Four-wheel independent braking torque vectoring method and system based on EMB controller

Abstract

This application relates to the field of four-wheel independent braking technology, specifically to a method and system for four-wheel independent braking torque vector coordination based on an EMB controller. The method includes: establishing a baseline prediction model for the response delay of each wheel, the baseline prediction model including a communication delay sub-model, an idle travel delay sub-model, and a torque response delay sub-model; calculating the baseline response delay prediction value for each wheel in the current braking cycle; determining memory adjustment weights to generate a dynamic correction amount for the current braking cycle; correcting the baseline response delay prediction value to obtain the final response delay prediction value for each wheel in the current braking cycle; and sending braking torque commands to each wheel in a staggered manner to compensate for the asynchronous response of each wheel, thereby synchronizing the actual braking torque of all four wheels. This application compensates for the asynchronous response of each wheel by sending braking torque commands to each wheel in a staggered manner, thereby suppressing the transient vector deviation of the four-wheel braking torque.

Description

Technical Field

[0001] This application relates to the field of four-wheel independent braking technology, specifically to a method and system for four-wheel independent braking torque vector coordination based on an EMB controller. Background Technology

[0002] In the field of drive-by-wire chassis for new energy vehicles, the Electro-Mechanical Brake (EMB) system is gradually becoming mainstream. This system eliminates traditional hydraulic lines and equips each of the four wheels with an independent actuator. The EMB controller sends braking commands to each actuator via a bus, and the motor directly drives the caliper to generate braking force.

[0003] However, because the four-wheel brake actuators operate completely independently, the response time of each wheel from receiving the command to actually achieving the target braking torque varies significantly due to the combined effects of factors such as the wear degree of the friction linings of each wheel, mechanical transmission efficiency, motor operating temperature, and bus communication load. This asynchronous response leads to transient vector deviations in the braking torque of the four wheels, which in turn causes unexpected yaw of the vehicle, severely affecting driving stability.

[0004] Most existing synchronization compensation schemes rely on wheel speed feedback or response time comparison for post-event adjustments, such as increasing motor speed to catch up with lagging wheels. These schemes are essentially passive compensation strategies, unable to predict the amount of response delay, and unable to eliminate the initial torque deviation caused by response delay in the initial braking stage, resulting in a persistent lag defect in the coordinated control of four-wheel independent braking. Summary of the Invention

[0005] In view of the above, it is necessary to provide a four-wheel independent braking torque vector coordination method and system based on EMB controller. By sending braking torque commands to each wheel in a staggered manner, the asynchronous response of each wheel is compensated, thereby suppressing the transient vector deviation of the four-wheel braking torque. In a first aspect, embodiments of this application provide a four-wheel independent braking torque vector coordination method based on an EMB controller, the method comprising the following steps: A baseline prediction model for the response delay of each wheel is established. The baseline prediction model includes a communication delay sub-model based on bus load rate, an idle travel delay sub-model based on cumulative braking times and motor temperature, and a torque response delay sub-model based on target torque, motor temperature, and vehicle speed. During the current braking, the current vehicle operating state variables are obtained and input into the baseline prediction model to calculate the baseline response delay prediction value of each wheel during the current braking. The measured response delay and the predicted final response delay of each wheel during the previous braking are obtained and compared to determine the memory adjustment weight, which is used to generate the dynamic correction amount for the current braking. The baseline response delay prediction value is corrected according to the dynamic correction amount to obtain the predicted final response delay value of each wheel during the current braking. Then, braking torque commands are sent to each wheel to compensate for the asynchronous response of each wheel, so that the actual braking torque of the four wheels is established synchronously. The predicted final response delay for the first braking action is equal to the predicted baseline response delay.

[0006] Furthermore, the communication delay characterizes the time difference between the moment when the wheel brake motor current first undergoes a step change and the moment when the braking torque command is issued; the idle travel delay characterizes the time difference between the moment when the friction lining contacts the brake disc and the moment when the wheel brake motor current first undergoes a step change; and the torque response delay characterizes the time difference between the moment when the braking torque reaches the target value preset ratio and the moment when the friction lining contacts the brake disc.

[0007] Furthermore, the idle travel delay sub-model is configured as follows: Based on the initial constant of the idle travel delay, the linear wear delay increment generated by the cumulative braking number is positively superimposed, and the linear expansion delay increment is positively superimposed when the motor temperature is higher than the preset reference temperature; wherein, when the friction lining of the corresponding wheel is replaced, the cumulative braking number is reset to zero.

[0008] Furthermore, the torque response delay sub-model is configured as follows: Based on the fundamental constant of torque response delay, the linear delay increment caused by the proportion of the target torque amplitude, the quadratic delay acceleration deterioration increment caused by the deviation of motor temperature from the preset reference temperature, and the linear delay increment caused by the proportion of vehicle longitudinal travel speed amplitude are positively superimposed.

[0009] Furthermore, the method for determining the memory adjustment weights is as follows: Calculate the standard deviation of the fitting residuals of each sub-model in the baseline prediction model; Obtain the absolute deviation between the predicted final response delay of the previous braking event and the measured response delay; Calculate the ratio of the absolute deviation to the sum of the standard deviations of the fitting residuals of all sub-models in the baseline prediction model; The negative exponent mapping result of the ratio is used as the memory adjustment weight.

[0010] Furthermore, the method for determining the memory adjustment weights also includes: If the time interval between the current braking and the previous braking is greater than a preset time interval threshold, the memory adjustment weight is forcibly set to zero.

[0011] Furthermore, the dynamic correction amount is generated as follows: The difference between the predicted final response delay of the previous braking action and the predicted baseline response delay of the current braking action is calculated, and the product of the difference and the memory adjustment weight is used as the dynamic correction amount.

[0012] Furthermore, the step of sending braking torque commands to each wheel in a misaligned manner includes: Extract the maximum value from the final response delay predictions of the four rounds; Subtract the predicted final response delay of each wheel from the maximum value to obtain the relative delay time difference of each wheel; use the relative delay time difference as the delay value for issuing braking torque command to each wheel.

[0013] Furthermore, the baseline prediction model is obtained by pre-extracting historical braking data and fitting parameters using the least squares method; and during vehicle use, when the number of new braking events reaches a set threshold, the parameters in the baseline prediction model are updated using the new braking data.

[0014] Secondly, embodiments of this application also provide a four-wheel independent braking torque vector coordination system based on an EMB controller, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any of the above-described four-wheel independent braking torque vector coordination methods based on an EMB controller.

[0015] This application has at least the following beneficial effects: By establishing a benchmark prediction model, the main influencing factors of each link of communication transmission, mechanical backlash elimination and torque establishment can be quantified, and the response delay of each wheel can be estimated in advance, overcoming the defect of existing passive compensation strategies that cannot predict the amount of response delay. During the current braking, the current vehicle operating state variables are acquired and input into the baseline prediction model, and the baseline response delay prediction value of each wheel during the current braking is output. The theoretical delay estimate of each wheel can be quickly output according to the real-time operating conditions, providing a quantitative basis for subsequent synchronization compensation. The measured response delay and the predicted final response delay of each wheel during the previous braking are obtained and compared to determine the memory adjustment weight, which is used to generate the dynamic correction amount for the current braking. This can evaluate the prediction deviation of the benchmark prediction model and make dynamic corrections based on the actual situation. The baseline response delay prediction value is corrected based on the dynamic correction amount to obtain the final response delay prediction value of each wheel in the current braking. This can compensate for the prediction lag of the baseline prediction model when the operating parameters change abruptly, and improve the accuracy of response delay prediction. Then, braking torque commands are sent to each wheel in a staggered manner to compensate for the asynchronous response of each wheel, so that the actual braking torque of the four wheels is established synchronously. It can actively compensate for the time difference of each wheel in communication transmission, mechanical action and electromagnetic response at the command sending end, avoid the initial torque deviation caused by the difference in response delay in the early stage of braking, suppress the transient vector deviation of the braking torque of the four wheels, reduce the risk of unexpected yaw of the vehicle, and significantly improve driving stability. Attached Figure Description

[0016] Figure 1 A flowchart illustrating the steps of a four-wheel independent braking torque vector coordination method based on an EMB controller, as provided in one embodiment of this application; Figure 2 A schematic diagram of the process for obtaining weights for memory adjustment. Detailed Implementation

[0017] The following description, in conjunction with the accompanying drawings, details the specific scheme of the four-wheel independent braking torque vector coordination method and system based on the EMB controller provided in this application.

[0018] In this embodiment, the following communication architecture is adopted: it includes an EMB controller and EMB actuators installed on the four wheels respectively. The EMB controller refers to the Brake Control Unit (BCU). The EMB controller is responsible for calculating the response delay of each wheel and issuing braking torque commands in a staggered manner; the four EMB actuators receive the corresponding braking torque commands and drive their internal brake motors to generate braking force.

[0019] Please see Figure 1 It illustrates a flowchart of a four-wheel independent braking torque vector coordination method based on an EMB controller according to an embodiment of this application. The method includes the following steps: Step 1: Obtain braking data for each wheel during each braking action.

[0020] For road test data of new energy vehicles before their market launch, the EMB controller is used to acquire and record key event stamps and state variables of each wheel in real time during each braking operation, collectively referred to as braking data. A data record set for the i-th wheel during the j-th braking operation is then constructed, and the data record set and its parameters are defined as follows: ; in, This represents the set of data records for the j-th braking action of the i-th wheel; The wheel number i can be FL, FR, RL, or RR, corresponding to the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively. This indicates the moment when the braking torque command for the i-th wheel is issued during the j-th braking action. It is recorded by the internal timer of the EMB controller with an accuracy of 1ms. The time when the current of the brake motor of the i-th wheel first shows a step change during the j-th braking is marked by the start of the motor and the beginning of eliminating the braking gap. It is achieved by the current sensor located in the EMB actuator of the i-th wheel collecting the operating current of the brake motor in real time at a preset sampling period and recording the timestamp when a step change in the operating current is detected. Usually with The difference is 3ms to 30ms; in this embodiment, the preset sampling period is 2ms. The moment when the friction pad of the i-th wheel contacts the brake disc during the j-th braking action marks the completion of free travel elimination, determined by the first non-zero braking torque detected by the torque sensor located at the i-th wheel. To avoid failure in determination under slight braking conditions, a preset contact torque threshold is used for determining the non-zero braking torque. Usually with The time difference is 2ms to 50ms; in this embodiment, the contact torque threshold is 5Nm. This indicates the moment when the braking torque of the i-th wheel reaches the preset proportion of the target value during the j-th braking action, which is continuously monitored and determined by the torque sensor. Usually with The time difference is 5ms to 120ms; in this embodiment, the preset ratio is 95%. This represents the magnitude of the target braking torque command issued by the EMB controller to the i-th wheel during the j-th braking action, typically ranging from 0 Nm to 15000 Nm. This indicates the operating temperature of the brake motor of the i-th wheel at the initial stage of the j-th braking event. It is measured in real time by the temperature sensor built into the motor, and the value range is usually -40°C to 150°C. This indicates the load rate of the CAN-FD (Controller Area Network with Flexible Data-Rate) bus during the j-th braking event. This load rate is obtained in real time by the communication module of the EMB controller and typically ranges from 10% to 80%. This represents the cumulative number of braking operations of the i-th wheel before the j-th braking operation. It is used to characterize the wear of the friction lining and is recorded cumulatively by the EMB controller. The value range is usually 0 to 500,000. This represents the initial longitudinal speed of the vehicle during the j-th braking event, typically ranging from 0 km / h to 200 km / h.

[0021] This application focuses on quantifying communication delay, idle travel delay, and torque response delay. Based on the recorded data, the corresponding delays are extracted as follows: In the formula, This represents the communication delay of the i-th wheel during the j-th braking event, and its value typically ranges from 3ms to 30ms. This indicates the moment when the current of the brake motor of the i-th wheel first undergoes a step change during the j-th braking action; This indicates the moment when the braking torque command for the i-th wheel is issued during the j-th braking action; In the formula, This represents the time delay of the idle travel of the i-th wheel during the j-th braking action, and its value range is typically 2ms to 50ms. This indicates the moment when the friction pad of the i-th wheel contacts the brake disc during the j-th braking action; In the formula, This represents the torque response delay of the i-th wheel during the j-th braking event, and its value typically ranges from 5ms to 120ms. This indicates the moment when the braking torque of the i-th wheel reaches the preset proportion of the target value during the j-th braking action.

[0022] Based on the above analysis, the total braking time delay can be obtained, as shown in the following formula: In the formula, This represents the total braking delay of the i-th wheel during the j-th braking action.

[0023] This allows us to obtain the communication delay, idle travel delay, and torque response delay of a single wheel during a single braking operation, providing a data foundation for the quantitative fitting of subsequent benchmark prediction models.

[0024] Step 2: Establish a baseline prediction model for the response delay of each wheel. The baseline prediction model includes a communication delay sub-model based on bus load rate, an idle travel delay sub-model based on cumulative braking times and motor temperature, and a torque response delay sub-model based on target torque, motor temperature, and vehicle speed.

[0025] In step 1, based on the braking data of each wheel during a single braking operation, the communication delay, idle travel delay, and torque response delay of each wheel were extracted. Due to the adoption of a four-wheel independent braking architecture, the mechanical state, operating conditions, and wear degree of each wheel are not entirely the same, resulting in independent and dynamically changing delays for the four wheels. To accurately quantify the dynamic changes of various delays, the causes of these delays were further analyzed, and a baseline prediction model was constructed accordingly, including: a communication delay sub-model, an idle travel delay sub-model, and a torque response delay sub-model.

[0026] Step 201: Construct a communication delay sub-model.

[0027] During vehicle braking, the EMB controller typically sends braking torque commands to each wheel by analyzing the pressure applied to the brake pedal or the output of the autonomous driving control algorithm. There are inherent and dynamic delays in the transmission process from the issuance of the braking torque command to its receipt by the corresponding wheel's EMB actuator. The inherent delay characterizes the basic physical transmission delay under ideal conditions; the dynamic delay is mainly affected by the CAN-FD bus load rate. A higher bus load rate results in a longer message queuing time, thus increasing the transmission delay.

[0028] The communication delay sub-model is as follows: In the formula, This represents the baseline estimate of the communication delay for the i-th wheel; The inherent transmission delay, representing the communication delay of the i-th wheel, is used to characterize the minimum basic transmission delay when the bus is under zero load. It is determined by the CAN-FD frame structure and baud rate. The parameters to be fitted are obtained offline using historical data, and their values ​​typically range from 2ms to 8ms. This represents the linear sensitivity coefficient of the communication delay of the i-th wheel to the bus load rate, reflecting the additional transmission delay increment caused by each 1% increase in the bus load rate. The parameters to be fitted are obtained offline using historical data, and their values ​​typically range from 0.05ms / % to 0.30ms / %. This indicates the load rate of the CAN-FD bus, typically ranging from 10% to 80%. The random fluctuation term representing the communication delay of the i-th wheel approximately follows a mean of 0 and a variance of . follows a normal distribution, where This represents the corresponding standard deviation, typically ranging from 1ms to 5ms.

[0029] Step 202: Construct the empty journey delay sub-model.

[0030] During the operation of the EMB actuator, the brake motor corresponding to the wheel, such as the permanent magnet synchronous motor (PMSM), receives the braking torque command and outputs a rotational torque. After the rotational torque is amplified by the planetary gear reduction and torque amplification mechanism, it drives the roller screw structure to convert the rotational motion into linear motion, which in turn pushes the brake piston, causing the friction lining to press against the brake disc, thereby establishing a braking clamping force.

[0031] In the initial unbraked state, a small gap, typically 1mm to 3mm, exists between the friction pads and the brake disc. Since effective braking force can only be established when the friction pads are in full contact with the brake disc, the process of eliminating this gap naturally causes a travel delay. However, in actual operation, the different loads on each wheel lead to varying wear on the friction pads, resulting in different travel delays for each wheel. Furthermore, the operating temperature of the brake motor significantly affects the thermal expansion and electromagnetic response speed of the mechanical components. All these factors combined contribute to the dynamic differences in travel delays among the wheels.

[0032] The idle travel delay sub-model is as follows: In the formula, This represents the baseline estimate of the idle travel delay of the i-th wheel; The initial constant representing the idle travel delay of the i-th wheel is used to characterize the basic idle travel time under the condition of brand-new friction linings and brake motor in normal temperature reference state. These are the parameters to be fitted, and their values ​​typically range from 5ms to 15ms. This represents the linear wear coefficient of the idle travel delay with respect to the cumulative number of braking cycles, reflecting the contribution of the increase in friction lining wear caused by each braking cycle to the idle travel delay. These are the parameters to be fitted, and their values ​​typically range from 0.00005 ms / time to 0.0005 ms / time. This represents the cumulative number of braking operations for the i-th wheel. To ensure the accuracy of wear calculation, the cumulative number of braking operations will be reset to zero when the friction lining of the corresponding wheel is replaced. This represents the linear expansion delay coefficient of the i-th wheel's idle travel delay with respect to the brake motor's temperature deviation. These are the parameters to be fitted, and their values ​​typically range from -0.1 ms / °C to 0.3 ms / °C. and These represent the operating temperature and preset reference temperature of the i-th wheel brake motor, respectively, where the preset reference temperature is room temperature 25°C. The random fluctuation term representing the idle travel delay approximately follows a mean of 0 and a variance of . follows a normal distribution, where This represents the corresponding standard deviation, typically ranging from 1ms to 3ms.

[0033] Specifically, if When the calculated result is less than 0, it is truncated to 0.

[0034] In the idle travel delay sub-model, the physical basis for each item is as follows: For the first item This reflects the time required for the brake motor to start from a standstill, drive the ball screw to push the piston forward, and until the friction lining first contacts the brake disc. It includes the fundamental delay determined by the initial braking clearance and the motor's no-load response speed.

[0035] For the second item This is used to evaluate the additional clearance compensation time caused by friction lining wear. Under standardized braking conditions, the wear caused by a single braking action is approximately constant, therefore the cumulative wear is positively correlated with the number of braking actions. As the number of braking actions accumulates, the friction lining wears and thins, leading to an increase in the actual braking clearance. Consequently, with the brake motor speed remaining constant, the idle travel elimination time increases approximately linearly.

[0036] Regarding the third item This reflects the aggravating effect of high temperature on the idle travel delay. This is mainly manifested in two aspects: Firstly, due to the high-temperature environment, the metal lead screw elongates due to heat while the piston seat position remains relatively fixed, and the thermal expansion effect leads to a further increase in the actual physical clearance; secondly, the copper wire resistance of the brake motor winding increases approximately linearly with temperature, resulting in a smaller starting current and a reduced motor starting acceleration under the same driving voltage, thus increasing the idle travel delay. When the calculated result is less than 0, the aforementioned significant problems of increased thermal expansion gap and deteriorated line resistance do not exist; therefore, the third term is set to zero. When the operating temperature of the brake motor is lower than the preset reference temperature, the minimal delay error caused by small temperature fluctuations is directly accommodated by the random fluctuation term and does not affect the overall accuracy of the estimation.

[0037] Step 203: Construct the torque response delay sub-model.

[0038] When the friction pads contact the brake disc, a contact torque is generated, thus producing braking force. There is a torque response delay from the initial contact of the friction pads until the braking force reaches the target braking torque command amplitude. This torque response delay is influenced by various factors, including the target torque, motor temperature, and vehicle speed.

[0039] The torque response delay sub-model is as follows: In the formula, This represents the baseline estimate of the torque response delay of the i-th wheel; The fundamental constant representing the torque response delay of the i-th wheel. These are the parameters to be fitted, and their values ​​typically range from 8ms to 25ms. The linear delay coefficient represents the proportion of the torque response delay to the magnitude of the target braking torque command. These are the parameters to be fitted, and their values ​​typically range from 10ms to 60ms. This represents the target braking torque command amplitude for the i-th wheel; This represents the maximum braking torque capacity of the EMB actuator of the i-th wheel, and its value range is usually 8000~15000 Nm; This represents the deterioration factor of the torque response delay on the quadratic term of the motor temperature deviation. These are the parameters to be fitted, and their values ​​typically range from 5ms to 25ms. and These represent the operating temperature and preset reference temperature of the i-th wheel brake motor, respectively; This represents the maximum operating temperature limit of the i-th wheel brake motor, typically ranging from 120°C to 150°C. The linear delay coefficient represents the proportion of torque response delay to the amplitude of the vehicle's longitudinal speed. These are the parameters to be fitted, and their values ​​typically range from 3ms to 15ms. This indicates the initial longitudinal speed of the vehicle during braking. This indicates the preset vehicle reference speed, such as the statistical average speed of 100 km / h under typical urban and highway mixed driving conditions; The random fluctuation term representing the torque response delay approximately follows a normal distribution with a mean of 0.

[0040] In the torque response delay sub-model, the physical basis for each term is as follows: For the first item This reflects the basic physical time required to establish effective braking force under minimum torque command and standard motor operating conditions. When the friction lining contacts the brake disc, the rate of increase in clamping force is proportional to the rotational speed of the brake motor, and the rate of establishment of braking force depends on the rate of increase in clamping force. As long as braking force is required, this inherent delay will always exist.

[0041] For the second item This reflects the principle that the larger the target braking torque, the longer the torque response delay. When the target braking torque increases, the required target clamping force increases, and the required target motor current increases. During the transition process of the braking motor current rising from zero to the target value, the rate of current increase is limited by the inductance of the motor stator windings. According to the electrical equations... It can be seen that in the initial stage when the current starts from zero, the actual current I is extremely small, making the voltage drop across the resistor negligible, and the rate of current rise... Therefore, it is approximately a constant due to the limitation of inductance. Since the current rises at a constant rate, the rise time required to reach the target motor current is approximately proportional to the magnitude of the target motor current. By introducing the maximum braking torque capacity for normalization, the difference in absolute capacity between different actuator models is eliminated. Wherein, The value represents the DC voltage of the brake motor, and L and R represent the winding inductance and winding resistance of the brake motor, respectively.

[0042] Regarding the third item This reflects the nonlinear accelerated deterioration effect caused by the motor temperature deviating from the preset reference temperature, leading to a delay in torque response. This is mainly manifested in two aspects: Firstly, the motor copper loss increases with increasing temperature. According to the law of conservation of energy, the usable electromagnetic power of the brake motor equals the total input power minus the motor copper loss. From the motor copper loss formula... It can be seen that the increase in motor copper losses contains a significant quadratic term component. This leads to an accelerated decay of the available electromagnetic power, exhibiting a quadratic characteristic, which in turn causes the rate of torque increase to decrease at an accelerated rate. This indicates the DC voltage of the brake motor. Indicates the temperature coefficient of copper conductors. Indicates the temperature deviation; On the other hand, the remanent magnetic flux density of a permanent magnet decreases approximately linearly with increasing temperature, and its expression can be given as follows: ;in, The remanent magnetic flux density is The initial magnetic flux density, This is the magnetic flux temperature coefficient; since the torque constant of a brake motor is proportional to the remanent magnetic flux density, the torque constant also decreases linearly with increasing temperature; consequently, the torque rise time... It is inversely proportional to the torque constant, that is A mathematical expansion of the inverse proportional relationship reveals that the result is approximately equal to This indicates that the increase in torque response delay caused by temperature rise also contains a significant quadratic term component. Especially under high-temperature conditions, the contribution of this secondary term to the accelerated deterioration of torque response delay is not negligible.

[0043] For the fourth item This reflects the impact of vehicle longitudinal speed on torque response delay. Specifically, the higher the vehicle's longitudinal speed, the faster the corresponding wheel and brake disc rotation speed. This results in greater frictional heat generation per unit time after the friction lining contacts the brake disc, causing a rapid rise in localized temperature on the brake disc surface. The high surface temperature leads to a dynamic decay of the local friction coefficient, resulting in a "fast at first, slow later" deceleration characteristic in the torque rise curve. Ultimately, this significantly prolongs the time it takes for the braking torque to reach the target value. Within the normal driving speed range below 120 km / h, the increase in torque response delay caused by frictional heat generation is approximately linearly correlated with the vehicle's longitudinal speed.

[0044] Step 204: Solve for the parameters to be fitted in the baseline prediction model; during the current braking, obtain the current vehicle operating state variables and input them into the baseline prediction model to calculate the baseline response delay prediction value of each wheel during the current braking.

[0045] For the i-th wheel, the collected historical braking data set is used. ,in, This represents the set of data records for the j-th braking action of the i-th wheel; This represents the total number of historical braking events extracted. The least squares method is used to solve the parameters to be fitted in the benchmark prediction model offline, with the goal of minimizing the sum of squares of the historical prediction residuals.

[0046] (1) Solving for the parameters to be fitted in the communication delay sub-model In the formula, The fitted value represents the inherent transmission delay of the communication delay of the i-th wheel; The fitted value of the linear sensitivity coefficient of the communication delay of the i-th wheel to the bus load rate is represented; argmin() represents the argmin function, which is a well-known technique and will not be described in detail in this application. This indicates the total number of historical brakes extracted; This represents the communication delay of the i-th wheel during the j-th braking event; The inherent transmission delay represents the communication delay of the i-th wheel; This represents the linear sensitivity coefficient of the communication delay of the i-th wheel to the bus load rate; This indicates the load rate of the CAN-FD (Controller Area Network with Flexible Data-Rate) bus during the j-th braking event; Simultaneously, the standard deviation of the fitting residuals of the communication delay sub-model is calculated. The formula is as follows: (2) Solving for the fitting parameters of the idle travel delay sub-model In the formula, The fitted value of the initial constant representing the idle travel delay of the i-th wheel; This represents the fitted value of the linear wear coefficient for the idle travel delay on the basis of the cumulative number of braking cycles; This represents the fitted value of the linear expansion delay coefficient of the i-th wheel's idle travel delay to the brake motor's temperature deviation; This indicates the delay in the idle travel of the i-th wheel during the j-th braking action; The initial constant represents the delay of the idle travel of the i-th wheel; This represents the linear wear coefficient of the idle travel delay with respect to the cumulative number of braking cycles; This represents the cumulative number of braking actions taken by the i-th wheel before the j-th braking action. The linear expansion delay coefficient represents the temperature deviation of the brake motor due to the idle travel delay of the i-th wheel. This represents the operating temperature of the brake motor of the i-th wheel at the initial stage of the j-th braking event. This indicates the preset reference temperature of the i-th wheel brake motor; The standard deviation of the fitting residual of the idle travel delay sub-model is calculated according to the method for calculating the standard deviation of the fitting residual of the communication delay sub-model.

[0047] (3) Solving for the fitting parameters of the torque response delay sub-model In the formula, The fitted value of the fundamental constant representing the torque response delay of the i-th wheel; The fitted value of the linear delay coefficient representing the proportion of the torque response delay to the magnitude of the target braking torque command; This represents the fitted value of the deterioration delay coefficient of the quadratic term of the motor temperature deviation, indicating the torque response delay. The fitted value of the linear delay coefficient representing the proportion of the torque response delay to the amplitude of the vehicle's longitudinal travel speed; This represents the torque response delay of the i-th wheel during the j-th braking event; The fundamental constant representing the torque response delay of the i-th wheel; The linear delay coefficient represents the proportion of the torque response delay to the magnitude of the target braking torque command; This represents the magnitude of the target braking torque command issued by the EMB controller to the i-th wheel during the j-th braking action. This represents the deterioration delay coefficient of the quadratic term of the motor temperature deviation due to the torque response delay; This represents the operating temperature of the brake motor of the i-th wheel at the initial stage of the j-th braking event. This indicates the preset reference temperature of the i-th wheel brake motor; This represents the maximum operating temperature limit of the i-th wheel brake motor; The linear delay coefficient represents the proportion of torque response delay to the amplitude of the vehicle's longitudinal speed. This represents the initial longitudinal speed of the vehicle during the j-th braking event; Indicates the preset vehicle reference speed; The standard deviation of the fitting residuals of the torque response delay sub-model is calculated using the method for calculating the standard deviation of the fitting residuals of the communication delay sub-model. .

[0048] The parameters to be fitted from the baseline prediction model of the i-th wheel and the standard deviation of the fitted residuals are summarized into a comprehensive parameter vector, as follows: ;in, The comprehensive parameter vector is a 12-dimensional vector. During actual vehicle use, the EMB controller continuously loads the comprehensive parameter vector when the vehicle starts. At the same time, when the cumulative number of new braking events reaches a set threshold, the above least squares solution process is re-executed based on the new braking data to update the comprehensive parameter vector.

[0049] In summary, after obtaining the parameters to be fitted in the benchmark prediction model using historical braking data, the EMB controller only needs to collect data in real time during the current braking event. Substitute this value into the baseline prediction model and sum it to obtain the baseline response delay prediction value of the i-th wheel in the current braking, which corresponds to the total braking delay in step 1.

[0050] Step 3: Obtain and compare the measured response delay and the predicted final response delay of each wheel during the previous braking to determine the memory adjustment weight, which is used to generate the dynamic correction amount for the current braking; correct the baseline response delay prediction value according to the dynamic correction amount to obtain the predicted final response delay value of each wheel during the current braking.

[0051] The baseline response delay prediction reflects the theoretical delay when the current braking event reaches steady state. However, when operating parameters such as bus load rate, motor temperature, torque command, and vehicle speed change rapidly between two adjacent braking events, the actual physical response delay of the EMB system does not instantly jump to the new theoretical steady-state value during actual vehicle operation. Instead, it undergoes a gradual physical adaptation process. Therefore, a dynamic correction amount needs to be calculated to provide real-time dynamic compensation and correction.

[0052] The formula for calculating the dynamic correction amount is as follows: In the formula, This represents the dynamic correction amount for the i-th wheel during the k-th braking action; This represents the predicted final response delay of the i-th wheel during the (k-1)-th braking event; This represents the baseline response delay prediction value of the i-th wheel during the k-th braking event, obtained from the baseline prediction model. in, The memory adjustment weight for the i-th wheel during the k-th braking event is calculated using the following formula: In the formula, exp() represents an exponential function with the natural constant as the base; This represents the measured response delay of the i-th wheel during the (k-1)-th braking event; This indicates the absolute value operation; The standard deviation of the fitting residuals of the communication delay sub-model is represented. The standard deviation of the fitting residuals of the idle travel delay sub-model is represented. The standard deviation of the fitting residuals of the torque response delay sub-model is represented. Figure 2 A schematic diagram illustrating the process of obtaining weights for memory adjustment; Specifically, in the formula for calculating the memory adjustment weight, if there is a case where the denominator is 0, the sum of the denominator and the preset value greater than 0 is calculated first, and then subsequent calculations are performed. In this embodiment, the preset value greater than 0 is 0.01. The implementer can flexibly set it according to the actual situation, and this application does not impose any special restrictions on it.

[0053] Predicted final response delay of the i-th wheel during the k-th braking event. The calculation formula is as follows: .

[0054] What needs to be understood is: when When this occurs, it indicates a deterioration in operating conditions, and the baseline prediction yields a higher delay, because the actual physical delay has not yet fully deteriorated to its full potential. Automatically negate the value to subtract a portion from the baseline response delay prediction to prevent overcompensation; when This indicates improved operating conditions, with baseline predictions showing lower latency, since actual physical latency has not yet fully recovered. Automatically add a positive value to the baseline response delay prediction; when At that time, the baseline response delay prediction value is already accurate enough. Automatically set to 0.

[0055] In particular, to avoid the loss of reference value of historical states due to long-term vehicle parking, when the time interval between the k-th braking and the (k-1)-th braking exceeds the preset time interval threshold, the memory adjustment weight is forcibly reset to 0, the dynamic correction amount is 0, and the baseline response delay prediction value is used as the final response delay prediction value.

[0056] Specifically, the predicted final response delay for the first braking action is equal to the predicted baseline response delay.

[0057] In this embodiment, the preset time interval threshold is set to 20 minutes. The value of the preset time interval threshold can be flexibly set by the implementer according to the actual situation, and this application does not impose any special restrictions on it.

[0058] Step 4: Send braking torque commands to each wheel in a staggered manner to compensate for the asynchronous response of each wheel and to establish the actual braking torque of the four wheels synchronously.

[0059] To address the asynchronous response issue across the four wheels, the EMB controller sends braking torque commands to each wheel in a staggered manner, as follows: First, the maximum value among the predicted final response delays of the four wheels is extracted. Second, the maximum value is subtracted from the calculated result of the predicted final response delay of each wheel to obtain the relative delay time difference of each wheel. For the wheel with the slowest response, the relative delay time difference is 0, and the EMB controller issues the braking torque command to it first. For other wheels, the EMB controller waits until the corresponding relative delay time difference is reached before issuing the braking torque command.

[0060] By sending braking torque commands at staggered intervals, the EMB controller actively compensates for the time differences in communication transmission, mechanical action, and electromagnetic response among the wheels at the command sending end. This ensures that the actual braking torque of all four wheels reaches the target value synchronously at the same physical level. Based on this, the torque distribution ratio of each wheel is adjusted using conventional braking force distribution algorithms in this field, ensuring that the combined braking force vector of the four wheels always meets the vehicle's yaw stability requirements.

[0061] Based on the same inventive concept as the above methods, this application also provides a four-wheel independent braking torque vector coordination system based on an EMB controller, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described four-wheel independent braking torque vector coordination methods based on an EMB controller.

[0062] In summary, this application, by establishing a benchmark prediction model, can quantify the main influencing factors of each stage of communication transmission, mechanical backlash elimination, and torque establishment, and achieve advance estimation of the response delay of each wheel, overcoming the defect of existing passive compensation strategies that cannot predict the amount of response delay. During the current braking, the current vehicle operating state variables are acquired and input into the baseline prediction model, and the baseline response delay prediction value of each wheel during the current braking is output. The theoretical delay estimate of each wheel can be quickly output according to the real-time operating conditions, providing a quantitative basis for subsequent synchronization compensation. The measured response delay and the predicted final response delay of each wheel during the previous braking are obtained and compared to determine the memory adjustment weight, which is used to generate the dynamic correction amount for the current braking. This can evaluate the prediction deviation of the benchmark prediction model and make dynamic corrections based on the actual situation. The baseline response delay prediction value is corrected based on the dynamic correction amount to obtain the final response delay prediction value of each wheel in the current braking. This can compensate for the prediction lag of the baseline prediction model when the operating parameters change abruptly, and improve the accuracy of response delay prediction. Then, braking torque commands are sent to each wheel in a staggered manner to compensate for the asynchronous response of each wheel, so that the actual braking torque of the four wheels is established synchronously. It can actively compensate for the time difference of each wheel in communication transmission, mechanical action and electromagnetic response at the command sending end, avoid the initial torque deviation caused by the difference in response delay in the early stage of braking, suppress the transient vector deviation of the braking torque of the four wheels, reduce the risk of unexpected yaw of the vehicle, and significantly improve driving stability.

Claims

1. A four-wheel independent braking torque vector coordination method based on an EMB controller, characterized in that, The method includes the following steps: A baseline prediction model for the response delay of each wheel is established. The baseline prediction model includes a communication delay sub-model based on bus load rate, an idle travel delay sub-model based on cumulative braking times and motor temperature, and a torque response delay sub-model based on target torque, motor temperature, and vehicle speed. During the current braking, the current vehicle operating state variables are obtained and input into the baseline prediction model to calculate the baseline response delay prediction value of each wheel during the current braking. The measured response delay and the predicted final response delay of each wheel during the previous braking are obtained and compared to determine the memory adjustment weight, which is used to generate the dynamic correction amount for the current braking. The baseline response delay prediction value is corrected according to the dynamic correction amount to obtain the predicted final response delay value of each wheel during the current braking. Then, braking torque commands are sent to each wheel to compensate for the asynchronous response of each wheel, so that the actual braking torque of the four wheels is established synchronously. The predicted final response delay for the first braking action is equal to the predicted baseline response delay.

2. The four-wheel independent braking torque vector coordination method based on an EMB controller as described in claim 1, characterized in that, The communication delay characterizes the time difference between the moment when the wheel brake motor current first jumps and the moment when the braking torque command is issued; the idle travel delay characterizes the time difference between the moment when the friction lining contacts the brake disc and the moment when the wheel brake motor current first jumps; the torque response delay characterizes the time difference between the moment when the braking torque reaches the target value preset ratio and the moment when the friction lining contacts the brake disc.

3. The four-wheel independent braking torque vector coordination method based on an EMB controller as described in claim 1, characterized in that, The idle travel delay sub-model is configured as follows: Based on the initial constant of the idle travel delay, the linear wear delay increment generated by the cumulative braking number is positively superimposed, and the linear expansion delay increment is positively superimposed when the motor temperature is higher than the preset reference temperature; wherein, when the friction lining of the corresponding wheel is replaced, the cumulative braking number is reset to zero.

4. The four-wheel independent braking torque vector coordination method based on an EMB controller as described in claim 1, characterized in that, The torque response delay sub-model is configured as follows: Based on the fundamental constant of torque response delay, the linear delay increment caused by the proportion of the target torque amplitude, the quadratic delay acceleration deterioration increment caused by the deviation of motor temperature from the preset reference temperature, and the linear delay increment caused by the proportion of vehicle longitudinal travel speed amplitude are positively superimposed.

5. The four-wheel independent braking torque vector coordination method based on an EMB controller as described in claim 1, characterized in that, The memory adjustment weights are determined as follows: Calculate the standard deviation of the fitting residuals of each sub-model in the baseline prediction model; Obtain the absolute deviation between the predicted final response delay of the previous braking event and the measured response delay; Calculate the ratio of the absolute deviation to the sum of the standard deviations of the fitting residuals of all sub-models in the baseline prediction model; The negative exponent mapping result of the ratio is used as the memory adjustment weight.

6. The four-wheel independent braking torque vector coordination method based on an EMB controller as described in claim 5, characterized in that, The method for determining the memory adjustment weights also includes: If the time interval between the current braking and the previous braking is greater than a preset time interval threshold, the memory adjustment weight is forcibly set to zero.

7. The four-wheel independent braking torque vector coordination method based on an EMB controller as described in claim 1, characterized in that, The dynamic correction amount is generated in the following way: The difference between the predicted final response delay of the previous braking action and the predicted baseline response delay of the current braking action is calculated, and the product of the difference and the memory adjustment weight is used as the dynamic correction amount.

8. The four-wheel independent braking torque vector coordination method based on an EMB controller as described in claim 1, characterized in that, The step of sending braking torque commands to misaligned wheels includes: Extract the maximum value from the final response delay predictions of the four rounds; Subtract the predicted final response delay of each wheel from the maximum value to obtain the relative delay time difference of each wheel; use the relative delay time difference as the delay value for issuing braking torque command to each wheel.

9. The four-wheel independent braking torque vector coordination method based on an EMB controller as described in claim 1, characterized in that, The baseline prediction model is obtained by pre-extracting historical braking data and fitting parameters using the least squares method; and during vehicle use, when the number of new braking events reaches a set threshold, the parameters in the baseline prediction model are updated using the new braking data.

10. A four-wheel independent braking torque vector coordination system based on an EMB controller, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the four-wheel independent braking torque vector coordination method based on any one of claims 1-9.

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