Hybrid brake control device, method and storage medium for integrating in-wheel motor with EMB

Abstract

The present application relates to the technical field of vehicle control, and particularly relates to a kind of wheel hub motor and EMB integrated composite brake control device, method and storage medium, including input interface module receives target braking torque and current wheel end state parameter;Capability boundary calculation module determines available braking torque upper limit;Heat loss and heat margin calculation module generates each thermal node heat margin weight;Quadratic programming construction module constructs two-stage quadratic programming with the braking torque to be distributed as decision variable, primary minimizes unachievable braking torque, and secondary multi-objective optimization constructs objective function;Real-time solution module solves two-stage quadratic programming;Output interface module sends optimal braking torque instruction.Through the two-stage quadratic programming of safety priority, it is guaranteed that braking force meets priority, and through heat margin weight, heat load dynamic shift is realized, and energy recovery, wear and continuity are comprehensively optimized, without establishing prediction model, the problem that existing technology is difficult to consider braking force safety and multi-objective performance is solved.

Description

Technical Field

[0001] This invention relates to the field of vehicle control technology, and in particular to a composite braking control device, method and storage medium integrating a hub motor and an EMB. Background Technology

[0002] The in-wheel motor can switch from driving mode to power generation mode when the vehicle decelerates, converting the mechanical energy of the wheel into electrical energy and feeding it back to the power battery; the EMB (Electro-Mechanical Brake) generates clamping force through the motor, reduction gear and brake caliper, dissipating the mechanical energy of the wheel as frictional heat. The two are complementary in terms of energy utilization, braking force capability, temperature characteristics and low-speed availability, so they are suitable to form a wheel-end composite braking actuator.

[0003] Existing composite braking distribution schemes mainly include threshold / rule control, fuzzy control, and optimized distribution. For example, Chinese patent CN116653626A discloses a control system for a hub motor-driven vehicle that switches different braking modes based on the power battery charge, wheel braking force requirements, and hub motor fault status; Chinese patent CN119659560B discloses a composite braking slip ratio control system based on a hub motor and EMB that selects the braking torque distribution mode based on the motion mode switch and slope; and Chinese patent CN108162766B discloses a hub motor-driven automotive electromechanical-hydraulic redundant braking system and control method, whose control logic is "to prioritize the use of the hub motor for regenerative braking, and the electromechanical braking system is used for service braking compensation." Optimal braking force distribution methods aimed at maximizing regenerative energy also exist in academic research.

[0004] However, the existing solutions still have shortcomings in the secondary allocation of single-wheel hub motors and EMBs. Some solutions rely on predictive models, requiring multi-step predictions of the vehicle's future battery state of charge, motor feedback power, and wheel speed, resulting in a heavy online computational burden that is difficult to implement in real-time in wheel-end embedded microcontrollers. Furthermore, existing solutions struggle to balance braking safety and multi-objective performance under multiple physical constraints. Allocation logic based on fixed thresholds or rules is difficult to obtain continuously optimal solutions when operating conditions change, and its allocation results are easily affected by threshold calibration, limiting its adaptability to different operating conditions. In addition, the strategy of "using motor braking as much as possible" may further exacerbate the thermal load when the motor is at high temperatures. Nonlinear constraints such as motor efficiency graphs, temperature derating, and battery charging power lack efficient online processing methods. Moreover, if only a normal weight is set for braking force error in a single cost function, there is a safety risk of sacrificing the degree of braking force satisfaction to reduce energy consumption or heat loss. Summary of the Invention

[0005] In view of this, the present invention aims to provide a composite braking control device, method and storage medium integrating a hub motor and EMB, in order to solve the problem of real-time distribution of composite braking force at the wheel end that relies on predictive models and is difficult to balance braking force safety and multi-objective performance under multiple physical constraints.

[0006] To achieve the above objectives, the technical solution created by this invention is implemented as follows:

[0007] A first aspect of the present invention provides a composite braking control device integrating a hub motor and an EMB, comprising:

[0008] The input interface module is used to receive the target braking torque and the current wheel end state parameters, and to preprocess the target braking torque and the current wheel end state parameters;

[0009] The capability boundary calculation module, whose input end is connected to the input interface module, is used to determine the upper limit of the available regenerative braking torque of the hub motor and the upper limit of the available braking torque of the EMB within the current control cycle based on the current wheel end state parameters.

[0010] The heat loss and heat margin calculation module has its input end connected to the input interface module, and is used to generate the heat margin weight corresponding to each hot node based on the current wheel end state parameters.

[0011] The quadratic programming construction module, whose input terminals are connected to the input interface module, the capacity boundary calculation module, and the heat loss and heat margin calculation module, is used to construct a two-level quadratic programming problem with the regenerative braking torque of the hub motor to be allocated and the braking torque of the EMB to be allocated as decision variables. The two-level quadratic programming problem includes a first-level problem and a second-level problem. The first-level problem aims to minimize the unsatisfiable braking torque. The second-level problem constructs an objective function with multi-objective optimization within the feasible set corresponding to the minimum unsatisfiable braking torque determined by the first-level problem.

[0012] The real-time solution module, whose input is connected to the quadratic programming construction module, is used to solve the two-level quadratic programming in each control cycle to obtain the optimal hub motor driving torque and the optimal EMB braking torque of the target wheel.

[0013] The output interface module, whose input end is connected to the real-time solution module, is used to send the optimal hub motor driving torque and the optimal EMB braking torque to the hub motor controller and the EMB controller, respectively.

[0014] Furthermore, the current wheel-end status parameters include the current wheel speed, hub motor temperature, EMB actuator motor temperature, brake disc temperature, allowable charging power of the power battery, state of charge of the power battery, and allowable charging current of the power battery.

[0015] Furthermore, the heat loss and heat margin calculation module constructs a heat generation power function on the hub motor side, a heat generation power function on the EMB execution motor side, and a heat generation power function on the brake disc side based on the current wheel speed and the temperature of each heat node, and generates a corresponding heat margin weight based on the difference between the current temperature of each heat node and the preset temperature upper limit.

[0016] Furthermore, the heat generation power function on the hub motor side is a convex quadratic function of the regenerative braking torque of the hub motor to be allocated; the heat generation power function on the EMB actuator motor side is a convex quadratic function of the braking torque of the EMB to be allocated; and the heat generation power function on the brake disc side is positively correlated with the product of the current wheel speed and the braking torque of the EMB to be allocated.

[0017] Furthermore, the thermal margin weight increases monotonically as the difference between the current temperature of the thermal node and the preset upper temperature limit decreases.

[0018] Furthermore, the multi-objective optimization includes constructing an objective function with at least two of the following as optimization objectives: net braking energy recovery, thermal load of each of the hot nodes, friction and wear, and distribution changes between adjacent cycles.

[0019] Furthermore, the friction and wear are positively correlated with the product of the current wheel speed and the braking torque of the EMB to be allocated; the adjacent cycle allocation change is a quadratic function of the difference between the current cycle decision variable and the previous cycle decision variable.

[0020] Furthermore, the multi-objective optimization also includes battery stress, which is positively correlated with the square of the regenerative braking torque of the hub motor to be allocated, and the weight of battery stress increases when the state of charge of the power battery is higher than a preset threshold or the allowable charging power of the power battery is lower than a preset threshold.

[0021] Furthermore, the secondary problem also includes a constraint condition, which is a limit on the rate of change of braking torque in adjacent control cycles; when the braking urgency exceeds a preset threshold, the limit on the rate of change of braking torque is relaxed.

[0022] Furthermore, it also includes: a rollback allocation module, used to generate an executable allocation instruction according to the deterministic priority rule when the real-time solving module times out or an abnormal value occurs, and to report the unmet braking torque and abnormal status to the vehicle controller;

[0023] The deterministic priority rule is as follows: the maximum regenerative braking torque currently allowed by the hub motor is used first, and any insufficient part is made up by the EMB.

[0024] Furthermore, the factors determining the upper limit of the available regenerative braking torque include at least two of the following: the external characteristic profile of the hub motor, the allowable charging power of the power battery, the allowable charging current of the power battery, the upper limit of the thermal constraint of the hub motor, and the availability coefficient of the hub motor; the factors determining the upper limit of the available braking torque of the EMB include at least two of the following: the upper limit of the mechanical capacity of the EMB, the upper limit of the thermal constraint of the EMB actuator motor, the upper limit of the thermal constraint of the brake disc, and the availability coefficient of the EMB.

[0025] A second aspect of the present invention provides a composite braking control method integrating a hub motor and an EMB, for controlling the composite braking control device integrating a hub motor and an EMB described in the first aspect, comprising the following steps:

[0026] S1. Receive the target braking torque allocated to the target wheel by the vehicle controller, and obtain the current wheel-end state parameters;

[0027] S2. Based on the current wheel end state parameters, determine the upper limit of the available regenerative braking torque of the hub motor and the upper limit of the available braking torque of the EMB within the current control cycle.

[0028] S3. Generate the thermal margin weights corresponding to each hot node based on the current wheel end state parameters;

[0029] S4. Using the regenerative braking torque of the hub motor to be allocated and the braking torque of the EMB to be allocated as decision variables, construct a two-level quadratic programming problem. The two-level quadratic programming problem includes a first-level problem and a second-level problem. The first-level problem aims to minimize the unsatisfiable braking torque. The second-level problem constructs an objective function using multi-objective optimization within the feasible set corresponding to the minimum unsatisfiable braking torque determined by the first-level problem.

[0030] S5. Solve the two-level quadratic programming in each control cycle to obtain the optimal hub motor driving torque and optimal EMB braking torque of the target wheel;

[0031] S6. The optimal hub motor driving torque and the optimal EMB braking torque are sent to the hub motor controller and the EMB controller, respectively.

[0032] Furthermore, when solving the two-level quadratic programming problem, if the solution times out or a numerical anomaly occurs, an executable allocation instruction is generated according to the deterministic priority rule, and the unsatisfied braking torque and abnormal state are reported to the vehicle controller, instead of the step of sending the optimal hub motor braking torque and the optimal EMB braking torque to the hub motor controller and the EMB controller.

[0033] The deterministic priority rule is as follows: the maximum regenerative braking torque currently allowed by the hub motor is used first, and any insufficient part is made up by the EMB.

[0034] The third invention provides a computer-readable storage medium, wherein when the computer program is executed by a processor, it implements the steps of the composite braking control method integrating the hub motor and EMB described in the second aspect above.

[0035] Compared with the prior art, the present invention can achieve the following beneficial effects:

[0036] The target braking torque and current wheel end state parameters are received through the input interface module. The upper limit of the available regenerative braking torque of the hub motor and the upper limit of the available braking torque of the EMB are determined as linear boundary constraints through the capacity boundary calculation module. There is no need to build a prediction model for multi-step prediction, which significantly reduces the online calculation burden.

[0037] By constructing a two-level quadratic programming model with safety as the priority, the first-level problem ensures that the braking torque gap is quantified and reported first, and the second-level problem seeks the comprehensive optimal allocation through multi-objective optimization, which ensures that the braking force meets the priority of other performance objectives and eliminates the safety hazard of sacrificing braking force to reduce energy consumption.

[0038] Meanwhile, by generating heat margin weights for each hot node through the heat loss and heat margin calculation module, the secondary optimization can dynamically transfer braking loads between hot nodes, effectively reducing the risk of local overheating and thermal decay.

[0039] The two-level quadratic programming problem is solved by a real-time solution module, and the optimal hub motor driving torque and optimal EMB braking torque are sent to the hub motor controller and EMB controller respectively through the output interface module, realizing a complete control link from data input, optimization calculation to command output.

[0040] In summary, this invention only requires the current wheel-end state parameters to complete the optimal allocation calculation, effectively solving the problem of real-time allocation of wheel-end composite braking force that relies on prediction models and is difficult to balance braking force safety and multi-objective performance in existing technologies. Attached Figure Description

[0041] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments and descriptions of the invention are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0042] Figure 1 A schematic diagram of the functional composition and data flow of a single-wheel compound braking control device provided in an embodiment of the present invention;

[0043] Figure 2 A flowchart illustrating the compound braking force distribution method based on quadratic programming provided for embodiments of the present invention;

[0044] Figure 3 A schematic diagram illustrating the principle of thermally constrained torque reduction provided for embodiments of the present invention;

[0045] Figure 4 A schematic diagram of a two-level quadratic programming structure prioritizing safety is provided for an embodiment of the present invention;

[0046] Figure 5 A schematic diagram of the hardware / software modules of the composite braking control device provided in an embodiment of the present invention;

[0047] Figure 6 A flowchart of a composite braking control method integrating a hub motor and an EMB, provided for an embodiment of the present invention. Detailed Implementation

[0048] 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 specific embodiments. It should be understood that the specific embodiments described herein are only for explaining the invention and do not constitute a limitation thereof. Similar elements in different embodiments are referred to by associated similar element reference numerals. In the following embodiments, many details are described to facilitate a better understanding of the invention. However, those skilled in the art will readily recognize that some features may be omitted in different situations, or may be replaced by other elements, materials, or methods. In some cases, some operations related to the invention are not shown or described in the specification. This is to avoid obscuring the core parts of the invention with excessive description. For those skilled in the art, detailed description of these related operations is not necessary; they can fully understand the related operations based on the description in the specification and general technical knowledge in the art.

[0049] It should be noted that, unless otherwise specified, the embodiments and features described in this invention can be combined to form various implementations. Furthermore, the order of the steps or actions in the method description can be changed or adjusted in a manner readily apparent to those skilled in the art. Therefore, the various orders in the specification and drawings are merely for the clear description of a particular embodiment and do not imply a mandatory order, unless otherwise stated that a particular order must be followed.

[0050] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this invention. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0051] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0052] The invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0053] like Figures 1 to 6 As shown, the first aspect of this embodiment provides a composite braking control device integrating a hub motor and an EMB, including an input interface module, a capacity boundary calculation module, a heat loss and heat margin calculation module, a quadratic programming construction module, a real-time solution module, and an output interface module.

[0054] It should be noted that in actual vehicle architecture, after the vehicle controller completes the calculation of the total braking force requirement and the distribution to the four wheels, the target braking torque at each wheel end and the current wheel end status parameters are transmitted to the composite braking control device of this embodiment through a communication interface module (such as CAN, CAN-FD, or vehicle Ethernet). This communication interface module is an interface of the upper-layer communication network and is used to input external data to this device. This device receives the target braking torque and current wheel end status parameters transmitted via this communication interface module through an input interface module.

[0055] Specifically, the input interface module receives the target braking torque and current wheel-end state parameters, and preprocesses these parameters. The current wheel-end state parameters include the current wheel speed, hub motor temperature, EMB actuator motor temperature, brake disc temperature, allowable charging power of the power battery, power battery state of charge, and allowable charging current of the power battery. Through preprocessing, the input interface module converts the raw data acquired by the communication interface module into a unified format and physical units for use by subsequent modules.

[0056] The input end of the capability boundary calculation module is connected to the input interface module, and is used to determine the upper limit of the available regenerative braking torque of the hub motor and the upper limit of the available braking torque of the EMB within the current control cycle based on the preprocessed current wheel end state parameters.

[0057] In some embodiments, the upper limit of the available regenerative braking torque of the hub motor can be determined based on at least two of the following: the hub motor external characteristic profile, the allowable charging power of the power battery, the allowable charging current of the power battery, the upper limit of the hub motor thermal constraint, and the hub motor availability coefficient. The upper limit of the available braking torque of the EMB can be determined based on at least two of the following: the upper limit of the EMB mechanical capacity, the upper limit of the EMB actuator motor thermal constraint, the upper limit of the brake disc thermal constraint, and the EMB availability coefficient. Specifically, the hub motor external characteristic profile represents the upper limit of the generator braking torque of the motor / inverter at different speeds and DC bus voltages; the allowable charging power and allowable charging current of the power battery represent the current allowable charging capacity provided by the battery management system; the upper limit of the hub motor thermal constraint is the upper limit of the braking torque to prevent overheating, determined based on the current temperature of the hub motor; and the hub motor availability coefficient is a coefficient characterizing the health status or temperature derating degree of the hub motor, which is 1 under normal conditions and less than 1 when the temperature is too high or there is a partial fault. The upper limit of EMB mechanical capacity is jointly determined by the maximum clamping force of EMB, the friction coefficient of brake disc, and the effective radius of brake disc; the upper limit of EMB actuator motor thermal constraint is the upper limit of braking torque to prevent overheating of actuator motor determined based on the current temperature of EMB actuator motor; the upper limit of brake disc thermal constraint is the upper limit of braking torque to prevent brake disc thermal fade determined based on the current temperature of brake disc; the EMB availability coefficient is a coefficient characterizing the health status or temperature derating degree of EMB, which is 1 under normal conditions and less than 1 when the temperature is too high or there is a partial fault.

[0058] The input end of the heat loss and heat margin calculation module is connected to the input interface module, which is used to generate the heat margin weight corresponding to each hot node based on the current wheel end state parameters.

[0059] It should be noted that hot nodes refer to critical thermodynamic nodes in compound braking systems that require temperature monitoring to prevent overheating failure. These include the hub motor / inverter hot node, the EMB actuator motor hot node, and the brake disc / friction pair hot node. Specifically, the hub motor / inverter hot node corresponds to the hub motor stator windings and the inverter power switching devices; exceeding their temperature limits will lead to insulation aging and power device failure. The EMB actuator motor hot node corresponds to the EMB drive motor windings; exceeding its temperature limit will cause a decrease in the motor's output clamping force. The brake disc / friction pair hot node corresponds to the friction pair between the brake disc and the friction pads; exceeding its temperature limit will cause a decrease in the coefficient of friction (i.e., thermal decay), resulting in a reduction in braking torque output capability.

[0060] The temperature of each hot node can be directly measured by a temperature sensor. The preset upper limit of the hot node temperature can be determined by bench calibration or obtained by other means, without any restrictions here.

[0061] Specifically, the heat loss and heat margin calculation module constructs the heating power functions for the hub motor, EMB execution motor, and brake disc based on the current wheel speed and the temperature of each hot node. It then generates corresponding heat margin weights based on the difference between the current temperature of each hot node and a preset upper temperature limit. Specifically, the hub motor heating power function is a convex quadratic function of the regenerative braking torque of the hub motor to be allocated; the EMB execution motor heating power function is a convex quadratic function of the braking torque of the EMB to be allocated; and the brake disc heating power function is positively correlated with the product of the current wheel speed and the braking torque of the EMB to be allocated. Furthermore, the heat margin weights monotonically increase as the difference between the current temperature of the hot node and the preset upper temperature limit decreases, quantifying the margin between the current temperature and the upper temperature limit, for use by the subsequent secondary planning module when constructing the objective function.

[0062] Specifically, each hot node includes the hub motor / inverter hot node, the EMB actuator motor hot node, and the brake disc / friction pair hot node. The heat loss and thermal margin calculation module first uses loss or efficiency maps to fit the heat generation power of each hot node as a convex quadratic function of the corresponding braking torque, based on the current wheel speed and the temperature of each hot node, to describe the heat generation characteristics of each hot node near the current operating point. Then, it calculates the thermal margin of each hot node based on the difference between the current temperature and the preset upper temperature limit. The smaller the difference, the smaller the thermal margin, and the larger the corresponding thermal margin weight. The thermal margin weight is used to weight the heat load of each hot node in the objective function of subsequent quadratic programming. When the temperature of a hot node increases and the thermal margin decreases, the thermal penalty weight of that node automatically increases, thereby guiding the optimal allocation to shift towards the actuator with a larger thermal margin, realizing dynamic heat load transfer between hot nodes.

[0063] Furthermore, the heat loss and heat margin calculation module can calculate the allowable heat power budget of each hot node in the current control cycle based on the lumped heat balance, and convert each heat power function constraint into a scalar torque upper limit to update the upper limits of each heat constraint in the capacity boundary calculation module.

[0064] Specifically, for each hot node, the maximum allowable heat generation power (i.e., allowable heat power budget) is calculated based on the difference between its current temperature and the preset upper temperature limit, the control cycle duration, and the heat dissipation conditions. Then, by ensuring that the heat generation power function of each hot node does not exceed the corresponding allowable heat power budget, the scalar torque upper limit for each hot node can be obtained, including the upper limit of the hub motor thermal constraint, the upper limit of the EMB actuator motor thermal constraint, and the upper limit of the brake disc thermal constraint. This is used by the capability boundary calculation module when updating the upper limit of available braking torque in the next control cycle or the current control cycle.

[0065] In the above way, the constraint of the heat generation power function is pre-converted into the scalar torque upper limit of the current control cycle, and after entering the quadratic programming, it only manifests as a linear boundary constraint.

[0066] Furthermore, the upper limits of the thermal constraints for the hub motor and the EMB actuator motor are calculated by the heat loss and thermal margin calculation module based on the thermal margin between the current temperature of each hot node and the preset upper limit of temperature, and then output to the capability boundary calculation module. The upper limit of the brake disc thermal constraint is related to the product of the current wheel speed and the EMB braking torque. When the brake disc temperature approaches the preset upper limit, the upper limit of the brake disc thermal constraint decreases to limit the use of EMB friction braking. Through the above method of determining the capability boundaries, this embodiment uniformly converts the electrical capability of the hub motor, the battery charging capability, the EMB mechanical capability, and the temperature state of each hot node into the upper limit of the available braking torque for the current control cycle, transforming multiple nonlinear physical constraints into linear boundary constraints for use by the secondary planning construction module.

[0067] The input terminals of the quadratic programming construction module are connected to the input interface module, the capacity boundary calculation module, and the heat loss and heat margin calculation module, respectively. It is used to construct a two-level quadratic programming problem with the regenerative braking torque of the hub motor to be allocated and the braking torque of the EMB to be allocated as decision variables. The two-level quadratic programming problem includes a first-level problem and a second-level problem. The first-level problem aims to minimize the unsatisfiable braking torque. The second-level problem constructs the objective function through multi-objective optimization within the feasible set corresponding to the minimum unsatisfiable braking torque determined by the first-level problem.

[0068] Specifically, the quadratic programming construction module obtains the target braking torque from the input interface module, the upper limit of the available regenerative braking torque of the hub motor and the upper limit of the available braking torque of the EMB from the capacity boundary calculation module, and the heat margin weight of each hot node from the heat loss and heat margin calculation module. The decision variables of the two-level quadratic programming are the regenerative braking torque of the hub motor to be allocated and the braking torque of the EMB to be allocated.

[0069] The primary problem aims to minimize the unsatisfiable braking torque. Specifically, the quadratic programming module aims to minimize the square of the difference between the target braking torque and the sum of the regenerative braking torque of the hub motor and the braking torque of the EMB. Using the upper limits of the available regenerative braking torque of the hub motor and the available braking torque of the EMB as constraints, the minimum unsatisfiable braking torque is obtained. When the total available capacity of the hub motor and EMB meets the target braking torque, the minimum unsatisfiable braking torque is zero; when the total available capacity is insufficient, the minimum unsatisfiable braking torque is the difference between the total available capacity and the target braking torque.

[0070] The second-level problem, within the feasible set corresponding to the minimum unsatisfactory braking torque determined by the first-level problem, constructs an objective function using multi-objective optimization. Preferably, the multi-objective optimization can include at least two of the following as optimization objectives: net braking energy recovery, thermal load of each hot node, friction and wear, and adjacent cycle allocation change. Specifically, the net braking energy recovery term maximizes the net recovered power after deducting losses from the hub motor and inverter; the thermal load term for each hot node weights the heat generation power of each hot node using thermal margin weights, with a larger penalty for a smaller thermal margin; the friction and wear term reduces the wear of the EMB friction pads; and the adjacent cycle allocation change term suppresses allocation jumps between adjacent control cycles. When the temperature of a hot node increases and the thermal margin decreases, the weight of the corresponding thermal load term in the objective function automatically increases, thereby guiding the optimal allocation to shift towards actuators with larger thermal margins.

[0071] Furthermore, frictional wear is positively correlated with the product of the current wheel speed and the braking torque of the EMB to be allocated. That is, the larger the EMB frictional braking torque and the higher the current wheel speed, the larger the value of the frictional wear term. This suppresses unnecessary EMB frictional braking during optimization, reducing friction pad wear and brake dust emissions. The allocation change between adjacent cycles is a quadratic function of the difference between the current cycle's decision variable and the previous cycle's decision variable. Specifically, it is the sum of the square of the difference between the current cycle's hub motor braking torque and the previous cycle's hub motor braking torque, and the square of the difference between the current cycle's EMB braking torque and the previous cycle's EMB braking torque. This is used to suppress allocation jumps and frequent actuator switching between adjacent control cycles, improving system stability and service life. When braking urgency increases, the weight of the allocation change term between adjacent cycles decreases to ensure rapid response during emergency braking.

[0072] Preferably, the multi-objective optimization also includes battery stress, which is positively correlated with the square of the regenerative braking torque of the hub motor to be allocated; that is, the larger the regenerative braking torque of the hub motor, the larger the value of the battery stress term. When the state of charge of the power battery is higher than a preset threshold or the allowable charging power of the power battery is lower than a preset threshold, the weight of battery stress increases, thereby limiting the regenerative braking power when the battery is close to full charge or its charging capacity is limited, avoiding excessive charging stress on the battery and protecting its health.

[0073] Through the objective function constructed by the above multi-objective optimization, this embodiment comprehensively balances multiple performance indicators such as energy recovery efficiency, heat load distribution, friction and wear, distribution continuity and battery stress while ensuring that braking force is satisfied first.

[0074] Preferably, the constraints of the secondary problem also include a limit on the rate of change of braking torque between adjacent control cycles to prevent abrupt changes in braking torque command. When the braking urgency exceeds a preset threshold, the limit on the rate of change of braking torque is relaxed to ensure rapid response during emergency braking. The optimization objectives of the secondary problem are weighted and summed to form the overall objective function. The weights of each objective are adaptively adjusted according to the thermal state, braking urgency, battery state, and operating mode. However, regardless of the mode, the safety priority of the primary problem remains unchanged. Through the above-mentioned two-level quadratic programming with safety priority, this embodiment ensures that braking force takes precedence over other performance objectives such as energy recovery and thermal management.

[0075] The input of the real-time solution module is connected to the quadratic programming construction module, which is used to solve two-level quadratic programming in each control cycle to obtain the optimal hub motor driving torque and optimal EMB braking torque of the target wheel.

[0076] Specifically, the real-time solution module receives a two-level quadratic programming problem output by the quadratic programming construction module. First, it solves the first-level problem to obtain the minimum unsatisfiable braking torque. Then, under the constraints corresponding to the minimum unsatisfiable braking torque, it solves the second-level problem to obtain the optimal hub motor braking torque and the optimal EMB braking torque. The two-level quadratic programming problem is a convex quadratic programming problem with a convex quadratic objective function and linear constraints. The real-time solution module can use any of the active set method, interior point method, or alternating direction multiplier method for solution, or it can use an embedded quadratic programming solver. No specific limitations are imposed on the solution method here.

[0077] Within each control cycle, the real-time solving module can use the optimal solution from the previous control cycle as the initial value for the current cycle's hot start, thereby improving solving efficiency. Each control cycle can preferably be 1ms to 20ms. After the solution is completed, the real-time solving module outputs the optimal hub motor driving torque and optimal EMB braking torque of the target wheel to the output interface module.

[0078] Since the decision variables in a two-level quadratic programming problem are only two and the computational scale is fixed, the real-time solution module can efficiently complete the solution within each control cycle, making it suitable for real-time implementation in wheel-end embedded microcontrollers.

[0079] The input end of the output interface module is connected to the real-time solution module, which is used to send the optimal hub motor driving torque and the optimal EMB braking torque to the hub motor controller and the EMB controller, respectively.

[0080] Specifically, the output interface module receives the optimal hub motor driving torque and optimal EMB braking torque output by the real-time solving module, sends the optimal hub motor driving torque to the hub motor controller, and sends the optimal EMB braking torque to the EMB controller. Based on the received optimal hub motor driving torque, the hub motor controller controls the hub motor to output the corresponding regenerative braking torque; based on the received optimal EMB braking torque, the EMB controller controls the EMB to output the corresponding friction braking torque. Through this method, the optimal distribution of the target braking torque for this wheel between the hub motor and the EMB can be achieved.

[0081] It is understandable that the braking torque sent by the output interface module is a non-negative amplitude. When it is actually sent to the actuator, a negative sign can be added according to the vehicle coordinate system convention to indicate the direction of braking force. The specific processing method is not limited here.

[0082] The above technical solution receives the target braking torque and current wheel end state parameters through the input interface module, and determines the upper limit of the available regenerative braking torque of the hub motor and the upper limit of the available braking torque of the EMB as linear boundary constraints through the capability boundary calculation module. This eliminates the need to build a prediction model for multi-step prediction, significantly reducing the online calculation burden.

[0083] By constructing a two-level quadratic programming model with safety as the priority, the first-level problem ensures that the braking torque gap is quantified and reported first, and the second-level problem seeks the comprehensive optimal allocation through multi-objective optimization, which ensures that the braking force meets the priority of other performance objectives and eliminates the safety hazard of sacrificing braking force to reduce energy consumption.

[0084] Meanwhile, by generating heat margin weights for each hot node through the heat loss and heat margin calculation module, the secondary optimization can dynamically transfer braking loads between hot nodes, effectively reducing the risk of local overheating and thermal decay.

[0085] The two-level quadratic programming problem is solved by a real-time solution module, and the optimal hub motor driving torque and optimal EMB braking torque are sent to the hub motor controller and EMB controller respectively through the output interface module, realizing a complete control link from data input, optimization calculation to command output.

[0086] In summary, this invention only requires the current wheel-end state parameters to complete the optimal allocation calculation, effectively solving the problem of real-time allocation of wheel-end composite braking force that relies on prediction models and is difficult to balance braking force safety and multi-objective performance in existing technologies.

[0087] In some embodiments, the composite braking control device integrating the hub motor and EMB may further include a backoff allocation module, used to generate executable allocation instructions according to a deterministic priority rule when the real-time solution module times out or an anomaly occurs, and to report the unmet braking torque and the abnormal state to the vehicle controller. It is understood that the deterministic priority rule is: the maximum regenerative braking torque currently allowed by the hub motor is used first, and any shortfall is supplemented by the EMB. That is, when an anomaly occurs, the backoff allocation module first compares the target braking torque of the current wheel with the maximum regenerative braking torque currently allowed by the hub motor, and takes the smaller value as the actual braking torque of the hub motor; if the target braking torque exceeds the maximum regenerative braking torque currently allowed by the hub motor, the excess is supplemented by the EMB; if the target braking torque still cannot be fully satisfied, the remaining unmet braking torque is reported to the vehicle controller as a capability gap.

[0088] Through the above-described rollback allocation method, this embodiment can provide a deterministic and verifiable degradation allocation scheme when the solver is abnormal, ensuring that the composite braking system can output executable braking torque commands under any circumstances, and promptly report the capacity gap to the vehicle controller so that the vehicle layer can take corresponding compensation measures, thereby improving the functional safety and reliability of the system.

[0089] A second aspect of the present invention provides a composite braking control method integrating a hub motor and an EMB, for controlling the composite braking control device integrating a hub motor and an EMB as described in the first aspect, comprising the following steps:

[0090] S1. Receive the target braking torque allocated to the target wheel by the vehicle controller, and obtain the current wheel end state parameters.

[0091] Specifically, the target braking torque allocated to the target wheels by the vehicle controller is received through the input interface module. And obtain the current wheel-end state parameters. The current wheel-end state parameters include the current wheel speed. Hub motor temperature EMB motor temperature control Brake disc temperature Permissible charging power of the power battery The state of charge (SOC) of the power battery and the allowable charging current of the power battery. The obtained parameters are used in subsequent steps for capacity boundary calculation, heat margin weight generation, and quadratic programming construction.

[0092] S2. Based on the current wheel end state parameters, determine the upper limit of the available regenerative braking torque of the hub motor and the upper limit of the available braking torque of the EMB within the current control cycle.

[0093] Specifically, the upper limit of the available regenerative braking torque of the hub motor is determined based on at least two of the following: the external characteristic profile of the hub motor, the allowable charging power of the power battery, the allowable charging current of the power battery, the upper limit of the thermal constraint of the hub motor, and the availability coefficient of the hub motor. Preferably, the upper limit of the available regenerative braking torque of the hub motor is determined according to the following formula:

[0094] ,

[0095] in, This is represented by the upper limit of the generator braking torque obtained from the external characteristic diagram of the hub motor. This represents the current wheel speed. Represented as DC bus voltage. This is expressed as the temperature of the hub motor; This indicates the allowable charging power of the power battery. This represents the allowable charging current of the power battery. This is expressed as the equivalent efficiency from the mechanical power of the wheel to the charging power of the battery. This represents the minimum angular velocity set to prevent division by zero at low speeds; This represents the upper limit of the thermal constraint for the hub motor; ∈[0,1] represents the availability factor of the hub motor, which is 1 under normal conditions and less than 1 under temperature derating or partial failure. This is expressed as the rated regenerative braking torque of the hub motor; The target braking torque. When the wheel speed is lower than the effective speed of regenerative braking. It can be set to 0 or gradually decayed according to a smoothing function.

[0096] The upper limit of the available braking torque of the EMB is determined based on at least two of the following: the upper limit of the EMB mechanical capacity, the upper limit of the EMB actuator thermal constraint, the upper limit of the brake disc thermal constraint, and the EMB availability coefficient. Preferably, the upper limit of the available braking torque of the EMB is determined according to the following formula:

[0097] ,

[0098] in, This represents the upper limit of EMB mechanical capacity. Apply the upper limit of motor thermal constraints to EMB. This is the upper limit of the brake disc thermal constraint. ∈[0,1] is the EMB availability coefficient, which is 1 under normal conditions and less than 1 when the temperature is too high or there is a partial failure; Rated power torque for EMB.

[0099] It should be noted that the upper limit of EMB mechanical capacity is jointly determined by the maximum clamping force of the EMB, the coefficient of friction of the brake disc, and the effective radius of the brake disc, i.e.

[0100] ,

[0101] in, This is expressed as the coefficient of friction as a function of brake disc temperature. This represents the maximum clamping force of the EMB (which varies with the temperature of the EMB actuator motor). Let be the effective radius of the friction pair.

[0102] In this way, the electrical capability of the hub motor, the battery charging capability, the EMB mechanical capability, and the temperature status of each thermal node are uniformly converted into the upper limit of the available braking torque in the current control cycle, thus transforming multiple nonlinear physical constraints into linear boundary constraints.

[0103] S3. Generate the thermal margin weights for each hot node based on the current wheel end state parameters.

[0104] Specifically, this step first determines the current wheel speed. and the temperature of each thermal node , , Construct the heat generation power function for each hot node. Among them, the heat generation power function for the hub motor side is... For the regenerative braking torque of the hub motor to be allocated Convex quadratic function:

[0105] ,

[0106] in, , , Indicated based on the current speed and current temperature The fitting coefficients are read from the calibration graph or obtained through interpolation, and .

[0107] EMB executes the motor-side heat generation power function For the braking torque of the EMB to be assigned Convex quadratic function:

[0108] ,

[0109] in, , , To be based on the current temperature The fitting coefficients obtained from the calibration data, and .

[0110] Brake disc side heat generation power function With current wheel speed Braking torque of the EMB to be allocated The product of them is positively correlated:

[0111] ,

[0112] in, ∈(0,1] represents the heat distribution coefficient allocated to the monitored brake disc / friction pair hot nodes.

[0113] Then, based on the lumped heat balance, the allowable heat power budget for each hot node within the current control cycle is calculated. :

[0114] ,

[0115] in, These represent the thermal nodes of the hub motor, the EMB actuator motor, and the brake disc / friction pair, respectively. Expressed as equivalent heat capacity, It is expressed as the equivalent heat dissipation coefficient to the environment. This indicates the preset upper temperature limit. Indicated as ambient temperature. This is represented as the control cycle. The corresponding heating power is set to not exceed... The upper limit of the scalar torque corresponding to the thermal constraint can then be obtained. , and This is used to update the upper limits of each thermal constraint in step S2.

[0116] Finally, based on the current temperature of each hot node... With preset temperature upper limit The difference between them generates the corresponding heat margin weight. :

[0117] ,

[0118] in, This is to prevent small positive numbers with a denominator of zero. , This is expressed as a reference temperature difference value. This represents the upper and lower limits of the saturation function. This represents the lower limit of the heat margin weight. This is expressed as the upper limit of the heat margin weight, i.e., the heat margin weight. The saturation interval constraint boundary. and The specific values ​​can be preset according to calibration or design requirements, for example... 0.1 is acceptable. A value of 10 can be used, without any specific limitation. This heat margin weight increases monotonically as the difference between the current temperature of the hot node and the preset upper temperature limit decreases. When a hot node approaches its preset upper temperature limit, the heat margin weight of that node increases, thereby guiding subsequent secondary optimizations to shift towards actuators with larger heat margins.

[0119] S4. Using the regenerative braking torque of the hub motor to be assigned and the braking torque of the EMB to be assigned as decision variables, construct a two-level quadratic programming problem. The two-level quadratic programming problem includes a first-level problem and a second-level problem. The first-level problem aims to minimize the unsatisfiable braking torque. The second-level problem constructs the objective function by multi-objective optimization within the feasible set corresponding to the minimum unsatisfiable braking torque determined by the first-level problem.

[0120] Specifically, using the regenerative braking torque of the hub motor and EMB braking torque For the decision variables, construct a two-level quadratic programming problem.

[0121] The first-level problem aims to minimize the unsatisfiable braking torque:

[0122] ,

[0123] ,

[0124] ,

[0125] ,

[0126] ,

[0127] in, Represents minimizing the objective function The subscript "1" represents a first-level question; This indicates that the braking torque is unsatisfactory. This indicates the upper limit of the available regenerative braking torque of the hub motor. This represents the upper limit of the available braking torque of the EMB. The solution to this first-order problem is... When total capacity meets demand. When total capacity is insufficient, the gap is clearly quantified. If If so, the gap will be reported to the vehicle controller.

[0128] The second-level problem, within the feasible set corresponding to the minimum unsatisfiable braking torque ε* determined by the first-level problem, constructs its objective function through multi-objective optimization. The constraints of the second-level problem are:

[0129] ,

[0130] ,

[0131] ,

[0132] Objective function of the second-order problem Including net braking energy recovery items Heat load items at each thermal node Friction and wear items and adjacent period allocation change terms At least two of the following:

[0133] ,

[0134] ,

[0135] ,

[0136] ,

[0137] in, , , , , These are respectively represented as the weight coefficients of each item. , Represented as loss fitting coefficients, This represents the actual regenerative braking torque of the hub motor in the previous control cycle. This represents the actual braking torque of the EMB in the previous control cycle. The friction and wear term is related to the current wheel speed. and EMB braking torque The product of the variables is positively correlated; the change term in the distribution between adjacent periods is a quadratic function of the difference between the decision variable of the current period and the decision variable of the previous period.

[0138] Preferably, the objective function of the second-order problem also includes a battery stress term. :

[0139] ,

[0140] Battery stress term and regenerative braking torque of hub motor The square of the equation is positively correlated. When the state of charge (SOC) of the power battery exceeds a preset threshold or the allowable charging power of the power battery... When the weight of the battery stress term is below a preset threshold, Increase.

[0141] The overall objective function of the second-order problem is the weighted sum of all terms:

[0142] ,

[0143] The weights of each item are adaptively adjusted based on thermal state, braking urgency, battery state, and operating mode, but the safety priority of the first-level problem remains unchanged regardless of the mode.

[0144] Preferably, the constraints of the second-level problem also include a limit on the rate of change of braking torque between adjacent control cycles:

[0145] ,

[0146] ,

[0147] in, This indicates the maximum allowable change in the torque of the hub motor per control cycle. This indicates the maximum allowable decrease in EMB braking torque per control cycle. The absolute value of the difference between the regenerative braking torque of the wheel hub motor in the current cycle and the regenerative braking torque of the wheel hub motor in the previous cycle must not exceed the preset maximum change. .Right now The value of is restricted to the interval Within. The absolute value of the difference between the braking torque of the current EMB cycle and the braking torque of the previous EMB cycle must not exceed the preset maximum change. .Right now The value of is restricted to the interval Inside.

[0148] When braking emergency When the threshold is exceeded, it indicates that the current braking torque demand is relatively urgent, and the limit on the rate of change of braking torque is relaxed. and Increasing the value allows for a larger single-cycle change in the decision variables of the current cycle relative to the previous cycle, ensuring a rapid response during emergency braking; conversely, when... When the value is small, the rate of change limit is kept relatively strict to suppress allocation jumps and frequent actuator switching, thereby improving system stability and actuator lifespan. The target braking torque for the current control cycle, The preset maximum target braking torque (i.e., the maximum braking demand that the vehicle can achieve). The braking urgency level typically ranges from [0,1]. A smaller value indicates a smaller current braking torque demand and a less urgent braking situation. The larger the value, the closer the current braking torque demand is to the maximum value and the higher the braking urgency.

[0149] S5. Solve the two-level quadratic programming problem in each control cycle to obtain the optimal hub motor driving torque and the optimal EMB braking torque of the target wheel.

[0150] Specifically, the two-level quadratic programming problem constructed in step S4 is solved within each control cycle. First, the first-level problem is solved to obtain the minimum unsatisfiable braking torque. Subsequently, in Solving the second-order problem under constraints yields the optimal driving torque of the hub motor. and optimal EMB braking torque Each control cycle is preferably 1ms to 20ms. The optimal solution from the previous control cycle is used during the solution process. , Used as the initial value for a warm start.

[0151] S6. Send the optimal hub motor driving torque and the optimal EMB braking torque to the hub motor controller and the EMB controller, respectively.

[0152] Specifically, this step will use the optimal hub motor driving torque obtained in step S5. and optimal EMB braking torque The signals are sent to the hub motor controller and the EMB controller, respectively. The hub motor controller controls the hub motor to output the corresponding regenerative braking torque based on the received optimal hub motor braking torque; the EMB controller controls the EMB to output the corresponding friction braking torque based on the received optimal EMB braking torque, thereby achieving optimal distribution of the target braking torque for this wheel between the hub motor and the EMB. If step S5 triggers a rollback distribution, this step sends the executable distribution command generated by the rollback distribution module. and It is understandable that the transmitted braking torque is a non-negative amplitude. When it is actually transmitted to the actuator, a negative sign can be added according to the vehicle coordinate system convention to indicate the direction of braking force.

[0153] Furthermore, when solving the two-level quadratic programming problem, if the solution times out or numerical anomalies occur, an executable allocation instruction is generated according to the deterministic priority rule, and the unmet braking torque and abnormal state are reported to the vehicle controller, instead of sending the optimal hub motor driving torque and the optimal EMB braking torque to the hub motor controller and the EMB controller.

[0154] The deterministic priority rule is as follows: the maximum regenerative braking torque currently allowed by the hub motor is used first, and any shortfall is made up by the EMB.

[0155] Specifically, if the solution times out or an abnormal value occurs, a rollback assignment will be triggered:

[0156] ,

[0157] ,

[0158] ,

[0159] This means that the maximum regenerative braking torque currently allowed by the hub motor will be used first, with any shortfall made up by the EMB, and the remaining gap will be filled. And report abnormal conditions to the vehicle controller. Among them, This represents the actual braking torque of the hub motor in reversing mode. This represents the actual braking torque of the EMB in rollback mode. This is represented as the unsatisfiable braking torque (capacity gap) in the backoff mode. Represented as the target braking torque, This represents the upper limit of the regenerative braking torque available for the hub motor. This represents the upper limit of the available braking torque for the EMB. This represents taking the minimum value.

[0160] First, the target braking torque The upper limit of the regenerative braking torque available from the hub motor The smaller value is selected as the actual braking torque of the hub motor in the reversing mode. That is, the maximum regenerative braking torque currently allowed by the hub motor is used first to bear the braking torque; if the target braking torque Exceeding the upper limit of the available regenerative braking torque of the hub motor The excess is then supplemented by the EMB, which is the actual braking torque of the EMB in the rollback mode. The remaining requirement is obtained by subtracting the actual braking torque of the hub motor from the target braking torque. With the upper limit of the available braking torque of the EMB The smaller of the two values; if the target braking torque still cannot be fully satisfied, then the target braking torque is subtracted from the difference between the actual braking torque of the hub motor and the actual braking torque of the EMB. The capability gap is reported to the vehicle controller.

[0161] like This indicates that the target braking torque has been fully satisfied; if This indicates that the total available capacity of the actuators is insufficient. This gap needs to be reported to the vehicle controller, and the vehicle level will decide whether to request compensation from other wheels or take degraded measures.

[0162] By using the above-mentioned rollback allocation method, a deterministic and verifiable degradation allocation scheme can be provided when the solver is abnormal, ensuring that the composite braking system can output executable braking torque commands under any circumstances, and promptly report the capacity gap to the vehicle controller so that the vehicle level can take corresponding compensation measures, thereby improving the functional safety and reliability of the system.

[0163] The third invention provides a computer-readable storage medium in which a computer program, when executed by a processor, implements the steps of the composite braking control method integrating a hub motor and an EMB as described in the second aspect.

[0164] Specifically, the computer program includes program code. When the program code is executed by the processor, it can perform the following steps: receive the target braking torque allocated to the target wheel by the vehicle controller and obtain the current wheel-end state parameters; determine the upper limit of the available regenerative braking torque of the hub motor and the upper limit of the available braking torque of the EMB in the current control cycle based on the current wheel-end state parameters; generate the heat margin weights corresponding to each hot node based on the current wheel-end state parameters; construct a two-level quadratic programming problem using the regenerative braking torque of the hub motor to be allocated and the braking torque of the EMB to be allocated as decision variables. The two-level quadratic programming problem includes a first-level problem and a second-level problem. The first-level problem aims to minimize the unsatisfiable braking torque, and the second-level problem constructs the objective function using multi-objective optimization within the feasible set corresponding to the minimum unsatisfiable braking torque determined by the first-level problem; solve the two-level quadratic programming problem in each control cycle to obtain the optimal hub motor braking torque and the optimal EMB braking torque of the target wheel; and send the optimal hub motor braking torque and the optimal EMB braking torque to the hub motor controller and the EMB controller, respectively.

[0165] Preferably, when the computer program is executed by the processor, it can also achieve the following: when solving a two-level quadratic programming problem, if the solution times out or a numerical anomaly occurs, an executable allocation instruction is generated according to the deterministic priority rule, and the unmet braking torque and abnormal state are reported to the vehicle controller, instead of the step of sending the optimal hub motor braking torque and the optimal EMB braking torque to the hub motor controller and the EMB controller; the deterministic priority rule is: the maximum regenerative braking torque currently allowed by the hub motor is used first, and the insufficient part is supplemented by the EMB.

[0166] Computer-readable storage media can be any tangible medium capable of storing program code, including, but not limited to, USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0167] The method of the present invention can be stored in the medium as program code and executed on a suitable processor through the computer-readable storage medium described above, thereby realizing the optimal allocation calculation and rollback allocation functions provided by the present invention.

[0168] Although embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

[0169] The specific embodiments of the present invention described above do not constitute a limitation on the scope of protection of the present invention. Any other corresponding changes and modifications made in accordance with the technical concept of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A composite braking control device integrating a hub motor and an EMB, characterized in that, include: The input interface module is used to receive the target braking torque and the current wheel end state parameters, and to preprocess the target braking torque and the current wheel end state parameters; The capability boundary calculation module, whose input end is connected to the input interface module, is used to determine the upper limit of the available regenerative braking torque of the hub motor and the upper limit of the available braking torque of the EMB within the current control cycle based on the current wheel end state parameters. The heat loss and heat margin calculation module has its input end connected to the input interface module, and is used to generate the heat margin weight corresponding to each hot node based on the current wheel end state parameters. The quadratic programming construction module, whose input terminals are connected to the input interface module, the capacity boundary calculation module, and the heat loss and heat margin calculation module, is used to construct a two-level quadratic programming problem with the regenerative braking torque of the hub motor to be allocated and the braking torque of the EMB to be allocated as decision variables. The two-level quadratic programming problem includes a first-level problem and a second-level problem. The first-level problem aims to minimize the unsatisfiable braking torque. The second-level problem constructs an objective function with multi-objective optimization within the feasible set corresponding to the minimum unsatisfiable braking torque determined by the first-level problem. The real-time solution module, whose input is connected to the quadratic programming construction module, is used to solve the two-level quadratic programming in each control cycle to obtain the optimal hub motor driving torque and the optimal EMB braking torque of the target wheel. The output interface module, whose input end is connected to the real-time solution module, is used to send the optimal hub motor driving torque and the optimal EMB braking torque to the hub motor controller and the EMB controller, respectively.

2. The composite braking control device integrating a hub motor and EMB according to claim 1, characterized in that, The current wheel end status parameters include the current wheel speed, hub motor temperature, EMB actuator motor temperature, brake disc temperature, allowable charging power of the power battery, state of charge of the power battery, and allowable charging current of the power battery.

3. The composite braking control device integrating a hub motor and EMB according to claim 2, characterized in that, The heat loss and heat margin calculation module constructs a heat generation power function for the hub motor side, a heat generation power function for the EMB execution motor side, and a heat generation power function for the brake disc side based on the current wheel speed and the temperature of each heat node, and generates a corresponding heat margin weight based on the difference between the current temperature of each heat node and the preset temperature upper limit.

4. The composite braking control device integrating a hub motor and EMB according to claim 3, characterized in that, The heat generation power function on the hub motor side is a convex quadratic function of the regenerative braking torque of the hub motor to be allocated; the heat generation power function on the EMB actuator motor side is a convex quadratic function of the braking torque of the EMB to be allocated; the heat generation power function on the brake disc side is positively correlated with the product of the current wheel speed and the braking torque of the EMB to be allocated.

5. The composite braking control device integrating a hub motor and EMB according to claim 3, characterized in that, The heat margin weight increases monotonically as the difference between the current temperature of the thermal node and the preset upper temperature limit decreases.

6. The composite braking control device integrating a hub motor and EMB according to claim 2, characterized in that, The multi-objective optimization includes constructing an objective function with at least two of the following as optimization objectives: net braking energy recovery, thermal load of each of the aforementioned hot nodes, friction and wear, and distribution changes between adjacent cycles.

7. The composite braking control device integrating a hub motor and EMB according to claim 6, characterized in that, The friction and wear are positively correlated with the product of the current wheel speed and the braking torque of the EMB to be allocated; the change in allocation between adjacent cycles is a quadratic function of the difference between the decision variable of the current cycle and the decision variable of the previous cycle.

8. The composite braking control device integrating a hub motor and EMB according to claim 6, characterized in that, The multi-objective optimization also includes battery stress, which is positively correlated with the square of the regenerative braking torque of the hub motor to be assigned, and the weight of battery stress increases when the state of charge of the power battery is higher than a preset threshold or the allowable charging power of the power battery is lower than a preset threshold.

9. The composite braking control device integrating a hub motor and EMB according to claim 2, characterized in that, The secondary problem also includes a constraint condition, which is a limit on the rate of change of braking torque between adjacent control cycles; when the braking urgency exceeds a preset threshold, the limit on the rate of change of braking torque is relaxed.

10. The composite braking control device integrating a hub motor and an EMB according to any one of claims 1 to 9, characterized in that, Also includes: The rollback allocation module is used to generate an executable allocation instruction according to the deterministic priority rule when the real-time solution module times out or an abnormal value occurs, and to report the unmet braking torque and abnormal status to the vehicle controller. The deterministic priority rule is as follows: the maximum regenerative braking torque currently allowed by the hub motor is used first, and any insufficient part is made up by the EMB.

11. The composite braking control device integrating a hub motor and an EMB according to any one of claims 1 to 9, characterized in that, The factors determining the upper limit of the available regenerative braking torque include at least two of the following: the external characteristic profile of the hub motor, the allowable charging power of the power battery, the allowable charging current of the power battery, the upper limit of the thermal constraint of the hub motor, and the availability coefficient of the hub motor; the factors determining the upper limit of the available braking torque of the EMB include at least two of the following: the upper limit of the mechanical capacity of the EMB, the upper limit of the thermal constraint of the EMB actuator motor, the upper limit of the thermal constraint of the brake disc, and the availability coefficient of the EMB.

12. A composite braking control method integrating a hub motor and an EMB, characterized in that, A composite braking control device integrating a hub motor and an EMB as described in any one of claims 1 to 11, comprising the following steps: S1. Receive the target braking torque allocated to the target wheel by the vehicle controller, and obtain the current wheel-end state parameters; S2. Based on the current wheel end state parameters, determine the upper limit of the available regenerative braking torque of the hub motor and the upper limit of the available braking torque of the EMB within the current control cycle. S3. Generate the thermal margin weights corresponding to each hot node based on the current wheel end state parameters; S4. Using the regenerative braking torque of the hub motor to be allocated and the braking torque of the EMB to be allocated as decision variables, construct a two-level quadratic programming problem. The two-level quadratic programming problem includes a first-level problem and a second-level problem. The first-level problem aims to minimize the unsatisfiable braking torque. The second-level problem constructs an objective function using multi-objective optimization within the feasible set corresponding to the minimum unsatisfiable braking torque determined by the first-level problem. S5. Solve the two-level quadratic programming in each control cycle to obtain the optimal hub motor driving torque and optimal EMB braking torque of the target wheel; S6. The optimal hub motor driving torque and the optimal EMB braking torque are sent to the hub motor controller and the EMB controller, respectively.

13. The composite braking control method integrating a hub motor and EMB according to claim 12, characterized in that, When solving a two-level quadratic programming problem, if the solution times out or a numerical anomaly occurs, an executable allocation instruction is generated according to the deterministic priority rule, and the unsatisfied braking torque and abnormal state are reported to the vehicle controller, instead of sending the optimal hub motor braking torque and the optimal EMB braking torque to the hub motor controller and the EMB controller. The deterministic priority rule is as follows: the maximum regenerative braking torque currently allowed by the hub motor is used first, and any insufficient part is made up by the EMB.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the composite braking control method integrating the hub motor and EMB as described in any one of claims 12 to 13.

Images