TW201708003A - Chassis system integration structure of multiple-wheel drive electric vehicle, and control method thereof effectively integrating the chassis subsystem functions such as the active front wheel steering, differential driving, and differential braking to enhance the maneuverability and safety - Google Patents

Abstract

The invention provides a chassis system integration structure of multiple-wheel drive electric vehicle and control method thereof to enhance the maneuverability and safety of multiple-wheel drive electric vehicle. The technical means thereof is that the integration structure can be match up with a multiple-wheel drive electric vehicle having dynamic sensing system of vehicle body to effectively integrate three chassis subsystem functions such as the active front wheel steering, differential driving, and differential braking of front wheel to achieve the application of integrated chassis control technology. In the aspect of integration structure, it comprises a dynamic vehicle control unit, a steering control system, a tire slip ratio control system, and a chassis power control system. In the aspect of control method, based on the relationship among the active front wheel steering, differential driving, and differential braking, the dynamic vehicle control unit can be configured in three ways, i.e. the tight coupling control structure, loose coupling control structure, and non-coupling control structure, so as to enhance the maneuverability and safety of multiple-wheel drive electric vehicle.

Description

Chassis system integration architecture of multi-wheel drive electric vehicle and control method thereof

The invention relates to a chassis system integration structure of a multi-wheel drive electric vehicle and a control method thereof, in particular to an integrated structure of a chassis power, a brake and a steering system which can be applied to a multi-wheel drive electric vehicle and a control method derived therefrom .

In order to improve the tracking performance of vehicles and the dynamic stability of high-speed cornering vehicles, the existing electronic stability control system is mainly controlled by active steering control and differential braking to generate appropriate yaw rotation. The moment [yaw moment] is reached.

The multi-wheel drive electric vehicle can also be used for the stability control of the vehicle body because it can independently control the driving force of the left and right wheels and generate the yaw torque by the differential traction method.

The differential driving method is used for the stability control of the vehicle body, so that the vehicle speed can be reduced without the intervention of the brake car, so that the high-speed cornering steering performance of the vehicle can be improved, and the kinetic energy of the vehicle can be reduced in the braking process, and the energy use of the vehicle can be improved. effectiveness.

The automatic assist/autonomous driving system, because of the need to control the heading angle of the vehicle, must perform the steering control of the front wheels through the active electronic steering system. However, when the vehicle is traveling, the steering of the front axle tires and the torque output of each tire will be applied to the vehicle. Dynamically affects.

What's more, the current common driving assistance control system, such as the Electronic Stability Control (ESC) shown in Figure 1, the Anti-lock Brake System (ABS) and the automatic lane maintenance aid (Lane Keeping Assist) system architecture Intended, generally applied vehicle active safety system (200), including an automatic assisted driving system (201) and vehicle dynamics that can be combined with a conventional power system (300), a conventional brake system (400), and a conventional steering system (500) A stability control system (202), wherein the automatic assisted driving system (201) includes an automatic lane maintenance assist system, and the vehicle dynamic stability control system (202) includes an electronic stability control and an anti-lock brake system, and the active electronic steering control has not yet been Differential braking, differential drive control is an integration, and there is no effective control method. The main problem is that the existing driving assistance control system is not designed for multi-wheel drive electric vehicles. For multi-wheel drive electric vehicles, It is not effective at the same time to improve its energy-saving performance and high-speed cornering ability, handling and dynamic stability of the vehicle body.

In view of this, how to provide a driving section that can enhance multi-wheel drive electric vehicles The multi-wheel drive electric vehicle undercarriage integrated structure and control method thereof, such as energy capability, high-speed cornering ability, maneuverability and dynamic stability of the vehicle body, have become objects to be improved by the present invention.

The object of the present invention is to provide a system integration architecture and a control method for a multi-wheel drive electric vehicle capable of improving the handling and safety of a multi-wheel drive electric vehicle.

In order to solve the above problems and achieve the object of the present invention, the technical means of the present invention is realized in the system integration architecture, and is a system integration architecture of a multi-wheel drive electric vehicle, which can cooperate with a vehicle dynamic sensing system (20). Multi-wheel drive electric vehicle (10) application, characterized in that the integrated structure (100) includes a multi-wheel drive electric vehicle (10) mounted thereon, and the body dynamic sensing system (20) Connected vehicle dynamic control unit (1), the vehicle dynamic control unit (1) and a steering control system (2) mounted on the multi-wheel drive electric vehicle (10), and a tire slip control system (3) The connection is made, and the slip control system (3) is also connected to a chassis power control system (4) mounted on the multi-wheel drive electric vehicle (10).

More preferably, the chassis power control system (4) further includes a multi-wheel drive system (41) consisting of a plurality of motors and a multi-wheel brake system (42).

Regarding the control method, it can be divided into three types. The first one is applicable to multiple wheel drives. The electric vehicle chassis system (including front wheel steering, power and braking) adopts a tightly coupled integrated architecture control method, characterized in that the vehicle dynamic control unit (1) as described in claim 1 is in a tightly coupled control architecture Setting and causing the vehicle dynamic control unit (1) to include an optimization controller (11) containing a model predictive control algorithm (A), and the model predictive control algorithm (A) has a body dynamics The solving ability of the optimization problem (A1) allows the vehicle dynamic control unit (1) to vertically position the front wheel according to the vehicle dynamic value and the reference value (T) transmitted by the vehicle body dynamic sensing system (20). The effects of steering, wheel drive and braking actions on the overall vehicle dynamics are taken into consideration, and the first control command (C1) given to the steering control system (2) and the tire slip control system (3) are directly calculated. a second control command (C2); and after the tire slip control system (3) receives the second control command (C2), after the correction, a third control command (C3) is generated to be given to the chassis power control system. (4) to control each power motor and brake The torque output achieves the functions of differential drive and/or differential brake to improve the dynamic stability of the vehicle.

More preferably, the vehicle dynamic optimization problem (A1) is a linear optimization problem with limited conditions, which is easier to solve than the nonlinear optimization problem, and is more suitable for use in a vehicle immediate control system, such as The following is shown: u _n =[ T _f ,T _rl ,T _rr ,Pb _{L 1} ,Pb _{R 1} ,Pb _{L 2} ,Pb _{R 2} ,δ ]; Subject to Where J is the cost function, w ₁ , w ₂ , and w ₃ are the weights of the respective cost items, and T _p and T _C are the number of time-steps Δt in the prediction interval and the control interval, respectively. Representative model predictive control algorithm at time t η predicted prediction value of the time t + i, Then the reference value of η at time t + i , , , Represents the longitudinal speed, lateral velocity, and yaw rate of the vehicle, respectively (the x-axis is positive in front of the car, the y-axis is positive in the left side of the car, and the z-axis is positive in the upper part of the car), T _f , T _rl , T _rr Representing the torque provided by the front axle motor, the left rear wheel motor and the right rear wheel motor, respectively, Pb _{L 1} , Pb _{R 1} , Pb _{L 2} , Pb _{R 2} represent the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel, respectively. Brake pressure, δ represents the steering angle of the front axle tire, m and I _zz represent the mass of the vehicle and the moment of inertia with respect to the z-axis, respectively. , , , Representing the longitudinal friction of the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel, respectively. , Represents the total lateral friction between the first two wheels and the ground and the total lateral friction between the rear two wheels and the ground. L _f and L _r are the distances from the front and rear axles to the vehicle center of mass, respectively, d _f , d _r respectively front and rear wheels track, I _w, R _w are the moment of inertia and the effective radius of the tire, , Tire longitudinal friction and tire rotation angular acceleration, respectively , They are the driving torque of the wheel and the braking torque, respectively, where i=L and R represent the left and right wheels respectively, j=1 and 2 respectively represent the front and rear axles, and C _f and C _r respectively represent the steering rigidity of the front and rear wheels, △X X represents the amount of change between the current time step before step (representative of a physical quantity X), X, min and X, max respectively represent the lower limit and upper limit of X.

More preferably, the slip control system (3) further has a tracking control system (31) and an anti-lock braking system (32); the first control command (C1), which is a front wheel steering system maneuver command ( δ ); the second control command (C2) comprising one or a combination of the following: an output torque control command ( T _f , T _rl , T _rr ) of each drive motor, Each wheel brake control command ( Pb _{L 1} , Pb _{R 1} , Pb _{L 2} , Pb _{R 2} ); the third control command (C3) is for the tracking control system (31) and the anti-lock brake The system (32) corrects each of the driving motors and the respective wheel brake control commands; the vehicle dynamic reference value (T) includes the following combined message: a vehicle longitudinal speed reference value (T1), and a vehicle lateral speed reference value ( T2), vehicle yaw rate reference value (T3).

Regarding the control method, it can be divided into three types, and the second is applicable to multiple wheel drives. A control method for a loosely coupled integrated architecture of an electric vehicle chassis system (including front wheel steering, power and braking), characterized in that the vehicle dynamic control unit (1) according to claim 1 is loosely coupled to control the architecture Setting and causing the vehicle dynamic control unit (1) to include a controller (11) incorporating a model predictive control algorithm (A), and a tire force distribution controller (12) using output feedback control, The controller (11) incorporating the model predictive control algorithm (A) can transmit a yaw moment control command (C4) to the tire force distribution controller (12), and the model predictive control calculus The method (A) has a solving ability of a body dynamic optimization problem (A1), and the controller (11) can calculate and generate a first control command (C1) according to the vehicle dynamic reference value (T), giving The steering control system (2), at the same time, the tire force distribution controller (12) according to the vehicle yaw moment control command (C4) transmitted by the controller (11), the vehicle dynamic reference value (T), and the current Speed, calculate and generate a second control command (C2), give the tire The difference between the control system (3); after the tire slip (3) receiving the second control command (C2) control system also generates a third control command (C3) administering to the chassis dynamics control system (4).

More preferably, the vehicle dynamic optimization problem (A1) is a linear optimization problem with limited conditions, which is easier to solve than the nonlinear optimization problem, and is more suitable for use in a vehicle immediate control system, such as The following is shown: u _n =[ δ,T _d ]; Subject to Where J is the cost function, w ₁ , w ₂ , and w ₃ are the weights of the respective costs, and T _p and T _C are the number of time-steps Δ t of the prediction interval and the control interval, respectively. Representative model predictive control algorithm at time t η predicted prediction value of the time t + i, Then the reference value of η at time t + i , , Representing the longitudinal speed of the vehicle and the yaw rate, δ represents the steering angle of the front axle tire, T _d is the yaw moment control command, m and I _zz represent the mass of the vehicle and the moment of inertia with respect to the z axis, respectively. , Lateral frictional forces on behalf of the front axle and rear lateral friction, L _f, L _r, respectively front and rear axles of the wheelbase, C _f, C _r represent the front and rear wheels steering rigidity, representing △ X X The value of the change between the current and the previous time step ( X represents a certain physical quantity).

More preferably, the slip control system (3) further has a tracking control system (31) and an anti-lock braking system (32); the first control command (C1), which is a front wheel steering system maneuver command ( δ ); the second control command (C2) comprising one or a combination of the following: an output torque control command ( T _f , T _rl , T _rr ) of each drive motor, Each wheel brake control command ( Pb _{L 1} , Pb _{R 1} , Pb _{L 2} , Pb _{R 2} ); the third control command (C3) is for the tracking control system (31) and the anti-lock brake The system (32) corrects each of the driving motors and the respective wheel brake control commands; the vehicle dynamic reference value (T) includes the following combined message: a vehicle longitudinal speed reference value (T1), and a vehicle lateral speed reference value ( T2), vehicle yaw rate reference value (T3).

More preferably, the tire force distribution controller (12) further includes a round a tire force calculation module (121) and a power distribution module (122); the tire force calculation module (121) can be based on the vehicle yaw control torque command (C4), the vehicle dynamic reference value (T And the current vehicle speed, calculating a longitudinal force reference value (C5) required for each tire of the multi-wheel drive electric vehicle (10), and transmitting to the power distribution module (122); the power distribution module (122), according to the different types of front and rear wheel motor drive systems of the multi-wheel drive electric vehicle (10), the longitudinal force reference value (C5) given by the tire force calculation module (121) is assigned Drive motor and torque output of each wheel brake.

More preferably, the tire force calculation module (121) is determined by the following formula

The longitudinal force reference value (C5):

Where F _x is the total longitudinal force, T _d is the vehicle yaw moment control command, k is the feedback gain, m is the mass of the vehicle, and V _x is the instantaneous longitudinal speed. For the reference value of the longitudinal velocity, n ₁ and n ₂ are proportional constants.

More preferably, the power distribution module (122) can be divided into a single-axis single-drive module and a single-axis dual-drive module according to different types of the motor drive system.

More preferably, when the power distribution module (122) is a single-axis single-drive module, the motor driving force distribution mode is determined according to the following formula:

Among them, T, Pb _L and Pb _R are the motor torque output, the hydraulic brake pressure of the left wheel and the hydraulic brake pressure of the right wheel, and R _w , GR and G are the effective tire radius, gear ratio and hydraulic brake pressure respectively converted into torque. The gain value, T _max , T _min is the upper and lower limits of the motor torque output, and Pb _max is the upper limit of the hydraulic brake pressure. , Then it is the longitudinal tire road friction command of the left and right wheels.

More preferably, when the power distribution module (122) is a single-axis dual-drive module, the motor driving force distribution mode is determined according to the following formula:

Among them, T _L and T _R are the torque output of the left and right motors, and Pb _L and Pb _R are the hydraulic brake pressure of the left wheel and the hydraulic brake pressure of the right wheel respectively. R _w , GR and G are the effective tire radius, gear ratio and The hydraulic brake pressure is converted into the gain value of the torque, , For the upper and lower limits of the torque output of the right wheel motor, , For the upper and lower limits of the torque output of the left wheel motor, Pb _max is the upper limit of the hydraulic brake pressure. , Then it is the longitudinal tire road friction command of the left and right wheels.

Regarding the control method, it can be divided into three types, and the third is applicable to multiple wheel drives. A control method for a non-coupling integrated architecture of an electric vehicle chassis system (including front wheel steering, power and braking), characterized in that the vehicle dynamic control unit (1) according to claim 1 is in an uncoupled control architecture manner Setting and causing the vehicle dynamic control unit (1) to include an optimization controller (11) containing a model predictive control algorithm (A) and a tire force distribution controller (12), the optimization control The vehicle (11) and the tire force distribution controller (12) operate separately, do not communicate with each other but have the same control target, and the model predictive control algorithm (A) has a vehicle dynamic optimization problem ( The solving ability of A1) enables the vehicle dynamic control unit (1) to be based on the vehicle dynamic reference value (T) transmitted by the vehicle dynamic sensing system (20), by the optimization controller (11) according to The car a dynamic reference value (T), calculated and generated a first control command (C1), given to the steering control system (2), and simultaneously by the tire force distribution controller (12) according to the vehicle dynamic reference value (T And the current vehicle speed and yaw rate, calculating and generating a second control command (C2), giving the slip control system (3); the slip control system (3) receiving the second control command (C2) After that, after the correction of the tracking control system (31) and the anti-lock braking system (32), a third control command (C3) is also given to the chassis power control system (4).

More preferably, the vehicle dynamic optimization problem (A1) is a linear optimization problem with limited conditions, which is easier to solve than the nonlinear optimization problem, and is more suitable for use in a vehicle immediate control system, such as The following is shown: u _n =[ δ ];Subject to

Where J is the cost function, w ₁ and w ₂ are the weights of the respective costs, and T _p and T _C are the time-step Δ t number of the prediction interval and the control interval, respectively. Representative model predictive control algorithm at time t η predicted prediction value of the time t + i, Then the reference value of η at time t + i , Represents the yaw rate of the vehicle, δ represents the steering angle of the front axle tire, I _zz represents the moment of inertia of the vehicle with respect to the z axis, L _f is the wheelbase of the front axle, C _f represents the steering stiffness of the front wheel, and ΔX represents the value of X The amount of change between the current and previous time steps ( X represents a certain physical quantity).

More preferably, the first control command (C1) is a front wheel steering command; the second control command (C2) includes one or a combination of the following: output torque of each drive motor Control commands ( T _f , T _rl , T _rr ), brake control commands for each round ( Pb _{L 1} , Pb _{R 1} , Pb _{L 2} , Pb _{R 2} ); the third control command (C3), which is The drive motor and each wheel brake control command after the correction by the tracking control system (31) and the anti-lock brake system (32); the vehicle dynamic reference value (T) includes one or a combination of the following messages : Vehicle longitudinal speed reference value (T1), vehicle lateral speed reference value (T2), vehicle yaw rate reference value (T3).

More preferably, the tire force distribution controller (12) further includes a round a tire force calculation module (121) and a power distribution module (122); the tire force calculation module (121) can be based on the vehicle dynamic reference value (T), and the current vehicle speed and yaw rate, With the output feedback control, the value of the yaw control torque of the vehicle body is calculated, and the longitudinal force reference value (C5) required for each tire of the multi-wheel drive electric vehicle (10) is finally calculated and transmitted to the power distribution module. (122); the power distribution module (122) can be matched with the different types of front and rear wheel motor drive systems of the multi-wheel drive electric vehicle (10), and the tire force calculation module (121) The longitudinal force reference value (C5) distributes the power output of each motor and the torque output of each wheel.

More preferably, the tire force calculation module (121) determines the total longitudinal force reference value (C5) of the vehicle body according to the following formula: The tire force calculation module (121) calculates a vehicle yaw control torque value according to the following formula: T _d = - k _T I _zz ( AVz - AVz _ref ); the tire force calculation module (121) The following formula determines the longitudinal force of four rounds:

Where F _x is the total longitudinal force, T _d is the yaw control torque of the vehicle body, k _F and k _T are the feedback gains of the longitudinal force of the tire and the yaw control torque of the vehicle respectively, m and I _zz represent the mass and relative of the vehicle respectively. Moment of inertia on the z-axis, V _x , They are the instantaneous longitudinal velocity and longitudinal velocity reference values of the vehicle's centroid, respectively. AVz and AVz _ref are the reference values of instantaneous yaw rate and yaw rate, respectively, and n ₁ and n ₂ are proportional constants.

More preferably, the power distribution module (122) includes a single-axis single-drive module and a single-axis dual-drive module according to different types of the motor power system, and the motor output torque distribution control is performed in different manners.

More preferably, when the power distribution module (122) is a single-axis single-drive module, the power distribution mode is determined according to the formula, and the formula is the same as the second control method.

More preferably, when the power distribution module (122) is a single-axis dual-drive module, the power distribution mode is determined according to the formula, and the formula is the same as the second control method.

Compared with the prior art, the functions and effects of the present invention are as follows:

The first point: in the present invention, the integrated architecture (100) designed for the multi-wheel drive electric vehicle (10), through the vehicle dynamic control unit (1), the steering control system (2) and the chassis power control system (4) Integration can effectively integrate the control of the active steering system, differential drive and differential brake system to improve the handling and safety of the multi-wheel drive electric vehicle (10).

The second point: the integrated architecture (100) of the present invention can also provide tight coupling, loose coupling, and uncoupling according to the integration degree of the multi-wheel drive electric vehicle steering control system (2) and the chassis power control system (4). These three different control architectures form three different control methods that allow the invention to be effectively applied.

The third point: the integrated architecture (100) of the present invention can respond to different motor drive systems (41) types of multi-wheel drive electric vehicles (10), has fewer problems in production integration, and can be quickly put into use.

1‧‧‧Vehicle Dynamic Control Unit

11‧‧‧Optimized controller

12‧‧‧ Tire force distribution controller

121‧‧‧ Tire force calculation module

122‧‧‧Power Distribution Module

2‧‧‧Steering Control System

3‧‧‧Tire slip control system

31‧‧‧Track Control System

32‧‧‧Anti-lock brake system

4‧‧‧Chassis Power Control System

41‧‧‧Multi-wheel drive system

42‧‧‧Multi-wheel brake system

10‧‧‧Multi-wheel drive electric vehicles

20‧‧‧Body dynamic sensing system

30‧‧‧Motor

40‧‧‧Axis

50‧‧‧Steering wheel

60‧‧‧ Gearbox

100‧‧‧Integrated Architecture

200‧‧‧Vehicle Active Safety System

201‧‧‧Automatic assisted driving system

202‧‧‧Vehicle Dynamic Stability Control System

300‧‧‧Traditional Power System

400‧‧‧Traditional brake system

500‧‧‧Traditional steering system

A‧‧‧ model predictive control algorithm

A1 body dynamic optimization problem

T‧‧‧ Vehicle dynamics and reference values

T1‧‧‧ Vehicle longitudinal speed reference

T2‧‧‧ Vehicle lateral speed reference

T3‧‧‧ Vehicle yaw rate reference

C1‧‧‧ first control order

C2‧‧‧ second control order

C3‧‧‧ third control order

C4‧‧‧ Body yaw control torque command

C5‧‧‧ longitudinal force reference

Figure 1: Schematic diagram of the structure of a traditional vehicle dynamic stability control and automatic assisted driving system.

Figure 2 is a schematic diagram showing the architecture of the first vehicle dynamic control unit in the present invention.

Figure 3 is a schematic diagram showing the architecture of a second vehicle dynamic control unit in the present invention.

Fig. 4 is a schematic view showing the architecture of a third vehicle dynamic control unit in the present invention.

Figure 5: Schematic diagram of the structure of a multi-wheel drive electric vehicle.

Figure 6 is a schematic view showing the architecture of the tire force distribution controller of the present invention.

The following is a detailed description of the embodiment shown in the drawings. As shown in FIG. 1 to FIG. 6 , the system discloses a system integration architecture for a multi-wheel drive electric vehicle, which can be combined with a vehicle dynamic sensing system. (20) A multi-wheel drive electric vehicle (10) application, characterized in that the integrated structure (100) includes a multi-wheel drive electric vehicle (10) mounted thereon, and with the vehicle dynamic sensing system (20) a connected vehicle dynamic control unit (1), respectively, a front axle steering control system (2) mounted on the multi-wheel drive electric vehicle (10), and a tire slippery The differential control system (3) is coupled, and the tire slip control system (3) is also coupled to a chassis power control system (4) mounted to the multi-wheel drive electric vehicle (10).

Among them, through the application of the vehicle dynamic control unit (1), the control of the steering control system (2) and the chassis power control system (4) is integrated, and the vehicle dynamic control unit (1) is received by the vehicle body dynamic sensing system (20). After the reference value of the multi-wheel drive electric vehicle (10) is transmitted, the respective outputs of the steering control system (2) and the chassis power control system (4) are calculated, and the tire slip control system (3) is used. Ensure that the vehicle does not enter the situation of slipping and yaw dynamic instability, and improve multi-wheel drive power The handling and safety of the motor car (10).

In the above, the chassis power control system (4) includes a multi-wheel drive system (41) composed of a plurality of motors and a brake system (42).

Among them, through the design of different vehicle dynamic control units, and using the corresponding power distribution module, the multi-wheel drive electric vehicle (10) can have better handling performance, and at the same time take into account the vehicle dynamic stability and safety.

For the application of the first control method, please refer to Figure 2, which is a control method for a tightly coupled integrated architecture of a multi-wheel drive electric vehicle undercarriage system (including steering, drive and brake), which is characterized by The vehicle dynamic control unit (1) according to claim 1 is arranged in a tightly coupled control architecture, and the vehicle dynamic control unit (1) includes an optimization of an embedded model predictive control algorithm (A). The controller (11), and the model predictive control algorithm (A) has a solving ability of the vehicle dynamic optimization problem (A1), so that the vehicle dynamic control unit (1) can be based on the vehicle dynamic sensing system ( 20) The transmitted vehicle dynamic reference value (T), taking into account the effects of the vehicle dynamics on each subsystem of the chassis, including steering, driving and braking, and directly calculating the steering control system (2) a first control command (C1), and a second control command (C2) given to the tire slip control system (3); and the tire slip control system (3) receives the second control command (C2) After that, a third control command (C3) is given Chassis power control system (4).

In the above, the vehicle dynamic optimization problem (A1) is as follows: u _n =[ T _f ,T _rl ,T _rr ,Pb _{L 1} ,Pb _{R 1} ,Pb _{L 2} ,Pb _{R 2} ,δ ]; Subject to Where J is the cost function, w ₁ , w ₂ , and w ₃ are the weights of the respective costs, and T _p and T _C are the time-step Δ t numbers of the prediction interval and the control interval, respectively. Representative model predictive control algorithm at time t η predicted prediction value of the time t + i, Then the reference value of η at time t + i , , , Representing the longitudinal speed, lateral velocity and yaw rate of the vehicle, respectively, T _f , T _rl , T _rr represent the torque provided by the front motor, the left rear motor and the right rear motor, respectively, Pb _{L 1} , Pb _{R 1} , Pb _{L 2} , Pb _{R 2} represents the brake pressure of the left front wheel, the right front wheel, the left rear wheel and the right rear wheel, respectively, δ represents the steering angle of the front axle tire, and m and I _zz represent the mass of the vehicle and the moment of inertia with respect to the z-axis, respectively. , , , Representing the longitudinal friction of the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel, respectively. , Representing the lateral friction of the front axle and the lateral friction of the rear axle, respectively, L _f and L _r are the distances between the front axle and the rear axle to the center of mass of the vehicle, respectively, d _f and d _f are the intervals of the front axle and the rear axle respectively. , I _w , R _w are the moment of inertia and effective radius of the tire, respectively. , Tire longitudinal friction and tire rotation angular acceleration, respectively , The motor drives the driving torque and the braking torque on the wheel respectively, where i=L and R represent the left and right wheels, j=1 and 2 represent the front and rear axles, C _f and C _r represent the steering rigidity of the front and rear wheels, respectively, and ΔX represents X. The amount of change between the current and the previous time step ( X represents a physical quantity).

For the application of the second control method, please refer to FIG. 3, which is a control method of a system integration architecture of a multi-wheel drive electric vehicle, characterized in that the vehicle dynamic control unit according to claim 1 is provided. ), set in a loosely coupled control architecture, and the vehicle dynamic control unit (1) includes an optimization controller (11) incorporating a model predictive control algorithm (A) and an output feedback control Tire force distribution controller (12), the optimized controller (11) A differential torque command (C4) can be transmitted to the tire force distribution controller (12), and the model predictive control algorithm (A) has an optimization problem (A1) by optimizing the controller (11) calculating and generating a first control command (C1) according to the vehicle dynamic reference value (T), giving the steering control system (2), and simultaneously passing the tire force distribution controller (12) according to the maximum The vehicle yaw control torque command (C4) transmitted by the controller (11), the vehicle dynamic reference value (T), and the current vehicle speed, calculate and generate a second control command (C2), giving the tire slip The differential control system (3); after receiving the second control command (C2), the tire slip control system (3) also generates a third control command (C3) for the chassis power control system (4).

Among them, the body dynamics optimization controller (11) operates using the model predictive control algorithm (A), and the tire force distribution controller (12) operates using the output feedback control method.

In the above, the body dynamics optimization problem (A1) is as follows: u _n =[ δ,T _d ]; Subject to Where J is the cost function, w ₁ , w ₂ , and w ₃ are the weights of the respective costs, and T _p and T _C are the time-step Δ t numbers of the prediction interval and the control interval, respectively. Representative model predictive control algorithm at time t η predicted prediction value of the time t + i, Then the reference value of η at time t + i , , Representing the longitudinal speed of the vehicle and the yaw rate, δ represents the steering angle of the front axle tire, T _d is the yaw control torque command of the vehicle, and m and I _zz represent the mass of the vehicle and the moment of inertia with respect to the z axis, respectively. , Representing the total lateral friction of the first two rounds and the total lateral friction of the last two rounds, L _f and L _r are the distances from the front and rear axles to the vehicle's center of mass, respectively, C _f and C _r represent the front, the rear wheel steering rigidity, △ X X represents the current value of a change amount between the previous time step order (X representative of a physical quantity).

In the above, the tire force distribution controller (12) further includes a tire force calculation module (121) and a power distribution module (122); the tire force calculation module (121) can be based on The vehicle yaw control torque command (C4), the vehicle dynamic reference value (T), and the current vehicle speed, and the longitudinal force reference value (C5) required for each tire of the multi-wheel drive electric vehicle (10) is calculated. And transmitting to the power distribution module (122); the power distribution module (122) can be given according to the type of the multi-wheel drive electric vehicle (10) motor drive system, and the tire force calculation module (121) The tire longitudinal force reference value (C5) is assigned to the torque output of each drive motor or brake.

Wherein, the calculation process in the tire force distribution controller (12) is divided into two parts, and the first part needs to determine the longitudinal force required to generate the four tires, which is performed by the tire force calculation module (121). The second part is performed by the power distribution module (122), which has different drive control methods depending on the type of motor power system of the multi-wheel drive electric vehicle (10).

Secondly, the vehicle power system of the multi-wheel drive electric vehicle (10) can be roughly divided into a single-axis single-drive module and a single-axis dual-drive module, for example, a double-type electric propulsion electric vehicle, as shown in Fig. 5. The multi-wheel drive electric vehicle (10) has a plurality of motors (30), a plurality of rotating shafts (40), a steering wheel (50), and a gear box (60). The front axle is driven by a single motor (30). In two wheels, the rear axle uses two motors (30) to drive one rear wheel. No matter what kind of multi-wheel drive electric vehicle (10), multi-wheel drive can be ensured by the application of the tire force distribution controller (12). The electric vehicle (10) is safe to drive.

In addition, when setting the power distribution module (122), it is also necessary to pay attention to the motor power system type of the multi-wheel drive electric vehicle (10), because the left and right wheels driven by the single-axis single-drive module have the same torque. Therefore, the differential drive function cannot be provided by the motor drive module, thereby generating the yaw control torque of the vehicle, and the yaw control torque must be generated by the differential brake; and the output of the single axle dual drive module for the tire. The torque is independently controlled, so the torque output of the left and right wheels is independently provided by the left and right motors (30), so the differential drive can be achieved by independent drive torque control of the left and right wheels, thus providing the body The torque required for yaw dynamic stability control; however, if the required yaw control torque of the vehicle is large, the upper limit of the differential torque that can be provided by the differential drive of the left and right wheels can still be used to compensate for the offset required by the brakes. Aerodynamic control torque.

In addition, when the tire force distribution controller (12) is operated, the longitudinal force required for the four tires is calculated by the tire force calculation module (121), wherein the total longitudinal force is a longitudinal speed feedback gain control. The differential torque is calculated by the optimization controller (11).

In the above, the tire force calculation module (121) determines the longitudinal force reference value (C5) of each tire according to the following formula:

Where F _x is the total longitudinal force, T _d is the vehicle yaw control torque, k is the feedback gain value, m is the mass of the vehicle, and V _x is the instantaneous longitudinal speed. For the reference value of the longitudinal velocity, n ₁ and n ₂ are proportional constants.

In the above, the power distribution module (122) can be divided into a single-axis single-drive module and a single-axis dual-drive module according to different types of the motor drive system.

When the power distribution module (122) is a single-axis single-drive module, the motor driving force distribution mode is determined according to the following formula:

Among them, T, Pb _L and Pb _R are the motor torque output, the hydraulic brake pressure of the left wheel and the hydraulic brake pressure of the right wheel, and R _w , GR and G are the effective tire radius, gear ratio and hydraulic brake pressure respectively converted into torque. The gain value, T _max , T _min is the upper and lower limits of the motor torque output, and Pb _max is the upper limit of the hydraulic brake pressure. , Then it is the longitudinal tire road friction command of the left and right wheels.

When the power distribution module (122) is a single-axis dual-drive module, the motor driving force distribution mode is determined according to the following formula:

Among them, T _L and T _R are the torque output of the left and right motors, and Pb _L and Pb _R are the motor torque output, the hydraulic brake pressure of the left wheel and the hydraulic brake pressure of the right wheel, respectively, and R _w , GR and G are the effective tire radius respectively. , gear ratio and hydraulic brake pressure are converted into torque gain values, , For the upper and lower limits of the torque output of the right wheel motor, , For the upper and lower limits of the torque output of the left wheel motor, Pb _max is the upper limit of the hydraulic brake pressure. , Then it is the longitudinal tire road friction command of the left and right wheels.

For the application of the third control method, please refer to Figure 4, which is a multi-purpose A control method for a chassis-driven electric vehicle chassis system adopting a non-coupling integrated architecture, characterized in that: the vehicle dynamic control unit (1) according to claim 1 is set in an uncoupled control architecture manner, And the vehicle dynamic control unit (1) includes an optimization controller (11) including a model predictive control algorithm (A) and a tire force distribution controller (12), the optimized controller ( 11) The tire force distribution controller (12) operates separately and does not communicate with each other but has the same control target, and the model predictive control algorithm (A) has a vehicle dynamic optimization problem (A1) The solution computing capability enables the vehicle dynamic control unit (1) to calculate and generate the vehicle dynamic reference value (T) transmitted by the vehicle dynamic sensing system (20) through the optimization controller (11) The first control command (C1) is given to the steering control system (2), and at the same time, the tire force distribution controller (12) calculates and generates the first according to the vehicle dynamic reference value (T) and the current vehicle speed. a second control command (C2) for giving the tire slip control system (3); after receiving the second control command (C2), the tire slip control system (3) also generates a third control command (C3) The chassis power control system (4) is given.

The above uncoupled control architecture is suitable for the chassis of a multi-wheel drive electric vehicle (10) The system (with steering, drive and brake) is used in the least tight integration, unlike the vehicle dynamics control unit (1) used in the loosely coupled control architecture, which optimizes the controller (11) and tire force. The distribution controller (12) operates separately and cannot communicate with each other to calculate the torque output of the motor and brake system in the chassis power control system (4), and improve the differential drive and/or differential brake. The handling and safety of the multi-wheel drive electric vehicle (10).

Second, the optimization controller (11) operates to use the model predictive control algorithm (A), and the tire force distribution controller (12) operates to use the output feedback control.

In the above, the optimization problem (A1) is as follows: u _n =[δ]; Subject to Where J is the cost function, w ₁ and w ₂ are the weights of the respective costs, and T _p and T _C are the time step Δt of the prediction interval and the control interval, respectively. Representative model predictive control algorithm at time t η predicted prediction value of the time t + i, Then the reference value of η at time t + i , Represents the yaw rate of the vehicle, δ represents the steering angle of the front axle tire, I _zz represents the moment of inertia of the vehicle relative to the z axis, L _f is the wheelbase of the front axle, C _f represents the steering stiffness of the front wheel, and ΔX represents the X value The amount of change between the current and the previous time step (X represents a certain physical quantity).

In the above, the tire force distribution controller (12) further includes a tire force a calculation module (121) and a power distribution module (122); the tire force calculation module (121) can use an output according to the vehicle dynamic reference value (T) and the current vehicle speed and yaw rate The feedback control calculates the values of the total longitudinal force of the vehicle body and the yaw control torque, and finally calculates the longitudinal force reference value (C5) required for each tire of the multi-wheel drive electric vehicle (10) and transmits it to the power distribution. a module (122); the power distribution module (122) can be provided according to different types of front and rear wheel motor drive systems of the multi-wheel drive electric vehicle (10), and the tire force calculation module (121) The longitudinal force reference value (C5) assigns the power output of each motor and the brake torque output of each wheel.

Among them, the tire force distribution controller in the uncoupled control architecture, although the same package It includes a longitudinal force calculation module (121) and a power distribution module (122), but it is different from the tire force distribution controller in the loosely coupled control architecture, mainly in the body dynamic optimization controller (11). Does not determine the size of the body yaw control torque, but by the tire force distribution controller (12) It is determined that the tire force distribution controller (12) in the uncoupled control architecture calculates the value of the vehicle yaw control torque for the gain control method using the yaw rate feedback feedback to ensure the stability of the vehicle yaw dynamics.

The tire force calculation module (121) determines the total longitudinal force reference value (C5) according to the following formula: The tire force calculation module (121) calculates a vehicle yaw control torque value according to the following formula: T _d = - k _T I _zz ( AVz - AVz _ref ); the tire force calculation module (121) The following formula determines the longitudinal force of four rounds: Where F _x is the total longitudinal force, T _d is the vehicle yaw control torque, k _F and k _T are the feedback gain values of the longitudinal force and the differential torque, respectively, m and I _zz represent the mass of the vehicle and relative to z The moment of inertia of the shaft, V _x , They are the reference values of the instantaneous longitudinal velocity and longitudinal velocity of the vehicle centroid respectively. AVz and AVz _ref are the reference values of the instantaneous yaw angular velocity and the yaw angular velocity, respectively, and n ₁ and n ₂ are proportional constants.

In the above, the power distribution module (122) includes a single-axis single-drive module and a single-axis dual-drive module according to different types of the motor power system, and the motor output torque distribution control is performed in different manners.

When the power distribution module (122) is a single-axis single-drive module, the power distribution mode is determined according to the formula, and the formula is the same as the second control method.

When the power distribution module (122) is a single-axis dual-drive module, the power distribution mode is determined according to the formula, and the formula is the same as the second control method.

Among the above three control methods, the first control command (C1) is a front wheel steering control system manipulation command; the second control command (C2) includes one or a combination of the following: each drive motor Outputting a torque control command, each wheel brake torque control command; the third control command (C3), which is a drive motor that has been corrected by the tracking control system (31) and the anti-lock brake system (32) And each wheel torque control command; the vehicle dynamic reference value (T) includes the following combination message: vehicle longitudinal speed reference value (T1), vehicle lateral speed reference value (T2), vehicle yaw rate reference value (T3).

Wherein, the front wheel active steering control through the first control command (C1) and the differential driving and/or differential braking control through the third control command (C3) can simultaneously improve the body tracking and yaw dynamic stability, so The vehicle dynamic control unit (1) can effectively integrate the front wheel active steering control system (2) and the chassis power control system (4), and smoothly control the multi-wheel drive electric vehicle (10) without worrying about the problem of poor operation.

Secondly, through the cooperation of different reference values in the vehicle dynamic reference value (T), the vehicle dynamic control unit (1) can follow the reference value to perform the longitudinal speed, the lateral speed, and the multi-wheel drive electric vehicle (10). The yaw angle speed is monitored to effectively judge the driving dynamic stability of the multi-wheel drive electric vehicle (10), so that the vehicle dynamic control unit (1) can effectively and correctly control the multi-wheel drive electric vehicle (10) by calculation. .

The structure, features and effects of the present invention are described in detail above with reference to the embodiments shown in the drawings. However, the above description is only the preferred embodiment of the present invention. Modifications that are consistent with the intent of the present invention are intended to fall within the scope of the invention as long as they are within the scope of the invention.

1‧‧‧Vehicle Dynamic Control Unit

11‧‧‧ Controller

2‧‧‧Steering Control System

3‧‧‧Tire slip control system

31‧‧‧Track Control System

32‧‧‧Anti-lock brake system

4‧‧‧Chassis Power Control System

41‧‧‧Motor drive system

42‧‧‧ brake system

100‧‧‧Integrated Architecture

A‧‧‧ model predictive control algorithm

A1‧‧‧ Vehicle dynamic optimization problem

C1‧‧‧ first control order

C2‧‧‧ second control order

C3‧‧‧ third control order

T‧‧‧Vehicle dynamic reference

T1‧‧‧ Vehicle longitudinal speed reference

T2‧‧‧ Vehicle lateral speed reference

T3‧‧‧ Vehicle yaw rate reference

Claims (21)

A multi-wheel drive electric vehicle system integration architecture capable of cooperating with a multi-wheel drive electric vehicle (10) application having a body dynamic sensing system (20), characterized in that: the integrated structure (100) includes a mounting a vehicle dynamic control unit (1) connected to the vehicle body dynamic sensing system (20) on the multi-wheel drive electric vehicle (10), and the vehicle dynamic control unit (1) is respectively mounted on the multi-wheel drive electric vehicle (10) a steering control system (2), and a tire slip control system (3) connected, and the slip control system (3) is also mounted on the multi-wheel drive electric vehicle (10) The chassis power control system (4) is connected. The system integration architecture of the multi-wheel drive electric vehicle according to claim 1, wherein: the chassis power control system (4) further comprises a multi-wheel drive system (41) and a motor composed of a plurality of motors. Set of multi-wheel brake system (42). A method for controlling a system integration architecture of a multi-wheel drive electric vehicle, characterized in that: the vehicle dynamic control unit (1) according to claim 1 is set in a tightly coupled control architecture manner, and the vehicle dynamic control unit is (1) includes an optimization controller (11) with a model prediction control algorithm (A), and the model prediction control algorithm (A) has a body dynamic optimization problem (A1) solution The capability of the vehicle dynamic control unit (1) to steer the front wheel, the wheel drive and the brake action in one time according to the vehicle dynamic value and the reference value (T) transmitted by the vehicle body dynamic sensing system (20). The influence of the overall vehicle dynamics is taken into consideration, and the first control command (C1) given to the steering control system (2) and the second control command (C2) given to the tire slip control system (3) are directly calculated; After receiving the second control command (C2), the tire slip control system (3), after being corrected, generates a third control command (C3) for the chassis power control system (4). The control method of the system integration architecture of the multi-wheel drive electric vehicle according to claim 3, wherein: the vehicle dynamic optimization problem (A1) is as follows: u _n =[ T _f ,T _rl ,T _rr ,P _{L 1} ,Pb _{R 1} ,Pb _{L 2} ,Pb _{R 2} ,δ ];Subject to Wherein, J is a cost _{function, w 1, w 2, w} 3 are each cost heavy weight, T _p, T _C, respectively, and the control section prediction interval step time step (time step) △ t is a number, Representative model predictive control algorithm at time t η predicted prediction value of the time t + i, Then the reference value of η at time t + i , , , Representing the longitudinal speed, lateral velocity and yaw rate of the vehicle, respectively, T _f , T _rl , T _rr represent the torque provided by the front wheel motor, the left rear wheel motor and the right rear wheel motor, respectively, Pb _{L 1} , Pb _{R 1} , Pb _{L 2} and Pb _{R 2} represent the braking pressure of the left front wheel, the right front wheel, the left rear wheel and the right rear wheel, respectively, δ represents the steering angle of the front axle tire, and m and I _zz represent the mass of the vehicle and the rotation with respect to the z axis, respectively. Through quantity, , , , Representing the longitudinal friction of the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel, respectively. , Representing the lateral friction of the front axle and the lateral friction of the rear axle, respectively, L _f and L _r are the distances between the front axle and the rear axle to the center of mass of the vehicle, respectively, d _f and d _r are the first two rounds and the last two rounds respectively. The track, I _w and R _w are the moment of inertia and effective radius of the tire, respectively. , Tire longitudinal friction and rotational angular acceleration, respectively , The motor drive torque and the brake torque are respectively, where i=L, R represents the left and right wheels, j=1, 2 represents the front and rear axles, C _f and C _r represent the steering rigidity of the front and rear wheels respectively, and ΔX represents X in the present and The amount of change between steps in the previous time ( X represents a certain physical quantity), and η ₁ is the longitudinal speed of the vehicle's centroid. The control method of the system integration architecture of the multi-wheel drive electric vehicle according to claim 4, wherein: the slip control system (3) further has a tracking control system (31) and an anti-lock brake System (32); said first control command (C1), which is a front wheel steering control system maneuver command; said second control command (C2), comprising one or a combination of the following: each drive motor Outputting a torque control command, each wheel brake torque control command; the third control command (C3), which is a drive motor that has been corrected by the tracking control system (31) and the anti-lock brake system (32) And each wheel torque control command; the vehicle dynamic reference value (T) includes the following combination message: vehicle longitudinal speed reference value (T1), vehicle lateral speed reference value (T2), vehicle yaw rate reference value (T3). A method for controlling a system integration architecture of a multi-wheel drive electric vehicle, characterized in that: the vehicle dynamic control unit (1) according to claim 1 is set in a loosely coupled control architecture manner, and the vehicle dynamic control unit is (1) includes an optimization controller (11) incorporating a model predictive control algorithm (A) and a tire force distribution controller (12) capable of transmitting a body bias The aerodynamic control torque command (C4) gives the tire force distribution controller (12), and the model predictive control algorithm (A) has a solution solving ability of the vehicle dynamic optimization problem (A1) through which the optimization control is performed. The controller (11) calculates and generates a first control command (C1) according to the vehicle dynamic reference value (T), and gives the steering control system (2), and at the same time, according to the tire force distribution controller (12) Optimizing the vehicle yaw control torque command (C4), the vehicle dynamic reference value (T), and the current vehicle speed transmitted by the controller (11), calculating and generating a second control life Let (C2) give the tire slip control system (3); after receiving the second control command (C2), the tire slip control system (3) passes through its internal tracking control system (31) and After the anti-lock brake system (32) is modified, a third control command (C3) is also generated for the chassis power control system (4). The control method of the system integration architecture of the multi-wheel drive electric vehicle according to claim 6, wherein: the optimization problem (A1) is as follows: u _n =[ δ,T _d ];Subject to Where J is the cost function, w ₁ , w ₂ , and w ₃ are the weights of the respective costs, and T _p and T _C are the time step Δt of the prediction interval and the control interval, respectively. Representative model predictive control algorithm at time t η predicted prediction value of the time t + i, Then the reference value of η at time t + i , , Representing the longitudinal velocity of the vehicle and the yaw rate, δ represents the steering angle of the front axle tire, T _d is the yaw control torque command, and m and I _zz represent the mass of the vehicle and the moment of inertia with respect to the z axis, respectively. , Representing the lateral friction of the front axle and the lateral friction of the rear axle, respectively, L _f and L _r are the distances from the front axle and the rear axle to the center of mass of the vehicle, respectively, and C _f and C _r represent the steering rigidity of the front and rear wheels, respectively. ΔX represents the amount of change of X between the current and previous time steps ( X represents a certain physical quantity). The control method of the system integration architecture of the multi-wheel drive electric vehicle according to claim 7, wherein: the slip control system (3) further has a tracking control system (31) and an anti-lock brake System (32); the first control command (C1), which is a front wheel steering system maneuver command; the second control command (C2), which includes one or a combination of the following: each drive motor output torque a control command, each wheel torque control command; the third control command (C3), which is a drive motor that has been corrected by the tracking control system (31) and the anti-lock brake system (32) and each The rim brake torque control command; the vehicle dynamic reference value (T) includes the following combined message: vehicle longitudinal speed reference value (T1), vehicle lateral speed reference value (T2), vehicle yaw rate reference value (T3) ). The method for controlling a system integration architecture of a multi-wheel drive electric vehicle according to claim 8, wherein: the tire force distribution controller (12) further includes a tire force calculation module (121), and a power distribution a module (122); the tire force calculation module (121), according to the vehicle yaw control torque command (C4), the vehicle Dynamic reference value (T), and current vehicle speed, calculate the longitudinal force reference value (C5) required for each tire of the multi-wheel drive electric vehicle (10), and transmit it to the power distribution module (122); The power distribution module (122) can be matched with the longitudinal force reference value given by the tire force calculation module (121) according to different types of front and rear wheel motor drive systems of the multi-wheel drive electric vehicle (10). (C5), distribute the torque output of each drive motor and each rim brake. The control method of the system integration architecture of the multi-wheel drive electric vehicle according to claim 9, wherein: the tire force calculation module (121) determines the tire force reference value (C5) according to the following formula: Where F _x is the total longitudinal force, T _d is the vehicle yaw control torque, k is the feedback gain value, m is the mass of the vehicle, and V _x is the instantaneous longitudinal speed. For the reference value of the longitudinal velocity, n ₁ and n ₂ are proportional constants. The control method of the system integration architecture of the multi-wheel drive electric vehicle according to claim 10, wherein the power distribution module (122) can be divided into a single-axis single-drive module according to different types of the motor drive system. Single-axis dual drive module. The control method of the system integration architecture of the multi-wheel drive electric vehicle according to claim 11, wherein: the power distribution module (122) is a single-axis single-drive module, and the motor drive is determined according to the following formula: Force distribution method: Among them, T, Pb _L and Pb _R are the motor torque output, the hydraulic brake pressure of the left wheel and the hydraulic brake pressure of the right wheel, and R _w , GR and G are the effective tire radius, gear ratio and hydraulic brake pressure respectively converted into torque. The gain value, T _max , T _min is the upper and lower limits of the motor torque output, and Pb _max is the upper limit of the hydraulic brake pressure. , Then it is the longitudinal tire road friction command of the left and right wheels. The control method of the system integration architecture of the multi-wheel drive electric vehicle according to claim 11, wherein: the power distribution module (122) is a single-axis dual-drive module, and the motor drive is determined according to the following formula. Force distribution method: Among them, T _L and T _R are the torque output of the left and right motors, and Pb _L and Pb _R are the motor torque output, the hydraulic brake pressure of the left wheel and the hydraulic brake pressure of the right wheel, respectively, and R _w , GR and G are the effective tire radius respectively. , gear ratio and hydraulic brake pressure are converted into torque gain values, , For the upper and lower limits of the torque output of the right wheel motor, , For the upper and lower limits of the torque output of the left wheel motor, Pb _max is the upper limit of the hydraulic brake pressure. , Then it is the longitudinal tire road friction command of the left and right wheels. A control method for a system integration architecture of a multi-wheel drive electric vehicle, characterized in that: the vehicle dynamic control unit (1) according to claim 1 is set in an uncoupled control architecture manner, and the vehicle dynamic control unit is (1) includes an optimization controller (11) having a model prediction control algorithm (A) and a tire force distribution controller (12), the optimization controller (11) and the tire force distribution The controller (12) operates separately, does not communicate with each other but has the same control target, and the model predictive control algorithm (A) has a solving ability of the vehicle dynamic optimization problem (A1), so that the controller The vehicle dynamic control unit (1) can according to the vehicle dynamic reference value (T) transmitted by the vehicle dynamic sensing system (20), according to the optimized controller (11) according to the vehicle a dynamic reference value (T), calculated and generated a first control command (C1), given to the steering control system (2), and simultaneously by the tire force distribution controller (12) according to the vehicle dynamic reference value (T And the current vehicle speed and yaw rate, calculating and generating a second control command (C2), giving the slip control system (3); the slip control system (3) receiving the second control command (C2) After that, after the correction of the tracking control system (31) and the anti-lock braking system (32), a third control command (C3) is also given to the chassis power control system (4). The control method of the system integration architecture of the multi-wheel drive electric vehicle according to claim 14, wherein: the optimization problem (A1) is as follows: u _n =[ δ ];Subject to Where J is the cost function, w ₁ and w ₂ are the weights of the respective costs, and T _p and T _C are the number of time steps Δt of the prediction interval and the control interval, respectively. Representative model predictive control algorithm at time t η predicted prediction value of the time t + i, Then the reference value of η at time t + i , Represents the yaw rate of the vehicle, δ represents the steering angle of the front axle tire, I _zz represents the moment of inertia of the vehicle with respect to the z axis, L _f is the wheelbase of the front axle, C _f represents the steering stiffness of the front wheel, and ΔX represents the X at the moment The amount of change from the previous time step ( X represents a certain physical quantity). The control method of the system integration architecture of the multi-wheel drive electric vehicle according to claim 15, wherein: the first control command (C1) is a front wheel steering control system manipulation command; and the second control command ( C2), which comprises one or a combination of the following: each drive motor output torque control command, each wheel brake torque control command; the third control command (C3), which is an already passed tracking control system (31) And the vehicle dynamic reference value (T) of each of the drive motor and each wheel brake torque control command after the modified anti-lock brake system (32) includes the following combination message: vehicle longitudinal speed reference value (T1), vehicle Lateral speed reference (T2), vehicle yaw rate reference (T3). The method for controlling a system integration architecture of a multi-wheel drive electric vehicle according to claim 16, wherein: the tire force distribution controller (12) further includes a tire force calculation module (121), and a power distribution a module (122); the tire force calculation module (121) can calculate the total longitudinal force of the vehicle body according to the vehicle dynamic reference value (T), the current vehicle speed and the yaw angle speed, and the output feedback control The value of the yaw control torque finally calculates the longitudinal force reference value (C5) required for each tire of the multi-wheel drive electric vehicle (10) and transmits it to the power distribution module (122); the power distribution module The group (122) can be allocated according to different types of front and rear wheel motor drive systems of the multi-wheel drive electric vehicle (10), and the longitudinal force reference value (C5) given by the tire force calculation module (121) is allocated. The power output of each motor and the torque output of each wheel. The control method of the system integration architecture of the multi-wheel drive electric vehicle according to claim 17, wherein: the tire force calculation module (121) determines the longitudinal force reference value (C5) according to the following formula: The tire force calculation module (121) calculates a vehicle yaw control torque value according to the following formula: T _d = - k _T I _zz ( AVz - AVz _ref ); the tire force calculation module (121) The following formula determines the longitudinal force of four rounds: Where F _x is the total longitudinal force, T _d is the vehicle yaw control torque, k _F and k _T are the feedback gain values of the longitudinal force and the differential torque, respectively, m and I _zz represent the mass of the vehicle and relative to z The moment of inertia of the shaft, V _x , They are the reference values of the instantaneous longitudinal velocity and longitudinal velocity of the vehicle centroid respectively. AVz and AVz _ref are the reference values of the instantaneous yaw angular velocity and the yaw angular velocity, respectively, and n ₁ and n ₂ are proportional constants. The method for controlling a system integration architecture of a multi-wheel drive electric vehicle according to claim 18, wherein: the power distribution module (122) includes a single-axis single-drive module and a single-axis according to different types of the motor power system. The dual drive module will control the distribution of the motor output torque in different ways. The control method of the system integration architecture of the multi-wheel drive electric vehicle according to claim 19, wherein: the power distribution module (122) is a single-axis single-drive module, and the power distribution is determined according to the following formula: the way: Among them, T, Pb _L and Pb _R are the motor torque output, the hydraulic brake pressure of the left wheel and the hydraulic brake pressure of the right wheel, and R _w , GR and G are the effective tire radius, gear ratio and hydraulic brake pressure respectively converted into torque. The gain value, T _max , T _min is the upper and lower limits of the motor torque output, and Pb _max is the upper limit of the hydraulic brake pressure. , Then it is the longitudinal tire road friction command of the left and right wheels. The control method of the system integration architecture of the multi-wheel drive electric vehicle according to claim 19, wherein: the power distribution module (122) is a single-axis dual-drive module, and the motor is determined according to the following formula Output power distribution method: Among them, T _L and T _R are the torque output of the left and right motors, and Pb _L and Pb _R are the motor torque output, the hydraulic brake pressure of the left wheel and the hydraulic brake pressure of the right wheel, respectively, and R _w , GR and G are the effective tire radius respectively. , gear ratio and hydraulic brake pressure are converted into torque gain values, , For the upper and lower limits of the torque output of the right wheel motor, , For the upper and lower limits of the torque output of the left wheel motor, Pb _max is the upper limit of the hydraulic brake pressure. , Then it is the longitudinal tire road friction command of the left and right wheels.