Active control system and method for improving driving comfort of commercial vehicle

Abstract

The invention relates to the technical field of vehicle chassis suspensions and vehicle body suspensions, in particular to an active control system and method for improving the driving comfort of a commercial vehicle, and aims to solve the problem that the driving comfort and the handling stability of the commercial vehicle are insufficient under complex and changeable road conditions. The system is mainly composed of a road condition sensing module, a posture sensing and predicting module, a response analysis module, an active control center, a chassis servo control module, a vehicle body servo control module, a suspension and a suspension adjusting actuating mechanism, and a closed-loop control system is formed. Through the technical means of real-time road condition sensing, posture sensing and prediction, vibration response analysis, suspension and suspension independent adjustment, introduction of an advanced control algorithm and the like, the driving comfort and the handling stability of the commercial vehicle can be remarkably improved, and a new thought and method are provided for development of the commercial vehicle suspension and suspension active control technology.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle chassis suspension and body suspension, specifically to an active control system and method aimed at improving the driving comfort of commercial vehicles. BACKGROUND

[0002] With the rapid development of the automotive industry, the requirements for driving comfort and handling stability of commercial vehicles are increasing. Traditional chassis suspension and body suspension systems have been difficult to meet the needs of complex and variable road conditions. Active suspension and suspension systems can significantly improve the ride comfort and handling stability of vehicles through real-time sensing and intelligent adjustment of parameters. However, the existing active suspension and active suspension systems often have problems such as response lag and complex tuning. SUMMARY

[0003] The purpose of the present application is to provide an active control system and method aimed at improving the driving comfort of commercial vehicles, which uses highly integrated system components and advanced control strategies to intelligently adjust suspension and suspension parameters through real-time road condition sensing, body posture sensing and prediction, and real-time response analysis of chassis and body, significantly improving the driving comfort and handling stability of commercial vehicles under complex and variable road conditions.

[0004] To achieve the above purpose, the present application provides the following technical solutions: an active control system aimed at improving the driving comfort of commercial vehicles, which comprehensively integrates the following key components and technical features:

[0005] Road condition sensing module: this module is composed of a group of high-precision and high-sensitivity vehicle-mounted sensors, including but not limited to radar sensors, optical cameras, and interfaces with external data sources. Sensors and data sources work together to capture and analyze real-time road roughness information in front of the vehicle, including road undulation, potholes, slope, and road surface material changes, providing accurate and comprehensive data basis for subsequent posture estimation and suspension adjustment;

[0006] Posture sensing and prediction module: this posture sensing module is based on high-performance three-dimensional motion posture measurement technology, including but not limited to precision gyroscopes, precision electronic compasses, accelerometers, displacement sensors, and inclination sensors, which can obtain real-time three-dimensional posture data of the chassis and body. The posture prediction module is built-in with advanced algorithms and models, such as physical models, statistical learning models or deep neural network models, which can quickly and accurately estimate the optimal posture of the vehicle when driving on the sensed road surface based on the data provided by the road condition sensing module and the current state of the vehicle. The estimation process takes into account the vehicle dynamics, suspension system characteristics and driver preferences to calculate the expected body posture value that best meets the current driving conditions;

[0007] Active suspension controller: As one of the cores of the active control center, the active suspension controller receives the road unevenness information from the road condition perception module, the chassis attitude expectation value from the attitude perception and estimation module, and calculates the specific suspension adjustment instructions according to the real-time vehicle dynamics, chassis vibration response and driver input through the built-in advanced control algorithm. The control algorithm also iteratively optimizes the adjustment instructions in combination with the real-time vibration response feedback to minimize the chassis vibration response. The instructions aim to achieve optimal adjustment of the suspension system to maximize the ride comfort and handling stability of the vehicle chassis;

[0008] Active suspension controller: As one of the cores of the active control center, the active suspension controller receives the road unevenness information from the road condition perception module, the chassis attitude expectation value from the attitude perception and estimation module, and calculates the specific suspension adjustment instructions according to the real-time vehicle dynamics, chassis vibration response and driver input through the built-in advanced control algorithm. The control algorithm also iteratively optimizes the adjustment instructions in combination with the real-time vibration response feedback to minimize the chassis vibration response. The instructions aim to achieve optimal adjustment of the suspension system to maximize the ride comfort and handling stability of the vehicle chassis;

[0009] Chassis servo control module: The chassis servo control module is responsible for receiving instructions from the active suspension controller and accurately controlling the suspension actuator mechanism connecting the vehicle frame and the axle. The actuator mechanism includes solenoid valves, motors, hydraulic pumps, which can independently or cooperatively adjust the stiffness, damping, height or inclination angle of the suspension according to the instructions to adapt to road changes and improve the handling and ride comfort of the chassis.

[0010] Suspension adjustment actuator mechanism: As the actuator of the active suspension system, the suspension actuator mechanism directly responds to the instructions from the chassis servo control module, adjusts the suspension parameters through mechanical, hydraulic or electromagnetic methods, and realizes dynamic adjustment of the vehicle chassis attitude. The actuator mechanism has high precision, high response speed and high reliability to ensure that the suspension system can accurately and quickly respond to road conditions and vehicle state changes.

[0011] Vehicle body servo control module: The vehicle body servo control module is responsible for receiving instructions from the active suspension controller and accurately controlling the suspension actuator mechanism connecting the vehicle frame and the vehicle body. The actuator mechanism includes solenoid valves, motors, hydraulic pumps, which can independently or cooperatively adjust the stiffness, damping, height or inclination angle of the suspension according to the instructions to adapt to the real-time changes of the chassis attitude and vibration, ensure the stability of the vehicle body attitude and improve the driving comfort of the vehicle.

[0012] Suspension adjustment actuator: As the actuator of the active suspension system of the cab, the suspension actuator directly responds to the instructions of the vehicle body controller, adjusts the suspension parameters through mechanical, hydraulic or electromagnetic methods, and realizes the dynamic adjustment of the vehicle body posture and suspension stiffness and damping. The actuator has high precision, high response speed and high reliability to ensure that the suspension system can accurately and quickly respond to road conditions and vehicle state;

[0013] The response analysis module can obtain and process the chassis and in-vehicle vibration acceleration signals in real time, and feed the obtained signal time domain and frequency domain characteristics to the active control center to provide data support for the iteration and adjustment of the active control adjustment instructions.

[0014] Preferably, the road condition perception module further comprises a data processing unit responsible for pre-processing the collected road condition information, such as filtering, denoising and feature extraction, to improve the accuracy and efficiency of subsequent posture estimation.

[0015] Preferably, the posture perception and prediction module uses machine learning or deep learning algorithms that can continuously optimize the estimation model based on historical data and real-time feedback to improve the accuracy and speed of posture estimation. In addition, the posture perception and prediction module includes an online learning mechanism to update model parameters in real time to adapt to different driving environments and vehicle states.

[0016] Preferably, the active suspension and active suspension controller are built-in with multiple control modes, such as standard mode, sport mode and comfort mode. The mode can be switched according to the driver's selection or the vehicle's automatic judgment of the current driving environment. Each mode corresponds to a specific set of control parameters and strategies to meet different driving needs and preferences.

[0017] Preferably, it also includes a fault diagnosis and fault tolerance processing mechanism to ensure that the system can continue to operate in a degraded mode in case of sensor failure, actuator failure or controller abnormality, ensuring the basic safety and smoothness of the vehicle. The method can be further integrated into the electronic control unit of the vehicle to realize cooperation with other systems of the vehicle to comprehensively improve the driving performance, safety and comfort of the vehicle. The method also supports remote monitoring and diagnosis functions to monitor the performance and troubleshoot faults in real time during vehicle use.

[0018] Preferably, the method for improving the comfort of commercial vehicles includes the following detailed steps:

[0019] Step 1: Real-time acquisition of road roughness information in front of the vehicle through the road condition perception module, including road undulation, potholes and slope, and pre-processing and feature extraction of the information;

[0020] Step two: Use the pose perception and prediction module to combine the pre-processed road condition information and the current state of the vehicle, estimate the best driving pose of the vehicle through algorithms and models, and calculate the chassis and body pose expected value;

[0021] Step three: The active suspension controller calculates the chassis suspension stiffness, damping, height and inclination angle adjustment instructions based on the vehicle's best driving pose estimation results and real-time road condition information. The control algorithm also iteratively optimizes the adjustment instructions based on real-time chassis vibration response feedback to minimize chassis vibration response. The instructions aim to achieve optimal adjustment of the suspension system.

[0022] Step four: The chassis servo control module receives the instructions from the active suspension controller and accurately controls the suspension actuator for independent or collaborative adjustment to adapt to road changes and maintain stable driving of the vehicle chassis.

[0023] Step five: The active suspension control system calculates specific body suspension stiffness, damping, height and inclination angle adjustment instructions based on the body pose expected estimation results and real-time chassis vibration response information. To ensure that the parameters of the suspension and suspension systems are reasonably matched, the control algorithm also considers modal frequency avoidance and decoupling between systems. The control algorithm also iteratively optimizes the adjustment instructions based on real-time body vibration response feedback to minimize body vibration response. The instructions aim to achieve optimal adjustment of the suspension system.

[0024] Step six: The body servo control module receives the instructions from the active suspension controller and accurately controls the suspension actuator for independent or collaborative adjustment to adapt to changes in chassis pose and vibration in real time, maintaining the stability and comfort of the body.

[0025] Step seven: Based on the actual driving conditions of the vehicle and the feedback from the driver, the pose estimation model and control algorithm parameters are adjusted through the feedback mechanism to achieve continuous optimization and self-learning of the system.

[0026] Compared with the prior art, the beneficial effects of the present application are as follows:

[0027] I. System composition

[0028] Road condition perception module

[0029] Sensor configuration: This module integrates multiple high-precision sensors, including radar sensors for detecting the distance and shape changes of the road ahead, and optical cameras for capturing road images and identifying unevenness features.

[0030] Data processing: The collected road condition information is pre-processed, such as filtering, denoising and feature extraction, to eliminate interference and improve the accuracy of subsequent processing.

[0031] External Data Source Interface: The system also has an interface with external data sources such as high-precision GPS maps and road condition databases to obtain more comprehensive road condition information.

[0032] Posture Perception and Prediction Module

[0033] Sensor Configuration: This module integrates a variety of high-precision sensors, including precision gyroscopes, precision electronic compasses, accelerometers, displacement sensors, and inclination sensors, to obtain real-time three-dimensional attitude data of the vehicle body

[0034] Algorithm and Model: This module uses advanced algorithms and models, such as physical models combined with statistical learning methods or deep neural network models, to quickly estimate the optimal driving posture of the vehicle.

[0035] Considerations: The estimation process takes into account factors such as road conditions, current vehicle state (speed, load, steering, etc.), suspension system characteristics, and driver preferences.

[0036] Output: Calculate the expected value of the chassis and body posture that meets the current driving conditions, providing targets for subsequent chassis suspension and body suspension adjustment.

[0037] Active Suspension and Suspension Controller

[0038] Control Algorithm: The controller has multiple advanced control algorithms built-in, such as fuzzy logic control, neural network control, adaptive control, etc., to calculate suspension and suspension adjustment instructions according to the estimated posture and real-time road conditions.

[0039] Mode Switching: Supports multiple control mode switching, such as standard mode, sports mode, comfort mode, etc., to meet different driving needs and preferences.

[0040] Feedback Mechanism: Adjust control parameters and strategies based on actual vehicle driving conditions and driver feedback to achieve continuous optimization of the system.

[0041] Chassis Servo Controller and Suspension Actuator

[0042] Chassis Servo Controller: Receives instructions from the active suspension controller and accurately controls the suspension actuator.

[0043] Suspension Actuator: Includes solenoid valves, motors, hydraulic pumps, and other actuators that can independently or cooperatively adjust the stiffness, damping, height, or inclination angle of the suspension according to instructions.

[0044] Body Servo Controller and Suspension Actuator

[0045] Body Servo Controller: Receives instructions from the active suspension controller and accurately controls the suspension actuator.

[0046] Suspension Actuation Mechanism: Includes solenoid valves, motors, hydraulic pumps, and other actuators that can independently or cooperatively adjust the stiffness, damping, height, or inclination angle of the suspension according to instructions.

[0047] II. Control Method

[0048] Road Condition Perception and Data Processing: Real-time acquisition of road unevenness information in front through the road condition perception module, and preprocessing to improve accuracy.

[0049] Posture Perception and Prediction: Utilizing the posture estimation module and preprocessed road condition information, combined with the current state of the vehicle, to estimate the best driving posture of the vehicle and calculate the expected value of the chassis and body posture.

[0050] Suspension Control Instruction Calculation: The active suspension controller calculates specific suspension adjustment instructions based on the best driving posture estimation results and real-time road condition information through the built-in control algorithm.

[0051] Suspension Adjustment Actuation: The chassis controller receives instructions and controls the suspension actuation mechanism for independent or cooperative adjustment to adapt to road changes and maintain smooth driving of the vehicle chassis.

[0052] Suspension Control Instruction Calculation: The active suspension controller calculates specific suspension adjustment instructions based on the best driving posture estimation results and real-time road condition information through the built-in control algorithm.

[0053] Suspension Adjustment Actuation: The chassis controller receives instructions and controls the suspension actuation mechanism for independent or cooperative adjustment to adapt to road changes and maintain smooth driving of the vehicle chassis.

[0054] Feedback and Optimization (Optional): Adjust the posture estimation model and control algorithm parameters based on the actual driving conditions and driver feedback to achieve continuous optimization and self-learning of the system.

[0055] III. Technical Features and Advantages

[0056] High Integration: The system integrates various sensors, controllers, and actuators to achieve comprehensive tuning of vehicle smoothness.

[0057] Advanced Algorithms: Advanced algorithms such as machine learning and deep learning are used to improve the accuracy and speed of posture estimation.

[0058] Multi-mode Switching: Supports multiple control mode switching to meet different driving needs and preferences.

[0059] Continuous Optimization: Through the feedback mechanism, the system realizes continuous optimization and self-learning, improving the adaptability and robustness of the system.

[0060] Synergy: can work with other vehicle systems, comprehensive improve the driving performance, safety and comfort of the vehicle.

[0061] The active control system and method for improving the driving comfort of commercial vehicles provided by the present application significantly improves the driving comfort and maneuvering stability of commercial vehicles under complex and variable road conditions through highly integrated system components, advanced control strategies and technical features, providing new ideas and methods for the development of active control technology for commercial vehicle suspensions and mounts. BRIEF DESCRIPTION OF DRAWINGS

[0062] Fig. 1 The active control system of the present application and the working process schematic diagram;

[0063] Fig. 2 The fuzzy neural network control schematic diagram of the present application. DETAILED DESCRIPTION

[0064] Please refer to Figs. 1-2 The active control system for improving the driving comfort of commercial vehicles, which comprehensively integrates the following key components and technical features:

[0065] Road condition perception module 1: this module is composed of a group of high-precision and high-sensitivity vehicle-mounted sensors, including but not limited to radar sensors, optical cameras, and interfaces with external data sources (such as high-precision GPS map services, road condition databases), these sensors and data sources work together to capture and analyze the unevenness information of the road ahead in real time, including road undulation, potholes, slope, road material changes, etc., providing accurate and comprehensive data basis for subsequent attitude estimation and suspension adjustment;

[0066] Attitude perception and prediction module 2: this attitude perception module is based on high-performance three-dimensional motion attitude measurement technology, including but not limited to precision gyroscopes, precision electronic compasses, accelerometers, displacement sensors, and inclination sensors, etc. motion sensors, real-time acquisition of chassis and vehicle body three-dimensional attitude data, attitude prediction module has advanced algorithms and models built-in, such as physical models, statistical learning models or deep neural network models, which can quickly and accurately estimate the optimal attitude that the vehicle should maintain when driving on the road surface perceived based on the data provided by the road condition perception module and the current state of the vehicle (including speed, load, steering angle, braking state, current attitude, etc.), the estimation process takes into account the vehicle dynamics characteristics, suspension system characteristics and driver preferences, etc. to calculate the most suitable vehicle body attitude expectation value under the current driving conditions;

[0067] Active Suspension Controller 3-1: As one of the cores of the active control center 3, the active suspension controller receives road unevenness information from the road condition perception module, chassis attitude expectation value from the attitude perception and estimation module, and calculates specific suspension adjustment instructions through built-in advanced control algorithms (such as fuzzy logic control, neural network control, adaptive control, etc.) according to real-time vehicle dynamics, chassis vibration response and driver input. The control algorithm also iteratively optimizes the adjustment instructions in combination with real-time chassis vibration response feedback to minimize chassis vibration response. These instructions aim to achieve optimal adjustment of the suspension system to maximize the smoothness and handling stability of the vehicle chassis;

[0068] Active Suspension Controller 3-2: As another core of the active control center 3, the active suspension controller receives chassis vibration signals from the response analysis module 8, vehicle body attitude expectation value from the attitude perception and estimation module, and calculates specific suspension adjustment instructions through built-in advanced control algorithms (such as fuzzy logic control, neural network control, adaptive control, etc.) according to real-time vehicle dynamics, vehicle body vibration response and driver input. To make the parameters of the suspension and suspension system reasonable, the control algorithm also considers the modal frequency avoidance and decoupling between systems, and also iteratively optimizes the adjustment instructions in combination with real-time vehicle body vibration response feedback to minimize in-vehicle vibration response. These instructions aim to achieve optimal adjustment of the cab suspension system to always maintain the stability of the vehicle body attitude and maximize the driving comfort of the vehicle;

[0069] Chassis Servo Control Module 4: The chassis servo control module is responsible for receiving instructions from the active suspension controller and accurately controlling the suspension actuator mechanism connecting the frame and the axle. These actuators, including solenoid valves, motors, hydraulic pumps, etc., can independently or cooperatively adjust the stiffness, damping, height or inclination angle of the suspension to adapt to road changes and improve chassis handling and smoothness;

[0070] Suspension Adjustment Actuator 5: As the actuator of the active suspension system, the suspension actuator directly responds to the instructions of the chassis servo control module, adjusts the suspension parameters through mechanical, hydraulic or electromagnetic means, and realizes dynamic adjustment of the vehicle chassis attitude. These actuators have high precision, high response speed and high reliability to ensure that the suspension system can accurately and quickly respond to road conditions and vehicle status;

[0071] Vehicle Body Servo Control Module 6: The vehicle body servo control module is responsible for receiving instructions from the active suspension controller and accurately controlling the suspension actuator mechanism connecting the frame and the vehicle body. These actuators, including solenoid valves, motors, hydraulic pumps, etc., can independently or cooperatively adjust the stiffness, damping, height or inclination angle of the suspension to adapt to real-time changes in chassis attitude and vibration, ensuring stable vehicle body attitude and improving vehicle driving comfort;

[0072] Suspension adjustment actuator 7: As the actuator of the active suspension system of the cab, the suspension actuator directly responds to the instructions of the vehicle body controller, adjusts the suspension parameters through mechanical, hydraulic or electromagnetic methods, etc., realizes the dynamic adjustment of the vehicle body posture and suspension stiffness, damping, and has high precision, high response speed and high reliability, to ensure that the suspension system can accurately and quickly respond to road conditions and vehicle state;

[0073] The response analysis module 8 will obtain and process the chassis and in-vehicle vibration acceleration signals in real time, and feed the obtained signal time domain and frequency domain characteristics to the active control center, to provide data support for the iteration and adjustment of the active control adjustment instructions;

[0074] Further, the road condition perception module also includes a data processing unit responsible for pre-processing the collected road condition information, such as filtering, denoising, feature extraction, etc., to improve the accuracy and efficiency of subsequent posture estimation;

[0075] The posture perception and prediction module uses machine learning or deep learning algorithms that can continuously optimize the estimation model based on historical data and real-time feedback to improve the accuracy and speed of posture estimation. In addition, the posture perception and prediction module includes an online learning mechanism to update model parameters in real time to adapt to different driving environments and vehicle states.

[0076] Further, the active suspension and active suspension controller are built-in with multiple control modes, such as standard mode, sport mode, comfort mode, etc. These modes can be switched according to the driver's choice or the vehicle's automatic judgment of the current driving environment. Each mode corresponds to a specific set of control parameters and strategies to meet different driving needs and preferences.

[0077] Further, it also includes a fault diagnosis and fault tolerance processing mechanism to ensure that the system can continue to operate in a degraded mode in the event of sensor failure, actuator failure or controller abnormality, to ensure the basic safety and smoothness of the vehicle;

[0078] The method can be further integrated into the vehicle's electronic control unit (ECU) to realize collaborative work with other systems of the vehicle (such as the braking system, steering system, power system, etc.), to comprehensively improve the driving performance, safety and comfort of the vehicle. The method also supports remote monitoring and diagnosis functions to monitor the performance and troubleshoot faults in real time during vehicle use.

[0079] Further, the method aims to improve the comfort of commercial vehicle drivers and passengers, including the following detailed steps:

[0080] Step one: Real-time acquisition of road unevenness information in front, including road undulation, potholes, slope, etc., by road condition perception module, and pre-processing and feature extraction of these information;

[0081] Step two: Using the attitude perception and prediction module, combining the pre-processed road condition information and the current state of the vehicle, the best driving attitude of the vehicle is estimated through algorithms and models, and the chassis and body attitude expected value is calculated;

[0082] Step three: According to the best driving attitude estimation results of the vehicle and real-time road condition information, the active suspension controller calculates the suspension stiffness, damping, height and inclination angle adjustment instructions through the built-in control algorithm, and the control algorithm also iteratively optimizes the adjustment instructions combined with the real-time vibration response feedback of the chassis, so as to minimize the vibration response of the chassis. These instructions aim to achieve the optimal adjustment of the suspension system;

[0083] Step four: The chassis servo control module receives the instructions issued by the active suspension controller, and accurately controls the suspension actuator to adjust independently or cooperatively to adapt to road changes and maintain stable driving of the vehicle chassis;

[0084] Step five: According to the body attitude expected estimation results and the real-time vibration response information of the chassis, the active suspension control system calculates the specific body suspension stiffness, damping, height and inclination angle adjustment instructions through the built-in control algorithm, in order to make the parameters of the suspension and suspension system reasonable, the control algorithm also considers the modal frequency avoidance and decoupling between the systems, and iteratively optimizes the adjustment instructions combined with the real-time vibration response feedback of the body, so as to minimize the vibration response of the body. These instructions aim to achieve the optimal adjustment of the suspension system;

[0085] Step six: The body servo control module receives the instructions issued by the active suspension controller, and accurately controls the suspension actuator to adjust independently or cooperatively to adapt to the real-time changes of the chassis attitude and vibration, and maintain the stability and comfort of the body;

[0086] Step seven: According to the actual driving situation of the vehicle and the feedback of the driver, the attitude estimation model and control algorithm parameters are adjusted through the feedback mechanism to realize the continuous optimization and self-learning of the system.

[0087] I. Installation and configuration of system components

[0088] Road condition perception module

[0089] Install radar sensors, optical cameras, etc. on the front of the commercial vehicle to ensure that they can clearly perceive the unevenness information of the road in front.

[0090] Connect the accelerometer and gyroscope to the electronic control unit (ECU) of the vehicle to obtain real-time motion state data of the vehicle.

[0091] Configure external data source interfaces, such as high-precision GPS receivers, to obtain more comprehensive road condition information.

[0092] Posture estimation module

[0093] Install or integrate the posture estimation algorithm and model in the vehicle's ECU.

[0094] Parameterize the algorithm and model according to the specific parameters of the vehicle and the characteristics of the suspension system.

[0095] Ensure that the posture estimation module can receive and process data from the road condition perception module in real time.

[0096] Active suspension and suspension controller

[0097] Install or integrate the active suspension and suspension control algorithm in the ECU.

[0098] Parameterize the control algorithm according to the comfort targets of the vehicle and the body posture control requirements, combined with the characteristics of the suspension and suspension system.

[0099] Ensure that the active suspension controller can receive and process data from the road surface perception module and the posture perception and prediction module in real time, calculate and output suspension control instructions.

[0100] Ensure that the active suspension controller can receive and process data from the posture perception and prediction module and the response analysis module in real time, calculate and output suspension control instructions.

[0101] Chassis servo controller and suspension actuator

[0102] Install the chassis servo controller and ensure that it can receive instructions from the active suspension controller and accurately control the suspension actuator.

[0103] According to the configuration of the vehicle's suspension system, install the corresponding suspension actuator, such as solenoid valves, motors, hydraulic pumps, etc., to ensure that they can accurately respond to the instructions of the chassis servo controller.

[0104] Body servo controller and suspension actuator

[0105] Install the body servo controller and ensure that it can receive instructions from the active suspension controller and accurately control the suspension actuator.

[0106] According to the configuration of the vehicle's body suspension system, install the corresponding suspension actuator, such as solenoid valves, motors, hydraulic pumps, etc., to ensure that they can accurately respond to the instructions of the body servo controller.

[0107] II. Development and debugging of software algorithms

[0108] Road condition perception algorithm

[0109] Develop analysis algorithms for processing data collected by radar sensors, optical cameras, etc. to extract unevenness information of the road ahead.

[0110] Debug and optimize the algorithm to ensure it can accurately and quickly perceive changes in road conditions.

[0111] Posture perception algorithm

[0112] Develop analysis algorithms for processing data collected by precision gyroscopes, precision electronic compasses, accelerometers, etc. to obtain real-time three-dimensional posture data of the chassis and vehicle body.

[0113] Debug and optimize the algorithm to ensure it can accurately and quickly perceive changes in vehicle state.

[0114] Posture estimation algorithm

[0115] Develop posture estimation algorithms based on physical models, statistical learning methods or deep neural network models.

[0116] Train and test the algorithm according to the specific parameters of the vehicle and the characteristics of the suspension system to ensure it can accurately estimate the optimal driving posture of the vehicle.

[0117] Active suspension control algorithm

[0118] Develop control algorithms for calculating chassis stability and smoothness, such as fuzzy logic control, neural network control, adaptive control, etc.

[0119] Debug and optimize the control algorithm to ensure it can accurately output suspension adjustment control instructions based on the optimal driving posture estimation results and real-time road condition information.

[0120] Active suspension control algorithm

[0121] Develop control algorithms for calculating vehicle body stability and comfort, such as fuzzy logic control, neural network control, adaptive control, etc.

[0122] Debug and optimize the control algorithm to ensure it can accurately output suspension adjustment control instructions based on the body posture expectation estimation results and real-time vibration response information of the chassis and vehicle body, etc.

[0123] System integration and testing

[0124] Integrate road condition perception algorithms, posture perception and prediction algorithms, and active suspension and suspension control algorithms into the vehicle's ECU.

[0125] Test the integrated system to ensure that communication between components is normal and that the system can accurately and quickly respond to changes in road conditions and vehicle state.

[0126] III. Testing and Validation on Actual Vehicles

[0127] Road Testing

[0128] Actual driving tests are conducted on different types of roads (such as highways, urban roads, rural roads, etc.) to verify the effectiveness of the ride comfort tuning.

[0129] Vehicle motion state data, suspension and mount adjustment, and driver feedback during testing are recorded.

[0130] Performance Evaluation

[0131] Based on the test data, the ride comfort tuning performance of the system is evaluated, including the stability, comfort, and maneuverability of the vehicle under different road conditions.

[0132] Comparisons are made with traditional suspension and mount systems to analyze the advantages and disadvantages of the system.

[0133] Optimization and Improvement

[0134] Based on the performance evaluation results, the system components, algorithms, and control strategies are optimized and improved.

[0135] Iterative testing is conducted until satisfactory ride comfort tuning results are achieved.

[0136] User Feedback and Market Promotion

[0137] User feedback is collected to understand user satisfaction with system performance and use.

[0138] Based on user feedback, further optimization and improvement are made to enhance user experience.

[0139] The optimized system is brought to market for commercial application and promotion.

[0140] In summary, the specific embodiments of the invention involve the installation and configuration of system components, the development and debugging of software algorithms, and the testing and validation on actual vehicles. Through these steps, the system can accurately and quickly perceive road condition changes and accurately output suspension control instructions based on vehicle optimal driving posture estimation results and real-time road condition information, achieving good vehicle chassis handling and ride comfort. Further, based on body posture expectation estimation results and chassis, body real-time vibration response information, etc., accurate mount control instructions are output, achieving stable body posture and good ride comfort.

[0141] While embodiments of the application have been shown and described, it is to be understood that the embodiments described are merely exemplary of the principles and application of the present application. Numerous modifications and adaptions can be effected without departing from the spirit and scope of the present application, which is not limited to the exact construction and arrangement described. It is intended, therefore, to cover all modifications and adaptions that fall within the scope of the claims and their equivalents.

Claims

1. An active control system designed to improve driving comfort in commercial vehicles, characterized by: The system fully integrates the following key components and technical features: Road condition perception module (1): This module consists of a set of high-precision, high-sensitivity on-board sensors, including but not limited to radar sensors, optical cameras, and interfaces with external data sources. The sensors and data sources work together to capture and analyze the unevenness information of the road ahead in real time, including road undulations, potholes, slopes, and changes in road surface material, providing an accurate and comprehensive data foundation for subsequent posture estimation and suspension adjustment. Posture perception and prediction module (2): This posture perception module is based on high-performance three-dimensional motion posture measurement technology, including but not limited to precision gyroscopes, precision electronic compasses, accelerometers, displacement sensors, and inclination sensors, to obtain real-time three-dimensional posture data of the chassis and body. The posture prediction module has built-in advanced algorithms and models, such as physical models, statistical learning models, or deep neural network models. They can quickly and accurately estimate the optimal posture that the vehicle should maintain when driving on the perceived road surface based on the data provided by the road condition perception module and the current state of the vehicle. The estimation process takes into account the vehicle dynamics, suspension system characteristics, and driver preferences to calculate the expected value of the body posture that best meets the current driving conditions; Active suspension controller (3-1): As one of the core components of the active control center (3), the active suspension controller receives road roughness information from the road condition perception module and chassis attitude expectations from the attitude perception and prediction module. Based on real-time vehicle dynamics, chassis vibration response, and driver input, it calculates specific suspension adjustment instructions through a built-in advanced control algorithm. The control algorithm also iteratively optimizes the adjustment instructions based on the real-time chassis vibration response feedback to minimize the chassis vibration response. The instructions are designed to achieve optimal adjustment of the suspension system to maximize the vehicle chassis's smoothness and handling stability. Active suspension controller (3-2): As another core of the active control center (3), the active suspension controller receives chassis vibration signals from the response analysis module (8) and the expected value of the vehicle body posture from the posture perception and estimation module. Based on the real-time vehicle dynamics, vehicle body vibration response and driver input, it calculates specific suspension adjustment instructions through the built-in advanced control algorithm. In order to make the parameters of the suspension and suspension system match reasonably, the control algorithm also considers modal frequency avoidance and decoupling between the systems. At the same time, it will iteratively optimize the adjustment instructions based on the real-time vibration response feedback of the vehicle body to minimize the vibration response in the vehicle. The instructions are designed to achieve the optimal adjustment of the cab suspension system to always keep the vehicle body posture stable and maximize the driving comfort of the vehicle. Chassis servo control module (4): The chassis servo control module is responsible for receiving instructions from the active suspension controller and accurately controlling the suspension actuator connecting the frame and the axle. The actuator includes a solenoid valve, a motor, and a hydraulic pump. They can independently or collaboratively adjust the stiffness, damping, height or tilt angle of the suspension according to the instructions to adapt to changes in the road surface and improve the chassis handling stability and smoothness; Suspension adjustment actuator (5): As the actuator of the active suspension system, the suspension actuator directly responds to the instructions of the chassis servo control module and adjusts the suspension parameters through mechanical, hydraulic or electromagnetic means to achieve dynamic adjustment of the vehicle chassis posture. The actuator has high precision, high response speed and high reliability to ensure that the suspension system can accurately and quickly respond to changes in road conditions and vehicle status; Body servo control module (6): The body servo control module is responsible for receiving instructions from the active suspension controller and accurately controlling the suspension actuator connecting the frame and the body. The actuator includes a solenoid valve, a motor, and a hydraulic pump. They can independently or collaboratively adjust the stiffness, damping, height or tilt angle of the suspension according to the instructions to adapt to the chassis posture and vibration changes in real time, ensuring the stability of the body posture and improving the driving comfort of the vehicle; Suspension adjustment actuator (7): As the actuator of the active cab suspension system, the suspension actuator directly responds to the instructions of the vehicle body controller and adjusts the suspension parameters through mechanical, hydraulic or electromagnetic means to achieve dynamic adjustment of the vehicle body posture and suspension stiffness and damping. The actuator has high precision, high response speed and high reliability to ensure that the suspension system can accurately and quickly respond to changes in road conditions and vehicle status; The response analysis module (8) will acquire and process the chassis and vehicle interior vibration acceleration signals in real time, and feed back the obtained signal time domain and frequency domain characteristics to the active control center to provide data support for the iteration and adjustment of the active control adjustment instructions.

2. The active control system for improving driving comfort of commercial vehicles according to claim 1, characterized in that: The road condition perception module also includes a data processing unit, which is responsible for preprocessing the collected road condition information, such as filtering, denoising, and feature extraction, to improve the accuracy and efficiency of subsequent posture estimation.

3. The active control system for improving driving comfort of commercial vehicles according to claim 1, characterized in that: The posture perception and prediction module uses a machine learning or deep learning algorithm that can continuously optimize the estimation model based on historical data and real-time feedback to improve the accuracy and speed of posture estimation. In addition, the posture perception and prediction module includes an online learning mechanism to update model parameters in real time to adapt to different driving environments and vehicle conditions.

4. The active control system for improving driving comfort of commercial vehicles according to claim 1, characterized in that: The active suspension and active suspension controller have built-in multiple control modes, such as standard mode, sport mode, and comfort mode. The modes can be switched based on the driver's selection or the vehicle's automatic judgment of the current driving environment. Each mode corresponds to a specific set of control parameters and strategies to meet different driving needs and preferences.

5. The active control system for improving driving comfort of commercial vehicles according to claim 1, characterized in that: It also includes a fault diagnosis and fault-tolerant processing mechanism to ensure that the system can continue to operate in a degraded mode in the event of sensor failure, actuator failure, or controller abnormality, thereby ensuring basic vehicle safety and ride quality. This method can be further integrated into the vehicle's electronic control unit to achieve collaborative work with other vehicle systems to comprehensively improve the vehicle's driving performance, safety, and comfort. The method also supports remote monitoring and diagnostic functions to enable real-time performance monitoring and troubleshooting during vehicle use.

6. The method for improving the driving comfort of a commercial vehicle according to claim 1, characterized in that The detailed steps include: Step 1: The road condition perception module obtains real-time information about road roughness ahead, including road undulations, potholes, and slopes, and performs preprocessing and feature extraction on the information. Step 2: Using the posture perception and prediction module, combined with pre-processed road condition information and the vehicle's current state, the algorithm and model are used to estimate the vehicle's optimal driving posture and calculate the expected values ​​of the chassis and body posture; Step 3: Based on the vehicle's predicted optimal driving posture and real-time road conditions, the active suspension controller uses a built-in control algorithm to preliminarily calculate chassis suspension stiffness, damping, height, and tilt angle adjustment commands. The control algorithm also iteratively optimizes these adjustment commands based on real-time chassis vibration response feedback to minimize chassis vibration response. The commands are designed to achieve optimal suspension system adjustment. Step 4: The chassis servo control module receives instructions from the active suspension controller and accurately controls the suspension actuators to make independent or coordinated adjustments to adapt to road surface changes and maintain a stable vehicle chassis. Step 5: The active mount control system uses a built-in control algorithm to calculate specific adjustments for the vehicle's suspension stiffness, damping, height, and tilt angle based on the expected vehicle posture estimate and the chassis' real-time vibration response. To ensure proper parameter matching between the mount and suspension system, the control algorithm also considers modal frequency avoidance and decoupling between the systems. Furthermore, the control algorithm iteratively optimizes the adjustment instructions based on the vehicle's real-time vibration response feedback to minimize the vehicle's vibration response. The instructions are designed to achieve optimal adjustment of the suspension system. Step 6: The body servo control module receives commands from the active mount controller and precisely controls the suspension actuators to perform independent or coordinated adjustments to adapt to chassis posture and vibration changes in real time, maintaining vehicle stability and comfort. Step 7: Based on the actual vehicle driving conditions and driver feedback, the posture estimation model and control algorithm parameters are adjusted through the feedback mechanism to achieve continuous optimization and self-learning of the system.

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