A method for indirectly deriving the systematic dependence of the system behavior of a cleaning system, a cleaning method, the use of systematic dependence, a cleaning system, and an automobile.

Abstract

The present invention relates to a method for indirectly deriving systematic dependencies of the system behavior of a washing system of a vehicle, particularly preferably of the system behavior of a washing process of a surface of a vehicle, for at least one washing of a vehicle, preferably a resource-efficient washing, particularly preferably a resource-saving washing. Furthermore, the present invention relates to a washing method, a use of the systematic dependencies, a washing system and a vehicle.

Description

[Technical Field]

[0001] This invention relates to a method for indirectly deriving the systematic dependence of the system behavior of a cleaning system, a cleaning method, the utilization of systematic dependence, a cleaning system, and an automobile.

[0002] Specifically, the present invention relates to a method for indirectly deriving the systematic dependence of the system behavior of a cleaning method, a vehicle cleaning system, particularly preferably the system behavior of a cleaning process for 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 the systematic dependence of the system behavior of a system component of a vehicle cleaning system, a method for diagnosing a deviation between an actual system behavior and an expected system behavior of a system component of a vehicle cleaning system, a method for selecting a solution strategy, the use of a selected solution strategy, a method for indirectly deriving the systematic dependence of the system behavior of a soiling process of a vehicle surface, the use of a dependency table and / or a systematic dependency to determine an expected availability at a distance or operating time of the vehicle that has not been covered yet, when an availability threshold is reached, the use of a dependency table and / or a systematic dependency to determine an expected distance or operating time of the vehicle that has not been covered yet, the use of a dependency table and / or a systematic dependency to optimize resource requirements of a cleaning process of a vehicle surface, the use of a dependency table and / or a systematic dependency to determine a cleaning strategy for cleaning a surface to be cleaned of a vehicle, the use of a dependency table and / or a systematic dependency to determine a required expected increase in availability, the use of a systematic dependency derived by a method for indirectly deriving the systematic dependency for resource-efficient cleaning of at least one surface of a vehicle, the use of a control amount setpoint derived by a method for optimizing resource requirements for a cleaning process of a vehicle surface for resource-efficient cleaning of at least one surface of a vehicle, the 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] With the steady expansion of recent driver assistance systems, the number of sensors installed in vehicles has also increased.

[0004] In many modern vehicles, sensors support the driver within the framework of safety features, for example, in obstacle recognition, preferably in pedestrian recognition, and / or within the framework of semi-autonomous or autonomous vehicles.

[0005] For functional sensor operation, and therefore the continuous operation of these safety features, and / or the operation of (partially) autonomous vehicles, these sensors rely on surfaces that are not excessively dirty; therefore, an increase in the number of sensors also led to an increased need for cleaning.

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

[0007] Furthermore, as the number of sensors installed in automobiles increases, while the failure of a single sensor would typically lead to a failure in the driver assistance system, it has become possible to acquire some data redundantly through multiple sensors.

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

[0009] Therefore, the decision-making process for properly cleaning the appropriate sensors is more complex. Many factors influence the determination of proper cleaning and how this is achieved.

[0010] The most advanced cleaning of automobile front and / or rear windows is known in particular for use with windshield wipers, which allow the cleaning solution to be applied to the front and / or rear windows as well.

[0011] A device for controlling a windshield wiping and / or rinsing system is already known from document EP 0 932 533 A1. The 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 the reverse gear is engaged, the wiping and / or rinsing system is switched on. This ensures clear visibility from the vehicle's windows as a precaution when the vehicle is started and the reverse gear is engaged. Depending on the degree of wetness and / or contamination, it is also possible to specify the duration for which the wiping and / or rinsing system is switched on.

[0012] DE 103 07 216 A1 discloses a process for operating a washer / wiper system for the windshield of an automobile, using at least one windshield wiper, a washer unit for spraying cleaning fluid onto the windshield, an electronic control unit, at least one windshield wiper motor, and a transport pump for windshield cleaning fluid. The wiper speed during the cleaning process is adaptively controlled by the electronic control unit in accordance with driving conditions and / or environmental input parameters.

[0013] DE 10 2009 040 993 A1 reveals a device for operating a wipe and / or rinse system for a vehicle's windshield, having a control device for controlling the cleaning process of the wipe and / or rinse system, the device being able to expose the vehicle's windshield to the cleaning fluid of the rinse system and / or move the wipers of a wiper system in relation thereto in contact with the windshield, the control means being adapted to determine the degree of contamination and / or wetness of a disc in accordance with at least one detected piece of information, and to set at least one specific parameter of the cleaning process in accordance with the determined degree of contamination and / or wetness, the control means being adapted to determine the degree of contamination and / or wetness of a disc during the cleaning process, and to adjust at least one specific parameter in accordance with the degree of contamination and / or wetness during the cleaning process, a predetermined set of multiple value combinations for at least two specific parameters of the cleaning process being stored in the control means, the control means being adapted to select a combination of values ​​from the set of multiple value combinations in accordance with the degree of contamination and / or wetness, and to adjust at least two specific parameters in accordance with the selected value combination.

[0014] This invention is based on the task of providing improvements or alternatives to state-of-the-art technologies.

[0015] According to a first aspect of the present invention, the task is a cleaning method for resource-efficient cleaning, preferably resource-saving cleaning, of at least one surface of an automobile, wherein the automobile comprises a cleaning system and at least one sensor, the sensor being operably connected to one surface, the cleaning method comprising at least one cleaning process, the cleaning process being adapted to clean one surface, and the cleaning period comprising a start time and an end time, and the cleaning system comprising an electronic control unit, preferably a cleaning fluid distribution system comprising at least one fluid reservoir, at least one nozzle, and at least one cleaning fluid line. A cleaning method comprising a stem, wherein the sensor is adapted to detect at least one quantifiable quantity, preferably sensor availability, processing capacity, preferably humidity and / or temperature near the vehicle, and / or rainfall and / or snowfall, and / or coordinates of the vehicle, and / or a control quantity, and transmits the quantifiable quantity to an electronic control unit, the nozzle is adapted to operably connect the cleaning fluid to the surface, and the electronic control unit is adapted to control and / or adjust the cleaning process by at least one control quantity of the cleaning process, wherein the resource requirements of the cleaning process depend on the control quantity setpoint, The electronic control unit controls resource-efficient cleaning, preferably resource-saving cleaning, according to a dependency table showing at least two datasets, preferably at least 50 datasets, and particularly preferably at least 200 datasets, wherein each dataset is stored in an interrelated and ordered manner, indicating at least one input quantity of the cleaning system, preferably processing quantity, preferably humidity and / or temperature near the vehicle, and / or rainfall and / or snowfall, and / or vehicle coordinates, and / or control quantity, and / or vehicle type, and / or sensor availability, and at least one output quantity of the cleaning system, preferably resource requirements and / or sensor availability for the cleaning process. and / or The electronic control unit controls resource-efficient cleaning, preferably resource-saving cleaning, in accordance with the system behavior of the cleaning system, in particular, the systematic dependence of the system behavior of the cleaning process on the surface of the vehicle, in particular, the systematic dependence derived by the method for indirectly deriving the systematic dependence of the system behavior of the cleaning system for the vehicle, as described in the second aspect of this specification, between the input amount of the cleaning system, preferably at least one control amount of the cleaning process, and / or at least one processing amount, preferably humidity and / or temperature near the vehicle, and / or rainfall and / or snowfall, and / or coordinates of the vehicle, and / or vehicle type, and / or sensor availability, and the output amount of the cleaning system, preferably resource requirements and / or sensor availability of the cleaning process, and in accordance with the systematic dependence of the system behavior of the cleaning process on the surface of the vehicle, in particular, the systematic dependence derived by the method for indirectly deriving the systematic dependence of the system behavior of the cleaning system for the vehicle, as described in the second aspect of this specification. and / or The electronic control unit controls resource-efficient cleaning, preferably by applying a control amount setpoint, particularly preferably by applying a control amount setpoint derived by the method described in the third aspect of the present invention, to conserve resources. and / or The electronic control unit controls resource-efficient cleaning, preferably by applying a cleaning strategy, particularly preferably by applying a cleaning strategy derived by the method described in the fourth aspect of the present invention, to conserve resources. and / or The cleaning method includes a process step for indirectly deriving the systematic dependence of the system behavior of the system components of an automobile cleaning system, preferably a process step for indirectly deriving the systematic dependence described in the fifth aspect of the present invention. and / or The cleaning method includes a process step for diagnosing the system behavior of system components of an automobile cleaning system, preferably a process step for diagnosing the system behavior of system components of a cleaning system according to the first alternative example of the sixth aspect of the present invention. and / or The cleaning method includes a process step for diagnosing deviations between the actual and expected system behavior of system components of an automobile cleaning system, preferably a process step for diagnosing deviations between the actual and expected system behavior of system components of a cleaning system according to a second alternative example of the sixth aspect of the present invention. and / or The cleaning method includes 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 includes a process step for using a selected solution strategy, preferably a process step for using a selected solution strategy as described in the eighth aspect of the present invention. and / or The cleaning method includes process steps for indirectly deriving the systematic dependence of the system behavior of the fouling process on the surface of an automobile, preferably process steps for indirectly deriving the systematic dependence as described in the ninth aspect of the present invention. and / or The cleaning method is - A dependency table showing at least two datasets, preferably at least 50 datasets, particularly preferably at least 200 datasets, wherein each dataset is stored in a related and ordered manner, containing at least one input quantity of a contamination process, in particular the vehicle mileage between a first availability and a second availability, and / or the operating time by covering the vehicle mileage between the first availability and a second availability, and / or the vehicle's driving speed, preferably the driving speed along the route between the first availability and a second availability, and / or the processing volume, preferably humidity, particularly preferably the first A dependency table showing the humidity process along the path between the first availability and the second availability, and / or the temperature near the vehicle, particularly preferably the temperature process along the path between the first availability and the second availability, and / or the rainfall, particularly preferably the rainfall process along the path between the first availability and the second availability, and / or the snowfall, particularly preferably the snowfall process along the path between the first availability and the second availability, and / or the vehicle's coordinates, particularly preferably the vehicle's coordinates along the path between the first availability and the second availability, and / or the first availability of the sensor, and the evaluated changes in availability. and / or - A process step for cleaning at least one surface of an automobile, for resource-efficient cleaning, preferably for resource saving, preferably using a systematic dependency on the system behavior of an automobile surface fouling process derived by a method for indirectly deriving a systematic dependency as described in the 9th aspect of the present invention, Preferably, the expected availability of an automobile in a distance or operating time that is not yet covered, as described in the tenth aspect of the present invention, and / or When the availability threshold is reached, preferably, the expected distance or expected operating time of the uncovered vehicle according to the 11th aspect of the present invention is determined, and / or In particular, by applying the method for optimizing resource requirements for an automobile surface cleaning process described in a third aspect of the present invention, the resource requirements for an automobile surface cleaning process are optimized. and / or In particular, by applying the method for determining a cleaning strategy for cleaning a surface of an automobile to be cleaned according to the fourth aspect of the present invention, a cleaning strategy for cleaning a surface of an automobile to be cleaned is determined. and / or Preferably, the problem is solved by a cleaning method, characterized by including a process step of determining an expected increase in availability, as described in a 14th aspect of the present invention, such that the sum of the actual availability and the required expected increase in availability is sufficient to achieve a distance or operating time not yet covered by the vehicle, such that an availability threshold is not exceeded.

[0016] Let's explain the terminology in detail. First and foremost, it is necessary to clearly state that in the context of this patent application, indefinite articles and numbers such as "1" and "2" should generally be understood as "at least" information, i.e., "at least one...", "at least two...", etc., unless it 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 essential.

[0017] In the context of this patent application, the term “in particular” should always be understood to mean the introduction of an optional preferential feature. This expression should not be understood as “that is.”

[0018] The "cleaning method" refers to a method for cleaning at least one surface or a surface component of a motor vehicle, by which impurities are reduced or removed. Preferably, the driver of the motor vehicle can preferably select a cleaning mode in an automatic cleaning method, and the cleaning method, which is required to replenish resources necessary for the cleaning method as needed, is implemented automatically or semi-automatically.

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

[0020] It is particularly preferred that, in order to clean at least one component of the vehicle surface, the cleaning method may be automatically implemented during vehicle operation and / or outside vehicle operation hours, and therefore it is also conceivable that, apart from replenishing necessary resources, the cleaning method may be implemented autonomously.

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

[0022] "Cleaning liquid" may 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", wherein one cleaning process relates to cleaning of one surface. Each cleaning process represents a "cleaning period" in which at least one cleaning means is operatively connected to the corresponding surface, and the cleaning period has 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 performed while the cleaning process is running, 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 either case, the term end time refers to the end time of the cleaning process and / or the end time of the evaluation process of the cleaning process, depending on the question under consideration.

[0025] In particular, it should be especially considered that a single cleaning process, in the context of evaluating the cleaning process, may lead to several datasets, preferably different datasets, differing only by the completion time of the cleaning process evaluation.

[0026] "Surface" refers to the surface elements of an automobile. The preferred term for surface is the windshield and / or rear window and / or side window of an automobile. Furthermore, a surface is preferably understood as a surface element behind which a sensor is located. Another preferred term for surface is any part of the surface of an automobile that is visible from the outside, and in particular includes hidden surfaces such as parts of the wheel arch liner within the wheel arch of an automobile.

[0027] A surface can also be understood as a surface element located inside a vehicle, preferably inside the vehicle and / or in the vehicle's engine compartment.

[0028] A "vehicle" or "automobile" is generally understood to be a self-propelled vehicle with wheels that does not operate on rails and is used for transporting people or goods.

[0029] Preferably, the propulsion of the vehicle is provided by an engine or a motor, usually an internal combustion engine or an electric motor, or a combination of two or more, 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 for a physical cleaning process.

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

[0032] A "cleaning fluid distribution system" refers to a system designed to provide cleaning fluid to the surface of a vehicle being cleaned.

[0033] Preferably, the cleaning fluid distribution system includes at least one "cleaning fluid line" adapted to transport the cleaning fluid from a pump and / or cleaning fluid reservoir to a nozzle.

[0034] A "nozzle" is a device through which the cleaning fluid can leave the cleaning system, and is designed to allow the cleaning fluid to interact with the surface being cleaned, preferably in an operable connection.

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

[0036] Preferably, the nozzle represents an actuator designed to influence the direction in which the cleaning fluid is directed away from the cleaning fluid distribution system.

[0037] Preferably, the nozzle features a second actuator designed to influence the rate of the cleaning fluid, which is the mechanism by which the cleaning fluid leaves the cleaning fluid distribution system.

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

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

[0040] The electric pump is preferably connected to a cleaning fluid reservoir and nozzle by a "cleaning fluid line" 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. The data processing system 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 preferably performs a cleaning method, particularly preferably the cleaning method described in the first aspect of the present invention, and / or performs a method for indirectly deriving systematic dependencies, preferably the system behavior of the automotive cleaning system, particularly preferably the system behavior of the automotive surface cleaning process, particularly preferably the method for indirectly deriving systematic dependencies described in the second aspect of the present invention, and / or performs a method for indirectly deriving systematic dependencies of the system behavior of the system components of the automotive cleaning system, particularly preferably the method for indirectly deriving systematic dependencies described in the fifth aspect of the present invention, and / or performs a method for indirectly deriving systematic dependencies of the system behavior of the automotive surface soiling process, particularly preferably the method for indirectly deriving systematic dependencies described in the ninth aspect of the present invention, and / or performs a method for optimizing resource requirements for the automotive surface cleaning process, particularly preferably the method for optimizing resource requirements according to the first and / or second alternative examples of the third aspect of the present invention, and / or a cleaning strategy for cleaning the automotive surface to be cleaned. A method for determining, particularly preferably a method for determining a cleaning strategy as described in the fourth aspect of the present invention, and / or a method for diagnosing deviations between the actual and expected system behavior of the system components of the automobile cleaning system, particularly preferably a method for diagnosing deviations between the actual and expected system behavior as described in the sixth aspect of the present invention, and / or a method for selecting a solution strategy, particularly preferably a method for selecting a solution strategy as described in the seventh aspect of the present invention, and / or using the selected solution strategy, particularly preferably using the selected solution strategy as described in the eighth aspect of the present invention, and / or using a dependency table and / or systematic dependencies to determine the expected availability at a distance or operating time for automobiles not yet covered, particularly preferably using a dependency table and / or systematic dependencies as described in the tenth aspect of the present invention, and / or using a dependency table and / or systematic dependencies to determine the expected distance or operating time for automobiles not yet covered when an availability threshold is reached, particularly preferably,Using the dependency table and / or systematic dependencies described in the 11th aspect of the present invention and / or using the dependency table and / or systematic dependencies to optimize resource requirements for the cleaning process of the surfaces of the vehicle, particularly preferably using the dependency table and / or systematic dependencies described in the 12th aspect of the present invention and / or using the dependency table and / or systematic dependencies to determine a cleaning strategy for cleaning the surfaces of the vehicle to be cleaned, particularly preferably using the dependency table and / or systematic dependencies described in the 13th aspect of the present invention and / or using the dependency table and / or systematic dependencies to determine the necessary expected increase in availability, particularly preferably using the dependency table and / or systematic dependencies described in the 14th aspect of the present invention and / or using the resources of at least one surface of the vehicle Using a systematic dependency derived by a method for indirectly deriving a systematic dependency for highly efficient cleaning, particularly preferably using the systematic dependency described in the 15th aspect of the present invention, and / or using a control variable setpoint derived by a method for optimizing the resource requirements of a vehicle surface cleaning process for resource-efficient cleaning of at least one surface of the vehicle, particularly preferably using the control variable setpoint described in the 15th aspect of the present invention, and / or using a cleaning strategy derived by a method for determining a cleaning strategy for resource-efficient cleaning of at least one surface of the vehicle to be cleaned, particularly preferably using the cleaning strategy described in the 15th aspect of the present invention, and / or being set to be part of a cleaning system described in the 16th aspect of the present invention, and / or being part of a vehicle described in the 17th aspect of the present invention.

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

[0045] Of particular priority is that the electronic control unit includes a data processing system.

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

[0047] Preferably, the data processing system is a system that enables organized processing of data capacity for the purpose of obtaining information about these data capacity and / or changing these data capacity.

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

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

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

[0051] Specifically, it should be considered that such a data processing unit can determine the contamination status of a surface operably connected to a sensor, and preferably, based on the measured quantities detected by the sensor, it should be able to determine the availability of the sensor, and / or the intensity of rain, and / or snowfall, and / or condensation, and / or hail.

[0052] Preferably, such an electronic data processing unit forms a unit having sensors or is part of an electronic control unit of an automobile.

[0053] This type of data processing unit is preferably configured to process quantities recorded by several sensors.

[0054] The current value of the measured quantity is the "actual or current measured value" and / or the "current or actual measured value".

[0055] In particular, a sensor should also be understood as a virtual sensor. 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 composition of the environment. Thus, a sensor is both a physical sensor and a virtual sensor, qualitatively or quantitatively recording quantities and / or conditions of the surrounding environment. In other words, a virtual sensor determines quantities, in particular, measured quantities, controlled quantities, or processing quantities, by mathematical definition.

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

[0057] Preferably, the optical sensor is understood as a camera and / or lidar and / or radar and / or ultrasonic sensor.

[0058] The light sensor can preferably determine the brightness level, that is, 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 by comparing it with the light intensity level of a second sensor whose field of view overlaps with that of the sensor.

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

[0061] The “measured value” is the current, i.e., actual value of the “measured quantity.” The “measured quantity setpoint” is the default value of the measured quantity. Preferably, the measured quantity is any quantity that can be measured or otherwise determined in a manner that allows the measured value of the measured quantity to be further processed electronically. In particular, the measured quantity is understood to be a quantity that represents a controlled quantity, a processing quantity, or the availability of a sensor.

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

[0063] Preferably, the measured values ​​of the quantity to be measured can be determined experimentally and / or numerically. In the case of experimental investigation of measured values ​​of the quantity to be measured, preferably, experimental investigations may be considered in a laboratory, or of the entire vehicle during normal vehicle operation, or of modules or components within the framework of a modular test bench. In numerical investigations, it is necessary to consider measured values ​​of the quantity to be measured, numerical analysis and / or numerical simulation within the framework of a physical model, and the entire vehicle or modules or components may be considered individually.

[0064] The measured quantity can also be understood as a quantity representing data, which is also called “data representing the measured quantity.” The data is preferably searchable data, preferably wirelessly available data, preferably weather near the vehicle and / or along the planned route, and / or the current or actual coordinates of the vehicle. Furthermore, it is preferable to consider the data as the date of the most recent inspection of the sensor type, vehicle type, sensor and / or cleaning system and / or vehicle.

[0065] Measurement values, measured quantities, and measured quantity settings should not be understood as purely scalar quantities or values; however, whenever it seems technically reasonable, measurement values, measured quantities, and measured quantity settings should be understood as vector quantities having multiple values ​​for each dimension of a vector quantity.

[0066] The "vehicle type" refers to the specific configuration of the vehicle. In particular, the vehicle type provides information about which surfaces the vehicle exhibits, how these surfaces are formed, and which sensors are hidden behind which surfaces.

[0067] The "Processing Value" is the current value of the "Processing Amount." The "Processing Amount Setting Value" is the default value of the "Processing Amount." Preferably, the Processing Amount should be understood as a quantity that is suitable for influencing the cleaning process and cleaning results, but which itself cannot be influenced.

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

[0069] Preferably, the processing volume is equal to the vehicle speed.

[0070] Preferably, the processing volume is a system-related processing volume related to the behavior of the system, preferably the behavior of the cleaning system, which is preferably indicated by a systematic dependency. In other words, the system-related processing volume depends on the system's controllable volume.

[0071] Preferably, the processing amount is an environmental processing amount related to the surrounding environment, preferably the environment surrounding the vehicle. Examples of environmental processing amounts include the ambient temperature near the vehicle, the humidity near the vehicle, the atmospheric pressure near the vehicle, and the current rainfall and / or snowfall.

[0072] In particular, the processing volume is understood as the ambient temperature near the vehicle and / or the humidity near the vehicle and / or the actual solar radiation and / or the surface temperature of the surface being cleaned.

[0073] The processing volume is preferably an amount that occurs within or around the cleaning system and that may be at least indirectly affected by the input volume.

[0074] Preferably, the processing parameters are current, power consumption, flow rate pressure, operating time, fill level signal, reaction time, sensing time, leak signal via sensor, flow meter signal, number of operations, 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 Amount Setting Value" is the default value of the actuator that is configured to adjust the "Controlled Amount." The current value of the controlled amount is the "Actual Controlled Amount Value."

[0076] Preferably, the control quantity is suitable for influencing the cleaning process and cleaning results, and should be understood as a quantity that is regulated to control the cleaning method and / or cleaning process, and preferably controlled to influence the cleaning method and / or cleaning process.

[0077] Preferably, the controlled variable and / or the controlled variable setpoint and / or the controlled value is not a purely scalar quantity or value, but a vector quantity having multiple values ​​for each dimension of the vector quantity.

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

[0079] In particular, the controlled quantities are understood as the type of cleaning fluid, especially water and / or air, and / or the type of detergent and / or the proportion of detergent in the cleaning fluid and / or the temperature of the cleaning fluid and / or the pressure of the cleaning fluid as it leaves the nozzle and / or the flow rate of the cleaning fluid and / or the duration of the cleaning process and / or the number of cycles of the cleaning process and / or the current consumption of the fluid pump and / or the voltage of the fluid pump.

[0080] Of particular priority is that the control of the controlled quantity pursues the objective of cleaning at least one surface of the vehicle, preferably a resource-efficient, preferably resource-saving, cleaning objective.

[0081] Preferably, the control of the controlled quantity pursues multiple criteria objectives, and Pareto optimal goal achievement is aimed at cleaning at least one surface of the automobile, preferably in a resource-efficient, and especially preferably resource-saving manner, under one or more boundary conditions.

[0082] The "availability" of a technical system is a measure of its ability to perform its task.

[0083] According to possible variations, availability specifies whether the system can perform its task, based on two acceptable states.

[0084] Preferably, the surface in the first state is not excessively dirty from the viewpoint of the sensor and / or the driver of the vehicle, and in the second state it is not excessively dirty.

[0085] According to the preferred variant, availability also specifies the characteristic value that the system can use to perform that task.

[0086] Of particular priority is that availability can be assumed to represent a range of values ​​indicating intervals, where one interval limit for reach means that the system can fully meet its requirements, and other interval limits for reach mean that the system will no longer be able to meet its requirements.

[0087] Even if the availability value falls within the interval limit, the system can still meet its requirements, but under more difficult conditions. In particular, the availability value reflects the degree of contamination of the vehicle's surfaces, preferably the surface itself, preferably the sensor's surface, and especially preferably the optical sensor and / or the driver's surface.

[0088] In principle, since the degree of surface contamination can be assumed to increase with the time the vehicle is driven until cleaning, availability, if reproduced within an interval, 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 those requirements, at least partially, until it must be cleaned in order for the technical system, preferably the sensor, to be able to meet its requirements.

[0089] Availability may preferably have a value outside these interval limits. An availability higher than the interval limit value at which the associated sensor can fully meet its requirements indicates that the sensor can fully meet its requirements. An availability lower than the interval limit value 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 to which the sensor is operationally connected must be cleaned by a cleaning process so that its availability improves again to a value that allows the sensor to perform at least part of its original task again, and the surface can also be cleaned by passive cleaning processes such as rain and / or snowfall.

[0090] It should be clearly noted that surface availability should be understood to mean both the availability of the surface for the less severely impaired operation of the sensor, and the degree of purity of the surface, preferably the surface, in particular for the less severely restricted view of the driver of the vehicle, such as the windshield and / or rear window.

[0091] "Actual availability," or current availability, is the availability that is dominant at the present time.

[0092] "Expected availability" should preferably be understood as the estimated availability over a specific distance not yet covered and / or a specific operating time for a vehicle that has not yet traveled.

[0093] The expected availability can preferably be determined based on current and / or planned conditions, in particular the operating conditions of the vehicle, preferably by the estimation procedure described in the 10th aspect of the present invention, where the expected availability represents the availability at points in the vehicle's travel path that have not yet been traversed.

[0094] The “availability threshold” is understood as the threshold for availability. Preferably, reaching the availability threshold requires cleaning the surface to which the sensor whose availability is being considered is operationally connected.

[0095] "Expected increase in availability" is the estimated increase in the availability of the sensor when the surface operably connected to the corresponding sensor is cleaned, preferably, in a defined cleaning process, and more preferably, in a cleaning process defined by a control variable setpoint.

[0096] The expected increase in availability, that is, the required expected increase in availability, can preferably be derived by a 14th aspect of the present invention.

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

[0098] A "resource" is a source or supply from which profits are generated, and possesses a certain degree of usefulness.

[0099] Preferably, resources are understood here as those that can be used to clean the surface of the vehicle. Specifically, we need to consider here cleaning fluids and / or cleaning agents and / or energy and / or wiping elements, preferably wiping elements that can be replaced as needed.

[0100] "Resource requirements" are understood as the need for resources required for a cleaning process, particularly a cleaning process with defined control setpoints.

[0101] "Resource-efficient cleaning" means that the cleaning of the surface being cleaned is optimized so that the ratio of cleaning effectiveness to cleaning power is taken into consideration. In other words, resource-efficient cleaning methods require selecting the amount of control over the cleaning process based on the fact that the greatest cleaning success can be achieved with the least effort.

[0102] A control set value for resource-efficient cleaning can preferably be derived by a method for optimizing resource requirements for the automotive cleaning process, preferably by the method described in the third aspect of the present invention.

[0103] "Resource-saving cleaning" is understood to mean that the cleaning of the surface being cleaned is optimized by the highest priority cleaning objective to be achieved, which may preferably be based on the fact that the vehicle will not fail due to surface contamination, in particular due to contamination of sensor surfaces, or due to sensor malfunction caused by contamination. The preferred cleaning objective may also be that the vehicle's level of autonomy will not be compromised due to surface contamination, in particular due to contamination of sensor surfaces, or due to sensor malfunction caused by contamination.

[0104] A cleaning strategy for resource-saving cleaning can preferably be derived by a method for determining a cleaning strategy for cleaning the surfaces of an automobile to be cleaned, preferably by the method according to the fourth aspect of the present invention.

[0105] "Control" is understood as monitoring and, if possible, adjusting input quantities to achieve an objective, and in particular, adjusting input quantities in response to the occurrence of disturbances.

[0106] A "disturbance" is an output quantity that deviates from the desired output quantity.

[0107] Preferably, the disturbance is availability.

[0108] Preferably, the control means specifying a control quantity setpoint for performing a cleaning method for resource-efficient cleaning of at least one surface of an automobile, preferably for resource-saving cleaning, in order to achieve a specific purpose.

[0109] Preferably, the control is understood to be performing a cleaning method, preferably the cleaning method described in the first aspect of the present invention.

[0110] The term "adjust" refers to the automated interaction between the continuous acquisition of a measured quantity and the control of the system, depending on the specified quantity. In particular, a continuous comparison is made between the measured quantity and the specified quantity.

[0111] The "operating conditions" of an automobile refer to the conditions under which the automobile is currently used.

[0112] The active operating condition is understood to preferably mean that the vehicle is used to achieve the objective by the active operation of the vehicle, preferably to cover the distance between the starting point and the planned endpoint.

[0113] Preferably, the passive action indicates that the car 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 a value of a state quantity. Preferably, such an observable change in the state of a system or a value of a state quantity occurs as a function of the change in the value of an input quantity.

[0116] "Dependency," particularly "systematic dependency," describes a relationship where one depends on the other, preferably between the output and input quantities of a system. Changing one can achieve a causal change in the other. Functional dependency in a mathematical sense is not necessary in this context of systematic dependency, but it is possible.

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

[0118] It should be clearly pointed out that systematic dependency should be understood not only as a dependency between the pure scalar values ​​of input quantities and the pure scalar values ​​of output quantities, but also, where applicable, as a multidimensional dependency between the number of corresponding input quantities whose systematic dependency with their respective associated values ​​is considered, and the output quantities that depend on those associated values.

[0119] A "dependency table" is understood as a list of individual experiences relating to the system behavior of the cleaning system, preferably in the form of a dataset, where each dataset represents at least one input quantity, preferably an input quantity of the cleaning system, stored in a related and ordered manner, and at least one output quantity, preferably an output quantity of the cleaning system.

[0120] Preferably, the experience regarding system behavior shall represent the system operation under consideration based on a single documented cleaning process collected, preferably under laboratory conditions and / or on an actual vehicle and / or during actual vehicle operation and / or based on a numerical model.

[0121] Therefore, in particular, dependency tables can be advantageous for already documented experiences that can be applied again later, by selecting associated input quantities from a list of datasets in the dependency table, depending on the output quantity to be achieved.

[0122] In other words, the dependency table allows, on the one hand, that the empirical values ​​stored therein can always be retrieved and reprocessed, particularly regarding the control of the cleaning process, and that, at least technically reasonable and possible in the sense of control variable setpoints, input quantities from the dependency table can be used to control the cleaning process.

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

[0124] The "input quantity" is defined as the amount by which, with its help, a targeted intervention occurs in the system, preferably in the control or regulation system of the cleaning system. Its instantaneous value is the "input quantity value".

[0125] Preferably, the input quantity should not be understood as a pure scalar quantity or value, but whenever it seems technically reasonable, the input quantity value and input quantity should be understood as a vector input quantity having multiple values ​​for each dimension of the vector input quantity.

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

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

[0128] Preferably, the input amount includes further data, in particular the current location of the vehicle and / or the planned route of the vehicle and / or the covered route of the vehicle and / or the expected weather, in particular the local weather at each location along the vehicle's pre-planned route, in particular the information regarding humidity and / or solar radiation and / or temperature and / or rainfall and / or snowfall.

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

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

[0131] Preferably, the input value can be understood as the amount of the washing solution mixture, particularly the amount of one or more additives.

[0132] Preferably, the input quantity value includes, but is not limited to, the spray pattern, particularly the oscillating spray pattern and / or continuous spray pattern and / or pulsed spray pattern and / or the alignment or characteristics of the spray pattern on the surface being cleaned.

[0133] "Output volume" refers to the amount produced by a system, particularly a cleaning system. Its instantaneous value is the "output volume value."

[0134] Preferably, the output quantity should not be understood as a pure scalar quantity or value, but whenever this seems technically reasonable, the output quantity value and 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 system's response to the input quantity. The system's response to the input quantity is determined by the system behavior and can be described by the system's systematic dependencies.

[0136] Prioritizing the resource requirements and / or availability of the system-related processing volume and / or cleaning process, preferably the availability of the sensor surface and / or the surface itself, preferably the purity of the surface, particularly the windshield and / or rear window.

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

[0138] An "electronic data processing and evaluation unit" is an electronic unit that processes data capacity in a systematic manner for the purpose of acquiring or correcting information about such data capacity. Preferably, the data is recorded in a dataset, processed by a person or machine according to a specified procedure, and output as a result.

[0139] A "database" is a system for managing electronic data. The primary task of a database is to store large amounts of data efficiently, consistently, and persistently, and to provide users and application programs with the necessary subsets of the stored data in different demand-oriented representation types.

[0140] Preferably, the database includes dependency tables.

[0141] Preferably, the database includes systematic dependencies.

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

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

[0144] Preferably, the database indicates a function that the database can manage itself.

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

[0146] In particular, when a new dataset is entered, the database may delete existing datasets, especially using dependency tables. Prioritizing the deletion of datasets that exhibit the largest Euclidean distance to the statistical mean of other datasets may be desirable. Similarly, prioritizing the deletion of datasets that exhibit the greatest deviation from systematic dependencies between data may be desirable.

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

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

[0149] An "algorithm" is a clear instruction for solving a problem or classifying a problem. Preferably, an algorithm consists of a finite number of defined individual steps. Thus, the individual steps can be implemented in a computer program for execution, but they can also be formulated in human language. Preferably, an algorithm supports problem solving because a specific input, preferably an input to a dataset, can be transformed by the algorithm into a specific output.

[0150] A "curve" is understood as a two-dimensional, three-dimensional, or multi-dimensional relationship between variables. Preferably, a systematic dependency 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 an 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 of the dependent variable that can be predicted from the independent variable.

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

[0154] Regression analysis is understood as a set of statistical processes for estimating relationships between variables. When the focus is on the relationship between a dependent variable and one or more independent variables, it involves many techniques for modeling and analyzing several variables. Preferably, regression analysis helps understand how a typical value of the dependent variable changes when one of the independent variables changes, while the other independent variables remain 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 nonlinear regression.

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

[0157] "Self-learning optimization methods" is a classification of algorithms that can also be categorized under the general term "machine learning." These algorithms are characterized by the fact that they learn from examples on the one hand, and can generalize the learned knowledge on the other. Therefore, such algorithms generate knowledge from experience.

[0158] "Optimization" means the process aimed at finding an optimal value, in particular an optimal value for an input quantity, by selecting a value for an input quantity known to enable or demonstrate the best achievement of an objective, in order to maximize the degree to which the objective is achieved, in particular by minimizing or maximizing the corresponding objective function and / or by enabling or demonstrating the best achievement of the objective.

[0159] In particular, it is necessary to explicitly state that optimization does not necessarily mean finding the exact optimal value for the input quantity.

[0160] "Distance" is understood as the distance between two points that are covered, will be covered, or are scheduled to be covered by a 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, the route planning to establish the distance is carried out with the help of a navigation system.

[0164] Actual availability may be "sufficient to cover the distance to the next wash process" if it can be used to cover the next distance or planned distance before the next wash process without falling below a predefined availability threshold. In other words, the available availability in this case is probably sufficient to cover the planned distance to the next wash process in the vehicle without losing the functionality of the sensor linked to the corresponding available area.

[0165] "Expected distance covered by the vehicle when the availability threshold is reached" is the expected distance that the vehicle can cover until it reaches a predefined availability threshold.

[0166] "Operating time" refers to the period of use of the vehicle that has already elapsed, or is currently on hold or planned.

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

[0168] "Expected operating time of the vehicle 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" refer to the geographical location of a vehicle on Earth, and can be coordinates already passed, actual or current coordinates, or coordinates along a planned route.

[0170] Preferably, the coordinates can also be understood as a sequence of coordinates along an already completed or planned path.

[0171] A "cleaning strategy" is a plan of how the cleaning system will behave under all conceivable circumstances. Therefore, the cleaning strategy completely describes the behavior of the cleaning system.

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

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

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

[0175] The "cleaning mode" or "actual cleaning mode" is the operating mode of the cleaning system. By selecting a cleaning mode, the vehicle manufacturer and / or driver can influence which driver assistance systems should not fail due to sensor contamination, and the selected cleaning mode may also include the possibility that cleaning should not be performed at all. This can directly affect the availability of the driver assistance systems.

[0176] The cleaning mode determines whether the driver assistance systems are protected from failure due to excessive fouling caused by the cleaning measures, or how many driver assistance systems are protected from failure due to excessive fouling caused by the cleaning measures. Therefore, the selection of the cleaning mode also indirectly affects the number of "selected sensors" that should not undershoot the availability threshold.

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

[0178] Preferably, there may be one or more cleaning modes, and one or more cleaning modes can be selected simultaneously.

[0179] Preferably, the first cleaning mode means "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 means "comfortable vehicle operation," which means that the cleaning system takes all necessary cleaning measures to ensure that the comfortable operation of the vehicle is not impaired due to contamination of the vehicle's sensors. This includes, among other things, that the cleaning system maintains the functions of the driver assistance systems, such as distance keeping, lane keeping, parking assist, parking assist, and / or trailer assist, by all necessary cleaning measures.

[0181] Preferably, the third cleaning mode means "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. This includes, among other things, that the cleaning system maintains the pedestrian recognition and / or road user recognition functions of the driver assistance system by all necessary cleaning measures.

[0182] Preferably, the fourth cleaning mode means "to the best possible extent," which means that the cleaning system performs only the cleaning methods prescribed by law for the operation of the vehicle.

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

[0184] "System components" are understood as any component of a cleaning system. It should be clearly noted that system components 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. Since 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] "Electric current" can flow through an electrical circuit under certain conditions. Furthermore, an electrical circuit may have consumers, particularly consumers that enable useful applications in the form of system components. Consumers may have "power consumption," which represents the energy demands of the consumer.

[0187] Consumers who enable electrical applications require energy to perform their work. Specifically, it is conceivable that power consumption may fluctuate when a consumer performs the same task. This could be due to different operating conditions, particularly different ambient temperatures, and / or the effects of consumer aging.

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

[0189] "Fluid pressure" is the pressure of a fluid, particularly a cleaning fluid, and consists of static and dynamic components. Local fluid pressure can be measured locally, especially with a pressure sensor.

[0190] "Operating time" refers to the operating time of each individual system component.

[0191] The "fill level signal" is understood as information that directly indicates the fill level value within the storage container, and indirectly indicates the amount of substance stored.

[0192] "Reaction time" is generally understood as the time between an action and a reaction, and more specifically, the time between a measurement and the effect of that measurement.

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

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

[0195] "Leak sensor signal" refers to information provided by a leak sensor that provides information about the presence of a leak and / or the flow rate of the leaking fluid. In particular, leak sensors may include sensors attached to the coupling of two fluid channels.

[0196] "Operation count" refers to the number of times a system component has been used. In particular, the number of pump operations already performed by a pump, or the number of heating operations already performed by a heater, can be taken into consideration.

[0197] The "spray pattern" is the pattern that the cleaning solution remains on the surface being cleaned after it leaves the cleaning nozzle.

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

[0199] "Fragment sensor signal" is understood to be information provided by a fragment sensor that provides information about the quantity and / or type of foreign matter in the cleaning system.

[0200] "Check valve signal" is understood as part of the information provided by the check valve, indicating its position.

[0201] "Drip sensor signal" is understood as information provided by a drip sensor indicating the presence and / or 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 the object detected by the sensor.

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

[0204] "Actual system behavior" refers to the observable system behavior of the system components of a car washing system. Preferably, the actual system behavior can be monitored and / or determined by a measuring system. Preferably, the actual system behavior can be described by the actual output amount determined, preferably by a measuring system, and preferably by a sensor.

[0205] It is important to clearly point out that actual output quantities can be understood as scalar and vector quantities. If an actual output quantity has only one parameter, it is a scalar quantity. If an actual output quantity has multiple parameters, especially a process of parameters over time, then the actual output quantity is a vector quantity.

[0206] Preferably, the actual output is designed to reflect the system behavior of the system components with respect to all parameters related to characterizing the system behavior.

[0207] The expected system behavior is the system behavior of the system components for the automobile washing 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 the "expected output."

[0208] It should also be explicitly noted that the expected output quantity may be a scalar or vector quantity similar to the actual output quantity.

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

[0210] In particular, deviations can indicate typical measurement errors of the system. Specifically, the size of this typical measurement error can vary 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] If the deviation falls within the specified range of measurement error, a numerical deviation exists, 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 a car washing system may be affected by measurement errors, as well as further variations and / or deviations, which may be within the expected range. These expected non-significant deviations and / or variations may differ for each dimension of the output quantity.

[0213] A "temporal process," particularly a temporal process of deviation, is a data series as a function of time, especially a data series that includes data of deviation.

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

[0215] Preferably, the data points have time distances that are equidistant from each other.

[0216] Preferably, the time interval between data points increases. Particularly preferred is a time distance between data points that is logarithmically proportional to 1 from time.

[0217] A "step response" is an output signal of a system, particularly an output signal of a system component of a cleaning system that responds to a planned change in input quantity. Preferably, it can be advantageously used to characterize a linear time-invariant system. Preferably, the temporal process of the step response can be used to draw conclusions about decay present in the system, and for example, it can be advantageously used to determine whether there is a blockage in the flow channel for the cleaning fluid.

[0218] "Drift" is a systematic deviation that changes continuously in one direction.

[0219] Preferably, the drift of the output signals of system components can allow for statements about the aging degradation phenomena of system components. Drift can be used, in particular, to determine how long a system component can still be used. Specifically, drift can be used to analyze when a system component needs to be replaced to avoid failure.

[0220] Overall, the system behavior of the system components preferably deviates from acceptable system behavior only when the output exceeds an "upper threshold amount" and / or falls below a "lower threshold amount," taking into account measurement errors and expected non-significant fluctuations.

[0221] It should be clearly noted that the upper and / or lower threshold quantities can be scalar or vector quantities, as well as the expected or actual output quantity or deviation. Preferably, the upper and / or lower threshold quantities indicate the dimensions of the output quantity.

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

[0223] Preferably, the system behavior of a system component may depend on the input quantity, and the reversible range of the expected system behavior and / or actual output quantity of a system component may depend on the input quantity; therefore, the upper and lower thresholds may depend on the input quantity.

[0224] "Diagnosing" generally refers to understanding the comparison between the observed system behavior and the expected system behavior of the system components of a cleaning system.

[0225] In particular, "diagnose" refers to the process of monitoring output levels and, in particular, comparing the output levels to upper and / or lower threshold levels to determine whether the observed system behavior of a system component deviates from the expected system behavior within acceptable limits.

[0226] Similarly, unacceptable deviations from actual system behavior can preferably be evaluated based on a percentage limit corresponding to the expected output level.

[0227] The diagnosis can preferably also be understood as a characterization of possible deviations. This characterization may preferably be performed based on the temporal process of the output quantity.

[0228] The “diagnostic signal” preferably describes the result of a method for diagnosing the system behavior of system components of an automobile washing system.

[0229] In particular, diagnostic signals can demonstrate that the actual system behavior perfectly corresponds 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 preferably the diagnostic signal may include, in what form and on what component of the output quantity, the actual system behavior does not correspond to the expected system behavior.

[0231] "Current diagnostic signals" are understood as diagnostic signals that are currently present and for which a solution strategy is sought.

[0232] A "solution strategy" is understood as a procedure that, based on available experience, is suitable for eliminating deviations between the actual system behavior of a system component and the expected system behavior of that system component in the cleaning system.

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

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

[0235] "First availability" is understood as the first state of availability. "Second availability" is understood as the second state of availability, after a time has elapsed between the first and second availability states.

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

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

[0238] With the increasing number of driver assistance systems, the number of sensors in vehicles, particularly those with optical operating principles, is also increasing. In particular, sensors with optically active components rely on the fact that the part of the vehicle surface that is actively connected to the sensor, especially the part that is actively connected to the sensor with optically active components, may only exhibit an upper limit of contamination.

[0239] If the contamination of this part of the vehicle's surface exceeds this maximum level, the sensor's functionality can no longer be guaranteed to a sufficiently high degree, and the functionality of the driver assistance system will also be affected by the level of contamination.

[0240] As a result, in order to maintain the functionality of the driver assistance system, it is necessary to clean the surfaces that are actively connected to each sensor that provides data for the driver assistance system, which increases as the number of sensors increases.

[0241] This cleaning process 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, and further contributes to an increase in the vehicle's weight.

[0242] The additional weight and space requirements of the system components are undesirable.

[0243] Therefore, this paper proposes a specific cleaning method for resource-efficient cleaning, preferably resource-saving cleaning, of at least a portion of the surface of an automobile.

[0244] Resource-efficient cleaning means that the cleaning of the surface being cleaned is optimized so that the ratio of cleaning effectiveness to cleaning cost is taken into consideration. In other words, resource-efficient cleaning requires selecting the control amount of the cleaning process so that the maximum cleaning success is achieved with the minimum effort, and the control amount setting at least indirectly determines the amount of resources the process requires to clean the surface.

[0245] "Resource-saving cleaning" is understood to mean that the cleaning of the surface being cleaned is optimized by the highest priority cleaning objective to be achieved, which may preferably be based on the fact that the vehicle will not fail due to surface contamination, in particular due to contamination of sensor surfaces, or due to sensor malfunction caused by contamination. The preferred cleaning objective may also be that the vehicle's level of autonomy will not be compromised due to surface contamination, in particular due to contamination of sensor surfaces, or due to sensor malfunction caused by contamination.

[0246] The cleaning method proposed herein involves using an automobile cleaning system to plan, optimize, and / or execute individual cleaning processes, each of which relates to the cleaning of individual parts surfaces of the automobile by the use of cleaning means, in particular cleaning fluids.

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

[0248] The cleaning system includes an electronic control unit and a cleaning fluid distribution system, which 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 partially automatically within the scope of the cleaning method proposed herein, and a sensor actively connected to the surface being cleaned is preferably able to transmit the availability of the sensor to the cleaning system or is arranged to do so, and the availability of the sensor represents at least indirectly a measured value of the cleaning status of the surface to which the sensor is actively connected.

[0250] Furthermore, it is suggested that the cleaning system may have access to, or possess, available information regarding the availability of sensors and, therefore, the cleaning status of the surface being cleaned through an active connection with the sensors.

[0251] Furthermore, the sensors may be arranged to detect processing loads, in particular humidity and / or temperature near the vehicle, as well as rainfall and / or snowfall.

[0252] The cleaning system may have, or be connected to, additional sensors that can provide the cleaning system with quantifiable quantities, particularly processing and / or controllable quantities. In this way, temperature, rainfall, etc., can also be made available to the cleaning system by other sensors. This also includes the transmission to the cleaning system of corresponding data that the vehicle may retrieve via a wireless data connection as needed.

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

[0254] In particular, it is necessary to consider a cleaning method that can use information about the system behavior of the cleaning system and / or, in particular, provide this information itself by a dependency table and / or systematic dependency, in particular by the dependency table and / or systematic dependency described in a second aspect of the present invention.

[0255] As described in the second aspect of the present invention, it is understood that the advantages of the dependency table and / or systematic dependency described in the second aspect of the present invention extend directly to the cleaning method described in the first aspect of the present invention, which applies the dependency table and / or systematic dependency described in the second aspect of the present invention and / or performs a procedure for deriving the dependency table and / or systematic dependency described in the second aspect of the present invention.

[0256] Furthermore, a cleaning method is proposed to control resource-saving cleaning, preferably by applying a control variable setting value, and more preferably by applying a control variable setting value derived by the method described in the third aspect of the present invention.

[0257] As described in the third aspect of the present invention, it is understood that the advantages of the control variable setting value described in the third aspect of the present invention directly extend to the cleaning method to which such control variable setting value described in the first aspect of the present invention is applied.

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

[0259] As described in the fourth aspect of the present invention, it is understood that the advantages of the cleaning strategy described in the fourth aspect of the present invention directly extend to the cleaning method to which such cleaning strategy described in the first aspect of the present invention is applied.

[0260] In particular, it is necessary to consider a cleaning method that can use information about the system behavior of the system components of the cleaning system and / or, in particular, provide this information itself by a dependency table and / or systematic dependency, in particular by the dependency table and / or systematic dependency described in the fifth aspect of the present invention.

[0261] As described in the fifth aspect of the present invention, it is understood that the advantages of the dependency table and / or systematic dependency described in the fifth aspect of the present invention extend directly to the cleaning method described in the first aspect of the present invention, which applies the dependency table and / or systematic dependency described in the fifth aspect of the present invention and / or performs a procedure for deriving the dependency table and / or systematic dependency described in the fifth aspect of the present invention.

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

[0263] As described in the first alternative example of the sixth aspect of the present invention, the advantages of the method for diagnosing the system behavior of system components of a cleaning system according to the first alternative example of the sixth aspect of the present invention are understood to directly extend to the cleaning method described in the first aspect of the present invention, which includes such process steps for diagnosing the system behavior of system components of a car cleaning system.

[0264] In particular, a cleaning method should also be considered that includes a process step for diagnosing deviations between the actual and expected system behavior of system components of an automobile cleaning system, preferably a process step for diagnosing deviations between the actual and expected system behavior of system components of a cleaning system according to a second alternative example of the sixth aspect of the present invention.

[0265] As described in the second alternative example of the sixth aspect of the present invention, the advantages of the method for diagnosing deviations between the actual and expected system behavior of system components of an automobile washing system according to the second alternative example of the sixth aspect of the present invention are understood to directly extend to the washing method described in the first aspect of the present invention, which includes such process steps for diagnosing deviations between the actual and expected system behavior of system components of an automobile washing system.

[0266] A cleaning method is also proposed that includes a process step for selecting a solution strategy, preferably a process step for selecting a solution strategy as described in the seventh aspect of the present invention.

[0267] As described in the seventh aspect of the present invention, the advantages of a method for selecting a solution strategy, preferably the method for selecting a solution strategy as described in the seventh aspect of the present invention, are understood to directly extend to cleaning methods to which such a method for selecting a solution strategy as described in the first aspect of the present invention is applied.

[0268] Furthermore, a cleaning method should be considered that includes a process step for using a selected solution strategy, preferably a process step for using a selected solution strategy as described in the eighth aspect of the present invention.

[0269] It is understood that the advantages of a method using a selected solution strategy, preferably a process step for using a selected solution strategy as described in the eighth aspect of the present invention, directly extend to a cleaning method that applies such a method using a selected solution strategy as described in the first aspect of the present invention.

[0270] In particular, it is necessary to consider cleaning methods that can use information about the system behavior of the fouling process on the surface of an automobile, and / or provide this information itself, in particular by dependency tables and / or systematic dependencies, in particular by the dependency tables and / or systematic dependencies described in the ninth aspect of the present invention.

[0271] As described in the ninth aspect of the present invention, it is understood that the advantages of the dependency table and / or systematic dependency described in the ninth aspect of the present invention directly extend to the cleaning method described in the first aspect of the present invention, which applies the dependency table and / or systematic dependency described in the ninth aspect of the present invention and / or performs a procedure for deriving the dependency table and / or systematic dependency described in the ninth aspect.

[0272] In particular, within the scope of the cleaning methods proposed herein, it is necessary to consider determining the expected availability at the distance or operating time of the vehicle that has not yet been covered, preferably using the dependency table and / or systematic dependency described in Aspect 9 of the Invention, and / or preferably by applying the method for optimizing the resource requirements for the vehicle surface cleaning process, particularly the method for optimizing the resource requirements for the vehicle surface cleaning process, described in Aspect 3 of the Invention, to determine the expected distance or operating time of the vehicle that has not yet been covered when the availability threshold is reached, and / or preferably by applying the method for determining the cleaning strategy for cleaning the vehicle surface that is to be cleaned, particularly the method for determining the cleaning strategy for cleaning the vehicle surface that is to be cleaned, described in Aspect 4 of the Invention, and / or preferably by determining the required expected increase in availability, as described in Aspect 14 of the Invention, such that the sum of the actual availability and the required expected increase in availability is sufficient to achieve the distance or operating time of the vehicle that has not yet been covered, such that the availability threshold is not exceeded.

[0273] Using the dependency table and / or systematic dependency described in the ninth aspect of the present invention, preferably, the expected availability at distance or operating time for an uncovered vehicle as described in the tenth aspect of the present invention, and / or, preferably, the expected distance or expected operating time for an uncovered vehicle when the availability threshold is reached, by applying the method for optimizing resource requirements for the vehicle surface cleaning process, in particular the method for optimizing resource requirements for the vehicle surface cleaning process described in the third aspect of the present invention, to optimize resource requirements for the vehicle surface cleaning process, and / or, in particular, the cleaning strategy for cleaning the vehicle surface to be cleaned as described in the fourth aspect of the present invention. By applying the method, the advantages of determining a cleaning strategy for cleaning the surfaces of an automobile to be cleaned, and / or preferably determining the required expected increase in availability as described in the 9th and / or 10th, and / or 11th, and / or 12th, and / or 13th and / or 14th correspondence of the present invention, and that the sum of the actual availability and the required expected increase in availability is sufficient to achieve the distance or operating time that the automobile has not yet covered, such that the availability threshold is not exceeded, and that this is sufficient to 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.

[0274] In a convenient embodiment, an electronic control unit controls and / or adjusts resource-efficient cleaning, preferably resource-saving cleaning, in accordance with the actual measured value, preferably the actual availability of a sensor operably connected to the surface being cleaned.

[0275] In particular, it is specifically proposed that the cleaning method be carried out in a modified manner.

[0276] In other words, the cleaning method needs to be applied within a framework of adjustment, not just controlled by specifications.

[0277] The cleaning method needs to be adjusted as a function of the measured quantity, and in particular as a function of the availability of the sensor, whose surface is actively connected to the sensor and is 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 performed within the scope of the cleaning method based on the availability of associated sensors.

[0279] This is particularly advantageous because the availability of associated sensors allows for feedback on the current cleaning state, enabling the system to respond to deviations from the cleaning results in a situation-appropriate manner.

[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 to run less effective cleaning processes for longer than planned than anticipated, thereby achieving resource-optimal cleaning results in an overall assessment, and even if additional resources are needed for these individual cleaning processes, 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 to the surfaces to be cleaned by the cleaning process, provided that each surface is not currently excluded from cleaning by the cleaning strategy.

[0283] Here, we propose that, in particular, a cleaning process, specifically a cleaning process pre-planned by a control variable setpoint, be initiated in response to the occurrence of a trigger condition, as soon as a predefined threshold for sensor availability is reached.

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

[0285] Furthermore, it is proposed that the cleaning method initiates a cleaning process if the sensor availability is lower than or close to a predefined threshold for sensor availability.

[0286] Among other things, this may be advantageous for the cleaning method to initiate a cleaning process even after a malfunction of the cleaning system and / or after replenishing previously insufficient cleaning resources, in particular even after initiating an extensive cleaning process.

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

[0288] If it is not feasible to complete the planned route in the currently selected cleaning mode, the cleaning method suitably forces a change of the cleaning mode.

[0289] When it becomes impossible to reach the pre-planned destination in the preselected cleaning mode, it is proposed to change the cleaning mode such that a cleaning mode that can still implement the pre-planned route is reselected without requiring additional changes to the cleaning mode, and subject to compliance with the above conditions, the cleaning mode that enables the driver to have the most comfortable driving experience possible can be selected.

[0290] The advantage of this is that the planned destination can be reached without replenishing cleaning resources during a service stop, by using the resources available for cleaning under the most comfortable conditions possible for the driver.

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

[0292] In an advantageous embodiment, when the cleaning resource reaches a reserve level, the cleaning method shifts to keeping only the sensors absolutely necessary for manual driving sufficiently available by executing a corresponding cleaning process.

[0293] Herein, a kind of reserve strategy is proposed, in which the cleaning mode is changed by the cleaning system to such an extent that only the sensors absolutely necessary for manual driving remain sufficiently available, as a last-minute measure when reaching a pre-planned destination without service maintenance is endangered 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 perform this countermeasure as late as possible so that the destination on the travel route can be reached with the last available cleaning resource.

[0295] The advantage of this is that the driver can only be forced to further intervene in the driving of the motor vehicle when it is absolutely necessary.

[0296] Furthermore, as a modification according to a further optional embodiment, it is proposed that the surface that is effectively connected only to unnecessary sensors is occasionally moistened with spraying of cleaning liquid.

[0297] In this way, a surface not actively connected to one of the required sensors will not dry out, and thus advantageously, the adhesion of contaminants present on this surface can be advantageously prevented. In this way, another cleaning process aimed at directly cleaning the surface can be advantageously achieved by using fewer cleaning resources, as it does not need to remove a layer of covered dirt in a short time, but rather removes dirt that is already soaked or pre-soaked.

[0298] In other words, while no cleaning process specifically aimed at immediate surface cleaning is proposed here, a cleaning process is proposed that facilitates subsequent cleaning processes aimed at immediate surface cleaning, particularly those that improve usability with less resource consumption.

[0299] Therefore, by combining them, a more efficient cleaning process can be enabled.

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

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

[0302] Here, we propose a cleaning method that demonstrates a cleaning process designed to moisten the surface to be cleaned.

[0303] The cleaning method should preferably consist of two cleaning processes, the first of which is designed to moisten only the surface so that the covered dirt on the surface to be cleaned is softened. This has the advantage that the contaminants are easier to dissolve in the subsequent cleaning process.

[0304] The second cleaning process from a temporal perspective is designed to reduce or remove previously softened dirt by using a cleaning means.

[0305] Furthermore, it should particularly be considered that the cleaning process configured to clean the surface to be cleaned is preceded by a plurality of cleaning processes each intended to moisten the surface to be cleaned. These cleaning processes configured to humidify the surface may be performed during active and / or passive operating conditions of a motor vehicle.

[0306] In this way, drying of dirt on the surface to be cleaned can advantageously be prevented.

[0307] Therefore, it is particularly conceivable that the surface of the motor vehicle to be cleaned can also be moistened in a parked state by a cleaning process.

[0308] An advantage is that overall resource efficiency can be improved when cleaning the surface to be cleaned.

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

[0310] In an optional embodiment, the cleaning method comprises a cleaning process that is adapted to be started when an operating condition of the motor vehicle changes.

[0311] Here, it is suggested that the cleaning method is adapted to start the cleaning process when the operating condition of the motor vehicle changes.

[0312] Preferably, the cleaning method should begin the cleaning process when the vehicle starts, i.e., when the vehicle transitions from a passive to an active operating state, and as a result, consideration should be given to the possibility that the availability of sensors may be improved at the start of movement, in particular, in such a way that the sensors achieve the minimum availability for functional sensor operation.

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

[0314] The advantage of this is that the cleaning method can respond to changes in the vehicle's operating state depending on the situation.

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

[0316] According to a second aspect of the present invention, a method for indirectly deriving the systematic dependence of the system behavior of an automobile cleaning system, particularly preferably the system behavior of an automobile surface cleaning process, for cleaning at least one surface of an automobile, preferably, for resource-efficient cleaning, particularly preferably, for resource-saving cleaning, wherein the output amount depends on the input amount due to the system behavior of the system, - A step of determining an input quantity as a first parameter of the method using at least one sensor, - Preferably, the method includes the step of determining the output amount as a second parameter of the method, using at least one sensor. - A step of digitizing and recording the determined first and second parameters as necessary by a data processing system, wherein the data processing system represents an electronic data processing and evaluation system and a database, and the step of digitizing and recording. - The steps include storing the determined first and second parameters in the database as a dataset in a dependency table, in a related and ordered manner, - A step of deriving 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, and particularly preferably from at least 200 datasets of dependency tables, by an electronic data processing and evaluation system, wherein the electronic data processing and evaluation unit accesses the datasets of the dependency tables and determines and derives the systematic dependency from the datasets using an algorithm. - Preferably, the task is solved by a method that includes the step of 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, the surfaces of vehicles being washed were typically cleaned at predetermined intervals upon the driver's request, or automatically when contamination was detected.

[0318] As the number of sensors in vehicles increases, and as safety aspects arise from the potential provided by driver assistance systems leading up to autonomous driving, the relevance of cleaning vehicle surfaces, particularly those superimposed on sensors, has increased significantly.

[0319] Surfaces superimposed on the sensor are defined in particular as the outermost surfaces of the vehicle that cover the sensor, specifically the windshield, rear window, camera lens, and / or sensor cover.

[0320] As the need for cleaning increases, so does the need for resources to clean the corresponding surfaces.

[0321] This highlights the need for new cleaning strategies, specifically the need to achieve resource-efficient cleaning, or more preferably resource-saving cleaning, so that fewer resources need to be allocated to the required cleaning process.

[0322] Therefore, the relationship between the success of the cleaning process and the resulting resource requirements is a point of consideration, particularly with the aim of achieving the most efficient or even better resource savings possible.

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

[0324] The success of the cleaning process is influenced, in particular, by the different processing volumes of the cleaning process, and especially by air humidity and / or temperature, as well as rainfall and / or snowfall, as well as the actual amount of solar radiation, and / or the temperature of the surface being cleaned.

[0325] Furthermore, the success of the cleaning process is also influenced by the speed at which the vehicle travels during the cleaning process and the type of vehicle. The vehicle type provides information about the number of surfaces to be cleaned, where those surfaces are located on the vehicle, and how they are oriented relative to the vehicle's direction of travel.

[0326] Furthermore, there are numerous possible cleaning processes, each with a different selection of control parameters.

[0327] The controlled quantity determines when, for how long, and in what form to use which resources and / or cleaning means to clean each surface.

[0328] The resource requirements for the cleaning process can be determined directly or indirectly, in particular, depending on the amount of control over the cleaning process.

[0329] When implementing resource-efficient cleaning, preferably resource-saving cleaning, specific questions arise regarding which control levels can be used for which vehicle type, and under what processing volume and resource requirements a particular cleaning method will be successful.

[0330] As already explained above, the complexity of the questions we consider here increases because numerous influencing factors can affect the outcome of the cleaning process and resource requirements.

[0331] In recent years, the complexities of the cleaning process have led to a wide range of potential influences, and the potential for individual effects to overlap means that resource-efficient cleaning is often beyond the realm of intuitive understanding.

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

[0333] As a result, not only has the effort required to design cleaning systems and strategies increased significantly, but the resources needed have also increased significantly because it is necessary to ensure cleaning success while guaranteeing a certain level of safety. This goal can be achieved primarily by expanding the use of resources.

[0334] In this regard, the objective of resource-efficient cleaning of automotive surfaces, preferably resource-saving cleaning, is a currently highly debated topic, particularly because the overall system behavior between input and output amounts is not determined.

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

[0336] Deviating from the above, we propose here a method for indirectly deriving the systematic dependence of the system behavior of an automobile washing system between the system's input and output quantities, where the output quantity depends on the input quantity due to the system's behavior.

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

[0338] Preferably, the input quantity indicates the pressure of the cleaning solution and / or the temperature of the cleaning solution and / or the mixture of the cleaning solution, 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 a spray pattern aligned to the surface being cleaned.

[0339] Preferably, the input quantity indicates the processing quantity.

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

[0341] Furthermore, it is suggested that the output volume should indicate the resource requirements of the cleaning method. Resource requirements can be determined indirectly, or directly, based on corresponding measurements, particularly as a function of the controlled volume.

[0342] Preferably, systematic dependencies are suggested to describe the system behavior of a surface cleaning process for an automobile for cleaning at least one surface of the automobile.

[0343] The procedure proposed here, - First, in the case of an individual cleaning process, the input quantity is determined as the first parameter, and the output quantity is determined as the second parameter. The data processing system records the determined first and second parameters and stores them in the database as a single dataset for the individual cleaning process in a related and ordered manner. Next, the systematic dependency between the first parameter and the second parameter is systematically derived from multiple datasets, specifically using multiple datasets from a dependency table, by the algorithm.

[0344] Needless to say, unless existing data is available, obtaining more datasets to derive systematic dependencies requires first running the first part of the procedure where the first and second parameters are recorded several times initially.

[0345] The corresponding datasets can be collected directly during the washing process performed on the vehicle, particularly during normal vehicle operation.

[0346] Furthermore, such datasets can also be determined and / or derived from laboratory experiments.

[0347] In further variations, the dataset may be determined by a numerical model representing the corresponding purification process.

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

[0349] From these empirical observations, the systematic dependencies proposed here can be derived in the manner proposed here. These systematic dependencies can be used to select or determine the optimal or resource-efficient cleaning process.

[0350] Preferably, systematic dependencies are determined based on at least two datasets, preferably at least 50 datasets, more preferably at least 200 datasets, and most preferably at least 1000 datasets.

[0351] It should be noted that the above values ​​regarding the number of datasets should not be understood as abrupt limits, but rather should be able to be exceeded or fallen below on an engineering scale without deviating from the described aspects of the invention. Simply put, the values ​​are intended to represent the size of the proposed number of datasets.

[0352] The systematic dependencies thus obtained allow us to not only evaluate and reproduce already performed cleaning processes, but also devise new cleaning processes based on systematic analysis of the data, which is advantageous in that it allows us to pursue the objective of further reducing resource requirements. This can be achieved by interpolation between available datasets. Furthermore, it is conceivable that a curve can be generated from the obtained dataset using regression methods, which enables a continuous and differentiable systematic relationship between the input and output quantities of the cleaning process.

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

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

[0355] Conveniently, the data processing system refers to an electronic data processing and evaluation system, as well as a database.

[0356] If necessary, it is suggested that the data processing system digitize the first and second parameters determined, and as a result, manage the recorded values, especially those determined by the sensors, in a digital database so that they can be processed electronically.

[0357] A systematic dependency between input and output amounts, preferably resource requirements, developed according to the proposed procedure, describes the system behavior of the cleaning system.

[0358] Therefore, for each surface being cleaned, a systematic dependency is derived that takes into account the portion of the controlled quantity that is effectively related to the corresponding surface. Specifically, this systematic dependency can be expressed as a function of this portion of the controlled quantity, and possibly as a function of the processing quantity, by a continuously differentiable, systematically determined curve that reflects the success of the cleaning and, preferably, the interdependence of quantities.

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

[0360] Optionally, the systematic dependency 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.

[0361] Such systematic dependencies can be used in various ways. Therefore, in particular, it is conceivable that a control quantity that can clean the surface in question particularly efficiently from a resource perspective can be found by comparing input quantities. Furthermore, by comparing cleaning success rates with resource requirements, it is conceivable to specifically determine a control quantity that allows for cleaning while conserving special resources for the corresponding surface.

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

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

[0364] Preferably, the input amount represents a cleaning means, in particular a wiping element on which the surface to be cleaned is treated.

[0365] Preferably, the input amount indicates the time the cleaning means is used.

[0366] Preferably, the input quantity indicates the type of automobile for which systematic dependence is considered.

[0367] Preferably, the input amount indicates the amount of cleaning solution to immerse the surface to be cleaned before it is subsequently treated by the cleaning means. More preferably, the input amount also indicates the immersion time before the surface to be cleaned is subsequently treated by the cleaning means.

[0368] Preferably, the input quantity indicates the amount of cleaning solution used to clean the surface to be cleaned and / or the duration for which the cleaning solution 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 are used and / or the type of automobile, of which systematic dependence is taken into consideration and / or the amount of cleaning solution into which the surface to be cleaned is immersed before the surface to be cleaned is subsequently treated with the cleaning means and / or the duration for which the surface to be cleaned is immersed until the surface to be cleaned is subsequently treated with the cleaning means.

[0369] By continuously specifying systematic dependencies, the design of procedures becomes more favorable, and the robustness of these dependencies can be checked. Therefore, it becomes possible to quantify whether a systematic dependency is a regularity or a trend with a specific probability that can be captured with continuous accuracy.

[0370] Another advantage of the procedure described here is that a virtually unlimited number of parameters can be stored in relation to each other and used to derive systematic dependencies, preferably (n+i)-dimensional systematic dependencies.

[0371] Operators of appropriate lavage systems naturally have limitations in their ability to map (n+i)-dimensional systematic dependencies, particularly with regard to decisions concerning the designation of control quantities in the brain. Especially with the ever-increasing complexity of the corresponding lavage systems and the growing number of detectable influence quantities, today's operators often already reach the natural limits of their comprehension. Systematic dependencies are advantageous because they are not subject to such limitations.

[0372] According to this, a suitable implementation of the proposed procedure can map complex correlations between the procedure's parameters. This is particularly applicable to dependencies involving numerous related quantities that may exhibit various correlations with one another.

[0373] Advantageously, the embodiments of the present invention presented herein can achieve the mapping of the system behavior of all related interdependent cleaning systems, resulting in extensive experience in the proper and resource-efficient cleaning of vehicle-type surfaces.

[0374] In particular, by resource-efficiently cleaning a single surface of a vehicle type, it is possible to record or derive that efficient cleaning is possible under given environmental conditions and given initial contamination levels of each surface.

[0375] It should be clearly stated that the result of the cleaning process does not necessarily have to be a complete cleaning of the surface. In particular, since the success of surface cleaning is very small, special consideration should be given to ensuring that sensors hidden behind it continue to function.

[0376] This applies in particular to the front and rear windows of an automobile, and these windows are cleaned to such an extent that, after the completion of the cleaning process, at least the windshield, preferably the sensors behind the driver of the automobile inside the windshield, can operate through the front and rear windows so that safe driving operations do not fail due to contamination of the front and / or rear windows.

[0377] Thus, by using a cleaning method that utilizes such systematic dependencies, cleaning resources can be advantageously saved, allowing for safe driving over longer distances under the same initial conditions as existing cleaning resources, and / or requiring fewer resources to cover the same distance, thus reducing the weight of the vehicle, and / or allowing the associated fluid tanks in the vehicle to be designed to be smaller for the cleaning fluid, thus saving installation space within the vehicle.

[0378] Conveniently, the input quantity represents at least one metered quantity, preferably a processing quantity and / or a control quantity.

[0379] This suggests that the input quantity represents the measured quantity.

[0380] If the input quantity is insufficient to indicate the measured quantity, the systematic dependence may also depend on the default value of the controlled quantity within the control system framework.

[0381] However, by using a metric, the accuracy of systematic dependence can be advantageously improved.

[0382] Preferably, such a measured quantity is a controlled quantity, and as a result, a systematic dependence between the output quantity and the controlled quantity of the cleaning process for the surface of the automobile being cleaned can be derived, and thus can later be used for the cleaning of the corresponding surface, in particular for the control and / or adjustment of the cleaning process for the surface being cleaned.

[0383] Furthermore, it is suggested that the input quantity represents the processing quantity, and as a result, a systematic relationship between the output quantity and the processing quantity, preferably air humidity and / or air temperature, as well as actual solar radiation and / or the temperature of the surface being cleaned, can be derived during the cleaning process of the surface of the car being cleaned, and thus can later be used for optimal cleaning of the corresponding surface.

[0384] The advantage of this approach is that it can improve the accuracy of the derived systematic dependencies while simultaneously taking into account numerous influencing factors from the domains of the controlled and / or processed variables.

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

[0386] The vehicle's speed may affect the cleaning process of the surface being cleaned, particularly the distribution of the cleaning fluid on the surface being cleaned, and / or the displacement of the cleaning fluid on the surface being cleaned due to relative airflow or / or evaporation of the cleaning fluid on the surface being cleaned, and may also affect the effective exposure time during which the cleaning fluid can dissolve contaminants.

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

[0388] In the preferred embodiment, the input quantities represent humidity, in particular the current humidity near the vehicle and / or temperature near the vehicle, in particular the current temperature near the vehicle and / or rainfall, in particular the current rainfall near the vehicle and / or snowfall, in particular the current snowfall near the vehicle and / or the coordinates of the vehicle.

[0389] Air humidity and temperature have been shown to be important factors influencing the success of the cleaning process for surfaces being cleaned.

[0390] Therefore, it is proposed here that a systematic dependence on these particularly relevant influencing factors for resource-efficient cleaning can be derived.

[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 and thus potentially saving cleaning fluid.

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

[0393] In particular, when selecting a cleaning process, especially one specified by a control variable setting, current environmental conditions can also be taken into consideration, and as a result, it is possible to select and execute a cleaning process that optimally conserves resources and / or is resource-efficient.

[0394] Furthermore, when statistically considering the expected temperature and / or expected humidity and / or expected rainfall and / or expected snowfall, the vehicle's current coordinates may also be taken into account. Therefore, based on the vehicle's current coordinates, the expected environmental conditions can be determined, and based on the expected environmental conditions and their systematic dependencies, the most resource-saving and / or resource-efficient cleaning process can be selected and implemented for cleaning the surfaces to be cleaned.

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

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

[0397] The vehicle type provides information about a number of different influencing factors that affect the cleaning process of some of the surfaces of the vehicle. These include, among other things, the location where the surface to be cleaned is installed and / or the size of the surface to be cleaned and / or the cleaning means capable of cleaning the surface to be cleaned and / or the expected degree and / or type of contamination and / or the exposure of the surface to be cleaned to airflow and / or the exposure of the surface to be cleaned to sunlight and / or the number of surfaces to be cleaned.

[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 to the location where each sensor is installed, with respect to the functional type in which each sensor is installed and / or each installed sensor type.

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

[0400] The advantage of this is that it allows for the systematic dependence of influencing factors associated with vehicle type, and can therefore be applied individually to each vehicle type in the future for resource-efficient cleaning.

[0401] Conveniently, the input quantity indicates the sensor's availability.

[0402] Sensor availability is the amount of information that can ultimately be provided about how badly the sensor is contaminated.

[0403] Of particular priority is availability, which can assume values ​​within an interval, where one interval limit for reach means the system can fully meet its requirements, and other interval limits for reach mean the system can no longer meet its requirements.

[0404] Even if the availability value is within the interval limit, the system can meet its requirements, but under more difficult conditions. In particular, the availability value reflects the degree of contamination of the vehicle's surfaces, preferably the surface, preferably the sensor surface, especially the surface of the optical sensor, and / or the degree of contamination of the windows seen by the driver of the vehicle, particularly the windshield and / or rear window, and / or the headlights and / or rear headlights.

[0405] The availability of sensors before the surface cleaning process, while controlling the same quantity, was found to affect the success of the cleaning process due to different levels of availability before the cleaning process.

[0406] The embodiments proposed herein can advantageously achieve the ability to take into account the availability of sensors as an influencing factor of the derived systematic dependence.

[0407] Preferably, the output volume indicates increased availability of the sensor and / or availability due to the cleaning process.

[0408] Aspects of the present invention proposed herein, in particular, enable the determination of cleaning success in a cleaning process by comparing the availability of sensors before and after the cleaning process, which is called increased 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] Therefore, the success of the cleaning process, preferably the increase in availability, can be advantageously quantified by the embodiments proposed herein.

[0411] This allows for the determination of control quantities based on a systematic dependence on sensor availability before the cleaning process, enabling resource-efficient cleaning of the surface being cleaned while simultaneously achieving the desired sensor availability after the cleaning process is complete. This facilitates advantageous future cleaning processes.

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

[0413] Furthermore, in order to achieve optimal cleaning from the standpoint of resource efficiency and / or sensor functionality and / or vehicle safety, it is conceivable that several cleaning processes specified by each controlled quantity can be executed in sequence.

[0414] It is particularly important to note that such a sequence of cleaning steps is already defined before the first cleaning process.

[0415] Furthermore, during the cleaning process of the surface cleaning sequence, the availability of each sensor is re-evaluated, and the control amount of the subsequent cleaning process is determined according to the availability of each sensor achieved during that time.

[0416] Overall, it can be advantageously achieved that the cleaning of one or more surfaces of an automobile can be performed autonomously, or at least partially autonomously.

[0417] In a favorable embodiment, the output amount indicates the resource requirements of the vehicle surface cleaning process, and preferably, the resource requirements are determined according to a control amount setpoint for the surface cleaning process.

[0418] This is advantageous when using systematic dependencies, particularly when selecting the optimal cleaning process, which is represented by the control variable setpoint of the current initial conditions that optimize surface cleaning, as it allows for taking into account the resource requirements of the cleaning process.

[0419] In the preferred embodiment, systematic dependencies are determined by regression analysis.

[0420] Here, it is suggested that a regression algorithm be used as an algorithm to indirectly derive systematic dependencies.

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

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

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

[0424] Preferably, the curve is continuous and differentiable, so that a control variable suitable for the requirements of the cleaning process can be determined by using the systematic dependence of the control variable within its control range, which would otherwise lead to discontinuities in the adjustment range or non-differentiable changes in the effects of variations in the control variable.

[0425] Evaluating the coefficient of determination from the determined data and the curve determined by the regression model provides an indicator of the accuracy of systematic dependence, assuming a sufficient number of datasets are available. It can favorably assess how meaningful the correlation between the input and output volumes of the washing 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 can be assumed that the data can be numerically supplemented and / or estimated with margins of existing data.

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

[0427] Here, it is suggested that the parameters of the systematic dependency are determined by an optimization procedure, in particular by a minimization procedure that minimizes the cumulative deviation of the empirical values ​​considered by the dataset from the systematic dependency. In this way, it is advantageous to determine the systematic dependency that can be derived in an optimal manner, in particular with the smallest cumulative deviation from the initial empirical values.

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

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

[0430] In particular, it has been proposed to use an algorithm that demonstrates the characteristics of the algorithm from machine learning classification. Thus, the algorithm can derive a systematic dependence between the input quantity and the output quantity.

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

[0432] Since the optimization procedure attempts to determine the optimal systematic dependencies even under multi-reference environments and various boundary conditions, the quality of the derived systematic dependencies can be improved by the embodiment proposed here.

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

[0434] Conveniently, systematic dependencies can be derived using existing database datasets.

[0435] The advantage of this approach is that it also allows for the deriving of systematic dependencies using data from existing databases. Therefore, it eliminates the need to first collect empirical data for specific vehicles, transfer it to the database, and then later transfer it to systematic dependencies. In this way, existing data and empirical data can be used to ensure the direct operation of the vehicle washing system based on systematic dependencies.

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

[0437] Conveniently, it can be achieved that the number of derivable systematic dependencies increases over time.

[0438] Furthermore, the large amount of empirical data known from the dataset is advantageous in that it allows for improved accuracy in systematic dependencies.

[0439] In a favorable embodiment, the new dataset replaces the dataset that deviates most from the derived systematic dependencies.

[0440] In particular, we must take into account the fact that empirical points are exchanged for the maximum Euclidean distance to systematic dependencies.

[0441] Conveniently, the systematic dependence becomes increasingly accurate over time, which can be represented by an increase in the coefficient of determination.

[0442] Furthermore, this has the advantage of allowing even weakly correlated systematic dependencies to be identified more appropriately over time.

[0443] It should be noted that the subject matter of the second embodiment can be advantageously combined with the subject matter of the first embodiment of the present invention, individually or cumulatively in any combination.

[0444] According to a first alternative example of a third aspect of the present invention, the task is a method for optimizing resource requirements for a cleaning process of an automobile surface, wherein a sensor is operably connected to the surface, and the method uses data from a dependency table for the system behavior of the automobile cleaning system, preferably the system behavior of the cleaning process of at least one surface, preferably resource-efficient cleaning, particularly preferably resource-saving cleaning, the dependency table representing a dataset showing inputs and outputs of the cleaning system, the output being dependent on the inputs, the system behavior of the system, preferably at least one controllable quantity of the cleaning process, and 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, the resource requirements of the cleaning process being dependent on the controllable quantity. - Steps include accessing data in dependency tables from a database and / or an electronic data processing and evaluation unit and / or an electronic control unit, - For each dataset in the dependency table, the step is to derive the difference between the availability of sensors for the end time of the cleaning process and the availability of sensors for the start time of the cleaning process, - For each dataset in the dependency table, the steps involve deriving the respective resource requirements and the ratio of their differences, - A step of selecting a control amount for the dataset that shows the maximum value of that ratio, - Preferably, the problem is solved by a method that includes the step of storing the controlled amount as a controlled amount 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-powered vehicles also needs to increase. Since these sensors primarily detect optical signals, their operation depends on the fact that the surface on which the optical signals are detected and to which the sensors are operably connected is sufficiently clean. Cleanliness is defined individually by each sensor, by the fact that it can receive and / or process each optical signal to be processed with at least primarily no interference.

[0446] Therefore, surfaces actively connected to sensors must be cleaned from time to time using cleaning methods. This also applies to most sensors that do not operate on optical signals, as their signal transmission can be impaired by contamination.

[0447] Therefore, it is necessary to clearly point out that this aspect of the present invention may affect not only optical sensors but all sensors in an automobile, at least sensors that are actively connected to the surface of the automobile.

[0448] Each cleaning process is linked to the resource requirements that the vehicle needs to provide.

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

[0450] The increasing number of vehicle assistance systems, and consequently the increasing number of sensors installed in vehicles, has led to a significant increase in the need to keep resources available.

[0451] The increase in sensors has also increased the control workload for the required number of cleaning processes. Therefore, semi-automatic or automatic cleaning of the relevant surfaces is desirable.

[0452] In particular, preferably, a procedure that can be advantageously automated to minimize resource consumption for cleaning surfaces effectively connected to the relevant sensors by performing resource-efficient, and especially resource-saving, individual cleaning processes is currently proposed, and as a result, resource consumption, and therefore the resource requirements of at least one cleaning means, can also be advantageously reduced.

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

[0454] The fact that the cleaning solution is applied to the surface to be cleaned in several stages should also be prioritized, preferably a relatively small amount in the first stage that can soften the contaminants, and a second amount in the second stage that can wash away the softened contaminants from the surface. The method of using the cleaning agent, in particular the amount of cleaning solution, directly affects the resource requirements of a single cleaning process.

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

[0456] Each cleaning process is affected by system behavior, which depends on at least one parameter, preferably an input quantity, more preferably a controlled quantity, and within the framework of an output quantity, more preferably availability, which can also be used to make statements about the results of the cleaning process, in particular, resource requirements used or planned to be used in a planning sense, and statements about the success of the cleaning.

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

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

[0459] In the context of input volume, the location of the surface to be cleaned can also be a priority. Therefore, differences in resource-efficient, and especially priority, resource-saving cleaning methods may stem from whether the surface to be cleaned is on the front, one side, the rear, the bottom, or the top of the vehicle.

[0460] Furthermore, the input quantity may also include the type of contamination, particularly whether it is dirt and / or dust or layered deposits such as mud or snow. It should also be noted that the vehicle's operating location and operating history, especially in combination with weather forecasts, can statistically predict the type of surface contamination. In other words, the range of input quantities may include weather conditions as well as operating location and / or operating history. These can be assessed using the vehicle's coordinates and, if necessary, other searchable data, particularly data searchable from data networks.

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

[0462] Washing processes with different definitions can be evaluated based on system behavior consisting of at least one input quantity and at least one output quantity.

[0463] If several defined cleaning process empires exist, a resource-efficient cleaning method that conserves particularly preferred resources can be selected, especially based on the existing empires for each contamination situation.

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

[0465] In this context, based on existing contamination conditions, particularly available resources, it may be particularly considered that a controlled amount resulting in optimal, resource-efficient cleaning, especially one that conserves preferred resources, is selected based on existing experience, and that the corresponding controlled amount is reproduced within the framework of the cleaning procedure. During regeneration, in particular, the controlled amount or controlled cleaning process may be considered.

[0466] Possible empirical data may preferably consist of empirical data derived from experience gained with automobiles, particularly specific automobiles, and / or experience gained with reference vehicles, and / or experience generated based on numerical models, and / or experience based on laboratory tests.

[0467] The experience considered for selecting a resource-efficient, and in particular, resource-saving, cleaning process is preferably related to the experience gained based on the surfaces to be cleaned, which are currently being cleaned or at least are scheduled to be evaluated.

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

[0469] Preferably, the dependency table can be expanded with new experience points.

[0470] The dependency table can be read preferentially.

[0471] Preferably, the dependency table can be stored in the database and / or in the electronic data processing and evaluation unit and / or the electronic control unit.

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

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

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

[0475] The optimal control variable setting corresponds to a defined empirical control value of the cleaning process that promises optimal cleaning of the surface resources to be cleaned according to the proposed procedure. If the corresponding optimal empirical value is selected, the optimal control variable setting can be obtained from the corresponding input variable.

[0476] The method proposed here is designed to optimize the cleaning of sensors and their interconnected surfaces, generating optimized control variable setpoints for each individual surface being cleaned.

[0477] Preferably, the procedure may be performed sequentially on several surfaces to be cleaned, which is advantageous in that the control variable setpoint can be defined sequentially for each surface of the automobile being cleaned.

[0478] this is, - A step of accessing data in a dependency table from a database and / or an electronic data processing and evaluation unit and / or an electronic control unit, wherein the collected expected values ​​can be favorably retrieved and processed in the next step. - A step of deriving the difference between the availability of sensors for the end time of the cleaning process and the availability of sensors for the start time of the cleaning process for each dataset in the dependency table, wherein the increase in availability for each stored experience value is favorably determined. - A step of deriving, for each dataset in the dependency table, the respective resource requirements and the ratio of the difference, wherein the efficiency of the cleaning process can be favorably defined by the ratio of expected resource requirements and expected cleaning successes, - A step of selecting a control amount for a dataset that shows the highest value of that ratio, wherein the most resource-efficient control amount may be selected based on existing empirical data. - Preferably, this can be achieved by the step of storing the controlled quantity as a controlled quantity setpoint in a database and / or an electronic data processing and evaluation unit and / or an electronic control unit, wherein a particular controlled quantity setpoint can be retrieved and advantageously applied within the framework of a downstream cleaning process.

[0479] According to a second alternative example of a third aspect of the present invention, the task is a method for optimizing resource requirements for a cleaning process of an automobile surface, wherein a sensor is operably connected to the surface, and the method uses systematic dependencies for the system behavior of the automobile cleaning system, preferably the system behavior of the cleaning process of at least one surface, preferably resource-efficient cleaning, particularly preferably resource-saving cleaning, preferably the systematic dependencies described in the second aspect of the present invention, wherein the systematic dependencies each represent a dataset indicating an input amount and an output amount of the cleaning system, wherein the output amount depends on the system behavior of the system, preferably at least one controllable amount of the cleaning process, and the systematic dependency of the cleaning system behavior 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, and the resource requirements of the cleaning process depend on the controllable amount. - Steps to access systematic dependencies from a database and / or an electronic data processing and evaluation unit and / or an electronic control unit, - Regarding the process of systematic dependence, the step is to derive the process of the difference between the availability of sensors for the end time of the cleaning process and the availability of sensors for the start time of the cleaning process, - Regarding the process of systematic dependence, the steps involve deriving the process of the difference and the process of the ratio of each resource requirement, - A step of selecting a control variable that belongs to a point in the process of that ratio that shows the highest value of that ratio, - Preferably, the problem is solved by a method that includes the step of storing the controlled amount as a controlled amount setpoint in a database and / or an electronic data processing and evaluation unit and / or an electronic control unit.

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

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

[0482] Alternatively, it is proposed here to map the system behavior of the cleaning process by systematic dependency, preferably by the systematic dependency described in the second aspect of the present invention.

[0483] Preferably, systematic dependencies represent datasets, each dataset representing the input and output quantities of the cleaning process. In particular, systematic dependencies are thought to be represented by a defined number of datasets and a defined distribution within a range of possible input quantities.

[0484] This advantageously allows systematically dependent datasets to be derived empirically so that, for the purpose of resource-efficient, and especially preferably resource-saving, washing, an optimal number of datasets and an optimized distribution of those datasets are obtained within the range of possible representations of the input quantities.

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

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

[0487] Particularly preferred is that the systematic dependence in the form of a curve over the full definition 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 the same size as the range of possible representations of the input quantity.

[0489] Furthermore, if systematic dependencies are defined by a curve, then we can say that the systematic dependencies represent a dataset, each representing at least one input quantity and at least one output quantity of the cleaning system. In particular, the individual datasets can be read from the curve, for example, by calculating the output quantities of a grid of input quantities.

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

[0491] Preferably, the systematic dependency has 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, thereby allowing for the determination of an increase in availability.

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

[0493] Furthermore, this alternative example can be advantageously achieved by determining better optimality for the control variable setpoint compared to the first alternative example of the third aspect of the present invention, thereby enabling even greater resource savings in comparison.

[0494] On the one hand, this process of determining systematic dependencies, particularly the subsequent determination according to the second aspect of the present invention, smooths out measurement inaccuracies and variations in system behavior, preferably by discrete empirical values, which can form a discrete description, generate a continuous and stable differentiable representation of systematic dependencies, and achieve higher accuracy in mapping system behavior.

[0495] Furthermore, while the optimization results may be optimal from a mathematical standpoint, they can be improved by selecting optimal control variable setpoints from areas where no empirical data is currently available.

[0496] Here, it is specifically proposed that the resource consumption for cleaning the selected surface is optimized based on the system behavior of the cleaning process, and as a result, better cleaning results can be advantageously achieved with less resource input, in particular, depending on the current initial conditions and using the systematic dependency described in the second aspect of the present invention.

[0497] The method proposed here is designed to optimize the cleaning of sensors and their corresponding surfaces, and to generate optimized control variable setpoints for each individual surface being cleaned.

[0498] Preferably, the procedure may be performed sequentially on several surfaces to be cleaned, which is advantageous in that the control variable setpoint can be defined sequentially for each surface of the automobile being cleaned.

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

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

[0501] Furthermore, it is understood that, preferably, discrete data points are not used in the calculation, but each mathematical operation is preferably performed across the entire curve over its entire course. This can preferably be done in defined steps, either analytically or by discretization.

[0502] Furthermore, the advantages of systematic dependency are leveraged, and it is understood that the dataset is not selected from documented empirical values ​​(which promises optimal resource-saving cleaning of the surface being cleaned), but rather represents an extremum of the systematic dependency process, or at least an extremum in the region where the control variables can be adapted. In particular, it is understood that by adjusting the control variables, the selected control variable setpoints can be placed at the edges of the range.

[0503] It is important to clearly point out that the systematic dependence considered here is not limited to its own dimension, but can have any number of dimensions for the input quantity and any number of dimensions for the output quantity.

[0504] Preferably, -The dependency table and / or systematic dependencies show the dependency on the processing volume, preferably the humidity and / or temperature near the vehicle, and / or the amount of rainfall and / or the coordinates of the vehicle. - Before selecting a control variable, the datasets and / or regions of systematic dependencies considered in the selection of a control variable from the dependency table are first limited to regions that deviate from each processing variable, preferably the current humidity and / or predicted humidity along the planned journey, and / or the current temperature and / or predicted temperature near the vehicle along the planned journey, and / or the current rainfall and / or predicted rainfall along the planned journey, and / or the current snowfall and / or predicted snowfall along the planned journey, and / or the coordinates and / or predicted coordinates of the vehicle along the planned journey, deviating by less than 20%, preferably less than 10%, and particularly preferably less than 5%.

[0505] Here, it is particularly suggested that the optimization of the control variable setpoint, in other words, minimizing the resource requirements for cleaning a single surface of the vehicle being cleaned, also take into account at least one processing volume.

[0506] Needless to say, the success of a cleaning process performed after a prolonged period of drizzle will differ from that of a cleaning process performed on a hot summer day with strong sunlight, defined by the same control amount, at least taking into account the same degree and type of prior contamination.

[0507] In other words, a resource-optimized cleaning process depends on at least one processing volume. Therefore, this can be taken into consideration when optimizing the optimal control volume setpoint.

[0508] The same can be achieved even if the empirical values ​​stored in the dependency table initially depend on the processing volume, preferably the relevant processing volume. The same applies when using systematic dependencies, particularly the later systematic dependencies of the second aspect of the present invention, which must also depend on the processing volume, preferably the relevant processing volume, so that the proposed approach can be taken into consideration in optimization.

[0509] For consideration during optimization, the number of empirical values ​​from the dependency table considered when selecting the optimal range of control variable setpoints and / or systematic dependencies is limited to a range that does not deviate by more than 20% from the currently prevailing workload or the workload expected according to the weather forecast at the time of the planned cleaning process, preferably less than 10% deviation, and particularly preferably no deviation of 5%.

[0510] Such restrictions ensure that the experience gained from a cleaning process conducted in sunlight is not transferred to a pending cleaning during snowfall. In other words, only the experience gained from a situation that is inherently relevant to the imminent cleaning situation is transferred to that situation.

[0511] In particular, it can advantageously improve the mapping accuracy between the selected control amount, which is expected to be optimal, and the results achieved during the cleaning process.

[0512] The processing volume is preferably understood as the weather along a pre-planned route. Determining the optimal control volume setpoint may also depend on whether the pre-planned route encounters weather conditions that require fewer resources for washing, particularly during rain and / or snowfall. In this way, by including expected weather conditions in the determination of the control volume setpoint, which may also include washing time, it may be advantageously achieved to favorably reduce the total resources required for washing. This is also suggested, among other things, by including the processing volume.

[0513] It should be noted that the above values ​​for the processing volume domain under consideration should not be understood as abrupt limits, but rather should be able to be exceeded or fallen below on an engineering scale without deviating from the described aspects of the present invention. Simply put, the values ​​are intended to represent the size of the processing volume regime under consideration proposed herein.

[0514] Conveniently, -The dependency table and / or systematic dependencies show the dependency on the availability of sensors at the start time of the cleaning process. - Particularly preferably by applying the method for determining the expected availability at a distance or operating time of an uncovered vehicle as described in a tenth aspect of the present invention, the regions of datasets and / or systematic dependencies considered in the selection of a control variable from a dependency table are first limited to regions that deviate by less than 20%, preferably less than 10%, and particularly preferably less than 5%, from the actual availability of the sensor and / or the expected availability of the sensor at a point on the planned route.

[0515] This suggests that optimizing the control variable setting value may involve utilizing sensors actively connected to the surface being cleaned.

[0516] A cleaning process defined by a controlled quantity, measured by increased availability, yields different cleaning successes for different initial surface contamination levels. Preferably, better cleaning results are obtained for less contaminated initial conditions than for more contaminated surfaces, and since cleaning is performed with the same controlled quantity in each case, equivalent resource requirements are needed 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, the examination of the initial contamination status of the surface to be cleaned, which is evaluated 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 first depend on the availability of sensors at the start time of the cleaning process. The same applies when using systematic dependencies, especially the later systematic dependencies of the second aspect of the present invention, which must also depend on the availability of sensors at the start time of the cleaning process, and this can therefore be considered in optimization.

[0519] When considering the availability of the sensor at the start of the cleaning process, the same approach that was already taken to consider the workload applies. Here again, the range of empirical values ​​and / or systematic dependencies considered for optimization from the dependency table is limited to a range that deviates by less than 20%, preferably less than 10%, and particularly preferably less than 5%, from the actual availability of the sensor.

[0520] Due to the resulting limitations, it may be advantageously achieved that only experiences from situations that are essentially consistent with the following cleaning situations are transferred to these situations.

[0521] In particular, it can advantageously improve the mapping accuracy between the selected control amount, which is expected to be optimal, and the results achieved during the cleaning process.

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

[0523] Therefore, the expected availability of sensors can be determined first, depending on the distance the vehicle covers to the cleaning process, or the operating time the vehicle covers to the cleaning process, and based on this, empirical constraints can be performed from the dependency table and / or the region of systematic dependencies.

[0524] This allows for a significant improvement in the planning accuracy of the cleaning process and also reduces resource requirements for cleaning surfaces connected to sensors.

[0525] It should be noted that the above values ​​relating to the area under consideration for the availability of sensors for the start time of the cleaning process should not be understood as abrupt limits, but rather should be able to be exceeded or fallen below on an engineering scale without deviating from the described aspects of the present invention. In short, the values ​​are intended to represent the size of the under consideration for the sensors for the start time of the cleaning process proposed herein.

[0526] Optionally, -The dependency table and / or systematic dependencies show the dependency on the availability of sensors at the start time of the cleaning process. - Before selecting a control variable, the datasets and / or regions of systematic dependencies considered in the selection of a control variable from the dependency table are first limited to regions where the availability of the sensor at the start of the cleaning process is less than or equal to the actual availability of the sensor. - The availability of sensors for the start time of the cleaning process associated with the selected control quantity is further stored along with the selected control quantity as the control quantity setpoint.

[0527] Conversely, it has been proposed to optimize the cleaning process in terms of resource efficiency, so that the conditions that must be met to initiate the cleaning process during optimization are determined, in particular, regarding the availability of sensors that can be achieved to initiate the cleaning process.

[0528] In other words, a pre-planned cleaning process must be initiated by a cleaning method, in particular by the cleaning method described in the first aspect of the present invention, provided that a predetermined availability of a sensor for the start time of the cleaning process is achieved by the process proposed herein.

[0529] The proposed method is made possible by the fact that the empirical values ​​stored in the dependency table first depend on the availability of the sensor for the start time of the cleaning process. The same applies when using systematic dependencies, particularly the later systematic dependencies of the second aspect of the invention, which must also depend on the availability of the sensor for the start time of the cleaning process, and this can therefore be considered in optimization.

[0530] Simultaneously, in addition to the control variable setpoint, the optimal availability of the sensor at startup is also selected or determined from the input quantity of the optimal point of the selected optimal empirical value or systematic dependency.

[0531] After the sensor, which is effectively connected to the surface to be cleaned, has already indicated its actual availability, this method allows for the selection of only the optimal cleaning process, which can be started immediately because the physically possible resource-optimized cleaning process is already at the limit of the sensor's current attainable availability, or to be started in the future at the defined availability of the sensor at the start time, as this must first be achieved by additional contamination of the surface to be cleaned.

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

[0533] Therefore, the procedure proposed here can further reduce the resource requirements of the cleaning process in a favorable manner, as it still selects the most resource-efficient cleaning process within the framework of what is possible.

[0534] In preferred embodiments, prior to the selection of a control variable, the datasets considered in the selection of the control variable from the dependency table, and / or the regions of systematic dependencies considered in the selection of the control variable, are first limited to regions where the expected increase in availability does not exceed by 20% of the availability that allows the vehicle to perform its current journey without unintended failure of the sensor function, and / or until an availability threshold is reached, preferably not exceeding by 10%, and particularly preferably not exceeding by 5%. In particular, preferably, by applying a method for determining the expected increase in availability according to a 14th aspect of the present invention, the sum of the current availability and the expected increase in availability is sufficient to achieve the distance or operating time covered by the vehicle so that the availability threshold is not exceeded.

[0535] Automobiles contaminate not only through active vehicular activity, particularly when they are used to cover distances, but also through passive vehicular activity, especially when they are parked in a spot and are exposed to the weather unprotected.

[0536] Regarding the use of resources for washing a vehicle, if the vehicle or a part of it is washed immediately before the end of the vehicle's planned operation, especially if it is likely to be before the next active operation in which the vehicle will be heavily soiled by the vehicle's passive operation, it may be resource-inefficient, and therefore, at least one washing process must be initiated at the start of the vehicle's next operation to restore the availability of the driver assistance systems.

[0537] In other words, to conserve both beneficial and overall resources for cleaning, it is possible to prevent possible over-cleaning before the active vehicle operation is complete. The procedure proposed here makes this possible.

[0538] Alternatively, there are provisions for modifications by further optional embodiments for occasionally moistening surfaces that are effectively connected only to unnecessary sensors with a spray of cleaning solution.

[0539] In this way, a surface not actively connected to one of the required sensors will not dry out, and thus advantageously, the adhesion of contaminants present on this surface can be advantageously achieved. In this way, another cleaning process aimed at direct cleaning of the surface can advantageously achieve that it does not need to remove a layer of covered dirt in a short time, but rather removes dirt that is already soaked or pre-soaked, thus working with fewer cleaning resources.

[0540] In other words, while no cleaning process specifically aimed at immediate surface cleaning is proposed here, a cleaning process is proposed that facilitates subsequent cleaning processes aimed at immediate surface cleaning, particularly those that improve usability with less resource consumption.

[0541] Therefore, by combining them, a more efficient cleaning process can be enabled.

[0542] For this purpose, the region of system behavior mapped by empirical values ​​from a dependency table or by systematic dependencies that can be selected by procedure is limited to a certain region, and as a result, the expected increase in availability does not exceed by 20% of the availability that allows the vehicle to perform its current journey without unintended failure of sensor functions, and / or not exceed by 10%, particularly preferably 5%, until an availability threshold is reached.

[0543] Preferably, the expected increase in the availability of each evaluated cleaning process can be determined by applying the method according to the 14th aspect of the present invention.

[0544] Therefore, the cleaning process selected by this method can be advantageously achieved in that, on the one hand, it does not result in significant over-cleaning of the surface in active connection with the sensor, and on the other hand, post-cleaning is not required to maintain the driver assistance system with a certain degree of safety before reaching the target.

[0545] In this way, resources for cleaning the surface to which the sensor is effectively connected can be saved.

[0546] It should be noted that the above values ​​in the area under consideration for the expected increase in sensor availability due to the cleaning process should not be understood as abrupt limits, but rather should be able to be exceeded or fallen below on an engineering scale without deviating from the described aspects of the present invention. Simply put, the values ​​are intended to represent the size of the expected increase in sensor availability under consideration due to the cleaning process proposed herein.

[0547] A method for optimizing resource requirements for a vehicle surface cleaning process, wherein, prior to the selection of a control quantity, the datasets and / or regions of systematic dependencies considered in the selection of a control quantity from a dependency table are first limited to regions sufficient to cover the distance or operating time to the next cleaning process, by applying a method for determining the expected distance or operating time of vehicles not yet covered when the availability threshold is reached, preferably by applying the method according to the 11th aspect of the present invention, particularly by applying a method for determining the expected increase in availability, preferably by applying the method according to the 14th aspect of the present invention, without falling below the availability threshold, and without exceeding by 20%, preferably by 10%, particularly preferably by 5%, the increase in availability required to cover the distance or operating time to the next cleaning process, without falling below the availability threshold. The method according to any one of claims 1 to 6, characterized in that the sum of current availability and the expected increase in availability is sufficient to achieve the distance or operating time covered by the vehicle so as not to exceed the availability threshold.

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

[0549] In particular, it is believed that the necessary cleaning methods can be minimized while maintaining the operation of the autonomous vehicle to the next gas station. Even if the minimally invasive cleaning process proposed here is not optimally resource-efficient in the sense of minimizing the use of cleaning agents and maximizing availability, the available resources are used optimally and efficiently, especially in the sense of achieving the operational goal of the vehicle operator who wants to reach the next intermediate destination by autonomous driving.

[0550] This can be achieved by first limiting the regions of datasets and / or systematic dependencies considered in the selection of a control variable from a dependency table, prior to the selection of a control variable, to regions where the expected increase in availability is sufficient to cover the distance or operating time to the next cleaning process without falling below the availability threshold, and particularly when the availability threshold is reached, by not exceeding by 20%, preferably 10%, and especially preferably 5%, the increase in availability required to cover the distance or operating time to the next cleaning process without falling below the availability threshold.

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

[0552] It should be noted that, prior to selecting a control variable setpoint, the expected distance or expected operating time of vehicles that are not yet covered when the availability threshold is reached is preferably determined by the procedure described in the 11th aspect of the present invention.

[0553] Furthermore, it should be particularly considered that, before the control amount setting value is selected, the expected increase in availability during the execution of the cleaning process is also determined by the procedure described in the 14th aspect of the present invention.

[0554] The advantage of this is that the vehicle can select a cleaning process that best achieves the minimum objective defined by the driver with the available resources.

[0555] It should be noted that the above values ​​in the area under consideration for the expected increase in sensor availability due to the cleaning process should not be understood as abrupt limits, but rather should be able to be exceeded or fallen below on an engineering scale without deviating from the described aspects of the present invention. Simply put, the values ​​are intended to represent the size of the expected increase in sensor availability under consideration due to the cleaning process proposed herein.

[0556] In the preferred embodiment, a first control variable and a second control variable are selected, and the respective first control variable setpoint and the respective second control variable setpoint define a first and a second cleaning process for a sequence of cleaning processes, the second cleaning process being executed after the 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 co-planned sequence.

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

[0559] It should also be considered that both control variable setpoints include conditions that trigger each cleaning process within the range of the cleaning method, particularly within the range of the cleaning method described in the first aspect of the present invention. In particular, the temporal distance, spatial distance, or achievement of defined trigger availability between individual cleaning processes should be considered.

[0560] The advantage is that it can save resources for cleaning when multiple cleaning processes are more resource-efficient than a single cleaning process. Surprisingly, it has been found that this can manifest in each input volume or in several constellations of each input volume.

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

[0562] So far, the cleaning process described has been limited to the extent that it is optimized for only one surface at a time.

[0563] Here, it is specifically proposed that this procedure be applied to a number of surfaces to be cleaned, either sequentially or in parallel.

[0564] Conveniently, the controlled variable is selected by a multi-criterion 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] This procedure is particularly suitable when different resources need to be optimized simultaneously and independently of each other.

[0567] Prioritizing the use of a dedicated cleaning lotion in addition to the cleaning solution is essential.

[0568] By using multi-criteria optimization methods, it is advantageous to be able to consider different resources equally favorably as resource-efficient in decisions based on the Pareto front under development.

[0569] According to a third aspect of the present invention, it is preferable to take into account other influencing variables, particularly the sensor device type, the temperature of the cleaning solution, the composition of the cleaning solution, the movement speed of the wiping element, the amount of cleaning solution, the orientation of the nozzle, etc., for resource optimization.

[0570] The temperature of the cleaning solution, the composition of the cleaning solution, the movement speed of the wiping element, the amount of cleaning solution, and / or the orientation of the nozzle can also be controlled quantities.

[0571] Needless to say, the advantages of systematic dependency, in particular the systematic dependency described in the second aspect of the present invention, also apply to the use of systematic dependency, in particular the use of systematic dependency proposed herein in accordance with the third aspect of the present invention.

[0572] It should be noted that the subject matter of the third embodiment can be advantageously combined with the subject matter of the preceding embodiments of the present 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 cleaning strategy for cleaning a surface of an automobile to be cleaned, wherein the surface to be cleaned is selected depending on the cleaning mode, and a sensor is operably connected to the surface to be cleaned. The sensor indicates actual usability, and the cleaning strategy indicates control variable setpoints that define the cleaning process of the surface being cleaned. - Preferably, the step of checking the actual cleaning mode, - A step of selecting at least one sensor required for the currently selected cleaning mode, - A step to check the actual availability of each selected sensor, - In particular, by applying a method for optimizing resource requirements for the cleaning process of automotive surfaces, preferably by applying the method according to a third aspect of the present invention, the steps include determining a resource-efficient, preferably resource-saving, control setpoint for cleaning each surface to be cleaned, which is operably connected to each selected sensor, - Preferably, the solution is provided by a method that involves operably connecting each selected sensor to store a control variable setpoint determined for resource-efficient, preferably resource-saving, cleaning of each surface to be cleaned, and more preferably storing the determined control variable setpoint 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 sensor availability falls below the availability threshold, this can result in limited sensor functionality, which could indirectly impair the functionality of at least one driver assistance system.

[0575] A third aspect of the present invention describes a procedure for optimizing a cleaning process with respect to the consumption of resources for a surface to be cleaned, which is operably 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 present invention does not take into consideration whether it is necessary to thoroughly clean a particular surface connected to the sensor, in other words, preferably whether it is necessary to increase the availability of the sensor by performing the cleaning process after the first aspect of the present invention for the current or planned use of the vehicle.

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

[0579] If you are cleaning a surface that contains sensors that are not currently needed, you will also need cleaning resources for this purpose.

[0580] A fourth aspect of the present invention utilizes this context to conserve cleaning resources and allows only the surfaces of the vehicle to be cleaned by the cleaning process, in particular by the cleaning method described in 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 a selected cleaning mode.

[0581] This allows for the availability of sensors that are not currently required to fall below the availability threshold, which in turn benefits from the possibility of saving cleaning resources falling below the availability threshold.

[0582] For this purpose, the cleaning strategy for cleaning the surfaces of the automobile to be cleaned is determined by the procedure proposed herein, and depending on the cleaning mode, when cleaning the surfaces of the entire automobile, how, i.e., by which cleaning process the surfaces are cleaned, is also determined, preferably by determining a corresponding control quantity, preferably using the procedure described in a third aspect of the present invention.

[0583] Depending on the cleaning mode, surfaces actively connected to sensors required for the vehicle's current use are selected and reserved for cleaning. In this context, the corresponding sensors are sometimes referred to as "selected sensors."

[0584] Furthermore, a control variable setpoint, preferably a resource-efficient, and especially preferably a resource-saving, control variable setpoint for cleaning, is determined for each selected sensor, preferably by applying a method for optimizing resource requirements for the cleaning process of the surface of the automobile, and especially preferably by applying the method according to a third aspect of the present invention.

[0585] Preferably, each control variable setpoint determined in this way for each selected sensor is stored in the cleaning strategy.

[0586] Needless to say, as soon as the cleaning mode changes, the cleaning strategy becomes invalid. As soon as the cleaning mode changes, a different cleaning strategy must be applied within the scope of the cleaning method, preferably within the scope of the cleaning method described in the first aspect of the present invention, or a new cleaning strategy must be determined according to the proposed procedure.

[0587] While it has been clearly stated that the cleaning mode may coincide with the operating mode, this is not always the case, so these terms are used separately here.

[0588] Preferably, the assignment of the selected sensor can be obtained from a relevant list, which can preferably be obtained from a database and / or an electronic evaluation and data processing unit and / or an electronic control unit.

[0589] Preferably, the cleaning strategy is suggested to override vehicle and / or driver commands as a last-minute remedy for cleaning the surface of selected sensors whose availability has reached and / or fallen below the availability threshold.

[0590] Furthermore, a clean strategy should prioritize being able to provide a solution that also includes cleaning of sensors other than the selected sensor, especially if one of the selected sensors is malfunctioning.

[0591] Preferably, before the control variable setpoint is determined, in particular when the availability threshold is reached, by applying a method for determining the expected distance or expected operating time of a vehicle that is not yet covered, preferably by applying the method according to the 11th aspect of the present invention, the expected availability is then determined as a function of the actual availability of the selected sensor until the availability threshold is reached, which requires cleaning of the surface to which the associated sensor is operably connected.

[0592] To date, the range of vehicles that can be cleaned with available cleaning resources has not been considered when determining cleaning strategies.

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

[0594] When operating a vehicle, it is possible to distinguish between the vehicle's operating modes, such as active vehicle operation characterized by the fact that the vehicle completes a driving distance, and passive vehicle operation in which a parked vehicle awaits the next active vehicle operation.

[0595] Automobiles become contaminated during both active and passive driving. For the sake of optimal cleaning of the automobile's surfaces, it is particularly suggested that the surfaces should not be over-cleaned, which is characterized by the fact that the automobile's surfaces are thoroughly cleaned immediately before reaching the purpose of active driving.

[0596] Instead, it is proposed here that the cleaning process may only pursue the objective of cleaning a surface to the extent that the availability obtained by the cleaning process is sufficient to achieve the objective of the active vehicle operation. For this purpose, the associated control variable setpoint can be determined, in particular, by the method according to 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, cleaning modes designed to maintain autonomous vehicle operation require more cleaning resources than cleaning modes designed to maintain at least one driver assistance system that is simply intended to assist the driver in driving the vehicle but does not allow autonomous vehicle operation.

[0598] As a result, here, In accordance with the steps prior to determining the control variable setpoint, first, the expected distance and / or expected operating time that the vehicle can still cover is determined as a function of the actual availability of the selected sensor, preferably by applying the method according to the 11th aspect until the expected availability reaches the respective threshold of availability. Before determining the control amount setpoint, the amount of available cleaning resources is checked, following further steps, particularly those prioritizing the corresponding sensors, especially level sensors, etc. Depending on the currently selected cleaning mode, the cleaning strategy is determined using the corresponding control quantity setting, and in connection with this, the resource requirements for cleaning are also determined. • Compare whether sufficient resources are available to meet the resource requirements of this cleaning strategy to reach the destination. Otherwise, it is preferable to provide the driver with a washing mode that allows the vehicle to reach its destination with available resources and / or to request that the corresponding resources be replenished, and the washing strategies provided are achieved in descending order according to resource requirements to determine the washing strategy, by using selectable washing modes, until a washing strategy is found that allows the vehicle to reach its destination even if one of the selected sensors does not reach an availability below the associated availability threshold.

[0599] In this way, it can be advantageously achieved that when the resources required by the selected washing mode are insufficient to reach the destination, the driver of the vehicle can decide whether to perform a service stop to replenish the resources needed to maintain the currently selected washing mode, or to disable the availability of the driver assistance system and, if necessary, arrive at the destination faster.

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

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

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

[0603] Here, it is proposed that the availability threshold for 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 for different cleaning modes.

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

[0606] This suggests that the cleaning mode can be read from the electronic control unit. This is advantageous because the cleaning mode can be defined in the electronic control unit and used to determine the range of cleaning methods, particularly the cleaning methods and cleaning strategies described in the first aspect of the present invention, and especially the methods described in the fourth aspect of the present invention.

[0607] Furthermore, in particular, automobile manufacturers can define cleaning modes in electronic control units, and as a result, it can be advantageously achieved that automobile manufacturers can also influence the cleaning of sensor surfaces, especially since these are safety-related aspects that may extend to the manufacturer's responsibility in the event of a malfunction.

[0608] The cleaning mode is optionally selected from the selection means.

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

[0610] The "selection means" should be understood as a device that allows for the selection of a cleaning mode. Here, preferably, a rotary switch, a selector slide, or an electronic input unit may be considered.

[0611] Here, the washing mode can be obtained from a selection means, in particular from a selection means within the direct influence of the vehicle driver, and as a result, the driver can influence the washing mode and, therefore, adjust the selection means, thereby indirectly influencing a washing strategy that suits their needs.

[0612] According to a preferred modification of the embodiment, the cleaning mode is configured to enable fully autonomous vehicle operation, and each surface that is operably connected to sensors related to fully autonomous vehicle operation is to be cleaned.

[0613] Here, we propose setting a washing mode for fully autonomous vehicle operation.

[0614] If a vehicle is 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 ensured.

[0615] In other words, this could lead to a situation where, at the very least, if such a vehicle falls below the availability threshold, it must cease all autonomous vehicle operation until the corresponding availability again exceeds 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 to cleaning methods, in particular to the cleaning method described in the first aspect of the present invention, and consequently to the method proposed herein for determining the cleaning strategy.

[0617] According to another preferred modification of the embodiment, the cleaning mode is set to enable comfortable vehicle operation for a designated driver of the vehicle, and each surface that is operably connected to sensors related to comfortable vehicle operation is to be cleaned.

[0618] The washing mode proposed here relates to the smooth operation of the automobile.

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

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

[0621] In other words, what is proposed here is to ensure that the cleaning system has access to all selected sensors associated with a cleaning mode set to enable comfortable vehicle operation with a suitable cleaning method, in particular the cleaning method described in the first aspect of the present invention.

[0622] According to another preferred modification of the embodiment, the cleaning mode is configured to enable vehicle operation that is as safe as possible for a designated driver of the vehicle, and each surface that is operably connected to sensors related to vehicle operation that is as safe as possible is to be cleaned.

[0623] Here, it is proposed that the availability of all sensors required for safety-related driver assistance systems be monitored, and the proposed method is configured to ensure that the availability of each sensor does not fall below the associated value of the associated availability threshold.

[0624] According to another preferred modification of the embodiment, the cleaning mode is configured such that the vehicle has the best possible range, and each surface that is operably connected to sensors related to the operation of the vehicle has the best possible range is to 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 operations not stipulated by law, and as a result, the associated sensors also become available below any relevant availability threshold.

[0627] In a convenient embodiment, the method is carried out for multiple surfaces to be cleaned, particularly for two, three, four, five or more surfaces to be cleaned.

[0628] Here, the method proposes establishing a cleaning strategy for multiple surfaces to be cleaned. This can be carried out in series or in parallel.

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

[0630] Optionally, the step of determining the control variable set value takes into account the measured quantity, preferably the processing quantity, particularly preferably the current humidity and / or predicted humidity along the planned journey, and / or the current temperature and / or predicted temperature near the vehicle along the planned journey, and / or the current rainfall and / or predicted rainfall along the planned journey, and / or the current snowfall and / or predicted snowfall along the planned journey.

[0631] Here, it is stipulated that the measured quantity should be taken into consideration when determining the cleaning strategy.

[0632] This preferably makes it possible to find a control variable setpoint based on current or expected weather conditions along a pre-planned route, thereby providing increased availability of individual selected sensors and a better relationship with the cleaning resources used than a control variable setpoint that does not take the measured quantity into account.

[0633] More specifically, what has already been done under a third aspect of the present invention, with necessary adjustments, applies hereto.

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

[0635] In particular, the type of vehicle provides information regarding the built-in cleaning system and the location and orientation of the surfaces intended for cleaning in this context. More specifically, this applies to any necessary adjustments already made under a second aspect of the present invention.

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

[0637] Preferably, it is proposed that selected sensors be cleaned as a last-minute remedy by a predetermined pre-cleaning process if their availability falls below a corresponding availability threshold.

[0638] It should be noted that the subject matter of the fourth embodiment can be advantageously combined with the subject matter of the preceding embodiments of the present invention, individually or cumulatively in any combination.

[0639] According to a fifth aspect of the present invention, a method for indirectly deriving the systematic dependence of the system behavior of system components of an automobile washing system, wherein the washing system is adapted to at least one surface of an automobile by a washing process, preferably adapted to resource-efficient washing, and particularly preferably adapted to resource-saving washing, and the output amount depends on the input amount by the system behavior of the system, - A step of determining an input quantity as a first parameter of the method using at least one sensor, - A step of determining the output amount as a second parameter of the method, preferably determined by at least one sensor, - A step of digitizing and recording the determined first and second parameters as necessary by a data processing system, wherein the data processing system represents an electronic data processing and evaluation system and a database, and the step of digitizing and recording. - The steps include storing the determined first and second parameters in the database as a dataset in a dependency table, in a related and ordered manner, - A step of deriving 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, and particularly preferably from at least 200 datasets of dependency tables, by an electronic data processing and evaluation system, wherein the electronic data processing and evaluation unit accesses the datasets of the dependency tables and determines and derives the systematic dependency from the datasets of the dependency tables by an algorithm. - Preferably, the task is solved by a method that includes the step of storing the derived systematic dependencies in a database and / or an electronic data processing and evaluation unit and / or an electronic control unit. Furthermore, as driver assistance systems that rely on information provided by sensors become increasingly important, cars are being equipped with more and more sensors.

[0640] Most of these sensors rely on the functionality of the surface to which they are actively connected in order to avoid excessive contamination.

[0641] In addition to the number of sensors, the number of locations where sensors can be installed on vehicles has also increased, and so has the number of surfaces that are cleaned by cleaning systems that are operationally connected to at least one of these sensors.

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

[0643] Just as the increasing automation of the entire vehicle through sensors necessitates increased automation of individual washing processes, the degree of automation in automotive washing systems is also increasing. After all, drivers of partially autonomous or autonomous vehicles cannot be expected to monitor the fouling status of relevant surfaces, which are interconnected with sensors for monitoring and / or adjusting driving behavior. Therefore, automation through driver assistance systems also requires the automation of automotive washing systems.

[0644] In addition to these complexities, the networking of systems is playing an increasingly important role.

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

[0646] As a result, the susceptibility to errors and the associated maintenance requirements for the system components of the cleaning system increased. As the complexity of individual system components increases, and the overall complexity of the cleaning system increases, it becomes more difficult to identify potential errors, and maintenance work on the cleaning system becomes increasingly time-consuming over time.

[0647] Since the different system components of a defined automobile washing system may also be supplied by different suppliers, identifying potential errors becomes even more difficult.

[0648] While expectations for the maintenance of such cleaning systems are increasing, recent studies have shown that these expectations cannot keep pace with the ever-growing complexity of the systems and the need for constantly accelerating system changes in the realm of automotive cleaning systems.

[0649] This paper proposes a method for deriving systematic dependencies for describing the system behavior of system components in an automobile washing system.

[0650] The system behavior of a system component is its response to a specification of that system component; the specification of a system component is described by an input quantity, and the response of the system component is described by an output quantity.

[0651] In other words, the output of a system component depends on the input, depending on the system's behavior.

[0652] It has been noted that the system components of a cleaning system can be understood as individual parts of the cleaning system, as well as as a single assembly and the cleaning system as a whole. In particular, each of the above variations has individual system behaviors that can be analyzed, so knowledge about the system behavior can be used to one's advantage later.

[0653] In particular, it is conceivable that the known system behavior of a system component, especially the known system behavior in the form of systematic dependencies derived here, can be used to compare with the observed system behavior of that 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 significant feature and / or malfunction and / or defect in the system component and / or cleaning system.

[0654] Thus, the systematic dependencies proposed here are derived empirically and provide a favorable way to compare the observed behavior of system components with the expected system behavior of the system components described by the systematic dependencies, and therefore to verify whether the system components and / or the cleaning system behave as expected.

[0655] Preferably, each system component exhibits individual systematic dependencies.

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

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

[0658] The method proposed here for deriving systematic dependencies from empirical data can be divided into two sections. In the first section, empirical data on the system behavior of system components is collected and stored in a dependency table. Input quantities that lead to the activity of system components and output quantities that represent the system components' response to the activity caused by the associated input quantities are stored in the dependency table in an ordered manner.

[0659] In the second section of the method, the empirical data collected in the dependency table is further processed into systematic dependencies by the algorithm.

[0660] It is important to clearly point out that empirical data can be collected within the framework of this procedure during the normal operation of the system components in a vehicle in operation. Furthermore, it is conceivable to collect corresponding empirical data during the operation of the system components in a laboratory or through numerical simulations using a suitable numerical model and store it in a dependency table.

[0661] Needless to say, the systematic dependence proposed here can only take into account the quantities 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 operating principles should be considered. Furthermore, the determination of quantities by numerical sensors should also be considered, which can provide further quantities that are not measured but can be numerically determined based on at least one measured quantity, or whose values ​​can be recorded in a numerical model.

[0662] While empirical data represents individual experiences for a single input quantity, the advantage of systematic dependency is that it can reproduce the system behavior of system components within a range of input quantities, particularly in a continuous and discrete manner.

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

[0664] Preferably, the input quantity is understood to be a quantity that is suitable, at least indirectly, to affect the system components. It is not necessary for the input quantity to be directly controllable. The input quantity may also arise from environmental conditions. Low temperatures, in particular, can lead to ice formation in the washing system and potentially alter the system behavior of the system components.

[0665] It is important to clearly point out that the input and output quantities described in the embodiments proposed here 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 is necessary to consider that all input quantities and all output quantities may be considered in this embodiment. This is because they 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 procedure proposed here is: - A step of determining an input quantity as a first parameter of a method, using at least one sensor, wherein the input quantity may have multiple dimensions and may be advantageously provided for further processing by the sensor, representing the behavior of at least one system component. - A step of determining an output quantity as a second parameter of the method, preferably determined by at least one sensor, which may have multiple dimensions, and wherein the output quantity, which describes the system behavior of the system components as a function of the input quantity determined by the above process step, can be advantageously provided by the sensor for further processing. - A step of digitizing and recording, as necessary, the first and second parameters determined by the data processing system, wherein the data processing system represents an electronic data processing and evaluation system and a database, and the input and output quantities are prepared and stored in a manner favorable for digital processing. -The step of storing the determined first and second parameters in a database as a dataset of dependency tables in a related and ordered manner, wherein in the dependency tables, the quantities of the previously determined method can be stored in a mutually favorable ordered manner such that the output quantities are assigned to the input quantities that describe the system behavior of the system components caused by the input quantities.

[0667] In short, the first section of the procedure facilitates the generation of a dependency table consisting of empirical data on the system behavior of the system components under consideration.

[0668] The second section of the procedure proposed here is: - A step of deriving 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, and 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, determines the systematic dependency from the datasets of the dependency tables by an algorithm, and derives the systematic dependency in a mathematically advantageous way by a suitable algorithm.

[0669] Next, the derived systematic dependencies can be advantageously stored so that they can be recalled for further processing, and in particular, the systematic dependencies are stored in non-volatile data memory. Preferably, the systematic dependencies may be 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 metered quantity, preferably a processing quantity and / or a control quantity.

[0671] Here, it is suggested that the input quantity represents the measured quantity, in particular, the processing quantity and / or the controlled quantity.

[0672] The 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 the processing quantity is at least indirectly dependent on the controlled quantity or cannot be influenced by conventional means, and only affects the system behavior of the system components.

[0673] The processing volume is preferably an amount present within or around the cleaning system that may be affected, at least indirectly, by the input volume.

[0674] Dependency tables and / or systematic dependencies can advantageously achieve the ability to have dependencies on directly measured input quantities, particularly processing quantities and / or control quantities, and to take into account the significant influence of system components on system behavior.

[0675] In the preferred embodiment, the output and / or input quantities represent the resource requirements, preferably power consumption, of the automotive surface cleaning process, and preferably the resource requirements are determined according to a control quantity setpoint for the surface cleaning process.

[0676] Power consumption can be determined relatively easily by combining it with the system components of the cleaning system.

[0677] The power consumption of system components can be used relatively quickly and easily to determine whether a change has occurred in the energy-consuming system components, because under normal conditions, the energy requirements of system components tend to fluctuate relatively little.

[0678] Therefore, power consumption can also be taken into consideration in describing the system behavior of system components, and it can be advantageously achieved that, in the context of diagnosing system components, particularly in the context of the diagnosis described in the sixth aspect of the present invention, the power consumption required by the system components can be advantageously used for comparison between expected system behavior and actual system behavior.

[0679] Optionally, the output and / or input quantities represent a processing volume, preferably flow rate and / or current and / or operating time and / or temperature and / or fill level signal and / or reaction time and / or sensing time and / or leak sensor signal and / or flow meter signal and / or several operation and / or spray pattern and / or thermal monitoring signal, preferably a signal based on a thermal monitoring reference area and / or debris sensor signal and / or check valve signal and / or drip sensor signal and / or distance sensor signal and / or force sensor signal.

[0680] In the context of output and / or input volumes, processing volume is also a valuable indicator for assessing the system behavior of system components in an automobile washing system.

[0681] In particular, in this context, it is necessary to consider whether the decision is easy to make or whether the processing volume is particularly meaningful.

[0682] Specifically, the level signal of the cleaning fluid reservoir can be examined. If a decrease in the cleaning fluid reservoir level signal is observed even though the cleaning system is not currently in active use, and in particular the cleaning fluid pump is not actively operating, this relatively simply means an unwanted leak in the cleaning system where the cleaning fluid is escaping.

[0683] Alternatively, the signal from the flow velocity sensor in the flow channel for the cleaning fluid can also be considered, in particular by determining the static pressure of the wall of the flow channel for the cleaning fluid. For example, if the cleaning fluid pump is operating actively and all possible valves in the cleaning system are set so that the cleaning fluid flows through the cleaning fluid flow channel, and the signal from the flow velocity sensor does not indicate this, then there is a deviation between the expected system behavior and the actual system behavior. This could be due to several causes, such as a leak or an empty cleaning fluid reservoir in the cleaning fluid system.

[0684] It is necessary to explicitly mention that causal correlations with system behavior occur regarding other processing volumes as well.

[0685] Therefore, the processing volume in the form of output volume can be included in dependency tables and / or systematic dependencies for the assessment of system behavior, and it can be advantageously achieved that the diagnosis of the cleaning system can be favorably improved in downstream steps.

[0686] In an optional embodiment, the input quantities represent humidity and / or temperature near the vehicle, and / or rainfall and / or snowfall.

[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, leading to localized flow blockages.

[0689] Furthermore, the interdependence and influence of each other's quantities can be taken into consideration.

[0690] By including the above quantities in the input, the accuracy of systematic dependency can be advantageously improved.

[0691] In a convenient embodiment, the input quantity indicates the vehicle type.

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

[0693] Therefore, in different constellations and / or arrangements of system components, different effects on the system behavior of the first system component may also be caused by the system behavior of the second system component. The vehicle type provides information about the constellation and / or arrangement of the system components of the washing system and thus represents a simple possibility for clearly recording the corresponding interactions.

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

[0695] Therefore, by including vehicle types, the systematic dependencies proposed here, and thus the mapping accuracy of the dependency tables, can be advantageously improved.

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

[0697] Here, if the input quantity is suggested to indicate availability, this preferably means availability before initiating the 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 that are actively connected to the system and whose surfaces are cleaned.

[0699] Sensor availability is determined by measuring the degree of contamination on the surface to which the sensor is connected.

[0700] Studies have shown that different sensor availability at the start of a cleaning process can affect the cleaning outcome. In other words, the potential for increased availability can differ in cleaning processes performed in the same manner.

[0701] In particular, it is suggested that the input quantity indicates the parameters of the cleaning process, and / or the output quantity indicates an increase in availability.

[0702] This makes it possible to evaluate the system behavior of the cleaning system and / or its system components based on the cleaning results, particularly depending on the parameters of the cleaning process.

[0703] This makes it advantageous to be able to evaluate the system behavior of the washing system using sensors that have already been installed, particularly sensors for supporting the driver assistance system.

[0704] In this way, it can be advantageously achieved that there is no need to add additional sensors necessary solely for evaluating the cleaning system in order to evaluate the system behavior of the system components of the cleaning system.

[0705] It is important to clearly state that this aspect is particularly related to the second, third, ninth, and tenth aspects of the present invention. Needless to say, this aspect is also related to and interrelated with other aspects of the present invention.

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

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

[0708] Preferably, weather conditions that depend on the vehicle's coordinates 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, as well as / or solar radiation, and / or precipitation and / or snowfall.

[0709] According to a relatively simple procedure, weather conditions at the vehicle's coordinates correlate with the current latitude on the planet, which can be determined by the vehicle's coordinates.

[0710] Therefore, based on the vehicle's coordinates and its correlation with weather conditions, relevant influencing variables of the system components of the washing system to its system behavior can be taken into account, and the accuracy of the dependency table and / or systematic dependencies can be advantageously improved for the system behavior, which can be advantageously achieved.

[0711] A more precise approach suggests that the vehicle may also use local information regarding the current and / or predicted weather at its coordinates. Thus, when determining dependency tables and / or systematic dependencies, influencing variables that are effectively related to the system behavior of the system components of the washing system and can be determined directly or indirectly by the vehicle's coordinates can be used to improve the accuracy of mapping the predicted system behavior.

[0712] Needless to say, this aspect is related to and interrelated with other aspects of the present invention.

[0713] In the preferred embodiment, the output amount indicates increased availability due to the sensor and / or the cleaning process.

[0714] Here, the output volume is suggested to indicate increased availability due to the availability of the sensor and / or the use of the cleaning system.

[0715] If the output quantity is indicated to indicate availability, this preferably means availability after the completion of the cleaning process using the cleaning system.

[0716] In this way, it is possible to favorably determine how the system behavior of the system components of the cleaning system depends on the success of the cleaning process performed by the cleaning system. 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 a favorable embodiment, systematic dependencies are determined by regression analysis.

[0718] Here, it is suggested that a regression algorithm be used as an algorithm to indirectly derive systematic dependencies.

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

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

[0721] The advantage of this is that the systematic dependency can be represented by a curve as a function of at least one input quantity of the system behavior of the system components, and in particular, this curve has no gaps, and as a result a clear assignment between the input and output quantities, in particular a continuous and differentiable dependency between the input and output quantities due to the system behavior of the system components, can be achieved, and as a result the systematic dependency can be ideally fitted to any mathematical method for which the same is to be used.

[0722] Evaluating the coefficient of determination from the determined data and the curve determined by the regression model provides an indicator of the accuracy of systematic dependence, assuming a sufficient number of datasets are available. It can favorably assess 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 can be assumed that the data can be numerically supplemented and / or estimated using the margins of existing data.

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

[0724] Here, it is suggested that the parameters of the systematic dependency are determined by an optimization procedure, particularly a minimization procedure, which minimizes the cumulative deviation of the empirical values ​​examined by the dataset from the systematic dependency. In this way, it is advantageously possible to determine the systematic dependency that can be derived in an optimal manner, in particular with the smallest cumulative deviation from the initial empirical values.

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

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

[0727] In particular, it has been proposed to use an algorithm that demonstrates the characteristics of the algorithm from machine learning classification. Thus, the algorithm can derive a systematic dependence between the input quantity and the difference in availability due to contamination.

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

[0729] Since the optimization procedure attempts to determine the optimal systematic dependencies even under multi-reference environments and various boundary conditions, the quality of the derived systematic dependencies can be improved by the embodiment proposed here.

[0730] Thus, it is conceivable that optimization can be performed under multiple equal objectives and / or boundary conditions (multi-criterion optimization). In particular, a classification of algorithms capable of determining Pareto optimality and / or Pareto fronts is considered. Specifically, a classification of algorithms in areas such as simplex methods and / or evolutionary strategies and / or evolutionary optimization algorithms is proposed here in order to derive systematic dependencies.

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

[0732] The advantage of this approach is that systematic dependencies can also be derived using data from existing databases. Therefore, it is possible to achieve the elimination of the need to first collect empirical data for specific vehicles, transfer it to the database, and then transfer it to systematic dependencies later. In this way, using existing data and empirical data, systematic dependencies to the contamination process can be derived without first needing to collect empirical data representing the systematic dependencies of the contamination process.

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

[0734] Conveniently, it can be achieved that the number of derivable systematic dependencies increases over time.

[0735] Furthermore, the large amount of empirical data known from the dataset can be advantageously achieved by improving the accuracy of systematic dependencies.

[0736] Conveniently, the new dataset replaces the dataset of dependency tables that deviate the most from the derived systematic dependencies.

[0737] In particular, we must take into account the fact that empirical points are exchanged for the maximum Euclidean distance to systematic dependencies.

[0738] Conveniently, the systematic dependence becomes increasingly accurate over time, which can be represented by an increase in the coefficient of determination.

[0739] Furthermore, this has the advantage of allowing even weakly correlated systematic dependencies to be identified more appropriately over time.

[0740] It has also been suggested that the output and / or input volumes indicate the frequency and / or speed of the cleaning fluid pump.

[0741] This allows for advantageous improvement in the dependency table and / or systematic dependency accuracy, since it has been found that the frequency and / or speed of the cleaning fluid pump can affect the system behavior of the system components.

[0742] Furthermore, it is suggested that the output and / or input volumes indicate the nozzle dimensions and / or the type and / or quality of the cleaning fluid.

[0743] This allows for advantageous improvement in 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] The output and / or input quantities suggest that they indicate the pump diaphragm material and / or hose material.

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

[0746] It should be noted that the subject matter of the fifth embodiment can be advantageously combined with the subject matter of the preceding embodiments of the present invention, individually or cumulatively in any combination.

[0747] According to a first alternative example of a sixth aspect of the present invention, the task is a method for diagnosing the system behavior of system components of an automobile washing system, The output amount depends on the input amount, depending on the system behavior of the system components of the cleaning system. If the actual output exceeds the upper threshold and / or falls below the lower threshold, it indicates that the actual system behavior deviates from the expected system behavior. - Preferably, the steps include determining the input amount, - The step of determining the actual output amount, - Preferably, the steps include searching for an upper threshold amount and / or a lower threshold amount according to the input amount, - A step of comparing the actual output amount with the upper threshold amount and / or lower threshold amount, - Preferably, if the actual output amount exceeds the upper threshold, calculate the deviation between the actual output amount and the upper threshold, and / or if the actual output amount falls below the lower threshold, calculate the deviation between the actual output amount and the lower threshold, - Preferably, this is resolved by a method that includes the step of 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] This paper proposes procedures for monitoring and diagnosing the system components of an automobile washing system.

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

[0750] At the same time, the number of different combinations of system components available on the market to form cleaning systems is also increasing, and typically, different system components are supplied by different suppliers.

[0751] As a result, the complexity of the cleaning system is increasing, as is the need for maintenance to keep the system running without failure.

[0752] This highlights the need for a systematic, at least partially automated, or automatable approach to the early detection of potential errors in the system components of cleaning systems.

[0753] Unexpectedly, it was discovered that electrical and mechanical anomalies in the system behavior of the system components of the cleaning system were often associated with each other. This finding can be used to evaluate system components based on mechatronics concepts.

[0754] If the evaluation of cleaning systems currently relies primarily on visual inspection, then evaluating system components based on mechatronics concepts could be advantageous because existing, or with minimal effort, additional electrical signals of the system components of the cleaning system can also be used to evaluate possible mechanical failures. Previously, this was only possible through 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. Therefore, by monitoring electrical quantities, different problems related to the cleaning system can be detected.

[0756] In particular, it is unexpectedly determined that the time process of the inrush current of the cleaning fluid pump in the presence of mechanical interruption of the cleaning fluid flow channel may show a characteristic difference from the time process in the presence of error-free normal switching of the cleaning fluid pump, especially in the case of mechanical interruption of the flow channel up to the specified outlet of the cleaning fluid at the nozzle. It may be particularly advantageous to distinguish between partial and complete interruption of the cleaning fluid flow channel.

[0757] Under normal circumstances, the temporal process of the inrush current when the cleaning fluid pump is switched on results in only a short overshoot step response. However, in the presence of a mechanical interlock, the step response can exhibit a more pronounced temporal process, particularly as the current reaches the expected value for continuous operation of the cleaning fluid pump with only measurable decay.

[0758] The procedure proposed herein can preferably be performed autonomously, and therefore preferably within the framework of a self-diagnosis of the cleaning system, and can report if abnormal system behavior of the system components of the cleaning system is diagnosed.

[0759] In particular, it should be considered that the diagnostic procedure proposed herein may preferably be activated by the vehicle's electronic control unit and / or cleaning system without intervention from the vehicle's driver. Furthermore, it should be considered that the diagnostic procedure proposed herein may preferably be activated manually by the vehicle's driver.

[0760] The diagnostic method proposed here compares the expected behavior of a system component of the cleaning system with the system behavior determined during monitoring of that component, based on its actual output. This comparison is performed using at least one value of the output.

[0761] The expected system behavior is based on empirical data of particularly evaluated system components. This empirical data may be based on normal vehicle operation, laboratory observations, or the results of numerical models.

[0762] By comparison, if the monitored system behavior of a system component yields results corresponding to the expected system behavior, it can be concluded that the system component is free from defects and / or failures, and / or has not been damaged by external influences acting on it.

[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 signal is within or performs within the range defined by the upper and lower threshold quantities, then the system behavior of the system components under consideration is not unexpected, and this range may also be open if only the upper or lower threshold quantity is specified.

[0764] Therefore, the method proposed herein requires a list having at least one upper threshold or at least one lower threshold for the output quantity. Each threshold is a separate value for each output quantity and may preferably also depend on the input quantity and the system components under consideration.

[0765] Preferably, the upper and / or lower threshold amounts depend on the processing volume.

[0766] If the monitored output exceeds an individually associated upper threshold, or if the monitored output falls below an individually associated lower threshold, then, if necessary, there is a deviation that may be characterized by another output.

[0767] Furthermore, particularly after the seventh and / or eighth aspects of the present invention, it is believed that solution strategies are known from experience that certain deviations can be modified.

[0768] When the characterization of system behavior that deviates from the expected output of the monitored output, and / or deviates from the expected output, results in known behavioral patterns, this can be associated with recommendations for action. Such recommendations for action are also based on experience, and these experiences can largely be systematized.

[0769] With regard to systematized 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. Preferably, this conclusion is valid, or at least transferable, for multiple different system components and multiple different cleaning systems.

[0770] For example, it is necessary to consider here that increased power consumption of the cleaning fluid pump, and therefore deviations in system behavior, could lead to the conclusion that errors exist in the cleaning system. Of particular concern here is the aging of the cleaning fluid pump, specifically the need to use higher energy requirements for the controlled pump pressure of the cleaning fluid pump.

[0771] Alternatively, in this case, there may be a blockage in the flow channel downstream of the cleaning fluid pump, which is causing an increase in back pressure, affecting the system behavior of the cleaning fluid pump. Depending on the situation, a distinction can be made to identify the cause of the diagnosed deviation by comparing different output levels. This requires empirical knowledge, especially if available in the list.

[0772] This also indicates that deviations between the expected output and the actual output of a system component's system behavior do not necessarily have to be caused by the system component being monitored itself.

[0773] If there is an obstruction before the pump, a possible solution strategy to correct the deviation with the mounted means is to increase the pump pressure in the target manner, thereby releasing the obstruction and flushing it out of the cleaning system. In particular, the selection of the 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 selected and implemented solution strategy is successful, the system behavior of the system components will occur, which corresponds to the expected system behavior.

[0776] It is important to clearly state that the diagnostic methods described here are applicable to any system component. Given a sufficient number of sensors or measuring devices, enough experience 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 by the onboard devices. Deviations in system behavior that cannot be corrected by onboard resources can also be detected early and corrected within the scope of normal or early maintenance, thus advantageously preventing the escalation of damage that might otherwise occur.

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

[0778] Furthermore, it is suggested that the diagnostic signals may be optionally stored or passed to the vehicle's electronic control unit.

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

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

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

[0782] In the case of the actual output quantity of a vector, the deviation calculation is performed individually for each component, that is, for each dimension.

[0783] Deviations may occur in some or all components of the actual output quantity, and simultaneously, a component deviation is possible because the corresponding component of the lower threshold quantity is undershooting, and a component deviation is possible because the corresponding component of the upper threshold quantity is overshooting.

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

[0785] This diagnostic signal may include the detection of no deviation from the expected system behavior in the actual system behavior.

[0786] Furthermore, the diagnostic signal may include the detection of a deviation in actual system behavior from expected system behavior, and the type and representation of the deviation may also be stored in the diagnostic signal.

[0787] Preferably, the diagnostic signal suggests a deviation.

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

[0789] It should be noted that the above values ​​relating to the amount of value over time should not be understood as abrupt limits, but rather should be able to be exceeded or fallen below on an engineering scale without deviating from the described aspects of the present invention. Simply put, these values ​​are intended to represent the magnitude of the amount of value over the proposed time range.

[0790] In particular, it should be noted that diagnostic signals often exhibit multiple temporal curves of output quantities over time, especially along with input and / or processing quantities.

[0791] This makes it advantageous to observe and evaluate changes in the system behavior of system components, particularly in relation to the possible aging degradation and / or remaining lifespan of system components, depending on the input volume and / or processing volume.

[0792] Therefore, it is possible to advantageously enable at least partially automated error detection regarding the system behavior of system components of a washing system for automobiles, and to detect potential errors autonomously and early.

[0793] This makes it possible to identify possible causes of follow-up errors early on, thereby advantageously limiting the expansion of errors.

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

[0795] According to a second alternative example of a sixth aspect of the present invention, the task is a method for diagnosing a deviation between the actual system behavior and the expected system behavior of a system component of an automobile washing system, The output amount depends on the input amount, depending on the system behavior of the system components of the cleaning system. The actual system behavior in response to the input is represented by the actual output, and the expected system behavior in response to the input is represented by the expected output. The expected system behavior is represented by a dependency table or systematic dependencies, preferably at least one dataset of systematic dependencies derived by the method according to the fifth aspect of the present invention. - Preferably, the steps include determining the input amount, - The step of determining the actual output amount, - A step of determining the expected output amount, • Select the dataset that best matches the input quantity from the dependency table, read the output quantity stored in the selected dataset, and take that as the expected output quantity. • Select the two datasets that best match the input quantities from the dependency table, and then use linear interpolation based on the two selected datasets to determine the expected output quantities, or The steps involve determining the expected output quantity by inserting the input quantity into a systematic dependency, and calculating the expected output quantity. - A step of calculating the deviation between the actual output and the expected output, - Preferably, the problem is solved by a method that includes the step of storing a diagnostic signal when the deviation is greater than 10% of the expected output, preferably 5% greater than the expected output, and particularly preferably 2% greater than the expected output.

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

[0797] The unrestricted description of the first alternative example of the sixth aspect of the present invention described above is also valid for the second alternative example of the sixth aspect, and vice versa, and it should be clearly noted that the actual output is compared differently to the expected output, rather than to a lower threshold and / or upper threshold.

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

[0799] The diagnostic method proposed here compares the expected system behavior of the system components of the cleaning system with the expected system behavior. This comparison is performed based on at least one value of the actual output compared with the corresponding value of the expected output.

[0800] The expected system behavior is based, in particular, on empirical data of system components diagnosed using the proposed method. These empirical data may be based on the normal operation of an automobile or observations in a laboratory setting, or on numerical models suitable for mapping the normal system behavior of a cleaning system.

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

[0802] Preferably, the expected system behavior, and therefore the expected output, depends on the processing load.

[0803] According to this second alternative example of the sixth aspect of the present invention, three further modifications are proposed in each case, thereby enabling the determination of the expected output amount based on empirical values.

[0804] According to the first and second modifications, 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 present invention.

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

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

[0807] Regarding the evaluation of the dependency table, the first and second variations for determining the expected output are different from each other.

[0808] According to the first variation for selecting the expected output, it is proposed to select the empirical value of the best-fitting dataset, defined in particular by the shortest Euclidean distance between the input and / or processing amounts between the datasets stored in the dependency table and the actual input and / or processing amounts, by comparing the actual input and / or processing amounts from the dependency table with the input and / or processing amounts of each dataset.

[0809] According to the second variation for selecting the expected output, it is proposed to select two optimal adjacent empires from the dependency table in the form of two datasets, following the description of the first variation, and to interpolate between these two empires according to the actual input and / or actual processing amounts.

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

[0811] The systematic dependency allows us to continuously describe the expected system behavior as a function of the actual input and / or processing volume, and as a result, no selection or interpolation between empirical values ​​is required, as described above for the second variation.

[0812] Similar to the dependency tables in Variations 1 and 2, systematic dependencies are valid for only one system component, and as a result, in order to examine a system component that deviates, one can or should select a deviating systematic dependency or a deviating dependency table.

[0813] It is understood that input quantities, actual output quantities, expected output quantities, and / or deviations can be scalar or vector quantities. The above quantities are scalars when only a single parameter describing the system behavior of the system components is evaluated, without considering the temporal process of this parameter. In all other cases, particularly when considering several parameters of a cleaning system and / or considering at least one temporal process of the parameter, the above variables are understood as vector quantities.

[0814] Therefore, the calculation of the deviation between the actual output and the expected output also depends on whether the output is a scalar or a vector. If it is not yet a vector, it is preferably suggested to adjust the expected output to the dimensional characteristics of the actual output, and in either case, it must be ensured that the expected output and the actual output each have corresponding quantities.

[0815] In the case of the actual output quantity of a vector, the deviation calculation is performed individually for each component, that is, for each dimension.

[0816] If a deviation is determined with respect to at least one component between the expected output and the actual output, further investigation of this deviation is proposed.

[0817] As discussed earlier, when determining the measured values, measurement errors and expected variations in each signal can occur even under normal operation.

[0818] Therefore, not all nominal deviations between expected and actual output levels result in deviations of the actual system behavior of system components from the expected system behavior.

[0819] To quantify the deviation of the actual system behavior of system components from the expected system behavior, it is suggested here to use the relative deviation between the actual output and the expected output.

[0820] This relative comparison is performed for each component. It should also be considered that the threshold value beyond which a system component's deviation from its actual system behavior exceeds the expected system behavior may be specified for components of different sizes, depending on the available empirical data.

[0821] In particular, a deviation limit of 10%, preferably 5%, and especially 2% has been proposed.

[0822] It should be noted that the above values ​​regarding the deviation limits should not be understood as abrupt limits, but rather should be able to be exceeded or fallen below the engineering scale without deviating from the described aspects of the invention. Simply put, the values ​​are intended to indicate the magnitude of the deviation limits proposed herein.

[0823] Preferably, the deviation limit is 15%. More preferably, the deviation limit is 20%. Even more preferably, the deviation limit is 25%. Even more preferably, the deviation limit is 30%.

[0824] If the ratio of the actual output to the expected output exceeds a limit in at least one component, the actual system behavior will differ from the expected system behavior of the system component under consideration.

[0825] Otherwise, the actual system behavior corresponds to the expected system behavior, and it can be concluded that the system components under consideration of the cleaning system are free from defects and / or malfunctions, and / or that the system components are not damaged by external influences acting on them.

[0826] In particular, deviations between the expected output and the actual output of a system component's system behavior do not need to be caused by the system component being monitored itself.

[0827] Rather, it could be part of a further diagnosis indicating which system components of the cleaning system might exhibit, or could exhibit, errors depending on the determined deviation.

[0828] It should be noted that the diagnostic methods described here can be used for any system component. Many deviations that occur can be corrected by the onboard devices if a sufficient number of sensors or measuring devices, sufficient experience with the expected system behavior of one or more system components, and a list of likely successful resolution strategies are available. Deviations in system behavior that cannot be corrected by onboard resources can also be detected early and corrected within the scope of normal or early maintenance, thus advantageously preventing the escalation of damage that might otherwise occur.

[0829] Furthermore, it is suggested that the diagnostic signals may be optionally stored or passed to the vehicle's electronic control unit.

[0830] This diagnostic signal may include the detection of no deviation from the expected system behavior in the actual system behavior.

[0831] Furthermore, the diagnostic signal may include the detection of a deviation in actual system behavior from expected system behavior, and the type and representation of the deviation may also be stored in the diagnostic signal.

[0832] Preferably, the diagnostic signal indicates the output amount and / or the process of the output amount over time, and the process of the output amount over time indicates at least two time points, preferably at least 10 time points, and particularly preferably at least 20 time points.

[0833] It should be noted that the above values ​​relating to the amount of value over time should not be understood as abrupt limits, but rather should be able to be exceeded or fallen below on an engineering scale without deviating from the described aspects of the present invention. Simply put, the values ​​are intended to represent the magnitude of the amount of value over the proposed time range.

[0834] In particular, it should be noted that diagnostic signals often exhibit multiple temporal curves of output quantities over time, especially along with input and / or processing quantities.

[0835] This makes it advantageous to observe and evaluate changes in the system behavior of system components, particularly with respect to possible aging and / or remaining lifespan of system components depending on the input and / or processing load.

[0836] Once the comparison between the actual output and the expected output is complete, the diagnostic process can be stopped or continued with the same system components or different system components.

[0837] Therefore, it is possible to advantageously enable at least partially automated error detection regarding the system behavior of system components of a washing system for automobiles, and to detect potential errors autonomously and early.

[0838] This makes it possible to detect possible causes of follow-up errors early on, and to advantageously limit the propagation of errors.

[0839] In this way, trained professionals can advantageously extend the intervals at which optical inspections should be performed, and thus reduce the overall maintenance costs of the cleaning system.

[0840] In preferred embodiments, the deviation represents a temporal process, preferably the temporal process represents at least two points in time, preferably at least ten points in time, and particularly preferably at least twenty points in time.

[0841] Here, it is specifically proposed to consider the aforementioned deviations as deviations that occur over time.

[0842] Preferably, the process of deviation over time can also be stored in the database.

[0843] Preferably, the temporal process is stored in a diagnostic signal.

[0844] In particular, it is suggested that the time process of deviation begins immediately before the planned change in the input quantity. Preferably, the time process of deviation ends after the next planned change in time.

[0845] In particular, it should be noted that the output volume is diagnosed over a period that at least slightly exceeds the two planned changes in the input volumes on both sides. Specifically, the diagnosis of the output volume over time begins before switching the cleaning fluid pump on and ends after switching the cleaning fluid pump off.

[0846] Based on the time process of the output quantity, it is possible to evaluate systematic errors of system components, particularly systematic errors that indicate the dependence of system components on the decay of system behavior.

[0847] Furthermore, it is advantageous to consider recording specific output quantities after each system component is started, rather than having the temporal process run continuously.

[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 intervals following the switch-on process, and the individual values ​​recorded in each case are recorded and diagnosed as a time series.

[0849] In this way, the performance degradation of the cleaning fluid pump over its lifespan can be favorably evaluated, and a warning can be provided when the cleaning fluid pump is expected to need to be replaced.

[0850] It should be noted that the above values ​​relating to the quantity of data points in time should not be understood as abrupt limits, but rather should be able to be exceeded or fallen below on an engineering scale without deviating from the described aspects of the present invention. Simply put, the values ​​are intended to represent the size of the quantity of data points within the proposed time range.

[0851] The system behavior of system components can be favorably evaluated based on the temporal process of the output quantity, and the possibility of further analysis supporting the transmission behavior of system components in relation to this, in particular, the diversity of such analytical possibilities, is provided.

[0852] In particular, the temporal process of deviation can be evaluated as a function of input and / or output quantities, and data with the same or very similar input and / or processing quantities are compared to one another.

[0853] Preferably, the temporal process represents at least 30 points in time. Preferably, the temporal process represents at least 40 points in time. Preferably, the temporal process represents at least 50 points in time.

[0854] Preferably, the results of the analysis of the temporal process of the deviation are stored together with and / or in the diagnostic signal.

[0855] Preferably, the temporal process of deviation is investigated in terms of the step response.

[0856] Here, it is proposed to evaluate the temporal process of the output quantity with respect to the step response, particularly the step response as a response to changes in the input quantity.

[0857] In particular, it is possible to examine the value of the output quantity or the change in the output quantity in relation to the change in the input quantity.

[0858] Furthermore, it has been proposed that the temporal process of the output amount can be investigated, preferably with respect to the transmission behavior as part of the system behavior of the system components, to determine the attenuation that affects the output amount.

[0859] Preferably, it is possible to diagnose whether the nozzle is "partially or completely clogged with the cleaning fluid." For example, a pressure spike 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] Comparing characteristic features may require comparing the spike process with one or more benchmark processes of pressure.

[0861] If nozzle blockage is detected, a solution strategy can be used according to the seventh and / or eighth aspect of the present invention.

[0862] Alternatively, you can generate a warning requesting manual cleaning of the nozzle.

[0863] By monitoring the inrush current of the cleaning fluid pump over time, it is possible to diagnose whether the cleaning fluid pump is blocked, especially under freezing conditions.

[0864] In particular, a blocked cleaning fluid pump exhibits greater attenuation with respect to inrush current.

[0865] If a blocked cleaning fluid pump is detected, it can be switched off, which has the advantage of preventing the cleaning fluid pump from burning out.

[0866] The system behavior of system components can be favorably evaluated based on the temporal process of the output quantity, and the possibility of further analysis supporting the transmission behavior of system components in relation to this, in particular, the diversity of such analytical possibilities, is provided.

[0867] In particular, the step response can be evaluated as a function of input and / or output quantities, and data with the same or very similar input and / or processing quantities are compared to each other.

[0868] Preferably, the results of the analysis of the temporal process of the deviation are stored together with and / or in the diagnostic signal.

[0869] Conveniently, at least two temporal processes of the deviation are examined for the existence of drift in the deviation over time, preferably for at least five deviation processes, and preferably for at least ten deviation processes.

[0870] This suggests evaluating the temporal process of output power in relation to the drift of output power over time.

[0871] Drift is a systematic change in output quantity as a response to input quantity over the lifetime of a system component.

[0872] The temporal process of the output quantity can be compared with previously observed temporal processes of the output quantity over time, particularly multiple temporal processes of the output quantity over time.

[0873] Drift exists when deviations over time, starting from the expected system behavior of a system component, continuously move in one direction. Depending on the characteristics, it is possible to favorably determine, in particular, how changes related to the aging degradation of the system behavior of a system component occur.

[0874] Furthermore, it is advantageous to consider recording specific output quantities after each system component is started, rather than having the temporal process run continuously.

[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, the performance degradation of the cleaning fluid pump over its lifespan can be favorably evaluated, and a warning can be provided when the cleaning fluid pump is expected to need to be replaced.

[0877] In particular, the temporal process of deviation can be evaluated for the existence of drift as a function of input and / or output quantities, thereby comparing data with the same or very similar input and / or processing quantities with each other.

[0878] Preferably, at least 20 temporal processes of the deviation are examined for the presence of deviation drift over time. Preferably, at least 30 temporal processes of the deviation are examined for the presence of deviation drift over time. Preferably, at least 40 temporal processes of the deviation are examined for the presence of deviation drift over time.

[0879] It should be noted that the above values ​​relating to the amount of the temporal process of deviation should not be understood as abrupt limits, but rather should be able to be exceeded or fallen below on an engineering scale without deviating from the described aspects of the invention. Simply put, the values ​​are intended to represent the magnitude of the amount of the temporal process within the proposed deviation range.

[0880] Preferably, the results of the analysis of the temporal process of the deviation are stored together with and / or in the diagnostic signal.

[0881] The cause of actual system behavior that deviates from expected system behavior may be based on the currently diagnosed system component, or it may be based on the deviating system component but have a cause that is actually forwarded to the diagnosed system component according to a system-dependent transmission function between components.

[0882] If the corresponding transfer function is unknown, it is suggested to diagnose further system components to narrow down the cause.

[0883] Diagnostic signals prioritize information regarding input levels, which have an impact on the cleaning system and / or system components during the diagnosis of system components.

[0884] Diagnostic signals prioritize information regarding processing volume. This indicates that the cleaning system and / or system components are being affected during the diagnosis of system components.

[0885] Needless to say, the advantages of systematic dependency, in particular the advantages of systematic dependency as described in the fifth aspect of the present invention, also apply to the use of systematic dependency, in particular the use of systematic dependency proposed herein in accordance with the sixth aspect of the present invention.

[0886] It should be noted that the subject matter of the sixth embodiment can be advantageously combined with the subject matter of the preceding embodiments of the present invention, individually or cumulatively in any combination.

[0887] According to a seventh aspect of the present invention, the task is resolved by a method of selecting a solution strategy from a list of solution strategies included in a database in response to a current diagnostic signal, preferably in response to a current diagnostic signal received in accordance with a sixth aspect of the present invention, wherein the list of solution strategies includes at least one solution strategy associated with a diagnostic signal, and the solution strategy is selected from a list of solution strategies that best match the associated diagnostic signal to the current diagnostic signal.

[0888] If the actual system behavior of the system components of an automobile washing system does not correspond to the expected system behavior, the deviation between the actual system behavior and the expected system behavior can 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 it may be attributable to the system component causing the deviation, but the cause may be transferred to the system component actually diagnosed according to a system-dependent transmission function between system components.

[0890] Preferably, the category of causes of deviations between actual system behavior and expected system behavior can be determined by diagnostic signals, particularly by current diagnostic signals as described in a sixth aspect of the present invention.

[0891] The current diagnostic signal refers to a diagnostic signal that is subject to the solution strategy within the scope of this method. In particular, the current diagnostic signal may have been generated using the method of the sixth aspect of the present invention. Specifically, the current diagnostic signal indicates that there is a deviation between the actual system behavior and the expected system behavior.

[0892] When using diagnostic signals to determine the cause of deviations between actual and expected system behavior, input and / or processing amounts that affect system components and / or the cleaning system are given particular priority when determining the diagnostic signals.

[0893] It is particularly important to consider whether the current diagnostic signals can be associated, preferably clearly associated, with the cause of deviations in the system behavior of system components, based on existing empirical data.

[0894] Furthermore, it can be specifically considered that these empirical values ​​are systematized to the extent that they are effective for multiple different system components and / or multiple different cleaning systems, or at least transferable.

[0895] In this way, it can be advantageously achieved that, based on existing experience with different system components of different cleaning systems, particularly different cleaning systems from different manufacturers or suppliers, a clear assignment can be made between the current diagnostic signal and the cause of the deviation in system behavior, in particular a clear assignment that is manufacturer-independent and type-independent for the cleaning system and / or specific system components.

[0896] In particular, four distinct categories of causes for deviations between actual system behavior and expected system behavior are proposed, which can preferably be distinguished by diagnostic signals, and are especially preferred by current diagnostic signals as described in a sixth aspect of the present invention.

[0897] Specifically, it is proposed here to determine the category of the cause in the presence of the current diagnostic signal.

[0898] According to the first category of causes for deviations between actual system behavior and expected system behavior, there is a defect in the system components. In this regard, numerous different defects are possible.

[0899] In particular, if a defect exists, the cleaning fluid line may have isolated itself from the system components of the cleaning system. Such defects can be repaired even by an untrained person.

[0900] Furthermore, there appears to be a leak in the cleaning fluid line. In this case, spare parts will be needed, 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 the second category of causes for deviations between actual system behavior and expected system behavior, there is the phenomenon of aging and deterioration of system components.

[0902] Even if most of the system components of an automobile washing system are designed to withstand the expected lifespan of the automobile, these components still degrade over time. Specifically, the degradation of system components may occur faster than intended, resulting in their expected lifespan being shorter than the planned lifespan of the automobile. In this case, replacement of such components becomes unavoidable for the continued normal operation of the washing system.

[0903] Preferably, the aging degradation phenomenon can be detected and / or evaluated based on the drift of deviation over time, and in particular based on the drift of deviation described in the sixth aspect of the present invention.

[0904] The process of deviation drift over time is a particularly preferred method for determining how large the remaining expected value for the usability of system components is.

[0905] According to the third category of causes for deviations between actual system behavior and expected system behavior, there are disturbances in the system components.

[0906] It should be explicitly stated that a system component undergoing a diagnostic procedure, particularly the diagnostic procedure described in the sixth aspect of the present invention, may be faulty. Alternatively, the fault may also be caused by a deviation in the system component, in particular, by a transfer function, to a system behavior of the system component that is inferior to that of the diagnostic procedure.

[0907] According to the fourth category of causes for deviations between actual system behavior and expected system behavior, there are unknown causes for deviations in the system behavior of system components.

[0908] If the cause of the deviation between the actual system behavior and the expected system behavior of the system components cannot be determined based on the diagnostic signals, then an unknown cause exists.

[0909] In particular, it is important to note that, so far, there is a lack of sufficient experience regarding the possible causes of deviations, or that the assignment of causes may lead to ambiguous results.

[0910] The solution strategy is a method designed to track the deviation between the actual system behavior and the expected system behavior observed in the system components of the automotive washing system when applied to an automotive washing system.

[0911] In other words, the solution strategy may be advantageously achieved by reducing the deviations in system components, or by ensuring that the actual system behavior again corresponds to the expected system behavior.

[0912] Of particular priority is that the solution strategy indicates the input quantity, which affects the cleaning system and / or system components on the cleaning system and / or system components when the solution strategy is applied.

[0913] Preferably, the solution strategy provides notification to the vehicle driver and / or the vehicle manufacturer.

[0914] Preferably, the solution strategy provides means for planning the maintenance and / or repair of the vehicle.

[0915] The solution strategy is preferably based on experience of the operation of the cleaning system. This experience may have been obtained during vehicle operation and / or in a laboratory and / or based on numerical models and / or as a result of existing maintenance recommendations and / or based on heuristic findings.

[0916] A preferred solution strategy depends on deviations in system behavior and / or current diagnostic signals, particularly current diagnostic signals determined according to a sixth aspect of the present invention.

[0917] Preferably, the preferred solution strategy depends on the processing volume.

[0918] Preferably, the solution 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 signals is determined.

[0919] The system components of the cleaning system can be advantageously restored to their expected operation through the solution strategy. This allows the cleaning system to return to normal operation despite any previously existing deviations in system behavior.

[0920] Overall, the solution strategy is highly advantageous because it allows the driver assistance system to maintain its functionality for a longer period, even though deviations in the system behavior of the system components of the washing system have been diagnosed.

[0921] Here, it is particularly suggested 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 a list of known solution strategies be obtained from a database accessible from the vehicle. The vehicle may also wirelessly connect to a suitable database that displays solution strategies.

[0923] In addition to the solution strategy, the database also shows the associated diagnostic signals to which the solution strategy is configured to provide relief.

[0924] In addition to the solution strategy, the database preferably indicates the input quantities that have an impact on the system components and / or the 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 when determining the current diagnostic signal.

[0926] Preferably, the solution strategy can be determined by the current diagnostic signal, in particular by the current diagnostic signal obtained according to a sixth aspect of the present invention.

[0927] The solution strategy involves selecting a diagnostic signal from the database that best matches the current diagnostic signal.

[0928] Preferably, the most suitable solution strategy is selected from the database using the minimum Euclidean distance between the diagnostic signal assigned to it in the database and the current diagnostic signal.

[0929] When determining a solution strategy based on the current diagnostic signal, input and / or processing amounts that have an impact on system components and / or the cleaning system are given particular priority when determining the current diagnostic signal.

[0930] More preferably, the database having a solution strategy is first pre-filtered for optimal input and / or optimal processing amounts, in particular based on the corresponding Euclidean distance between the input and / or processing amounts stored in the diagnostic signal and the input and / or processing amounts in the database.

[0931] Next, it is proposed to select a solution strategy based on the current diagnostic signal, following the procedure described above, according to the smallest possible Euclidean distance to the remaining solution strategies.

[0932] Therefore, a solution strategy can be favorably selected, which is favorably set to reduce deviations in the system behavior of the system components of the cleaning system, and / or to notify the operator and / or manufacturer of the failure, and / or to lead to future maintenance and / or corrective measures.

[0933] Furthermore, the empirical knowledge underlying each solution strategy should be specifically considered to be systematized to the extent that it is effective, or at least transferable, to multiple different system components and / or multiple different cleaning systems.

[0934] In this way, it can be advantageously achieved to make clear assignments between current diagnostic signals and solution strategies, particularly across manufacturers and types for cleaning systems and / or specific system components, based on existing experience with different cleaning systems from different manufacturers or suppliers, and with different system components of different cleaning systems.

[0935] Possible solution strategies include increasing the supply voltage and / or the target speed of the cleaning fluid pump when the actual system behavior deviates from the expected system behavior in the cleaning fluid pump, which in particular indicates blockage of the flow channel between the cleaning fluid reservoir and the nozzle outlet opening, especially due to the increased energy requirements of the cleaning fluid pump and / or the relatively low outlet volume of cleaning fluid at the nozzle outlet opening and / or the increased static pressure of the cleaning fluid downstream of the cleaning fluid pump and / or the lower flow velocity of the cleaning fluid downstream of the cleaning fluid pump. This may be advantageous in removing the blockage and flushing it out of the cleaning system.

[0936] If the cleaning fluid pump shows a high current but there is no impulse from the current Hall sensor, this indicates that the cleaning fluid pump motor has stopped.

[0937] If cleaning results are not obtained, particularly in the case of increased availability and / or if the cleaning fluid pump cannot be observed to start, it is suggested to check the cleaning system controller, in particular the electronic control unit of the cleaning system, for phase open circuit faults and / or phase ground faults and / or short circuit faults. If a fault is detected, a plan for service and maintenance measures will be proposed.

[0938] It is proposed that the cleaning fluid pump be activated if there is a deviation between the actual system behavior and the expected system behavior at different pressures and / or engine speeds. Since cycles at different pressures and / or engine speeds do not result in the actual system behavior corresponding to the expected system behavior, it is proposed that a corresponding warning be sent to the vehicle driver and / or manufacturer, signaling that the cleaning fluid pump needs to be replaced, and / or that the cleaning system be shut down until the cleaning fluid pump is replaced, thereby halting the use of the cleaning fluid pump and / or the entire cleaning system.

[0939] It is proposed that the cleaning fluid pump should not be operated any further if the ambient temperature exceeds a defined temperature, particularly above 45°C, with a particular preference above 55°C, and / or if the ambient temperature falls below a defined temperature, particularly below 0°C, with a particular preference below -15°C, thereby advantageously increasing the remaining lifespan of the cleaning fluid pump.

[0940] With respect to the cleaning fluid pump, it is proposed to monitor the lifespan of the cleaning fluid pump, in particular by monitoring the flow rate and / or static pressure and / or flow rate through the cleaning fluid pump in combination with the cleaning fluid pump, and / or by monitoring the number of existing operating cycles of the cleaning fluid pump, and / or by monitoring the usage time of the cleaning fluid pump to date, and if it is foreseeable that the cleaning fluid pump is nearing the end of its lifespan, it is proposed to send a corresponding warning to the vehicle driver and / or manufacturer, signaling that the cleaning fluid pump needs to be replaced within the expected remaining lifespan, and / or to shut down the use of the cleaning fluid pump and / or the entire cleaning system until the cleaning fluid pump is replaced.

[0941] If the cleaning fluid pump has excessive energy requirements, particularly as detectable by a current sensor, it is proposed that a warning be sent to the driver and / or the vehicle manufacturer indicating that the cleaning fluid pump needs to be replaced, and / or that the cleaning system be shut down until the cleaning fluid pump is replaced, thereby halting the use of the cleaning fluid pump and / or the entire cleaning system.

[0942] If the cleaning fluid pump has an excessive temperature, particularly as detected by the temperature sensor, it is proposed that a warning be sent to the driver and / or the vehicle manufacturer indicating that the cleaning fluid pump needs to be replaced, and / or that the cleaning system be shut down until the cleaning fluid pump is replaced, thereby halting the use of the cleaning fluid pump and / or the entire cleaning system.

[0943] With respect to the cleaning fluid pump, it is proposed to monitor the pump's performance, particularly preferably by a flow sensor operably connected to the cleaning fluid pump, and / or a pressure sensor flow sensor operably connected to the cleaning fluid pump, and / or a flow meter flow sensor operably connected to the cleaning fluid pump, by causing the actual system behavior to deviate from the expected system behavior. If a deviation occurs, it is proposed to accordingly warn the driver and / or the vehicle manufacturer, send a signal that the cleaning fluid pump needs to be replaced, and / or shut down the use of the cleaning fluid pump and / or the entire cleaning system until the cleaning fluid pump is replaced.

[0944] In particular, it has been proposed to monitor the system behavior of the cleaning fluid pump by a flow sensor operably connected to the cleaning fluid pump and / or by a flow sensor actively connected to the cleaning fluid pump and / or by a pressure sensor flow sensor actively connected to the cleaning fluid pump and / or by a flow meter flow sensor actively connected to the cleaning fluid pump. If deviations indicate that the cleaning fluid pump has stopped and / or that the cleaning fluid pump is blocked by debris, especially under freezing conditions, it is suggested to switch the cleaning fluid pump off to warn the vehicle driver and / or manufacturer and signal that the cleaning fluid pump needs to be replaced.

[0945] A possible solution strategy is proposed in the presence of deviations from the expected system behavior in the cleaning fluid reservoir, particularly due to irregularly decreasing static pressure operably connected to the bottom of the cleaning fluid reservoir and / or irregularly decreasing fill level of the cleaning fluid reservoir determined by a level sensor, especially in the event of frost and / or leakage of the cleaning fluid reservoir resulting in partitioning of the cleaning fluid reservoir, and in the event of irregularly decreasing fill level of the cleaning fluid reservoir determined by a level sensor. In this way, the cleaning system can be made operational again in an advantageous manner.

[0946] With respect to level sensors, particularly those operably connected to a cleaning fluid reservoir, it is proposed to monitor their functionality, and if it indicates that functionality is no longer present, in particular by ceasing to emit a signal and / or if the emitted signal does not match the expected system behavior, it is proposed to subject the level sensor to maintenance and replace it if necessary.

[0947] If the level sensor has an excessive energy demand, particularly as detected by the current sensor, it is proposed that a signal be sent to the driver and / or the vehicle manufacturer warning that the level sensor needs to be replaced, and / or to the cleaning system to stop the use of the cleaning fluid pump and / or the entire cleaning system until the level sensor is replaced.

[0948] If the level sensor has an excessive temperature, particularly as detected by the temperature sensor, it is proposed that a signal be sent to the driver and / or the vehicle manufacturer warning that the level sensor needs to be replaced, and / or to the cleaning system to stop the use of the cleaning fluid pump and / or the entire cleaning system until the level sensor is replaced.

[0949] A possible solution strategy for level sensors is to suggest replacing the level sensor if the reaction 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 especially preferably at the interface between the cleaning fluid reservoir and the level sensor, to monitor whether a leak is present, and if a leak is present, maintenance and / or remedial measures are planned.

[0951] The possible solution strategy lies in the fact that, in particular, in the presence of deviations from the expected system behavior in the cleaning fluid reservoir, especially due to irregularly decreasing static pressure operatively connected to the cleaning fluid line and / or blockage of the cleaning fluid line as a result of frost and / or leakage of the cleaning fluid line, maintenance and / or repair measures and / or heating of the cleaning fluid line are proposed as a solution strategy, particularly due to blockage of the cleaning fluid line determined by a flow meter. This is an advantageous way to make the cleaning system operational again.

[0952] With regard to telescopic cleaning nozzles, it is proposed to monitor the remaining lifespan of the telescopic cleaning nozzle, in particular by monitoring the number of existing operating cycles of the telescopic cleaning nozzle, and if it is foreseeable that the lifespan of the telescopic cleaning nozzle is nearing its end, a corresponding warning should be sent to the vehicle driver and / or manufacturer, signaling that the telescopic cleaning nozzle should be replaced within the expected remaining lifespan range.

[0953] Furthermore, with respect to retractable cleaning nozzles, it is proposed to monitor the existing number of operating cycles of the retractable cleaning nozzle and, if a predefined number of operating cycles is reached, send a warning...

Claims

1. A method (MDSD1) for deriving a correspondence between input and output amounts from a cleaning system (16, 200) in a cleaning process (30, 32, 34, 36, 38, 40) for cleaning the surface parts (20, 22, 24, 26, 28) of the automobile (14), in order to adjust the amount of resources so as to maintain resources until the destination for cleaning the surface parts (20, 22, 24, 26, 28) of the automobile (14), wherein, The output amount (204) is determined by the cleaning mode of the cleaning system (16, 200) and depends on the input amount (202), and the output amount indicates how far or for how long the sensor can be used. - A step (BDTS1) of determining the input quantity (202) as the first parameter of the method (MDSD1) using a measurement value obtained by at least one sensor (50, 52, 54, 56, 56a, 56b, 58), - A step (BDTS2) of determining the output amount (204) as a second parameter of the method (MDSD1) using the measured value obtained by at least one of the sensors (50, 52, 54, 56, 56a, 56b, 58), - A step of digitizing (BDTS3) and recording the first and second parameters determined above by a data processing system (150) as necessary, wherein the data processing system (150) represents an electronic data processing and evaluation system (152) and a database (154), and the step of digitizing and recording, - Step (BDTS4) of recording the first and second parameters determined above as datasets (DP1, DP2, DP3, DP4) of a dependency table (DT) in the database (154) in a related and ordered manner, - A step (DSDS2) of deriving systematic dependencies (120, 120D, 120R) showing the correspondence between the first parameter and the second parameter from at least two datasets (DP1, DP2, DP3, DP4) of the dependency table (DT) recorded in the database (154) by the electronic data processing and evaluation system (152), wherein the electronic data processing and evaluation unit (152) accesses the datasets (DP1, DP2, DP3, DP4) of the dependency table (DT) and determines and derives the systematic dependencies (120, 120D, 120R) from the datasets (DP1, DP2, DP3, DP4) of the dependency table (DT) in the form of curves and coefficients of determination of the curves by a regression algorithm, - The step (DSDS3) of recording the derived systematic dependencies (120, 120D, 120R) in a data processing system (150) and / or an electronic control unit (18) is shown. Method (MDSD1).

2. The input quantity (202) is characterized in that it represents at least one measured quantity (100, 102, 104, 106, 107, 108), specifically, a processing quantity (140, 141, 142, 143, 144, 145, 146, 147) and / or a controlled quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119), The measured quantities (100, 102, 104, 106, 107, 108) are quantities measured by at least one of the sensors (50, 52, 54, 56, 56a, 56b, 58), The processing amounts (140, 141, 142, 143, 144, 145, 146, 147) are environmental processing amounts related to the surrounding environment of the automobile (14), and are the amounts processed by the cleaning system (16, 200). The method according to claim 1 (MDSD1).

3. The method according to claim 1 or 2 (MDSD1), characterized in that the input amount (202) indicates the driving speed of the automobile (14).

4. The method according to any one of claims 1 to 3 (MDSD1), characterized in that the input quantity (202) represents the humidity, temperature, rainfall, snowfall, coordinates of the automobile (14), or any combination thereof in the vicinity of the automobile (14).

5. The method according to any one of claims 1 to 4 (MDSD1), characterized in that the input quantity (202) indicates the vehicle type.

6. The input amount (204) is a parameter that indicates the degree of contamination of at least one sensor (50, 52, 54, 56, 56a, 56b, 58) at the start time of cleaning the sensors, and is characterized by indicating the availability of the sensors (220, 222, 224), The aforementioned availability (220, 222, 224) is a measurement of the degree of contamination of the at least one surface portion (20, 22, 24, 26, 28) connected to the sensor (50, 52, 54, 56, 56a, 56b, 58). The method according to any one of claims 1 to 5 (MDSD1).

7. The method according to claim 6 (MDSD1), characterized in that the output amount (204) indicates an increase in the availability (220, 222, 224) of the sensors (50, 52, 54, 56, 56a, 56b, 58) and / or the availability (229) due to the cleaning process (30, 32, 34, 36, 38, 40).

8. The method according to any one of claims 1 to 7 (MDSD1), characterized in that the output amount (204) represents the resource requirements (30d, 32d, 34d, 36d, 38d, 40d) for the cleaning process (30, 32, 34, 36, 38, 40) of the surface portions (20, 22, 24, 26, 28) of the automobile (14), and the resource requirements (30d, 32d, 34d, 36d, 38d, 40d) are determined according to the set values ​​of the control amounts (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) for the cleaning process (30, 32, 34, 36, 38, 40) of the surface portions (20, 22, 24, 26, 28).

9. The method according to any one of claims 1 to 8 (MDSD1), characterized in that the systematic dependencies (120, 120D, 120R) are determined by regression analysis.

10. The method according to any one of claims 1 to 9 (MDSD1), characterized in that the parameters of the systematic dependencies (120, 120D, 120R) are determined by an optimization procedure that minimizes the cumulative deviation of empirical values ​​considered by the datasets (DP1, DP2, DP3, DP4).

11. The method according to any one of claims 1 to 10 (MDSD1), characterized in that the systematic dependencies (120, 120D, 120R) are derived using a dataset (DP1, DP2, DP3, DP4) of the dependency table (DT) from an existing database (154), and the dataset (DP1, DP2, DP3, DP4) from the existing database (154) has been previously accessed (DSDS1).

12. The method according to claim 11 (MDSD1), characterized in that the existing database (154) is continuously expanded.

13. The method according to claim 11 (MDSD1), characterized in that a new dataset (DP1, DP2, DP3, DP4) replaces the dataset (DP1, DP2, DP3, DP4) that deviates the most from the derived systematic dependencies (120, 120D, 120R) in the dependency table (DT).

14. A cleaning method (10) for cleaning at least one surface portion (20, 22, 24, 26, 28) connected to a sensor of an automobile (14), wherein the amount of resources is adjusted to maintain resources until the destination, The automobile (14) has a washing system (16) and at least one sensor (50, 52, 54, 56, 56a, 56b, 58), At least one of the sensors (50, 52, 54, 56, 56a, 56b, 58) is operably connected to one surface portion (20, 22, 24, 26, 28), The cleaning method (10) comprises at least one cleaning process (30, 32, 34, 36, 38, 40), The at least one cleaning process (30, 32, 34, 36, 38, 40) is adapted to clean one surface portion (20, 22, 24, 26, 28) and includes a cleaning period (38a, 40a) with a start time (38b, 40b) and an end time (38c, 40c), The cleaning system (16) includes an electronic control unit (18), and the cleaning fluid distribution system (60) includes at least one fluid reservoir (62), at least two nozzles (70, 72, 74, 76, 76a, 76b, 78, 78a, 78b), and at least two cleaning fluid lines (80, 82, 84, 86, 88). The at least one sensor (50, 52, 54, 56, 56a, 56b, 58) is adapted to detect at least one measurement quantity (100, 102, 104, 106, 107, 108), specifically humidity, temperature, rainfall, snowfall near the vehicle (14), the coordinates or control quantities (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) of the vehicle (14), or any combination thereof, and transmits the at least one measurement quantity (100, 102, 104, 106, 107, 108) to the electronic control unit (18), which is used to determine the availability (220, 222, 224) of the at least one sensor (50, 52, 54, 56, 56a, 56b, 58). The at least two nozzles (70, 72, 74, 76, 76a, 76b, 78, 78a, 78b) are adapted to connect to the at least one surface portion (20, 22, 24, 26, 28) to deliver the cleaning fluid (64), The electronic control unit (18) is adapted to control or adjust the at least one cleaning process (30, 32, 34, 36, 38, 40) by at least one control amount (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) of the at least one cleaning process (30, 32, 34, 36, 38, 40), A cleaning method (10) wherein the resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of at least one cleaning process (30, 32, 34, 36, 38, 40) depend on the set values ​​of the control variables (110, 111, 112, 113, 114, 115, 116, 117, 118, 119), In accordance with a dependency table (DT) showing at least two datasets (DP1, DP2, DP3, DP4), the electronic control unit (18) controls or adjusts the cleaning that adjusts the resources. Each dataset (DP1, DP2, DP3, DP4) contains at least one input quantity (202) of the washing system (16), specifically, humidity, temperature, rainfall, snowfall near the vehicle (14), coordinates (14) of the vehicle (14), control quantities (110, 111, 112, 113, 114, 115, 116, 117, 118, 119), vehicle type, or any combination thereof, and The output amount (204) of the cleaning system (16), the resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of the at least one cleaning process (30, 32, 34, 36, 38, 40), and The present invention is characterized by indicating the availability (220, 222, 224) of at least one of the sensors (50, 52, 54, 56, 56a, 56b, 58), The measured quantities (100, 102, 104, 106, 107, 108) are quantities measured by at least one of the sensors (50, 52, 54, 56, 56a, 56b, 58). Cleaning method (10).

15. A cleaning method (10) for cleaning at least one surface portion (20, 22, 24, 26, 28) connected to a sensor of an automobile (14), wherein the amount of resources is adjusted to maintain resources until the destination, The automobile (14) has a washing system (16) and at least one sensor (50, 52, 54, 56, 56a, 56b, 58), The sensors (50, 52, 54, 56, 56a, 56b, 58) are operably connected to one surface portion (20, 22, 24, 26, 28), The cleaning method (10) comprises at least one cleaning process (30, 32, 34, 36, 38, 40), The cleaning process (30, 32, 34, 36, 38, 40) is adapted to clean one surface portion (20, 22, 24, 26, 28) and includes a cleaning period (38a, 40a) with a start time (38b, 40b) and an end time (38c, 40c), The cleaning system (16) includes an electronic control unit (18), and the cleaning fluid distribution system (60) includes at least one fluid reservoir (62), at least two nozzles (70, 72, 74, 76, 76a, 76b, 78, 78a, 78b), and at least two cleaning fluid lines (80, 82, 84, 86, 88). The sensors (50, 52, 54, 56, 56a, 56b, 58) are adapted to detect at least one measurement quantity (100, 102, 104, 106, 107, 108), specifically humidity, temperature, rainfall, snowfall near the vehicle (14), the coordinates of the vehicle (14), control quantities (110, 111, 112, 113, 114, 115, 116, 117, 118, 119), or any combination thereof, and to transmit the measurement quantities (100, 102, 104, 106, 107, 108) to the electronic control unit (18), which is used to determine the availability (220, 222, 224) of the sensors (50, 52, 54, 56, 56a, 56b, 58). The nozzles (70, 72, 74, 76, 76a, 76b, 78, 78a, 78b) are adapted to connect with the surface portions (20, 22, 24, 26, 28) to deliver the cleaning fluid (64). The electronic control unit (18) is adapted to control or adjust the cleaning process (30, 32, 34, 36, 38, 40) by at least one control amount (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) of the cleaning process (30, 32, 34, 36, 38, 40), A cleaning method wherein the resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of the cleaning process (30, 32, 34, 36, 38, 40) depend on the set values ​​of the controlled variables (110, 111, 112, 113, 114, 115, 116, 117, 118, 119), The input quantities (202) of the cleaning system (16), specifically, at least one control quantity (110, 111, 112, 113, 114, 115, 116, 117, 118, 119) of the cleaning process (30, 32, 34, 36, 38, 40), humidity, temperature, rainfall, snowfall near the automobile (14), coordinates of the automobile (14), vehicle type, or any combination thereof, Between the output amount (204) of the cleaning system (16), specifically the resource requirements (30d, 32d, 34d, 36d, 38d, 40d) of the cleaning process (30, 32, 34, 36, 38, 40) and / or the availability (220, 222, 224) of the sensors (50, 52, 54, 56, 56a, 56b, 58), The electronic control unit (18) controls or adjusts the cleaning to adjust the resources in accordance with the system behavior of the cleaning system (16), specifically, the dependency relationships (120, 120D, 120R) of the cleaning processes (30, 32, 34, 36, 38, 40) of the surface portions (20, 22, 24, 26, 28) of the automobile (14), and in accordance with the dependency relationships (120, 120D, 120R) described in any one of claims 1 to 13. The dependency relationships (120, 120D, 120R) are determined by a regression algorithm in the form of a curve and the coefficient of determination of the curve, and represent the correspondence between the input quantity (202) and the output quantity (204). Cleaning method (10).

16. The cleaning method (10) according to claim 14 or 15, characterized in that the electronic control unit (18) controls or adjusts the cleaning to adjust the resources according to the actual measured values, specifically, the actual availability (221) of the sensors (50, 52, 54, 56, 56a, 56b, 58) that are operably connected to the surface portions (20, 22, 24, 26, 28) to be cleaned.

17. A cleaning system (16) having an electronic control unit (18) and a cleaning fluid distribution system (60), wherein the cleaning fluid distribution system (60) includes at least one fluid reservoir (62), at least two nozzles (70, 72, 74, 76, 76a, 76b, 78, 78a, 78b), and at least two cleaning fluid lines (80, 82, 84, 86, 88), The cleaning system (16) is configured to perform a method (MDSD1) for deriving the correspondence between the input and output amounts of the cleaning system (16, 200) for the cleaning process (30, 32, 34, 36, 38, 40) of the surface parts (20, 22, 24, 26, 28) of the automobile (14), specifically, the system behavior of the cleaning system (16, 200) described in any one of claims 1 to 13, and / or The cleaning system (16) is configured to perform a cleaning method (10) for resource-adjusting cleaning on at least one surface portion (20, 22, 24, 26, 28) of the automobile (14) according to any one of claims 14 to 16, The aforementioned systematic dependencies (120, 120D, 120R) are determined by a regression algorithm in the form of a curve and the coefficient of determination of the curve, and represent the correspondence between the input quantity (202) and the output quantity (204). Cleaning system (16).

18. Automobile (14), The automobile (14) is equipped with the washing system (16) described in claim 17, The cleaning system (16) The device is configured to perform a cleaning method (10) for adjusting the resources for cleaning at least one surface portion (20, 22, 24, 26, 28) of an automobile (14) according to any one of claims 14 to 16, and / or The system is configured to perform a method (MDSD1) for deriving a correspondence between input and output amounts by a car (14) washing system (16, 200) according to any one of claims 1 to 13, and / or The system is configured to use systematic dependencies (120, 120D, 120R) derived by a method (MDSD1) for deriving the correspondence between input and output amounts by a car (14) cleaning system (16, 200) according to any one of claims 1 to 13, for cleaning to adjust resources to at least one surface portion (20, 22, 24, 26, 28) of the car (14), The aforementioned systematic dependencies (120, 120D, 120R) are determined by a regression algorithm in the form of a curve and the coefficient of determination of the curve, and represent the correspondence between the input quantity (202) and the output quantity (204). Automobile (14).

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