Vehicle lateral stability coordinated control system based on multi-source sensor fusion

Abstract

The present invention relates to the technical field of vehicle lateral stability control, and discloses a vehicle lateral stability coordinated control system based on multi-source sensor fusion, which includes a multi-source sensor module, a fusion decision module, a control execution module, a state evaluation module, and a coordinated optimization module. The multi-source sensor module deploys multiple types of sensors to collect and pre-process vehicle lateral motion parameters, tire adhesion parameters, etc.; the fusion decision module constructs a data fusion model and control rules, and dynamically simulates control parameters; the control execution module transmits the rules to steering, braking, and other mechanisms, adjusts the output power, and transmits feedback data back; the state evaluation module standardizes the data, calculates a first evaluation index, compares it with a baseline threshold, and preliminarily evaluates stability; the coordinated optimization module calculates a second evaluation index in combination with road environment parameters when unstable, and conducts a secondary evaluation and adjusts the control instructions. This system is applicable to the field of active safety control of various types of vehicles.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle lateral stability control, and in particular to a vehicle lateral stability coordinated control system based on multi-source sensor fusion. Background Art

[0002] In modern vehicle engineering, vehicle lateral stability control is a key technology for ensuring driving safety. With the increasing intelligence and automation of vehicles, traditional single sensors or simple control systems are no longer able to meet the stability control requirements under complex operating conditions.

[0003] Vehicle lateral stability control faces multiple challenges in existing technologies. On the one hand, traditional systems often rely on a single type of sensor (such as wheel speed sensors or inertial measurement units). Due to the limited sensor coverage parameters, it is difficult to fully capture multi-dimensional data such as the vehicle's lateral motion characteristics, tire adhesion status, and steering system response. This leads to insufficient data acquisition accuracy on complex road surfaces (such as slippery, icy, and snowy roads) or in emergency steering conditions, which in turn affects the accuracy of stability control. On the other hand, existing control strategies often independently control systems such as steering, braking, and power distribution, lacking a collaborative optimization mechanism for multiple actuators. This leads to prominent problems such as asynchronous responses between systems and control logic conflicts, making it difficult to achieve global optimal control of lateral stability. For example, when the vehicle understeers or oversteers, independent braking intervention and steering power adjustment may cause the vehicle's posture to lose control due to insufficient coordination.

[0004] Existing assessment systems often rely solely on vehicle motion parameters to determine stability, failing to fully incorporate factors such as tire adhesion and actuator response delay. Furthermore, they lack dynamic integration and analysis of road environment parameters. This results in an inability to adjust control strategies in response to sudden changes in road adhesion or actuator performance degradation, posing a safety hazard. Furthermore, traditional control parameter calibration often relies on offline presets, making it difficult to dynamically optimize based on real-time operating conditions. This results in poor system adaptability to varying loads, vehicle speeds, and road conditions.

[0005] In response to the above problems, the present invention proposes a vehicle lateral stability coordination control system with multi-source sensor fusion. Through the coordinated deployment of multiple types of sensors, multi-source data fusion modeling, coordinated control of actuators and multi-level dynamic evaluation, it solves the problems of one-sided data collection, insufficient system coordination, poor environmental adaptability in the existing technology, and improves the vehicle's lateral stability control accuracy and safety under complex working conditions. Summary of the Invention

[0006] The purpose of the present invention is to provide a vehicle lateral stability coordinated control system based on multi-source sensor fusion to solve the problems raised in the above background technology.

[0007] To achieve the above objectives, the present invention provides the following technical solutions: a vehicle lateral stability coordinated control system based on multi-source sensor fusion, the system comprising a multi-source sensor module, a fusion decision module, a control execution module, a state evaluation module and a coordinated optimization module;

[0008] The multi-source sensing module is used to deploy multiple types of sensors in the vehicle's steering system, suspension system, and key body parts, and collect vehicle lateral motion parameters, tire adhesion parameters, and steering system status data in real time, while performing preliminary screening and format conversion on the collected data.

[0009] The fusion decision module is used to build a multi-source sensor data fusion model and use information fusion technology to analyze the vehicle's lateral motion characteristics. At the same time, it uses control strategy generation technology to build lateral stability control rules and dynamically simulate the vehicle's lateral stability control parameters based on real-time collected vehicle motion parameters and system status data;

[0010] The control execution module is used to transmit the generated lateral stability control rules to the vehicle steering actuator, brake actuator and power distribution mechanism to perform execution instruction encoding and output power adjustment, and transmit execution feedback data back to the state evaluation module;

[0011] The state evaluation module is used to perform a preliminary comparative evaluation and analysis of the vehicle's lateral motion stability after normalizing the acquired lateral motion parameters, tire adhesion parameters, and execution feedback data;

[0012] The coordination optimization module is used to further calculate and obtain a second evaluation index in combination with road environment parameters when analyzing that the vehicle's lateral motion is unstable, and to preset a second benchmark threshold and perform a secondary comparative evaluation with the second evaluation index to further analyze the performance of the vehicle's lateral stability under different driving conditions and actuator response states.

[0013] Preferably, the multi-source sensing module includes a motion parameter acquisition unit, an adhesion characteristic acquisition unit and a data synchronization unit;

[0014] The motion parameter acquisition unit includes a wheel speed acquisition unit and a posture acquisition unit, which is used to monitor and acquire the vehicle's lateral motion parameters in real time by deploying a sensor group at the vehicle's left front wheel, right front wheel, and body center of mass, and transmit the collected data to the data synchronization unit via the CAN bus. The sensor group includes a wheel speed sensor group and an inertial measurement unit. The vehicle's lateral motion parameters include wheel speed data and lateral acceleration data.

[0015] The wheel speed acquisition unit is used to collect the wheel speed data of the left and right front wheels in real time based on the wheel speed sensor group. The wheel speed sensor group includes a magnetoelectric wheel speed sensor, a signal conditioning circuit and a data interface, and respectively collects the rotation speed value, pulse frequency and measurement error of the wheel speed data;

[0016] The attitude acquisition unit is used to collect vehicle lateral acceleration and roll angle data in real time based on an inertial measurement unit, wherein the inertial measurement unit includes a three-axis accelerometer, a three-axis gyroscope and a temperature compensation module, and the lateral motion parameters include lateral acceleration, roll angle rate and attitude angle deviation;

[0017] The adhesion characteristic acquisition unit is used to establish a communication protocol to connect with the tire pressure monitoring system, read the tire pressure and temperature data in the tire pressure monitoring system in real time, and extract and summarize the tire pressure value, temperature value and sensor position in the tire pressure data in real time to obtain tire adhesion status data.

[0018] Preferably, the data synchronization unit is used to filter out electromagnetic interference noise and abnormal jump values ​​from the collected wheel speed data, lateral acceleration data and tire adhesion status data, and unify the formats of CAN bus data, inertial measurement unit data and tire pressure monitoring data. At the same time, the collected multi-source data are time synchronized through timestamp alignment technology to obtain the wheel speed value, lateral acceleration value and tire pressure value at the same moment.

[0019] Preferably, the fusion decision module includes a multi-source fusion unit, a control strategy generation unit and a parameter calibration unit;

[0020] The multi-source fusion unit includes a data association unit and a fusion calculation unit;

[0021] The data association unit extracts historical motion data and control parameters from the vehicle's electronic stability program, uses a fusion algorithm to establish an association model for multi-source sensor data, and associates the dynamic relationship between wheel speed data and lateral acceleration, and the coupling characteristics between tire pressure and roll angle. After the initial association is completed, a filtering algorithm is used to dynamically compensate for wheel speed deviation, acceleration noise, and roll angle drift in the association model. At the same time, the input range of the steering system, the response delay of the braking system, and the torque threshold of the power distribution are set to perform static association, dynamic association, and working condition association to associate the multi-source sensor data of the vehicle's lateral motion parameters.

[0022] The fusion calculation unit is used to input the vehicle's steering angle parameters, including steering wheel angle, steering angular velocity and steering torque, and then perform Kalman filter processing after the input to calculate the center of mass sideslip angle, yaw angular velocity and lateral acceleration of the vehicle's lateral motion;

[0023] The control strategy generation unit is used to establish a lateral stability control model, including a steering intervention threshold, a brake distribution ratio, and a power torque limit, and then apply fuzzy control rules to generate lateral stability control instructions. The control strategy generation technology is used to analyze the response characteristics of the actuator and evaluate the steering intervention angle range, the brake pressure distribution gradient, and the power torque adjustment rate.

[0024] The parameter calibration unit is used to import the multi-source fusion model into the control strategy model for integration to obtain the collaborative control model, and then transmit the real-time collected vehicle motion parameters and system status data to the Kalman filter processing and fuzzy control rules for dynamic optimization, and import the optimization results into the collaborative control model to calibrate the vehicle lateral stability control parameters in real time, and display the calibration data through the human-computer interaction interface to provide parameter adjustment function.

[0025] Preferably, the state assessment module includes a lateral stability assessment unit, a tire adhesion assessment unit and a steering response assessment unit;

[0026] The lateral stability evaluation unit is used to construct a lateral stability evaluation algorithm, calculate and obtain the stability index of the vehicle's lateral motion based on the synchronized motion parameters, and evaluate the stability of the vehicle's lateral motion;

[0027] The tire adhesion evaluation unit is used to construct a tire adhesion evaluation algorithm, calculate and obtain the tire adhesion coefficient based on the synchronized tire adhesion status data, and evaluate the adhesion performance of the tire to the ground;

[0028] The steering response evaluation unit is used to construct a steering response evaluation algorithm, calculate and obtain the steering system response time based on the synchronized system status data, and evaluate the response speed of the steering actuator.

[0029] Preferably, the lateral stability evaluation unit is used to calculate and obtain a lateral stability index by analyzing the sideslip angle and yaw rate of the center of mass after multi-source fusion, combined with the synchronized wheel speed data, and evaluate the degree of deviation of the vehicle's lateral movement from the ideal trajectory.

[0030] Preferably, the tire adhesion evaluation unit is used to calculate and obtain the tire adhesion coefficient by comparing the wheel speed difference between the left and right front wheels in combination with the synchronized tire pressure data, and evaluate the difference in adhesion between the left and right front wheels and the ground.

[0031] Preferably, the coordination optimization module includes a multi-objective optimization unit and a control instruction adjustment unit;

[0032] The multi-objective optimization unit is used to perform normalization processing on the obtained lateral stability index, tire adhesion coefficient, and steering response time, and then perform correlation calculation to obtain a first evaluation index, and perform a comprehensive analysis on the stability of the vehicle's lateral motion;

[0033] The control instruction adjustment unit is used to preset a first benchmark threshold based on the design specifications and historical test data of the vehicle's lateral stability, and perform a preliminary comparative evaluation with the obtained first evaluation index to evaluate the stability of the vehicle's lateral movement. The specific evaluation scheme is as follows; when the first evaluation index is greater than the first benchmark threshold, it indicates that the vehicle's lateral movement is stable under the current driving condition and continues to maintain the current control strategy; when the first evaluation index is less than or equal to the first benchmark threshold, it indicates that the vehicle's lateral movement is unstable under the current driving condition, and it is necessary to trigger the coordination optimization mechanism and adjust the control instruction.

[0034] Preferably, the control execution module includes a steering execution unit, a braking execution unit and a power distribution unit;

[0035] The steering execution unit is used to receive the steering intervention instruction generated by the fusion decision module, adjust the steering assist torque through the electric power steering system, and perform the steering intervention operation of the lateral stability control;

[0036] The brake execution unit is used to receive the brake distribution instruction generated by the fusion decision module, adjust the brake pressure of the left and right front wheels through the electronic stability program, and perform the brake intervention operation of the lateral stability control;

[0037] The power distribution unit is used to receive the power adjustment instruction generated by the fusion decision module, adjust the torque output of the left and right drive wheels through the power control unit, and perform the power intervention operation of the lateral stability control.

[0038] Preferably, the steering execution unit is used to calculate and obtain the control current of the power-assisting motor by analyzing the target angle and intervention rate in the steering intervention instruction, combined with the maximum output torque of the electric power steering system, and perform the steering angle correction operation of the lateral stability control; the braking execution unit is used to calculate and obtain the pressure value of the brake wheel cylinder by analyzing the target pressure and adjustment gradient in the braking distribution instruction, combined with the maximum pressure building rate of the electronic stability program, and perform the braking pressure adjustment operation of the lateral stability control; the power distribution unit is used to calculate and obtain the output current of the drive motor by analyzing the target torque and distribution ratio in the power adjustment instruction, combined with the maximum torque response of the power control unit, and perform the power torque distribution operation of the lateral stability control.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] This invention utilizes a multi-source sensing module, deploying multiple types of sensors in key areas of the vehicle's steering system, suspension system, and body. This module collects multi-dimensional parameters such as wheel speed, lateral acceleration, tire pressure, and temperature in real time. After preliminary screening and format conversion, it provides the system with comprehensive and accurate raw data, effectively addressing the incompleteness of single-sensor data and improving data reliability. The fusion decision module constructs a multi-source sensor data fusion model, utilizing information fusion and control strategy generation techniques, combined with Kalman filtering and fuzzy control rules, to dynamically simulate lateral stability control parameters. This allows for precise analysis of the vehicle's lateral motion characteristics, enhancing the scientific nature and adaptability of the control strategy.

[0041] The control execution module transmits control rules to the steering, braking, and power distribution mechanisms. By executing command codes and adjusting output power, it achieves coordinated control of multiple actuators. For example, the steering actuator adjusts the assist torque, the braking actuator distributes brake pressure, and the power distribution unit adjusts torque output. These mechanisms respond synchronously and complementary, resolving coordination conflicts inherent in traditional independent control and improving vehicle posture control accuracy. The state assessment module standardizes the collected data and calculates indicators such as lateral stability, tire adhesion, and steering response time. By comparing these data against baseline thresholds, it provides a preliminary assessment of the vehicle's lateral motion, providing data support for control strategy adjustments.

[0042] If the initial assessment indicates instability, the coordinated optimization module conducts a secondary assessment based on road environment parameters. Through multi-objective optimization and control command adjustments, it dynamically optimizes control parameters to adapt to varying driving conditions and actuator response states. For example, on slippery roads or when actuator performance degrades, timely adjustments to steering intervention angles and brake pressure distribution gradients are made to enhance system robustness under complex conditions. The parameter calibration unit dynamically optimizes the coordinated control model using real-time data collection, enabling online calibration of control parameters to ensure optimal control performance under varying load and speed conditions.

[0043] The data synchronization unit ensures the temporal consistency and accuracy of multi-source data through filtering, format unification and timestamp alignment technology, laying the foundation for subsequent fusion calculation and state evaluation. The multi-source fusion unit further improves the accuracy of data fusion by establishing a data association model and dynamic compensation, and deeply analyzes the coupling relationship between parameters such as wheel speed, lateral acceleration, and tire pressure. In general, the present invention constructs a complete closed-loop system from data acquisition, fusion decision-making, execution control to state evaluation and optimization through the collaborative work of multiple modules, significantly improving the accuracy, real-time performance and environmental adaptability of vehicle lateral stability control, effectively reducing the probability of dangerous conditions such as vehicle skidding and tail-swinging, and ensuring driving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1This is a working principle diagram of the vehicle lateral stability coordinated control system based on multi-source sensor fusion according to the present invention;

[0045] Figure 2 This is the working principle diagram of the lateral stability assessment unit;

[0046] Figure 3 This is the working principle diagram of the tire adhesion evaluation unit;

[0047] Figure 4 This is the working principle diagram of the coordination optimization module. DETAILED DESCRIPTION

[0048] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0049] See also Figures 1-4 The present invention relates to a multi-source sensor fusion vehicle lateral stability coordinated control system, which includes: a multi-source sensor module, a fusion decision module, a control execution module, a state evaluation module, and a coordinated optimization module. The specific implementation is as follows:

[0050] The multi-source sensing module deploys multiple types of sensors in the vehicle's steering system, suspension system and key parts of the body to collect vehicle lateral motion parameters, tire adhesion parameters and steering system status data in real time, and performs preliminary screening and format conversion on the collected data.

[0051] The fusion decision module builds a multi-source sensor data fusion model, uses information fusion technology to analyze the vehicle's lateral motion characteristics, and uses control strategy generation technology to build lateral stability control rules. Based on the real-time collected vehicle motion parameters and system status data, it dynamically simulates the vehicle's lateral stability control parameters.

[0052] The control execution module transmits the generated lateral stability control rules to the vehicle steering actuator, brake actuator and power distribution mechanism to perform execution instruction encoding and output power adjustment, and transmits the execution feedback data back to the state evaluation module.

[0053] The state assessment module normalizes the acquired lateral motion parameters, tire adhesion parameters, and execution feedback data, obtains a first assessment index through correlation calculation, presets a first benchmark threshold, and performs a preliminary comparative assessment to analyze the stability of the vehicle's lateral motion.

[0054] When the coordinated optimization module analyzes that the vehicle's lateral motion is unstable, it combines the road environment parameters to calculate a second evaluation index, presets a second benchmark threshold, and performs a secondary comparative evaluation with the second evaluation index to further analyze the vehicle's lateral stability performance under different driving conditions and actuator response states.

[0055] Example 1:

[0056] This embodiment describes in detail the specific structure and workflow of the multi-source sensing module, which includes a motion parameter acquisition unit, an adhesion characteristic acquisition unit, and a data synchronization unit. These units cooperate with each other to realize the acquisition, processing, and synchronization of vehicle-related data.

[0057] The motion parameter acquisition unit is a key component of the multi-source sensing module, consisting of a wheel speed acquisition unit and an attitude acquisition unit. These units utilize sensor groups deployed on the vehicle's left and right front wheels, as well as at the vehicle's center of mass, to monitor and collect the vehicle's lateral motion parameters in real time. The collected data is transmitted to the data synchronization unit via the CAN bus. The sensor group consists of a wheel speed sensor group and an inertial measurement unit, and the vehicle's lateral motion parameters include wheel speed data and lateral acceleration data.

[0058] The wheel speed acquisition unit collects real-time wheel speed data from the left and right front wheels using a wheel speed sensor assembly. The wheel speed sensor assembly is a complex system consisting of a magnetoelectric wheel speed sensor, a signal conditioning circuit, and a data interface. The magnetoelectric wheel speed sensor senses wheel rotation to obtain wheel speed information; the signal conditioning circuit processes the output signal from the magnetoelectric wheel speed sensor for greater stability and accuracy; and the data interface is used for data transmission. Through the coordinated operation of these components, the wheel speed acquisition unit collects the rotational speed value, pulse frequency, and measurement error of the wheel speed data, providing accurate wheel speed information for subsequent analysis of vehicle motion.

[0059] Next, the attitude acquisition unit (AMU) relies on an inertial measurement unit (IMU) to collect real-time data on the vehicle's lateral acceleration and roll angle. The IMU consists of a triaxial accelerometer, a triaxial gyroscope, and a temperature compensation module. The triaxial accelerometer measures the vehicle's acceleration in all three axes, thereby determining lateral acceleration. The triaxial gyroscope measures attitude parameters such as the vehicle's roll rate. The temperature compensation module eliminates the effects of temperature changes on measurement results, ensuring data accuracy. The lateral motion parameters collected by the AMU include lateral acceleration, roll rate, and attitude angle deviation, all of which are crucial for assessing the vehicle's lateral stability.

[0060] The Adhesion Characteristics Acquisition Unit (ACU) acquires tire adhesion data. This unit connects to the tire pressure monitoring system (TPM) via a communication protocol, enabling real-time reading of tire pressure and temperature data. After reading the data, the ACU extracts and aggregates the tire pressure, temperature, and sensor position data in real time to generate tire adhesion data. Tire adhesion directly impacts vehicle handling and stability, so accurate acquisition of this data is crucial for subsequent analysis and control.

[0061] The data synchronization unit plays a key role in integrating the multi-source sensor module. It first processes the collected wheel speed, lateral acceleration, and tire adhesion data, filtering out electromagnetic interference and abnormal jump values ​​to ensure data quality. During vehicle operation, sensors may be subject to various interferences, resulting in noise and abnormal values ​​in the data. Unprocessed data can affect subsequent analysis and control.

[0062] The data synchronization unit must unify the formats of CAN bus data, inertial measurement unit data, and tire pressure monitoring data. Since different sensors may output data in different formats, a unified format facilitates subsequent data processing and fusion.

[0063] The data synchronization unit synchronizes the collected multi-source data using timestamp alignment technology, enabling simultaneous acquisition of wheel speed, lateral acceleration, and tire pressure values. Time synchronization is crucial; ensuring the temporal consistency of data from different sources allows for accurate analysis of the relationships between vehicle parameters and provides reliable data support for subsequent fusion decision-making modules.

[0064] Throughout the multi-source sensing module's operation, each unit works closely together. From sensor deployment to data collection, and then to data processing and synchronization, every link is carried out strictly in accordance with design requirements to ensure the provision of accurate, reliable, and synchronized raw data for the entire vehicle's lateral stability coordinated control system, laying a solid foundation for subsequent modules to analyze, control, and optimize vehicle lateral stability.

[0065] Example 2:

[0066] The fusion decision module, the core processing unit of the entire system, has a direct impact on the accuracy and response speed of vehicle lateral stability control through its internal structure and operating logic. This module consists of a multi-source fusion unit, a control strategy generation unit, and a parameter calibration unit. These units implement a hierarchical data processing flow to optimize the entire process, from raw sensor data to control parameter generation.

[0067] The multi-source fusion unit is the foundational processing element of the fusion decision module and consists of two submodules: the data association unit and the fusion calculation unit. The data association unit's primary task is to extract vehicle motion data (such as wheel speed, lateral acceleration, and roll angle) and control parameters (such as brake pressure and steering torque) under different operating conditions from the vehicle's electronic stability program (ESP) historical database. This historical data covers the vehicle's operating conditions under various typical operating conditions, including straight-line driving, steering, and braking, providing a rich sample base for establishing a correlation model for multi-source sensor data.

[0068] After acquiring historical data, the data association unit uses a fusion algorithm (such as one based on probabilistic statistics) to establish a dynamic correlation model between wheel speed data and lateral acceleration, as well as a coupling model between tire pressure and roll angle. For example, when a vehicle turns, the difference in wheel speed between the inside and outside wheels and lateral acceleration form a specific functional relationship. The fusion algorithm can be used to fit a mathematical model of this relationship, thereby achieving a dynamic correlation between the two. After completing the initial correlation, the data association unit initiates a filtering algorithm (such as a Kalman filter or complementary filter) to dynamically compensate for wheel speed deviations (such as wheel speed measurement errors caused by sensor installation errors), acceleration noise (such as acceleration fluctuations caused by road bumps), and roll angle drift (such as zero-point drift of the inertial measurement unit during long-term driving) in the correlation model.

[0069] At the same time, the data association unit also needs to set the input range of the steering system (such as the effective range of steering wheel angle), the response delay of the braking system (such as the time interval from receiving the braking command to the establishment of brake pressure), and the torque threshold of power distribution (such as the maximum difference in torque distribution between the left and right drive wheels). Based on these parameters, it performs static association (such as fixed values ​​for the steering input range at different vehicle speeds), dynamic association (such as corrections for braking response delay that vary with vehicle speed), and operating condition association (such as the difference in tire pressure-roll angle coupling models on wet and dry roads), ultimately achieving comprehensive association of multi-source sensor data of the vehicle's lateral motion parameters.

[0070] The fusion calculation unit uses the output of the data association unit as input. It first receives the vehicle's steering angle parameters, including the steering wheel angle (the steering angle input by the driver), steering angular velocity (the speed of the steering wheel rotation), and steering torque (the torque applied by the driver to the steering wheel). These steering angle parameters reflect the driver's steering intention and are key inputs for controlling the vehicle's lateral motion.

[0071] After acquiring the steering angle parameters, the fusion calculation unit applies a Kalman filter to eliminate measurement noise and interference signals. The Kalman filter establishes a state-space model to optimally estimate the true value of the steering angle parameters, resulting in smoother and more accurate steering angle data. Based on the filtered steering angle parameters, the fusion calculation unit further calculates the vehicle's lateral slip angle (the angle between the vehicle's center of mass velocity and the longitudinal axis, reflecting the degree of sideslip), yaw rate (the angular velocity of the vehicle about its vertical axis, reflecting the severity of the vehicle's steering), and lateral acceleration (the vehicle's acceleration in the lateral direction, reflecting the intensity of the vehicle's lateral motion). These parameters are key indicators for assessing the vehicle's lateral stability.

[0072] The control strategy generation unit builds a lateral stability control model based on the calculation results of the multi-source fusion unit. This model includes key parameters such as steering intervention threshold (for example, triggering steering intervention when the sideslip angle exceeds a certain threshold), brake distribution ratio (the distribution of brake pressure between the left and right front wheels), and power torque limit (the maximum output torque of the drive wheels). These parameters are based on vehicle dynamics principles and extensive real-world test data to ensure that the control model accurately reflects the vehicle's stability requirements under different operating conditions.

[0073] After establishing the control model, the control strategy generation unit applies fuzzy control rules to generate lateral stability control commands. These rules are based on expert experience and common driving knowledge, such as "When the sideslip angle is large and the yaw rate is high, apply a larger steering torque and brake pressure." These fuzzy control rules convert the continuous output of the multi-source fusion unit (such as the specific value of the sideslip angle) into discrete control commands (such as the intensity level of steering intervention and the amount of brake pressure).

[0074] Furthermore, the control strategy generation unit uses control strategy generation technology to analyze the actuator's response characteristics. This includes evaluating the steering intervention angle range (the maximum steering assist angle the electric power steering system can provide), the brake pressure distribution gradient (the rate at which brake pressure changes over time), and the torque modulation rate (the rate at which the drive wheel torque output changes). This response characteristic analysis ensures that the generated control commands match the actuator's actual capabilities, preventing control failures caused by control commands exceeding the actuator's capabilities.

[0075] The parameter calibration unit is a key component in achieving real-time optimization within the fusion decision module. This unit first integrates the multi-source fusion model established by the multi-source fusion unit into the control strategy model of the control strategy generation unit, generating a collaborative control model. This collaborative control model integrates sensor data fusion logic and control strategy generation logic to more comprehensively reflect the vehicle's lateral stability control requirements.

[0076] During vehicle operation, the parameter calibration unit receives real-time data on vehicle motion parameters (such as wheel speed, lateral acceleration, and slip angle) and system status data (such as actuator operating status and sensor health status). This data is then transmitted to the Kalman filter processing module and the fuzzy control rule module for dynamic optimization. For example, when the vehicle enters a new driving condition (such as transitioning from a dry road to a slippery one), the real-time data will reflect changes in the tire adhesion coefficient. The parameter calibration unit adjusts the Kalman filter's noise covariance matrix and the fuzzy control rule's membership function based on this change, thereby optimizing the fusion model and control strategy.

[0077] The optimized results are then imported into the collaborative control model, enabling real-time calibration of the vehicle's lateral stability control parameters. The parameter calibration unit also displays calibration data (such as current control parameter values ​​and pre- and post-calibration comparison curves) through a human-computer interface and provides parameter adjustment functionality, enabling engineers to manually optimize and verify control parameters during vehicle development and commissioning.

[0078] Example 3:

[0079] As a key component of the vehicle's lateral stability coordinated control system, the state assessment module's core function is to accurately assess the vehicle's lateral motion, tire adhesion, and steering system responsiveness through multi-dimensional data processing and analysis. This module consists of a lateral stability assessment unit, a tire adhesion assessment unit, and a steering response assessment unit. Each unit, through standardized data processing procedures and algorithmic models, provides the system with objective state assessment results, thereby supporting the coordinated optimization module's decision-making process.

[0080] The lateral stability assessment unit is a core component of the state assessment module. Its primary task is to develop a lateral stability assessment algorithm. This algorithm is based on synchronized motion parameters, including wheel speed data, lateral acceleration, slip angle, yaw rate, and other key indicators fused from multiple sources. These parameters are acquired in real time from the multi-source sensing module and the fusion decision module via the CAN bus or other communication protocols, ensuring data timeliness and accuracy.

[0081] After acquiring the data, the lateral stability evaluation unit first normalizes it to eliminate the effects of dimensional differences in various parameters. For example, parameters such as lateral acceleration (in m / s²) and slip angle (in radians) are converted to dimensionless values ​​within the [0, 1] range using a normalization formula to facilitate subsequent correlation calculations. After normalization, the evaluation unit then uses specific calculation logic to determine the vehicle's lateral stability index.

[0082] The core evaluation logic of this unit is to analyze the multi-source fusion of the center of mass slip angle and yaw rate, and perform a comprehensive calculation based on the synchronized wheel speed data. The center of mass slip angle reflects the degree of deviation between the vehicle's actual direction of motion and the longitudinal axis of the vehicle body and is a key indicator of whether the vehicle is skidding. The yaw rate reflects the severity of the vehicle's steering. The combination of the two can intuitively reflect the stability of the vehicle's lateral motion. For example, when the vehicle is turning, if the center of mass slip angle exceeds a certain threshold and the yaw rate continues to increase, it may indicate that the vehicle is about to enter a dangerous understeer or oversteer condition.

[0083] The lateral stability assessment unit establishes a mathematical model (non-formulaic) linking slip angle, yaw rate, and wheel speed data to calculate a stability index that comprehensively reflects the degree to which the vehicle's lateral motion deviates from its ideal trajectory. This calculation fully considers vehicle dynamics, such as the varying safety thresholds for slip angle at different speeds. A smaller slip angle at high speeds may indicate a higher risk of sideslip. The assessment unit compares the calculated stability index with a preset reference range to assess the vehicle's lateral stability and provide a basis for subsequent control decisions.

[0084] The Tire Adhesion Evaluation Unit (TAU) evaluates tire adhesion to the road, a performance that directly impacts vehicle handling stability and braking safety. This unit utilizes a dedicated algorithm based on synchronized tire adhesion data, including parameters such as tire pressure, temperature, and wheel speed differentials obtained from wheel speed sensors.

[0085] The core assessment method of the tire adhesion evaluation unit is to compare the speed difference between the left and right front wheels and perform a comprehensive calculation based on synchronized tire pressure data. When the vehicle is turning or traversing uneven roads, the wheel speeds of the left and right front wheels may differ, but under normal adhesion conditions, this difference is within a reasonable range. However, if the adhesion coefficient of one tire decreases (such as when driving on wet, icy or snowy roads), the tire on that side may slip, resulting in a significantly higher speed than the other tire, and a significant increase in the speed difference.

[0086] The evaluation unit first collects and synchronously processes wheel speed data from both front wheels in real time, ensuring temporal consistency in calculating the wheel speed difference. It then combines this with tire pressure data (which affects the tire's contact area with the ground and ground pressure distribution, thus affecting the adhesion coefficient) to determine the tire adhesion coefficient using a specific calculation logic (not a formal description). For example, given the same wheel speed difference, the side with higher tire pressure may have a higher actual adhesion coefficient due to a more even ground pressure distribution.

[0087] The tire adhesion evaluation unit uses the calculated tire adhesion coefficients to assess the difference in adhesion between the left and right front wheels and the road. If the difference exceeds a certain threshold, the vehicle may experience instability, such as deviation and increased braking distance. The evaluation unit then transmits the results to the coordination and optimization module, which then implements appropriate control measures (such as differential braking) to balance the adhesion difference and improve vehicle stability.

[0088] The steering response evaluation unit assesses the response speed of the steering actuator, a key indicator of vehicle handling. This unit develops a steering response evaluation algorithm based on synchronized system status data, including parameters such as the steering actuator control command input time, the steering assist torque buildup time, and the actual steering angle change time.

[0089] The evaluation process of the steering response evaluation unit mainly includes the following steps: first, real-time monitoring of the time point when the steering intervention instruction is sent by the fusion decision module to the steering execution unit; then, monitoring the time point when the electric power steering system starts to adjust the steering assist torque after the steering execution unit receives the instruction; finally, monitoring the time point when the steering wheel actually starts to rotate and reaches a certain angle (such as 1% of the target angle) through the angle sensor.

[0090] The evaluation unit determines the steering system response time by calculating the time interval from the command being sent to the steering wheel's response. This response time reflects the steering actuator's efficiency in executing the control command. A shorter response time indicates better dynamic responsiveness of the steering system, leading to improved vehicle handling and stability. The steering response evaluation unit compares the calculated response time with a preset standard value to assess whether the steering actuator's response speed meets the requirements. The evaluation results are then transmitted to the coordination and optimization module, enabling the system to adjust control commands based on the steering system's actual responsiveness, ensuring their effectiveness and accuracy.

[0091] The three units of the Condition Assessment Module work together to comprehensively evaluate the vehicle's condition across three dimensions: lateral stability, tire adhesion, and steering responsiveness. Each unit's evaluation process is rigorously based on real-time, multi-source data. Through standardized data processing and specialized algorithmic models, the objectivity and accuracy of the assessment results are ensured. These results not only inform the coordinated optimization module's decisions but also provide crucial reference information for the optimization and commissioning of the entire vehicle's lateral stability coordinated control system, thereby enabling comprehensive monitoring and assurance of the vehicle's lateral stability.

[0092] Example 4:

[0093] The Coordination Optimization Module is the core component of the vehicle's lateral stability coordinated control system, enabling multi-dimensional assessment and dynamic control adjustments. Through the collaborative work of the Multi-Objective Optimization Unit and the Control Command Adjustment Unit, it achieves in-depth analysis and precise intervention in the vehicle's lateral stability. Building on the initial assessments made by the State Assessment Module, this module further integrates multi-source data to construct a hierarchical assessment system. Based on the assessment results, it triggers appropriate control strategy adjustments to ensure vehicle lateral stability under complex operating conditions.

[0094] The primary task of the multi-objective optimization unit is to standardize the input evaluation parameters. This unit receives parameters such as lateral stability, tire adhesion, and steering response time from the state assessment module. These parameters differ in physical meaning and dimension, so a standardization algorithm is used to convert them into values ​​with a unified dimension. For example, the lateral stability index may be a combined calculation of the sideslip angle and yaw rate, the tire adhesion coefficient is a dimensionless coefficient, and the steering response time is a time-dimensional parameter. The multi-objective optimization unit maps these parameters to the standard interval [0,1] through linear normalization or nonlinear mapping (non-formulaic description), eliminating the impact of dimensional differences on subsequent calculations.

[0095] After standardization, the multi-objective optimization unit performs a correlation calculation on the above parameters to obtain the first evaluation index. This calculation process is based on the multi-physics coupling characteristics of vehicle lateral stability and takes into account the mutual influence of various parameters. For example, when the tire adhesion coefficient decreases, the sensitivity of the vehicle's lateral stability to steering response time increases, and in this case, the steering response time needs to be weighted higher in the correlation calculation. The multi-objective optimization unit establishes a parameter correlation model (non-formulaic description) to weight the standardized lateral stability index, tire adhesion coefficient, and steering response time to form a first evaluation index that comprehensively reflects the vehicle's lateral motion stability. The construction of this index fully considers the characteristics of the vehicle under different driving conditions, such as giving a higher weight to the lateral stability index when turning at high speed and a higher weight to the tire adhesion coefficient when driving on slippery roads.

[0096] The multi-objective optimization unit performs a comprehensive analysis of the vehicle's lateral stability based on the first evaluation metric. This analysis not only focuses on the numerical value of a single metric but also considers the changing trends and coupling relationships of various parameters. For example, if the lateral stability metric is at a critical value, but the tire adhesion coefficient continues to decline and the steering response time increases, the multi-objective optimization unit will determine that the vehicle stability risk is increasing. Even if the first evaluation metric has not yet exceeded the threshold, it will issue a warning signal to the control command adjustment unit.

[0097] The core function of the Control Command Adjustment Unit is to determine stability and adjust the control strategy based on the evaluation results of the Multi-Objective Optimization Unit. This unit first presets a first baseline threshold based on the vehicle's lateral stability design specifications and historical test data. The design specifications define the stability safety margins for different vehicle models and load conditions, while the historical test data covers vehicle stability performance under various typical operating conditions (such as steering on dry roads, braking on wet roads, and driving on icy and snowy roads). The Control Command Adjustment Unit statistically analyzes this data to determine a reasonable first baseline threshold, which serves as the key basis for determining whether the vehicle's lateral motion is stable.

[0098] The control command adjustment unit performs a preliminary comparison and evaluation of the first evaluation indicator output by the multi-objective optimization unit against a preset first baseline threshold. Specifically, when the first evaluation indicator is greater than the first baseline threshold, the vehicle's lateral motion is stable under the current driving conditions, and the system maintains the current control strategy without intervention. When the first evaluation indicator is less than or equal to the first baseline threshold, the vehicle's lateral motion is deemed unstable under the current driving conditions, triggering the coordinated optimization mechanism and adjusting the control instructions.

[0099] After triggering the coordinated optimization mechanism, the control command adjustment unit further analyzes road environment parameters. These parameters include road adhesion coefficient (detected in real time by sensors or obtained from an onboard map), slope, curvature, and other parameters. For example, when the vehicle is traveling on a slippery curve and the first evaluation metric is below a threshold, the control command adjustment unit calculates the curve's curvature radius and road adhesion coefficient, combining these with parameters such as the vehicle's current speed and lateral acceleration to calculate a second evaluation metric. This metric, based on the first evaluation metric, adds weight to the influence of road environment factors, more accurately reflecting the vehicle's stability under specific operating conditions.

[0100] The control command adjustment unit presets a second baseline threshold and performs a secondary comparative evaluation of the second evaluation indicator against the second baseline threshold. This second baseline threshold is also based on design specifications and historical test data, but is differentiated for different road conditions. For example, the second baseline threshold for wet roads may be lower than for dry roads to trigger control intervention earlier. The purpose of this secondary comparative evaluation is to further analyze the vehicle's lateral stability under different driving conditions and actuator response states, avoiding misjudgments caused by single-dimensional evaluation.

[0101] If the secondary comparative evaluation still indicates insufficient vehicle stability, the control command adjustment unit generates a control command adjustment plan based on the evaluation results. The adjustment plan covers multiple dimensions, including steering intervention angle, brake pressure distribution, and power torque adjustment. For example, if it is determined that the vehicle's stability has decreased due to understeer, the control command adjustment unit will send a command to the steering actuator unit to increase the steering assist torque and a command to the brake actuator unit to apply braking to the inner rear wheel to generate additional yaw torque to correct the understeer. If tire adhesion differences are determined to be the primary cause, the torque output of the power distribution unit will be adjusted to balance the driving force of the left and right drive wheels and improve vehicle stability.

[0102] When generating adjustment plans, the control command adjustment unit also considers the actuator's response characteristics and current operating status. For example, if the brake actuator's braking performance degrades due to prolonged operation, the control command adjustment unit will prioritize improving stability through steering intervention and power distribution adjustments rather than simply increasing brake pressure. After generating the adjustment plan, the control command adjustment unit transmits it to the control execution module and simultaneously feeds back the evaluation process and adjustment basis to the state assessment module, forming a closed-loop control system.

[0103] Example 5:

[0104] The control execution module is the key link in the vehicle's lateral stability coordinated control system, translating the control strategies generated by the fusion decision module into actual physical actions. Through the coordinated operation of the steering execution unit, braking execution unit, and power distribution unit, it achieves precise control of the vehicle's steering, braking, and power output, thereby ensuring lateral stability. Upon receiving control commands, this module must complete a series of operations, including command parsing, parameter calculation, actuator actuation, and feedback data transmission. Each link is tightly integrated to ensure the accuracy and timeliness of control actions.

[0105] The core function of the steering actuator unit is to receive the steering intervention command generated by the fusion decision module and execute the steering intervention for lateral stability control through the Electric Power Steering (EPS) system. The steering intervention command includes two key parameters: the target angle and the intervention rate. The target angle represents the magnitude of the correction to the driver's steering angle input, while the intervention rate reflects the speed of the correction. Upon receiving the command, the steering actuator unit parses it and extracts the specific values ​​of the target angle and intervention rate.

[0106] After parsing the command, the steering actuator unit calculates the control current for the power-assist motor based on the maximum output torque parameter of the electric power steering system. The maximum output torque of the electric power steering system determines the maximum steering assistance the system can provide. The maximum output torque of the electric power steering system may vary depending on the vehicle model or configuration. The steering actuator unit uses specific calculation logic (not formalized) to determine the control current required for the power-assist motor based on the target angle, intervention rate, and maximum output torque. For example, when the target angle is large and the intervention rate is high, a higher assist torque is required to quickly complete the steering correction, and the control current increases accordingly.

[0107] After calculating the control current, the steering actuator unit transmits this current signal to the power-assisted steering motor, driving it to operate. This adjusts the steering torque and implements steering angle correction for lateral stability control. During this process, the steering actuator unit also monitors the power-assisted steering motor's operating status and steering system feedback, such as the output of the steering torque sensor and the feedback from the steering angle sensor, to ensure the accuracy and stability of the steering intervention. If a deviation between the actual steering angle and the target angle is detected, the steering actuator unit promptly adjusts the control current to correct the error.

[0108] The Brake Actuator (BAU) receives the brake distribution command generated by the fusion decision module and, through the Electronic Stability Program (ESP), adjusts the brake pressure on the left and right front wheels to implement brake intervention for lateral stability control. The brake distribution command includes two core parameters: target pressure and adjustment gradient. The target pressure is the pressure to be applied to the left and right front wheel brake cylinders, while the adjustment gradient indicates the rate of change of brake pressure. Upon receiving the command, the BAU first parses it to determine the specific requirements for the target pressure and adjustment gradient.

[0109] The brake actuator unit calculates the wheel cylinder pressure value based on the maximum pressure buildup rate parameter of the electronic stability program. The maximum pressure buildup rate of the electronic stability program determines the braking system's ability to quickly build brake pressure. It is a key system parameter that affects the response speed and effectiveness of brake intervention. The brake actuator unit determines the required wheel cylinder pressure value based on the target pressure, the adjustment gradient, and the maximum pressure buildup rate using specific calculation logic (not a formal description). For example, when the target pressure is high and the adjustment gradient is large, in order to build up the required brake pressure in a short period of time, it is necessary to consider the maximum pressure buildup rate limit and rationally plan the pressure increase process.

[0110] After calculating the wheel cylinder pressure, the brake actuator unit transmits a control signal to the electronic stability program's hydraulic control unit. By controlling the on / off state of the hydraulic valves, it adjusts the pressure in the left and right front wheel cylinders, implementing brake pressure regulation for lateral stability control. During braking intervention, the brake actuator unit monitors the feedback signal from the brake pressure sensor in real time to ensure that the actual brake pressure is consistent with the target pressure. If any abnormalities such as slow pressure buildup or pressure fluctuations occur, the brake actuator unit will promptly adjust its control strategy to ensure the effectiveness of the braking intervention.

[0111] The power distribution unit (PDU) receives the power adjustment commands generated by the fusion decision module and, through the power control unit (PCU), adjusts the torque output to the left and right drive wheels, executing the power intervention for lateral stability control. These commands contain two key parameters: target torque and distribution ratio. The target torque represents the total torque output to the drive wheels, while the distribution ratio determines the torque distribution relationship between the left and right drive wheels. Upon receiving the commands, the PDU first parses them to obtain the specific values ​​for the target torque and distribution ratio.

[0112] The power distribution unit calculates the output current of the drive motor based on the maximum torque response parameters of the power control unit. The maximum torque response of the power control unit reflects the drive system's ability to quickly respond to torque commands and is a key factor influencing the effectiveness of power intervention. The power distribution unit determines the output current of the drive motor using specific calculation logic (not formalized) based on the target torque, the distribution ratio, and the maximum torque response. For example, when the target torque is large and the torque distribution needs to be adjusted quickly, the maximum torque response limitations must be considered and the output current must be properly calculated to ensure that the drive motor can deliver the required torque in a timely and accurate manner.

[0113] After calculating the output current of the drive motor, the power distribution unit transmits this current signal to the power control unit, which controls the operation of the drive motor and adjusts the torque output to the left and right drive wheels to achieve the power-torque distribution operation for lateral stability control. During the power intervention process, the power distribution unit monitors the torque output and speed signals of the drive motor in real time to ensure that the actual torque output is consistent with the target torque and that the torque distribution to the left and right drive wheels meets the requirements. If any abnormal torque output or distribution ratio deviation is detected, the power distribution unit will make timely adjustments to ensure the accuracy of the power intervention.

[0114] After transmitting the generated lateral stability control rules to the vehicle's steering, braking, and power distribution mechanisms, the control execution module, in addition to completing the specific operations of each of these execution units, also performs execution instruction encoding and output power regulation. Execution instruction encoding converts control instructions into electrical or digital signals that the various actuators can recognize and execute, ensuring correct transmission and understanding of the instructions. Output power regulation dynamically adjusts output power based on the actual operating status of the actuators and the vehicle's real-time operating conditions to avoid over- or under-control issues caused by excessive or insufficient power.

[0115] Furthermore, the control execution module must transmit execution feedback data back to the state evaluation module. This feedback data includes information such as the operating status of each actuator and the actual execution results, such as the actual steering angle of the steering actuator, the actual braking pressure of the braking actuator, and the actual torque output of the power distribution unit. This feedback data is crucial for the state evaluation module to accurately assess the vehicle's lateral stability and the actuator's response status. It constitutes a key component of the system's closed-loop control, enabling the system to continuously optimize the control strategy based on actual execution results, thereby improving the accuracy and reliability of the vehicle's lateral stability control.

[0116] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "includes," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0117] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A multi-source sensor fusion coordinated vehicle lateral stability control system, characterized by: It includes multi-source sensing module, fusion decision module, control execution module, state assessment module and coordination optimization module; The multi-source sensing module is used to deploy multiple types of sensors in the vehicle's steering system, suspension system, and key body parts, and collect vehicle lateral motion parameters, tire adhesion parameters, and steering system status data in real time, while performing preliminary screening and format conversion on the collected data. The fusion decision module is used to build a multi-source sensor data fusion model and use information fusion technology to analyze the vehicle's lateral motion characteristics. At the same time, it uses control strategy generation technology to build lateral stability control rules and dynamically simulate the vehicle's lateral stability control parameters based on real-time collected vehicle motion parameters and system status data; The control execution module is used to transmit the generated lateral stability control rules to the vehicle steering actuator, brake actuator and power distribution mechanism to perform execution instruction encoding and output power adjustment, and transmit execution feedback data back to the state evaluation module; The state evaluation module is used to perform a preliminary comparative evaluation and analysis of the vehicle's lateral motion stability after normalizing the acquired lateral motion parameters, tire adhesion parameters, and execution feedback data; The coordination optimization module is configured to calculate a second evaluation index based on the road environment parameters when analyzing that the vehicle's lateral motion is unstable, and to perform a secondary comparative evaluation between a preset second reference threshold and the second evaluation index to analyze the vehicle's lateral stability under different driving conditions and actuator response states; The fusion decision module includes a multi-source fusion unit, a control strategy generation unit and a parameter calibration unit; The multi-source fusion unit includes a data association unit and a fusion calculation unit; The data association unit extracts historical motion data and control parameters from the vehicle's electronic stability program, uses a fusion algorithm to establish an association model for multi-source sensor data, and associates the dynamic relationship between wheel speed data and lateral acceleration, and the coupling characteristics between tire pressure and roll angle. After the initial association is completed, a filtering algorithm is used to dynamically compensate for wheel speed deviation, acceleration noise, and roll angle drift in the association model. At the same time, the input range of the steering system, the response delay of the braking system, and the torque threshold of the power distribution are set to perform static association, dynamic association, and working condition association to associate the multi-source sensor data of the vehicle's lateral motion parameters. The fusion calculation unit is used to input the vehicle's steering angle parameters, including steering wheel angle, steering angular velocity and steering torque, and then perform Kalman filter processing after the input to calculate the center of mass sideslip angle, yaw angular velocity and lateral acceleration of the vehicle's lateral motion; The control strategy generation unit is used to establish a lateral stability control model, including a steering intervention threshold, a brake distribution ratio, and a power torque limit, and then apply fuzzy control rules to generate lateral stability control instructions. The control strategy generation technology is used to analyze the response characteristics of the actuator and evaluate the steering intervention angle range, the brake pressure distribution gradient, and the power torque adjustment rate. The parameter calibration unit is used to import the multi-source fusion model into the control strategy model for integration to obtain the collaborative control model, and then transmit the real-time collected vehicle motion parameters and system status data to the Kalman filter processing and fuzzy control rules for dynamic optimization, and import the optimization results into the collaborative control model to calibrate the vehicle lateral stability control parameters in real time, and display the calibration data through the human-computer interaction interface to provide parameter adjustment function.

2. The multi-source sensor fusion vehicle lateral stability coordinated control system according to claim 1, characterized in that: The multi-source sensing module includes a motion parameter acquisition unit, an adhesion characteristic acquisition unit and a data synchronization unit; The motion parameter acquisition unit includes a wheel speed acquisition unit and a posture acquisition unit, which is used to monitor and acquire the vehicle's lateral motion parameters in real time by deploying a sensor group at the vehicle's left front wheel, right front wheel, and body center of mass, and transmit the collected data to the data synchronization unit via the CAN bus. The sensor group includes a wheel speed sensor group and an inertial measurement unit. The vehicle's lateral motion parameters include wheel speed data and lateral acceleration data. The wheel speed acquisition unit is used to collect the wheel speed data of the left and right front wheels in real time based on the wheel speed sensor group. The wheel speed sensor group includes a magnetoelectric wheel speed sensor, a signal conditioning circuit and a data interface, and respectively collects the rotation speed value, pulse frequency and measurement error of the wheel speed data; The attitude acquisition unit is used to collect vehicle lateral acceleration and roll angle data in real time based on an inertial measurement unit, wherein the inertial measurement unit includes a three-axis accelerometer, a three-axis gyroscope and a temperature compensation module, and the lateral motion parameters include lateral acceleration, roll angle rate and attitude angle deviation; The adhesion characteristic acquisition unit is used to establish a communication protocol to connect with the tire pressure monitoring system, read the tire pressure and temperature data in the tire pressure monitoring system in real time, and extract and summarize the tire pressure value, temperature value and sensor position in the tire pressure data in real time to obtain tire adhesion status data.

3. The multi-source sensor fusion vehicle lateral stability coordinated control system according to claim 2, characterized in that: The data synchronization unit is used to filter out electromagnetic interference noise and abnormal jump values ​​from the collected wheel speed data, lateral acceleration data, and tire adhesion status data, and unify the formats of CAN bus data, inertial measurement unit data, and tire pressure monitoring data. At the same time, the collected multi-source data is time-synchronized through timestamp alignment technology to obtain the wheel speed values, lateral acceleration values, and tire pressure values ​​at the same moment.

4. The multi-source sensor fusion vehicle lateral stability coordinated control system according to claim 1, characterized in that: The state assessment module includes a lateral stability assessment unit, a tire adhesion assessment unit and a steering response assessment unit; The lateral stability evaluation unit is used to construct a lateral stability evaluation algorithm, calculate and obtain the stability index of the vehicle's lateral motion based on the synchronized motion parameters, and evaluate the stability of the vehicle's lateral motion; The tire adhesion evaluation unit is used to construct a tire adhesion evaluation algorithm, calculate and obtain the tire adhesion coefficient based on the synchronized tire adhesion status data, and evaluate the adhesion performance of the tire to the ground; The steering response evaluation unit is used to construct a steering response evaluation algorithm, calculate and obtain the steering system response time based on the synchronized system status data, and evaluate the response speed of the steering actuator.

5. The multi-source sensor fusion vehicle lateral stability coordinated control system according to claim 4, characterized in that: The lateral stability evaluation unit is used to calculate and obtain a lateral stability index by analyzing the sideslip angle and yaw rate after multi-source fusion, combined with the synchronized wheel speed data, and evaluate the degree of deviation of the vehicle's lateral motion from the ideal trajectory.

6. The multi-source sensor fusion vehicle lateral stability coordinated control system according to claim 4, characterized in that: The tire adhesion evaluation unit is used to calculate the tire adhesion coefficient by comparing the wheel speed difference between the left and right front wheels and combining it with the synchronized tire pressure data, and evaluate the difference in adhesion between the left and right front wheels and the ground.

7. The multi-source sensor fusion vehicle lateral stability coordinated control system according to claim 1, characterized in that: The coordinated optimization module includes a multi-objective optimization unit and a control instruction adjustment unit; The multi-objective optimization unit is used to perform normalization processing on the obtained lateral stability index, tire adhesion coefficient, and steering response time, and then perform correlation calculation to obtain a first evaluation index, and perform a comprehensive analysis on the stability of the vehicle's lateral motion; The control instruction adjustment unit is used to preset a first benchmark threshold based on the design specifications and historical test data of the vehicle's lateral stability, and perform a preliminary comparative evaluation with the obtained first evaluation index to evaluate the stability of the vehicle's lateral movement. When the first evaluation index is greater than the first benchmark threshold, it indicates that the vehicle's lateral movement is stable under the current driving conditions and continues to maintain the current control strategy. When the first evaluation index is less than or equal to the first benchmark threshold, it indicates that the vehicle's lateral movement is unstable under the current driving conditions, and it is necessary to trigger a coordinated optimization mechanism and adjust the control instructions.

8. The multi-source sensor fusion vehicle lateral stability coordinated control system according to claim 1, characterized in that: The control execution module includes a steering execution unit, a braking execution unit and a power distribution unit; The steering execution unit is used to receive the steering intervention instruction generated by the fusion decision module, adjust the steering assist torque through the electric power steering system, and perform the steering intervention operation of the lateral stability control; The brake execution unit is used to receive the brake distribution instruction generated by the fusion decision module, adjust the brake pressure of the left and right front wheels through the electronic stability program, and perform the brake intervention operation of the lateral stability control; The power distribution unit is used to receive the power adjustment instruction generated by the fusion decision module, adjust the torque output of the left and right drive wheels through the power control unit, and perform the power intervention operation of the lateral stability control.

9. The multi-source sensor fusion vehicle lateral stability coordinated control system according to claim 8, characterized in that: The steering execution unit is used to calculate and obtain the control current of the power-assisted motor by analyzing the target angle and intervention rate in the steering intervention command in combination with the maximum output torque of the electric power steering system, and perform the steering angle correction operation of the lateral stability control; The brake execution unit is used to calculate and obtain the pressure value of the brake wheel cylinder by analyzing the target pressure and adjustment gradient in the brake distribution instruction, combined with the maximum pressure building rate of the electronic stability program, and perform the brake pressure adjustment operation of the lateral stability control; the power distribution unit is used to calculate and obtain the output current of the drive motor by analyzing the target torque and distribution ratio in the power adjustment instruction, combined with the maximum torque response of the power control unit, and perform the power torque distribution operation of the lateral stability control.

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