Energy efficiency optimization method and system for electric four-wheel-drive automobile and storage medium

Abstract

The invention discloses an energy efficiency optimization method and system for an electric four-wheel-drive automobile and a storage medium, and belongs to the technical field of automobile energy efficiency optimization. The method comprises the following steps: constructing a motor energy efficiency model according to motor parameters used by an automobile, and obtaining the driving efficiency of the whole automobile; reversely deducing energy efficiency characteristic parameters according to the running state of the motor; an optimal performance function of the whole vehicle without motion control is constructed, and the optimal torque of a single motor is calculated; designing an optimal energy efficiency torque distribution model according to the energy efficiency characteristic parameters, the motor energy efficiency model and the optimal torque of the single motor; obtaining automobile stability parameters through a phase plane method, and performing coupling optimization on the automobile stability parameters and the energy efficiency characteristic parameters by adopting game control of a Nash equilibrium principle to obtain weight parameters; and endowing the weight parameters to an energy efficiency torque distribution model to calculate the additional yawing moment of four wheels. According to the method, the situation that double-output results are generated in the control process due to mutual contradiction between energy-saving optimization and stability margin in automobile control is avoided.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of automobile energy efficiency optimization, and particularly relates to an energy efficiency optimization method and system for an electric four-wheel drive automobile and a storage medium. BACKGROUND

[0002] In the current control method of electric four-wheel drive automobiles, the most commonly used method is torque vectoring distribution, which distributes the longitudinal acceleration torque and additional yaw torque of the automobile to the four wheel hub motors of the four-wheel independent drive automobile according to the automobile dynamics model. Through the output characteristics and operating conditions of the four-wheel motors, the output power can be increased or decreased to obtain the control effect.

[0003] In the control of four-wheel independent drive electric automobiles, additional yaw torque control is a common means. It obtains the target value of the motion state of the automobile through automobile dynamics, and according to the difference between the current automobile state and the target value, a specific algorithm is used to obtain the additional lateral torque applied to the automobile to stabilize the lateral motion state of the automobile.

[0004] For example, Chinese patent document CN202410217134.2 discloses a distributed electric vehicle multi-agent coordination control method based on cooperative game. First, the subsystems of the distributed electric vehicle are divided into six agents, and a dynamic model representing the agents of each subsystem is constructed. The state information of the vehicle is collected in real time by the vehicle-mounted sensor, the T-S fuzzy theory is used to process the nonlinear problems caused by the change of vehicle speed, the dynamic coordination control strategy of the distributed electric vehicle subsystem is established based on the cooperative game theory, and finally, the robust compensation control strategy is established to realize the cooperative driving method.

[0005] Chinese patent document CN202010396171.6 discloses a torque optimization distribution control method for four-wheel drive electric vehicles. The motor efficiency calculation model under driving, coasting and starting conditions is developed, the vehicle driving mode is divided into dual-axle driving mode, single-axle driving mode, dual-axle starting mode and single-axle starting mode, the power consumption calculation method under different modes is determined, the torque distribution coefficient is obtained by offline global optimization algorithm to optimize energy, the dynamic weight factor is determined by fuzzy control rule, and finally the four-wheel torque distribution result is determined.

[0006] The above patents have produced effects on the optimization of energy output of the automobile, but none of them mentions the mechanism of energy consumption in the operation of the motor, and none of them optimizes the deeper energy loss. This will lead to the fact that the energy efficiency optimization methods of the vehicle under different conditions are not unified, and the energy efficiency and stability of the automobile cannot meet the control target requirements. SUMMARY

[0007] In view of the deficiencies of the prior art, the purpose of the present application is to provide an energy efficiency optimization method and system for an electric four-wheel drive vehicle and a storage medium, which solve the problems in the prior art.

[0008] The purpose of the present application can be achieved by the following technical solutions:

[0009] An energy efficiency optimization method for an electric four-wheel drive vehicle comprises the following steps:

[0010] According to the motor parameters used by the vehicle, a motor energy efficiency model is constructed, and the overall vehicle driving efficiency is obtained;

[0011] According to the motor energy efficiency model, the energy efficiency characteristic parameters are back-calculated from the motor operating state, and the optimal performance function of the overall vehicle without motion control is constructed according to the overall vehicle driving efficiency, and the optimal torque of the single motor is calculated;

[0012] According to the energy efficiency characteristic parameters, the motor energy efficiency model, and the optimal torque of the single motor, an optimal energy efficiency torque distribution model is designed;

[0013] The vehicle stability parameters are obtained by the phase plane method, and the Nash equilibrium principle game control is used to couple and optimize the vehicle stability parameters and the energy efficiency characteristic parameters, and the weight parameters are obtained;

[0014] The weight parameters are assigned to the energy efficiency torque distribution model to calculate the additional yaw moment of the four wheels.

[0015] Further, characterized in that the motor energy efficiency model is:

[0016]

[0017] P motor =ai q 2 +bi q 2 n 2 +ci q n+dn+en 2 +Const

[0018]

[0019] T=pi q k e

[0020] wherein η i is the output efficiency of the motor numbered i (i = fl, fr, rl, rr), fl, fr, rl, and rr represent the corresponding tire orientation of the motor in the vehicle body, in order: front left, front right, rear left, and rear right; P outi is the output power of the motor numbered i, P motoriP is the energy consumption power of the motor numbered i; P motor P is the motor consumption power; a, b, c, d, e and Const are all equivalent state parameters of the motor, and the initial values thereof are calculated as follows: a = R a 、 R a R is an equivalent resistance of a stator of the motor, R i k is an equivalent resistance of iron loss of the motor, k m K is a friction loss coefficient of rotation of the motor, K e L is an amplitude of a magnetic flux of a permanent magnet of the motor, L d L is an equivalent inductance of a direct axis of the motor, L q L is an equivalent inductance of a cross axis of the motor; P out P is an output power of the motor; p is a number of pole pairs of the motor.

[0021] Further, the whole vehicle driving efficiency η is:

[0022]

[0023] wherein P outfl , P outfr , P outrl and P outrr respectively represent output powers of left front, right front, left rear and right rear motors; P motorfl , P motorfr , P motorrl and P motorrr respectively represent energy consumption powers of the left front, right front, left rear and right rear motors.

[0024] Further, a process of calculating the optimal torque of a single motor according to the energy efficiency characteristic parameter comprises:

[0025] 1) calculating a single motor energy efficiency function:

[0026]

[0027] 2) obtaining a derivative of the single motor energy efficiency function about the cross axis current i q :

[0028]

[0029] The cross axis current i qbest of the optimal efficiency is a positive value:

[0030]

[0031] 3) calculating the optimal torque T besti of the single motor according to a torque formula:

[0032]

[0033] Further, the optimal performance function of the whole vehicle under the motionless control is:

[0034]

[0035] P Me =∑a i T i 2 +b i T i 2 n i 2 +c i T i n i p i K ei +p i 2 K ei 2 (T i n i +Const i )

[0036] Wherein, J motor is the optimal performance function of the whole vehicle under the motionless control; P Mout is the total output power of the four motors, P Me is the total power consumption of the four motors, t mi is the weight coefficient corresponding to the motor numbered i.

[0037] Further, the step of designing the optimal energy efficiency torque distribution model comprises:

[0038] Step 1, according to the optimal performance function of the whole vehicle under the motionless control, considering the motion state and energy consumption state of the automobile, the energy efficiency optimization final performance function is designed as:

[0039] J energy (T energy )=α1J motor (T)+α2J yaw (T)

[0040] Wherein, J energy is the energy efficiency optimization final performance function, α1 and α2 are the weight coefficients of the game intensity in the energy efficiency optimization algorithm; ρ is the stability parameter obtained in the stability control, J yaw is the cost function representing the compromise to the motion state of the automobile, J yaw = (M Z (T)-M zout ) 2 , M Z(T) is the additional yaw moment obtained by optimizing energy efficiency, M zout is the additional yaw moment output by the vehicle stability control;

[0041] Step 2: using the quadratic programming method to solve the performance function designed in step 1, the optimal energy efficiency torque distribution model can be obtained.

[0042] An energy efficiency optimization system of an electric four-wheel drive vehicle, comprising:

[0043] An energy efficiency model construction module: constructing an energy efficiency model of the motor according to the motor parameters used by the vehicle, and obtaining the overall vehicle driving efficiency;

[0044] A parameter calculation module: according to the energy efficiency model of the motor, the energy efficiency characteristic parameters are back calculated through the motor operating state; and according to the overall vehicle driving efficiency, the optimal performance function of the overall vehicle without motion control is constructed, and the best torque of the single motor is calculated;

[0045] A distribution model design module: according to the energy efficiency characteristic parameters, the energy efficiency model of the motor and the best torque of the single motor, the optimal energy efficiency torque distribution model is designed;

[0046] A weight solving module: the vehicle stability parameters are obtained through the phase plane method, and the vehicle stability parameters and the energy efficiency characteristic parameters are coupled and optimized by using the game control of the Nash equilibrium principle, so that the weight parameters are obtained;

[0047] A torque distribution module: the weight parameters are assigned to the energy efficiency torque distribution model to calculate the additional yaw moment of the four wheels.

[0048] A computer storage medium, storing a readable program, when the program runs, the program can instruct a computing device to execute an energy efficiency optimization method of an electric four-wheel drive vehicle as described above.

[0049] An electronic device, comprising: a processor, a memory, a communication interface and a communication bus, the processor, the memory and the communication interface complete the communication among each other through the communication bus;

[0050] The memory is used to store at least one executable instruction, and the executable instruction makes the processor execute the operation corresponding to the energy efficiency optimization method of the electric four-wheel drive vehicle as described above.

[0051] A computer program product, comprising computer instructions, the computer instructions instruct a computing device to execute the operation corresponding to the energy efficiency optimization method of the electric four-wheel drive vehicle as described above.

[0052] The beneficial effects of the present application are:

[0053] 1. The single motor internal energy efficiency model is designed based on motor control and driving model, and a motor efficiency observer is constructed with motor control feedback parameters as variables, so that the influence of actual driving environment and long-time operation on the motor internal parameters is avoided, the efficiency cloud map of the automobile cannot accurately reflect the motor efficiency due to the change of the motor internal parameters.

[0054] 2. Based on the single motor energy efficiency model, the optimal torque of each motor is obtained, and the optimal torque of four motors is designed; combined with the four-wheel torque state, the mutual influence of the four-wheel motors is avoided, and the single motor maintains high efficiency under the four-wheel coupling condition.

[0055] 3. Based on the single motor energy efficiency model, the whole vehicle energy efficiency model is obtained, the driving efficiency and energy consumption of the vehicle are more accurate, and the controller is limited to the efficiency of the single motor and cannot accurately control the overall efficiency of the four motors.

[0056] 4. Based on the single motor energy efficiency model and the whole vehicle energy efficiency model, the torque distribution strategy is improved through the vehicle battery state and the motor state, so that the single motor energy consumption and the whole vehicle energy consumption are coordinated and consistent during the running process of the automobile; the total output efficiency of the automobile driving system in the running process is improved, and the stability of the motor operating state is ensured.

[0057] 5. Based on the whole vehicle energy efficiency torque distribution strategy, combined with the automobile motion demand, a torque distribution method further matching the automobile energy consumption is designed, which is combined with the additional yaw moment to widen the range of automobile energy efficiency that can be improved; the coordination consistency of the whole vehicle is strengthened, and the flexibility of the control algorithm of the vehicle in different motion states is enhanced.

[0058] 6. Based on the phase plane method and the integrated automobile model, the dynamic variable range of the additional yaw moment is obtained, the optimization range of the multi-objective optimization of the vehicle is widened, and more space is allocated to other optimization objectives under the condition that the automobile has sufficient stability margin.

[0059] 7. The stability observation and control method is used, the energy efficiency optimization and stability margin management are balanced as two ends of non-cooperative game, so that the stability and economy in the running process are kept in a high range; the mutual contradiction between energy saving optimization and stability margin in automobile control is avoided, which leads to the result of double loss in the control process.

[0060] 8. The game method is used, the weight function of the lower torque vector distribution is generated combined with the automobile motion state, the automobile motor state and the automobile battery state, the accuracy of the automobile torque distribution is improved, and the applicability of the torque vector distribution under different conditions is improved. BRIEF DESCRIPTION OF DRAWINGS

[0061] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0062] Figure 1 This is a block diagram of the energy efficiency optimization control of the present invention;

[0063] Figure 2 This refers to the range of motor energy flow in this invention;

[0064] Figure 3 This is the equivalent diagram of motor energy consumption of the present invention;

[0065] Figure 4 This is a diagram of the vehicle dynamics model of the present invention;

[0066] Figure 5 This is a phase plan view of the vehicle state according to the present invention;

[0067] Figure 6 This involves comparing the performance of a car under different control algorithms when accelerating from its normal driving speed (60km / h) to its overtaking speed (90km / h) under overtaking conditions, with the driving trajectory being a double-line trajectory.

[0068] Figure 7 This is a comparison of vehicle performance under normal speed lane changing conditions, with the vehicle speed maintained at 60km / h and the driving trajectory being a left lane change followed by straightening and driving straight. Detailed Implementation

[0069] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0070] Example 1

[0071] like Figure 1 As shown, an energy efficiency optimization method for an electric four-wheel drive vehicle includes the following steps:

[0072] S1. Based on the parameters of the motor used in the car, construct a motor energy efficiency model and obtain the overall vehicle drive efficiency;

[0073] Through the motor control unit, by Figure 2 The range of energy flow within the motor is obtained, and based on this range, four parameters of the motor's internal structure are derived: quadrature-axis current i. q( Figure 2 The middle blue part), the direct axis current i d ( Figure 2 The middle green part), the torque T and the speed n Figure 2 The middle red part); and then the motor efficiency model is constructed with the above four parameters; the specific content includes:

[0074] The motor input model is:

[0075] T=pi q k e

[0076] Wherein, p is the motor pole pair number, k e is the motor permanent magnet flux amplitude;

[0077] The motor output model is:

[0078]

[0079] Wherein, P out is the motor output power;

[0080] The motor energy consumption model is:

[0081] P motor =ai q 2 +bi q 2 n 2 +ci q n+dn+en 2 +Const

[0082] Wherein, P motor is the motor consumption power, a, b, c, d, e and Const are all motor equivalent state parameters, representing the different relationships between the control current and the speed and the consumption power, and the initial values are calculated as follows:

[0083] a=R a 、 d=k m 、 Wherein, R a is the motor stator equivalent resistance, R i is the motor iron loss equivalent resistance, k m is the motor rotating friction loss coefficient, K e is the permanent magnet flux amplitude, L d is the motor direct axis equivalent inductance, L q is the motor cross axis equivalent inductance, and the specific classification source can be obtained from Figure 3 .

[0084] The motor efficiency model is:

[0085]

[0086] wherein η i is the output efficiency of the motor numbered i (i = fl, fr, rl, rr), fl, fr, rl, rr represent the corresponding tire orientation of the motor in the vehicle body, in turn: front left, front right, rear left, rear right; P outi is the output power of the motor numbered i, P motori is the energy consumption power of the motor numbered i.

[0087] According to the total energy consumption of the four motors and the total output of the four motors as parameters, the whole vehicle driving efficiency η is constructed:

[0088]

[0089] wherein P outfl , P outfr , P outrl and P outrr represent the output power of the front left, front right, rear left and rear right motors respectively; P motorfl , P motorfr , P motorrl and P motorrr represent the energy consumption power of the front left, front right, rear left and rear right motors respectively;

[0090] S2, according to the motor energy efficiency model, the energy efficiency characteristic parameters are backstepped through the motor operating state, and the optimal torque of the single motor is calculated according to the whole vehicle driving efficiency, and the optimal performance function of the whole vehicle under the condition of no motion control is established by the whole vehicle driving efficiency and the optimal torque of the single motor;

[0091] The step of backstepping the energy efficiency characteristic parameters comprises:

[0092] 1) Obtain the motor consumption power P motor and the motor output power P out ; Record the motor consumption power P motor , the motor output power P out , the quadrature axis current i q , the direct axis current i d , the torque T and the speed n in the adjacent four time points as the calculation parameters;

[0093] 2) Take the following formula as an observer to backstep and calculate the energy efficiency characteristic parameters:

[0094]

[0095] P motor = ai q 2 + bi q2 n 2 +ci q n+dn+en 2 +Const

[0096] The calculated energy efficiency characteristic parameters include: a, b, c, d, e, Const.

[0097] The process of calculating the optimal torque of the single motor according to the energy efficiency characteristic parameters includes:

[0098] 1) The energy efficiency function of the motor condition is obtained as:

[0099]

[0100] 2) The derivative of the function with respect to the quadrature axis current i q is:

[0101]

[0102] Considering that the car mainly advances in the display operation, the optimal efficiency quadrature axis current i qbest is positive:

[0103]

[0104] 3) The optimal torque T besti of the single motor is calculated according to the torque formula:

[0105]

[0106] The process of the optimal performance function of the whole car under the no motion control is as follows:

[0107] 1) The total efficiency function of the whole car is obtained according to the whole car driving efficiency function: is the total output power of the four motors, P Me =∑a i T i 2 +b i T i 2 n i 2 +c i T i n i p i K ei +p i 2 K ei 2 (T i n i +Const i ) is the total power consumption of the four motors, and the total efficiency is wherein, Kei The permanent magnet flux linkage amplitude of the numbered i motor;

[0108] 2) According to the single motor optimal efficiency, so that the output torque of each motor is close to its optimal torque ∑(T i -T besti ) 2 ;

[0109] 3) Since the performance function is to solve its minimum value in the optimization process, the calculation method of the overall optimal performance is

[0110] 4) Considering that each motor needs different weights due to its characteristics, the weight coefficient t mi of the numbered i motor is designed to maintain the overall safety of the function, has and the sum of the weight coefficients SOC is the state of charge of the battery.

[0111] The optimal performance function of the whole vehicle under no motion control is:

[0112]

[0113] Where J motor is the optimal performance function of the whole vehicle under no motion control.

[0114] S3, according to the energy efficiency characteristic parameters, motor energy efficiency model and single motor optimal torque, design optimal energy efficiency torque distribution model;

[0115] The steps of designing the optimal energy efficiency torque distribution model include:

[0116] In order to play against stability control, therefore, the energy efficiency optimization is given countermeasures, so that it can not comply with the additional yaw moment control, but in order to ensure the stability of the car, the cost function J yaw =(M Z (T)-M zout ) 2 , wherein M Z (T) is the additional yaw moment output by the energy efficiency optimization, M zout is the additional yaw moment output by the stability control;

[0117] According to the optimal performance function of the whole vehicle under no motion control obtained in S2 Considering the motion state and energy consumption state of the vehicle, the final energy efficiency optimization performance function is designed as:

[0118] J energy (T energy )=α1J motor (T)+α2J yaw (T)

[0119] wherein J energy is the energy efficiency optimization final performance function, and α1, α2 are weight coefficients of game strength in the energy efficiency optimization algorithm. ρ is the stability parameter obtained in the stability control.

[0120] The function is solved by using a quadratic programming method to obtain an optimal energy efficiency torque distribution model; the matrix used in the quadratic programming solution of the optimal energy efficiency torque distribution model is:

[0121]

[0122] In the formula, Mzfl represents the influence of the left front wheel torque on the additional yaw moment, Mzfr represents the influence of the right front wheel torque on the additional yaw moment, and Mzr represents the influence of the rear wheel torque on the additional yaw moment, and the remaining parameters are provided by the vehicle dynamics model shown in Figure 4 L f is the front wheelbase of the vehicle, t wf is the front track of the vehicle, t wr is the rear track of the vehicle, δ f is the front wheel angle of the vehicle, r is the dynamic radius of the tire of the vehicle, M z is the additional yaw moment transmitted by the stability control in the game process, H 11 to H 44 is an intermediate parameter in the quadratic programming matrix.

[0123] S4, the automobile stability parameter is obtained by the phase plane method, and the game control based on the Nash equilibrium principle is used to couple and optimize the automobile stability parameter and the energy efficiency characteristic parameter to obtain the weight parameter;

[0124] The distance from the current state of the automobile to the boundary of the stability domain is obtained by the phase plane method, and then the automobile stability parameter ρ is obtained by corresponding different distances to different numerical values of the automobile stability parameter.

[0125] According to the automobile phase plane diagram shown in Figure 5 It can be divided into:

[0126] 1) ideal stability region;

[0127] 2) yaw rate instability region;

[0128] 3) stable but poor handling performance region;

[0129] 4) unstable region;

[0130] The stability domain can be equivalent to:

[0131]

[0132] In the formula, vx is the longitudinal speed of the vehicle, μ is the road adhesion coefficient, p1 to p9 are the stability boundary parameters obtained from the simulation of the planar surface under laboratory conditions according to the vehicle body parameters, λ1 to λ3 represent the calculation parameters of the stability boundary, and β is the vehicle's mass center side slip angle.

[0133] According to the coefficients of the stability domain, the mass center side slip angle and the yaw rate of the vehicle's motion state are calculated to limit the range:

[0134]

[0135] In the formula, β max ,β min are the upper and lower boundaries of the mass center side slip angle, γ max ,γ min are the upper and lower boundaries of the yaw rate, β is the rate of change of the mass center side slip angle, and g is the gravitational constant.

[0136] The stability condition can be obtained from the distance between the mass center side slip angle and the yaw rate and the boundary:

[0137]

[0138] where γ is the yaw rate, I β ,I γ are the stability evaluations of the mass center side slip angle and the yaw rate, respectively, and I actual is the final stability evaluation

[0139] The stability parameter ρ is:

[0140]

[0141] In the formula, z is a self-set boundary parameter, and a battery state SOC is generally used;

[0142] The steps of coupling optimization of the vehicle stability parameters and the energy efficiency characteristic parameters to obtain the weight parameters include:

[0143] 1) The additional yaw moment obtained by the method can be calculated according to the vehicle body dynamics through the four-motor distributed power obtained by the energy efficiency optimization, and the rate of change of the mass center side slip angle under the distribution strategy is:

[0144]

[0145] where C af ,C ar are the side stiffness of the front and rear wheels of the vehicle, l f ,l r are the front and rear wheelbases of the vehicle, and C is the matrix for calculating the additional yaw moment by the vehicle body dynamics, and Tenergy Four-wheel torque distribution for energy efficiency optimization

[0146] 2) The current state of the vehicle is obtained by stability judgment, and the energy efficiency optimization needs to use these states as optimization weight parameters;

[0147]

[0148] 3) Repeat the optimization of the two until the end of the limited number of steps, after the game is over, the final output of the model includes the additional yaw moment M output by the stability optimization zfin ; According to the stability parameters in the stability function and the four-wheel torque distribution, the reference relationship between the four-wheel motion is given, combined with the energy efficiency weight matrix WeiPara obtained by energy efficiency optimization QP And four-wheel torque energy efficiency reference torque T ref = [T reffl T reffr T refrl T refrr ] T , wherein the energy efficiency weight matrix is:

[0149]

[0150] Wherein, q mi , q ci , p mi , p ci are the weight parameters input to the lower torque distribution model, T outi is the four-wheel torque currently output by the motor numbered i, T refi is the best reference torque of the motor numbered i obtained by energy efficiency optimization, T reffl +T reffr +T refrl +T refrr is the sum of the best reference torque of the four-wheel motor, ΔT i is the difference between the current output torque of the motor numbered i and the best reference torque, is the current wheel speed change trend.

[0151] S5, the weight parameters obtained in S4 are given to the lower torque, and the torque vector distribution is carried out to determine the four-wheel torque;

[0152] After the weight parameters of the energy efficiency torque distribution model are determined, the weight parameters are added to the lower torque distribution performance function, and the performance function corresponding to each weight parameter is as follows:

[0153] 1. is the motion energy consumption and stability performance function of the tire corresponding to the motor numbered i of the vehicle;

[0154] 2. The energy consumption optimization of the electromagnetic range corresponding to the motor numbered i for the automobile is performed;

[0155] 3. The state control optimization of the motor numbered i for the automobile is performed;

[0156] 4. The torque change limitation optimization of the motor numbered i for the automobile is performed;

[0157] After the combination, the additional yaw moment of the four wheels is calculated considering the automobile motion requirement:

[0158]

[0159] wherein, w i is the tire moving speed corresponding to the motor numbered i, M zfin is the additional yaw moment of the final result of the game

[0160] It should be noted that the control method described in this embodiment is to insert another layer as a correction layer of automobile control in the hierarchical control system, and balance the energy efficiency and stability requirements of the automobile by using the motor energy efficiency model and the Nash equilibrium optimization principle; The stability and economy of the automobile are considered at the same time when the automobile is running, the multi-objective collaborative optimization is achieved, and the endurance time of the automobile in the city is prolonged.

[0161] Based on the similar inventive concept, the embodiment of the present application also provides a computer storage medium, which stores a readable program, when the program is run by a processor, the program can execute the energy efficiency optimization method of the electric four-wheel drive automobile.

[0162] Based on the similar inventive concept, the embodiment of the present application provides an electronic device, which comprises a processor, a memory, a communication interface and a communication bus, the processor, the memory and the communication interface complete the communication among each other through the communication bus;

[0163] The memory is used to store at least one executable instruction, and the executable instruction makes the processor execute the operation corresponding to the energy efficiency optimization method of the electric four-wheel drive automobile.

[0164] Based on the similar inventive concept, the embodiment of the present application also provides a computer program product, which comprises computer instructions, and the computer instructions instruct a computing device to execute the operation corresponding to the energy efficiency optimization method of the electric four-wheel drive automobile.

[0165] Embodiment 2

[0166] In this embodiment, an energy efficiency optimization system of an electric four-wheel drive automobile is provided, which comprises:

[0167] An energy efficiency model construction module: constructing an energy efficiency model of the motor according to motor parameters used by the automobile, and obtaining a total vehicle driving efficiency;

[0168] A parameter calculation module: inversely deducing energy efficiency characteristic parameters according to a motor running state based on the energy efficiency model of the motor, and constructing an optimal performance function of the whole vehicle without motion control based on the total vehicle driving efficiency, and calculating the optimal torque of a single motor;

[0169] A distribution model design module: designing an optimal energy efficiency torque distribution model according to the energy efficiency characteristic parameters, the energy efficiency model of the motor and the optimal torque of the single motor;

[0170] A weight solving module: obtaining automobile stability parameters by a phase plane method, and coupling and optimizing the automobile stability parameters and the energy efficiency characteristic parameters by a game control based on a Nash equilibrium principle to obtain weight parameters;

[0171] A torque distribution module: assigning the weight parameters to the energy efficiency torque distribution model to calculate additional yaw torques of four wheels.

[0172] Embodiment 3

[0173] In this embodiment, the optimization method proposed in Embodiment 1 is simulated.

[0174] This example simulates the distributed drive electric vehicle lateral stability adaptive optimization control method of the present application. The simulation object of this example is a C-Class, Hatchback automobile model selected from carsim. Based on carsim / simulink, a double lane shift working condition (corresponding to 90 km / h overtaking) with a road adhesion coefficient of 0.85 and a left lane change (corresponding to 60 km / h urban daily driving) are jointly simulated.

[0175] The obtained test results are shown in Figure 6 and Figure 7 ; wherein, Figure 6 (a) in (a) is a comparison chart of automobile steering characteristics under different control algorithms in the example; Figure 6 (b) in (b) is a comparison chart of automobile lateral velocity changes under different control algorithms in the example; Figure 6 (c) in (c) is a comparison chart of total driving energy consumptions of the automobile under different control algorithms in the example; Figure 6 (d) in (d) is a comparison chart of longitudinal driving efficiencies of the automobile under different control algorithms in the example. Figure 7 (a) in (a) is a comparison chart of automobile steering characteristics under different control algorithms in the example; Figure 7 (b) in (b) is a comparison chart of automobile lateral velocity changes under different control algorithms in the example; Figure 7 (c) in (c) is a comparison chart of total driving energy consumptions of the automobile under different control algorithms in the example; Figure 7(d) in the example is a comparison of the longitudinal driving efficiency of the car under different control algorithms.

[0176] Figure 6 (a) to (d) are simulation diagrams for μ = 0.85 and Vx = 90 km / h. Figure 7 (a) to (d) are simulation diagrams for μ = 0.85 and Vx = 60 km / h; Figure 6 (a) to (d) and Figure 7 In (a) to (d), the blue curve represents game-theoretic optimization control (the optimization control method of this invention); the orange curve represents traditional optimization control; and the green curve represents no control.

[0177] Depend on Figure 6 As can be seen in (a) of the diagram, under vehicle acceleration, the lack of control, by distributing the driving torque evenly, easily leads to drifting, resulting in excessive dynamic steering performance; while under traditional control methods, the vehicle, in order to return to center as quickly as possible, exhibits greater steering angle fluctuations, further exacerbated by... Figure 6 As can be seen from (b) in the diagram, the game-theoretic optimization control first makes a small-angle turn during cornering to maintain vehicle balance, then straightens the steering wheel and restores the dynamic steering characteristics to the optimal value (0) based on the vehicle's motion posture. Figure 6 As can be seen from (c) in 6 and (d) in 6, in the longitudinal drive, the efficiency fluctuation of the game-theoretic optimization control is minimized, and the total energy consumption is minimized by controlling the magnitude of the additional yaw moment.

[0178] Depend on Figure 7 As can be seen in (a) of the diagram, during constant speed driving, lane changes without control result in a continuous error in the vehicle's steering after turning. When traditional control conditions are applied to correct the steering, the vehicle returns to normal and maintains normal motion. At this point, due to the vehicle's design structure, the steering characteristics remain negative. Game-theoretic optimization control, however, gradually optimizes the steering characteristics, bringing them closer to the optimal control feel. Figure 7 As can be seen in (b) above, both control methods and the absence of control allow for normal driving levels during lane changes at constant speed. Figure 7 As can be seen from (c), under normal driving conditions, the energy consumption of electric drives using traditional control methods and game-theoretic optimization control is not significantly different. However, from... Figure 7 As can be seen from (d) in the figure, the efficiency fluctuation of the game-theoretic optimization control method is minimal under the longitudinal driving condition.

[0179] The methods of the present application can be implemented in hardware, firmware, or software, or any combination thereof, and can be stored in or implemented with the aid of software or computer code stored in a recording medium as a computer program product without departing from the scope of the present application. The computer program product includes a computer readable medium, such as but not limited to the non-transitory machine-readable medium of the recording medium, having stored therein the computer program code, computer readable program code, or program. The computer readable medium can be implemented using any appropriate medium, including but not limited to electronic, magnetic, optical, electromagnetic, infrared, or semiconductor technology, including the Internet or World Wide Web. The computer program code can include any suitable set of instructions directly feasible for causing a processor or a computer to perform anything described herein. The computer program code can include, for example, source code, object code, scripts, machine code, binary, dead code, comments, or any other descriptive text or programming. The computer program code can be written as one or more instructions implementing any suitable computer language, programming language, scripting language, or deployment language, for example, and can be wholly embodied on a non-transitory machine-readable medium, such as a computer-usable or computer-readable recording medium of the recording medium. The computer program code can be downloaded over a network from a remote computer (e.g., a server) or to a remote computer (e.g., a server) for execution by a processor of that server. From the server, the end user's computer can be caused, for example, by downloading an appropriate program code to the user's computer or by employing another networked element that can cause the end user's computer to execute the code. In this manner, the computer program code can be transferred from the remote computer to a remote computer of the end user who uses the end user's computer to execute it.

[0180] The foregoing is considered as illustrative only of the principles of the application. Those skilled in the art will appreciate that the application is capable of being practiced with various modifications and changes without departing from the spirit and scope of the application. Accordingly, the scope of the application is not intended to be limited to the above examples, but rather is to be accorded the widest scope consistent with the principles and various features disclosed herein.

Claims

1. A method for optimizing the energy efficiency of an electric four-wheel drive vehicle, characterized in that, Includes the following steps: Based on the parameters of the motors used in automobiles, a motor energy efficiency model is constructed, and the overall vehicle drive efficiency is obtained; Based on the motor energy efficiency model, the energy efficiency characteristic parameters are derived from the motor's operating status. Based on the overall vehicle drive efficiency, the optimal performance function of the entire vehicle without motion control is constructed, and the optimal torque of a single motor is calculated. Based on energy efficiency characteristic parameters, motor energy efficiency model, and the optimal torque of a single motor, design an optimal energy efficiency torque distribution model. The vehicle stability parameters are obtained by using the phase plane method, and the vehicle stability parameters and energy efficiency characteristic parameters are coupled and optimized by using game control based on the Nash equilibrium principle to obtain weight parameters. The weighting parameters are assigned to the energy efficiency torque distribution model to calculate the additional yaw moment of the four wheels.

2. The energy efficiency optimization method for an electric four-wheel drive vehicle according to claim 1, characterized in that, The motor energy efficiency model is as follows: P.S motor s q 2 +bi q 2 n 2 +ci q n+dn+en 2 +Const T=pi q k e Where, η i Let i be the output efficiency of motor numbered i (i = fl, fr, rl, rr), where fl, fr, rl, rr represent the tire positions of the motor within the vehicle body, in the following order: front left, front right, rear left, rear right; P outi P represents the output power of motor number i. motori P represents the energy consumption power of motor number i. motor The power consumed by the motor; a, b, c, d, e, and Const are all equivalent state parameters of the motor, and their initial values ​​are calculated as follows: a = R a , R a R is the equivalent resistance of the motor stator. i k is the equivalent resistance of the motor's iron loss. m K is the coefficient of friction loss during motor rotation. e L is the flux linkage amplitude of the permanent magnet in the motor. d L is the equivalent inductance of the motor's direct shaft. q P is the quadrature-axis equivalent inductance of the motor; out denoted as , where is the motor output power; p is the number of pole pairs of the motor.

3. The energy efficiency optimization method for an electric four-wheel drive vehicle according to claim 2, characterized in that, The overall vehicle driving efficiency η is: Among them, P outfl P outfr P outrl and P outrr These represent the output power of the front left, front right, rear left, and rear right motors, respectively; P motorfl P motorfr P motorrl and P motorrr These represent the power consumption of the front left, front right, rear left, and rear right motors, respectively.

4. The energy efficiency optimization method for an electric four-wheel drive vehicle according to claim 3, characterized in that, The process of calculating the optimal torque of a single motor based on energy efficiency characteristic parameters includes: 1) Calculate the energy efficiency function of a single motor: 2) Obtain the single motor energy efficiency function with respect to the quadrature-axis current i q The derivative is: The optimal efficiency quadrature-axis current i qbest Positive value: 3) Calculate the optimal torque T of a single motor according to the torque formula. besti for:

5. The energy efficiency optimization method for an electric four-wheel drive vehicle according to claim 4, characterized in that, The optimal performance function of the entire vehicle without motion control is: P Me =∑a i T i 2 +b i T i 2 n i 2 +c i T i n i p i K ei +p i 2 K ei 2 (T i n i +Const i ) Among them, J motor Let P be the optimal performance function of the entire vehicle under no motion control. Mout P represents the total output power of the four motors. Me The total power consumption of the four motors is t. mi The weighting coefficient is the one corresponding to motor number i.

6. The energy efficiency optimization method for an electric four-wheel drive vehicle according to claim 5, characterized in that, The steps involved in designing an optimal energy-efficient torque distribution model include: Step 1: Based on the optimal performance function of the entire vehicle without motion control, and considering the vehicle's motion state and energy consumption state, the final energy efficiency optimization performance function is designed as follows: J energy (T energy )=α1J motor (T)+α2J yaw (T) Among them, J energy The final performance function for energy efficiency optimization is defined by α1 and α2, which are the weight coefficients of the game strength in the energy efficiency optimization algorithm. ρ is the stability parameter obtained in stability control, J yaw J represents the cost function that compromises with the car's motion state. yaw =(M Z (T)-M zout ) 2 M Z (T) represents the additional yaw moment obtained from energy efficiency optimization, and M represents the additional yaw moment. zout Additional yaw moment output for vehicle stability control; Step 2: Solve the performance function designed in Step 1 using the quadratic programming method to obtain the optimal energy-efficient torque distribution model.

7. An energy efficiency optimization system for an electric four-wheel drive vehicle, characterized in that, include: Energy efficiency model building module: Based on the parameters of the motor used in the car, build a motor energy efficiency model and obtain the overall vehicle drive efficiency; Parameter calculation module: Based on the motor energy efficiency model, the energy efficiency characteristic parameters are derived from the motor operating status; Based on the overall vehicle drive efficiency, the optimal performance function of the entire vehicle without motion control is constructed, and the optimal torque of a single motor is calculated. Distribution model design module: Based on energy efficiency characteristic parameters, motor energy efficiency model and the optimal torque of a single motor, design the optimal energy efficiency torque distribution model; Weighting module: The phase plane method is used to obtain the vehicle stability parameters, and the game control based on the Nash equilibrium principle is used to couple and optimize the vehicle stability parameters and energy efficiency characteristic parameters to obtain the weight parameters. Torque distribution module: Assigns the weight parameters to the energy efficiency torque distribution model to calculate the additional yaw torque of the four wheels.

8. A computer storage medium storing a readable program, characterized in that, When the program is running, it can instruct the computing device to execute an energy efficiency optimization method for an electric four-wheel drive vehicle as described in any one of claims 1-6.

9. An electronic device, characterized in that, include: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction, which causes the processor to perform an operation corresponding to the energy efficiency optimization method for an electric four-wheel drive vehicle as described in any one of claims 1-6.

10. A computer program product comprising computer instructions, characterized in that, The computer instructions instruct the computing device to perform the operation corresponding to the energy efficiency optimization method for an electric four-wheel drive vehicle as described in any one of claims 1-6.

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