Electric drive multi-axle vehicle torque optimal distribution control method and system

Abstract

The invention discloses an electric drive multi-axle vehicle torque optimal distribution control method and system, and relates to the technical field of electric drive multi-axle vehicle energy consumption control, and the method comprises the steps: solving the optimal number of drive axles of an electric drive multi-axle vehicle and the drive torque of each drive axle through a first objective function; optimizing the maximum copper loss sequence within the safe temperature rise threshold of the motor by using a second objective function, and further obtaining the maximum torque which can be provided within the safe temperature rise threshold of the motor; according to the distribution strategy, the motor temperature rise rate can be delayed, the efficiency of the electric driving system can be improved, the number of driving shafts and torque distribution on all the driving shafts can be adjusted in real time when the temperature of a certain shaft motor is too high, the motor temperature rise is limited by dynamically adjusting the motor output torque, and therefore the motor temperature of all the shafts is balanced, the economical efficiency of the electric driving system is improved, and the cost is reduced. And the thermal fault probability of the motor is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of energy consumption control of electric-driven multi-axle vehicles, and in particular to a torque-optimized distribution control method and system for electric-driven multi-axle vehicles. Background Art

[0002] Electric multi-axle vehicles have the characteristics of high control flexibility, short transmission chain, compact structure, high transmission efficiency, high space layout utilization, etc. They have significant advantages in stability control, active safety control and energy-saving control, and are widely used in cargo transportation, construction transportation, field operations, national defense and military, etc. However, due to the characteristics of overdrive and multiple constraints of electric multi-axle vehicles, as well as their large mass and strong carrying capacity, there are still theoretical and technical challenges in the control of the driving economy of electric multi-axle vehicles.

[0003] An effective way to deal with the energy consumption problem of electric multi-axle vehicles is to control the number of drive axles and the working torque of each drive motor, so as to improve the efficiency of each drive motor and reduce the energy consumption of the entire vehicle's electric drive system.

[0004] At present, the torque distribution control strategies for electric drive multi-axle vehicles mainly include torque average distribution control strategy, torque optimal average distribution control strategy based on motor efficiency map, etc. Among them, the torque average distribution control strategy is to distribute the torque required by the vehicle at the current moment to each drive motor. This strategy is simple and easy to design, but the efficiency of the electric drive system is low and the energy consumption is high; the torque optimal average distribution control strategy based on the motor efficiency map is to take the total energy consumption of the electric drive system under different drive shaft numbers as the objective function, solve the corresponding number of drive shafts, and use it as the optimal drive mode, and then distribute the vehicle demand torque to each motor involved in the drive. This strategy can effectively improve the efficiency of the electric drive system, but in some working conditions where the vehicle demand torque is small, in order to improve the efficiency of the electric drive system, one or several drive motors are usually made to work continuously in a high-efficiency area close to the peak torque, and this control strategy is to evenly distribute the drive torque between the shafts, resulting in a high motor temperature rise, which cannot provide the maximum efficiency of the electric drive system and can only slightly reduce the energy consumption of the electric drive system. Summary of the invention

[0005] The purpose of the present invention is to provide a torque optimization distribution control method and system for an electric drive multi-axle vehicle in view of the above-mentioned deficiencies in the prior art, so as to solve the problems in the prior art.

[0006] The present invention specifically provides the following technical solutions: A torque optimization distribution control method for an electric drive multi-axle vehicle, comprising: The first objective function is constructed through the instantaneous total energy consumption of the electric drive system, and the instantaneous total energy consumption of the electric drive system is minimized with the maximum torque that the motor can provide as a constraint condition. The axle with an axle load ratio greater than a threshold is preferentially selected as the drive axle according to the vertical load of each axle of the electric drive multi-axle vehicle, and the optimal control variable of the first objective function at the current moment is obtained. The control variables of the first objective function include the number of drive axles of the electric drive multi-axle vehicle, the drive torque on each drive axle, and the drive speed; Obtain the difference between the motor stator winding temperature prediction sequence output in the prediction time domain and the stator winding reference temperature, and use the sum of the difference and the copper loss change rate in the prediction time domain as the second objective function, minimize the second objective function with the copper loss and the copper loss change rate as constraints, and obtain the optimal control variable sequence of the second objective function through the minimized second objective function, wherein the optimal control variable sequence of the second objective function includes the maximum copper loss sequence within the motor safety temperature rise threshold; According to the maximum copper loss sequence within the motor safety temperature rise threshold, the maximum current effective value sequence within the motor safety temperature rise threshold is obtained, and based on the optimal control variable of the first objective function and the maximum current effective value sequence, the maximum torque that each axis motor can provide within the motor temperature rise safety threshold is obtained according to the current-speed-torque three-dimensional table lookup.

[0007] Preferably, before constructing the first objective function through the instantaneous total energy consumption of the electric drive system, the instantaneous total energy consumption of the electric drive system is also corrected, including: The torque distribution correction factor is represented by the relationship between the motor speed, working torque, rated torque and peak torque. The specific expression is: ; in, is the torque distribution correction factor, is the motor working torque, is the rated torque of the motor at the current speed, is the peak torque at the current motor speed, is the motor speed, For the i A drive shaft, For the left motor, For the right motor; The working torque is corrected by a correction factor, and a corrected instantaneous total energy consumption of the electric drive system is obtained by the corrected torque.

[0008] Preferably, in constructing the first objective function through the instantaneous total energy consumption of the electric drive system, the specific expression of the first objective function is: ; in, is the first objective function,N is the number of drive shafts, is the total power of the corrected electric drive system, The first part of the dynamic model of each component of the power system Axis left or right motor power, is the maximum number of drive axes, For the Axis left or right motor angular velocity, For the Motor efficiency for left or right axis.

[0009] Preferably, in the process of minimizing the instantaneous total energy consumption of the electric drive system with the maximum torque that the motor can provide as a constraint condition, the specific expression for minimizing the instantaneous total energy consumption of the electric drive system is: ; in, is the slip rate; For the The vertical load on the shaft, i.e. the normal reaction force; It is the maximum torque that the motor can provide within the safe temperature rise threshold; is the energy source power; is the energy source current; is the energy source voltage; is the charge state of the energy source; the subscripts min and max represent the minimum and maximum values ​​of the corresponding variables, respectively.

[0010] Preferably, the step of preferentially selecting an axle having an axle load ratio greater than a threshold as a driving axle according to the vertical load of each axle of the electric drive multi-axle vehicle comprises: Obtain the axle load ratio of each axle of the electric drive multi-axle vehicle. The specific expression is: ; in, It is The axle load ratio of the shaft, i.e. The ratio of the normal reaction force on the axis to the gravity of the electric multi-axle vehicle; m is the mass of the electric multi-axle vehicle, and g is the acceleration due to gravity; The axle with an axle load ratio greater than a threshold is preferentially selected as the drive axle, and the drive torque is distributed to the motors on the drive axle in descending order of the axle load ratio.

[0011] Preferably, the step of obtaining the difference between the motor stator winding temperature prediction sequence output in the prediction time domain and the stator winding reference temperature, and taking the sum of the difference and the copper loss change rate in the prediction time domain as the second objective function, minimizing the second objective function with the copper loss and the copper loss change rate as constraints, and obtaining the optimal control variable sequence of the second objective function by minimizing the second objective function includes: The linear variable parameter model predictive control method is used, copper loss is used as the control quantity, and the stator effective winding temperature of each drive motor parameter is used as the control quantity. , end winding temperature , stator core temperature , rotor temperature , permanent magnet temperature As the state quantity and output quantity, the stator yoke iron loss , stator tooth iron loss , rotor iron loss , eddy current loss of permanent magnet , Ambient temperature , Coolant temperature in cooling pipe As the interference quantity, copper loss , the copper loss change rate is the constraint condition of the second objective function, and the state space equation that separates copper loss from other losses is constructed, which is specifically: Select is the state variable, is the interference amount, To control the variables, construct the state space equation, the specific expression is: ; Discretize the state space equation, the specific expression is: ; in, is the state matrix, is the interference matrix, is the input matrix; is the discretized state variable, is the discretized disturbance quantity, is the discretized control variable, is the discretized state matrix, is the discretized interference matrix, is the discretized input matrix; According to the motor insulation level, set the maximum insulation temperature of the motor stator winding as the stator winding reference temperature; The discretized state space equation is used to obtain the predicted temperature sequence of each drive motor stator winding output by controlling the copper loss in the prediction time domain, and the difference between the predicted temperature sequence of each drive motor stator winding and the stator winding reference temperature is obtained. The sum of the difference and the copper loss change rate in the prediction time domain is used as the optimization target of the second objective function. The specific expression is: ; in, is the second objective function, For the prediction time domain; To control the time domain; is the temperature series of the motor stator winding in the prediction time domain; is the set motor stator winding reference temperature; is the weight coefficient of the motor temperature rise cost, is the sequence of changes in motor copper loss in the control time domain, is the weight coefficient of the motor copper loss change rate, Indicated in Calculated at the moment Variables at the moment; The copper loss and copper loss change rate are used as constraints for the second objective function, including: ; The discretized state space equation is transformed into a matrix, the optimization target of the second objective function is converted into a standard quadratic programming problem, and a linear quadratic programming algorithm is used to minimize the optimization target of the second objective function to obtain the optimal control variable sequence of the second objective function in the prediction time domain, that is, the maximum copper loss sequence within the safe temperature rise threshold of the motor.

[0012] Preferably, according to the maximum copper loss sequence within the motor safety temperature rise threshold, the maximum current effective value sequence within the motor safety temperature rise threshold is obtained, and based on the optimal control variable of the first objective function and the maximum current effective value sequence, the maximum torque that can be provided by each axis motor within the motor temperature rise safety threshold is obtained according to the current-speed-torque three-dimensional table lookup, including: The maximum current effective value sequence within the motor safety temperature rise threshold is obtained by the maximum copper loss sequence within the motor safety temperature rise threshold. The specific expression is: ; in, is the number of phases of PMSM winding; Copper loss The corresponding maximum effective value of the winding phase current; is the effective resistance of each phase winding, and its resistance is related to the temperature characteristics of the material; The corresponding torque is obtained by looking up the current-speed-torque three-dimensional table. The specific expression is: ; in, For the The maximum torque that the left or right motor can provide within the safe threshold of stator winding temperature rise. For the left motor, For the right motor; For the Axis left or right motor current, For the Axis left or right motor speed.

[0013] The present invention provides a torque optimization distribution control method for an electric drive multi-axle vehicle, comprising: a torque optimization distribution module, for constructing a first objective function through the instantaneous total energy consumption of the electric drive system, minimizing the instantaneous total energy consumption of the electric drive system with the maximum torque that the motor can provide as a constraint, and preferentially selecting an axle with an axle load ratio greater than a threshold as a drive axle according to the vertical load of each axle of the electric drive multi-axle vehicle, and obtaining the optimal control variable of the first objective function at the current moment, wherein the control variables of the first objective function include the number of drive axles of the electric drive multi-axle vehicle, the drive torque on each drive axle, and the drive speed; A temperature rise limiting module is used to obtain the difference between the motor stator winding temperature prediction sequence output in the prediction time domain and the stator winding reference temperature, and take the sum of the difference and the copper loss change rate in the prediction time domain as the second objective function, and minimize the second objective function with the copper loss and the copper loss change rate as constraints, and obtain the optimal control variable sequence of the second objective function through the minimized second objective function, wherein the optimal control variable sequence of the second objective function includes the maximum copper loss sequence within the motor safety temperature rise threshold; The maximum torque distribution module is used to obtain the maximum current effective value sequence within the motor safety temperature rise threshold according to the maximum copper loss sequence within the motor safety temperature rise threshold, and based on the optimal control variable of the first objective function and the maximum current effective value sequence, obtain the maximum torque that each axis motor can provide within the motor temperature rise safety threshold according to the current-speed-torque three-dimensional table lookup.

[0014] Compared with the prior art, the present invention has the following significant advantages: The present invention constructs a first objective function through the instantaneous total energy consumption of the electric drive system, minimizes the first objective function through the maximum torque as a constraint condition, preliminarily limits the temperature rise of the motor by minimizing the instantaneous total energy consumption of the electric drive system, and preferentially selects the axle with an axle load ratio greater than a threshold as the drive shaft to achieve the optimal control variable of the first objective function, further limits the temperature rise of the motor by reasonably allocating the number of drive shafts and the drive shaft, and minimizes the second objective function through copper loss and copper loss change rate to obtain the maximum copper loss sequence within the motor safety temperature rise threshold and the maximum current effective value sequence within the motor safety temperature rise threshold, and finally obtains the maximum torque that can be provided by each shaft motor within the motor temperature rise safety threshold through current-speed-torque three-dimensional table lookup, and actively limits the maximum torque of the electric drive multi-axis vehicle motor through the solved maximum torque, thereby achieving the problem of limiting the temperature rise of the motor by limiting the maximum torque and reasonably allocating the number of drive shafts and the drive shaft, solving the temperature rise caused by the long-term operation of the motor, preventing the wheel-side motor from overheating, reducing the probability of motor thermal failure, and providing the maximum efficiency of the electric drive system. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a schematic diagram of the model structure; Figure 2 The present invention is a flow chart of a torque optimization distribution control method for an electric drive multi-axle vehicle. DETAILED DESCRIPTION

[0016] The following is a clear and complete description of the technical solutions of the embodiments of the present invention in conjunction with the drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0017] like Figure 1-2 As shown, the present invention provides a torque optimization distribution control method for an electric drive multi-axle vehicle, which specifically includes the following steps: Step S1: Acquire parameters of each driving motor in the electric drive multi-axle vehicle.

[0018] According to the parameters of the electric drive multi-axle vehicle, the longitudinal dynamics model of the electric drive multi-axle vehicle is established to obtain the vehicle speed. The specific expression is: ; in, is the reduction ratio of the main reducer; Is the transmission efficiency of the main reducer; is the number of drive shafts; For the A drive shaft; For the left motor, For the right motor; For the The output torque of the left or right drive motor of the shaft; is the wheel rolling radius; For braking force; is the air density; is the drag coefficient; The frontal area of ​​an electric multi-axle vehicle; is the vehicle speed; is the vehicle weight; is the gravity coefficient; is the road rolling resistance coefficient; is the road slope.

[0019] Then get the motor speed, the specific expression is: ; in, is the wheel rolling radius, The reduction ratio of the main reducer.

[0020] The dynamic models of each component of the power system are established to obtain the motor efficiency, energy source current, and state of charge (SOC). The specific expressions are: ; ; ; in, For the Axis left or right motor power; For the Axis left or right motor angular velocity; For the The efficiency of the motor on the left or right side of the shaft can be obtained by consulting the motor universal characteristic diagram; charging or discharging current for energy sources; is the open circuit voltage of the battery pack; Internal resistance for charging or discharging the battery pack; is the battery pack power, Initial energy source value, The maximum capacity of the energy source.

[0021] According to the motor parameters of the electric drive multi-axis vehicle, a lumped-parameter thermal network model LPTN (Lumped-parameter Thermal Network) is constructed considering the water cooling of the drive motor.

[0022] To improve real-time performance, the motor thermal nodes are simplified to five nodes: effective winding, end winding, stator core, rotor core, and permanent magnet. To improve the accuracy of motor temperature estimation, the motor cooling system is considered, and its cooling process is equivalent to two steps: (1) heat exchange between the coolant and the cooling pipe wall; (2) heat exchange between the cooling pipe wall and the external environment.

[0023] ; ; in, is the net heat flow rate; is the heat flow rate of the convection part at non-zero flow rate; is the thermal conductivity of the coolant in the tube; is the hydraulic diameter of the pipe; is the surface area of ​​the pipe wall, which is equal to the product of the pipe circumference and length; is the tube wall temperature, It is heat flow; is the convective heat transfer coefficient; is the surface area; and are the temperatures of two objects, which are represented here as the pipe wall temperature and the ambient temperature respectively.

[0024] Step S2: The number of drive shafts and the driving torque on each drive shaft are used as control variables of the first objective function. The first objective function is constructed through the corrected instantaneous total energy consumption of the electric drive system. The energy source power limit, the motor external characteristic limit, the adhesion limit, and the maximum torque limit that the motor can provide within the motor safety temperature rise threshold are used as constraints of the first objective function. Under the constraints of the first objective function, the optimization target of the first objective function (the instantaneous total energy consumption of the electric drive system) is minimized, and according to the vertical load of each axle of the electric drive multi-axle vehicle, the axle with an axle load ratio greater than the threshold is preferentially selected as the drive shaft to obtain the optimal control variables of the first objective function at the current moment. The control variables of the first objective function include the number of drive shafts, the driving torque on each drive shaft and the driving speed of the electric drive multi-axle vehicle.

[0025] Before constructing the first objective function through the instantaneous total energy consumption of the electric drive system, the instantaneous total energy consumption of the electric drive system is also corrected, including: ; in, is the torque distribution correction factor, is the motor working torque, is the rated torque of the motor at the current speed, is the peak torque at the current speed of the motor; is the motor speed, For the i A drive shaft, For the left motor, For the right motor.

[0026] The working torque is corrected by the correction factor, and the corrected instantaneous total energy consumption of the electric drive system is obtained by calculating the corrected torque.

[0027] The first objective function is constructed by the instantaneous total energy consumption of the electric drive system. The specific expression of the first objective function is: ; in, is the first objective function, N is the number of drive shafts, is the total power of the corrected electric drive system, The first part of the dynamic model of each component of the power system Axis left or right motor power, is the maximum number of drive axes, For the Axis left or right motor angular velocity, For the Motor efficiency for left or right axis.

[0028] Taking the maximum torque that the motor can provide as a constraint, the specific expression for minimizing the instantaneous total energy consumption of the electric drive system is: ; in, is the slip rate; For the The vertical load on the shaft, i.e. the normal reaction force; It is the maximum torque that the motor can provide within the safe temperature rise threshold; is the energy source power; is the energy source current; is the energy source voltage; is the charge state of the energy source; the subscripts min and max represent the minimum and maximum values ​​of the corresponding variables, respectively.

[0029] Among them, according to the vertical load of each axle of the electric drive multi-axle vehicle, the axle with an axle load ratio greater than a threshold is preferentially selected as the driving axle, including: Obtain the axle load ratio of each axle of the electric drive multi-axle vehicle. The specific expression is: ; in, It is The axle load ratio of the shaft, i.e. The ratio of the normal reaction force on the axis to the gravity of the electric multi-axle vehicle; m is the mass of the electric multi-axle vehicle, and g is the acceleration due to gravity.

[0030] The axle with an axle load ratio greater than a threshold is preferentially selected as the drive axle, and the drive torque is distributed to the motors on the drive axle in descending order of the axle load ratio.

[0031] Step S3: Using the linear variable parameter model predictive control (LPV-MPC) method, copper loss is used as the control quantity, the stator effective winding temperature, end winding temperature, stator core temperature, rotor temperature, and permanent magnet temperature of each drive motor parameter are used as state quantities and output quantities, and iron loss, permanent magnet eddy current loss, ambient temperature, and coolant temperature in the cooling pipe are used as interference quantities. The difference between the stator winding temperature prediction sequence of each drive motor output when controlling copper loss in the prediction time domain and the stator winding reference temperature is obtained, and the sum of the difference and the copper loss change rate in the prediction time domain is used as the optimization target of the second objective function. The copper loss and the copper loss change rate are used as constraints of the second objective function. Under the constraints of the second objective function, a linear quadratic programming algorithm is used to minimize the optimization target of the second objective function. The optimal control variable sequence of the second objective function in the prediction time domain is obtained by minimizing the second objective function. The optimal control variable sequence of the second objective function in the prediction time domain includes the maximum copper loss sequence within the motor safety temperature rise threshold.

[0032] The linear variable parameter model predictive control method is used, copper loss is used as the control quantity, and the stator effective winding temperature of each drive motor parameter is used as the control quantity. , end winding temperature , stator core temperature , rotor temperature , permanent magnet temperature As the state quantity and output quantity, the stator yoke iron loss , stator tooth iron loss , rotor iron loss , eddy current loss of permanent magnet , Ambient temperature , Coolant temperature in cooling pipe As the interference quantity, copper loss , the copper loss change rate is the constraint condition of the second objective function, and the state space equation that separates copper loss from other losses is constructed, which is specifically: Select is the state variable, is the interference amount, To control the variables, construct the state space equation, the specific expression is: ; Discretize the state space equation, the specific expression is: ; in, is the state matrix, is the interference matrix, is the input matrix; is the discretized state variable, is the discretized disturbance quantity, is the discretized control variable, is the discretized state matrix, is the discretized interference matrix, is the discretized input matrix.

[0033] In Model Predictive Control (MPC), discretization of the state space equations is necessary because MPC algorithms are usually implemented in discrete time. Here are the main reasons: Computer implementation: When a computer executes a control algorithm, it operates on discrete time steps. By discretizing a continuous-time system, numerical algorithms can be used to predict and optimize the future behavior of the system.

[0034] Prediction and optimization: The MPC algorithm needs to predict a series of future control inputs and the state of the system. This requires multi-step prediction at discrete time points to ensure the feasibility and efficiency of the calculation.

[0035] Real-time applications: In real-time applications, control system measurements and actuator actions are performed at discrete time points (such as sampling of sensor data and execution of control signals). Discretization enables MPC to calculate and apply new control inputs in each sampling period.

[0036] Through discretization, the continuous-time dynamic equations can be converted into discrete-time equations, which are more suitable for implementation in digital control systems, thereby ensuring the accuracy and real-time performance of the control algorithm.

[0037] According to the motor insulation level, set the maximum insulation temperature of the motor stator winding as the reference temperature.

[0038] The discretized state space equation is used to obtain the predicted temperature sequence of each drive motor stator winding output by controlling the copper loss in the prediction time domain, and the difference between the predicted temperature sequence of each drive motor stator winding and the reference temperature of the stator winding is obtained. The sum of the difference and the copper loss change rate in the prediction time domain is taken as the second objective function. The specific expression is: ; in, is the second objective function, For the prediction time domain; To control the time domain; is the temperature series of the motor stator winding in the prediction time domain; is the set motor stator winding reference temperature; is the weight coefficient of the motor temperature rise cost, is the sequence of changes in motor copper loss in the control time domain, is the weight coefficient of the motor copper loss change rate, Indicated in Calculated at the moment Variables at time.

[0039] Establish the constraints of copper loss and copper loss change rate as the second objective function, including: ; The discretized state space equation is transformed into a matrix, and then the optimization target of the second objective function is transformed into a form like The standard quadratic programming problem is solved by using a linear quadratic programming algorithm to minimize the optimization target of the second objective function, and obtain the optimal control variable sequence of the second objective function in the prediction time domain, that is, the maximum copper loss sequence within the motor safety temperature rise threshold. is the control variable increment, is the quadratic coefficient matrix, is the linear term coefficient vector.

[0040] Step S4: Based on the maximum copper loss sequence within the motor safety temperature rise threshold, the maximum current effective value sequence within the motor safety temperature rise threshold is obtained, and based on the optimal control variable of the first objective function and the maximum current effective value sequence, the maximum torque that each axis motor can provide within the motor temperature rise safety threshold is obtained according to the current-speed-torque three-dimensional table lookup.

[0041] The maximum current effective value sequence within the motor safety temperature rise threshold is obtained through the maximum copper loss sequence within the motor safety temperature rise threshold. The specific expression is: ; in, is the number of phases of PMSM winding; Copper loss The corresponding maximum effective value of the winding phase current; is the effective resistance of each phase winding, and its resistance is related to the temperature characteristics of the material.

[0042] The corresponding torque is obtained by looking up the current-speed-torque three-dimensional table. The specific expression is: ; in, For the The maximum torque that the left or right motor can provide within the safe threshold of stator winding temperature rise. For the left motor, For the right motor; For the Axis left or right motor current, For the Axis left or right motor speed.

[0043] The motor temperature estimation used in the torque distribution control strategy proposed in the present invention can estimate and control the motor temperature rise without arranging sensors. Based on the mechanical stability, temperature rise stability and operational reliability of the motor near the rated external characteristic curve, the motor operating point is limited near the motor external characteristic curve, thereby reducing the motor temperature rise, improving the motor working efficiency, and reducing the electric power of the vehicle electric drive system. It focuses on achieving the optimal economy of distributed multi-axle heavy-load electric drive multi-axle vehicles and the safety of electric drive multi-axle vehicles.

[0044] Based on the above method, the present invention provides a distributed electric drive multi-axle vehicle optimal torque distribution control system, including: a torque optimization distribution module, a temperature rise limiting module and a maximum torque distribution module.

[0045] Among them, the torque optimization allocation module is used to construct the first objective function through the instantaneous total energy consumption of the electric drive system, minimize the instantaneous total energy consumption of the electric drive system with the maximum torque that the motor can provide as the constraint condition, and preferentially select the axle with an axle load ratio greater than the threshold as the drive axle according to the vertical load of each axle of the electric drive multi-axle vehicle, and obtain the optimal control variable of the first objective function at the current moment. The control variables of the first objective function include the number of drive axles of the electric drive multi-axle vehicle, the drive torque on each drive axle, and the drive speed; the temperature rise limitation module is used to obtain the difference between the motor stator winding temperature prediction sequence output in the prediction time domain and the stator winding reference temperature, and compare the difference with the copper loss variable in the prediction time domain. The sum of the conversion rates is used as the second objective function, and the copper loss and the copper loss change rate are used as constraints to minimize the second objective function. The optimal control variable sequence of the second objective function is obtained by minimizing the second objective function. The optimal control variable sequence of the second objective function includes the maximum copper loss sequence within the motor safety temperature rise threshold. The maximum torque allocation module is used to obtain the maximum current effective value sequence within the motor safety temperature rise threshold according to the maximum copper loss sequence within the motor safety temperature rise threshold, and based on the optimal control variables and the maximum current effective value sequence of the first objective function, the maximum torque that each axis motor can provide within the motor temperature rise safety threshold is obtained according to the current-speed-torque three-dimensional table lookup.

[0046] Among them, Figure 1 As shown in the model structure, the electric drive multi-axle vehicle obtains the motor speed and the required torque of the whole vehicle through the calculation model through the acceleration / brake pedal opening, and inputs the required torque of the whole vehicle into the torque optimization distribution module based on the instantaneous energy consumption optimization taking into account the motor torque distribution correction factor, so as to obtain the individual axle drive torque command, which is sent to the motor controller through CAN communication, otherwise the individual drive motor torque is sent to the motor thermal management module, and the motor speed is sent to the motor thermal management module, and the temperature and loss of each node are sent to the motor temperature rise limitation module based on the linear variable parameter model predictive control (LPV-MPC (Line-ar parameter variable and model predictive control)) through the motor thermal management module, and the maximum torque that the motor can provide within the safety temperature rise threshold is sent to the torque optimization distribution module, and then sent to the motor controller again to achieve control.

[0047] According to the disclosed embodiments, the embedded vehicle controller can communicate with one or more external devices (e.g., sensors, motor controllers, battery management systems), or with any device (e.g., Ethernet, CAN bus, etc.) that enables the controller to communicate with one or more other controllers or devices.

[0048] The above content is a further detailed description of the present invention in combination with a specific preferred embodiment. For technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as belonging to the protection scope of the present invention.

Claims

1. A torque optimization distribution control method for an electric drive multi-axle vehicle, characterized in that: include: The first objective function is constructed through the instantaneous total energy consumption of the electric drive system, and the instantaneous total energy consumption of the electric drive system is minimized with the maximum torque that the motor can provide as a constraint condition. The axle with an axle load ratio greater than a threshold is preferentially selected as the drive axle according to the vertical load of each axle of the electric drive multi-axle vehicle, and the optimal control variable of the first objective function at the current moment is obtained. The control variables of the first objective function include the number of drive axles of the electric drive multi-axle vehicle, the drive torque on each drive axle, and the drive speed; Obtain the difference between the motor stator winding temperature prediction sequence output in the prediction time domain and the stator winding reference temperature, and use the sum of the difference and the copper loss change rate in the prediction time domain as the second objective function, minimize the second objective function with the copper loss and the copper loss change rate as constraints, and obtain the optimal control variable sequence of the second objective function through the minimized second objective function, wherein the optimal control variable sequence of the second objective function includes the maximum copper loss sequence within the motor safety temperature rise threshold; According to the maximum copper loss sequence within the motor safety temperature rise threshold, the maximum current effective value sequence within the motor safety temperature rise threshold is obtained, and based on the optimal control variable of the first objective function and the maximum current effective value sequence, the maximum torque that each axis motor can provide within the motor temperature rise safety threshold is obtained according to the current-speed-torque three-dimensional table lookup.

2. The method for optimizing torque distribution control of an electric drive multi-axle vehicle according to claim 1, characterized in that: Before constructing the first objective function through the instantaneous total energy consumption of the electric drive system, the instantaneous total energy consumption of the electric drive system is corrected, including: The torque distribution correction factor is represented by the relationship between the motor speed, working torque, rated torque and peak torque. The specific expression is: ； in, is the torque distribution correction factor, is the motor working torque, is the rated torque of the motor at the current speed, is the peak torque at the current motor speed, is the motor speed, For the i A drive shaft, For the left motor, For the right motor; The working torque is corrected by a correction factor, and a corrected instantaneous total energy consumption of the electric drive system is obtained by the corrected torque.

3. The method for optimizing torque distribution control of an electric multi-axle vehicle according to claim 2, characterized in that: In the construction of the first objective function by the instantaneous total energy consumption of the electric drive system, the specific expression of the first objective function is: ； in, is the first objective function, N is the number of drive shafts, is the total power of the corrected electric drive system, The first part of the dynamic model of each component of the power system Axis left or right motor power, is the maximum number of drive axes, For the Axis left or right motor angular velocity, For the Motor efficiency for left or right axis.

4. The method for optimizing torque distribution control of an electric multi-axle vehicle according to claim 3, characterized in that: In the above-mentioned process of minimizing the instantaneous total energy consumption of the electric drive system with the maximum torque that the motor can provide as a constraint condition, the specific expression for minimizing the instantaneous total energy consumption of the electric drive system is: ； in, is the slip rate; For the The vertical load on the shaft, i.e. the normal reaction force; It is the maximum torque that the motor can provide within the safe temperature rise threshold; is the energy source power; is the energy source current; is the energy source voltage; is the charge state of the energy source; the subscripts min and max represent the minimum and maximum values ​​of the corresponding variables, respectively.

5. The method for optimizing torque distribution control of an electric multi-axle vehicle according to claim 4, characterized in that: The method of preferentially selecting an axle having an axle load ratio greater than a threshold as a driving axle according to the vertical load of each axle of the electric drive multi-axle vehicle comprises: Obtain the axle load ratio of each axle of the electric drive multi-axle vehicle. The specific expression is: ； in, It is The axle load ratio of the shaft, i.e. The ratio of the normal reaction force on the axis to the gravity of the electric multi-axle vehicle; m is the mass of the electric multi-axle vehicle, and g is the acceleration due to gravity; The axle with an axle load ratio greater than a threshold is preferentially selected as the drive axle, and the drive torque is distributed to the motors on the drive axle in descending order of the axle load ratio.

6. The method for optimizing torque distribution control of an electric multi-axle vehicle according to claim 1, characterized in that: The method comprises obtaining a difference between a motor stator winding temperature prediction sequence output in a prediction time domain and a stator winding reference temperature, and taking the sum of the difference and the copper loss change rate in the prediction time domain as a second objective function, minimizing the second objective function with the copper loss and the copper loss change rate as constraints, and obtaining an optimal control variable sequence of the second objective function through the minimized second objective function, including: The linear variable parameter model predictive control method is used, copper loss is used as the control quantity, and the stator effective winding temperature of each drive motor parameter is used as the control quantity. , end winding temperature , stator core temperature , rotor temperature , permanent magnet temperature As the state quantity and output quantity, the stator yoke iron loss , stator tooth iron loss , rotor iron loss , eddy current loss of permanent magnet , Ambient temperature , Coolant temperature in cooling pipe As the interference quantity, copper loss , the copper loss change rate is the constraint condition of the second objective function, and the state space equation that separates copper loss from other losses is constructed, which is specifically: Select is the state variable, is the interference amount, To control the variables, construct the state space equation, the specific expression is: ； Discretize the state space equation, the specific expression is: ； in, is the state matrix, is the interference matrix, is the input matrix; is the discretized state variable, is the discretized disturbance quantity, is the discretized control variable, is the discretized state matrix, is the discretized interference matrix, is the discretized input matrix; According to the motor insulation level, set the maximum insulation temperature of the motor stator winding as the stator winding reference temperature; The discretized state space equation is used to obtain the predicted temperature sequence of each drive motor stator winding output by controlling the copper loss in the prediction time domain, and the difference between the predicted temperature sequence of each drive motor stator winding and the stator winding reference temperature is obtained. The sum of the difference and the copper loss change rate in the prediction time domain is used as the second objective function. The specific expression is: ； in, is the second objective function, For the prediction time domain; To control the time domain; is the temperature series of the motor stator winding in the prediction time domain; is the set motor stator winding reference temperature; is the weight coefficient of the motor temperature rise cost, is the sequence of changes in motor copper loss in the control time domain, is the weight coefficient of the motor copper loss change rate, Indicated in Calculated at the moment Variables at the moment; The copper loss and copper loss change rate are used as constraints for the second objective function, including: ； The discretized state space equation is transformed into a matrix, the optimization target of the second objective function is converted into a standard quadratic programming problem, and a linear quadratic programming algorithm is used to minimize the optimization target of the second objective function to obtain the optimal control variable sequence of the second objective function in the prediction time domain, that is, the maximum copper loss sequence within the safe temperature rise threshold of the motor.

7. The method for optimizing torque distribution control of an electric multi-axle vehicle according to claim 6, characterized in that: According to the maximum copper loss sequence within the motor safety temperature rise threshold, the maximum current effective value sequence within the motor safety temperature rise threshold is obtained, and based on the optimal control variable of the first objective function and the maximum current effective value sequence, the maximum torque that each axis motor can provide within the motor temperature rise safety threshold is obtained according to the current-speed-torque three-dimensional table lookup, including: The maximum current effective value sequence within the motor safety temperature rise threshold is obtained by the maximum copper loss sequence within the motor safety temperature rise threshold. The specific expression is: ； in, is the number of phases of PMSM winding; Copper loss The corresponding maximum effective value of the winding phase current; is the effective resistance of each phase winding, and its resistance is related to the temperature characteristics of the material; The corresponding torque is obtained by looking up the current-speed-torque three-dimensional table. The specific expression is: ； in, For the The maximum torque that the left or right motor can provide within the safe threshold of stator winding temperature rise. For the left motor, For the right motor; For the Axis left or right motor current, For the Axis left or right motor speed.

8. A torque optimization distribution control system for an electric drive multi-axle vehicle, characterized in that: include: a torque optimization distribution module, for constructing a first objective function through the instantaneous total energy consumption of the electric drive system, minimizing the instantaneous total energy consumption of the electric drive system with the maximum torque that the motor can provide as a constraint, and preferentially selecting an axle with an axle load ratio greater than a threshold as a drive axle according to the vertical load of each axle of the electric drive multi-axle vehicle, and obtaining the optimal control variable of the first objective function at the current moment, wherein the control variables of the first objective function include the number of drive axles of the electric drive multi-axle vehicle, the drive torque on each drive axle, and the drive speed; A temperature rise limiting module is used to obtain the difference between the motor stator winding temperature prediction sequence output in the prediction time domain and the stator winding reference temperature, and take the sum of the difference and the copper loss change rate in the prediction time domain as the second objective function, and minimize the second objective function with the copper loss and the copper loss change rate as constraints, and obtain the optimal control variable sequence of the second objective function through the minimized second objective function, wherein the optimal control variable sequence of the second objective function includes the maximum copper loss sequence within the motor safety temperature rise threshold; The maximum torque distribution module is used to obtain the maximum current effective value sequence within the motor safety temperature rise threshold according to the maximum copper loss sequence within the motor safety temperature rise threshold, and based on the optimal control variable of the first objective function and the maximum current effective value sequence, obtain the maximum torque that each axis motor can provide within the motor temperature rise safety threshold according to the current-speed-torque three-dimensional table lookup.

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