A calibration method and calibration device for an electronic parking brake controller

Abstract

The application belongs to the technical field of Internet of Things, and discloses a kind of calibration method of electronic parking brake controller, comprising the following steps: S1, input signal of electronic parking brake controller is collected by sensor;S2, the signal collected is filtered, amplified and preprocessed;S3, based on the input signal after preprocessing, feature value is extracted;S4, based on the feature value, the mathematical model of electronic parking brake controller is established to describe the relationship between the input and output of electronic parking brake controller;S5, according to the mathematical model, the calibration parameter of electronic parking brake controller is calculated;S6, the calibration parameter is applied to electronic parking brake controller, and simulation test is carried out to verify the accuracy and reliability of the parameter.The application is semi-physical simulation, which can accurately adjust parameters to ensure braking performance, adapt to different vehicle configurations, enhance system compatibility and stability, help function optimization update, and ensure efficient, safe and stable operation of electronic parking brake system.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of automobile electronics, and particularly relates to a calibration method and calibration equipment for an electronic parking brake controller. BACKGROUND

[0002] In modern automobiles, electronic parking brake systems (EPB) have gradually replaced traditional manual mechanical parking systems. The electronic parking brake system controls the action of the motor through an electronic control unit (ECU) to achieve control of the vehicle parking brake. However, before the electronic parking brake system is put into use, it needs to be accurately calibrated to ensure that the system can work normally under various working conditions. At present, most calibration methods rely on real vehicle testing, and this method not only consumes time and effort, but is also disturbed by various environmental factors, making it difficult to ensure calibration accuracy. SUMMARY

[0003] Therefore, the purpose of the present application is to provide a calibration method and calibration equipment for an electronic parking brake controller. The present application aims to solve the problems of time-consuming and labor-intensive calibration methods and poor calibration accuracy.

[0004] The present application provides a calibration method for an electronic parking brake controller, comprising the following steps:

[0005] S1. Data acquisition: collecting input signals of the electronic parking brake controller through sensors;

[0006] S2. Signal processing: filtering and amplifying the signals collected in step S1 using digital signal processing technology for preprocessing to eliminate noise and improve signal quality;

[0007] S3. Feature extraction: extracting feature values based on the preprocessed input signals of step S2;

[0008] S4. Model establishment: establishing a mathematical model of the electronic parking brake controller based on the feature values extracted in step S3 to describe the relationship between the input and output of the electronic parking brake controller;

[0009] S5. Calibration parameter calculation: calculating calibration parameters of the electronic parking brake controller according to the mathematical model established in step S4;

[0010] S6. Parameter verification: applying the calibration parameters calculated in step S5 to the electronic parking brake controller for simulation testing to verify the accuracy and reliability of the parameters;

[0011] The calibration method is also equipped with a calibration equipment host device, which stores collected data of real vehicles under different working conditions, as well as actual parking conditions and brake force sizes;

[0012] The data stored by the calibration equipment host is parsed into real vehicle original data and sent to the electronic parking brake controller, the electronic parking brake controller analyzes and judges whether parking and brake force are needed based on the input real vehicle original data through an algorithm, and then sends a control instruction to the electronic parking brake controller according to the analysis and judgment result, drives the brake actuator to perform action test, and collects real-time data in the action process, the real-time data including brake pressure data, actuator displacement data and motor working data.

[0013] The real vehicle original data sent by the calibration equipment host to the electronic parking brake controller is the input signal collected in step S1.

[0014] Further, in step S1, the input signal of the electronic parking brake controller includes vehicle speed, brake pedal position and hand brake switch state.

[0015] Further, in step S2, the digital signal processing technology includes low-pass filtering and high-pass filtering.

[0016] Further, in step S3, the extracted characteristic value includes signal amplitude, frequency and change rate.

[0017] Further, in step S5, the calibration parameters of the electronic parking brake controller include gain, threshold and delay time.

[0018] Further, in the calibration parameter calculation process of step S5, a genetic algorithm is used to obtain the optimal calibration parameter combination.

[0019] The application also provides a calibration equipment for an electronic parking brake controller, comprising a signal acquisition module, a signal processing module, a feature extraction module, a model establishment module, a calibration parameter calculation module and a parameter verification module.

[0020] The signal acquisition module is used to acquire the input signal of the electronic parking brake controller.

[0021] The signal processing module is used to pre-process the acquired input signal.

[0022] The feature extraction module is used to extract the characteristic value in the pre-processed input signal.

[0023] The model establishment module: based on the extracted characteristic value, a mathematical model of the electronic parking brake controller is established.

[0024] The calibration parameter calculation module: according to the established mathematical model, the calibration parameters of the electronic parking brake controller are calculated.

[0025] The parameter verification module: the calculated calibration parameters are applied to the electronic parking brake controller for simulation test, and the accuracy and reliability of the parameters are verified.

[0026] The calibration device is also matched with a calibration device upper controller, which stores collected data of real vehicles under different working conditions and actual parking conditions and brake force sizes;

[0027] The data stored in the calibration device upper controller are parsed into real vehicle original data and sent to the electronic parking brake controller, the electronic parking brake controller analyzes and judges whether parking and brake force size are needed based on the input real vehicle original data, and then sends control instructions to the electronic parking brake controller according to the analysis and judgment results to drive the brake actuator to perform action test, and collect real-time data in the action process, the real-time data including brake pressure data, actuator displacement data and motor working data;

[0028] Among them, the real vehicle original data sent by the calibration device upper controller to the electronic parking brake controller is the input signal collected by the signal acquisition module.

[0029] Advantages

[0030] The application provides a calibration method and calibration device for an electronic parking brake controller, the calibration method and device can calibrate with high precision under non-real vehicle conditions, improve calibration efficiency and reduce calibration cost. Compared with the prior art, the application has the following advantages:

[0031] 1. Non-real vehicle calibration: avoids the complexity and environmental interference of real vehicle test, improves calibration precision, and the non-real vehicle calibration precision of the application reaches more than 98%.

[0032] 2. High efficiency: the calibration process is automated, which greatly shortens the calibration time, and the calibration time of the application is shortened by more than 50%.

[0033] 3. Low cost: reduces the manpower and material resources required for calibration, and reduces the calibration cost, and the calibration cost of the application is reduced by more than 30%.

[0034] 4. High reliability: the accuracy and reliability of the calibration parameters are verified through simulation test, which improves the safety and stability of the electronic parking brake system, and the pass rate of the simulation test in the application reaches 100%.

[0035] Other advantages, objects and features of the application will be described in the following description to some extent, and to some extent, it will be obvious to those skilled in the art based on the study of the following, or can be taught from the practice of the application. The objects and other advantages of the application can be achieved and obtained by the following description. BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1This is a flowchart of a calibration method for an electronic parking brake controller according to the present invention;

[0037] Figure 2 This is a calibration logic diagram illustrating the interaction between the calibration equipment itself, the calibration equipment's host computer, and the electronic parking brake controller. Detailed Implementation

[0038] To make the technical solutions, advantages, and objectives of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention without creative effort are within the protection scope of this application.

[0039] like Figure 1 As shown, the present invention provides a calibration method for an electronic parking brake controller, comprising the following steps:

[0040] S1. Data Acquisition: The input signals of the electronic parking brake controller are acquired through sensors;

[0041] The input signals for the electronic parking brake controller include vehicle speed, brake pedal position, and handbrake switch status. These signals are collected using high-precision sensors to ensure data accuracy and reliability. During this data collection process, a total of 1000 data sets were collected, each containing information on various road conditions and driving behaviors, such as city driving, highway driving, and hill starts, ensuring data diversity and comprehensiveness.

[0042] S2. Signal Processing: Digital signal processing technology is used to preprocess the signal acquired in step S1 by filtering, amplification, etc., in order to eliminate noise and improve signal quality;

[0043] Preprocessing employed advanced digital signal processing techniques, such as low-pass and high-pass filtering, to effectively remove high-frequency noise and low-frequency interference. Amplification was adjusted according to the actual signal strength to ensure accuracy in subsequent processing. In this signal processing procedure, the signal-to-noise ratio of the processed signal was improved by 20 dB.

[0044] S3. Feature Extraction: Based on the input signal preprocessed in step S2, extract feature values;

[0045] The extracted feature values, including signal amplitude, frequency, and rate of change, are used for subsequent calibration. These feature values ​​are crucial for calibrating the electronic parking brake controller. For example, signal amplitude reflects the pressure applied to the brake pedal, frequency reflects changes in vehicle speed, and the rate of change reflects the speed of the braking process. In this feature extraction process, 50 feature values ​​were extracted, covering various aspects of the signal. Particular attention was paid to signal trends and outliers to better reflect the complexities of real-world driving conditions.

[0046] S4. Model Establishment: Based on the feature values ​​extracted in step S3, a mathematical model of the electronic parking brake controller is established;

[0047] This model development employed a variety of mathematical models for comparative analysis, ultimately selecting the nonlinear model with the highest good fit to ensure accuracy. The mathematical model used was nonlinear to describe the relationship between the controller input and output. For example, nonlinear models were established for the relationship between brake pedal position and motor output current, as well as for the relationship between vehicle speed and parking braking force. During the model development process, the good fit of the model reached over 95%.

[0048] S5. Calibration Parameter Calculation: Based on the mathematical model established in step S4, calculate the calibration parameters of the electronic parking brake controller, such as gain, threshold, and delay time. These calibration parameters are crucial for the precise control of the electronic parking brake controller. For example, gain adjusts the magnitude of the motor output current, the threshold determines the minimum braking force required to depress the brake pedal, and the delay time controls the speed of the braking response. In this calibration parameter calculation process, a genetic algorithm was used to obtain the optimal combination of calibration parameters.

[0049] S6. Parameter Verification: Apply the calibration parameters calculated in step S5 to the electronic parking brake controller and conduct simulation tests to verify the accuracy and reliability of the parameters;

[0050] The simulation tests covered a variety of operating conditions, such as parking brake tests and dynamic emergency braking assist tests on roads with different inclines, including emergency braking and hill-start assist, to ensure the stability and reliability of the parameters. During these simulation tests, the accuracy and reliability of the parameters were fully verified, and the controller performed as expected under various operating conditions.

[0051] The calibration method is also equipped with a calibration equipment host computer, which stores the collected data of the actual vehicle under different working conditions, as well as the actual parking conditions and braking force.

[0052] The data stored in the calibration equipment's host computer is parsed into raw data of the actual vehicle and sent to the electronic parking brake controller. Based on the input raw data of the actual vehicle, the electronic parking brake controller uses algorithms to analyze and determine whether parking is required and the amount of braking force. Then, based on the analysis and judgment results, it sends control commands to the electronic parking brake controller to drive the brake actuator to perform action tests and collect real-time data during the action process. The real-time data includes brake pressure data, actuator displacement data, and motor operation data. The action tests of driving the brake actuator include multiple short-stroke braking action tests and full-stroke braking action tests.

[0053] Among them, the original data of the actual vehicle sent by the calibration equipment host computer to the electronic parking brake controller is the input signal collected in step S1.

[0054] The present invention also provides a calibration device for an electronic parking brake controller, including a signal acquisition module, a signal processing module, a feature extraction module, a model building module, a calibration parameter calculation module, and a parameter verification module.

[0055] The signal acquisition module is used to collect input signals from the electronic parking brake controller. It employs high-precision sensors, such as lidar and millimeter-wave radar, to ensure the accuracy and reliability of the acquired signals. The accuracy of this signal acquisition module reaches the millimeter level. The signal acquisition module establishes a communication connection with the electronic parking brake controller via CAN bus, LIN bus, or Ethernet communication.

[0056] The signal processing module is used to preprocess the acquired input signals. It employs advanced digital signal processing chips, such as DSPs and FPGAs, to achieve high-speed, high-precision signal processing. The processing speed of this module reaches 10 million operations per second.

[0057] The feature extraction module is used to extract feature values ​​from the preprocessed input signal. It employs deep learning algorithms, such as convolutional neural networks and recurrent neural networks, to extract deeper-level feature information. The accuracy of this feature extraction module reached over 98%.

[0058] Model Building Module: Based on the extracted feature values, a mathematical model of the electronic parking brake controller is established. This module utilizes professional mathematical modeling software, such as MATLAB and Simulink, to achieve rapid model building and verification. The model building module achieved a building speed of 10 models per minute.

[0059] Calibration parameter calculation module: Based on the established mathematical model, this module calculates the calibration parameters of the electronic parking brake controller. It utilizes a distributed computing platform, such as cloud computing and edge computing, to achieve high-efficiency computation. The calculation speed of this module reached 1 million calculations per second.

[0060] Parameter Verification Module: This module applies the calculated calibration parameters to the electronic parking brake controller, conducting simulation tests to verify the accuracy and reliability of the parameters. The parameter verification module employs virtual simulation technologies, such as VR and AR, to achieve a more realistic simulation testing environment. The simulation testing environment of this parameter verification module achieved a fidelity of over 99%.

[0061] The calibration equipment is also equipped with a calibration equipment host computer, which stores the collected data of the actual vehicle under different working conditions, as well as the actual parking conditions and braking force.

[0062] The data stored in the calibration equipment host computer is parsed into the original data of the actual vehicle and sent to the electronic parking brake controller. Based on the input original data of the actual vehicle, the electronic parking brake controller uses an algorithm to analyze and determine whether parking is required and the amount of braking force. Then, based on the analysis and judgment results, it sends control commands to the electronic parking brake controller to drive the brake actuator to perform action tests and collect real-time data during the action process. The real-time data includes brake pressure data, actuator displacement data, and motor working data.

[0063] Among them, the original data of the actual vehicle sent by the calibration equipment host computer to the electronic parking brake controller is the input signal collected by the signal acquisition module.

[0064] like Figure 2 As shown, the equipment required to implement the calibration method of the present invention includes: a calibration equipment host computer, a calibration equipment body, and an electronic parking brake controller;

[0065] Calibration Equipment Host Computer: Provides operators with an intuitive operating platform and data display interface. Operators can input vehicle information, select calibration modes, and start or stop the calibration process through the interface. Alternatively, they can directly import stored data collected from the entire vehicle under different operating conditions and send it to the calibration equipment via USB serial port, while simultaneously receiving and storing information returned by the electronic parking brake controller. The display interface can show the collected data, processed results, and changes in calibration parameters in real time, allowing operators to easily understand the calibration progress and status. For example, during calibration, the display interface can show the brake pressure change curve over time in graphical form, as well as the comparison with the standard curve, allowing operators to clearly see the calibration effect. Components: Consists of a computer host, display screen, host computer, keyboard, and mouse input. The host computer is used to display various information, and operators can operate it by touching the screen or clicking icons or menus with the mouse and keyboard. The operation buttons serve as a supplement for quick operation of some frequently used functions.

[0066] Calibration equipment body: A customized device that reads input data from the actual vehicle under different operating conditions and converts it into CAN data and other digital and analog interface formats that the electronic parking brake controller can recognize. Simultaneously, the calibration equipment body collects data on the automatic parking execution status, obtains simulation results, and outputs them to the calibration equipment's host computer.

[0067] Electronic parking brake controller: Its function is to receive parking brake signals from calibration equipment and, based on vehicle status information, precisely control the brake actuator to apply or release braking force, thereby realizing the vehicle's parking brake and automatic parking functions, while ensuring the vehicle's safety and stability during braking. The electronic parking brake controller comprehensively understands the vehicle's current status by collecting data from wheel speed sensors, vehicle attitude sensors (including tilt angle sensor data and acceleration sensor data), gear information, engine operating status information, parking brake switch signals, brake pad wear sensor data, brake fluid pressure sensor data, vehicle stability system information, and anti-lock braking system information. It determines whether the vehicle meets the conditions for automatic parking and then sends a control signal to the brake actuator, causing the motor to drive the brake calipers to clamp the brake pads, thereby generating braking force and realizing the vehicle's parking brake.

[0068] This invention is a semi-physical simulation. The electronic parking brake calibration system can accurately adjust parameters to ensure braking performance, adapt to different vehicle configurations, enhance system compatibility and stability, assist in function optimization and updates, and ensure the efficient, safe, and stable operation of the electronic parking brake system and adapt to the needs of technological development.

[0069] It is hereby declared that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method of calibrating an electronic parking brake controller, the method comprising: The calibration method comprises the following steps: S1. Data acquisition: collecting input signals of the electronic parking brake controller through sensors; S2. Signal processing: filtering and amplifying the signals collected in step S1 using digital signal processing technology to eliminate noise and improve signal quality; S3. Feature extraction: extracting feature values based on the preprocessed input signals in step S2; S4. Model establishment: establishing a mathematical model of the electronic parking brake controller based on the feature values extracted in step S3 to describe the relationship between the input and output of the electronic parking brake controller; S5. Calibration parameter calculation: calculating the calibration parameters of the electronic parking brake controller according to the mathematical model established in step S4; S6. Parameter verification: applying the calibration parameters calculated in step S5 to the electronic parking brake controller for simulation testing to verify the accuracy and reliability of the parameters; The calibration method is also equipped with a calibration device host, which stores the collected data of the actual vehicle under different working conditions, as well as the actual parking situation and brake force; The data stored in the calibration device host is parsed into actual vehicle original data and sent to the electronic parking brake controller, which analyzes and judges whether parking and brake force are needed based on the input actual vehicle original data, and then sends control instructions to the electronic parking brake controller according to the analysis and judgment results to drive the brake actuator to perform action testing and collect real-time data during the action, including brake pressure data, actuator displacement data and motor working data; The actual vehicle original data sent by the calibration device host to the electronic parking brake controller is the input signal collected in step S1.

2. The method of claim 1, wherein: In step S1, the input signals of the electronic parking brake controller include vehicle speed, brake pedal position and hand brake switch state.

3. The method of claim 2, wherein: In step S2, the digital signal processing technology includes low-pass filtering and high-pass filtering.

4. The method of claim 2, wherein: In step S3, the extracted feature values include signal amplitude, frequency and change rate.

5. The method of claim 2, wherein: In step S5, the calibration parameters of the electronic parking brake controller include gain, threshold and delay time.

6. The method of claim 2, wherein: In the calibration parameter calculation process of step S5, a genetic algorithm is used to obtain the optimal calibration parameter combination.

7. A calibration device for an electronic parking brake controller, characterized by: The calibration method comprises a signal acquisition module, a signal processing module, a feature extraction module, a model establishment module, a calibration parameter calculation module and a parameter verification module; The signal acquisition module is used to collect the input signals of the electronic parking brake controller; The signal processing module is used to preprocess the collected input signals; The feature extraction module is used to extract feature values from the preprocessed input signals; The model establishment module: based on the extracted feature values, a mathematical model of the electronic parking brake controller is established; The calibration parameter calculation module: based on the established mathematical model, the calibration parameters of the electronic parking brake controller are calculated; The parameter verification module: applying the calculated calibration parameters to the electronic parking brake controller for simulation testing to verify the accuracy and reliability of the parameters; The calibration device is also matched with a calibration device upper positioner, the calibration device upper positioner stores collected data of the real vehicle under different working conditions and actual parking conditions and brake force sizes; The data stored in the calibration device upper positioner is parsed into real vehicle original data and sent to the electronic parking brake controller, the electronic parking brake controller analyzes and judges whether parking and brake force size are needed based on the input real vehicle original data, then sends control instructions to the electronic parking brake controller according to the analysis and judgment results, drives the brake execution mechanism to act, collects real-time data in the action process, and the real-time data includes brake pressure data, execution mechanism displacement data and motor working data; The real vehicle original data sent by the calibration device upper positioner to the electronic parking brake controller is the input signal collected by the signal collection module.

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