A control method and device for a dual-motor drive system

Abstract

The present invention discloses a control method and device for a dual-motor drive system. The method includes: based on the vehicle speed information corresponding to the target vehicle at the current moment, performing prediction processing using a vehicle speed prediction model, and outputting a predicted vehicle speed sequence corresponding to the next prediction time period adjacent to the current moment; according to the predicted vehicle speed sequence, optimizing the motor energy consumption of the dual-motor drive system of the target vehicle in the prediction time period, and outputting a working mode sequence corresponding to the dual-motor drive system in the prediction time period; based on the motor control parameters corresponding to the first working mode in the working mode sequence, controlling the dual-motor drive system to perform a driving operation at the first prediction moment. Thus, the double-layer optimization algorithm proposed in this embodiment reduces the total motor energy consumption of the dual-motor drive system by optimizing the working mode, motor power, and brake action frequency of the motor drive system, and further solves the energy management problem of the multi-mode coupled drive system of electric vehicles.

Description

Technical Field

[0001] The present invention belongs to the technical field of motor control, and particularly relates to a control method and device for a dual-motor drive system. Background Art

[0002] With the continuous deepening of the concept of sustainable development, new energy vehicles have become the future development trend of the automotive industry. As a type of new energy vehicle with the highest sales volume, the related technologies of pure electric vehicles are developing rapidly. Although the progress of battery technology has significantly extended the driving range of electric vehicles, the currently widely used single-motor - reducer drive system has problems such as low comprehensive efficiency and high motor power demand. The dual-motor coupled drive system can reduce the energy consumption of the drive system through the coupled drive of two motors and the single-motor drive mode;

[0003] Regarding the energy management problem of the dual-motor coupled drive system of pure electric vehicles, the existing control methods can be divided into rule-based energy management strategies, dynamic programming-based energy management strategies, and minimum principle-based energy management strategies. However, the existing control methods have many defects. For example, most of the rule-based energy management strategies are obtained through offline optimization, unable to consider real-time road conditions information, with relatively high comprehensive energy consumption, and unable to take into account the dynamic performance of the drive system during mode switching. The energy management problem of the dual-motor coupled drive system involves many variables, and the dynamic programming-based energy management strategy has low computational efficiency when optimizing this problem. The energy management problem of the dual-motor coupled drive system is usually a mixed-integer optimization problem, and the commonly used processing methods of the minimum principle-based energy management strategy include polynomial fitting of the motor. Since this method has poor fitting accuracy for the motor, the minimum principle-based energy management strategy is difficult to handle the mixed-integer optimization problem.

[0004] Therefore, the present invention urgently needs to provide an optimization management strategy that can take into account the dynamic performance during mode switching of the dual-motor drive system, the action frequency of the mode switching actuator, and the motor energy consumption, so as to solve the energy management problem of the dual-motor multi-mode coupled drive system of pure electric vehicles. Summary of the Invention

[0005] In view of the above problems existing in the prior art, an embodiment of the present invention provides a control method and device for a dual-motor drive system; when solving the energy management problem of the dual-motor drive system of pure electric vehicles, this method can not only reduce the comprehensive energy consumption of the dual-motor drive system, but also improve the computational efficiency during the entire energy management process.

[0006] According to the first aspect of the embodiments of the present invention, a control method for a dual-motor drive system is provided. The method includes: based on the vehicle speed information corresponding to the target vehicle at the current moment, performing prediction processing using a vehicle speed prediction model, and outputting a predicted vehicle speed sequence corresponding to the next prediction time period adjacent to the current moment; wherein, the predicted vehicle speed sequence includes a plurality of predicted vehicle speed information arranged in chronological order; each of the predicted vehicle speed information includes a predicted speed and a corresponding predicted acceleration; according to the predicted vehicle speed sequence, optimizing the motor energy consumption of the dual-motor drive system of the target vehicle during the prediction time period, and outputting a working mode sequence corresponding to the dual-motor drive system during the prediction time period; wherein, the working mode sequence is a set formed by arranging the working modes corresponding to each prediction moment during the prediction time period in chronological order; obtaining the motor control parameters corresponding to the first working mode in the working mode sequence; and controlling the dual-motor drive system to perform a driving operation based on the motor control parameters at the first prediction moment adjacent to the current moment.

[0007] Optionally, the step of optimizing the motor energy consumption of the dual-motor drive system of the target vehicle during the prediction time period according to the predicted vehicle speed sequence and outputting the working mode sequence corresponding to the dual-motor drive system during the prediction time period includes: constructing a drive load model, a motor model corresponding to the dual-motor drive system, and a drive system model corresponding to the dual-motor drive system under different working modes; for any predicted vehicle speed information in the predicted vehicle speed sequence: based on the drive load model, the motor model, and the drive system model corresponding to different working modes, determining the optimal power distribution results corresponding to the dual-motor drive system of the predicted vehicle speed information under different working modes, and obtaining a plurality of optimal power distribution results; analyzing each of the plurality of optimal power distribution results corresponding to the predicted vehicle speed information based on a dynamic programming algorithm, and outputting the working mode sequence corresponding to the dual-motor drive system during the prediction time period.

[0008] Optionally, based on the drive load model, the motor model, and the drive system models corresponding to different operating modes, determining the optimal power distribution results corresponding to different operating modes of the dual-motor drive system to obtain a plurality of optimal power distribution results; including: based on the predicted vehicle speed information, determining the first ring gear speed corresponding to the dual-motor drive system and the first load torque acting on the first ring gear according to the drive load model; for any one of the different operating modes: based on the first ring gear speed and the first load torque, determining the torque feasible solution and the speed feasible solution corresponding to the dual-motor drive system in the operating mode according to the drive system model corresponding to the operating mode; based on the torque feasible solution and the speed feasible solution, determining the motor power feasible solution corresponding to the dual-motor drive system in the operating mode according to the motor model; based on the torque feasible solution, the speed feasible solution, and the motor power feasible solution corresponding to the dual-motor drive system, determining the optimal power distribution result corresponding to the dual-motor drive system in the operating mode; based on the optimal power distribution results corresponding to each operating mode, determining a plurality of motor power distribution results corresponding to different operating modes.

[0009] Optionally, based on the torque feasible solution, the speed feasible solution, and the motor power feasible solution corresponding to the dual-motor drive system, determining the optimal power distribution result corresponding to the dual-motor drive system in the operating mode; including: constructing a cost function for optimizing the operating mode of the dual-motor drive system with the motor speed change rate as a constraint.

[0010]

[0011] Δn = max(Δn1, Δn2)

[0012]

[0013] n 1,T ≥ -2000 rpm Equation (15);

[0014] where, Δn1 and Δn2 are respectively the rotational speed changes of motor 1 and motor 2 within 1 s; p B is the penalty coefficient for brake actuation; I B (k) is the brake actuation index, and its value is equal to the number of brake actuations; I ms (k) represents the number of brake actuations in mode S; 2I ms (k) represents the number of brake actuations in non-mode S; P m (k) is the motor power at the k-th step, P m,p (k) is the motor power corrected considering the motor speed change amplitude; n 1,Tis the rotational speed of the motor 1 in mode T, P m (k) is the motor power at the k-th step; is the power penalty coefficient.

[0015] Based on the torque feasible solution, rotational speed feasible solution, and motor power feasible solution corresponding to the dual-motor drive system, use the cost function to determine the optimal motor power distribution result corresponding to the dual-motor drive system in the working mode.

[0016] Optionally, the method further includes: based on the extreme value selection rule, select a first discrete interval from the historical speed sequence of the target vehicle at a first preset interval, and select a second discrete interval from the historical acceleration sequence of the target vehicle at a second preset interval; wherein, the historical speed sequence and the historical acceleration sequence are obtained by discretely sampling the speed and acceleration of the target vehicle at a preset sampling time respectively; obtain a plurality of grids formed by the first discrete interval and the second discrete interval, and determine the acceleration transition probability corresponding to each grid at the prediction step length; based on the acceleration transition probability corresponding to each grid, determine the first acceleration transition probability matrix corresponding to the plurality of grids at the prediction step length; based on the first acceleration transition probability matrix corresponding to the plurality of grids at each prediction step length, determine the second acceleration transition probability matrix corresponding to the plurality of grids in the prediction domain; wherein, the prediction domain includes a plurality of prediction step lengths; based on the maximum value selection principle of the acceleration transition probability, generate a vehicle speed prediction model according to the second acceleration transition probability matrix.

[0017] Optionally, the working mode is a single-motor working mode or a dual-motor working mode; the single-motor working mode is the first motor working mode or the second motor working mode; the dual-motor working mode is mode S or dual-motor working mode T; the method further includes: if the first working mode in the working mode sequence is a single-motor working mode, output the rotational speed and torque corresponding to the first motor in the single-motor working mode based on the optimal power distribution result, and use the rotational speed and torque corresponding to the first motor as the motor control parameters corresponding to the first working mode; if the working mode in the working mode sequence is a dual-motor working mode, output the rotational speed and torque corresponding to the first motor in the dual-motor working mode based on the optimal power distribution result; and based on the rotational speed and torque corresponding to the first motor; use the drive system model corresponding to the first working mode to determine the rotational speed and torque corresponding to the second motor; use the rotational speed and torque corresponding to the first motor, and the rotational speed and torque corresponding to the second motor, as the motor control parameters corresponding to the first working mode.

[0018] Optionally, the method further includes: at a first prediction moment adjacent to the current moment, controlling the dual-motor drive system to perform a driving operation based on the motor control parameters, and generating actual vehicle speed information corresponding to the target vehicle at the first prediction moment; using the actual vehicle speed information corresponding to the first prediction moment as the vehicle speed information corresponding to the target vehicle at the current moment; determining a working mode sequence corresponding to the dual-motor drive system in the next prediction time period adjacent to the first prediction moment; obtaining motor control parameters corresponding to the first working mode in the working mode sequence, and controlling the dual-motor drive system to perform a driving operation based on the motor control parameters at a second prediction moment adjacent to the first prediction moment.

[0019] According to a second aspect of the embodiments of the present invention, there is also provided a control device for a dual-motor drive system. The device includes: a prediction module, configured to perform a prediction process using a vehicle speed prediction model based on vehicle speed information corresponding to a target vehicle at a current moment, and output a prediction vehicle speed sequence corresponding to a next prediction time period adjacent to the current moment; wherein the prediction vehicle speed sequence includes a plurality of prediction vehicle speed information arranged in chronological order; each of the prediction vehicle speed information includes a predicted speed and a corresponding predicted acceleration; an optimization module, configured to optimize the motor energy consumption of the dual-motor drive system of the target vehicle in the prediction time period according to the prediction vehicle speed sequence, and output a working mode sequence corresponding to the dual-motor drive system in the prediction time period; wherein the working mode sequence is used to indicate a set formed by arranging the working modes corresponding to each prediction moment in the prediction time period in chronological order; a control module, configured to obtain motor control parameters corresponding to the first working mode in the working mode sequence; and control the dual-motor drive system to perform a driving operation based on the motor control parameters at a first prediction moment adjacent to the current moment.

[0020] According to a third aspect of an embodiment of the present invention, there is also provided a dual-motor drive system, including: a first motor, a second motor, and a power coupling device; the power coupling device is disposed between the first motor and the second motor and is connected to the first motor and the second motor; the power coupling device includes a first planetary gear set, a second planetary gear set, a first brake, a second brake, and a third brake; the power coupling device is capable of adjusting the output of the power coupling of the first motor and the second motor based on the first brake, the second brake, and the third brake; the first planetary gear set includes a first ring gear, a first sun gear, and three first planet gears; the first sun gear is disposed at the center of the first ring gear, and the three first planet gears are disposed between the first sun gear and the first ring gear, and each of the first planet gears meshes with the first ring gear and the first sun gear respectively; the bearings of the three first planet gears are connected by a first planet carrier; the second planetary gear set includes a second ring gear, a second sun gear, and three second planet gears; each component of the second planetary gear set has the same connection relationship as each component of the first planetary gear set; the first sun gear and the second sun gear are connected by a bearing; the first ring gear is connected to the second planet carrier; the first motor is connected to the first sun gear by a bearing, the second motor is connected to the second ring gear, the first brake acts on the output shaft of the first motor, the second brake acts on the second ring gear, and the third brake acts on the first planet carrier.

[0021] According to a fourth aspect of an embodiment of the present invention, there is also provided a computer-readable medium having a computer program stored thereon, and when the program is executed by a processor, the method described in the first aspect is implemented.

[0022] An embodiment of the present invention provides a control method and device for a dual-motor drive system. The method includes: First, based on the vehicle speed information corresponding to the target vehicle at the current moment, perform prediction processing using a vehicle speed prediction model, and output a predicted vehicle speed sequence corresponding to the next prediction time period adjacent to the current moment; wherein, the predicted vehicle speed sequence includes a plurality of predicted vehicle speed information arranged in chronological order; each of the predicted vehicle speed information includes a predicted speed and a corresponding predicted acceleration; Second, according to the predicted vehicle speed sequence, optimize the motor energy consumption of the dual-motor drive system of the target vehicle during the prediction time period, and output a working mode sequence corresponding to the dual-motor drive system during the prediction time period; wherein, the working mode sequence is used to indicate a set formed by arranging the working modes corresponding to each prediction moment during the prediction time period in chronological order; Finally, obtain the motor control parameters corresponding to the first working mode in the working mode sequence; and control the dual-motor drive system to perform a driving operation based on the motor control parameters at the first prediction moment adjacent to the current moment. Thus, the double-layer optimization algorithm proposed in this embodiment is constrained by the motor speed change rate, and by optimizing the working mode, motor power, and brake action frequency of the motor drive system, the total motor energy consumption of the dual-motor drive system is reduced, thereby solving the energy management problem of the multi-mode coupled drive system of pure electric vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Some specific embodiments of the present invention will be described in detail hereinafter with reference to the accompanying drawings in an exemplary and non-limiting manner. The same reference numerals in the drawings denote the same or similar components or parts. Those skilled in the art should understand that these drawings are not necessarily drawn to scale. In the drawings:

[0024] Figure 1 is a schematic structural diagram of a dual-motor drive system provided by an embodiment of the present invention; wherein, Fig. a is a structural diagram of the dual-motor drive system, and Fig. b is a structural diagram of the first planetary gear train;

[0025] Figure 2 is a schematic flow chart of a control method for a dual-motor drive system provided by an embodiment of the present invention;

[0026] Figure 3 is a schematic structural diagram of a vehicle speed prediction model in an embodiment of the present invention;

[0027] Figure 4 is a schematic diagram of the dynamic programming process related to mode T in an embodiment of the present invention;

[0028] Figure 5 is a schematic diagram of the dynamic programming process related to mode S in an embodiment of the present invention;

[0029] Figure 6Schematic diagram of the predictive control strategy architecture of the double-layer optimization algorithm provided by an embodiment of the present invention

[0030] Figure 7 Schematic diagram of the device structure for a dual-motor drive system provided by an embodiment of the present invention. Detailed implementation manners

[0031] To make the objectives, features, and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present invention.

[0032] The advantage of the rule-based control strategy is that the control logic is relatively simple, the real-time calculation amount is small, and the performance requirements for the controller are relatively low. Therefore, the rule-based control strategy has been widely applied. The power distribution and mode selection of the rule-based control strategy are both completed offline and stored in the controller in the form of a table. During actual use, only the vehicle speed and acceleration information need to be looked up in the table to obtain the corresponding control instructions. However, the traditional rule-based control strategy has the following disadvantages: on the one hand, the formulation of rules depends mostly on the experience, professional knowledge of the formulator, and heuristic tuning. Therefore, the rule-based control strategy has relatively high requirements for the formulator himself; on the other hand, since the rules are formulated in advance and cannot consider real-time road conditions, the performance of the rule-based control strategy is worse than that of the predictive control strategy.

[0033] As Figure 1 shown, it is a schematic diagram of the structure of a dual-motor drive system provided by an embodiment of the present invention.

[0034] A dual-motor drive system includes: a first motor 10, a second motor 20, a power coupling device 30, a main reducer 40, and a differential 50; the power coupling device 30 is disposed between the first motor 10 and the second motor 20 and is connected to the first motor 10 and the second motor 20; the power coupling device 30 includes a first planetary gear set 31, a second planetary gear set 32, a first brake 33, a second brake 34, and a third brake 35; the power coupling device 30 can adjust the output of the power coupling of the first motor 10 and the second motor 20 based on the first brake 33, the second brake 34, and the third brake 35;

[0035] The first planetary gear set 31 includes a first ring gear 310, a first sun gear 311, and three first planet gears 312; the first sun gear 311 is disposed at the center of the first ring gear 310, and the three first planet gears 312 are disposed between the first sun gear 311 and the first ring gear 310, and each first planet gear 312 meshes with the first ring gear 310 and the first sun gear 311 respectively; the bearings of the three first planet gears 312 are connected by a first planet carrier 313;

[0036] The second planetary gear set includes a second ring gear, a second sun gear, and three second planet gears; the components of the second planetary gear set have the same connection relationship as the components of the first planetary gear set;

[0037] The first sun gear 311 is connected to the second sun gear by a bearing; the first ring gear 310 is connected to the second planet carrier; the first motor 10 is connected to the first sun gear 311 by a bearing, the second motor 20 is connected to the second ring gear, the first brake 33 acts on the output shaft of the first motor 10, the second brake 34 acts on the second ring gear, and the third brake 35 acts on the first planet carrier 313.

[0038] The coupled drive system adopting the double planetary gear set in this embodiment can reduce the energy consumption of the drive system through the coupled drive of two motors and the single-motor drive mode; this is because the coupled drive system of the double planetary gear set can simultaneously have a speed coupling mode and a torque coupling mode, and has more excellent performance than the double-motor drive system based on torque coupling. This drive system can not only improve the economy by reasonably selecting the working mode, but also expand the working area of the drive system by using the torque coupling and speed coupling modes, and enhance the power performance of the drive system.

[0039] Table 1 Working modes of the drive system in this embodiment and the states of corresponding system components

[0040]

[0041] As Figure 2 shown, it is a schematic flow chart of a control method for a double-motor drive system provided by an embodiment of the present invention; as Figure 3 shown, it is a schematic structural diagram of a vehicle speed prediction model in an embodiment of the present invention.

[0042] A control method for a double-motor drive system at least includes the following steps:

[0043] S101. Based on the vehicle speed information corresponding to the target vehicle at the current moment, perform prediction processing using a vehicle speed prediction model, and output a predicted vehicle speed sequence corresponding to the next prediction time period adjacent to the current moment; wherein, the predicted vehicle speed sequence includes a plurality of predicted vehicle speed information arranged in chronological order; each predicted vehicle speed information includes a predicted speed and a corresponding predicted acceleration.

[0044] S102. According to the predicted vehicle speed sequence, optimize the motor energy consumption of the dual-motor drive system of the target vehicle in the prediction time period, and output a working mode sequence corresponding to the dual-motor drive system in the prediction time period; wherein, the working mode sequence is a set formed by arranging the working modes corresponding to each prediction moment in the prediction time period in chronological order.

[0045] S103. Obtain the motor control parameters corresponding to the first working mode in the working mode sequence; and control the dual-motor drive system to perform a driving operation based on the motor control parameters at the first prediction moment adjacent to the current moment.

[0046] In S101, there is no limitation on the acquisition method of the vehicle speed prediction model. It can be based on the Markov chain principle to construct a vehicle speed prediction model according to the historical vehicle speed information of the target vehicle; it can also be obtained through model training.

[0047] Specifically, the vehicle speed prediction model based on the Markov chain is a stochastic model based on the vehicle historical data set, which can reflect the driving habits of drivers, road information, etc. Its principle is to solve the transition probability between different vehicle speed information through historical data, and predict the vehicle speed information at the next time point according to the current vehicle speed information. The premise of this application is to assume that the prediction of the vehicle speed information at the next time point is only related to the current vehicle speed information and has nothing to do with the vehicle speed information before this transfer, that is, the state sequence of the vehicle speed information is a stochastic process without aftereffect - the Markov chain process.

[0048] Exemplarily, based on the maximum and minimum value selection rule, a first discrete interval is selected from the historical speed sequence of the target vehicle at a first preset interval, and a second discrete interval is selected from the historical acceleration sequence of the target vehicle at a second preset interval; wherein, the historical speed sequence and the historical acceleration sequence are obtained by discretely sampling the speed and acceleration of the target vehicle respectively according to a preset sampling time; obtain a plurality of grids formed by the first discrete interval and the second discrete interval, and determine the acceleration transition probability corresponding to each grid at a prediction step; based on the acceleration transition probability corresponding to each grid, determine a first acceleration transition probability matrix corresponding to the plurality of grids at the prediction step; based on the first acceleration transition probability matrix corresponding to the plurality of grids at each prediction step, determine a second acceleration transition probability matrix corresponding to the plurality of grids in the prediction domain; wherein, the prediction domain includes a plurality of prediction steps; based on the maximum value selection principle of the acceleration transition probability, generate a vehicle speed prediction model according to the second acceleration transition probability matrix.

[0049] For example: S1, discretely sample the speed and acceleration of the working condition at a fixed sampling time to obtain the historical speed sequence v and the historical acceleration sequence as shown in Equation (1). And according to the speed maximum and minimum value and acceleration maximum and minimum value selection rules, obtain the first discrete interval v as shown in Equation (2). d And the second discrete interval

[0050] S2, use the grids formed by the first discrete interval and the second discrete interval to classify the historical speed sequence and the historical acceleration sequence respectively to obtain a plurality of grids; for any grid: calculate the acceleration transition probability p corresponding to the grid at the prediction step based on Equation (3). j,k,z ;

[0051]

[0052] In the formula, l is the prediction step, C1 and C3 are two different acceleration intervals, C2 is the speed interval; n j,k ,z is the number of sampling points that satisfy the three conditions (C1, C2, and C3); n j,k is the number of sampling points that satisfy C2 and C3. Repeat Equation (3) to calculate the acceleration transition probability corresponding to each grid in the plurality of grids at the prediction step, and obtain the first acceleration transition probability matrix.

[0053] S3, to obtain the vehicle speed information within the entire prediction domain (1 - l max ), set the sampling time to [1s, 2s,... l maxs], and repeat step S2 to obtain the first acceleration transition probability matrix corresponding to each prediction step length, thereby obtaining the second acceleration transition probability matrix P corresponding to the entire prediction domain w , P w can be written as the following equation (4):

[0054] P w =[P1, P2, … P lmax Equation (4);

[0055] S4. Since when predicting acceleration using the acceleration probability transition matrix, the result with the maximum acceleration transition probability is usually selected as the prediction value, in order to improve the online calculation efficiency, the acceleration prediction for all scenarios is completed offline, and the prediction results are stored in the second acceleration transition probability matrix. At a specific prediction step length, the prediction results can be represented by the acceleration prediction diagram shown in the vehicle speed prediction model such as Figure 3 ; based on this acceleration prediction diagram, the acceleration corresponding to the prediction step length can be directly found through the current vehicle speed and acceleration.

[0056] In S102, the specific structure of the dual-motor drive system of the target vehicle of the present invention is not limited; preferably, the dual-motor drive system is a drive system with a double planetary gear train.

[0057] According to the predicted vehicle speed sequence, optimize the motor energy consumption of the dual-motor drive system of the target vehicle based on a training model or a preset rule, and output the working mode sequence corresponding to the dual-motor drive system during the prediction period.

[0058] Exemplarily, construct a drive load model, a motor model corresponding to the dual-motor drive system, and a drive system model corresponding to the dual-motor drive system in different working modes; for any predicted vehicle speed information in the predicted vehicle speed sequence: based on the drive load model, the motor model, and the drive system models corresponding to different working modes, determine the optimal power distribution results corresponding to the dual-motor drive system in different working modes for the predicted vehicle speed information, and obtain a number of optimal power distribution results; based on the dynamic programming algorithm, analyze the number of optimal power distribution results corresponding to each predicted vehicle speed information, and output the working mode sequence corresponding to the dual-motor drive system during the prediction period.

[0059] For example: when the dual-motor drive system is in mode T, the degree of freedom of the dual-motor drive system is 1, and the drive system models are shown in the following equations (5) and (6):

[0060]

[0061] Among them, n s1 , n r2 and n LThey are the rotational speed of the first sun gear, the rotational speed of the second ring gear, and the rotational speed of the first ring gear; i p1 and i p2 They are the gear ratios of the first ring gear to the first sun gear and the second ring gear to the second sun gear respectively; η1 represents the transmission efficiency of the internal gear pair formed by the first ring gear and the first planet gear (or the second ring gear and the second planet gear); η2 represents the transmission efficiency of the external gear pair formed by the first sun gear and the first planet gear (or the second sun gear and the second planet gear). T s1 and T r2 They are the torques acting on the first sun gear and the second ring gear respectively. T L is the load torque acting on the first ring gear, which is generated by the acceleration resistance and road resistance of the target vehicle. Sign(·) is the sign function.

[0062] When the dual-motor drive system is in mode S, the degree of freedom of the dual-motor drive system is 2. The dual-motor drive system model (the first motor operating mode and the second motor operating mode can be regarded as special cases of mode S, so they can also be represented by the following model) is shown in the following equations (7) and (8):

[0063] n s1 +i p2 n r2 =(1+i p2 )n L

[0064] Equation (7);

[0065]

[0066] The motor model mainly considers the limitations of motor speed and torque and the motor energy consumption associated with motor speed and torque. The motor energy consumption P loss (n,T) can be expressed as Equation (9):

[0067] P loss (n,T)=interp2(n e, T e ,P loss,e ,n,T)

[0068] s.t.

[0069] 0<n<n max ,-T max (n)<T(n)<T max (n) Equation (9);

[0070] Among them, P loss is the power loss of the motor at the operating point (n,T), which is calculated by interpolation based on experimental data. n e 、Te and P loss,e are the motor speed, motor torque, and corresponding power loss obtained from the experiment, respectively. n max and T max are the maximum motor speed and maximum torque, respectively; n is used to represent the motor speed. For example, n can be n s1 or n r2 ; T is used to represent the motor torque. For example, T can be T s1 and T r2 .

[0071] The drive load model can be expressed as Equation (10):

[0072]

[0073] where F v is the resistance caused by road slope, tire rolling, aerodynamic force, and acceleration. R w , i f , η f are the tire radius, main reduction ratio, and transmission efficiency of the main reducer, respectively. m V , A V , C d , C t [[ID=ID=40]], g, φ, ρ, and δ are the vehicle mass, vehicle frontal area, drag coefficient, tire rolling friction coefficient, gravitational acceleration, road inclination angle, air density, and combined rotational inertia coefficient, respectively. v and are the vehicle speed and acceleration, respectively.

[0074] Based on the drive load model, the motor model, and the corresponding drive system models under different working modes, the optimal power distribution results corresponding to different working modes of the dual-motor drive system for determining the predicted vehicle speed information are obtained by using the two-layer optimization algorithm, and several optimal power distribution results are obtained.

[0075] In S103, the first working mode in the working mode sequence is obtained, and the motor control parameters corresponding to the first working mode are obtained from the optimal power distribution results. The motor control parameters include: motor speed and motor torque. Since the first prediction moment in the prediction time period corresponds to the first working mode, the dual-motor drive system is controlled to perform a driving operation based on the motor control parameters corresponding to the first working mode at the first prediction moment adjacent to the current moment.

[0076] If the first working mode in the working mode sequence is the single-motor working mode, the rotational speed and torque corresponding to the first motor in the single-motor working mode are output based on the optimal power distribution result, and the rotational speed and torque corresponding to the first motor are used as the motor control parameters corresponding to the first working mode; if the first working mode in the working mode sequence is the dual-motor working mode, the rotational speed and torque corresponding to the first motor in the dual-motor working mode are output based on the optimal power distribution result; and based on the rotational speed and torque corresponding to the first motor, the rotational speed and torque corresponding to the second motor are determined by using the drive system model corresponding to the first working mode; the rotational speed and torque corresponding to the first motor, and the rotational speed and torque corresponding to the second motor are used as the motor control parameters corresponding to the first working mode. For example: when the first working mode is the dual-motor working mode, the rotational speed and torque corresponding to the first motor are input into the drive system model corresponding to the first working mode, and the rotational speed and torque corresponding to the second motor are output; thereby enabling the dual-motor drive system to output a torque equal to the driver's expected torque, which not only solves the energy management problem of the dual-motor multi-mode coupling drive system of pure electric vehicles, but also improves the user experience.

[0077] In this embodiment, the double-layer optimization algorithm is divided into an upper-layer algorithm and a lower-layer algorithm; the lower-layer algorithm calculates the optimal power distribution results of the motors in different modes according to the drive load model, the motor model, and the drive system model, the minimum power method and the step-by-step optimization method respectively, and then substitutes the optimal power distribution results of the motors into the upper-layer algorithm. According to the cost function in the upper-layer algorithm, the optimal working mode sequence is obtained by using the dynamic programming algorithm, and the first working mode in the sequence and the rotational speed and torque of the corresponding first motor are output. The rotational speed and torque of the first motor are substituted into the drive system model corresponding to the first working mode to obtain the output of the second motor; thus enabling the dual-motor drive system to output a torque equal to the driver's expected torque. Thereby, by optimizing the working mode of the drive system, the motor power, and the brake action frequency, the purpose of reducing the total energy consumption of the motor is achieved, so that the dynamic performance of the drive system during mode switching, the action frequency of the drive system mode switching actuator, and the energy consumption of the drive system can be taken into account, and the user experience is improved; the energy management problem of the multi-mode coupling drive system of pure electric vehicles is solved.

[0078] In a preferred embodiment of the present embodiment, the method further includes: at a first prediction moment adjacent to the current moment, controlling the dual-motor drive system to perform a driving operation based on the motor control parameters, and generating actual vehicle speed information corresponding to the target vehicle at the first prediction moment; using the actual vehicle speed information corresponding to the first prediction moment as the vehicle speed information corresponding to the target vehicle at the current moment; determining a working mode sequence corresponding to the next prediction time period adjacent to the first prediction moment for the dual-motor drive system; obtaining the motor control parameters corresponding to the first working mode in the working mode sequence, and controlling the dual-motor drive system to perform a driving operation based on the motor control parameters at a second prediction moment adjacent to the first prediction moment.

[0079] Specifically, in this embodiment, at the current moment, a first predicted vehicle speed sequence corresponding to the next adjacent prediction time period is predicted, and a first working mode sequence corresponding to the first predicted vehicle speed sequence is generated; the motor control parameters corresponding to the first working mode in the first working mode sequence are taken out to control the dual-motor drive system to perform a driving operation at the first prediction moment, and corresponding vehicle speed information is generated; wherein, the first prediction moment is used to indicate the first prediction moment in the next adjacent prediction time period predicted from the current moment. Then, based on the vehicle speed information at the first prediction moment, a second predicted vehicle speed sequence corresponding to the next adjacent prediction time period to the first prediction moment is re-predicted, a second working mode sequence corresponding to the second predicted vehicle speed sequence is generated, and the motor control parameters corresponding to the first working mode in the second working mode sequence are taken out to control the dual-motor drive system to perform a driving operation at the second prediction moment, and corresponding vehicle speed information is generated; wherein, the second prediction moment is used to indicate the second prediction moment in the next adjacent prediction time period to the current moment, or the first prediction moment in the next adjacent prediction time period to the first prediction moment. Therefore, this process is a cyclic process. For the working mode sequence generated in each cyclic process, only the motor control parameters corresponding to the first working mode are used to drive the dual-motor drive system.

[0080] Thus, in this embodiment, the working mode corresponding to the dual-motor drive system at each prediction moment is determined based on a global optimization method, so that the motor control parameters corresponding to each prediction moment can be accurately obtained, the motor energy consumption of the dual-motor drive system is effectively reduced, and thus the energy management problem of the dual-motor drive system of a pure electric vehicle is solved.

[0081] As Figure 4 shown, it is a schematic diagram of the dynamic programming process related to mode T in an embodiment of the present invention; as Figure 5 shown, it is a schematic diagram of the dynamic programming process related to mode S in an embodiment of the present invention.

[0082] In a preferred implementation of this embodiment, based on the drive load model, the motor model, and the drive system models corresponding to different operating modes, determining the optimal power allocation results corresponding to the dual-motor drive system of the predicted vehicle speed information in different operating modes, and obtaining several optimal power allocation results, at least includes the following steps:

[0083] S1, based on the predicted vehicle speed information, determining a first ring gear speed corresponding to the dual-motor drive system and a first load torque acting on the first ring gear according to the drive load model;

[0084] S2, for any of the different working modes: based on the first ring gear speed and the first load torque, determine, according to a drive system model corresponding to the working mode, a torque feasible solution and a speed feasible solution corresponding to the dual-motor drive system in the working mode; based on the torque feasible solution and the speed feasible solution, determine, according to the motor model, a motor power feasible solution corresponding to the dual-motor drive system in the working mode; based on the torque feasible solution, the speed feasible solution, and the motor power feasible solution corresponding to the dual-motor drive system, determine an optimal power allocation result corresponding to the dual-motor drive system in the working mode;

[0085] S3, based on the optimal power distribution result corresponding to each of the working modes, determine the power distribution results of the motors corresponding to the different working modes according to a prediction model or a preset rule.

[0086] For example, the predicted vehicle speed information is substituted into the driving load model shown in formula (10), and the output corresponding to the first ring gear speed n of the dual-motor drive system is: L And the first load torque T acting on the first ring gear L ; For any working mode: set the first ring gear speed n L And the first load torque T L Input the dual-motor drive system corresponding to the working mode and output the torque feasible solution and speed feasible solution corresponding to the working mode. The torque feasible solution and speed feasible solution corresponding to each of the four working modes are shown as follows:

[0087] First motor working mode:

[0088] T m1,1 =T s1 ,T m2,1 =0,n 1,1 =n s1 ,n 2,1 =0

[0089] Formula (11);

[0090] Second motor working mode:

[0091] T m1,2 = 0, T m2,2 = T r2 , n 1,2 = 0, n 2,2 = n r Equation (12);

[0092] Mode T:

[0093] T m1,T = T e sign(T L ), T e = [5:1:T max ,

[0094]

[0095] n 1,T = n s1 , n 2,T = n r2 Equation (13);

[0096] Mode S:

[0097] T m1,S = T s1 , T m2,S = T r2 ,

[0098]

[0099] where, T e represents the torque discrete interval formed by taking different values at intervals of 1 within the interval [5, T max ; n 1,S represents the discrete interval of the first motor speed formed by taking different values at intervals of 5 within the interval [5, n max .

[0100] For any working mode: Substitute the torque feasible solution and speed feasible solution corresponding to the dual-motor drive system of this working mode into the motor model shown in Equation (9), and output the motor power feasible solution P m,p (k) of the dual-motor drive system in this working mode.

[0101] For any working mode: Based on the torque feasible solution, speed feasible solution, and motor power feasible solution corresponding to the dual-motor drive system of this working mode, substitute them into the cost function, and output the optimal power distribution result of the dual-motor drive system in this working mode.

[0102] Construct a cost function for optimizing the working mode of the dual-motor drive system with the motor speed change rate as the constraint:

[0103]

[0104] where Δn1 and Δn2 are the rotational speed change amounts of motor 1 and motor 2 within 1 s respectively; p B is the penalty coefficient for the brake action; I B (k) is the action index of the brake, and its value is equal to the number of brake actions; I ms (k) represents the number of brake actions of the brake in mode S; 2I ms (k) represents the number of brake actions of the brake in non-mode S; P m (k) is the motor power at the k-th step, P m,p (k) is the motor power after correction considering the change range of the motor rotational speed; n 1,T is the rotational speed of motor 1 in mode T, P m (k) is the motor power at the k-th step.

[0105] Based on the torque feasible solution, rotational speed feasible solution, and motor power feasible solution corresponding to the dual-motor drive system, the optimal motor power distribution result corresponding to the dual-motor drive system in the working mode is determined by using the cost function.

[0106] Specifically, the energy optimization problem of the dual-motor drive system involves working mode selection and power distribution. Such problems are usually solved by dynamic programming. The dynamic programming algorithm takes a long time and is not conducive to the practical application of predictive control strategies. Different from the dynamic programming algorithm that simultaneously optimizes mode selection and power distribution, the two-layer optimization algorithm proposed by the present invention solves the optimal problem of the two-layer optimization algorithm in Equation (15) in two layers. The working mode selection problem of the dual-motor drive system is solved by the upper-layer algorithm, and the motor power distribution result is optimized by the lower-layer algorithm. The specific algorithm content is as follows:

[0107] When the dual-motor drive system has only four working modes, the state quantity of dynamic programming is reduced to 4, which is beneficial to improving the calculation efficiency; the cost function can be solved only by substituting the rotational speed feasible solution and torque feasible solution corresponding to each working mode into the cost function of the lower-layer algorithm; therefore, a lower-layer algorithm is proposed to obtain the optimal power distribution result under each working mode. In order to obtain an optimization result close to dynamic programming while optimizing the calculation efficiency, based on the dynamic programming algorithm, several optimal power distribution results corresponding to each predicted vehicle speed information are analyzed, and the working mode sequence corresponding to the dual-motor drive system in the prediction time period is output.

[0108] It can be seen from the expressions of the motor output under different working modes that the power distribution of the single-motor drive mode is unique, so the lower-layer algorithm directly obtains the motor output according to the transmission system efficiency model.

[0109] For the dual-motor drive mode, the motor output forms of different dual-motor drive modes are different. Therefore, mode T and mode S are discussed separately. When directly solving the cost function using dynamic programming, all possible motor outputs in Equation (13) are regarded as a state point. Then, the dynamic programming process involving mode T is as Figure 4 shown. Mode k-1 is any state point among the four working modes in the (k - 1)-th step, and Mode k+1 is any state point among the four working modes in the (k + 1)-th step. Mode T,i (i = 1, 2, … n) are all motor outputs in mode T at the k-th step. At the (k + 1)-th step, the total cost function from Mode k-1 to Mode k+1 can be expressed as:

[0110] J k+1 = min(J k-1 + P T,i (k) + p B I B,T (k) + P m,p (k + 1) + p B I B (k + 1)), i = 1, 2, … n Equation (16);

[0111] Among them, J k-1 and J k+1 are the total cost functions from the 1st step to Mode k-1 and Mode k+1 respectively. P T,i is the corrected motor power corresponding to mode T at the k-th step. I B,T (k) is the brake action index corresponding to mode T at the k-th step. P m,p (k + 1) is the corrected motor power of Mode k+1 . J k-1 depends on the working modes and power distribution from the 1st step to the (k - 1)-th step, and L k+1 depends on the working modes at the k-th step and the (k + 1)-th step and the power distribution at the (k + 1)-th step. It can be seen from Equation (13) that the motor speeds of all Mode T,i are the same. Therefore, for all Mode T,i and Mode k+1 , the penalty coefficients p p and p B are the same, that is, the motor speed of Mode k-1 does not affect the torque distribution in mode T at the k-th step, and the speed of Mode k+1 is not affected by the torque distribution in mode T at the k-th step. Therefore, J k+1Can be rewritten as:

[0112] J k+1 = J k-1 + min(P T,i (k)) + p B I B (k) + P m,p (k + 1) + p B I B (k + 1), i = 1, 2, … n

[0113] Equation (17);

[0114] Therefore, the optimal torque distribution under pattern T in the k-th step is the torque distribution when the motor power is minimized, that is:

[0115] P min,T = P T (T m1,T,op , T m2,T,op )

[0116] Equation (18);

[0117] Wherein, T m1,T,op and T m2,T,op are the optimal output torques of the first motor and the second motor under pattern T respectively. Therefore, in the upper layer algorithm, the motor operating point corresponding to pattern T is the operating point corresponding to the minimum motor power under pattern T.

[0118] It can be seen from Equation (14) that all motor outputs have the same output torque and different rotational speeds under pattern S. The variation range of the motor rotational speed will affect the magnitude of the cost function, which means that the rotational speed distribution of the motor at any step within the prediction range will be affected by the rotational speed distribution of the motor at other steps. To simplify the solution process, the sub-optimal solution obtained by the step-by-step optimal method is used to replace the global optimal solution. The core of the step-by-step optimal method is to ignore the influence of future states on the current state. The optimal rotational speed distribution of mode S is determined only by past states and the current state. The dynamic programming process involving mode S is as Figure 5 shown, where Mode1 represents mode 1, Mode2 represents mode 2, ModeT represents mode T, and ModeS represents mode S. Each mode in the figure represents the motor state under each mode. There are many feasible motor states at the k - 1 step, and they will all affect the motor rotational speed distribution under mode S at the k-th step. Assuming that the motor outputs under each mode are known at the k - 1 step, the total cost corresponding to any state (Mode k+1 ) at the k + 1 step can be expressed as:

[0119] J k+1 = min(J k-1,i + P S,j (k) + pB I B,S (k) + P m,p (k + 1) + p B I B (k + 1)), i = 1, 2, T, S j = 1, 2, … n

[0120] Equation (19);

[0121] where, J k-1,i is the total cost of any pattern at the (k - 1)-th step, which can be obtained by the recurrence formula and is assumed to be known in the derivation process. P S,i is the corrected motor power corresponding to pattern S at the k-th step. From the idea of dynamic programming, P S,i is affected by the pattern selection and power distribution at the (k - 1)-th step, k-th step, and (k + 1)-th step. If the step-by-step optimization method is used to calculate J k+1 , that is, the motor speed distribution of pattern S at the k-th step is only affected by the 1st step to the k-th step, then J k+1 can be re-expressed as:

[0122] J k+1 = min(min(J k-1,i + P S,j (k) + p B I B,S (k)) + P m,p (k + 1) + p B I B (k + 1)), i = 1, 2, T, S j = 1, 2, … n

[0123] Equation (20);

[0124] Define J k,S = min(J k-1,i + P S,j (k) + p B I B,S (k)), then

[0125] J k+1 = min(J k,S + P m,p (k + 1) + p B I B (k + 1)), i = 1, 2, T, S j = 1, 2, … n

[0126] Equation (21);

[0127] From Equation (21), it can be seen that after obtaining J k,S , the step-by-step optimization method can be used again to obtain J k+1 . The optimal solution at the k-th step is the motor power distribution corresponding to the minimum value of the total cost at the k-th step, that is:

[0128] J k,S (n 1,S,op ,n 2,S,op ) = min(J k-1,i +P S,j (k) + p B I B,S (k))

[0129] Equation (22);

[0130] That is: n 1,S,op and n 2,S,op are the rotational speed distributions of the first motor and the second motor in mode S respectively. Thus, the lower-layer algorithm has completed the solution of the motor power distribution in each working mode and generated the optimal power distribution result.

[0131] Based on the dynamic programming algorithm, analyze the several optimal power distribution results corresponding to each of the predicted vehicle speed information, and output the working mode sequence of the dual-motor drive system corresponding to the prediction time period.

[0132] The upper-layer algorithm uses the dynamic programming algorithm to optimize the working mode sequence of the dual-motor drive system corresponding to the prediction time period. The working mode recurrence formula can be simplified to the following Equation (23):

[0133] Mode(k + 1) = Mode(k) + O ms (k),

[0134] Mode ∈ {Mode 1, Mode 2, Mode T, Mode S} Equation (23);

[0135] where Mode(k) represents the working mode at the k-th step; O ms (k) represents the brake action parameter corresponding to the mode switch.

[0136] It should be noted that since the analysis and processing of data based on the dynamic programming algorithm are prior arts, no detailed introduction will be given here.

[0137] The control strategy based on the double-layer optimization algorithm in this embodiment includes that the vehicle speed prediction model can optimize the output of the dual-motor drive system according to real-time vehicle speed information. The proposed double-layer optimization algorithm is constrained by the motor speed change rate. By optimizing the working mode of the dual-motor drive system, the motor power, and the brake action frequency, the purpose of reducing the total motor energy consumption can be achieved, and it can take into account the dynamic performance of the dual-motor drive system during mode switching, the action frequency of the mode switch actuator of the dual-motor drive system, and the energy consumption of the dual-motor drive system. The simulation results show that compared with the rule-based control strategy, the predictive control strategy based on the double-layer optimization algorithm can reduce the energy consumption by 4.55% and reduce the number of brake actions by 11.54% on the premise of restricting the motor speed change range; compared with the predictive control strategy based on dynamic programming, due to the adoption of the double-layer optimization algorithm, the dynamic programming algorithm can be simplified according to the different coupling mode characteristics of the dual-motor drive system. The predictive control strategy based on the double-layer optimization algorithm saves 46.1% of the calculation time while obtaining similar energy consumption and the number of brake actions.

[0138] As Figure 6 shown, it is a schematic diagram of the predictive control strategy architecture of the double-layer optimization algorithm provided by an embodiment of the present invention.

[0139] Obtain the current vehicle speed information of the target vehicle model, process the current vehicle speed information based on the predictive control strategy of the present invention, and output the working mode corresponding to the next prediction moment adjacent to the current moment, as well as the motor control parameters corresponding to this working mode; the motor and brake controller control the dual-motor drive system of the double planetary gear set to perform a driving operation according to the motor control parameters, and generate the vehicle speed information corresponding to the next prediction moment;

[0140] The implementation process of the predictive control strategy is as follows: Input the current acceleration into the acceleration prediction map of the vehicle speed prediction model, and output the predicted acceleration sequence corresponding to the prediction time period Based on the speed prediction formula in the vehicle speed prediction model, determine the predicted speed sequence corresponding to the predicted acceleration sequence Input the predicted acceleration sequence and the predicted speed sequence into the double-layer optimization algorithm, and output the working mode sequence corresponding to the prediction time period, as well as the speed ω 1，c corresponding to motor 1 in the first working mode Mode in the working mode sequence m1,c and torque T 2，c ; Input the speed and torque corresponding to motor 1 into the drive system model corresponding to the first working mode, and output the speed ω m2，c corresponding to motor 2 1，c and torque T 2，c . Input the speeds ω m1,c、 T m2，cAs motor control parameters, based on the control parameters of motor 1 controller and motor 2 controller in working mode Mode c Control the dual-motor drive system of the dual planetary gear train to perform a driving operation, generating the actual vehicle speed v of the target vehicle.

[0141] The advantages of this solution are as follows: Compared with the regular energy management strategy, the predictive control strategy of this solution has lower comprehensive energy consumption; compared with the energy management strategy of dynamic programming, the predictive control strategy of this solution can improve the system calculation efficiency by constraining the motor speed and improving the dynamic performance during mode switching; compared with the energy management strategy of the minimum principle, the predictive control strategy of this solution can solve the energy management problem of the multi-mode coupled drive system of electric vehicles by optimizing the motor output and drive system mode.

[0142] As Figure 7 shown, it is a schematic structural diagram of a control device for a dual-motor drive system provided by an embodiment of the present invention.

[0143] A control device for a dual-motor drive system, the device 700 includes: a prediction module 701, configured to perform prediction processing using a vehicle speed prediction model based on the vehicle speed information corresponding to the target vehicle at the current moment, and output a predicted vehicle speed sequence corresponding to the next prediction time period adjacent to the current moment; wherein, the predicted vehicle speed sequence includes a plurality of predicted vehicle speed information arranged in chronological order; each of the predicted vehicle speed information includes a predicted speed and a corresponding predicted acceleration; an optimization module 702, configured to optimize the motor energy consumption of the dual-motor drive system of the target vehicle during the prediction time period according to the predicted vehicle speed sequence, and output a working mode sequence corresponding to the dual-motor drive system during the prediction time period; wherein, the working mode sequence is used to indicate a set formed by arranging the working modes corresponding to each prediction moment during the prediction time period in chronological order; a control module 703, configured to obtain the motor control parameters corresponding to the first working mode in the working mode sequence; and control the dual-motor drive system to perform a driving operation based on the motor control parameters at the first prediction moment adjacent to the current moment.

[0144] In a preferred embodiment of the present embodiment, the optimization module includes: a model construction unit for constructing a drive load model, a motor model corresponding to the dual-motor drive system, and a drive system model corresponding to the dual-motor drive system under different working modes; a determination unit for any predicted vehicle speed information in the predicted vehicle speed sequence: based on the drive load model, the motor model, and the drive system model corresponding to different working modes, determine the optimal power distribution results corresponding to the dual-motor drive system under different working modes for the predicted vehicle speed information, and obtain a plurality of optimal power distribution results; an analysis unit for analyzing the plurality of optimal power distribution results corresponding to each predicted vehicle speed information based on the dynamic programming algorithm, and outputting a working mode sequence corresponding to the dual-motor drive system in the predicted time period.

[0145] In a preferred embodiment of the present embodiment, the determination unit includes: a first determination subunit for determining a first ring gear speed corresponding to the dual-motor drive system and a first load torque acting on the first ring gear based on the predicted vehicle speed information according to the drive load model; a second determination subunit for any one of the different working modes: based on the first ring gear speed and the first load torque, determine a torque feasible solution and a speed feasible solution corresponding to the dual-motor drive system in the working mode according to the drive system model corresponding to the working mode; based on the torque feasible solution and the speed feasible solution, determine a motor power feasible solution corresponding to the dual-motor drive system in the working mode according to the motor model; based on the torque feasible solution, speed feasible solution, and motor power feasible solution corresponding to the dual-motor drive system, determine the optimal power distribution result corresponding to the dual-motor drive system in the working mode; a third determination subunit for determining a plurality of motor power distribution results corresponding to the different working modes based on the optimal power distribution results corresponding to each working mode.

[0146] In a preferred embodiment of the present embodiment, the second determination subunit includes: a construction unit for constructing a cost function for optimizing the working mode of the dual-motor drive system with the motor speed change rate as a constraint.

[0147]

[0148] where Δn1 and Δn2 are the speed change amounts of motor 1 and motor 2 within 1 s respectively; p B is a penalty coefficient for brake actuation; I B (k) is an action index of the brake, and its value is equal to the number of brake actuations; I ms (k) represents the number of brake actuations in mode S; 2I ms (k) represents the number of brake actuations in non-mode S; Pm (k) is the motor power at the k-th step, P m,p (k) is the motor power after correction considering the change range of the motor speed; n 1,T is the speed of motor 1 in mode T, P m (k) is the motor power at the k-th step.

[0149] A determination unit, configured to determine an optimal motor power distribution result corresponding to the dual-motor drive system in the working mode by using the cost function based on the torque feasible solution, speed feasible solution, and motor power feasible solution corresponding to the dual-motor drive system.

[0150] In a preferred implementation manner of this embodiment, the device further includes: a selection module, configured to select a first discrete interval from the historical speed sequence of the target vehicle at a first preset interval and select a second discrete interval from the historical acceleration sequence of the target vehicle at a second preset interval based on a maximum value selection rule; wherein, the historical speed sequence and the historical acceleration sequence are obtained by discretely sampling the speed and acceleration of the target vehicle respectively according to a preset sampling time; a first determination module, configured to obtain a plurality of grids formed by the first discrete interval and the second discrete interval, and determine an acceleration transition probability corresponding to each grid at a prediction step; a second determination module, configured to determine a first acceleration transition probability matrix corresponding to the plurality of grids at the prediction step based on the acceleration transition probability corresponding to each grid; a third determination module, configured to determine a second acceleration transition probability matrix corresponding to the plurality of grids in the prediction domain based on the first acceleration transition probability matrix corresponding to the plurality of grids at each prediction step; wherein, the prediction domain includes a plurality of prediction steps; a first generation module, configured to generate a vehicle speed prediction model according to the second acceleration transition probability matrix based on a maximum value selection principle of the acceleration transition probability.

[0151] In a preferred embodiment of the present embodiment, the working mode is a single-motor working mode or a dual-motor working mode; the single-motor working mode is a first-motor working mode or a second-motor working mode; the dual-motor working mode is mode S or dual-motor working mode T; the device further includes: a third determination module, configured to, if the first working mode in the working mode sequence is a single-motor working mode, output the rotational speed and torque corresponding to the first motor in the single-motor working mode based on the optimal power distribution result, and use the rotational speed and torque corresponding to the first motor as the motor control parameters corresponding to the first working mode; a fourth determination module, configured to, if the first working mode in the working mode sequence is a dual-motor working mode, output the rotational speed and torque corresponding to the first motor in the dual-motor working mode based on the optimal power distribution result; and based on the rotational speed and torque corresponding to the first motor, determine the rotational speed and torque corresponding to the second motor by using the drive system model corresponding to the first working mode; and use the rotational speed and torque corresponding to the first motor and the rotational speed and torque corresponding to the second motor as the motor control parameters corresponding to the first working mode.

[0152] In a preferred embodiment of the present embodiment, the device further includes: a second generation module, configured to, at a first prediction moment adjacent to the current moment, control the dual-motor drive system to perform a drive operation based on the motor control parameters, and generate actual vehicle speed information corresponding to the target vehicle at the first prediction moment; a fifth determination module, configured to use the actual vehicle speed information corresponding to the first prediction moment as the vehicle speed information corresponding to the target vehicle at the current moment; determine a working mode sequence corresponding to the next prediction time period adjacent to the first prediction moment for the dual-motor drive system; the control module is further configured to obtain the motor control parameters corresponding to the first working mode in the working mode sequence, and control the dual-motor drive system to perform a drive operation based on the motor control parameters at a second prediction moment adjacent to the first prediction moment.

[0153] The above device can execute a control method for a dual-motor drive system provided in an embodiment of the present invention, and has functional modules and beneficial effects corresponding to executing a control method for a dual-motor drive system. For technical details not described in detail in this embodiment, reference may be made to a control method for a dual-motor drive system provided in an embodiment of the present invention.

[0154] The present invention further provides an electronic device, including: a processor; a memory for storing executable instructions of the processor; the processor is configured to read the executable instructions from the memory and execute the instructions to implement the control method for a dual-motor drive system according to the present invention.

[0155] In addition to the above methods and devices, embodiments of the present application may also be computer program products, which include computer program instructions that, when run by a processor, cause the processor to execute the steps in the methods according to various embodiments of the present application described in the "Exemplary Methods" section above of this specification.

[0156] The computer program product may be written in any combination of one or more programming languages to write program code for performing the operations of the embodiments of the present application. The programming languages include object-oriented programming languages such as Java, C++, etc., and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computing device, partially on the user's device, executed as a stand-alone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0157] In addition, embodiments of the present application may also be computer-readable storage media, on which computer program instructions are stored, and the computer program instructions, when run by a processor, cause the processor to execute the steps in the methods according to the following embodiments of the present application described in the "Exemplary Methods" section above of this specification.

[0158] The computer-readable storage media may adopt any combination of one or more readable media. The readable media may be a readable signal medium or a readable storage medium. The readable storage medium may, for example, include but is not limited to an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0159] The basic principles of the present application have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, advantages, effects, etc. mentioned in the present application are only examples and not limitations, and it cannot be considered that these advantages, advantages, effects, etc. are essential for each embodiment of the present application. In addition, the above-disclosed specific details are only for the purpose of illustration and facilitation of understanding, and not for limitation. The above details do not limit the present application to necessarily adopt the above specific details for implementation.

[0160] The block diagrams of the devices, apparatuses, equipment, and systems involved in this application are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open-ended terms, meaning "including but not limited to", and can be used interchangeably with each other. The word "or" and "and" used herein refer to the word "and / or" and can be used interchangeably with it, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to" and can be used interchangeably with it.

[0161] It should also be noted that in the devices, equipment, and methods of this application, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent solutions of this application.

[0162] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of this application. Therefore, this application is not intended to be limited to the aspects shown herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.

[0163] The above description has been given for purposes of illustration and description. In addition, this description is not intended to limit the embodiments of this application to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

[0164] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0165] Furthermore, the terms "first" and "second" are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality of" means two or more unless otherwise specifically defined.

[0166] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily conceive of changes or substitutions, which should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claimed rights.

Claims

1. A control method for a dual-motor drive system, characterized in that Including: Based on the vehicle speed information corresponding to the target vehicle at the current moment, perform prediction processing using a vehicle speed prediction model, and output a predicted vehicle speed sequence corresponding to the next prediction time period adjacent to the current moment; wherein, the predicted vehicle speed sequence includes a plurality of predicted vehicle speed information arranged in chronological order; each of the predicted vehicle speed information includes a predicted speed and a corresponding predicted acceleration; According to the predicted vehicle speed sequence, optimize the motor energy consumption of the dual-motor drive system of the target vehicle during the prediction time period, and output a working mode sequence corresponding to the dual-motor drive system during the prediction time period; wherein, the working mode sequence is a set formed by arranging the working modes corresponding to each prediction moment during the prediction time period in chronological order; Obtain the motor control parameters corresponding to the first working mode in the working mode sequence; and control the dual-motor drive system to perform a driving operation based on the motor control parameters at the first prediction moment adjacent to the current moment; At the first prediction moment adjacent to the current moment, control the dual-motor drive system to perform a driving operation based on the motor control parameters, and generate the actual vehicle speed information corresponding to the target vehicle at the first prediction moment; Use the actual vehicle speed information corresponding to the first prediction moment as the vehicle speed information corresponding to the target vehicle at the current moment; determine the working mode sequence corresponding to the next prediction time period adjacent to the first prediction moment for the dual-motor drive system; Obtain the motor control parameters corresponding to the first working mode in the working mode sequence, and control the dual-motor drive system to perform a driving operation based on the motor control parameters at the second prediction moment adjacent to the first prediction moment.

2. The method according to claim 1, wherein The step of, according to the predicted vehicle speed sequence, optimizing the motor energy consumption of the dual-motor drive system of the target vehicle during the prediction time period, and outputting the working mode sequence corresponding to the dual-motor drive system during the prediction time period; includes: Construct a drive load model, a motor model corresponding to the dual-motor drive system, and a drive system model corresponding to the dual-motor drive system under different working modes; For any predicted vehicle speed information in the predicted vehicle speed sequence: based on the drive load model, the motor model, and the drive system models corresponding to different working modes, determine the optimal power distribution results corresponding to the dual-motor drive system of the predicted vehicle speed information under different working modes, and obtain a plurality of optimal power distribution results; Analyze the plurality of optimal power distribution results corresponding to each predicted vehicle speed information based on a dynamic programming algorithm, and output the working mode sequence corresponding to the dual-motor drive system during the prediction time period.

3. The method according to claim 2, wherein The step of, based on the drive load model, the motor model, and the drive system models corresponding to different working modes, determining the optimal power distribution results corresponding to the dual-motor drive system of the predicted vehicle speed information under different working modes, and obtaining a plurality of optimal power distribution results; includes: Based on the predicted vehicle speed information, determine the first ring gear speed corresponding to the dual-motor drive system and the first load torque acting on the first ring gear according to the drive load model; For any one of the different operating modes: Based on the first ring gear speed and the first load torque, determine the torque feasible solution and the speed feasible solution corresponding to the dual-motor drive system in the operating mode according to the drive system model corresponding to the operating mode; Based on the torque feasible solution and the speed feasible solution, determine the motor power feasible solution corresponding to the dual-motor drive system in the operating mode according to the motor model; Based on the torque feasible solution, speed feasible solution, and motor power feasible solution corresponding to the dual-motor drive system, determine the optimal power distribution result corresponding to the dual-motor drive system in the operating mode; Based on the optimal power distribution result corresponding to each operating mode, determine several motor power distribution results corresponding to the different operating modes.

4. The method according to claim 3, characterized in that The determining the optimal power distribution result corresponding to the dual-motor drive system in the operating mode based on the torque feasible solution, speed feasible solution, and motor power feasible solution corresponding to the dual-motor drive system includes: Construct a cost function for optimizing the operating mode of the dual-motor drive system with the motor speed change rate as a constraint; Equation (15); Among them, are the rotational speed change amounts of the motor 1 and the motor 2 within 1 s respectively; is the penalty coefficient for the brake action; is the action index of the brake, and its value is equal to the number of brake actions; represents the number of brake actions in mode S; represents the number of brake actions in non-mode S; is the motor power at the k-th step, is the motor power after correction considering the rotational speed change range of the motor; is the rotational speed of the motor 1 in mode T, is the motor power at the k-th step; is the power penalty coefficient; Based on the torque feasible solution, speed feasible solution, and motor power feasible solution corresponding to the dual-motor drive system, use the cost function to determine the optimal motor power distribution result corresponding to the dual-motor drive system in the operating mode.

5. The method according to claim 1, characterized in that It further includes: Based on the maximum value selection rule, select a first discrete interval from the historical speed sequence of the target vehicle at a first preset interval and select a second discrete interval from the historical acceleration sequence of the target vehicle at a second preset interval; wherein, the historical speed sequence and the historical acceleration sequence are obtained by discretely sampling the speed and acceleration of the target vehicle respectively according to a preset sampling time; Obtain several grids formed by the first discrete interval and the second discrete interval, and determine the acceleration transition probability corresponding to each grid at the prediction step; Based on the acceleration transition probability corresponding to each grid, determine the first acceleration transition probability matrix corresponding to the several grids at the prediction step; Based on the first acceleration transition probability matrix corresponding to the several grids at each prediction step, determine the second acceleration transition probability matrix corresponding to the several grids in the prediction domain; wherein, the prediction domain includes several prediction steps; Based on the maximum value selection principle of the acceleration transition probability, generate a vehicle speed prediction model according to the second acceleration transition probability matrix.

6. The method according to claim 3, wherein The operating mode is a single-motor operating mode or a dual-motor operating mode; the single-motor operating mode is the first motor operating mode or the second motor operating mode; the dual-motor operating mode is mode S or dual-motor operating mode T; the method further includes: If the first operating mode in the operating mode sequence is a single-motor operating mode, output the speed and torque corresponding to the first motor in the single-motor operating mode based on the optimal power distribution result, and use the speed and torque corresponding to the first motor as the motor control parameters corresponding to the first operating mode; If the first operating mode in the operating mode sequence is the dual-motor operating mode, the rotational speed and torque corresponding to the first motor in the dual-motor operating mode are output based on the optimal power distribution result; and based on the rotational speed and torque corresponding to the first motor, the rotational speed and torque corresponding to the second motor are determined by using the drive system model corresponding to the first operating mode; the rotational speed and torque corresponding to the first motor and the rotational speed and torque corresponding to the second motor are used as the motor control parameters corresponding to the first operating mode.

7. A control device for a dual-motor drive system, characterized in that, Comprising: A prediction module, configured to perform a prediction process by using a vehicle speed prediction model based on the vehicle speed information corresponding to the target vehicle at the current moment, and output a predicted vehicle speed sequence corresponding to the next prediction time period adjacent to the current moment; wherein, the predicted vehicle speed sequence includes a plurality of predicted vehicle speed information arranged in chronological order; each of the predicted vehicle speed information includes a predicted speed and a corresponding predicted acceleration; An optimization module, configured to optimize the motor energy consumption of the dual-motor drive system of the target vehicle in the prediction time period according to the predicted vehicle speed sequence, and output an operating mode sequence corresponding to the dual-motor drive system in the prediction time period; wherein, the operating mode sequence is used to indicate a set formed by arranging the operating modes corresponding to each prediction moment in the prediction time period in chronological order; A control module, configured to obtain the motor control parameters corresponding to the first operating mode in the operating mode sequence; and control the dual-motor drive system to perform a driving operation based on the motor control parameters at a first prediction moment adjacent to the current moment; A second generation module, configured to control the dual-motor drive system to perform a driving operation based on the motor control parameters at a first prediction moment adjacent to the current moment, and generate actual vehicle speed information corresponding to the target vehicle at the first prediction moment; A fifth determination module, configured to use the actual vehicle speed information corresponding to the first prediction moment as the vehicle speed information corresponding to the target vehicle at the current moment; and determine the operating mode sequence corresponding to the dual-motor drive system in the next prediction time period adjacent to the first prediction moment; The control module is further configured to obtain the motor control parameters corresponding to the first operating mode in the operating mode sequence, and control the dual-motor drive system to perform a driving operation based on the motor control parameters at a second prediction moment adjacent to the first prediction moment.

8. A dual-motor drive system applied to the control method according to any one of claims 1-6, characterized in that, Comprising: A first motor, a second motor, and a power coupling device; the power coupling device is arranged between the first motor and the second motor and is connected to the first motor and the second motor; the power coupling device includes a first planetary gear set, a second planetary gear set, a first brake, a second brake, and a third brake; the power coupling device can adjust the output of the power coupling of the first motor and the second motor based on the first brake, the second brake, and the third brake; The first planetary gear set includes a first ring gear, a first sun gear, and three first planet gears; the first sun gear is disposed at the center of the first ring gear, and the three first planet gears are disposed between the first sun gear and the first ring gear, and each of the first planet gears meshes with the first ring gear and the first sun gear respectively; the bearings of the three first planet gears are connected by a first planet carrier; The second planetary gear set includes a second ring gear, a second sun gear, and three second planet gears; each component of the second planetary gear set has the same connection relationship as each component of the first planetary gear set; The first sun gear and the second sun gear are connected by a bearing; the first ring gear is connected to the second planet carrier; the first motor is connected to the first sun gear by a bearing, the second motor is connected to the second ring gear, the first brake acts on the output shaft of the first motor, the second brake acts on the second ring gear, and the third brake acts on the first planet carrier.

9. A computer-readable medium having a computer program stored thereon, the program, when executed by a processor, implementing the method according to any one of claims 1-6.

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