Collaborative Optimization Control Method and System for Vehicle Components

Abstract

This invention relates to a collaborative optimization control method and system for vehicle components, comprising the following steps: real-time operating parameters of multiple target components of the vehicle are collected by sensors; the coupling relationship between the components is analyzed based on parameter quantification to obtain the component coupling coefficient and determine whether a preset threshold is triggered. If triggered, the optimizable parameter range of each target component is defined by combining the coupling threshold and the coupling coefficient, and the parameter adjustment interval is determined. Combining this interval with the real-time parameters, the adjustment priority and adjustment step size of each component are collaboratively allocated, and parameter adjustment commands are generated. The commands are sent to the corresponding actuators of the power system and stability control system to achieve synchronous adjustment of multiple components, thereby achieving coordinated action of the vehicle power system and stability control system, and solving the technical problem of how to achieve efficient collaborative and optimized control among multiple components.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, and in particular to a collaborative optimization control method and system for vehicle components. Background Technology

[0002] With the rapid development of the automotive industry and the continuous advancement of intelligent and electric vehicle trends, the number of components and system complexity in modern vehicles have increased significantly. The interaction between subsystems such as the powertrain, braking system, steering system, and stability control system is becoming increasingly close. Traditional independent control strategies are no longer sufficient to meet the comprehensive performance, energy efficiency, and safety requirements of vehicles under complex operating conditions. Especially in scenarios such as high-speed load changes, emergency obstacle avoidance, or slippery road surfaces, the dynamic coupling effect between components is significantly enhanced. Without an effective collaborative control mechanism, control conflicts or response lags can easily occur, affecting the overall vehicle handling quality and driving safety. Therefore, achieving efficient collaboration and optimized control among multiple components has become a key technical challenge for improving the overall performance of vehicles. Summary of the Invention

[0003] The main objective of this invention is to provide a collaborative optimization control method for vehicle components, which solves the technical problem of how to achieve efficient collaboration and optimized control among multiple components.

[0004] To achieve the above objectives, the present invention provides a collaborative optimization control method for vehicle components, comprising the following steps:

[0005] Real-time operating parameters of multiple target components of the vehicle are collected through sensors;

[0006] Based on the real-time operating parameters, the coupling relationship between each target component is quantitatively analyzed to obtain the component coupling coefficient, and based on the component coupling coefficient, it is determined whether a preset coupling threshold is triggered.

[0007] If triggered, the optimizable parameter range of each target component is defined based on the coupling threshold and the component coupling coefficient, and the parameter adjustment range of each target component is obtained.

[0008] Based on the parameter adjustment range and the real-time operating parameters, the adjustment priority and adjustment step size of each target component are coordinated and allocated to generate corresponding parameter adjustment instructions.

[0009] The parameter adjustment command is sent to the corresponding target component actuator to synchronously adjust each target component, thereby achieving coordinated operation of the vehicle power system and stability control system.

[0010] Furthermore, the real-time operating parameters of multiple target components of the vehicle are collected via sensors, including:

[0011] By collecting parameters from multiple target components using sensors that correspond one-to-one with each target component, raw operating data is obtained.

[0012] The original running data is timestamped to obtain running data with timestamps;

[0013] Outliers in the time-stamped running data are removed, and the removed time-stamped running data is associated with the identification information of the corresponding target component to obtain real-time running parameters.

[0014] Furthermore, the step of quantitatively analyzing the coupling relationship between each target component based on the real-time operating parameters to obtain the component coupling coefficient, and determining whether a preset coupling threshold is triggered based on the component coupling coefficient, includes:

[0015] The real-time operating parameters are segmented according to a preset time interval to obtain the parameter segment data of each target component, and the average value of the parameter segment data is calculated to obtain the segment mean parameter.

[0016] The piecewise mean parameters of any two target components are coupled and the calculated coupling changes are normalized to obtain the component coupling coefficient.

[0017] Subtract the component coupling coefficient of the previous cycle from the component coupling coefficient of the current cycle to obtain the change in coupling coefficient;

[0018] The change in the coupling coefficient is compared with a set dynamic threshold to obtain a comparison result, and a determination is made based on the comparison result to determine whether the preset coupling threshold is triggered.

[0019] Furthermore, the step of defining the optimizable parameter range for each target component based on the coupling threshold and the component coupling coefficient to obtain the parameter adjustment range for each target component includes:

[0020] Based on the coupling threshold and component coupling coefficient, the optimizable parameter range of each target component is determined, and the intersection of the optimizable parameter range and the safe operation threshold of the corresponding target component is calculated to obtain the safe parameter interval.

[0021] For target components with coupling relationships, a correlation conflict check is performed on the safety parameter range to obtain parameter conflict points, and the conflict points are classified into conflict levels to obtain conflict level identifiers.

[0022] Based on the conflict level identifier, adjust the optimizable parameter range of each target component until there are no more parameter conflict points, thus obtaining the parameter adjustment range of each target component.

[0023] Furthermore, a correlation conflict check is performed on the safety parameter ranges of target components with coupling relationships to identify parameter conflict points, including:

[0024] Cross-calculation is performed on the safety parameter ranges of two components in a target component with a coupling relationship to determine whether there are parameter values ​​that would cause the other component to exceed the safety range if the adjustment requirement of one of the two components is met, and the interval conflict determination result is obtained.

[0025] Record the conflicting parameter values ​​and corresponding component identifiers in the interval conflict determination results to obtain the parameter conflict points.

[0026] Furthermore, the step of performing an intersection operation between the optimizable parameter range and the safe operating threshold of the corresponding target component to obtain a safe parameter range includes:

[0027] Boundary extraction is performed on the range of optimizable parameters to obtain the upper and lower optimization limits, and interval analysis is performed on the safe operation threshold of the target component to obtain the upper and lower safety limits.

[0028] The optimization upper limit value is compared with the safety upper limit value, and the smaller value is taken as the intersection upper limit. The optimization lower limit value is compared with the safety lower limit value, and the larger value is taken as the intersection lower limit. The safety parameter range is determined based on the intersection upper limit and the intersection lower limit.

[0029] Furthermore, based on the parameter adjustment range and the real-time operating parameters, adjustment priorities and adjustment step sizes are collaboratively allocated for each target component, generating corresponding parameter adjustment instructions, including:

[0030] The adjustment requirement for each target component is calculated based on the parameter adjustment range and real-time operating parameters, and the adjustment priority is determined based on the adjustment requirement.

[0031] The single adjustment ratio of each target component is calculated based on the adjustment priority and component coupling coefficient to obtain the initial adjustment step size. The initial adjustment step size is then corrected by coupling correlation to obtain the balanced adjustment step size.

[0032] The adjustment priority is associated with the equalization adjustment step size to obtain the timing adjustment scheme for each target component, and a parameter adjustment instruction containing the adjustment sequence identifier and step size value is generated based on the timing adjustment scheme.

[0033] Furthermore, the target component actuator includes a power system actuator and a stability control system. Sending the parameter adjustment command to the corresponding target component actuator to synchronously adjust each target component and achieve coordinated operation of the vehicle power system and stability control system includes:

[0034] The parameter adjustment commands are classified according to their system category to obtain power system adjustment commands and stability control system adjustment commands;

[0035] The power system adjustment command is sent to the power system actuator, and the stability control system adjustment command is sent to the stability control system, so as to synchronously adjust each target component and realize the coordinated action of the vehicle power system and the stability control system.

[0036] The present invention also provides a cooperative optimization control system for vehicle components, comprising:

[0037] The acquisition module is used to collect real-time operating parameters of multiple target components of the vehicle through sensors;

[0038] The analysis module is used to perform quantitative analysis on the coupling relationship between each target component based on the real-time operating parameters, obtain the component coupling coefficient, and determine whether a preset coupling threshold is triggered based on the component coupling coefficient.

[0039] The definition module is used to define the optimizable parameter range of each target component based on the coupling threshold and the component coupling coefficient if triggered, so as to obtain the parameter adjustment range of each target component.

[0040] The allocation module is used to coordinate the allocation of adjustment priority and adjustment step size for each target component based on the parameter adjustment range and the real-time operating parameters, and generate corresponding parameter adjustment instructions.

[0041] The adjustment module is used to send the parameter adjustment command to the corresponding target component actuator to synchronously adjust each target component and realize the coordinated action of the vehicle power system and stability control system.

[0042] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of any of the methods described above.

[0043] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any of the methods described above.

[0044] This invention provides a collaborative optimization control method for vehicle components. It collects real-time operating parameters of multiple target components of the vehicle using sensors; quantifies and analyzes the coupling relationships between the target components based on these real-time operating parameters to obtain component coupling coefficients; and determines whether a preset coupling threshold is triggered based on these coupling coefficients. If triggered, it defines the optimizable parameter range for each target component based on the coupling threshold and the component coupling coefficients, obtaining the parameter adjustment range for each target component. Based on the parameter adjustment range and the real-time operating parameters, it collaboratively allocates adjustment priority and adjustment step size for each target component, generating corresponding parameter adjustment commands. These parameter adjustment commands are sent to the corresponding target component actuators to synchronously adjust each target component, achieving coordinated action between the vehicle's powertrain and stability control systems. This solves the technical problem of how to achieve efficient collaborative and optimized control between multiple components by synchronously sending parameter adjustment commands to each actuator, thus realizing collaborative regulation between multiple systems. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This is a schematic diagram of the steps of a collaborative optimization control method for vehicle components in one embodiment of the present invention;

[0047] Figure 2 This is a structural block diagram of a collaborative optimization control system for vehicle components in one embodiment of the present invention;

[0048] Figure 3 This is a schematic block diagram of the structure of a computer device according to an embodiment of the present invention.

[0049] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0051] like Figure 1 As shown, Figure 1 This invention provides a collaborative optimization control method for vehicle components, comprising the following steps:

[0052] Step S1: Collect real-time operating parameters of multiple target components of the vehicle using sensors.

[0053] Specifically, this step involves collecting real-time operating parameters of multiple target components of the vehicle using sensors. This is achieved by first deploying corresponding sensor devices on key target components of the vehicle. These target components include, but are not limited to, the drive motor, brake calipers, steering gear, suspension actuators, and the inertial measurement unit in the vehicle stability control system. The sensor types are configured according to the physical characteristics of each component. For example, speed and torque sensors are installed on the drive motor, pressure sensors are configured in the braking system, and acceleration and yaw rate sensors are placed on the vehicle body. All sensors continuously monitor the operating status of their respective target components and transmit the collected data, such as motor output torque, brake pressure, steering wheel angle, suspension displacement, and vehicle lateral acceleration, to the central control unit at a fixed sampling frequency. The data transmission process is achieved through the vehicle's CAN bus or high-bandwidth Ethernet to ensure real-time performance and synchronization. After receiving this raw data, the central control unit performs filtering, calibration, and timestamp alignment to form a set of real-time operating parameters under a unified time base. This provides a data foundation for subsequent quantitative analysis of the coupling relationship between various target components based on these parameters. For example, when the vehicle is driving at high speed and performing an emergency lane change, the steering wheel angle sensor and yaw rate sensor will capture the steering action and body response in real time. At the same time, the torque output of the drive motor and the compression of the outer suspension are also recorded synchronously. These real-time operating parameters from multiple target components are integrated to analyze the dynamic coupling effect between the steering system, power system, and suspension system, thereby supporting the subsequent determination of whether a preset coupling threshold is triggered.

[0054] Step S2: Quantitatively analyze the coupling relationship between each target component based on the real-time operating parameters to obtain the component coupling coefficient, and determine whether a preset coupling threshold is triggered based on the component coupling coefficient.

[0055] Specifically, based on the real-time operating parameters, the coupling relationship between each target component is quantitatively analyzed to obtain the component coupling coefficient. Then, based on the component coupling coefficient, it is determined whether a preset coupling threshold is triggered. This step is implemented by inputting the real-time operating parameters of multiple target components collected by sensors into a preset coupling relationship analysis model. This model uses dynamic correlation algorithms or state-space equations to mathematically model the interaction effects between different components. For example, it uses mutual information entropy, Granger causality, or neural network methods to calculate the interaction strength of any two target components under the current operating condition, thereby generating a component coupling coefficient characterizing their coupling degree. This component coupling coefficient is a dimensionless value, reflecting the degree of influence of the state change of one target component on the output response of another target component. The calculated component coupling coefficient is then compared with the preset coupling threshold in the control system. If the component coupling coefficient is greater than or equal to the coupling threshold, the trigger condition is determined to be met, and the subsequent optimization and adjustment process is initiated. Otherwise, the current control strategy remains unchanged. For example, when a vehicle makes an emergency lane change at high speed, the change in steering wheel angle causes a significant increase in the vehicle's yaw rate. At the same time, the drive motor outputs asymmetrical power due to the torque distribution strategy adjustment, and the suspension system experiences a difference in left and right travel due to roll. At this time, by analyzing the real-time operating parameters between the steering wheel angle and the yaw rate, the component coupling coefficient between the steering system and the stability control system is calculated. If the coefficient exceeds the preset coupling threshold, it indicates that there is a strong coupling effect between the two, and the parameter adjustment range definition and collaborative adjustment mechanism need to be activated.

[0056] Step S3: If triggered, the optimizable parameter range of each target component is defined based on the coupling threshold and the component coupling coefficient, and the parameter adjustment range of each target component is obtained.

[0057] Specifically, if triggered, the optimizable parameter range for each target component is defined based on the coupling threshold and the component coupling coefficient, resulting in the parameter adjustment range for each target component. This step is implemented by calling a pre-calibrated multi-dimensional parameter constraint model when the component coupling coefficient reaches or exceeds the preset coupling threshold. This model integrates vehicle dynamics boundary conditions, actuator physical limits, and stability safety margins, combined with the relative relationship between the current component coupling coefficient and the coupling threshold, to dynamically generate optimizable parameter boundaries for each target component. For example, when the component coupling coefficient is significantly higher than the coupling threshold, the aggressive adjustment range is narrowed to enhance system robustness, while a wider adjustment range is allowed when it slightly exceeds the threshold to improve response performance. The parameter boundaries are determined by a lookup table method or by solving the constraint optimization problem in real time, forming a range containing upper and lower limits. The parameter adjustment range covers the torque output range of the drive motor, the braking torque window that the electronic stability program can apply, the stiffness adjustment bandwidth of the active suspension, and the gain range of the steering system's additional assist. All parameter adjustment ranges are defined to ensure that the vehicle does not experience sideslip, instability, or actuator saturation. For example, when the vehicle is making an emergency lane change at high speed, if the coupling coefficient between the steering system and the vehicle stability control system triggers the coupling threshold due to violent operation, an adjustment range of ±15% is set for the torque difference between the left and right wheels of the drive motor based on the current yaw rate increase rate and the peak value of the lateral acceleration. An upper limit of 0.8 times the maximum value is set for the braking torque of the ESP system, and an adjustable range of 20%-40% is set for the stiffness of the outer support of the active suspension. This provides a safe and feasible operating boundary for generating coordinated parameter adjustment commands in the future.

[0058] Step S4: Based on the parameter adjustment range and the real-time operating parameters, the adjustment priority and adjustment step size of each target component are coordinated and allocated to generate corresponding parameter adjustment instructions.

[0059] Specifically, based on the parameter adjustment range and the real-time operating parameters, the adjustment priority and adjustment step size are collaboratively allocated for each target component, generating corresponding parameter adjustment instructions. This step is implemented by inputting the previously determined parameter adjustment ranges for each target component and the real-time operating parameters continuously collected by sensors into the multi-target collaborative decision-making module. This module performs comprehensive calculations based on preset priority determination rules and dynamic step size calculation algorithms. The priority determination rules rank the target components according to the urgency of their impact on vehicle stability under the current operating conditions. For example, in a scenario dominated by lateral stability, the ESP actuator in the vehicle stability control system has a higher priority than the drive motor and suspension system. The adjustment step size is calculated proportionally based on the degree to which the real-time operating parameters deviate from the safety threshold and the width of the parameter adjustment range. The greater the deviation and the wider the adjustable range, the larger the allocated adjustment step size. The larger the value, the more coordination factors are introduced to prevent multiple target components from having excessive adjustment ranges or canceling each other out in the same control cycle. All priority and step size allocation results are weighted and fused to generate specific parameter adjustment instructions for each target component. This instruction clearly indicates the target value and its rate of change that the actuator needs to adjust in the current control cycle. For example, when the vehicle is making an emergency lane change at high speed, if the real-time operating parameters show that the vehicle body yaw rate is rising rapidly and has triggered the coupling threshold, the parameter adjustment range determines that the ESP needs to increase the maximum braking torque by 0.6 times within 0.2 seconds, the drive motor needs to adjust the left and right torque difference to 12% within 0.3 seconds, and the outer stiffness of the active suspension needs to be increased by 30%. At this time, the coordination allocation mechanism will send adjustment instructions to the ESP first and allocate a larger step size, and then issue adjustment instructions to the motor and suspension in sequence according to priority to ensure that the vehicle response is coordinated and consistent.

[0060] Step S5: Send the parameter adjustment command to the corresponding target component actuator to synchronously adjust each target component and realize the coordinated operation of the vehicle power system and stability control system.

[0061] Specifically, the parameter adjustment commands are sent to the corresponding target component actuators to synchronously adjust each target component, achieving coordinated operation of the vehicle's powertrain and stability control systems. This step is implemented by encapsulating and timestamping the aforementioned parameter adjustment commands according to a preset communication protocol via the vehicle communication network, and distributing them according to the target component type and its corresponding actuator address specified in the command. For example, torque adjustment commands for the drive motor are sent to the motor controller (MCU), braking intervention commands are transmitted to the electronic stability program control unit (ESP), and suspension stiffness adjustment commands are sent to the adjustable damping controller. All commands are sent using a time synchronization mechanism to ensure that the time deviation of each actuator receiving the command is controlled within milliseconds. To ensure the synchronicity of adjustment actions, after receiving parameter adjustment commands, the actuators of each target component perform corresponding operations within their allowable dynamic range according to the adjustment target value and step size specified in the command, and feed back the execution status to the central control unit to form a closed loop. For example, when the vehicle makes an emergency lane change at high speed, when the parameter adjustment command requires the drive motor to adjust the torque difference between the left and right wheels, the ESP to apply a special torque, and the active suspension to increase the stiffness of the outer side, these commands are simultaneously sent to the corresponding motor controller, brake control unit, and suspension control module. Each actuator starts adjustment within the same control cycle, so that the torque distribution of the power system, the intervention force of the braking system, and the support response of the suspension system work together to suppress body roll and yaw oscillation, and achieve coordinated action of the vehicle's power system and stability control system.

[0062] In a specific scenario, the real-time operating parameters of multiple target components of the vehicle collected by sensors include:

[0063] By collecting parameters from multiple target components using sensors that correspond one-to-one with each target component, raw operating data is obtained.

[0064] The original running data is timestamped to obtain running data with timestamps;

[0065] Outliers in the time-stamped running data are removed, and the removed time-stamped running data is associated with the identification information of the corresponding target component to obtain real-time running parameters.

[0066] Specifically, real-time operating parameters of multiple target components of the vehicle are collected through sensors, including collecting parameters of multiple target components through sensors corresponding one-to-one with each target component to obtain raw operating data; and performing timestamp synchronization processing on the raw operating data to obtain time-stamped operating data.Outliers in the time-stamped operational data are removed, and the processed time-stamped operational data is associated with the identification information of the corresponding target components to obtain real-time operational parameters. The specific implementation process involves first installing dedicated sensors matching the functional characteristics of each target component on the vehicle. These target components include key subsystems such as the drive motor, brake calipers, steering gear, active suspension unit, and inertial measurement unit in the vehicle stability control system. Each target component is equipped with one or more dedicated sensors. For example, torque and speed sensors are arranged on the drive motor output shaft; hydraulic pressure sensors are installed on the brake master cylinder and wheel-side brakes; steering wheel angle and steering torque sensors are integrated into the steering gear; displacement sensors are installed on the four wheel suspension struts; and accelerometers and gyroscopes are arranged near the vehicle's center of gravity to obtain yaw rate and lateral acceleration. These sensors continuously collect the physical state signals of their respective target components, forming a set of unprocessed raw operational data. This raw operational data includes voltage, current, frequency, or pulse signals, etc. Subsequently, all the collected raw operational data is transmitted through the vehicle's CAN bus. The data is transmitted from the FD or in-vehicle Ethernet to the central control unit. During data reception, the central control unit adds a precise timestamp to each received data packet. This timestamp originates from a globally unified high-precision clock source, ensuring that all raw operating data from different target components are aligned on the timeline, forming time-stamped operating data. Next, outlier identification and removal are performed on the time-stamped operating data. A sliding window filtering algorithm or a statistical three-standard-deviation rule is used to determine whether a data point deviates from the normal fluctuation range. If a data point exceeds a preset threshold, it is identified as an outlier and removed. Simultaneously, cross-validation is performed using data from adjacent sensors. For example, if the steering wheel angle changes abruptly but the yaw rate does not respond accordingly, an anomaly in the data from one of the sensors is suspected, further improving data reliability. The time-stamped operating data after removal is then compared with the unique identifier of its corresponding target component. Identification information is bound to the system. This identification information is a preset numerical code, such as "MCU_FL" representing the left front motor, "ESP_RR" representing the right rear wheel brake, and "SUSP_FR" representing the right front suspension. This identification enables precise traceability of the data source, ultimately forming structured and parsable real-time operating parameters. These parameters are used for subsequent quantitative analysis of the coupling relationships between various target components. For example, during an emergency lane change at high speed, the steering wheel angle sensor records the driver's rapid steering action. Simultaneously, the left front motor torque increases sharply, the right rear wheel brake pressure rises, and the right front suspension compression increases. These raw operating data are tagged with the same timestamp after collection. After outlier removal and association with their respective target component identifiers, a set of synchronized and reliable real-time operating parameters is formed. This supports subsequent judgment on whether the coupling strength between the steering system and the stability control system triggers a preset coupling threshold.

[0067] In a specific scenario, the quantitative analysis of the coupling relationship between each target component based on the real-time operating parameters to obtain the component coupling coefficient, and the determination of whether a preset coupling threshold is triggered based on the component coupling coefficient, includes:

[0068] The real-time operating parameters are segmented according to a preset time interval to obtain the parameter segment data of each target component, and the average value of the parameter segment data is calculated to obtain the segment mean parameter.

[0069] The piecewise mean parameters of any two target components are coupled and the calculated coupling changes are normalized to obtain the component coupling coefficient.

[0070] Subtract the component coupling coefficient of the previous cycle from the component coupling coefficient of the current cycle to obtain the change in coupling coefficient;

[0071] The change in the coupling coefficient is compared with a set dynamic threshold to obtain a comparison result, and a determination is made based on the comparison result to determine whether the preset coupling threshold is triggered.

[0072] Specifically, the quantitative analysis of the coupling relationship between each target component based on the real-time operating parameters to obtain the component coupling coefficient, and the determination of whether a preset coupling threshold is triggered based on the component coupling coefficient, includes segmenting the real-time operating parameters according to a preset time interval to obtain parameter segment data for each target component, and calculating the average of the parameter segment data to obtain the segmented average parameter; calculating the coupling change of any two target components' segmented average parameters, and normalizing the calculated coupling change to obtain the component coupling coefficient; subtracting the component coupling coefficient of the previous period from the component coupling coefficient of the current period to obtain the coupling coefficient change; and then... The momentum is compared with a set dynamic threshold to obtain a comparison result. Based on the comparison result, it is determined whether a preset coupling threshold is triggered. The specific implementation of this step is as follows: First, the real-time operating parameters of the aforementioned associated identification information are processed into data slices according to a fixed time window length, such as 100 milliseconds per cycle, to form continuous time series segments, i.e., parameter segment data of each target component. Each parameter segment data contains multiple sampling points of a target component such as drive motor torque, braking pressure, or suspension displacement within that time period. Then, an arithmetic mean is performed on each parameter segment data to eliminate the influence of instantaneous fluctuations, resulting in a segment average representing the average working state within that time period. The parameters are then used to select any two target components that may have physical interaction, such as the left front drive motor and the right front active suspension, or the steering wheel angle sensor and the vehicle yaw rate sensor. The segmented average parameters of these components within the same time window are used to calculate their coupling changes. This calculation employs the differential rate of change method, which involves calculating the numerical changes of both components between two adjacent segments, and then calculating the consistency of their change direction and the correlation of their magnitudes. If both components increase or decrease synchronously, it is considered positive coupling; if the change directions are opposite, it is considered negative coupling. The absolute value of their product reflects the coupling strength. This coupling change value is then normalized to the 0-1 interval using a linear mapping method, forming a dimensionless component coupling parameter. The coupling coefficient is used to determine the dynamic correlation between two target components under the current operating conditions. The higher the coefficient, the stronger the dynamic correlation between the two components. The system continuously monitors the time evolution trend of the coupling coefficient and subtracts the coupling coefficient of the previous cycle from the coupling coefficient calculated in the current control cycle to obtain a difference, which is the change in coupling coefficient. This change reflects the rate of change of coupling strength. If the absolute value of the change is large, it indicates that the coupling state of the system is rapidly increasing or decreasing. Finally, the change in coupling coefficient is compared with a preset dynamic threshold in the control system. This dynamic threshold is adaptively adjusted according to operating conditions such as vehicle speed and road adhesion coefficient. For example, the threshold is set to 0.15 when driving at high speed and 0 when driving at low speed.10. If the change in coupling coefficient exceeds the dynamic threshold, a positive comparison result is output, indicating that the trigger condition has been met, and the process proceeds to the subsequent parameter adjustment range definition process. Otherwise, the current control strategy is maintained. For example, during an emergency lane change at high speed, the segmented average parameter of the steering wheel angle increases significantly in a short period of time, and the segmented average parameter of the vehicle's yaw rate also increases rapidly. After normalization of the coupled changes, the component coupling coefficient increases from 0.3 to 0.75. Subtracting the previous cycle from the current cycle yields a coupling coefficient change of 0.45, which significantly exceeds the set dynamic threshold of 0.15. Therefore, it is determined that the preset coupling threshold has been triggered, and the subsequent collaborative optimization adjustment mechanism is initiated.

[0073] In specific scenarios, the step of defining the optimizable parameter range for each target component based on the coupling threshold and the component coupling coefficient to obtain the parameter adjustment range for each target component includes:

[0074] Based on the coupling threshold and component coupling coefficient, the optimizable parameter range of each target component is determined, and the intersection of the optimizable parameter range and the safe operation threshold of the corresponding target component is calculated to obtain the safe parameter interval.

[0075] For target components with coupling relationships, a correlation conflict check is performed on the safety parameter range to obtain parameter conflict points, and the conflict points are classified into conflict levels to obtain conflict level identifiers.

[0076] Based on the conflict level identifier, adjust the optimizable parameter range of each target component until there are no more parameter conflict points, thus obtaining the parameter adjustment range of each target component.

[0077] Specifically, the step of defining the optimizable parameter range for each target component based on the coupling threshold and the component coupling coefficient to obtain the parameter adjustment range for each target component includes determining the optimizable parameter range for each target component based on the coupling threshold and the component coupling coefficient, and performing an intersection operation between the optimizable parameter range and the safe operation threshold of the corresponding target component to obtain a safe parameter range; performing an association conflict check on the safe parameter ranges of target components with coupling relationships to obtain parameter conflict points, and classifying the conflict points into conflict levels to obtain conflict level identifiers;Based on the conflict level identifier, the optimizable parameter range of each target component is adjusted until there are no more parameter conflict points, thus obtaining the parameter adjustment range for each target component. Specifically, this step involves first determining the optimizable parameter range for each target component under the current operating condition based on the relative relationship between the previously calculated component coupling coefficient and the preset coupling threshold. For example, if the component coupling coefficient is significantly higher than the coupling threshold, it indicates that the system is in a strongly coupled state. In this case, the optimizable parameter range is narrowed to limit aggressive adjustments. If the component coupling coefficient is slightly higher than the threshold, a wider adjustment window is allowed. This optimizable parameter range is centered on the baseline operating parameters of the target component, extending upwards and downwards by a certain proportion to form an interval. For example, the drive motor torque can be within ±... Within a 20% adjustment range, the active suspension stiffness can be adjusted within ±30%. This optimizable parameter range is then intersected with the preset safe operating thresholds of the corresponding target components. These safe operating thresholds are derived from vehicle dynamics limits and actuator physical capabilities, such as the maximum output torque of the motor, the upper limit of braking system pressure, and the maximum suspension travel. The intersection calculation ensures that the final adjustment range does not exceed the hardware safety boundaries, thus obtaining the safe parameter range. Next, a correlation conflict check is performed on the safe parameter ranges between coupled target components to determine if there are any contradictory control objectives. For example, during an emergency lane change, to suppress body roll, the outer suspension stiffness needs to be increased, but to improve comfort, it may be desirable to reduce stiffness, or to enhance steering response... The system addresses a conflict where increased front-wheel drive is needed, but torque output must be limited to prevent slippage. This conflict is termed a parameter conflict point. The system categorizes conflicts into high-conflict-level categories based on their impact on vehicle stability. Conflicts that could lead to instability or skidding are marked as high-conflict-level, while those affecting only comfort or energy consumption are marked as low-conflict-level. The system then dynamically adjusts the optimizable parameter ranges for each target component based on these conflict-level indicators. Priority is given to ensuring the adjustment freedom of high-conflict-level components, while appropriately compressing the range of low-conflict-level components. For example, at high-conflict-levels, priority is given to meeting the need for increased suspension stiffness, limiting the drive torque adjustment range. After adjustment, the safety parameter range is recalculated and conflict checks are performed. This process is repeated until all conflicts are resolved. Parameter conflicts are eliminated, ultimately outputting a set of conflict-free, safe, and feasible parameter adjustment ranges. For example, during an emergency lane change at high speed, the coupling coefficients of the steering wheel angle and yaw rate trigger coupling thresholds. Initially, the system determines the drive motor torque adjustment range to be ±18%, the suspension stiffness adjustment range to be +25% to +40%, and the ESP braking torque range to be 0.5 to 0.9 times the maximum value. After intersecting with the safe operating thresholds, a safe parameter range is formed. Conflict checks then reveal an execution conflict between the torque increase and braking intervention. After conflict level classification confirms that stability takes priority, the upper limit of the motor torque is adjusted to +12%, releasing braking adjustment space. Finally, a coordinated parameter adjustment range is achieved for subsequent command generation.

[0078] In specific scenarios, correlation conflict checks are performed on the safety parameter ranges of target components with coupling relationships to identify parameter conflict points, including:

[0079] Cross-calculation is performed on the safety parameter ranges of two components in a target component with a coupling relationship to determine whether there are parameter values ​​that would cause the other component to exceed the safety range if the adjustment requirement of one of the two components is met, and the interval conflict determination result is obtained.

[0080] Record the conflicting parameter values ​​and corresponding component identifiers in the interval conflict determination results to obtain the parameter conflict points.

[0081] Specifically, a correlation conflict check is performed on the safety parameter ranges of target components with coupling relationships to obtain parameter conflict points. This includes performing cross-calculation on the safety parameter ranges of two components within the coupled target components to determine whether there are parameter values ​​that would cause the other component to exceed its safe range if the adjustment requirement of one of the two components is satisfied, thus obtaining a range conflict determination result. The conflicting parameter values ​​and their corresponding component identifiers in the range conflict determination result are recorded to obtain parameter conflict points. The specific implementation of this step is to first extract component pairs with dynamic interaction relationships from the aforementioned multiple generated safety parameter ranges of target components. These component pairs are predefined based on the vehicle dynamics model, such as drive motors and electric motors. The Electronic Stability Program (ESP) forms a lateral and longitudinal force coordination pair, while the active suspension and steering system form a lateral stability correlation pair. The safety parameter ranges for each pair of components are expressed as numerical ranges, such as the drive motor torque adjustment range of +8% to +15%, the ESP braking torque adjustment range of 0.6 to 0.8 times the maximum value, the active suspension stiffness adjustment range of +20% to +35%, and the steering assist gain range of +10% to +25%. Subsequently, cross-calculation is performed on the safety parameter ranges of the two components in each pair of coupled target components. This calculation uses a combination of interval overlap analysis and coupling mapping functions, that is, traversing key nodes within the parameter value range of one side and deriving its effect on the other side through a preset coupling mapping relationship. The influence of parameters, for example, when the drive motor outputs +15% torque, according to the vehicle dynamics model, it will significantly increase the slip ratio of the outer wheel, thus requiring the ESP to increase the braking torque to more than 0.85 times to maintain stability. However, this value exceeds the upper limit of the current safe parameter range of ESP by 0.8 times, indicating that meeting the drive motor adjustment requirements will cause ESP to exceed its safe range, thus determining that there is a range conflict. Similarly, if the active suspension stiffness is increased to +35%, it will aggravate the vehicle's response sensitivity, causing the yaw rate to increase too quickly. The steering system needs to reduce the power assist gain to below +5% to suppress oversteer, but this value is lower than the steering system's set lower limit of +10%, which also constitutes a conflict. This type of conflict arises because a target component has its own safety parameters. The result of a conflict determination is when an adjustment within a certain range forces another target component to exceed its own safety boundary. The system records in a structured manner all the parameter values ​​involved in the identified conflict determination results and their corresponding target component identifiers. The parameter values ​​include the source parameter that caused the conflict and the target parameter that was affected. The component identifiers are clearly marked, such as "MCU_RR" for the right rear motor, "ESP_FL" for the left front brake, and "SUSP_FR" for the right front suspension. For example, when the vehicle is making an emergency lane change at high speed, if the system detects that the drive motor torque increases to +15%, the ESP will need to apply 0.85 times the braking torque to balance the lateral force, but this value exceeds the upper limit of the ESP safety parameter range.The torque is 8 times the normal torque, therefore a parameter conflict point is recorded as "When MCU_RR torque ≥ +14.5%, the required braking torque of the ESP assembly > 0.8max". Similarly, if the right front suspension stiffness is adjusted to +35%, the steering system will need to reduce the power assist gain to below +8%, which is lower than its safety limit of +10%. Therefore, another parameter conflict point is recorded as "When SUSP_FR stiffness ≥ +34%, the steering assist gain < +10%". These parameter conflict points serve as the basis for subsequent conflict level classification and optimization parameter range adjustment, ensuring that the final generated parameter adjustment range is executed without contradiction under multi-objective coordination.

[0082] In a specific scenario, the step of performing an intersection operation between the optimizable parameter range and the safe operating threshold of the corresponding target component to obtain a safe parameter range includes:

[0083] Boundary extraction is performed on the range of optimizable parameters to obtain the upper and lower optimization limits, and interval analysis is performed on the safe operation threshold of the target component to obtain the upper and lower safety limits.

[0084] The optimization upper limit value is compared with the safety upper limit value, and the smaller value is taken as the intersection upper limit. The optimization lower limit value is compared with the safety lower limit value, and the larger value is taken as the intersection lower limit. The safety parameter range is determined based on the intersection upper limit and the intersection lower limit.

[0085] Specifically, the step of performing an intersection operation between the optimizable parameter range and the corresponding target component's safe operating threshold to obtain a safe parameter interval includes: extracting the boundaries of the optimizable parameter range to obtain an upper and lower optimization limit; performing interval analysis on the target component's safe operating threshold to obtain a safe upper and lower safety limit; comparing the upper optimization limit with the safe upper limit and taking the smaller value as the upper intersection limit; comparing the lower optimization limit with the safe lower limit and taking the larger value as the lower intersection limit; and determining the safe parameter interval based on the upper and lower intersection limits. The specific implementation of this step is to first perform an intersection operation on each parameter range based on the aforementioned steps... Based on the optimizable parameter range determined by the threshold and component coupling coefficient, a boundary extraction operation is performed. This operation separates the maximum and minimum allowable values—the upper and lower limits of optimization—by parsing the numerical expression or data structure of this range. For example, for the torque adjustment requirement of the drive motor, if the optimizable parameter range calculated based on the current coupling state is +5% to +18%, then the upper limit of optimization is +18%, and the lower limit is +5%. For the stiffness adjustment requirement of the right front active suspension, if the optimizable parameter range is +22% to +40%, then the upper limit of optimization is +40%, and the lower limit is +22%. Subsequently, a preset safe operating threshold is applied to the corresponding target component. The process involves interval analysis. The safe operating thresholds are hard limitations set based on vehicle design specifications, actuator physical limits, and dynamic stability boundaries. For example, due to thermal protection and mechanical strength limitations, the maximum output torque of the drive motor cannot exceed +25% of its rated value, and the minimum cannot be lower than -5%, meaning the upper safety limit is +25% and the lower safety limit is -5%. Similarly, the stiffness adjustment of the right front suspension, due to structural travel limitations, cannot exceed +35% and the minimum cannot be lower than +15%, meaning the upper safety limit is +35% and the lower safety limit is +15%. Next, an intersection operation is performed. This operation uses interval intersection logic, comparing the optimized upper limit value with the safe upper limit value and taking the smaller of the two as the optimal value. The final intersection upper limit is determined by comparing the optimization lower limit and the safety lower limit, and taking the larger of the two as the intersection lower limit. For example, for the drive motor, the optimization upper limit of +18% is less than the safety upper limit of +25%, so the intersection upper limit is +18%. The optimization lower limit of +5% is greater than the safety lower limit of -5%, so the intersection lower limit is +5%. The final determined safety parameter range is +5% to +18%. For the right front suspension, the optimization upper limit of +40% is greater than the safety upper limit of +35%, so the intersection upper limit is +35%. The optimization lower limit of +22% is greater than the safety lower limit of +15%, so the intersection lower limit is +22%. The final safety parameter range is +22% to +35%.This process ensures that all subsequent adjustments are performed within the hardware capabilities and vehicle safety boundaries. For example, during an emergency lane change at high speed, the system determines that the steering and stability systems are strongly coupled based on real-time operating parameters. Initially, the drive motor torque can be adjusted to +20%, but its safe operating threshold is capped at +25%. After intersection calculation, the +20% upper limit is retained. The right front suspension could originally be optimized to +40%, but is limited by its safe operating threshold of +35%. Ultimately, the safety parameter range is compressed to within +35%, thereby preventing the actuators from operating beyond their limits and ensuring system stability and reliability.

[0086] In a specific scenario, adjusting the optimizable parameter range of each target component based on the conflict level identifier until there are no more parameter conflict points, to obtain the parameter adjustment range of each target component, includes:

[0087] Based on the conflict level identifier, the conflict points of the parameters are sorted by conflict severity to obtain a conflict priority sequence. Then, the parameter adjustment priority of each target component is determined according to the conflict priority sequence to obtain a component adjustment sequence.

[0088] The optimizable parameter range of high-priority target components in the component adjustment sequence is subjected to boundary shrinkage processing to obtain the shrunken parameter range. The shrunken parameter range is then re-matched and verified with the safety parameter range of other target components that have coupling relationships to obtain the parameter matching verification result.

[0089] Based on the parameter matching verification results, the remaining parameter conflict points are checked for conflict elimination to obtain the conflict elimination status. When the conflict elimination status shows that parameter conflict points still exist, the boundary shrinkage process is repeated for the next priority target component until the conflict elimination status shows that there are no parameter conflict points, thus obtaining the parameter adjustment range of each target component.

[0090] Specifically, adjusting the optimizable parameter range of each target component based on the conflict level identifier until there are no more parameter conflict points, to obtain the parameter adjustment range of each target component, includes sorting the parameter conflict points by conflict severity based on the conflict level identifier to obtain a conflict priority sequence, and determining the parameter adjustment priority of each target component according to the conflict priority sequence to obtain a component adjustment sequence; performing boundary shrinking processing on the optimizable parameter range of high-priority target components in the component adjustment sequence to obtain a shrunken parameter range, and re-matching and verifying the shrunken parameter range with the safety parameter range of other target components with coupling relationships to obtain a parameter matching verification result; based on The parameter matching verification results are used to check for conflict elimination of the remaining parameter conflict points to obtain a conflict elimination status. When the conflict elimination status indicates that parameter conflict points still exist, the boundary shrinkage process is repeated for the next priority target component until the conflict elimination status indicates that there are no parameter conflict points, thus obtaining the parameter adjustment range for each target component. The specific implementation of this step is to first sort the multiple parameter conflict points recorded in the aforementioned correlation conflict check process according to their corresponding conflict level labels. The conflict level labels are divided according to the level of impact on vehicle driving safety. For example, those that may cause sideslip, loss of control, or tire lift-off are classified as high conflict level, while those that only affect ride comfort or energy efficiency are classified as low conflict level, etc. The system ranks all parameter conflict points from high to low according to this level, forming a conflict priority sequence. For example, when a vehicle makes an emergency lane change at high speed, if there are two conflicting parameters simultaneously: "the drive motor torque increase causes the ESP to exceed the braking torque limit" and "the suspension stiffness increase causes the steering assist to be lower than the minimum set value," the former involves the risk of yaw stability control failure and is marked as a high conflict level, while the latter affects steering feel but does not endanger safety and is marked as a low conflict level. Therefore, the former is ranked first in the conflict priority sequence. Subsequently, the parameter adjustment priority of each target component is derived in reverse from this conflict priority sequence. That is, the target component that causes the high conflict level problem needs to make concessions in its adjustment freedom, and its optimizable parameters... The parameter range should be restricted first to obtain the component adjustment sequence. For example, the drive motor is placed at the front of the adjustment sequence because it causes high conflict. Then, the highest priority target component in the component adjustment sequence is subjected to boundary shrinkage processing. This processing is achieved by reducing the upper or lower limit of its optimizable parameter range. For example, the upper limit of the torque adjustment of the drive motor is shrunk from +18% to +12% to form the shrunk parameter range. Subsequently, the shrunk parameter range is re-matched and verified with the safety parameter range of other target components that are coupled with it to determine whether the parameter conflict caused by the adjustment of the component has been alleviated or eliminated. For example, if the motor torque no longer forces the ESP to exceed its safety limit after shrinkage, the verification result is a successful match.Based on the parameter matching verification results, a new round of conflict elimination checks is performed on the remaining parameter conflict points in the system to confirm whether any unresolved conflicts still exist. If the check results show that parameter conflict points still exist, the same boundary contraction process is performed on the next priority target component in the component adjustment sequence. For example, the steering system is processed because there is still a conflict with the comfort of the suspension, and its power assist gain lower limit is increased from +10% to +15%, further releasing the suspension stiffness adjustment space. This process is continuously iterated, each time contracting the adjustment range of high-priority components to improve the overall system coordination, until the conflict elimination status shows that all parameter conflict points have been resolved. Finally, a set of parameter adjustment ranges that are inconsistent and safe to execute under multi-objective coupling conditions is output for subsequent generation of cooperative control commands.

[0091] In specific scenarios, based on the parameter adjustment range and the real-time operating parameters, adjustment priorities and adjustment step sizes are collaboratively allocated for each target component, generating corresponding parameter adjustment instructions, including:

[0092] The adjustment requirement for each target component is calculated based on the parameter adjustment range and real-time operating parameters, and the adjustment priority is determined based on the adjustment requirement.

[0093] The single adjustment ratio of each target component is calculated based on the adjustment priority and component coupling coefficient to obtain the initial adjustment step size. The initial adjustment step size is then corrected by coupling correlation to obtain the balanced adjustment step size.

[0094] The adjustment priority is associated with the equalization adjustment step size to obtain the timing adjustment scheme for each target component, and a parameter adjustment instruction containing the adjustment sequence identifier and step size value is generated based on the timing adjustment scheme.

[0095] Specifically, based on the parameter adjustment range and the real-time operating parameters, adjustment priority and adjustment step size are collaboratively allocated for each target component to generate corresponding parameter adjustment instructions. This includes calculating the adjustment demand degree of each target component based on the parameter adjustment range and the real-time operating parameters, and determining the adjustment priority based on the adjustment demand degree; calculating the single adjustment ratio of each target component according to the adjustment priority and the component coupling coefficient to obtain the initial adjustment step size, and performing coupling correlation correction on the initial adjustment step size to obtain the balanced adjustment step size; associating and integrating the adjustment priority and the balanced adjustment step size to obtain the timing adjustment scheme for each target component, and generating parameters containing adjustment sequence identifiers and step size values ​​based on the timing adjustment scheme. The adjustment command is implemented by first comparing the parameter adjustment ranges of the previously determined target components with their current real-time operating parameters. The degree to which each target component deviates from its ideal operating state, i.e., the adjustment demand, is calculated using a normalized difference algorithm. For example, for a drive motor, its current output torque is compared with the target torque calculated based on the vehicle dynamics model. The percentage of the difference to the width of the parameter adjustment range is used as its adjustment demand. If the current torque is only 5% away from the upper limit, while the target value needs to be increased by 15%, the demand is high. For an active suspension, if the current stiffness is +20%, the parameter adjustment range is +22% to +35%, and the body roll angle has exceeded the threshold, then an adjustment is needed. The demand is also determined to be high; then, the components are sorted based on their adjustment demand values. The higher the demand, the higher the corresponding adjustment priority. A component coupling coefficient is introduced as a weighting factor. If a component has strong coupling with multiple other target components, its priority is appropriately increased. For example, during an emergency lane change, the ESP system has a high adjustment demand and significant coupling with the drive motor and suspension system, therefore it is assigned the highest adjustment priority. Next, the single-time adjustment ratio of each target component is calculated based on the adjustment priority and component coupling coefficient. This ratio is set according to the response capability within the control cycle, with higher-priority components allocated a larger ratio. This ratio is then scaled based on the component coupling coefficient to form the initial adjustment step size. For example, the initial adjustment step size for the ESP... The initial adjustment step size is set to 60% of the required amount, 40% for the drive motor, and 30% for the suspension. Subsequently, a coupling correlation correction is applied to the initial adjustment step size, considering the mutual influence when multiple target components are adjusted simultaneously. If adjusting a certain step size causes another component to exceed its parameter adjustment range or exacerbates coupled oscillations, a dynamic compensation algorithm is used to reduce its step size and increase the step size of the associated components, thus obtaining a balanced adjustment step size. Finally, the adjustment priority is correlated and integrated with the balanced adjustment step size to construct a timing adjustment scheme for each target component. This scheme clarifies the adjustment start order, time interval, and step size value for each component. For example, when making an emergency lane change at high speed, the system determines that the ESP adjustment has the highest priority and should be activated at 0 milliseconds with a step size of 0.The first step is adjusting the torque by 70% of the maximum braking torque (7 times the maximum torque); the second step is the drive motor, which starts after 50 milliseconds with a step size of +10% torque; the third step is the right front suspension, which starts after 100 milliseconds with a step size of +28% stiffness. The final parameter adjustment command includes the adjustment sequence identifiers for each target component, such as "P1", "P2", "P3", and their corresponding step sizes, and is sent to the corresponding actuators via the communication bus.

[0096] In a specific scenario, the target component actuator includes a power system actuator and a stability control system. Sending the parameter adjustment command to the corresponding target component actuator to synchronously adjust each target component and achieve coordinated action between the vehicle's power system and stability control system includes:

[0097] The parameter adjustment commands are classified according to their system category to obtain power system adjustment commands and stability control system adjustment commands;

[0098] The power system adjustment command is sent to the power system actuator, and the stability control system adjustment command is sent to the stability control system, so as to synchronously adjust each target component and realize the coordinated action of the vehicle power system and the stability control system.

[0099] Specifically, the target component actuators include powertrain actuators and stability control systems. Sending the parameter adjustment commands to the corresponding target component actuators to synchronously adjust each target component and achieve coordinated operation of the vehicle's powertrain and stability control systems includes classifying the parameter adjustment commands according to their system categories to obtain powertrain adjustment commands and stability control system adjustment commands; sending the powertrain adjustment commands to the powertrain actuators and the stability control system adjustment commands to the stability control system to synchronously adjust each target component and achieve coordinated operation of the vehicle's powertrain and stability control systems. The specific implementation of this step is to first receive the aforementioned generated parameter adjustment commands containing adjustment sequence identifiers and step sizes. Each item in this command is associated with the identifier information of the corresponding target component, such as "MCU_FL" representing... The left front drive motor, "ESP_RL" represents the right rear braking unit, and "SUSP_FR" represents the right front suspension controller. Then, all parameter adjustment commands are classified according to the preset system classification rules. The classification rules are defined based on the vehicle functional system to which the target component belongs. For example, all commands related to drive torque output, including adjustment commands to the motor controller or transmission control unit, are classified as powertrain adjustment commands. All commands involving braking intervention, yaw moment control, or vehicle attitude adjustment, such as commands sent to the ESP control unit, electronic steering system, or active stabilizer bar controller, are classified as stability control system adjustment commands. The classification process is completed by parsing the component identification information in the command and matching it with the system mapping table. For example, those with identifiers starting with "MCU" or "TCU" are classified as powertrain commands, and those starting with "ESP" or "VSC" are classified as stability control system commands.After classification, the system initiates the command distribution mechanism, transmitting powertrain adjustment commands via a high-real-time vehicle bus such as CAN. The system sends commands via FD or onboard Ethernet to the powertrain actuators, including drive motor power modules, electronic throttle controllers, or dual-clutch transmission actuators. Simultaneously, it sends stability control system adjustment commands to the stability control system, which includes an Electronic Stability Program (ESP) control unit, Braking By-Wire (BBW) system, or active suspension central controller. All commands are sent with a unified timestamp and synchronization flag to ensure that each actuator initiates adjustment actions according to a preset timing scheme upon receiving the commands. For example, during an emergency lane change at high speed, the system categorizes commands to increase the stiffness of the right front suspension and increase the driving force of the left rear wheel as powertrain adjustment commands and sends them to the corresponding motors and suspension controllers. Simultaneously, it categorizes commands to apply braking to the right front wheel to suppress oversteer as stability control system adjustment commands and sends them to the ESP unit. Both types of commands arrive at their respective actuators synchronously within milliseconds. The powertrain actuators adjust torque distribution to assist steering, while the stability control system applies selective braking to stabilize the vehicle body. These two systems work together to achieve coordinated action between the vehicle's powertrain and stability control systems, effectively suppressing roll and yaw, and improving driving safety and handling response consistency.

[0100] The above describes the cooperative optimization control method for vehicle components in the embodiments of the present invention. The following describes the cooperative optimization control system for vehicle components in the embodiments of the present invention. Please refer to [link / reference]. Figure 2 One embodiment of the collaborative optimization control system for vehicle components in this invention includes:

[0101] The acquisition module 21 is used to acquire real-time operating parameters of multiple target components of the vehicle through sensors;

[0102] Analysis module 22 is used to perform quantitative analysis on the coupling relationship between each target component based on the real-time operating parameters, obtain the component coupling coefficient, and determine whether a preset coupling threshold is triggered based on the component coupling coefficient;

[0103] The defining module 23 is used to define the optimizable parameter range of each target component based on the coupling threshold and the component coupling coefficient if triggered, so as to obtain the parameter adjustment range of each target component.

[0104] The allocation module 24 is used to coordinate the allocation of adjustment priority and adjustment step size for each target component based on the parameter adjustment range and the real-time operating parameters, and generate corresponding parameter adjustment instructions.

[0105] The adjustment module 25 is used to send the parameter adjustment command to the corresponding target component actuator to synchronously adjust each target component and realize the coordinated action of the vehicle power system and stability control system.

[0106] In this embodiment, the specific implementation of each unit in the above system embodiment is described in the above method embodiment, and will not be repeated here.

[0107] Reference Figure 3 This invention also provides a computer device whose internal structure can be as follows: Figure 3 As shown, the computer device includes a processor, memory, display screen, input device, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores the data corresponding to this embodiment. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements the above-described method.

[0108] Those skilled in the art will understand that Figure 3 The structures shown are merely block diagrams of some structures related to the present invention and do not constitute a limitation on the computer devices on which the present invention is applied.

[0109] An embodiment of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method. It is understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0110] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the present invention and embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual-rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM, etc.

[0111] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0112] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A collaborative optimization control method for vehicle components, characterized in that, Includes the following steps: Real-time operating parameters of multiple target components of the vehicle are collected through sensors; Based on the real-time operating parameters, the coupling relationship between each target component is quantitatively analyzed to obtain the component coupling coefficient, and based on the component coupling coefficient, it is determined whether a preset coupling threshold is triggered. If triggered, the optimizable parameter range of each target component is defined based on the coupling threshold and the component coupling coefficient, and the parameter adjustment range of each target component is obtained. Based on the parameter adjustment range and the real-time operating parameters, the adjustment priority and adjustment step size of each target component are coordinated and allocated to generate corresponding parameter adjustment instructions. The parameter adjustment command is sent to the corresponding target component actuator to synchronously adjust each target component, thereby achieving coordinated operation of the vehicle power system and stability control system. The step of defining the optimizable parameter range for each target component based on the coupling threshold and the component coupling coefficient to obtain the parameter adjustment range for each target component includes: Based on the coupling threshold and component coupling coefficient, the optimizable parameter range of each target component is determined, and the intersection of the optimizable parameter range and the safe operation threshold of the corresponding target component is calculated to obtain the safe parameter interval. For target components with coupling relationships, a correlation conflict check is performed on the safety parameter range to obtain parameter conflict points, and the conflict points are classified into conflict levels to obtain conflict level identifiers. Based on the conflict level identifier, adjust the optimizable parameter range of each target component until there are no more parameter conflict points, and obtain the parameter adjustment range of each target component; The step of performing an intersection operation between the optimizable parameter range and the safe operating threshold of the corresponding target component to obtain the safe parameter range includes: Boundary extraction is performed on the range of optimizable parameters to obtain the upper and lower optimization limits, and interval analysis is performed on the safe operation threshold of the target component to obtain the upper and lower safety limits. The optimization upper limit value is compared with the safety upper limit value, and the smaller value is taken as the intersection upper limit. The optimization lower limit value is compared with the safety lower limit value, and the larger value is taken as the intersection lower limit. The safety parameter range is determined based on the intersection upper limit and the intersection lower limit. The process of adjusting the optimizable parameter range of each target component based on the conflict level identifier until there are no more parameter conflict points, to obtain the parameter adjustment range of each target component, includes: Based on the conflict level identifier, the conflict points of the parameters are sorted by conflict severity to obtain a conflict priority sequence. Then, the parameter adjustment priority of each target component is determined according to the conflict priority sequence to obtain a component adjustment sequence. The optimizable parameter range of high-priority target components in the component adjustment sequence is subjected to boundary shrinkage processing to obtain the shrunken parameter range. The shrunken parameter range is then re-matched and verified with the safety parameter range of other target components that have coupling relationships to obtain the parameter matching verification result. Based on the parameter matching verification results, the remaining parameter conflict points are checked for conflict elimination to obtain the conflict elimination status. When the conflict elimination status shows that parameter conflict points still exist, the boundary shrinkage process is repeated for the next priority target component until the conflict elimination status shows that there are no parameter conflict points, thus obtaining the parameter adjustment range of each target component.

2. The collaborative optimization control method for vehicle components according to claim 1, characterized in that, The method of collecting real-time operating parameters of multiple target components of the vehicle through sensors includes: By collecting parameters from multiple target components using sensors that correspond one-to-one with each target component, raw operating data is obtained. The original running data is timestamped to obtain running data with timestamps; Outliers in the time-stamped running data are removed, and the removed time-stamped running data is associated with the identification information of the corresponding target component to obtain real-time running parameters.

3. The collaborative optimization control method for vehicle components according to claim 1, characterized in that, The step of quantitatively analyzing the coupling relationship between each target component based on the real-time operating parameters to obtain the component coupling coefficient, and determining whether a preset coupling threshold is triggered based on the component coupling coefficient, includes: The real-time operating parameters are segmented according to a preset time interval to obtain the parameter segment data of each target component, and the average value of the parameter segment data is calculated to obtain the segment mean parameter. The piecewise mean parameters of any two target components are coupled and the calculated coupling changes are normalized to obtain the component coupling coefficient. Subtract the component coupling coefficient of the previous cycle from the component coupling coefficient of the current cycle to obtain the change in coupling coefficient; The change in the coupling coefficient is compared with a set dynamic threshold to obtain a comparison result, and a determination is made based on the comparison result to determine whether the preset coupling threshold is triggered.

4. The collaborative optimization control method for vehicle components according to claim 1, characterized in that, For target components with coupling relationships, a correlation conflict check is performed on the safety parameter ranges to identify parameter conflict points, including: Cross-calculation is performed on the safety parameter ranges of two components in a target component with a coupling relationship to determine whether there are parameter values ​​that would cause the other component to exceed the safety range if the adjustment requirement of one of the two components is met, and the interval conflict determination result is obtained. Record the conflicting parameter values ​​and corresponding component identifiers in the interval conflict determination results to obtain the parameter conflict points.

5. The collaborative optimization control method for vehicle components according to claim 4, characterized in that, Based on the parameter adjustment range and the real-time operating parameters, adjustment priority and adjustment step size are collaboratively allocated for each target component, generating corresponding parameter adjustment instructions, including: The adjustment requirement for each target component is calculated based on the parameter adjustment range and real-time operating parameters, and the adjustment priority is determined based on the adjustment requirement. The single adjustment ratio of each target component is calculated based on the adjustment priority and component coupling coefficient to obtain the initial adjustment step size. The initial adjustment step size is then corrected by coupling correlation to obtain the balanced adjustment step size. The adjustment priority is associated with the equalization adjustment step size to obtain the timing adjustment scheme for each target component, and a parameter adjustment instruction containing the adjustment sequence identifier and step size value is generated based on the timing adjustment scheme.

6. The collaborative optimization control method for vehicle components according to claim 1, characterized in that, The target component actuator includes a power system actuator and a stability control system. Sending the parameter adjustment command to the corresponding target component actuator to synchronously adjust each target component and achieve coordinated operation of the vehicle's power system and stability control system includes: The parameter adjustment commands are classified according to their system category to obtain power system adjustment commands and stability control system adjustment commands; The power system adjustment command is sent to the power system actuator, and the stability control system adjustment command is sent to the stability control system, so as to synchronously adjust each target component and realize the coordinated action of the vehicle power system and the stability control system.

7. A collaborative optimization control system for vehicle components, characterized in that, include: The acquisition module is used to collect real-time operating parameters of multiple target components of the vehicle through sensors; The analysis module is used to perform quantitative analysis on the coupling relationship between each target component based on the real-time operating parameters, obtain the component coupling coefficient, and determine whether a preset coupling threshold is triggered based on the component coupling coefficient. The definition module is used to define the optimizable parameter range of each target component based on the coupling threshold and the component coupling coefficient if triggered, so as to obtain the parameter adjustment range of each target component. The allocation module is used to coordinate the allocation of adjustment priority and adjustment step size for each target component based on the parameter adjustment range and the real-time operating parameters, and generate corresponding parameter adjustment instructions. The adjustment module is used to send the parameter adjustment command to the corresponding target component actuator to synchronously adjust each target component and realize the coordinated action of the vehicle power system and stability control system. The step of defining the optimizable parameter range for each target component based on the coupling threshold and the component coupling coefficient to obtain the parameter adjustment range for each target component includes: Based on the coupling threshold and component coupling coefficient, the optimizable parameter range of each target component is determined, and the intersection of the optimizable parameter range and the safe operation threshold of the corresponding target component is calculated to obtain the safe parameter interval. For target components with coupling relationships, a correlation conflict check is performed on the safety parameter range to obtain parameter conflict points, and the conflict points are classified into conflict levels to obtain conflict level identifiers. Based on the conflict level identifier, adjust the optimizable parameter range of each target component until there are no more parameter conflict points, and obtain the parameter adjustment range of each target component; The step of performing an intersection operation between the optimizable parameter range and the safe operating threshold of the corresponding target component to obtain the safe parameter range includes: Boundary extraction is performed on the range of optimizable parameters to obtain the upper and lower optimization limits, and interval analysis is performed on the safe operation threshold of the target component to obtain the upper and lower safety limits. The optimization upper limit value is compared with the safety upper limit value, and the smaller value is taken as the intersection upper limit. The optimization lower limit value is compared with the safety lower limit value, and the larger value is taken as the intersection lower limit. The safety parameter range is determined based on the intersection upper limit and the intersection lower limit. The process of adjusting the optimizable parameter range of each target component based on the conflict level identifier until there are no more parameter conflict points, to obtain the parameter adjustment range of each target component, includes: Based on the conflict level identifier, the conflict points of the parameters are sorted by conflict severity to obtain a conflict priority sequence. Then, the parameter adjustment priority of each target component is determined according to the conflict priority sequence to obtain a component adjustment sequence. The optimizable parameter range of high-priority target components in the component adjustment sequence is subjected to boundary shrinkage processing to obtain the shrunken parameter range. The shrunken parameter range is then re-matched and verified with the safety parameter range of other target components that have coupling relationships to obtain the parameter matching verification result. Based on the parameter matching verification results, the remaining parameter conflict points are checked for conflict elimination to obtain the conflict elimination status. When the conflict elimination status shows that parameter conflict points still exist, the boundary shrinkage process is repeated for the next priority target component until the conflict elimination status shows that there are no parameter conflict points, thus obtaining the parameter adjustment range of each target component.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

Images