Method for indirectly deriving a systematic dependence for a system behaviour of a soiling process of a surface, cleaning system and motor vehicle

Patent metadata

Field	Value
Publication number	US-12594908-B2
Application number	US-201917786831-A
Country	US
Kind code	B2
Filing date	Dec 17, 2019
Priority date	Dec 17, 2019
Publication date	Apr 7, 2026
Grant date	Apr 7, 2026

Abstract

A method for indirectly deriving a systematic dependence for a system behavior of a soiling process of a surface of a motor vehicle. A soiling condition of the surface is evaluated via an availability of the sensor. Moreover, the method relates to a method of use of the systematic dependence, a cleaning system, and a motor vehicle.

First claim

The invention claimed is:

1 . A method for deriving a systematic dependence for a behavior of a soiling process of a motor vehicle, the motor vehicle including a sensor operatively connected to a surface of the motor vehicle, and the method comprising steps of:
receiving first sensor data from the sensor; determining, based at least in part on the first sensor data, a first availability of the sensor at a first time; determining a first soiling condition of the surface, based at least in part on the first availability of the sensor; receiving second sensor data from the sensor; determining, based at least in part on the second sensor data, a second availability of the sensor at a second time that is after the first time; determining, based at least in part on the second availability of the sensor, a second soiling condition of the surface; determining a soiling process between the first soiling condition of the sensor and the second soiling condition of the sensor; determining the motor vehicle travelled a distance between the first availability of the sensor and the second availability of the sensor; determining the motor vehicle increased an operating time while traveling the distance travelled by the motor vehicle between the first availability and the second availability: determining no cleaning process was performed while travelling the distance; determining a change of availability of the sensor based at least in part on the second availability of the sensor being less than the first availability of the sensor, wherein the change of availability depends on an input quantity via the behavior of the soiling process, determining the input quantity as a first parameter via the sensor; determining a second parameter via the sensor, based at least in part on the change of availability of the sensor; digitalizing and recording, via a data processing system, the first parameter and the second parameter, wherein the data processing system includes an electronic data processing and evaluation system and a database; storing the first parameter and second parameter in the database as a data set of a dependency table; deriving the systematic dependence between the first parameter and second parameter, via the electronic data processing and evaluation system, based at least in part on a first data set and a second data set of the dependency table, wherein an electronic data processing and evaluation unit determines the systematic dependence based at least in part on the first data set and the second data set of the dependency table, via an algorithm; storing the systematic dependence in at least one of the database, the electronic data processing and evaluation unit, or an electronic control unit; and controlling a cleaning system of the motor vehicle during the soiling process using the systematic dependence.

2 . The method according to claim 1 , wherein the input quantity exhibits the distance travelled by the motor vehicle between the first availability and the second availability.

3 . The method according to claim 1 , wherein the input Quantity includes the increase in the operating time by covering the distance travelled by the motor vehicle between the first availability and the second availability.

4 . The method according to claim 1 , wherein the input quantity exhibits a driving speed of the motor vehicle including a course of the driving speed along a route between the first availability and the second availability.

5 . The method according to claim 1 , wherein the input quantity exhibits a process quantity including one or more of:
a humidity including a course of the humidity along the route between the first availability and the second availability; a temperature in a vicinity of the motor vehicle including a course of the temperature along the route between the first availability and the second availability; a rainfall including a course of the rainfall along the route between the first availability and the second availability; or a snowfall quantity including a course of the snowfall quantity along the route between the first availability and the second availability.

6 . The method according to claim 1 , wherein the input quantity exhibits a vehicle type.

7 . The method according to claim 1 , wherein the input
quantity includes a current coordinate of the motor vehicle along the route between the first availability and the second availability.

8 . The method according to claim 1 , wherein the input quantity includes the first availability of the sensor.

9 . The method according to claim 1 , wherein the systematic dependence is determined via a regression analysis.

10 . The method according to claim 1 , wherein the systematic dependence is determined in a form of a curve and a coefficient of determination of the curve.

11 . The method according to claim 1 , wherein the systematic dependence is determined via an optimization process.

12 . The method according to claim 1 , wherein the systematic dependence is derived using the first data set and the second data set of the dependency table from the database accessed previously.

13 . The method according to claim 12 , wherein the database is continuously expanded.

14 . The method according to claim 1 , further comprising:
determining that the first data set deviates from the derived systematic dependence more than the second data set deviates from the derived systematic dependence; replacing, based at least in part on the determining that the first data set deviates from the derived systematic dependence more than the second data set deviates from the derived systematic dependence, the first data set with a third data set in the dependency table; and replacing, based at least in part on the determining that the first data set does not deviate from the derived systematic dependence more than the second data set deviates from the derived systematic dependence, the second data set with the third data set in the dependency table.

15 . The method according to claim 1 , further comprising:
using a cleaning system including:
an electronic control unit,
a cleaning fluid distribution system, wherein the cleaning fluid distribution system comprises at least one fluid reservoir,
at least one nozzle, and
at least one cleaning fluid line; and
executing, via the cleaning system, a cleaning process according to at least one of the systematic dependence and the dependency table.

16 . The method according to claim 1 , further comprising determining an expected availability of the sensor at one of:
a distance yet to be covered, or an operating time yet to be covered, by:
inserting the expected availability of the sensor at one of the distance yet to be covered, or the operating time yet to be covered, as the input quantity into the systematic dependence, and determining the expected availability starting from an actual availability;
selecting a data set from the dependency table that best matches the input quantity of the expected availability of the sensor at one of the distance yet to be covered, or the operating time yet to be covered, and determining the expected availability starting from the actual availability; or
performing linear interpolation between adjacent data sets of the dependency table that best matches the input quantity of the expected availability of the sensor at one of the distance yet to be covered, or the operating time yet to be covered, and determining the expected availability starting from the actual availability.

17 . The method

Assignees

• Kautex Textron Gmbh & Co Kg

Inventors

• Davies Chris
• Llion Stephen
• Barkow Axel
• Dreschers Daniel

Classifications

• Y10S700/00

  Data processing: generic control systems or specific applications · CPC title

• B60S1/56

  specially adapted for cleaning other parts or devices than front windows or windscreens {(rear-view mirror arrangements mounted on vehicle exterior including cleaning devices B60R1/0602)} · CPC title

• B60S1/50

  Arrangement of reservoir · CPC title

• B60S1/481 Primary

  the operation of at least part of the liquid supply being controlled by electric means (electrical washing liquid warming-up means B60S1/488) · CPC title

• B60S1/02 Primary

  Cleaning windscreens, windows or optical devices {(wind deflectors specially adapted for preventing soiling of windows or windscreens B60J1/2002)} · CPC title