Differential dynamic programming-based torque distribution energy-saving control method for dual-motor-driven electric vehicle

Abstract

The invention discloses a torque distribution energy-saving control method for a dual-motor-driven electric vehicle based on differential dynamic programming, and belongs to the field of electric vehicle driving control. According to the method, a vehicle longitudinal dynamics model and a motor energy consumption model are established, a differential dynamic programming algorithm is utilized, torque distribution of the double-motor-driven electric vehicle under different working conditions is optimized, and therefore the purposes of minimizing energy consumption and improving the overall system efficiency are achieved. Specifically, the vehicle longitudinal dynamics model is used for describing the total driving force needed by the vehicle in the driving process, and the motor energy consumption model is used for calculating the efficiency and energy consumption of the front axle motor and the rear axle motor based on a motor efficiency MAP. On the basis, the differential dynamic programming algorithm dynamically adjusts the motor torque distribution coefficient to balance the dynamic property and economical efficiency of the vehicle, so that a real-time and efficient control strategy is achieved, and the energy-saving requirement of the vehicle under the complex working condition is met. According to the method, the energy consumption of the dual-motor-driven electric vehicle is effectively reduced.

Description

Technical Field

[0003] The present invention belongs to the field of electric vehicle motor drive control, and in particular relates to a torque distribution energy-saving control method for a dual-motor driven electric vehicle based on differential dynamic programming. Background Art

[0005] As a new type of powertrain structure, all-wheel drive electric vehicles can install drive motors on the front and rear drive shafts of electric vehicles, or install power wheels such as wheel hubs or wheel-side motors on the wheels to drive the vehicle. As a unique power system, this structure can achieve flexible torque distribution, improve power, economy and stability of electric vehicles.

[0006] Torque distribution can be defined as the process involving torque distribution in order to bring about an improvement in vehicle efficiency. Torque distribution can improve economy and safety in electric vehicles. When considering vehicle safety, torque distribution can be used to improve the economy of electric vehicles, especially to improve the economy of four-wheel electric vehicles by reducing energy losses.

[0007] In the torque distribution problem of electric vehicles, economy is often ignored. Therefore, improving the economy of the vehicle is the focus of research to achieve energy saving improvement. In the research of all-wheel drive electric vehicle powertrain control, the focus is on establishing motor loss model and wheel adhesion optimization model, designing a multi-layer controller structure, the upper layer decides the target torque, and the lower layer controls the motor. In the target torque distribution decision process, most of them rely on the motor torque distribution method based on the change of tire dynamic load. In the torque distribution decision process, a local optimization algorithm is used to control the strategy.

[0008] Although local optimal solutions can be obtained, local optimization requires specific limiting conditions and cannot obtain the optimal energy efficiency of the electric drive system of electric vehicles in the entire driving cycle, resulting in a lack of globality under a known driving cycle. In actual all-wheel drive systems, due to manufacturing processes and other reasons, the characteristic parameters of multiple motors often have certain differences, which provides a thorny problem for torque distribution optimization.

[0009] In terms of torque distribution control, most electric vehicles at home and abroad use dynamic programming to study the motor torque distribution problem during the research and development process. Dynamic programming has accumulated a lot of results in the practical application of these problems, but its shortcomings are also very obvious. Its backward algorithm in time generates a huge amount of calculation, which makes the algorithm only suitable for the optimal control problem of small-scale and simple nonlinear systems. However, differential dynamic programming overcomes these shortcomings. Differential dynamic programming is an iterative algorithm derived from the basic recursive formula by locally expanding the optimal cost function to the second-order terms. Differential dynamic programming avoids the problems of dimensionality disaster and low computational efficiency through local linearization and quadratic approximation, and can handle continuous states and control variables. This makes it more efficient than classical dynamic programming in high-dimensional and nonlinear control problems.

[0010] In view of this, studying a torque distribution energy-saving control method for dual-motor driven electric vehicles based on differential dynamic programming is a technical problem that needs to be solved urgently by technicians in this technical field. Summary of the invention

[0012] In view of the problems existing in the background technology, the present invention provides an energy-saving control method for torque distribution of a dual-motor driven electric vehicle based on differential dynamic programming. Its purpose is to optimize the torque distribution energy consumption of the dual-axis motor of an all-wheel drive electric vehicle under complex working conditions by adopting a differential dynamic programming method to optimize the working point of the dual-axis motor and the distribution of the dual-axis motor driving torque, thereby ensuring the optimal efficiency of the working point of the dual-axis motor of the electric vehicle under multiple working conditions, and making the efficiency output of the dual-axis motor power system of the electric vehicle under different working conditions the optimal control law, thereby solving the contradiction between the power and efficiency of the electric vehicle and improving the power performance and efficiency of the dual-motor system of the electric vehicle.

[0013] The technical solution for implementing the present invention is as follows:

[0014] A torque distribution energy-saving control method for a dual-motor driven electric vehicle based on differential dynamic programming, the method comprising the following steps:

[0015] Step 1: Establishment of vehicle longitudinal dynamics model;

[0016] Step 2: Establishment of the energy consumption model of the shaft drive motor, including energy consumption calculation based on the motor efficiency MAP diagram;

[0017] Step 3: Based on the optimization algorithm of differential dynamic programming, the dynamic adjustment of motor torque distribution is realized, and the control strategy under different working conditions is designed based on the optimization results.

[0018] The specific method of step one is as follows:

[0019] The total driving force required for a four-wheel electric vehicle to travel on a slope can be derived from the following formula:

[0020]

[0021]

[0022]

[0023]

[0024]

[0025] In the formula, is the overall driving force, is the acceleration resistance, is the slope resistance, is the rolling resistance, is the aerodynamic drag, is the mass of the four-wheel electric vehicle, is the vehicle's acceleration, is the road slope. is the rolling resistance coefficient, is the aerodynamic drag coefficient, is the air density, Indicates the front area of ​​the four-wheel electric vehicle, is the vehicle speed.

[0026] The specific method of step 2 is as follows:

[0027] The power required for a four-wheel electric vehicle to travel can be calculated by the following formula:

[0028]

[0029] The total power required by the power system is:

[0030]

[0031] In the formula, is the total power consumption, The power required for the vehicle to travel, is the motor power loss.

[0032] The shaft drive motor efficiency can be calculated using the following formula:

[0033]

[0034] In the formula , are the output power and input power of the shaft drive motor respectively, where , .

[0035] By formula It can be seen that the energy consumption of the axle motor drive system in the case of four-wheel electric vehicle driving can be expressed by the following formula:

[0036]

[0037] In the formula , Represent the front axle motor energy consumption and the rear axle motor energy consumption respectively, , Represent the front and rear axle motor torques respectively, , Respectively represent the front and rear axle motor speeds, , Respectively represent the front and rear axle motor efficiency. The motor efficiency can be obtained from the current motor torque and speed through the motor efficiency MAP diagram.

[0038] The specific method of step three is as follows:

[0039] In the torque distribution process of dual-motor driven electric vehicles, the goal is to achieve a balance between power and economy by minimizing system energy consumption. Considering the driving requirements of electric vehicles under various working conditions, the optimization objective function can be defined as:

[0040]

[0041] in, and Represent the energy consumption of the front and rear axle motors respectively, It represents the vehicle driving demand torque and minimizes the energy consumption of the entire driving cycle in a discrete summation manner.

[0042] The optimization problem of torque distribution is solved by differential dynamic programming (DDP). The optimal control law output by the DDP algorithm in each iteration is used to determine the optimal torque distribution of the front and rear axle motors. By distributing the current power demand of the vehicle to the front and rear axle motors, and combining the motor efficiency MAP diagram, the torque output of the front and rear axles is dynamically adjusted to ensure that the energy consumption of the system is minimized. The convergence of the DDP algorithm is controlled by the change amplitude of the objective function. If the change amplitude of the objective function is less than the preset threshold in several consecutive iterations, the iteration is stopped and the current control law is determined to be the final optimal control strategy. At the same time, in order to ensure real-time performance, the maximum number of iterations can be set in actual applications to avoid calculation delays caused by convergence speed issues.

[0043] The beneficial effects of the present invention are:

[0044] (1) High efficiency and energy saving: Through global energy consumption optimization, the energy consumption of dual-motor driven electric vehicles can be effectively reduced and the efficiency of the overall system can be improved.

[0045] (2) Real-time control: Due to the local quadratic approximation method of differential dynamic programming, the amount of calculation can be effectively reduced, meeting real-time requirements, and is suitable for online control of vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 Flowchart of energy-saving control method for torque distribution of dual-motor driven electric vehicles based on differential dynamic programming;

[0048] Figure 2 Schematic diagram of the vehicle longitudinal dynamics model;

[0049] Figure 3 Differential dynamic programming optimization algorithm flow chart; DETAILED DESCRIPTION

[0051] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings.

[0052] The present invention provides a torque distribution energy-saving control method for a dual-motor driven electric vehicle based on differential dynamic programming, such as Figure 1 The detailed implementation process of the method of the present invention is as follows:

[0053] Step 1: Establishment of vehicle longitudinal dynamics model.

[0054] In order to realize the torque distribution control of electric vehicles, it is necessary to first establish a dynamic model of the electric vehicle to describe the power demand of the vehicle and the basis of torque distribution.

[0055] The first is the calculation of the total driving force of the vehicle, such as Figure 2 As shown in Figure 2, the total driving force required by four-wheel electric vehicles under different road conditions It can be expressed as:

[0056]

[0057] in, represents the acceleration resistance, represents the slope resistance, represents rolling resistance, Represents aerodynamic resistance. Specifically, the calculation formulas for each resistance are as follows:

[0058] Acceleration resistance:

[0059]

[0060] in is the total mass of the electric vehicle, is the acceleration of the vehicle.

[0061] Slope resistance:

[0062]

[0063] in is the acceleration due to gravity, is the slope angle.

[0064] Rolling resistance:

[0065]

[0066] in is the rolling resistance coefficient.

[0067] Air resistance:

[0068]

[0069] in is the air density, is the front projection area of ​​the vehicle body, is the air resistance coefficient, is the vehicle speed.

[0070] Step 2: Establish the motor energy consumption model.

[0071] In order to optimize the torque distribution, it is necessary to establish the energy consumption model of the motor. Through the energy consumption calculation method based on the motor efficiency MAP diagram, the motor efficiency can be obtained by looking up the table under known torque and speed. The specific steps are as follows:

[0072] First, the power required for a four-wheel electric vehicle to travel can be calculated by the following formula:

[0073]

[0074] The total power required by the power system is:

[0075]

[0076] In the formula, is the total power consumption, The power required for the vehicle to travel, is the motor power loss.

[0077] The shaft drive motor efficiency can be calculated using the following formula:

[0078]

[0079] In the formula , are the output power and input power of the shaft drive motor respectively, where , .

[0080] Then calculate the energy consumption of the front and rear axle motors. Assume that the front and rear axle motors are the front axle motor (f) and the rear axle motor (r), and their output powers are and , then the input power is:

[0081]

[0082]

[0083] in, and They are the efficiencies of the front and rear axle motors respectively, which are obtained by querying the current motor torque and speed according to the motor efficiency MAP diagram.

[0084] Finally, the energy consumption is calculated according to the formula And the known front and rear axle motor torque , and speed , In the case of , the energy consumption of the axle motor drive system in the case of four-wheel electric vehicle driving can be expressed by the following formula:

[0085]

[0086] In the formula , Represent the front axle motor energy consumption and the rear axle motor energy consumption respectively, , Represent the front and rear axle motor torques respectively, , Respectively represent the front and rear axle motor speeds, , Represent the efficiency of the front and rear axle motors respectively. By calculating the energy consumption of the front and rear axle motors, the objective function of the total energy consumption can be established to provide a basis for subsequent optimization.

[0087] Step 3: Optimization algorithm based on differential dynamic programming.

[0088] First, define the state variables and control variables. In order to achieve the optimal torque distribution under different driving requirements, the vehicle state variables are defined as , i.e., vehicle speed and acceleration; the control variables are , which is the driving torque distribution coefficient of the front and rear axle motors. In the torque distribution process of dual-motor driven electric vehicles, the goal is to achieve a balance between power and economy by minimizing system energy consumption. Considering the driving requirements of electric vehicles under various working conditions, the optimization objective function can be defined as:

[0089]

[0090] Then the differential dynamic programming iteration step is performed. First, the initial state of the vehicle and the initial control input are set, and the initial trajectory is forward calculated. .

[0091] make , calculate the gradient and Hessian matrix of the cost function and the objective function. For each time step k, the cost function The first-order and second-order derivative matrices of are defined as follows:

[0092]

[0093]

[0094] Let the system dynamics be , then the influence of state and control on the next state can be described by the following derivative matrix:

[0095]

[0096]

[0097] make In the nominal trajectory Perform a second-order Taylor expansion at After the second-order Taylor expansion, we can get

[0098]

[0099] in

[0100]

[0101] Find Minimum optimal incremental control input :

[0102]

[0103] Define the coefficients of the two control increments: the open loop term , and a feedback gain term , the optimal Substitute into From the expansion of

[0104]

[0105] In fact, here is the coefficient of 1, yes The coefficient of yes The coefficient of . Through reverse iteration, we can get , , , Calculated , . Then the control sequence is updated in the forward iteration:

[0106]

[0107] Finally, determine whether it converges. If it converges, the optimal control sequence is obtained. If it does not converge, return to the beginning and continue the cycle until it converges or reaches the maximum number of iterations.

[0108] The above is a detailed introduction to the energy-saving control method for torque distribution of a dual-motor driven electric vehicle based on differential dynamic programming proposed by the present invention.

Claims

1. A torque distribution energy-saving control method for a dual-motor driven electric vehicle based on differential dynamic programming, characterized in that: The motor control method comprises the following steps: Step 1: Establishment of vehicle longitudinal dynamics model; Step 2: Establishment of the energy consumption model of the shaft drive motor; Step 3: Optimization algorithm based on differential dynamic programming.

2. The method for energy-saving control of torque distribution of a dual-motor driven electric vehicle based on differential dynamic programming according to claim 1, characterized in that: In the step 1, the vehicle longitudinal dynamics model includes calculating acceleration resistance, slope resistance, rolling resistance and aerodynamic resistance as well as the total driving force of the vehicle.

3. The torque distribution energy-saving control method for a dual-motor driven electric vehicle based on differential dynamic programming according to claim 1 is characterized in that: In the step 2, the shaft drive motor energy consumption model calculates the torque and speed of the front and rear shaft motors, obtains the motor efficiency from the motor efficiency MAP diagram, and calculates the energy consumption based on the torque and speed.

4. The torque distribution energy-saving control method for a dual-motor driven electric vehicle based on differential dynamic programming according to claim 1 is characterized in that: In step 3, the optimization process of the motor torque distribution by the differential dynamic programming algorithm includes: (1) defining state variables and control variables, where the state variables include vehicle speed and acceleration, and the control variables include the driving torque distribution coefficient of the front and rear axle motors; (2) Based on the vehicle driving requirements, define the optimization objective function to minimize the energy consumption of the front and rear axle motors; (3) In each iteration, the optimal torque distribution strategy is obtained by calculating and updating the control input.

5. The torque distribution energy-saving control method for a dual-motor driven electric vehicle based on differential dynamic programming according to claim 4 is characterized in that: In step three, each iteration includes the steps of forward calculation trajectory, reverse iteration update control sequence and judgment on convergence.

6. The energy-saving control method for torque distribution of a dual-motor driven electric vehicle based on differential dynamic programming according to claim 5 is characterized in that: In step three, the forward trajectory calculation includes setting the initial state of the vehicle and the initial control input to obtain the initial trajectory, and dynamically adjusting the control input during the iteration process.

7. The torque distribution energy-saving control method for a dual-motor driven electric vehicle based on differential dynamic programming according to claim 6 is characterized in that: In the step three, if the change amplitude of the objective function is less than a preset threshold value in a number of consecutive iterations, the iteration is stopped and the current control law is determined to be the final optimal control strategy.

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