An intelligent chassis state parameter estimation system based on a vehicle dynamics model

Abstract

The application 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) collecting chassis state related data such as vehicle speed, acceleration, brake pressure and the like through a vehicle sensor; 2) pre-processing the collected data, including filtering, calibration, denoising and the like; 3) establishing a dynamics model of the vehicle, considering parameters such as the mass of the vehicle, suspension characteristics, tire characteristics and the like; 4) based on the collected data and the dynamics model, using a parameter estimation algorithm to estimate chassis state parameters such as lateral acceleration, longitudinal acceleration and the like; 5) analyzing and predicting the chassis state, such as evaluating the handling performance and stability of the vehicle; in summary, the intelligent chassis state parameter estimation system based on the vehicle dynamics model has multiple beneficial effects such as improving driving safety, improving the driving experience, optimizing vehicle performance, saving energy and personalized driving settings.

Description

Technical Field

[0001] This invention relates to the field of automotive system technology, specifically to an intelligent chassis state parameter estimation system based on a vehicle dynamics model. Background Technology

[0002] The intelligent chassis state parameter estimation system is based on a vehicle dynamics model; it utilizes sensor data and estimation algorithms to analyze and predict chassis state. It relies on the following background technologies: Vehicle dynamics theory: Vehicle dynamics theory is fundamental in intelligent chassis state parameter estimation. It includes mechanics, dynamics, and control theories, used to describe the mechanical, dynamic, and control characteristics of a vehicle during motion; Sensor technology: The intelligent chassis state parameter estimation system relies on sensors equipped on the vehicle, such as vehicle speed sensors, acceleration sensors, and brake pressure sensors. These sensors can collect real-time data related to the vehicle's motion state, providing a basis for parameter estimation; Data processing and filtering algorithms: The collected sensor data needs preprocessing, including filtering, calibration, and noise reduction, to improve data quality and accuracy. Commonly used data processing algorithms include Kalman filtering and unscented Kalman filtering; Parameter estimation algorithms: The intelligent chassis state parameter estimation system uses parameter estimation algorithms to estimate chassis state parameters. Commonly used parameter estimation algorithms include least squares method, extended Kalman filtering, and particle filtering. These algorithms are based on collected sensor data and vehicle dynamics models; they calculate chassis state parameters using mathematical models; control system integration: the intelligent chassis state parameter estimation system needs to be integrated with the vehicle control system to achieve real-time driving assistance and safety prompts. Through interaction with the vehicle control system, the intelligent system can provide functions such as dynamic stability control and grip control, improving driving safety and the driving experience.

[0003] There is an urgent need for an intelligent chassis state parameter estimation system that can estimate the vehicle chassis state in real time, provide accurate state information and driving assistance, and improve driving safety and driving experience for drivers. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an intelligent chassis state parameter estimation system based on a vehicle dynamics model, which solves the problems mentioned in the background section.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an intelligent chassis state parameter estimation system based on a vehicle dynamics model, comprising the following steps: 1) Collect chassis status data, such as vehicle speed, acceleration, and brake pressure, through vehicle sensors; 2) Preprocess the collected data, including filtering, calibration, and noise reduction; 3) Establish a dynamic model of the vehicle, taking into account parameters such as vehicle mass, suspension characteristics, and tire characteristics; 4) Based on the collected data and dynamic model, the chassis state parameters, such as lateral acceleration and longitudinal acceleration, are estimated using parameter estimation algorithms; 5) Analyze and predict chassis condition, such as assessing vehicle handling performance and stability; 6) In conjunction with the vehicle control system, it provides driving assistance and safety prompts, such as dynamic stability control and grip control; 7) Enhance the ability to monitor and analyze chassis status in real time, including detecting the working status of the chassis's suspension system, braking system, steering system, etc., and identifying potential faults or abnormal conditions; 8) Provide historical data recording and analysis of chassis status to facilitate subsequent fault diagnosis and repair; 9) By combining the vehicle navigation system and traffic information, it provides intelligent chassis status optimization suggestions, such as adjusting chassis parameters according to road conditions and driving habits to improve driving safety and comfort; 10) Integrate with other vehicle systems, such as electronic stability control systems and active suspension systems, to achieve more advanced chassis control and performance optimization; 11) Utilize machine learning and artificial intelligence technologies to predict and optimize chassis status parameters in order to provide early warnings of potential problems or offer more accurate adjustment suggestions.

[0006] Preferably, the estimation of lateral motion parameters includes the estimation of sideslip angle, and the estimation of longitudinal motion parameters includes the estimation of braking pressure.

[0007] Preferably, the estimation of chassis condition parameters also includes the estimation of suspension system parameters, such as suspension system pressure and travel.

[0008] Preferably, the estimation of chassis condition parameters also includes the estimation of tire parameters, such as tire slip ratio and tire lateral force.

[0009] Preferably, the estimation of chassis state parameters is based on calculation and analysis using real-time acquired sensor data and vehicle dynamics models.

[0010] Preferably, the intelligent chassis state parameter estimation system can provide real-time chassis state information, including lateral acceleration, longitudinal acceleration, sideslip angle, and braking pressure parameters.

[0011] Preferably, the intelligent chassis state parameter estimation system can be used to evaluate the vehicle's handling performance, stability, braking performance, and acceleration performance.

[0012] Preferably, the intelligent chassis state parameter estimation system can be combined with the vehicle control system to provide real-time driving assistance and safety prompts, such as dynamic stability control and grip control.

[0013] Preferably, the intelligent chassis state parameter estimation system can improve driving safety and driving experience, and provide the driver with accurate chassis state information and driving assistance functions.

[0014] Compared with the prior art, the present invention provides an intelligent chassis state parameter estimation system based on a vehicle dynamics model, which has the following advantages: 1. Enhanced driving safety: By estimating chassis status parameters in real time, the system can provide the driver with accurate chassis status information and real-time driving assistance. This helps remind the driver to pay attention to the vehicle's handling, stability, and braking performance, thereby reducing the risk of accidents.

[0015] 2. Improved Driving Experience: The intelligent chassis state parameter estimation system can provide real-time chassis state information such as lateral acceleration and longitudinal acceleration. This helps the driver better understand the vehicle's motion status, enhancing driving confidence and comfort.

[0016] 3. Optimize vehicle performance: By estimating and analyzing chassis parameters in real time, the intelligent system can assess the vehicle's handling, stability, and braking performance. This helps optimize the vehicle's design and tuning, enabling it to perform better under different road conditions and driving needs.

[0017] 4. Energy Saving: The intelligent chassis state parameter estimation system can provide real-time information such as longitudinal acceleration and braking pressure. This helps the driver better understand the vehicle's acceleration and braking behavior, thereby achieving more efficient driving operations, further saving energy and reducing carbon emissions.

[0018] 5. Personalized Driving Settings: Based on chassis state parameter estimation, the intelligent system can adjust the vehicle's dynamic characteristics and driving feel according to the driver's preferences and needs. This allows drivers to personalize their driving settings to provide a driving experience more suited to their driving style. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the method flow of the present invention. Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0021] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] A smart chassis state parameter estimation system based on a vehicle dynamics model includes the following steps: 1) Collect chassis state-related data, such as vehicle speed, acceleration, and brake pressure, through vehicle sensors; 1.1) Vehicle speed sensor: Use wheel speed sensors or GPS modules to obtain the current speed information of the vehicle; 1.2) Acceleration sensor: Through the acceleration sensor installed on the vehicle, the acceleration information of the vehicle during acceleration, deceleration, or turning can be measured. 1.3) Brake Sensors: Sensors in the braking system acquire brake pedal status information, including brake pressure, to understand the vehicle's braking force and braking status; 2) Preprocessing of the collected data, including filtering, calibration, and denoising; 2.1) Filtering: Using digital filters, the collected data is smoothed to remove noise and abrupt changes; 2.2) Calibration: The data collected by the sensors is calibrated to eliminate sensor errors and biases, thereby improving data accuracy; 2.3) Denoising: The collected data is denoised using signal processing algorithms to remove noise introduced by sensors or environmental factors, improving data reliability; 3) Establishing a vehicle dynamics model, considering parameters such as vehicle mass, suspension characteristics, and tire characteristics; 3.1) Vehicle Mass: Considering the influence of the vehicle's total weight and center of gravity position on the vehicle's dynamic characteristics; 3.2) Suspension Characteristics: Considering parameters such as the stiffness, damping, and geometry of the vehicle's suspension system, as well as the impact of the suspension system on the vehicle's dynamic performance; 3.3) Tire Characteristics: Considering parameters such as tire friction and lateral stiffness, as well as the impact of tires on vehicle handling performance; 4) Based on Collect data and dynamic models, and use parameter estimation algorithms to estimate chassis state parameters, such as lateral acceleration and longitudinal acceleration; 4.1) Lateral acceleration estimation: By analyzing the vehicle's lateral acceleration, we can understand the vehicle's lateral motion when cornering; 4.2) Longitudinal acceleration estimation: By analyzing the vehicle's longitudinal acceleration, we can understand the vehicle's longitudinal motion during acceleration and braking; 5) Analyze and predict chassis state, such as evaluating the vehicle's handling performance and stability; 5.1) Handling performance evaluation: By analyzing the vehicle's chassis state, such as acceleration and steering angle, we can... 5.2) Stability prediction: By analyzing the vehicle's chassis condition, such as roll angle and lateral force, the vehicle's stability and performance under different driving conditions can be predicted; 6) Combined with the vehicle control system, it provides driving assistance and safety prompts, such as dynamic stability control and grip control; 6.1) Dynamic stability control: By adjusting the vehicle's suspension system, brake force distribution and other parameters in real time according to chassis condition information, dynamic stability control function is provided to maintain the vehicle's stability under various driving conditions;6.2) Grip Control: By monitoring the vehicle's chassis status and tire grip, implement appropriate control strategies to maximize vehicle grip, prevent tire slippage, and improve vehicle handling performance and safety; 7) Increase the ability to monitor and analyze chassis status in real time, including detecting the working status of the chassis's suspension system, braking system, steering system, etc., and identifying potential faults or abnormalities; 8) Provide historical data recording and analysis of chassis status for subsequent fault diagnosis and repair; 9) Combine vehicle navigation system and traffic information to provide intelligent chassis status optimization suggestions, such as adjusting chassis parameters according to road conditions and driving habits to improve driving safety and comfort; 10) Integrate with other vehicle systems, such as cooperating with vehicle electronic stability control systems and active suspension systems, to achieve more advanced chassis control and performance optimization; 11) Utilize machine learning and artificial intelligence technologies to predict and optimize chassis status parameters to provide early warning of potential problems or more accurate adjustment suggestions. The estimation of lateral motion parameters includes the estimation of sideslip angle, and the estimation of longitudinal motion parameters includes the estimation of braking pressure. The estimation of chassis state parameters also includes the estimation of suspension system parameters, such as suspension system pressure and travel. Furthermore, the estimation of tire parameters, such as tire slip ratio and tire lateral force, is also included. The estimation of chassis state parameters is based on calculations and analysis using real-time collected sensor data and vehicle dynamics models. The intelligent chassis state parameter estimation system can provide real-time chassis state information, including lateral acceleration, longitudinal acceleration, sideslip angle, and braking pressure parameters. This system can be used to evaluate the vehicle's handling performance, stability, braking performance, and acceleration performance. In conjunction with the vehicle control system, it can provide real-time driving assistance and safety prompts, such as dynamic stability control and grip control. This system improves driving safety and experience by providing the driver with accurate chassis state information and driving assistance functions. Enhanced driving safety: By estimating chassis state parameters in real time, the system can provide the driver with accurate chassis state information and real-time driving assistance. This helps remind drivers to pay attention to the vehicle's handling, stability, and braking performance, thereby reducing the risk of accidents; improves the driving experience: the intelligent chassis state parameter estimation system can provide real-time chassis state information such as lateral acceleration and longitudinal acceleration. This helps drivers better understand the vehicle's motion status, increasing driving confidence and comfort; optimizes vehicle performance: through real-time estimation and analysis of chassis state parameters, the intelligent system can evaluate the vehicle's handling, stability, and braking performance. This helps optimize the vehicle's design and tuning, making it perform better under different road conditions and driving needs;Energy Saving: The intelligent chassis state parameter estimation system can provide real-time information such as longitudinal acceleration and braking pressure. This helps the driver better understand the vehicle's acceleration and braking behavior, thereby achieving more efficient driving operations, further saving energy and reducing carbon emissions; Personalized Driving Settings: Based on the estimation of chassis state parameters, the intelligent system can adjust the vehicle's dynamic characteristics and driving feel according to the driver's preferences and needs. This allows the driver to personalize driving settings according to their own preferences, providing a driving experience that better matches their driving style; In summary, the intelligent chassis state parameter estimation system based on vehicle dynamics models has multiple beneficial effects, such as improving driving safety, enhancing the driving experience, optimizing vehicle performance, saving energy, and enabling personalized driving settings. Although embodiments of the 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 to these embodiments without departing from the principles and spirit of the invention, the scope of which is limited by the appended claims and their equivalents.

Claims

1. A smart chassis state parameter estimation system based on a vehicle dynamics model, characterized in that, Includes the following steps: 1) Collect chassis status data through vehicle sensors, including vehicle speed, acceleration, and brake pressure; 1.1) Vehicle speed sensor: Uses wheel speed sensors or GPS modules to obtain the vehicle's current speed information; 1.2) Acceleration sensor: The acceleration information of the vehicle during acceleration, deceleration or turning is measured by the acceleration sensor installed in the vehicle; 1.3) Brake sensors: The brake system sensors acquire information about the brake pedal status, including brake pressure, to understand the vehicle's braking force and braking status. 2) Preprocess the collected data, including filtering, calibration, and noise reduction; 2.1) Filtering: By using digital filters, the acquired data is smoothed to remove noise and abrupt changes; 2.2) Calibration Process: The data acquired by the sensor is calibrated to eliminate sensor errors and biases, thereby improving the accuracy of the data; 2.3) Noise Reduction Processing: The acquired data is denoised by using signal processing algorithms to remove noise introduced by sensors or environmental factors, thereby improving the reliability of the data. 3) Establish a dynamic model of the vehicle, taking into account the vehicle's mass, suspension characteristics, and tire characteristics; 3.1) Vehicle mass: Consider the impact of the vehicle's total weight and center of gravity position on the vehicle's dynamic characteristics; 3.2) Suspension characteristics: Consider the stiffness, damping, and geometry of the vehicle suspension system, as well as the impact of the suspension system on the vehicle's dynamic performance; 3.3) Tire characteristics: Consider the tire's friction and lateral stiffness, as well as the tire's impact on vehicle handling performance; 4) Based on the collected data and dynamic model, the lateral acceleration and longitudinal acceleration of the chassis state parameters are estimated using a parameter estimation algorithm; 4.1) Lateral acceleration estimation: By analyzing the vehicle's lateral acceleration, we can understand the vehicle's lateral motion when driving in a curve; 4.2) Longitudinal acceleration estimation: By analyzing the vehicle's longitudinal acceleration, we can understand the vehicle's longitudinal motion during acceleration and braking; 5) Analyze and predict chassis condition, and evaluate vehicle handling performance and stability; 5.1) Handling performance evaluation: By analyzing the vehicle's chassis condition, acceleration, and steering angle, the vehicle's handling performance and the degree of response of the vehicle to driver commands are evaluated. 5.2) Stability prediction: By analyzing the vehicle's chassis condition, roll angle, and lateral force, the vehicle's stability and performance under different driving conditions are predicted. 6) In conjunction with the vehicle control system, it provides driving assistance and safety prompts, dynamic stability control, and grip control; 6.1) Dynamic stability control: By adjusting the vehicle's suspension system and braking force distribution in real time based on chassis status information, dynamic stability control function is provided to maintain the vehicle's stability under various driving conditions; 6.2) Grip Control: By monitoring the vehicle's chassis condition and tire grip, appropriate control strategies are implemented to maximize vehicle grip and prevent tire slippage, thereby improving vehicle handling performance and safety. 7) Enhance the ability to monitor and analyze chassis status in real time, including detecting the operating status of the chassis's suspension, braking, and steering systems, as well as identifying potential faults or abnormal conditions; 8) Provide historical data recording and analysis of chassis status to facilitate subsequent fault diagnosis and repair; 9) By combining the vehicle navigation system and traffic information, it provides intelligent chassis status optimization suggestions and adjusts chassis parameters according to road conditions and driving habits to improve driving safety and comfort; 10) Integrate with other vehicle systems, and work in conjunction with vehicle electronic stability control systems and active suspension systems to achieve more advanced chassis control and performance optimization; 11) Utilize machine learning and artificial intelligence technologies to predict and optimize chassis status parameters in order to provide early warnings of potential problems or offer more accurate adjustment suggestions.

2. The intelligent chassis state parameter estimation system based on a vehicle dynamics model according to claim 1, characterized in that, The estimation of lateral motion parameters includes the estimation of sideslip angle, and the estimation of longitudinal motion parameters includes the estimation of braking pressure.

3. The intelligent chassis state parameter estimation system based on a vehicle dynamics model according to claim 1, characterized in that, The estimation of chassis condition parameters also includes the estimation of suspension system parameters, including suspension system pressure and travel.

4. The intelligent chassis state parameter estimation system based on a vehicle dynamics model according to claim 1, characterized in that, The estimation of chassis condition parameters also includes the estimation of tire parameters, including tire slip ratio and tire lateral force.

5. The intelligent chassis state parameter estimation system based on a vehicle dynamics model according to claim 1, characterized in that, The estimation of chassis condition parameters is based on calculation and analysis using real-time sensor data and vehicle dynamics models.

6. The intelligent chassis state parameter estimation system based on a vehicle dynamics model according to claim 1, characterized in that, The intelligent chassis status parameter estimation system can provide real-time chassis status information, including lateral acceleration, longitudinal acceleration, sideslip angle, and braking pressure parameters.

7. The 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 can be used to evaluate the vehicle's handling performance, stability, braking performance, and acceleration performance.

8. The 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 can be combined with the vehicle control system to provide real-time driving assistance and safety prompts, including dynamic stability control and grip control.

9. The 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 can improve driving safety and driving experience, and provide drivers with accurate chassis state information and driving assistance functions.

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