Control method and device for dual-motor driving system

Abstract

The invention discloses a control method and device for a dual-motor driving system, and the method comprises the steps: carrying out the prediction processing through a vehicle speed prediction model based on the corresponding vehicle speed information of a target vehicle at a current moment, and outputting a predicted vehicle speed sequence corresponding to a next prediction time period adjacent to the current moment; according to the predicted vehicle speed sequence, motor energy consumption of the dual-motor driving system of the target vehicle in the predicted time period is optimized, and a corresponding working mode sequence of the dual-motor driving system in the predicted time period is output; and based on the motor control parameter corresponding to the first working mode in the working mode sequence, controlling the dual-motor driving system to execute driving operation at the first prediction moment. Therefore, according to the double-layer optimization algorithm provided by the embodiment of the invention, the working mode, the motor power and the brake action frequency of the motor driving system are optimized, so that the total energy consumption of the motors of the double-motor driving system is reduced, and the energy management problem of the multi-mode coupling driving system of the pure electric vehicle is solved.

Description

Technical Field

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

[0002] With the deepening of the concept of sustainable development, new energy vehicles have become the future development trend of the automotive industry. As the best-selling type of new energy vehicles, pure electric vehicles and related technologies are developing rapidly. Although the advancement 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 overall efficiency and high motor power demand. The dual-motor coupled drive system can reduce the energy consumption of the drive system through the coupling drive of two motors and the single motor drive;

[0003] For 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, such as: the rule-based energy management strategies are mostly obtained through offline optimization, which cannot consider real-time road conditions, have high comprehensive energy consumption, and cannot 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 energy management strategy based on dynamic programming 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 energy management strategy based on the minimum principle commonly uses polynomial fitting of the motor. Since the accuracy of the motor fitting of this method is poor, the energy management strategy based on the minimum principle is difficult to handle mixed integer optimization problems.

[0004] To this end, the present invention urgently needs to provide an optimization management strategy that can take into account the dynamic performance of the dual-motor drive system during mode switching, 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 coupling drive system of a pure electric vehicle. Summary of the invention

[0005] In view of the above-mentioned 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 a pure electric vehicle, this method can not only reduce the comprehensive energy consumption of the dual-motor drive system, but also improve the computing efficiency of the entire energy management process.

[0006] According to a first aspect of an embodiment of the present invention, a control method for a dual-motor drive system is provided, the method comprising: based on the vehicle speed information corresponding to the target vehicle at the current moment, using a vehicle speed prediction model to perform prediction processing, 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 comprises a plurality of predicted vehicle speed information arranged in chronological order; each of the predicted vehicle speed information comprises a predicted speed and a corresponding predicted acceleration; according to the predicted vehicle speed sequence, the motor energy consumption of the dual-motor drive system of the target vehicle in the prediction time period is optimized, and a working mode sequence corresponding to the dual-motor drive system in the prediction time period is output; wherein the working mode sequence is used to indicate a set of working modes corresponding to each prediction moment in the prediction time period arranged in chronological order; 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 the first prediction moment adjacent to the current moment.

[0007] Optionally, according to the predicted vehicle speed sequence, the motor energy consumption of the dual-motor drive system of the target vehicle in the predicted time period is optimized, and the working mode sequence corresponding to the dual-motor drive system in the predicted time period is output; including: constructing a driving load model and a motor model corresponding to the dual-motor drive system, and a driving 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 driving load model, the motor model, and the driving system model corresponding to different working modes, determining the optimal power allocation result corresponding to the dual-motor drive system of the predicted vehicle speed information in different working modes, and obtaining several optimal power allocation results; analyzing several optimal power allocation results corresponding to each of the predicted vehicle speed information based on a dynamic programming algorithm, and outputting the working mode sequence corresponding to the dual-motor drive system in the predicted time period.

[0008] Optionally, based on the driving load model, the motor model, and the driving system models corresponding to different working modes, the optimal power distribution results corresponding to the dual-motor drive system of the predicted vehicle speed information in different working modes are determined to obtain several 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 driving load model; for any of the different working 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 working mode according to the driving system model corresponding to the working 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 working mode according to the motor model; determining the optimal power distribution result 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; based on the optimal power distribution result corresponding to each of the working modes, determining several motor power distribution results corresponding to the different working modes.

[0009] Optionally, the step of determining the optimal power allocation result corresponding to the dual-motor drive system under the working mode based on the torque feasible solution, speed feasible solution, and motor power feasible solution corresponding to the dual-motor drive system comprises: constructing a cost function for optimizing the working mode of the dual-motor drive system with the motor speed change rate as a constraint;

[0010]

[0011] Δn=max(Δn 1 ,Δn 2 )

[0012]

[0013] n 1,T ≥-2000rpm Formula (15);

[0014] Among them, Δn 1 and Δn 2 are the speed changes of motor 1 and motor 2 within 1s; p B is the penalty coefficient for brake action; I B (k) is the brake action index, and its value is equal to the number of brake actions; I ms (k) indicates the number of brake actions in mode S; 2I ms (k) indicates the number of brake actions in non-mode S; P m (k) is the k-th step motor power, Pm,p (k) is the corrected motor power considering the motor speed variation; n 1,T is the speed of motor 1 in mode T, P m (k) is the motor power at the kth step; is the power penalty coefficient.

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

[0016] Optionally, the method also includes: based on the maximum value selection rule, selecting a first discrete interval from the historical speed sequence of the target vehicle according to a first preset interval, and selecting a second discrete interval from the historical acceleration sequence of the target vehicle according to a second preset interval; wherein the historical speed sequence and the historical acceleration sequence are used to indicate the speed and acceleration of the target vehicle obtained by discrete sampling at a preset sampling time; obtaining a number of grids formed by the first discrete interval and the second discrete interval, and determining the acceleration transfer probability corresponding to each grid at a prediction step; based on the acceleration transfer probability corresponding to each grid, determining a first acceleration transfer probability matrix corresponding to the prediction step of the number of grids; based on the first acceleration transfer probability matrix corresponding to each prediction step of the number of grids, determining a second acceleration transfer probability matrix corresponding to the number of grids in the prediction domain; wherein the prediction domain includes a number of prediction steps; based on the maximum value selection principle of the acceleration transfer probability, generating a vehicle speed prediction model according to the second acceleration transfer 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 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 method also includes: if the first working mode in the working mode sequence is a single-motor working mode, then based on the optimal power allocation result, the speed and torque corresponding to the first motor in the single-motor working mode are output, and the speed and torque corresponding to the first motor are used as motor control parameters corresponding to the first working mode; if the working mode in the working mode sequence is a dual-motor working mode, then based on the optimal power allocation result, the speed and torque corresponding to the first motor in the dual-motor working mode are output; and based on the speed and torque corresponding to the first motor; using the drive system model corresponding to the first working mode to determine the speed and torque corresponding to the second motor; using the speed and torque corresponding to the first motor, and the speed and torque corresponding to the second motor, as motor control parameters corresponding to the first working mode.

[0018] Optionally, the method also includes: at a first predicted 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 predicted moment; using the actual vehicle speed information corresponding to the first predicted moment as the vehicle speed information corresponding to the target vehicle at the current moment; determining a working mode sequence of the dual-motor drive system corresponding to a next predicted time period adjacent to the first predicted 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 predicted moment adjacent to the first predicted moment.

[0019] According to the second aspect of an embodiment of the present invention, a control device for a dual-motor drive system is also provided, the device comprising: a prediction module, for performing prediction processing using a speed prediction model based on the speed information corresponding to the target vehicle at the current moment, and outputting a predicted speed sequence corresponding to the next predicted time period adjacent to the current moment; wherein the predicted speed sequence comprises a plurality of predicted speed information arranged in chronological order; each of the predicted speed information comprises a predicted speed and a corresponding predicted acceleration; an optimization module, for optimizing the motor energy consumption of the dual-motor drive system of the target vehicle in the predicted time period according to the predicted speed sequence, and outputting a working mode sequence corresponding to the dual-motor drive system in the predicted time period; wherein the working mode sequence is used to indicate a set of working modes corresponding to each predicted moment in the predicted time period arranged in chronological order; a control module, for 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 the first predicted moment adjacent to the current moment.

[0020] According to a third aspect of an embodiment of the present invention, a dual-motor drive system is also provided, 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 comprises a first planetary gear row, a second planetary gear row, a first brake, a second brake, and a third brake; the power coupling device can adjust the output of the power coupling between the first motor and the second motor based on the first brake, the second brake, and the third brake; the first planetary gear row comprises a first ring gear, a first sun gear, and three first planetary gears; the first sun gear is arranged at the center of the first ring gear, and the three first planetary gears are arranged on the first Between a sun gear and the first ring gear, each of the first planetary gears is respectively meshed with the first ring gear and the first sun gear; the bearings of the three first planetary gears are connected through a first planet carrier; the second planetary gear row includes a second ring gear, a second sun gear, and three second planetary gears; the components of the second planetary gear row have the same connection relationship with the components of the first planetary gear row; the first sun gear is connected to the second sun gear through a bearing; the first ring gear is connected to the second planet carrier; the first motor is connected to the first sun gear through a bearing, and 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 further provided a computer-readable medium on which a computer program is stored. 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 comprising: first, based on the vehicle speed information corresponding to the target vehicle at the current moment, using a vehicle speed prediction model to perform prediction processing, 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; secondly, according to the predicted vehicle speed sequence, the motor energy consumption of the dual-motor drive system of the target vehicle in the prediction time period is optimized, and a working mode sequence corresponding to the dual-motor drive system in the prediction time period is output; wherein the working mode sequence is used to indicate a set of working modes corresponding to each prediction moment in the prediction time period arranged in chronological order; finally, obtaining a motor control parameter 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 parameter at the first prediction moment adjacent to the current moment. Therefore, the two-layer optimization algorithm proposed in this embodiment takes the motor speed change rate as a constraint, and reduces the total energy consumption of the dual-motor drive system by optimizing the working mode, motor power and brake action frequency of the motor drive system, thereby solving the energy management problem of the multi-mode coupled drive system of pure electric vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Hereinafter, some specific embodiments of the present invention will be described in detail in an exemplary and non-limiting manner with reference to the accompanying drawings. The same reference numerals in the accompanying drawings indicate the same or similar components or parts. It should be understood by those skilled in the art that these drawings are not necessarily drawn to scale. In the accompanying drawings:

[0024] Figure 1 A schematic diagram of the structure of a dual-motor drive system provided in one embodiment of the present invention; wherein FIG a is a schematic diagram of the structure of the dual-motor drive system, and FIG b is a schematic diagram of the structure of the first planetary gear row;

[0025] Figure 2 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 A schematic diagram of the structure of a vehicle speed prediction model in one embodiment of the present invention;

[0027] Figure 4 Schematic diagram of a dynamic planning process involving mode T in an embodiment of the present invention;

[0028] Figure 5 Schematic diagram of a dynamic planning process involving mode S in an embodiment of the present invention;

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

[0030] Figure 7 A schematic diagram of the structure of a dual-motor drive system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0031] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0032] The advantages of rule-based control strategies are that the control logic is relatively simple, the amount of real-time calculation is small, and the performance requirements of the controller are relatively low. Therefore, rule-based control strategies have been widely used. The power allocation and mode selection of rule-based control strategies are completed offline and stored in the controller in the form of a table. In actual use, it is only necessary to look up the table according to the vehicle speed and acceleration information to obtain the corresponding control instructions. However, traditional rule-based control strategies have the following disadvantages: on the one hand, the formulation of rules depends on the experience, professional knowledge and heuristic tuning of the maker, so the rule-based control strategy has high requirements for the maker himself; on the other hand, since the rules are formulated in advance and cannot take into account real-time road conditions, the performance of rule-based control strategies is worse than that of predictive control strategies.

[0033] like Figure 1 , which is a schematic structural diagram of a dual-motor drive system provided in one 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 final 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 row 31, a second planetary gear row 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 between 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 row 31 includes a first ring gear 310, a first sun gear 311, and three first planetary gears 312; the first sun gear 311 is arranged at the center of the first ring gear 310, and the three first planetary gears 312 are arranged between the first sun gear 311 and the first ring gear 310, and each of the first planetary gears 312 is respectively meshed with the first ring gear 310 and the first sun gear 311; the bearings of the three first planetary gears 312 are connected through a first planet carrier 313;

[0036] The second planetary gear row includes a second ring gear, a second sun gear, and three second planetary gears; each component of the second planetary gear row has the same connection relationship as each component of the first planetary gear row;

[0037] The first sun gear 311 is connected to the second sun gear via 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 via a bearing, and 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 of the double planetary gear row in this embodiment can reduce the energy consumption of the drive system by coupling the drive of two motors and driving a single motor. This is because the coupled drive system of the double planetary gear row can have both a speed coupling mode and a torque coupling mode, and has better performance than a dual-motor drive system based on torque coupling. The 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, thereby improving the power of the drive system.

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

[0040]

[0041] like Figure 2 As shown, it is a flow chart of a control method for a dual-motor drive system provided by an embodiment of the present invention; Figure 3 FIG. 1 is a schematic diagram of the structure of a vehicle speed prediction model in one embodiment of the present invention.

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

[0043] S101, based on the vehicle speed information corresponding to the target vehicle at the current moment, a vehicle speed prediction model is used to perform prediction processing, and a predicted vehicle speed sequence corresponding to the next prediction time period adjacent to the current moment is output; 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, optimizing 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 outputting the corresponding working mode sequence of the dual-motor drive system in the prediction time period; wherein the working mode sequence is used to indicate a set of working modes corresponding to each prediction moment in the prediction time period arranged in chronological order;

[0045] S103, 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 first predicted moment adjacent to the current moment.

[0046] In S101, there is no limitation on the method of obtaining the vehicle speed prediction model. The vehicle speed prediction model may be constructed based on the Markov chain principle according to the historical vehicle speed information of the target vehicle; or it may be obtained through model training.

[0047] Specifically, the vehicle speed prediction model based on Markov chain is a random model based on the vehicle historical data set, which can reflect the driver's driving habits, 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 based on 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 random process without aftereffect—Markov chain process.

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

[0049] For example: S1, use a fixed sampling time to discretely sample the speed and acceleration of the working condition, and obtain the historical speed sequence v and historical acceleration sequence as shown in formula (1): According to the selection rules of the maximum velocity and the maximum acceleration, the first discrete interval v is obtained as shown in formula (2): d and the second discrete interval

[0050] S2, using the grids formed by the first discrete interval and the second discrete interval to classify the historical velocity sequence and the historical acceleration sequence respectively, to obtain several grids; for any grid: based on formula (3), calculate the acceleration transfer probability p corresponding to the predicted step length of the grid j,k,z ;

[0051]

[0052] Where l is the prediction step length, C 1 , C 3 are two different acceleration intervals, C 2 is the speed interval; n j,k ,z is to satisfy the three conditions (C 1 , C 2 and C 3 ) The number of sampling points; n j,k is to satisfy C 2 and C 3By repeating formula (3), the acceleration transfer probability corresponding to the prediction step length of each grid in a number of grids can be calculated to obtain the first acceleration transfer probability matrix.

[0053] S3, to obtain the entire prediction domain (1-l max ), the sampling time is set to [1s, 2s, …l max s], and repeat step S2 to obtain the first acceleration transfer probability matrix corresponding to each prediction step length, thereby obtaining the second acceleration transfer probability matrix P corresponding to the entire prediction domain w , P w It can be written as the following formula (4):

[0054] P w =[P 1 ,P 2 ,…P lmax ] Formula (4);

[0055] S4, because when using the acceleration probability transfer matrix to predict acceleration, the result with the largest acceleration transfer probability is usually selected as the predicted value, so in order to improve the efficiency of online calculation, the acceleration prediction in all scenarios is completed offline, and the prediction results are stored in the second acceleration transfer probability matrix. Under a specific prediction step, the prediction results can be used in the vehicle speed prediction model such as Figure 3 The acceleration prediction diagram shown represents that based on the acceleration prediction diagram, the acceleration corresponding to the predicted 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 dual planetary gear drive system.

[0057] According to the predicted vehicle speed sequence, the motor energy consumption of the dual-motor drive system of the target vehicle in the predicted time period is optimized based on a training model or preset rules, and a corresponding working mode sequence of the dual-motor drive system in the predicted time period is output.

[0058] Exemplarily, a driving load model and a motor model corresponding to the dual-motor drive system, as well as a driving system model corresponding to the dual-motor drive system in different working modes are constructed; for any predicted vehicle speed information in the predicted vehicle speed sequence: based on the driving load model, the motor model, and the driving system models corresponding to different working modes, the optimal power allocation results corresponding to the dual-motor drive system of the predicted vehicle speed information in different working modes are determined, and several optimal power allocation results are obtained; based on the dynamic programming algorithm, several optimal power allocation results corresponding to each predicted vehicle speed information are analyzed, and the working mode sequence corresponding to the dual-motor drive system in the predicted time period is output.

[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 model is shown in the following equations (5) and (6):

[0060]

[0061] Among them, n s1 、n r2 and n L They are the speed of the first sun gear, the speed of the second ring gear and the speed of the first ring gear respectively; i p1 and i p2 are the gear ratios of the first ring gear and the first sun gear, and the gear ratios of the second ring gear and the second sun gear, respectively; η 1 represents the transmission efficiency of the internal gear pair formed by the first ring gear and the first planetary gear (or the second ring gear and the second planetary gear); η 2 Indicates 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). s1 and T r2 are the torque acting on the first sun gear and the torque acting on the second ring gear respectively. L is the load torque acting on the first ring gear, which is generated by the acceleration resistance of the target vehicle and the road resistance. Sign(·) is the sign function.

[0062] When the dual-motor drive system is in mode S, the dual-motor drive system has a degree of freedom of 2, and the dual-motor drive system model (the first motor working mode and the second motor working 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 ) L

[0064] Formula (7);

[0065]

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

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

[0068] st

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

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

[0071] The driving load model can be expressed as formula (10):

[0072]

[0073] In the formula, F v The drag is caused by road inclination, tire rolling, aerodynamics, and acceleration. w 、i f , η f are tire radius, main reduction ratio, and main reduction gear transmission efficiency respectively. m V , A V , C d , C t , g, φ, ρ and δ are vehicle mass, vehicle frontal area, drag coefficient, tire rolling friction coefficient, gravitational acceleration, road inclination angle, air density and comprehensive rotational inertia coefficient respectively. v and They are vehicle speed and acceleration.

[0074] Based on the driving load model, the motor model, and the corresponding driving system models under different working modes, a double-layer optimization algorithm is used to determine the optimal power allocation results of the dual-motor drive system under different working modes that predicts vehicle speed information, and several optimal power allocation 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 allocation result. The motor control parameters include: motor speed and motor torque. Since the first predicted 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 predicted moment adjacent to the current moment.

[0076] If the first working mode in the working mode sequence is a single motor working mode, the speed and torque corresponding to the first motor in the single motor working mode are output based on the optimal power allocation result, and the 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 a dual motor working mode, the speed and torque corresponding to the first motor in the dual motor working mode are output based on the optimal power allocation result; and based on the speed and torque corresponding to the first motor; the speed and torque corresponding to the second motor are determined using the drive system model corresponding to the first working mode; the speed and torque corresponding to the first motor, and the 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 a dual motor working mode, the speed and torque corresponding to the first motor are input into the drive system model corresponding to the first working mode, and the speed and torque corresponding to the second motor are output; thereby, the output torque of the dual motor drive system can be 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 user experience.

[0077] This embodiment divides the two-layer optimization algorithm into an upper algorithm and a lower algorithm; the lower algorithm calculates the optimal power distribution results of the motors in different modes according to the driving load model, the motor model, the driving system model, the minimum power method and the step-by-step optimal method, and then substitutes the optimal power distribution results of the motors into the upper algorithm, and uses the dynamic programming algorithm according to the cost function in the upper algorithm to obtain the optimal working mode sequence, and outputs the first working mode of the sequence and the corresponding speed and torque of the first motor. Substitute the speed and torque of the first motor into the driving system model corresponding to the first working mode to obtain the output of the second motor; thereby making the output torque of the dual-motor driving system equal to the driver's expected torque, thereby achieving the purpose of reducing the total energy consumption of the motor by optimizing the driving system working mode, motor power and brake action frequency, so as to take into account the dynamic performance of the driving system during mode switching, the action frequency of the driving system mode switching actuator, and the energy consumption of the driving system, and improve the user experience; and solve the energy management problem of the multi-mode coupling driving system of pure electric vehicles.

[0078] In a preferred implementation manner of this embodiment, the method also includes: at a first predicted moment adjacent to the current moment, controlling the dual-motor drive system to perform a driving operation based on the motor control parameters, generating actual vehicle speed information corresponding to the target vehicle at the first predicted moment; using the actual vehicle speed information corresponding to the first predicted moment as the vehicle speed information corresponding to the target vehicle at the current moment; determining a working mode sequence corresponding to the next predicted time period adjacent to the first predicted moment; 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 predicted moment adjacent to the first predicted moment.

[0079] Specifically, this embodiment predicts the first predicted vehicle speed sequence corresponding to the next predicted time period adjacent to the current moment, and generates the first working mode sequence corresponding to the first predicted vehicle speed sequence; 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 the driving operation at the first predicted moment, and generate the corresponding vehicle speed information; wherein, the first predicted moment is used to indicate the first predicted moment in the next predicted time period adjacent to the current moment. Then, based on the vehicle speed information at the first predicted moment, the second predicted vehicle speed sequence corresponding to the next predicted time period adjacent to the first predicted moment is re-predicted, and the 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 the driving operation at the second predicted moment, and generate the corresponding vehicle speed information; wherein, the second predicted moment is used to indicate the second predicted moment in the next predicted time period adjacent to the current moment, or the first predicted moment in the next predicted time period adjacent to the first predicted 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] Therefore, this embodiment determines the working mode corresponding to the dual-motor drive system at each prediction moment based on a global optimization method, so that the motor control parameters corresponding to each prediction moment can be accurately obtained, effectively reducing the motor energy consumption of the dual-motor drive system, and thus solving the energy management problem of the dual-motor drive system of pure electric vehicles.

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

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

[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 the torque feasible solution and the 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 the 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, the speed feasible solution, and the motor power feasible solution corresponding to the dual-motor drive system, determine the optimal power allocation result corresponding to the dual-motor drive system in the working mode;

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

[0086] For example, the predicted vehicle speed information is substituted into the driving load model shown in equation (10), and the first gear ring speed n corresponding to the dual-motor drive system is outputted. L And the first load torque T acting on the first ring gear L ; For any working mode: set the first gear ring 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 2 Formula (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 Formula (13);

[0096] Mode S:

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

[0098]

[0099] Among them, T e Indicates that in the interval [5, T max ] The torque discrete interval formed by taking different values ​​in interval 1; n 1,S Indicates that in the interval [5, n max ] is a discrete interval of the first motor speed formed by taking different values ​​at intervals of 5.

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

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

[0102] Taking the motor speed change rate as a constraint, a cost function is constructed to optimize the working mode of the dual-motor drive system:

[0103]

[0104] Among them, Δn 1 and Δn 2 are the speed changes of motor 1 and motor 2 within 1s; p B is the penalty coefficient for brake action; I B (k) is the brake action index, and its value is equal to the number of brake actions; I ms (k) indicates the number of brake actions in mode S; 2I ms (k) indicates the number of brake actions in non-mode S; P m (k) is the k-th step motor power, P m,p (k) is the corrected motor power considering the motor speed variation; n 1,T is the speed of motor 1 in mode T, P m (k) is the motor power at the kth step.

[0105] Based on the torque feasible solution, speed feasible solution, and motor power feasible solution corresponding to the dual-motor drive system, the cost function is used to determine the optimal motor power allocation result corresponding to the dual-motor drive system in the working mode.

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

[0107] When the dual-motor drive system has only four working modes, the number of states in dynamic programming is reduced to 4, which is conducive to improving computational efficiency; the feasible speed solution and torque feasible solution corresponding to each working mode are substituted into the cost function of the lower-level algorithm to complete the cost function solution; therefore, the lower-level algorithm is proposed to obtain the optimal power allocation result under each working mode. In order to optimize the computational efficiency while obtaining the optimization result close to dynamic programming, the dynamic programming algorithm is used to analyze several optimal power allocation results corresponding to each predicted vehicle speed information, and the working mode sequence corresponding to the dual-motor drive system in the predicted time period is output.

[0108] From the expressions of motor output in different working modes, it can be seen that the power distribution of the single-motor drive mode is unique, so the lower-level algorithm directly obtains the output of the motor based on the transmission system efficiency model.

[0109] For the dual-motor drive mode, the motor output forms of different dual-motor drive modes are different, so mode T and mode S are discussed separately. When using dynamic programming to directly solve the cost function, all possible motor outputs in equation (13) are regarded as a state point, and the dynamic programming process involving mode T is as follows: Figure 4 Mode k-1 is any state point in the four working modes in step k-1, Mode k+1 is any state point in the four working modes in step k+1. T,i (i=1,2,…n) are all motor outputs in mode T at step k. At step k+1, after Mode k-1 To Mode k+1 The total cost function 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 Formula (16);

[0111] Among them, J k-1 and J k+1 From step 1 to Mode k-1 and Mode k+1 The total cost function of P T,i is the corrected motor power corresponding to mode T at step k. B,T (k) is the brake action index corresponding to the pattern T of the kth step. m,p (k+1) is Mode k+1 Corrected motor power. J k-1 Depending on the operating mode and power allocation from step 1 to step k-1, L k+1 It depends on the working mode of the kth and k+1th steps and the power allocation of the k+1th step. From formula (13), we can see that all Mode T,i The motor speed is the same, so for all Mode T,i and Mode k+1 For p and p B is the same, that is, in Modek-1 The motor speed does not affect the torque distribution under mode T in step k. k+1 The speed will not be affected by the torque distribution of mode T in step k, so J k+1 can 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] Formula (17);

[0114] Therefore, the optimal torque distribution under mode T in step k is the torque distribution when the motor power is the smallest, that is:

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

[0116] Formula (18);

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

[0118] It can be seen from formula (14) that in mode S, all motor outputs have the same output torque and different speeds. The change in motor speed will affect the size of the cost function, which means that the speed distribution of the motor at any step within the prediction range will be affected by the speed distribution of the motor at other steps. In order to simplify the solution process, the suboptimal solution obtained by the step-by-step optimal method is used instead of the global optimal solution. The core of the step-by-step optimal method is to ignore the impact of future states on the current state. The optimal speed distribution of mode S is only determined by the past state and the current state. The dynamic planning process involving mode S is as follows: Figure 5 As shown, Mode1 represents Mode 1, Mode2 represents Mode 2, ModeT represents Mode T, and ModeS represents Mode S. In the figure, each mode represents the motor state in each mode. There are many feasible motor states in the k-1th step, and they will affect the motor speed distribution in Mode S in the kth step. Assuming that in the k-1th step, the motor output in each mode is known, then any state (Mode k+1) The corresponding total cost can be expressed as:

[0119] J k+1 =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

[0120] Formula (19);

[0121] Among them, J k-1,i is the total cost of any mode in the k-1th step, which can be obtained by the recursive formula, so it is assumed to be known in the derivation process. S,i is the corrected motor power corresponding to mode S at step k. From the idea of ​​dynamic programming, we know that P S,i Affected by the mode selection and power allocation in the k-1th step, kth step and k+1th step. If the step-by-step optimal method is used to calculate J k+1 , that is, the motor speed distribution of mode S in the kth step is only affected by the 1st step to the kth 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] Formula (20);

[0124] Definition 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] Formula (21);

[0127] From formula (21), we can see that when calculating J k,S Then, use the stepwise optimization method again to find J k+1 The optimal solution of step k is the motor power allocation corresponding to the minimum value of the total cost of step k, 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] Formula (22);

[0130] That is: n 1,S,op and n 2,S,op They are the speed distribution of the first motor and the second motor in mode S. So far, the lower-level 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, several optimal power allocation results corresponding to each predicted vehicle speed information are analyzed, and a working mode sequence corresponding to the dual-motor drive system in the predicted time period is output.

[0132] The upper-level algorithm uses a dynamic programming algorithm to optimize the working mode sequence corresponding to the dual-motor drive system in the prediction time period. The working mode recursive formula can be simplified as follows (23):

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

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

[0135] Wherein, Mode(k) represents the working mode of the kth step; ms (k) represents the brake action parameter corresponding to the mode switching.

[0136] It should be noted that since the analysis and processing of data based on the dynamic programming algorithm is an existing technology, it will not be introduced in detail here.

[0137] The control strategy based on the double-layer optimization algorithm in this embodiment includes a vehicle speed prediction model that 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, motor power and brake action frequency of the dual-motor drive system, the purpose of reducing the total energy consumption of the motor is achieved, and the dynamic performance of the dual-motor drive system during mode switching, the mode switching actuator action frequency of the dual-motor drive system, and the energy consumption of the dual-motor drive system can be taken into account. 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 the number of brake actions by 11.54% under the premise of constraining the motor speed change amplitude; compared with the predictive control strategy based on dynamic programming, due to the use of the double-layer optimization algorithm, the dynamic programming algorithm can be simplified according to the characteristics of different coupling modes 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 brake action times.

[0138] like Figure 6 , which is a schematic diagram of a predictive control strategy architecture of a two-layer optimization algorithm provided by an embodiment of the present invention.

[0139] The current vehicle speed information of the target vehicle model is obtained, and the current vehicle speed information is processed based on the predictive control strategy of the present invention, and the working mode corresponding to the next predicted moment adjacent to the current moment and the motor control parameters corresponding to the working mode are output; the motor and brake controller controls the dual-motor drive system of the dual planetary gear row to perform the driving operation according to the motor control parameters, and generates the vehicle speed information corresponding to the next predicted moment;

[0140] The implementation process of the predictive control strategy is as follows: Input the acceleration prediction graph of the vehicle speed prediction model and output the predicted acceleration sequence corresponding to the prediction time period Determine the predicted speed sequence corresponding to the predicted acceleration sequence based on the speed prediction formula in the vehicle speed prediction model The predicted acceleration sequence and the predicted speed sequence are input into the two-layer optimization algorithm, and the working mode sequence corresponding to the predicted time period and the speed ω corresponding to the motor 1 of the first working mode Mode in the working mode sequence are output. 1，c and torque T m1,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 corresponding to motor 2 2，c and torque T m2，c . Set the speed ω 1，c ,ω 2，c and torque T 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 The dual-motor drive system that controls the dual planetary gear row performs a driving operation to generate an actual vehicle speed v of the target vehicle.

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

[0142] like Figure 7 , which is a schematic diagram of the structure 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 comprising: a prediction module 701, for performing prediction processing based on the speed information corresponding to the target vehicle at the current moment, using a speed prediction model, and outputting a predicted speed sequence corresponding to the next predicted time period adjacent to the current moment; wherein the predicted speed sequence comprises a plurality of predicted speed information arranged in chronological order; each predicted speed information comprises a predicted speed and a corresponding predicted acceleration; an optimization module 702, for optimizing the motor energy consumption of the dual-motor drive system of the target vehicle in the predicted time period according to the predicted speed sequence, and outputting a working mode sequence corresponding to the dual-motor drive system in the predicted time period; wherein the working mode sequence is used to indicate a set of working modes corresponding to each predicted moment in the predicted time period arranged in chronological order; a control module 703, for 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 the first predicted moment adjacent to the current moment.

[0144] In a preferred implementation manner of this embodiment, the optimization module includes: a model building unit, used to build a driving load model and a motor model corresponding to the dual-motor drive system, and a driving system model corresponding to the dual-motor drive system in different working modes; a determination unit, used to determine, for any predicted vehicle speed information in the predicted vehicle speed sequence: based on the driving load model, the motor model, and the corresponding driving system models in different working modes, the optimal power allocation result corresponding to the dual-motor drive system of the predicted vehicle speed information under different working modes, and obtain several optimal power allocation results; an analysis unit, used to analyze several optimal power allocation results corresponding to each of the predicted vehicle speed information based on a dynamic programming algorithm, and output the working mode sequence corresponding to the dual-motor drive system in the predicted time period.

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

[0146] In a preferred implementation of this embodiment, the second determining subunit includes: a construction unit, configured to construct 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] Among them, Δn 1 and Δn 2 are the speed changes of motor 1 and motor 2 within 1s; p B is the penalty coefficient for brake action; I B (k) is the brake action index, and its value is equal to the number of brake actions; I ms (k) indicates the number of brake actions in mode S; 2I ms(k) indicates the number of brake actions in non-mode S; P m (k) is the k-th step motor power, P m,p (k) is the corrected motor power considering the motor speed variation; n 1,T is the speed of motor 1 in mode T, P m (k) is the motor power at the kth step.

[0149] A determination unit is used to determine the optimal motor power allocation result 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, using the cost function.

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

[0151] In a preferred implementation manner of this 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 also includes: a third determination module, which is used to output the speed and torque corresponding to the first motor in the single-motor working mode based on the optimal power allocation result if the first working mode in the working mode sequence is a single-motor working mode, and use the speed and torque corresponding to the first motor as the motor control parameters corresponding to the first working mode; a fourth determination module, which is used to output the speed and torque corresponding to the first motor in the dual-motor working mode based on the optimal power allocation result if the first working mode in the working mode sequence is a dual-motor working mode; and based on the speed and torque corresponding to the first motor; using the drive system model corresponding to the first working mode to determine the speed and torque corresponding to the second motor; using the speed and torque corresponding to the first motor, and the speed and torque corresponding to the second motor, as the motor control parameters corresponding to the first working mode.

[0152] In a preferred implementation manner of this embodiment, the device also includes: a second generation module, used to control the dual-motor drive system to perform a driving operation based on the motor control parameters at a first predicted moment adjacent to the current moment, and generate actual vehicle speed information corresponding to the target vehicle at the first predicted moment; a fifth determination module, used to use the actual vehicle speed information corresponding to the first predicted moment as the vehicle speed information corresponding to the target vehicle at the current moment; determine the working mode sequence corresponding to the next predicted time period adjacent to the first predicted moment of the dual-motor drive system; the control module is also used 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 a second predicted moment adjacent to the first predicted moment.

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

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

[0155] In addition to the above-mentioned methods and devices, an embodiment of the present application may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present application described in the above-mentioned "Exemplary Method" section of this specification.

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

[0157] In addition, an embodiment of the present application may also be a computer-readable storage medium on which computer program instructions are stored. When the computer program instructions are executed by a processor, the processor executes the steps of the method according to the following embodiments of the present application described in the above "Exemplary Method" section of this specification.

[0158] The computer readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with 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 are described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, effects, etc. mentioned in the present application are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required by each embodiment of the present application. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, not for limitation, and the above details do not limit the present application to being implemented by adopting the above specific details.

[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 diagram. As will be appreciated by those skilled in the art, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The words "such as" used here refer to the phrase "such as but not limited to", and can be used interchangeably with them.

[0161] It should also be noted that in the apparatus, device and method of the present application, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present application.

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

[0163] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present 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, changes, additions and sub-combinations thereof.

[0164] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction 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 may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0165] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0166] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A control method for a dual-motor drive system, characterized in that: include: Based on the vehicle speed information corresponding to the target vehicle at the current moment, a vehicle speed prediction model is used to perform prediction processing, and a predicted vehicle speed sequence corresponding to the next prediction time period adjacent to the current moment is output; 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, the motor energy consumption of the dual-motor drive system of the target vehicle in the predicted time period is optimized, and the working mode sequence corresponding to the dual-motor drive system in the predicted time period is output; wherein the working mode sequence is used to indicate a set of working modes corresponding to each predicted moment in the predicted time period arranged in chronological order; Acquire motor control parameters corresponding to a 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 predicted moment adjacent to the current moment.

2. The method according to claim 1, characterized in that The step of optimizing the motor energy consumption of the dual-motor drive system of the target vehicle in the predicted time period according to the predicted vehicle speed sequence, and outputting the operating mode sequence of the dual-motor drive system corresponding to the predicted time period, comprises: Constructing a driving load model and a motor model corresponding to the dual-motor driving system, and a driving system model corresponding to the dual-motor driving 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 allocation result corresponding to the dual-motor drive system of the predicted vehicle speed information in different working modes, and obtain a plurality of optimal power allocation results; Based on the dynamic programming algorithm, several optimal power allocation results corresponding to each predicted vehicle speed information are analyzed, and a working mode sequence corresponding to the dual-motor drive system in the predicted time period is output.

3. The method according to claim 2, characterized in that The method of determining the optimal power allocation results of the dual-motor drive system under different working modes based on the driving load model, the motor model, and the drive system models corresponding to different working modes, and obtaining a plurality of optimal power allocation results, includes: 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; For any of the different working 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 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 the 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, the speed feasible solution, and the motor power feasible solution corresponding to the dual-motor drive system, determine the optimal power allocation result corresponding to the dual-motor drive system in the working mode; Based on the optimal power allocation result corresponding to each of the working modes, several motor power allocation results corresponding to the different working modes are determined.

4. The method according to claim 3, characterized in that The method of determining the optimal power allocation result 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 comprises: Constructing a cost function for optimizing the working mode of the dual-motor drive system based on the motor speed change rate constraint; Among them, Δn1 and Δn2 are the speed changes of motor 1 and motor 2 within 1s respectively; p B is the penalty coefficient for brake action; I B (k) is the brake action index, and its value is equal to the number of brake actions; I ms (k) indicates the number of brake actions in mode S; 2I ms (k) indicates the number of brake actions in non-mode S; P m (k) is the k-th step motor power, P m,p (k) is the corrected motor power considering the motor speed variation; n 1,T is the speed of motor 1 in mode T, P m (k) is the motor power at the kth 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, the cost function is used to determine the optimal motor power allocation result corresponding to the dual-motor drive system in the working mode.

5. The method according to claim 1, characterized in that: Also includes: Based on the maximum value selection rule, a first discrete interval is selected from the historical speed sequence of the target vehicle according to a first preset interval, and a second discrete interval is selected from the historical acceleration sequence of the target vehicle according to a second preset interval; wherein the historical speed sequence and the historical acceleration sequence are used to indicate the speed and acceleration of the target vehicle obtained by discrete sampling at a preset sampling time, respectively; Acquire a plurality of grids formed by the first discrete interval and the second discrete interval, and determine the acceleration transfer probability corresponding to the prediction step length of each grid; Based on the acceleration transfer probability corresponding to each of the grids, determining a first acceleration transfer probability matrix corresponding to the prediction step length of the plurality of grids; Determine, based on the first acceleration transfer probability matrix corresponding to each of the prediction steps of the plurality of grids, the second acceleration transfer 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 transfer probability, a vehicle speed prediction model is generated according to the second acceleration transfer probability matrix.

6. The method according to claim 3, characterized in that 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 method further includes: If the first working mode in the working mode sequence is a single-motor working mode, outputting the speed and torque corresponding to the first motor in the single-motor working mode based on the optimal power allocation result, and using the speed and torque corresponding to the first motor 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 speed and torque corresponding to the first motor in the dual-motor working mode are output based on the optimal power allocation result; and based on the speed and torque corresponding to the first motor; the speed and torque corresponding to the second motor are determined using the drive system model corresponding to the first working mode; the speed and torque corresponding to the first motor, and the speed and torque corresponding to the second motor are used as motor control parameters corresponding to the first working mode.

7. The method according to claim 1, characterized in that Also includes: At a first predicted time adjacent to the current time, controlling the dual-motor drive system to perform a drive operation based on the motor control parameter to generate actual vehicle speed information corresponding to the first predicted time of the target vehicle; 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 the operating mode sequence of the dual-motor drive system corresponding to the next prediction time period adjacent to the first prediction moment; The motor control parameters corresponding to the first working mode in the working mode sequence are obtained, and the dual-motor drive system is controlled to perform a driving operation based on the motor control parameters at a second prediction time adjacent to the first prediction time.

8. A control device for a dual-motor drive system, characterized in that: include: A prediction module, used to perform prediction processing using a speed prediction model based on the speed information corresponding to the target vehicle at the current moment, and output a predicted speed sequence corresponding to the next prediction time period adjacent to the current moment; wherein the predicted speed sequence includes a plurality of predicted speed information arranged in chronological order; each of the predicted 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 a corresponding working mode sequence of the dual-motor drive system in the prediction time period; wherein the working mode sequence is used to indicate a set of working modes corresponding to each prediction moment in the prediction time period arranged in chronological order; The control module is used 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 a first predicted moment adjacent to the current moment.

9. A dual-motor drive system, characterized in that: include: 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 connected to the first motor and the second motor; the power coupling device comprises a first planetary gear row, a second planetary gear row, a first brake, a second brake, and a third brake; the power coupling device can adjust the output of the power coupling between the first motor and the second motor based on the first brake, the second brake, and the third brake; The first planetary gear row includes a first ring gear, a first sun gear, and three first planetary gears; the first sun gear is arranged at the center of the first ring gear, the three first planetary gears are arranged between the first sun gear and the first ring gear, and each of the first planetary gears is respectively meshed with the first ring gear and the first sun gear; the bearings of the three first planetary gears are connected through a first planet carrier; The second planetary gear row includes a second ring gear, a second sun gear, and three second planetary gears; each component of the second planetary gear row has the same connection relationship as each component of the first planetary gear row; The first sun gear is connected to the second sun gear via a bearing; the first ring gear is connected to the second planet carrier; the first motor is connected to the first sun gear via 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.

10. A computer readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method according to any one of claims 1 to 7.

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