time, in particular based on the drift of deviations according to the sixth aspect of the invention.

[0904] The course of deviation drift over time is a particularly preferred method for determining how large the remaining expected value is for the usability of a system component.

[0905] According to a third category of causes of deviations between actual and expected system behavior, there are disturbances of system components.

[0906] It should be explicitly mentioned that there may be a fault in the system component undergoing the diagnostic procedure, in particular the diagnostic procedure according to the sixth aspect of the invention. Alternatively, the fault may also be caused by a deviation in the system component, in particular the fault being transferred by the transfer function to a system behavior of the system component that is worse than the diagnostic procedure.

[0907] According to the fourth category of causes of deviations between actual and expected system behavior, there are unknown causes of deviations in the system behavior of system components.

[0908] An unknown cause exists when 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 signals.

[0909] In particular, it should be noted that so far there is not enough empirical evidence for the possible causes of deviations, or that the assignment of causes leads to ambiguous results.

[0910] The resolution strategy is a method that, when applied to an automobile wash system, is designed to track deviations between actual system behavior and expected system behavior observed in the system components of the automobile wash system.

[0911] In other words, the solution strategy may advantageously result in smaller deviations for the system components, or in the actual system behavior once again corresponding to the expected system behavior.

[0912] Of particular priority, the solution strategy indicates input quantities that affect the cleaning system and / or system components and / or system components on the cleaning system when the solution strategy is applied.

[0913] Preferably, the resolution strategy involves notifying the vehicle operator and / or the vehicle manufacturer.

[0914] Preferably, the solution strategy indicates measures for planning maintenance and / or repair of the vehicle.

[0915] The solution strategy is preferably based on experience of the operation of the washing system, which may have been obtained during vehicle operation and / or in the laboratory and / or based on numerical models and / or may be the result of existing maintenance recommendations and / or may be based on heuristic findings.

[0916] The preferred solution strategy depends on the deviation of the system behavior and / or the current diagnostic signal, in particular the current diagnostic signal determined according to the sixth aspect of the present invention.

[0917] Preferably, the preferred resolution strategy is throughput dependent.

[0918] Preferably, the resolution strategy depends on the amount of input that affected the cleaning system and / or system components when a deviation in system behavior and / or diagnostic signal was determined.

[0919] Advantageously, the system components of the cleaning system can be made to operate as expected again through a resolution strategy, thereby restoring the functionality of the cleaning system to normal operation despite pre-existing deviations in system behavior.

[0920] Overall, the solution strategy is highly advantageous, allowing the functionality of the driver assistance system to be maintained for a longer period of time despite diagnosed deviations in the system behavior of the system components of the washing system.

[0921] It is here particularly proposed to select a solution strategy suitable for the current diagnostic signal from a list of known solution strategies.

[0922] In particular, it is proposed that the list of known solution strategies be obtained from a database accessible to the vehicle, which may also be wirelessly connected to a suitable database indicating the solution strategies.

[0923] In addition to the resolution strategies, the database also indicates the associated diagnostic signals that the resolution strategies are configured to remedy.

[0924] In addition to the solution strategies, the database preferably indicates input quantities that have an effect on the system components and / or cleaning system when determining the current diagnostic signal.

[0925] In addition to the solution strategy, the database may preferably indicate the amount of processing that affected the system components and / or the cleaning system in determining the current diagnostic signal.

[0926] Preferably, the solution strategy can be determined by a current diagnostic signal, in particular by a current diagnostic signal obtained according to the sixth aspect of the present invention.

[0927] A solution strategy is selected from the database whose assigned diagnostic signal in the database best matches the current diagnostic signal.

[0928] Preferably, the most suitable solution strategy is selected from the database using the smallest Euclidean distance between the diagnostic signal assigned to it in the database and the current diagnostic signal.

[0929] When determining a solution strategy according to the current diagnostic signal, input quantities and / or process quantities that have an impact on the system components and / or the cleaning system are given particular priority when determining the current diagnostic signal.

[0930] It is furthermore suggested that the database with the solution strategies is first pre-filtered with respect to optimal input quantities and / or optimal processing quantities, in particular based on the corresponding Euclidean distances between the input quantities and / or processing quantities stored in the diagnostic signal and the input quantities and / or processing quantities in the database.

[0931] Subsequently, following the procedure above, a solution strategy is proposed to be selected based on the current diagnostic signal according to the smallest possible Euclidean distance to the remaining solution strategies.

[0932] Thus, a resolution strategy can be advantageously selected that is advantageously configured to reduce deviations in system behavior of system components of the washing system, and / or to notify the operator and / or manufacturer of the fault, and / or to provide for future maintenance and / or repair measures.

[0933] Furthermore, the empirical data underlying each solution strategy should be specifically considered to be systematic to the extent that they are valid or at least transferable to multiple different system components and / or multiple different cleaning systems.

[0934] In this way, it can be advantageously achieved that a clear allocation can be made between current diagnostic signals and solution strategies, in particular a clear allocation across manufacturers and across types of cleaning systems and / or specific system components, based on existing experience with different system components of different cleaning systems, in particular different cleaning systems from different manufacturers or suppliers.

[0935] A possible solution strategy is that if the actual system behavior deviates from the expected system behavior at the cleaning liquid pump, which indicates in particular a blockage of the flow channel between the cleaning liquid reservoir and the outlet opening of the nozzle, in particular due to an increased energy requirement of the cleaning liquid pump, and / or due to a relatively low outlet volume of cleaning liquid at the outlet opening of the nozzle, and / or due to an increased static pressure of the cleaning liquid downstream of the cleaning liquid pump, and / or due to a lower flow rate of the cleaning liquid downstream of the cleaning liquid pump, an increase in the supply voltage and / or the target speed of the cleaning liquid pump is suggested as a solution strategy, which may be advantageous to remove the blockage and flush it out of the cleaning system.

[0936] If the solution pump shows high current but no impulses from the current hall sensor, this indicates a stalled solution pump motor.

[0937] If no cleaning results are obtained, especially in the case of increased availability and / or if the start-up of the cleaning fluid pump cannot be observed, it is suggested to check the controller of the cleaning system, especially the electronic control unit of the cleaning system, for phase open circuit faults and / or phase to earth faults and / or short circuit faults. If faults are detected, a plan for service and maintenance measures is proposed.

[0938] If there is a deviation between the actual system behavior and the expected system behavior at different pressures and / or engine speeds, it is proposed to operate the washing fluid pump. Since cycling through different pressures and / or engine speeds does not again result in the actual system behavior corresponding to the expected system behavior, it is proposed to send a corresponding warning to the driver and / or the manufacturer of the vehicle, signaling that the washing fluid pump needs to be replaced and / or to stop the washing system from using the washing fluid pump and / or the entire washing system until the washing fluid pump is replaced.

[0939] If the outside temperature is above a defined temperature, in particular above 45°C, with particular preference being given to above 55°C, and / or if the outside temperature is below a defined temperature, in particular below 0°C, with particular preference being given to below minus 15°C, it is proposed that the cleaning fluid pump not be operated any further, which can advantageously increase the remaining service life of the cleaning fluid pump.

[0940] With regard to the cleaning fluid pump, it is proposed to monitor the service life of the cleaning fluid pump, in particular by monitoring the flow rate associated with the cleaning fluid pump and / or the static pressure associated with the cleaning fluid pump and / or the flow rate through the cleaning fluid pump, and / or by monitoring the number of existing operating cycles of the cleaning fluid pump, and / or by monitoring the time of use of the cleaning fluid pump to date, and if it is foreseeable that the service life of the cleaning fluid pump is approaching the end, it is proposed to send a corresponding warning to the driver and / or the manufacturer of the vehicle, signaling that the cleaning fluid pump needs to be replaced within the expected remaining service life, 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 is replaced.

[0941] If the washing solution pump has excessive energy requirements, which can be detected in particular by a current sensor, it is suggested that the driver and / or the vehicle manufacturer be warned accordingly, a signal be sent that the washing solution pump needs to be replaced, and / or the washing system be forced to stop using the washing solution pump and / or the entire washing system until the washing solution pump is replaced.

[0942] If the washing fluid pump has an excessive temperature, particularly as can be detected by a temperature sensor, it is suggested that the driver and / or the vehicle manufacturer be alerted accordingly, a signal be sent that the washing fluid pump needs to be replaced, and / or the washing system be stopped from using the washing fluid pump and / or the entire washing system until the washing fluid pump is replaced.

[0943] With regard to the washing liquid pump, it is proposed to monitor the pump's performance, particularly by detecting deviations of the actual system behavior from the expected system behavior, particularly preferably by a flow sensor operably connected to the washing liquid pump and / or by a pressure sensor flow sensor operably connected to the washing liquid pump and / or by a current meter flow sensor operably connected to the washing liquid pump. In case of deviations, it is proposed to accordingly warn the driver and / or the vehicle manufacturer, to send a signal that the washing liquid pump needs to be replaced, and / or to cause the washing system to stop using the washing liquid pump and / or the entire washing system until the washing liquid pump is replaced.

[0944] In particular, it is proposed to monitor the system behavior of the washing solution pump by a flow sensor operatively connected to the washing solution pump and / or by a flow sensor actively connected to the washing solution pump and / or by a pressure sensor flow sensor actively connected to the washing solution pump and / or by a flow meter flow sensor actively connected to the washing solution pump. If deviations indicate that the washing solution pump has stopped and / or is blocked by debris, especially in icy conditions, it is suggested to switch off the washing solution pump and to warn the vehicle driver and / or the manufacturer and send a signal that the washing solution pump needs to be replaced.

[0945] A possible solution strategy consists in the fact that in the presence of deviations of the actual system behavior from the expected system behavior at the cleaning fluid reservoir, in particular due to frost and / or a splitting of the cleaning fluid reservoir as a result of a leak in the cleaning fluid reservoir, in particular due to an irregularly decreasing static pressure operatively connected to the bottom of the cleaning fluid reservoir and / or due to an irregularly decreasing fill level of the cleaning fluid reservoir as determined by a level sensor, a maintenance and / or repair action plan is proposed as a solution strategy. In this way, the cleaning system can be made operational again in an advantageous manner.

[0946] With respect to level sensors, particularly those operatively connected to the cleaning fluid reservoir, it is proposed to monitor their functionality and, if this indicates that functionality is no longer present, particularly by ceasing to emit a signal and / or if the emitted signal does not correspond to the expected system behavior, it is proposed to subject the level sensor to maintenance measures and, if necessary, to replacement.

[0947] If the level sensor has an excessive energy demand, which can be detected in particular by a current sensor, it is proposed to accordingly warn the driver and / or the vehicle manufacturer, signal that the level sensor needs to be replaced, and / or to have the washing system stop using the washing liquid pump and / or the entire washing system until the level sensor is replaced.

[0948] If the level sensor has an excessive temperature, which can be detected in particular by the temperature sensor, it is proposed to accordingly warn the driver and / or the vehicle manufacturer, signal that the level sensor needs to be replaced, and / or to have the washing system stop using the washing fluid pump and / or the entire washing system until the level sensor is replaced.

[0949] A possible solution strategy for the level sensor is to suggest replacing the level sensor if the response time or detection time increases.

[0950] A possible solution strategy for the level sensor is to use a leak sensor, particularly at the interface to the cleaning fluid reservoir, and particularly preferably at the interface between the cleaning fluid rese...

Claims

1. A method (MDSD3) for deriving dependencies (124) between system input quantities and system output quantities of system components of a washing system (16, 200) of a motor vehicle (14), comprising: the washing system (16, 200) is adapted for resource-saving washing of at least one surface (20, 22, 24, 26, 28) of the motor vehicle (14) by a washing process (30, 32, 34, 36, 38, 40); a step (BDTS1) of taking data values ​​measured by at least one sensor (50, 52, 54, 56, 56a, 56b, 58) as first parameters of the method (MDSD3) and input quantities (202), the input quantities (202) including the availability of the sensor, a parameter indicating the degree of contamination of the at least one sensor, and humidity, temperature, rainfall, snowfall, or any combination thereof, in the vicinity of the vehicle (14), or the current coordinates of the vehicle (14); a step (BDTS2) in which the output quantity (204) is determined as a second parameter of the method (MDSD3) depending on the input quantity (202) according to the system behavior of the system (16, 200), the output quantity (204) comprising a flow rate through a washing fluid pump, a current of the washing fluid pump, an operating time of the vehicle, a temperature of the surface of the vehicle to be washed, a filling level signal of a washing fluid reservoir, a time between the start and end of a level change in a washing fluid storage tank, a spray pattern of washing fluid, or any combination thereof; - digitizing (BDTS3) and recording, if necessary, said determined first and second parameters by a data processing system (150), said data processing system (150) representing an electronic data processing and evaluation system (152) and a database (154); - storing (BDTS4) said determined first and second parameters in chronological order in said database (154) as data sets (DP1, DP2, DP3, DP4) of a dependency table (DT); a step (DSDS2) of deriving the dependency (124) between the first parameter and the second parameter by 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), in which the electronic data processing and evaluation unit (152) accesses the data sets (DP1, DP2, DP3, DP4) of the dependency table (DT) and determines, by means of a regression algorithm, the dependency (124) in the form of a curve and a coefficient of determination of the curve from the data sets (DP1, DP2, DP3, DP4) of the dependency table (DT); - storing (DSDS3) said derived dependencies (124) in said database (154), in said electronic data processing and evaluation unit (152) or in an electronic control unit (18).

2. 2. The method (MDSD3) of claim 1, characterized in that the input quantities (202) comprise at least one measured quantity (100, 102, 104, 106, 107, 108), processed quantity (140, 141, 142, 143, 144, 145, 146, 147) and / or controlled quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119).

3. 3. The method (MDSD3) according to claim 1 or 2, characterized in that the output quantity (204) further indicates 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), and the power consumption, in particular the resource requirements (30d, 32d, 34d, 36d, 38d, 40d), is determined depending on set values ​​of control quantities (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) of the cleaning process (30, 32, 34, 36, 38, 40) of the surface (20, 22, 24, 26, 28).

4. Method (MDSD3) according to any one of claims 1 to 3, characterized in that said input quantity (204) further indicates the availability (220, 222, 224) of said sensors (50, 52, 54, 56, 56a, 56b, 58).

5. The method (MDSD3) according to any one of claims 1 to 4, characterized in that the output quantity (204) further indicates an increase in availability (220, 222, 224) of the sensor (50, 52, 54, 56, 56a, 56b, 58) and / or availability (229) due to the cleaning process (30, 32, 34, 36, 38, 40).

6. Method (MDSD3) according to any one of claims 1 to 5, characterized in that said dependencies (124) are determined by an optimization process.

7. 7. The method (MDSD3) according to any one of claims 1 to 6, characterized in that the dependencies (124) are derived using datasets (DP1, DP2, DP3, DP4) of the dependency table (DT) from an existing database (154), the datasets (DP1, DP2, DP3, DP4) of the existing database (154) having been previously accessed (DSDS1).

8. 8. The method (MDSD3) of claim 7, characterized in that the existing database (154) is continuously expanded.

9. 9. The method (MDSD3) according to any one of claims 1 to 8, characterized in that new data sets (DP1, DP2, DP3, DP4) replace in the dependency table (DT) the data sets (DP1, DP2, DP3, DP4) that deviate most from the derived dependencies (124).

10. 1. A method for diagnosing system behavior of a system component of a washing system (16, 200) of a motor vehicle (14), comprising: an output quantity (204) is determined by the system behavior of the system components of the cleaning system (16, 200) in dependence on the input quantity (202); an actual output quantity (204) exceeding an upper threshold quantity or said actual output quantity (204) falling below a lower threshold quantity indicates that the actual system behavior deviates from the expected system behavior; - determining said input quantities (202), said input quantities (202) comprising the availability of sensors, parameters indicative of information on the degree of contamination of said at least one sensor, and humidity, temperature, rainfall, snowfall or any combination thereof in the vicinity of said vehicle (14), or the current coordinates of said vehicle (14); - determining the actual output quantity (204), wherein the output quantity (204) comprises the flow rate through a washing fluid pump, the current of the washing fluid pump, the operating time of the vehicle, the temperature of the surface of the vehicle to be washed, the filling level signal of a washing fluid reservoir, the time between the start and end of a level change in a washing fluid storage tank, the spray pattern of the washing fluid, or any combination thereof; - deriving said upper threshold amount and / or said lower threshold amount depending on said input amount (202); - comparing said actual output amount (204) with said upper threshold amount or said lower threshold amount; A method comprising:

11. calculating a deviation between the actual output quantity and the upper threshold quantity if the actual output quantity exceeds the upper threshold quantity, or calculating the deviation between the actual output quantity and the lower threshold quantity if the actual output quantity is below the lower threshold quantity; storing a diagnostic signal if the actual output quantity (204) exceeds the upper threshold quantity or if the actual output quantity (204) falls below the lower threshold quantity; The method of claim 10 further comprising:

12. 1. A method for diagnosing deviations between actual and expected system behavior of system components of a washing system (16, 200) of a motor vehicle (14), comprising: an output quantity (204) is determined by a system behavior of the system components of the cleaning system (16, 200) depending on the input quantity (202); The actual system behavior as a function of input quantities (202) is represented by actual output quantities (204), and the predicted system behavior as a function of input quantities (202) is represented by predicted output quantities (204), the expected system behavior is represented by at least one data set (DP1, DP2, DP3, DP4) of a dependency table (DT); - determining said input quantities (202), said input quantities (202) comprising the availability of sensors, parameters indicative of information on the degree of contamination of at least one sensor, and humidity, temperature, rainfall, snowfall or any combination thereof in the vicinity of said vehicle (14), or the current coordinates of said vehicle (14); - determining the actual output quantity (204), wherein the output quantity (204) comprises the flow rate through a washing fluid pump, the current of the washing fluid pump, the operating time of the vehicle, the temperature of the surface of the vehicle to be washed, the filling level signal of a washing fluid reservoir, the time between the start and end of a level change in a washing fluid storage tank, the spray pattern of the washing fluid, or any combination thereof; said expected output (204), selecting the data set (DP1, DP2, DP3, DP4) from the dependency table (DT) that best matches the input quantity (202), reading the output quantity (204) stored in the selected data set (DP1, DP2, DP3, DP4) and considering it as the expected output quantity (204); selecting two data sets (DP1, DP2, DP3, DP4) from the dependency table (DT) that best match the input quantity (202) 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 quantities (204) by inserting the input quantities (202) into dependencies (124); - calculating the deviation between said actual output quantity (204) and said expected output quantity (204); - storing the diagnostic signal.

13. 13. The method of claim 10 or 12, wherein the deviation is indicative of a time course, the time course being indicative of at least two points in a cleaning process.

14. 14. The method of claim 13, wherein the time course of the deviation is examined for a step response.

15. 15. A method according to claim 13 or 14, characterized in that at least two time courses of the deviation are examined for the presence of a drift of the deviation over time.

16. 16. A method for selecting a solution strategy from a list of solution strategies contained in a database (154) in response to a current diagnostic signal received according to any one of claims 10 to 15, wherein the list of solution strategies comprises at least one solution strategy associated with the diagnostic signal, and wherein the solution strategy is selected from the list of solution strategies whose associated diagnostic signal best matches the current diagnostic signal.

17. Use of a solution strategy selected according to claim 16, comprising: - sending a signal to the driver and manufacturer of said vehicle (14); - Improving the system behavior by applying the selected solution strategy in the cleaning system (16, 200); - Use by planning maintenance or repair of said cleaning system (16, 200).

18. A cleaning method (10) for resource-saving cleaning of at least one surface (20, 22, 24, 26, 28) of a motor vehicle (14), comprising: the vehicle (14) exhibits a washing system (16) and at least one sensor (50, 52, 54, 56, 56a, 56b, 58); the sensor (50, 52, 54, 56, 56a, 56b, 58) is connected to one surface (20, 22, 24, 26, 28); the cleaning method exhibits at least one cleaning process (30, 32, 34, 36, 38, 40); said cleaning process (30, 32, 34, 36, 38, 40) being adapted to clean one surface (20, 22, 24, 26, 28) and exhibiting a cleaning period (38a, 40a) comprising a start time (38b, 40b) and an end time (38c, 40c); The cleaning system (16) exhibits an electronic control unit (18), a cleaning fluid distribution system (60) including at least one fluid reservoir (62), 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); The sensors (50, 52, 54, 56, 56a, 56b, 58) are configured to measure at least one of the following: availability (220, 222, 224) of the sensors (50, 52, 54, 56, 56a, 56b, 58); throughput (140, 141, 142, 143, 144, 145, 146, 147); adapted to detect humidity, temperature, rainfall, snowfall, coordinates of the vehicle, control variables, or any combination thereof, in the vicinity of the vehicle, and to transmit the measured variables to the electronic control unit; the nozzles (70, 72, 74, 76, 76a, 76b, 78, 78a, 78b) are adapted to operatively connect a cleaning fluid (64) to the surfaces (20, 22, 24, 26, 28); the electronic control unit (18) is adapted to control and regulate the cleaning process (30, 32, 34, 36, 38, 40) by means of at least one controlled variable (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) of the cleaning process (30, 32, 34, 36, 38, 40), the resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of said cleaning processes (30, 32, 34, 36, 38, 40) are dependent on the set values ​​of the controlled variables (110, 111, 112, 113, 114, 115, 116, 117, 118, 119); The cleaning method comprises the process steps for deriving a dependency (124) according to any one of claims 1 to 9, or Process steps for diagnosing the system behavior of system components of a washing system (16, 200) of a motor vehicle (14) according to any one of claims 10 to 11, or - process steps for diagnosing deviations between actual and expected system behavior of system components of a washing system (16, 200) for a motor vehicle (14) according to any one of claims 12 to 15, or Process steps for selecting a solution strategy according to claim 16, or A cleaning method (10), characterized in that it comprises process steps for using a selected solution strategy according to claim 17.

19. 1. A cleaning system (16) showing an electronic control unit (18) and a cleaning fluid distribution system (60), said cleaning fluid distribution system (60) including at least one fluid reservoir (62), 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); or The washing system (16) is adapted to carry out the method (MDSD3) according to any one of claims 1 to 9, or 12. A method for diagnosing the system behavior of a system component of a washing system (16, 200) of a motor vehicle (14) according to claim 10 or 11, or A method for diagnosing deviations between actual and expected system behavior of system components of a washing system (16, 200) of a motor vehicle (14) according to any one of claims 12 to 15, or The method is adapted to perform a method for selecting a solution strategy from a list of solution strategies contained in a database (154) in response to a current diagnostic signal according to claim 16, or adapted to use a selected solution strategy according to claim 17, or 19. A washing system (16), wherein the washing system (16) is adapted to perform a washing method (10) for resource-saving washing of at least one surface (20, 22, 24, 26, 28) of a motor vehicle (14) as set forth in claim 18.

20. A motor vehicle (14), The vehicle (14) exhibits a washing system (16) according to claim 19, or The motor vehicle (14) is adapted to carry out a cleaning method (10) for resource-saving cleaning of at least one surface (20, 22, 24, 26, 28) of the motor vehicle (14) according to claim 18, or The motor vehicle (14) is adapted to carry out a method (MDSD3) according to any one of claims 1 to 9, or 12. A method for diagnosing the system behavior of a system component of a washing system (16, 200) of a motor vehicle (14) according to claim 10 or 11, or A method for diagnosing deviations between actual and expected system behavior of system components of a washing system (16, 200) of a motor vehicle (14) according to any one of claims 12 to 15, or The method is adapted to perform a method for selecting a solution strategy from a list of solution strategies contained in a database (154) in response to a current diagnostic signal according to claim 16, Or a motor vehicle (14) adapted to use the selected solution strategy according to claim 17.

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