CN117657171A - Intelligent chassis state parameter estimation system based on vehicle dynamics model - Google Patents
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Abstract
The invention relates to the technical field of automobile systems, and discloses an intelligent chassis state parameter estimation system based on a vehicle dynamics model, which comprises the following steps: 1) Acquiring chassis state related data such as vehicle speed, acceleration, brake pressure and the like through a vehicle sensor; 2) Preprocessing the acquired data, including filtering, calibrating, denoising and the like; 3) Establishing a dynamic model of the vehicle, and considering parameters such as the mass, suspension characteristics, tire characteristics and the like of the vehicle; 4) Estimating chassis state parameters, such as transverse acceleration, longitudinal acceleration and the like, by using a parameter estimation algorithm based on the acquired data and the dynamics model; 5) Analyzing and predicting chassis conditions, such as evaluating handling performance and stability of a vehicle; in summary, the intelligent chassis state parameter estimation system based on the vehicle dynamics model has the advantages of improving driving safety, improving driving experience, optimizing vehicle performance, saving energy, personalizing driving settings and the like.
Description
Technical Field
The invention relates to the technical field of automobile systems, in particular to an intelligent chassis state parameter estimation system based on a vehicle dynamics model.
Background
The intelligent chassis state parameter estimation system is based on a vehicle dynamics model; and (5) analyzing and predicting the chassis state by using the sensor data and an estimation algorithm. It relies on the following background art; theory of vehicle dynamics: in intelligent chassis state parameter estimation; the theory of vehicle dynamics is the basis. It includes mechanics, dynamics and control theory; for describing mechanical, dynamic and control characteristics during vehicle movement; sensor technology: the intelligent chassis state parameter estimation system relies on sensors equipped on the vehicle; such as a vehicle speed sensor, an acceleration sensor, a brake pressure sensor, etc. The sensors can acquire vehicle motion state related data in real time; providing basis for parameter estimation; data processing and filtering algorithm: the collected sensor data needs to be preprocessed; the method comprises the steps of filtering, calibrating, denoising and the like; to improve data quality and accuracy. Common data processing algorithms include Kalman filtering, unscented Kalman filtering, etc.; parameter estimation algorithm: the intelligent chassis state parameter estimation system uses a parameter estimation algorithm to estimate the chassis state parameters. Common parameter estimation algorithms include least squares, extended kalman filtering, particle filtering, etc. These algorithms are based on collected sensor data and a vehicle dynamics model; calculating the value of the chassis state parameter through a mathematical model; control system integration: the intelligent chassis state parameter estimation system needs to be integrated with a vehicle control system; real-time driving assistance and safety prompt are realized. Through interaction with the vehicle control system; the intelligent system can provide functions of dynamic stability control, ground grabbing force control and the like; and the driving safety and the driving experience are improved.
An intelligent chassis state parameter estimation system is needed to estimate the state of a vehicle chassis in real time; providing accurate state information and driving assistance; and the driving safety and the driving experience are improved for the driver.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an intelligent chassis state parameter estimation system based on a vehicle dynamics model, which solves the problems in the prior art.
In order to achieve the above purpose, the present invention provides the following technical solutions: an intelligent chassis state parameter estimation system based on a vehicle dynamics model, comprising the steps of:
1) Acquiring chassis state related data such as vehicle speed, acceleration, brake pressure and the like through a vehicle sensor;
2) Preprocessing the acquired data, including filtering, calibrating, denoising and the like;
3) Establishing a dynamic model of the vehicle, and considering parameters such as the mass, suspension characteristics, tire characteristics and the like of the vehicle;
4) Estimating chassis state parameters, such as transverse acceleration, longitudinal acceleration and the like, by using a parameter estimation algorithm based on the acquired data and the dynamics model;
5) Analyzing and predicting chassis conditions, such as evaluating handling performance and stability of a vehicle;
6) Providing driving assistance and safety prompts, such as dynamic stability control, grip control, and the like, in combination with a vehicle control system;
7) The capability of monitoring and analyzing the state of the chassis in real time is increased, wherein the capability comprises the steps of detecting the working states of a suspension system, a braking system, a steering system and the like of the chassis and identifying potential faults or abnormal conditions;
8) Providing a historical data record and analysis of chassis status for subsequent fault diagnosis and repair;
9) Providing intelligent chassis state optimization suggestions by combining a vehicle navigation system and traffic information, for example, adjusting chassis parameters according to road conditions and driving habits so as to improve driving safety and comfort;
10 Integrated with other vehicle systems, such as in cooperation with vehicle electronic stability control systems, active suspension systems, etc., to achieve higher level chassis control and performance optimization;
11 Using machine learning and artificial intelligence techniques to predict and optimize chassis state parameters to pre-warn of potential problems or to provide more accurate adjustment advice.
Preferably, wherein the estimation of the lateral motion parameter comprises an estimation of the sideslip angle, and the estimation of the longitudinal motion parameter comprises an estimation of the brake pressure.
Preferably, the estimation of chassis state parameters also includes estimation of suspension system parameters, such as suspension system pressure, travel.
Preferably, the estimation of the chassis state parameter also includes an estimation of tire parameters such as tire slip ratio, tire side force.
Preferably, the estimation of chassis state parameters is calculated and analyzed based on real-time acquired sensor data and a vehicle dynamics model.
Preferably, the intelligent chassis state parameter estimation system is capable of providing real-time chassis state information including lateral acceleration, longitudinal acceleration, slip angle, brake pressure parameters.
Preferably, the intelligent chassis state parameter estimation system can be used to evaluate the handling performance, stability, braking performance and acceleration performance of the vehicle.
Preferably, the intelligent chassis state parameter estimation system is capable of providing real-time driving assistance and safety cues, such as dynamic stability control, grip control, in conjunction with a vehicle control system.
Preferably, the intelligent chassis state parameter estimation system can improve driving safety and driving experience, and provides accurate chassis state information and driving auxiliary functions for a driver.
Compared with the prior art, the invention provides an intelligent chassis state parameter estimation system based on a vehicle dynamics model, which has the following beneficial effects:
1. and the driving safety is improved: by estimating chassis state parameters in real time, the system can provide accurate chassis state information and real-time driving assistance for the driver. This helps to alert the driver to the handling, stability and braking performance of the vehicle, thereby reducing the risk of accident.
2. Improve driving experience: the intelligent chassis state parameter estimation system can provide real-time chassis state information such as transverse acceleration, longitudinal acceleration and the like. This helps the driver to better understand the motion state of the vehicle, improving the driving confidence and comfort.
3. Optimizing vehicle performance: through real-time estimation and analysis of chassis state parameters, the intelligent system can evaluate the control performance, stability, braking performance and the like of the vehicle. This helps to optimize the design and tuning of the vehicle to make it perform better under different road conditions and driving demands.
4. Energy conservation: the intelligent chassis state parameter estimation system can provide real-time longitudinal acceleration, braking pressure and other information. This helps the driver to better grasp the acceleration and braking behavior of the vehicle, thereby achieving more efficient driving operation, further saving energy and reducing carbon emissions.
5. Personalized driving settings: based on the estimation of chassis state parameters, the intelligent system can adjust the dynamics and driving experience of the vehicle according to the preferences and demands of the driver. This allows the driver to make individual driving settings according to his own preferences, providing a driving experience that better fits his driving style.
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FIG. 1 is a schematic flow chart of the method of the invention.
Description of the embodiments
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
An intelligent chassis state parameter estimation system based on a vehicle dynamics model, comprising the steps of: 1) Acquiring chassis state related data such as vehicle speed, acceleration, brake pressure and the like through a vehicle sensor; 1.1 Vehicle speed sensor: acquiring current speed information of a vehicle by using a wheel speed sensor or a GPS module; 1.2 Acceleration sensor: acceleration information of the vehicle during running such as acceleration, deceleration, or cornering can be measured by an acceleration sensor mounted on the vehicle. 1.3 Brake sensor): acquiring state information of a brake pedal, including brake pressure, through a sensor of a brake system, so as to know the brake force and the brake state of the vehicle; 2) Preprocessing the acquired data, including filtering, calibrating, denoising and the like; 2.1 Filtering: smoothing the acquired data by using a digital filter to remove noise and abrupt changes; 2.2 Calibration process: calibrating the data acquired by the sensor to eliminate sensor errors and deviations, thereby improving the accuracy of the data; 2.3 Denoising: denoising the acquired data, removing noise introduced by a sensor or environmental factors by using a signal processing algorithm, and improving the reliability of the data; 3) Establishing a dynamic model of the vehicle, and considering parameters such as the mass, suspension characteristics, tire characteristics and the like of the vehicle; 3.1 Mass of vehicle): considering the influence of the total weight of the vehicle and the gravity center position on the dynamic characteristics of the vehicle; 3.2 Suspension characteristics): taking parameters such as rigidity, damping, geometric layout and the like of a vehicle suspension system into consideration, wherein the suspension system has an influence on the dynamic performance of the vehicle; 3.3 Tire characteristics): taking parameters such as friction force, lateral rigidity and the like of the tire into consideration, and the influence of the tire on the vehicle steering performance; 4) Estimating chassis state parameters, such as transverse acceleration, longitudinal acceleration and the like, by using a parameter estimation algorithm based on the acquired data and the dynamics model; 4.1 Lateral acceleration estimation): by analyzing the lateral acceleration of the vehicle, the lateral movement condition of the vehicle during the running of the curve can be known; 4.2 Longitudinal acceleration estimation): by analyzing the longitudinal acceleration of the vehicle, the longitudinal movement condition of the vehicle during acceleration and braking can be known; 5) Analyzing and predicting chassis conditions, such as evaluating handling performance and stability of a vehicle; 5.1 Handling performance evaluation): by analyzing the chassis state of the vehicle, such as acceleration, steering angle, etc., the handling performance of the vehicle and the degree of response of the vehicle to the driver instructions can be evaluated; 5.2 Stability prediction: the stability of the vehicle and the performance of the vehicle under different driving conditions can be predicted by analyzing the chassis states of the vehicle, such as the roll angle, the lateral force and the like; 6) Providing driving assistance and safety prompts, such as dynamic stability control, grip control, and the like, in combination with a vehicle control system; 6.1 Dynamic stability control: parameters such as a suspension system, braking force distribution and the like of the vehicle are adjusted in real time according to chassis state information, so that a dynamic stability control function is provided, and the stability of the vehicle under various driving conditions is maintained; 6.2 Grip control: by monitoring the chassis state of the vehicle and the grip force of the tires, a proper control strategy is implemented to furthest improve the grip force of the vehicle, prevent the tires from slipping and improve the control performance and safety of the vehicle; the method comprises the steps of carrying out a first treatment on the surface of the 7) The capability of monitoring and analyzing the state of the chassis in real time is increased, wherein the capability comprises the steps of detecting the working states of a suspension system, a braking system, a steering system and the like of the chassis and identifying potential faults or abnormal conditions; 8) Providing a historical data record and analysis of chassis status for subsequent fault diagnosis and repair; 9) Providing intelligent chassis state optimization suggestions by combining a vehicle navigation system and traffic information, for example, adjusting chassis parameters according to road conditions and driving habits so as to improve driving safety and comfort; 10 Integrated with other vehicle systems, such as in cooperation with vehicle electronic stability control systems, active suspension systems, etc., to achieve higher level chassis control and performance optimization; 11 Predicting and optimizing chassis state parameters using machine learning and artificial intelligence techniques to pre-warn of potential problems or to provide more accurate adjustment advice, wherein the estimation of lateral motion parameters includes an estimation of sideslip angle and the estimation of longitudinal motion parameters includes an estimation of brake pressure; the estimation of chassis state parameters also includes estimation of suspension system parameters such as suspension system pressure, travel; the estimation of chassis state parameters also includes the estimation of tire parameters such as tire slip ratio, tire lateral force; the estimation of the chassis state parameters is calculated and analyzed based on the sensor data acquired in real time and the vehicle dynamics model; the intelligent chassis state parameter estimation system can provide real-time chassis state information, including transverse acceleration, longitudinal acceleration, sideslip angle and brake pressure parameters; the intelligent chassis state parameter estimation system can be used for evaluating the control performance, stability, braking performance and acceleration performance of the vehicle; the intelligent chassis state parameter estimation system can be combined with a vehicle control system to provide real-time driving assistance and safety prompts, such as dynamic stability control and ground grabbing force control; the intelligent chassis state parameter estimation system can improve driving safety and driving experience, and provides accurate chassis state information and driving auxiliary functions for a driver; and the driving safety is improved: by estimating chassis state parameters in real time, the system can provide accurate chassis state information and real-time driving assistance for the driver. This helps to alert the driver to the handling, stability and braking properties of the vehicle, thereby reducing the risk of accidents; improve driving experience: the intelligent chassis state parameter estimation system can provide real-time chassis state information such as transverse acceleration, longitudinal acceleration and the like. The method is beneficial to the driver to better know the motion state of the vehicle, and improves the driving confidence and comfort; optimizing vehicle performance: through real-time estimation and analysis of chassis state parameters, the intelligent system can evaluate the control performance, stability, braking performance and the like of the vehicle. The design and adjustment of the vehicle are facilitated to be optimized, so that the vehicle is more excellent in performance under different road conditions and driving requirements; energy conservation: the intelligent chassis state parameter estimation system can provide real-time longitudinal acceleration, braking pressure and other information. The method is beneficial to a driver to better master the acceleration and braking behaviors of the vehicle, so that more efficient driving operation is realized, energy sources are further saved, and carbon emission is reduced; personalized driving settings: based on the estimation of chassis state parameters, the intelligent system can adjust the dynamics and driving experience of the vehicle according to the preferences and demands of the driver. The driver can perform personalized driving setting according to own preference, and driving experience which is more in line with the driving style of the driver is provided;
in summary, the intelligent chassis state parameter estimation system based on the vehicle dynamics model has the advantages of improving driving safety, improving driving experience, optimizing vehicle performance, saving energy, personalizing driving settings and the like.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (9)
1. An intelligent chassis state parameter estimation system based on a vehicle dynamics model, comprising the steps of:
1) Acquiring chassis state related data such as vehicle speed, acceleration, brake pressure and the like through a vehicle sensor;
1.1 Vehicle speed sensor: acquiring current speed information of a vehicle by using a wheel speed sensor or a GPS module;
1.2 Acceleration sensor: acceleration information of the vehicle during running such as acceleration, deceleration or turning can be measured through an acceleration sensor arranged on the vehicle;
1.3 Brake sensor): acquiring state information of a brake pedal, including brake pressure, through a sensor of a brake system, so as to know the brake force and the brake state of the vehicle;
2) Preprocessing the acquired data, including filtering, calibrating, denoising and the like;
2.1 Filtering: smoothing the acquired data by using a digital filter to remove noise and abrupt changes;
2.2 Calibration process: calibrating the data acquired by the sensor to eliminate sensor errors and deviations, thereby improving the accuracy of the data;
2.3 Denoising: denoising the acquired data, removing noise introduced by a sensor or environmental factors by using a signal processing algorithm, and improving the reliability of the data;
3) Establishing a dynamic model of the vehicle, and considering parameters such as the mass, suspension characteristics, tire characteristics and the like of the vehicle;
3.1 Mass of vehicle): considering the influence of the total weight of the vehicle and the gravity center position on the dynamic characteristics of the vehicle;
3.2 Suspension characteristics): taking parameters such as rigidity, damping, geometric layout and the like of a vehicle suspension system into consideration, wherein the suspension system has an influence on the dynamic performance of the vehicle;
3.3 Tire characteristics): taking parameters such as friction force, lateral rigidity and the like of the tire into consideration, and the influence of the tire on the vehicle steering performance;
4) Estimating chassis state parameters, such as transverse acceleration, longitudinal acceleration and the like, by using a parameter estimation algorithm based on the acquired data and the dynamics model;
4.1 Lateral acceleration estimation): by analyzing the lateral acceleration of the vehicle, the lateral movement condition of the vehicle during the running of the curve can be known;
4.2 Longitudinal acceleration estimation): by analyzing the longitudinal acceleration of the vehicle, the longitudinal movement condition of the vehicle during acceleration and braking can be known;
5) Analyzing and predicting chassis conditions, such as evaluating handling performance and stability of a vehicle;
5.1 Handling performance evaluation): by analyzing the chassis state of the vehicle, such as acceleration, steering angle, etc., the handling performance of the vehicle and the degree of response of the vehicle to the driver instructions can be evaluated;
5.2 Stability prediction: the stability of the vehicle and the performance of the vehicle under different driving conditions can be predicted by analyzing the chassis states of the vehicle, such as the roll angle, the lateral force and the like;
6) Providing driving assistance and safety prompts, such as dynamic stability control, grip control, and the like, in combination with a vehicle control system;
6.1 Dynamic stability control: parameters such as a suspension system, braking force distribution and the like of the vehicle are adjusted in real time according to chassis state information, so that a dynamic stability control function is provided, and the stability of the vehicle under various driving conditions is maintained;
6.2 Grip control: by monitoring the chassis state of the vehicle and the grip force of the tires, a proper control strategy is implemented to furthest improve the grip force of the vehicle, prevent the tires from slipping and improve the control performance and safety of the vehicle;
7) The capability of monitoring and analyzing the state of the chassis in real time is increased, wherein the capability comprises the steps of detecting the working states of a suspension system, a braking system, a steering system and the like of the chassis and identifying potential faults or abnormal conditions;
8) Providing a historical data record and analysis of chassis status for subsequent fault diagnosis and repair;
9) Providing intelligent chassis state optimization suggestions by combining a vehicle navigation system and traffic information, for example, adjusting chassis parameters according to road conditions and driving habits so as to improve driving safety and comfort;
10 Integrated with other vehicle systems, such as in cooperation with vehicle electronic stability control systems, active suspension systems, etc., to achieve higher level chassis control and performance optimization;
11 Using machine learning and artificial intelligence techniques to predict and optimize chassis state parameters to pre-warn of potential problems or to provide more accurate adjustment advice.
2. The vehicle dynamics model-based intelligent chassis state parameter estimation system of claim 1, wherein the estimation of lateral motion parameters includes an estimation of sideslip angle and the estimation of longitudinal motion parameters includes an estimation of brake pressure.
3. An intelligent chassis state parameter estimation system based on a vehicle dynamics model according to claim 1, characterized in that the estimation of the chassis state parameter further comprises the estimation of suspension system parameters like suspension system pressure, travel.
4. An intelligent chassis state parameter estimation system based on a vehicle dynamics model according to claim 1, characterized in that the estimation of the chassis state parameter further comprises the estimation of the tire parameters such as the tire slip ratio, the tire side force.
5. An intelligent chassis state parameter estimation system based on a vehicle dynamics model according to claim 1, wherein the estimation of the chassis state parameter is calculated and analyzed based on real-time collected sensor data and the vehicle dynamics model.
6. The vehicle dynamics model-based intelligent chassis state parameter estimation system of claim 1, wherein the intelligent chassis state parameter estimation system is capable of providing real-time chassis state information including lateral acceleration, longitudinal acceleration, sideslip angle, brake pressure parameters.
7. The vehicle dynamics model-based intelligent chassis state parameter estimation system of claim 1, wherein the intelligent chassis state parameter estimation system is operable to evaluate vehicle handling performance, stability, braking performance, and acceleration performance.
8. An intelligent chassis state parameter estimation system based on a vehicle dynamics model according to claim 1, characterized in that the intelligent chassis state parameter estimation system is capable of providing real-time driving assistance and safety cues, such as dynamic stability control, grip control, in combination with a vehicle control system.
9. The intelligent chassis state parameter estimation system based on a vehicle dynamics model according to claim 1, wherein the intelligent chassis state parameter estimation system can improve driving safety and driving experience, and provide accurate chassis state information and driving assistance functions for a driver.
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