CN110539647B - Four-wheel independent drive electric vehicle torque real-time optimization distribution control method facing straight line running working condition - Google Patents

Abstract

The invention relates to a torque real-time optimal distribution control method of a four-wheel independent drive electric vehicle facing a straight line running working condition, which aims at the torque distribution problem of the four-wheel independent drive electric vehicle taking a hub motor as a power unit under the straight line running working condition, a corresponding online optimal distribution control algorithm is formulated, an online optimization result is further compensated and corrected by using an offline obtained optimal distribution coefficient table, the design coupling of a torque distribution function and a vehicle control unit is separated, and the implementation of the modular design of control software is facilitated; the invention realizes the torque optimized distribution of the four-wheel independent drive electric automobile under the straight line running working condition, can effectively improve the energy efficiency of the power assembly on the premise of meeting the driving intention, and simultaneously ensures that the dynamic property and the braking stability of the automobile meet the design indexes.

Description

Four-wheel independent drive electric vehicle torque real-time optimization distribution control method facing straight line running working condition

Technical Field

The invention discloses a torque real-time optimal distribution control method for a four-wheel independent drive electric vehicle facing a straight line running working condition, belongs to the field of design and manufacture of new energy vehicles, and particularly relates to a torque distribution control technology for the four-wheel independent drive electric vehicle.

Background

The birth of the automobile is only hundreds of years till now, but the development process of the human society is deeply influenced by the consumed petroleum resources and the caused traffic pollution. With the continuous consumption of petroleum resources, energy safety has become a serious challenge that must be faced by survival and development in many countries including china; meanwhile, the urgent need for energy conservation and emission reduction and the increasingly stringent emission regulations of the human society have led automobile manufacturers to consciously recognize the necessity of developing electric automobiles.

The four-wheel independent drive electric vehicle taking the hub motor as a power unit has a simplified chassis structure, quick torque response and accurate control execution, and becomes one of the development directions of the future electric vehicles recognized in the industry; the torque distribution strategy aiming at the working condition can obviously influence the economy, the dynamic property and the braking property of the vehicle.

The torque distribution strategy of the four-wheel independent drive electric vehicle taking energy conservation as a target is widely concerned due to the fact that the endurance mileage becomes an important obstacle for preventing the electric vehicle from occupying a mainstream market due to the relatively limited energy density of the battery, in the prior art, energy optimization is only used as a single target, the change of road adhesion is generally ignored or road adhesion information is used as a known condition in the selection of constraint, and the optimization problem is mostly solved in an online numerical value iterative calculation mode. However, in practical engineering application, the real-time acquisition of the road adhesion coefficient is extremely difficult, which can cause that the existing torque distribution control method is difficult to implement or that a certain axle is locked or slipped prematurely due to the deficiency of necessary constraint information, thereby affecting the dynamic performance and braking performance of the vehicle; meanwhile, the online numerical solution of the optimization problem is not beneficial to guaranteeing the real-time performance of the automobile control. Therefore, a real-time torque optimal distribution method for the four-wheel independent drive electric vehicle under the condition of lacking of road adhesion information needs to be established.

Disclosure of Invention

The invention provides a torque real-time optimization distribution control method of a four-wheel independent drive electric vehicle for a straight line running working condition, which can implement optimized torque distribution control on the premise of meeting driving intentions by calibrating control parameters with clear physical meanings and small quantity, effectively improve the energy efficiency of a power assembly of the four-wheel independent drive electric vehicle, and simultaneously ensure that the dynamic property and the braking stability of the vehicle meet design indexes.

The technical scheme adopted by the invention for solving the technical problem is as follows:

a torque real-time optimal distribution control method for a four-wheel independent drive electric vehicle facing a straight line running working condition comprises the following steps:

the first step is as follows: acquiring real-time required torque and real-time speed of the electric automobile through a vehicle control unit of the electric automobile;

the second step is that: judging a rotating speed interval where the rotating speed of the motor corresponding to the acquired real-time vehicle speed is located, taking a minimum interval, and forming a rotating speed vector by using the endpoint of the minimum interval;

the third step: judging the real-time state of the electric automobile according to the acquired real-time required torque, wherein when the real-time required torque is zero, the electric automobile is judged to be in a zero output mode, when the real-time required torque is larger than zero, the electric automobile is judged to be in a driving mode, and when the real-time required torque is smaller than zero, the electric automobile is judged to be in a braking mode;

the fourth step: acquiring an optimized distribution coefficient vector corresponding to the rotating speed vector and a matched vehicle speed vector according to the judged real-time state of the electric vehicle;

the fifth step: calculating a real-time optimal distribution coefficient corresponding to the real-time vehicle speed by utilizing linear interpolation according to the optimal distribution coefficient vector obtained in the fourth step and the matched vehicle speed vector;

and a sixth step: modifying the real-time optimal distribution coefficient obtained in the fifth step by using an energy optimal torque distribution coefficient table manufactured off-line, and obtaining the optimal torque distribution coefficient under the real-time vehicle speed through a preferred decision function;

the seventh step: transmitting the optimal torque distribution coefficient obtained in the sixth step to a torque output calculation function to obtain a final torque output instruction, and then respectively sending the obtained final torque output instruction to a motor controller of a hub motor corresponding to the electric automobile;

as a further preferred aspect of the present invention,

defining the real-time required torque of the electric automobile as T _d The real-time vehicle speed is V _x The rotation speed vector composed of the minimum interval end points is [ n ] ₁ ,n ₂ ]The subscript t represents that the electric vehicle is in a driving mode, the subscript g represents that the electric vehicle is in a braking mode, and the subscript t/g represents the driving mode or the braking mode;

when the automobile is in a driving mode, acquiring an upper limit K and a lower limit K of a distribution coefficient according to a driving constraint calculation function _min,t And K _max,t Then, the rotation speed vector [ n ] is solved according to the adhesion-energy combined optimization function ₁ ,n ₂ ]Corresponding optimized distribution coefficient vector [ K _t,1 ,K _t,2 ]And matched vehicle speed vector [ V _x1 ,V _x2 ]Wherein n is _i In revolutions per minute, subscript i is 1 or 2;

when the automobile is in a braking mode, obtaining an upper limit K and a lower limit K of a distribution coefficient according to a braking constraint calculation function _min,g And K _max,g Then, the rotation speed vector [ n ] is solved according to the adhesion-energy combined optimization function ₁ ,n ₂ ]Corresponding optimized distribution coefficient vector [ K _g,1 ,K _g,2 ]And vehicle speed vector [ V ] _x1 ,V _x2 ]Wherein n is _i Represents the motor speed in revolutions per minute, with index i being 1 or 2;

as a further preferred aspect of the present invention, when the vehicle is in the driving mode, the upper and lower distribution coefficient limits K are obtained according to the driving constraint calculation function _min,t And K _max,t Said driving constraint calculation function being formed by equation (2),

wherein T is _f,max (n _i ) And T _r,max (n _i ) Maximum torque determined for the motor characteristics, obtained from the motor external characteristic curve, n _i The rotating speed of the motor is represented, and the rotating speeds are considered to be approximately equal under the working condition of straight line running because the front wheel and the rear wheel adopt the same hub motor; enabling feedback of maximum torque signal to motor controllerFor the in-wheel motor, T _f,max (n _i ) And T _r,max (n _i ) Or directly obtaining the feedback signals, and when the maximum torque signals fed back by the left hub motor and the right hub motor on the same shaft are inconsistent, taking a smaller value to calculate;

when the automobile is in a braking mode, obtaining an upper limit K and a lower limit K of a distribution coefficient according to a braking constraint calculation function _min,g And K _max,g The brake constraint calculation function is formed by formulas (3) and (4),

wherein L is _r Is the distance from the center of mass of the whole vehicle to the rear axle, h _g Is the height of mass center, L is the wheel base of the vehicle, M is the mass of the whole vehicle, G is the acceleration of gravity, G is the gravity of the whole vehicle, R _w Is the rolling radius of the wheel, T _f,min (n _i ) And T _r,min (n _i ) Algebraic minimum torque determined for the motor characteristics, in which the regenerative braking is specified as negative torque, obtained from the motor external characteristic curve, n _i The rotating speeds of the motors are represented, and the rotating speeds are considered to be approximately equal under the working condition of linear running because the front wheels and the rear wheels adopt the same hub motors;

for in-wheel motors where the motor controller can feed back a minimum torque signal, T _f,min (n _i ) And T _r,min (n _i ) Or directly obtaining the feedback signals, and calculating by taking a larger value when the maximum torque signals fed back by the left and right hub motors on the same shaft are inconsistent;

as a further preferred aspect of the present invention, the analytical form of the optimal solution of the optimization index function consumed in the adhesion-energy joint optimization function comprises the steps of,

step 4.1: the optimization index function is shown in equation (5),

wherein λ is ₁ And λ ₂ Respectively representing the optimal weight of road adhesion utilization and the optimal weight of motor energy consumption, F _zf And F _zr Representing the loads, Σ P, of the front and rear axles of the vehicle, respectively _hub Represents the sum of the power consumptions of the four in-wheel motors, T _fl 、T _fr Respectively, the left and right wheel output torque of the front axle, T _rl 、T _rr Output torque, T, of the left and right wheels of the rear axle, respectively _d For real-time torque demand, T _i For the output torque of each wheel, the index i indicates fl, fr, rl, rr, R _w The JEAA is an optimization index function;

step 4.2: the power loss characteristic field obtained by the motor bench test is calculated by adopting a formula (6) to obtain a motor power consumption characteristic field,

wherein T represents the motor torque measured by the test and the unit is N m; n represents the motor rotating speed measured by the test, and the unit is revolutions per minute, namely rpm; p _loss The loss power measured under each group (T, n) is obtained by subtracting the mechanical power output by the wheel end from the input direct current electric power, and the unit is kw; p _hub The unit of the electric power consumption of the hub motor is kw, positive torque is specified to represent driving, negative torque represents braking, positive power represents the power consumed by the motor from a battery, negative power represents the power fed back to the battery by the motor, and test rotating speed data in a characteristic field is made into a motor rotating speed working condition point data table according to a test result;

and 4.3, step: according to two modes of braking and driving, the relationship of the power consumption of the motor with the change of the torque under different rotating speeds is respectively fitted by adopting a cubic polynomial mode, the fitting formula is shown as (7), wherein a, b, c and d are parameters to be fitted and correspond to the rotating speed working condition point data table manufactured in the step (4.2)

P _hub ＝a(n)T _i ³ +b(n)T _i ² +c(n)T _i +d(n) (7)

Step 4.4: since the torque outputs of the left and right wheels should be the same under the straight-line driving condition, the output torque of the left and right wheels of the front axle is T _fl ＝T _fr ＝T _f The output torque of the left and right wheels of the rear axle is T _rl ＝T _rr ＝T _r The specific expression is shown in (8).

Wherein, K is defined as the proportion of the output torque of the front wheel accounting for 50 percent of the required torque, the proportion is the distribution coefficient of the torque of the front axle and the rear axle, T _d Torque is demanded in real time;

step 4.5: substituting the formulas (6), (7) and (8) into the formula (5), obtaining an analytic expression of a quadratic polynomial about K of the optimization problem, wherein coefficients are shown in formulas (10) - (12) as shown in (9);

J _EAA (K)＝τ ₁ K ² -τ ₂ K+ε (9)

wherein, T _d For real-time torque demand, λ ₁ And λ ₂ Respectively representing the optimal weight of road adhesion utilization and the optimal weight of motor energy consumption, F _zf And F _zr Respectively representing the loads of the front axle and the rear axle of the vehicle, a, b, c and d are parameters to be fitted，R _w Is the rolling radius of the wheel, J _EAA Representing an optimization index function;

step 4.6: for J in the formula (9) _EAA (K) The first order partial derivative of K is found and made equal to zero to obtain the extreme point of the function, and then the second order partial derivative of K is found for the function to obtain the monotonicity information of the function, and the results of the extreme point and the second order partial derivative are shown in equations (13) and (14).

The second-order partial derivative about K is calculated for the optimization index function JEAA, and Kex represents a possible extreme point of the JEAA function;

step 4.7: according to the principle of minimum value, the global minimum value point of the optimization problem can be obtained by a classification discussion mode, and the specific method is as follows,

4.7.1, when τ ₁ <When 0, K is judged _ex Representing the distance between one possible extreme point of the JEAA function and the partition coefficient boundary,

if K is _ex ≥K _max,t/g Then let K _t/g,i ＝K _min,t/g ；

If K is _ex ≤K _min,t/g Let K _t/g,i ＝K _max,t/g ；

If K is _min,t/g <K _ex <K _max,t/g Let K _t/g,i ＝argmax|κ-K _ex |(κ∈{K _min,t/g ,K _max,t/g })；

4.7.2 when τ ₁ >When 0, K is judged _ex Whether it is within the feasible domain, if K _ex >K _max,t/g Let K _t/g,i ＝K _max,t/g (ii) a If K is _ex <K _min,t/g Let K _t/g,i ＝K _min,t/g (ii) a Otherwise, let K _t/g,i ＝K _ex 。

4.7.3 when τ is greater ₁ When 0, the value τ is judged ₂ If τ is ₂ >0, order K _t/g,i ＝K _max,t/g (ii) a Otherwise, let K _t/g,i ＝K _min,t/g ；

Wherein, K _t/g,i Expressing that the optimization index function (5) in the step 4.1 obtains a value K of a global minimum value under a driving mode or a braking mode, wherein the subscript i is 1 or 2, and when the automobile is in the driving mode, K _min,t And K _max,t For the upper and lower limits of the distribution coefficient obtained from the driving constraint computation function, when the vehicle is in the braking mode, K _min,g And K _max,g Obtaining an upper limit and a lower limit of a distribution coefficient according to a brake constraint calculation function;

as a further preferred aspect of the present invention, the rotation speed vector [ n ] is obtained by an analytical form of the optimal solution of the optimization index function ₁ ,n ₂ ]Corresponding optimized distribution coefficient vector [ K _t/g,1 ,K _t/g,2 ]And matched vehicle speed vector [ V _x1 ,V _x2 ]The method comprises the following steps:

step 5.1: the rotation speed vector composed of the minimum interval end points is [ n ] ₁ ,n ₂ ]；

Step 5.2: judging whether the input data meets the solving requirement of the optimization problem,

if the motor is in the driving mode and the required torque exceeds the total peak torque of the motor, correcting the required torque into the sum of all the peak torques, and then solving the rotating speed n according to the optimization solving method in the step 4.7 and the fitting data in the step 4.3 ₁ ,n ₂ Corresponding optimized distribution coefficient vector [ K _t,1 ,K _t,2 ]；

If in the braking mode, when the total required torque is smaller than the total regenerative braking torque which can be provided by the motor or the feasible region obtained by the braking constraint calculation function is an empty set, K is enabled _g,i ＝K _I (ii) a Otherwise, according to the optimization solving method in the step 4.7 and the optimization solving method in the step 4.3To find the corresponding optimal distribution coefficient vector [ K ] _g,1 ,K _g,2 ]；

Step 5.3: the rotation speed vector [ n ₁ ,n ₂ ]Converted to a matched vehicle speed vector [ V ] according to equation (15) _x1 ,V _x2 ]

Wherein R is _w Is the rolling radius of the wheel, n _i Indicating the motor speed, subscript i being 1 or 2, n ₁ ,n ₂ Obtaining real-time vehicle speed; as a further preferable aspect of the present invention, in the fifth step, the calculation formula of the real-time optimal distribution coefficient corresponding to the real-time vehicle speed by using linear interpolation is as follows:

wherein, K _t/g,i Expressing that the optimization index function (5) in the step 4.1 obtains the value K of the global minimum value under the driving mode or the braking mode, the subscript i is 1 or 2, and V _x For real-time vehicle speed, V _xi Subscript i is 1 or 2 for the matched vehicle speed vector;

as a further preferred aspect of the present invention, in the sixth step, the step of forming the energy-optimized torque distribution coefficient table created off-line includes the steps of:

step 7.1: the energy-optimal torque distribution coefficient calculation method is shown in equation (16),

wherein P is _d (. cndot.) is a motor power calculation function, which can be calculated from the motor power consumption characteristic field in step 4.2 by using a linear interpolation method, and the constrained calculation formula is the above-mentioned formulas (2) - (4), V _x For real-time vehicle speed, T _d The torque is required in real time by the electric automobile, and K is the torque required by the output torque of the front wheelA proportion of 50%;

and 7.2: the problem is solved at each vehicle speed V by using a genetic algorithm optimizing function provided by a Matlab optimizing tool box _x And the required torque T _d Under the condition, respectively obtaining corresponding energy optimal distribution coefficients, and making a two-dimensional number table about the vehicle speed and the required torque;

as a further preference of the present invention, the preferred decision function in the sixth step is formed by equation (17),

K _opt ＝arg min J _EAA (κ) (κ∈{K _t/g ,K _off }) (17)

wherein, the function J _EAA As can be seen from equation (5), the motor power consumption part is directly obtained by interpolation calculation of the motor power consumption characteristic field; k _off Is obtained by an energy optimal torque distribution coefficient calculation method according to the current demand torque T _d And vehicle speed V _x Looking up a table to obtain; k _t/g Can be obtained from formula (1);

as a further preferable aspect of the present invention, in the seventh step, the torque output calculation function includes the steps of:

step 9.1, determining torque request commands of hub motors of front and rear axles according to a formula (18), wherein the output torques of the left and right wheels are the same due to the fact that the hub motors belong to the straight-line driving working condition

Wherein, T _d For the real-time torque demand of the electric automobile, the torque output of the left wheel and the torque output of the right wheel under the linear running working condition are the same, so the output torque of the left wheel and the right wheel of the front axle is regulated to be T _fl ＝T _fr ＝T _f The output torque of the left and right wheels of the rear axle is T _rl ＝T _rr ＝T _r ；

9.2, if the driving mode is adopted, the result is directly output;

if the motor is in the braking mode, further judging whether the torque output calculated by the formula (18) exceeds the regenerative braking torque boundary of the motor;

if the electric machine is unable to provide sufficient braking torque, the remaining torque is made up by friction braking according to the maximum regenerative torque output currently allowed;

if the motor can provide the torque calculated by the formula (18), the output calculation result is directly output.

Through the technical scheme, compared with the prior art, the invention has the following beneficial effects:

1. according to the method, the real-time acquisition of the road surface adhesion information is not needed in the control process, the global optimal torque distribution result aiming at the proposed optimization index function can be acquired in the vehicle-mounted controller in real time, the energy efficiency of the power assembly of the four-wheel independent drive electric vehicle is effectively improved, and meanwhile, the dynamic performance and the braking stability of the vehicle are ensured to meet the design index;

2. according to the invention, by designing an optimization index function comprehensively considering the energy consumption of the power assembly and the road adhesion utilization rate, a feasible domain boundary calculation model of the distribution coefficient completely considering the external characteristics of the motor, the braking safety and the braking regulation limit is established, so that the dependence of a control algorithm on the real-time acquisition of the road adhesion coefficient can be effectively avoided;

3. the invention develops the online optimization allocation control algorithm by deducing the global optimal solution of the designed optimization problem, and solves the real-time puzzlement of online solution of the optimization problem.

Drawings

The invention is further illustrated with reference to the following figures and examples.

FIG. 1 is a schematic diagram of the application of the preferred embodiment of the present invention;

FIG. 2 is a graph of the field versus external characteristic of the motor loss power characteristic of the preferred embodiment of the present invention;

FIG. 3 is a table of motor speed operating point data and corresponding motor coefficient fit table in accordance with a preferred embodiment of the present invention;

fig. 4 is a flowchart of a control method of the preferred embodiment of the present invention.

Detailed Description

The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic views illustrating only the basic structure of the present invention in a schematic manner, and thus show only the constitution related to the present invention.

The invention relates to a torque real-time optimal distribution control method of a four-wheel independent drive electric vehicle facing a straight line running working condition, which comprises the following steps of:

the first step is as follows: acquiring real-time required torque and real-time speed of the electric automobile through a vehicle control unit of the electric automobile;

the second step is that: judging a rotating speed interval where the rotating speed of the motor corresponding to the acquired real-time vehicle speed is located, taking a minimum interval, and forming a rotating speed vector by using the endpoint of the minimum interval;

the third step: judging the real-time state of the electric automobile according to the acquired real-time required torque, wherein when the real-time required torque is zero, the electric automobile is judged to be in a zero output mode, when the real-time required torque is larger than zero, the electric automobile is judged to be in a driving mode, and when the real-time required torque is smaller than zero, the electric automobile is judged to be in a braking mode;

the fourth step: acquiring an optimized distribution coefficient vector corresponding to the rotating speed vector and a matched vehicle speed vector according to the judged real-time state of the electric vehicle;

the fifth step: calculating a real-time optimal distribution coefficient corresponding to the real-time vehicle speed by utilizing linear interpolation according to the optimal distribution coefficient vector obtained in the fourth step and the matched vehicle speed vector;

and a sixth step: modifying the real-time optimal distribution coefficient obtained in the fifth step by using an energy optimal torque distribution coefficient table manufactured off-line, and obtaining the optimal torque distribution coefficient under the real-time vehicle speed through a preferred decision function;

the seventh step: transmitting the optimal torque distribution coefficient obtained in the sixth step to a torque output calculation function to obtain a final torque output instruction, and then respectively sending the obtained final torque output instruction to a motor controller of a hub motor corresponding to the electric automobile;

the vehicle controller is commonly used in a centralized driving electric vehicle at present, and plays a role in analyzing the operation of a person on an accelerator pedal and a brake pedal into a real-time required torque and processing a signal of the vehicle, such as calculating a real-time vehicle speed. Because a general electric automobile only has one motor, the obtained required torque can be directly sent to a motor controller, but for a four-wheel independent drive electric automobile, because of the existence of a plurality of motors, after a required torque signal analyzed by a whole automobile controller is obtained, torque distribution needs to be further carried out by using the method provided by the invention, so that a torque request instruction for each in-wheel motor is generated;

based on the background, the application provides a control method for real-time optimized distribution of the torque of the four-wheel independent drive electric vehicle on the premise of a straight line running working condition;

example (b):

fig. 1 shows a concrete form of the control method applied to a torque distribution control module, where the torque distribution control module is functionally connected with a vehicle control unit, a motor controller of a hub motor, and a friction brake controller, and analyzes a driver required torque T from the vehicle control unit _d According to the current vehicle speed information V _x Carrying out torque optimized distribution to obtain distributed front wheel motor torque T _f Rear wheel motor torque T _r And front wheel friction braking torque T _bf Rear wheel friction braking torque T _br And the control signals are respectively sent to the controllers of the corresponding actuating mechanisms, so that the driving and braking control of the automobile is realized.

It should be noted that, the so-called torque distribution module and the vehicle controller are functionally divided, and do not represent that related functions must be placed in two independent controllers, and the functions of the vehicle controller and the functions of the torque distribution control module may be integrated into one controller to operate under the permission of hardware resources.

Earlier stage work:

defining the real-time required torque of the electric automobile as Td, the real-time speed as Vx,

performing bench test on the power loss characteristic of a hub motor used by the electric automobile by using a dynamometer to obtain a power loss characteristic field and an external characteristic curve of the motor, as shown in fig. 2; the method comprises the following steps that positive torque is used for driving, negative torque is used for regenerative braking, positive power is used for consuming power from a battery of the motor, and negative power is used for feeding power back to the battery of the motor; the motor power loss is obtained by subtracting the mechanical power output by the wheel end from the input direct current power under different rotating speed and torque combinations; the external characteristic curves are the maximum torque and the minimum torque which can be output by the motor at different rotating speeds; defining subscript t to indicate that the electric vehicle is in a driving mode, subscript g to indicate that the electric vehicle is in a braking mode (i.e., a regenerative braking mode), and subscript t/g to indicate a driving mode or a braking mode;

FIG. 4 shows the specific implementation steps of the preferred embodiment:

the first step is as follows: acquiring a current vehicle demand torque Td and a real-time vehicle speed Vx by a vehicle controller;

the second step is that: judging a rotating speed interval (minimum interval) where the rotating speed of the motor corresponding to the real-time vehicle speed is located by using a motor rotating speed working condition point data table obtained by a wheel hub motor bench test, and forming a rotating speed vector [ n ] by using the end point of the minimum interval ₁ ,n ₂ ]，

The motor rotating speed operating point data table is obtained in the following mode:

the power loss characteristic field obtained by the rack test of the hub motor is calculated by adopting a formula (6) to obtain a power consumption characteristic field of the motor,

wherein T represents the motor torque measured by the test and the unit is N m; n represents the motor rotating speed measured by the test, and the unit is revolutions per minute, namely rpm; p _loss The loss power measured under each group (T, n) is obtained by subtracting the mechanical power output by the wheel end from the input direct current electric power, and the unit is kw; p _hub The unit of the electric power consumption of the hub motor is kw, and test rotating speed data in the characteristic field is made into a motor rotating speed working condition point data table according to a test result;

the third step: judging the real-time state of the electric automobile according to the acquired real-time required torque, wherein when the real-time required torque is zero, the electric automobile is judged to be in a zero output mode, when the real-time required torque is larger than zero, the electric automobile is judged to be in a driving mode, and when the real-time required torque is smaller than zero, the electric automobile is judged to be in a braking mode;

the fourth step: obtaining an optimized distribution coefficient vector corresponding to the rotating speed vector and a matched vehicle speed vector according to the judged real-time state of the electric vehicle, and comprising the following steps of:

the rotation speed vector composed of the minimum interval end points is [ n ] ₁ ,n ₂ ]；

Judging whether the input data meets the solving requirement of the optimization problem,

if the motor is in the driving mode and the required torque exceeds the total peak torque of the motor, correcting the required torque into the sum of all the peak torques, and then solving the rotating speed n according to an optimization solving method and fitting data ₁ ,n ₂ Corresponding optimized distribution coefficient vector [ K _t,1 ,K _t,2 ]；

If in the braking mode, when the total required torque is smaller than the total regenerative braking torque which can be provided by the motor or the feasible region obtained by the braking constraint calculation function is an empty set, K is enabled _g,i ＝K _I (ii) a Otherwise, according to the optimization solving method and the fitting data, solving the corresponding optimized distribution coefficient vector [ K _g,1 ,K _g,2 ]；

The rotation speed vector [ n ₁ ,n ₂ ]Converted to a matched vehicle speed vector [ V ] according to equation (15) _x1 ,V _x2 ]

Wherein R is _w Is the rolling radius of the wheel, n _i Indicating the motor speed, subscript i being 1 or 2, n ₁ ,n ₂ Obtaining real-time vehicle speed;

specifically, the method comprises the following steps: defining the distribution coefficient of the front and rear axle torques as K,

when the vehicle is in a zero output mode, the output of all the motors is zero;

when the automobile is in a driving mode, acquiring an upper limit K and a lower limit K of a distribution coefficient according to a driving constraint calculation function _min,t And K _max,t Then, the rotation speed vector [ n ] is solved according to the adhesion-energy combined optimization function ₁ ,n ₂ ]Corresponding optimized distribution coefficient vector [ K _t,1 ,K _t,2 ]And matched vehicle speed vector [ V _x1 ,V _x2 ]Wherein n is _i In revolutions per minute, subscript i is 1 or 2;

when the automobile is in a braking mode, obtaining an upper limit K and a lower limit K of a distribution coefficient according to a braking constraint calculation function _min,g And K _max,g Then, the rotation speed vector [ n ] is solved according to the adhesion-energy combined optimization function ₁ ,n ₂ ]Corresponding optimized distribution coefficient vector [ K _g,1 ,K _g,2 ]And vehicle speed vector [ V ] _x1 ,V _x2 ]Wherein n is _i Represents the motor speed in revolutions per minute, with index i being 1 or 2;

the more detailed description is: when the automobile is in a driving mode, acquiring an upper limit K and a lower limit K of a distribution coefficient according to a driving constraint calculation function _min,t And K _max,t Said driving constraint calculation function being formed by equation (2),

wherein T is _f,max (n _i ) And T _r,max (n _i ) Maximum torque determined for the motor characteristics, obtained from the motor external characteristic curve, n _i The rotating speed of the motor is represented, and the rotating speeds are considered to be approximately equal under the working condition of straight line running because the front wheel and the rear wheel adopt the same hub motor; for a wheel hub motor with a motor controller capable of feeding back a maximum torque signal, T _f,max (n _i ) And T _r,max (n _i ) Or directly obtaining the feedback signals, and when the maximum torque signals fed back by the left hub motor and the right hub motor on the same shaft are inconsistent, taking a smaller value to calculate;

when the automobile is in a braking mode, obtaining an upper limit K and a lower limit K of a distribution coefficient according to a braking constraint calculation function _min,g And K _max,g The brake constraint calculation function is formed by formulas (3) and (4),

wherein L is _r Is the distance h from the center of mass of the whole vehicle to the rear axle _g Is the height of mass center, L is the wheel base of the vehicle, M is the mass of the whole vehicle, G is the acceleration of gravity, G is the gravity of the whole vehicle, R _w As the rolling radius of the wheel, K in formula (3) _I The braking curve is derived from an automobile braking I curve, and the purpose is to prevent a rear wheel from locking before a front wheel in the braking process and ensure the braking stability; k _ECE The braking strength requirement proposed by ECE braking regulation is deduced, so that the problem that the braking distance is prolonged due to premature locking of a front axle in the braking process is solved;

T _f,min (n _i ) And T _r,min (n _i ) Algebraic minimum torque determined for the motor characteristics, in which the regenerative braking is specified as negative torque, obtained from the motor external characteristic curve, n _i The rotating speed of the motor is represented, and the rotating speeds are considered to be approximately equal under the working condition of straight line running because the front wheel and the rear wheel adopt the same hub motor;

for a hub motor with a motor controller capable of feeding back a minimum torque signal, T _f,min (n _i ) And T _r,min (n _i ) Or directly obtaining the feedback signals, and calculating by taking a larger value when the maximum torque signals fed back by the left and right hub motors on the same shaft are inconsistent;

in order to avoid the defect that the prior art only takes energy conservation as an optimization target and ignores the change of the road adhesion coefficient or takes the road adhesion coefficient as a known condition, an optimization index function which considers the road adhesion utilization optimization and the energy consumption of the electric drive assembly at the same time is established as shown in a formula (5);

the analytic form of the optimal solution of the optimization index function consumed in the attachment-energy joint optimization function comprises the following steps,

the optimization index function is shown in equation (5),

wherein λ is ₁ And λ ₂ Respectively representing the optimization weight of road adhesion utilization and the optimization weight of motor energy consumption (in practical application, the optimization weights can be calibrated through vehicle road tests), F _zf And F _zr Representing the loads, Σ P, of the front and rear axles of the vehicle, respectively _hub Represents the sum of the power consumptions of the four in-wheel motors, T _fl 、T _fr Respectively, the left and right wheel output torque of the front axle, T _rl 、T _rr Output torque, T, of the left and right wheels of the rear axle, respectively _d For real-time torque demand, T _i For the output torque of each wheel, the subscript i denotes fl, fr, rl, rr, R _w The rolling radius of the wheel is JEAA, and the JEAA is an optimization index function;

since the torque outputs of the left and right wheels should be the same under the straight-line driving condition, the output torque of the left and right wheels of the front axle is T _fl ＝T _fr ＝T _f The output torque of the left and right wheels of the rear axle is T _rl ＝T _rr ＝T _r The specific expression is shown in (8).

Wherein, K is defined as the proportion of the output torque of the front wheel accounting for 50 percent of the required torque, the proportion is the distribution coefficient of the torque of the front axle and the rear axle, T _d Torque is demanded in real time;

according to two modes of braking and driving, the relationship of the power consumption of the motor with the change of the torque under different rotating speeds is respectively fitted by adopting a cubic polynomial mode, the fitting formula is shown as (7), wherein a, b, c and d are parameters to be fitted and correspond to the rotating speed working condition point data table manufactured in the second step

P _hub ＝a(n)T _i ³ +b(n)T _i ² +c(n)T _i +d(n) (7)

The fitting coefficient is made into a motor fitting coefficient table corresponding to the electrode rotating speed working condition data table as shown in fig. 3, and the parameters are obtained through the fitting process described in the step. The parameters are different when being fitted at different rotating speeds, so that (n) is added in the formula (7) to show that the parameters are related to the rotating speed;

the global optimal analytic solution of the optimization problem is established, the real-time disadvantage that the prior art mostly depends on-line numerical iteration to solve the optimization problem is avoided,

substituting the formulas (6), (7) and (8) into the formula (5), obtaining an analytical expression of a quadratic polynomial of the optimization problem about K, wherein the analytical expression is shown as (9), and coefficients are shown as formulas (10) - (12);

J _EAA (K)＝τ ₁ K ² -τ ₂ K+ε (9)

wherein, T _d For real-time torque demand, λ ₁ And λ ₂ Respectively representing the optimal weight of road adhesion utilization and the optimal weight of motor energy consumption, F _zf And F _zr Respectively representing the loads of the front axle and the rear axle of the vehicle, a, b, c, d are parameters to be fitted, R _w Is the rolling radius of the wheel, J _EAA Representing an optimization index function;

for J in the formula (9) _EAA (K) This can be obtained by taking the first order partial derivative for K and making it equal to zeroAnd (3) solving a second-order partial derivative related to K of the function for obtaining monotonicity information of the function at the extreme point of the function, wherein the results of the extreme point and the second-order partial derivative are shown in formulas (13) and (14).

The second-order partial derivative about K is calculated for the optimization index function JEAA, and Kex represents a possible extreme point of the JEAA function;

according to the principle of minimum value, the global minimum value point of the optimization problem can be obtained by a classification discussion mode, and the specific method is as follows,

when tau is ₁ <When 0, K is judged _ex Representing the distance between one possible extreme point of the JEAA function and the partition coefficient boundary,

if K is _ex ≥K _max,t/g Then let K _t/g,i ＝K _min,t/g ；

If K is _ex ≤K _min,t/g Let K _t/g,i ＝K _max,t/g ；

If K is _min,t/g <K _ex <K _max,t/g Let K _t/g,i ＝argmax|κ-K _ex |(κ∈{K _min,t/g ,K _max,t/g })；

When tau is ₁ >When 0, judge K _ex Whether within a feasible domain, if K _ex >K _max,t/g Let K _t/g ,i＝K _max,t/g (ii) a If K is _ex <K _min,t/g Let K be _t/g,i ＝K _min,t/g (ii) a Otherwise, let K _t/g,i ＝K _ex 。

When tau is ₁ When 0, the value τ is judged ₂ If τ is ₂ >0, order K _t/g,i ＝K _max,t/g (ii) a Otherwise, let K _t/g,i ＝K _min,t/g ；

Wherein, K _t/g I represents the value K of the global minimum value obtained by the optimization index function (5) in the driving mode or the braking mode, the subscript i is 1 or 2, and when the automobile is in the driving mode, K is _min,t And K _max,t For the upper and lower limits of the distribution coefficient obtained from the driving constraint calculation function, when the vehicle is in the braking mode, K _min,g And K _max,g Obtaining an upper limit and a lower limit of a distribution coefficient according to a brake constraint calculation function;

calculating a rotation speed vector [ n ] according to the analysis form of the optimal solution of the optimization index function ₁ ,n ₂ ]Corresponding optimized distribution coefficient vector [ K _t/g,1 ,K _t/g,2 ]And matched vehicle speed vector [ V _x1 ,V _x2 ](ii) a The fifth step: the calculation formula for calculating the real-time optimal distribution coefficient corresponding to the real-time vehicle speed by utilizing linear interpolation is as follows:

wherein, K _t/g,i Expressing that the optimization index function (5) in the step 4.1 obtains the value K of the global minimum value under the driving mode or the braking mode, the subscript i is 1 or 2, and V _x For real-time vehicle speed, V _xi For a matching vehicle speed vector, subscript i is 1 or 2.

And a sixth step: modifying the real-time optimal distribution coefficient obtained in the fifth step by using an energy optimal torque distribution coefficient table manufactured off-line, and obtaining the optimal torque distribution coefficient under the real-time vehicle speed through a preferred decision function;

the step of forming the off-line manufactured energy optimal torque distribution coefficient table comprises the following steps:

the energy-optimal torque distribution coefficient calculation method is shown in equation (16),

wherein P is _d (. cndot.) is a motor power calculation function, which can be calculated from the motor power consumption characteristic field in step 4.2 by using a linear interpolation method, and the constrained calculation formula is the above-mentioned formulas (2) - (4), V _x For real-time vehicle speed, T _d The real-time torque demand of the electric automobile is realized, and K is the proportion of the output torque of the front wheel accounting for 50 percent of the demand torque;

the problem is solved at each vehicle speed V by using a genetic algorithm optimizing function provided by a Matlab optimizing tool box _x And the required torque T _d Under the condition, respectively obtaining corresponding energy optimal distribution coefficients, and making a two-dimensional number table about the vehicle speed and the required torque;

preferably the decision function is formed by equation (17),

K _opt ＝arg min J _EAA (κ)(κ∈{K _t/g ,K _off }) (17)

wherein, the function J _EAA As can be seen from equation (5), the motor power consumption part is directly obtained by interpolation calculation of the motor power consumption characteristic field; k is _off Is obtained by an energy optimal torque distribution coefficient calculation method according to the current demand torque T _d And vehicle speed V _x Looking up a table to obtain; k _t/g The formula (1) can be obtained;

the seventh step: transmitting the optimal torque distribution coefficient obtained in the sixth step to a torque output calculation function, obtaining a final torque output command, and then sending the obtained final torque output command to a motor controller of at least one in-wheel motor of the electric vehicle, wherein the torque output calculation function comprises the following steps:

determining torque request commands of hub motors of front and rear axles according to a formula (18), wherein the output torques of left and right wheels are the same due to the fact that the hub motors belong to the straight-line driving working condition

Wherein, T _d The torque is required in real time for the electric automobile, and the electric automobile is driven to the left under the condition of straight line drivingThe right-wheel torque output should be the same, so that the front axle left and right wheel output torque is specified as T _fl ＝T _fr ＝T _f The output torque of the left and right wheels of the rear axle is T _rl ＝T _rr ＝T _r ；

If the driver is in the driving mode, directly outputting the result;

if in the braking mode, further determining whether the torque output calculated by equation (18) exceeds the motor regenerative braking torque boundary;

if the electric machine is unable to provide sufficient braking torque, the remaining torque is made up by friction braking according to the maximum regenerative torque output currently allowed;

if the motor can provide the torque calculated by the formula (18), the output calculation result is directly output.

It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

The meaning of "and/or" as used herein is intended to include both the individual components or both.

The term "connected" as used herein may mean either a direct connection between components or an indirect connection between components via other components.

In light of the foregoing description of the preferred embodiment of the present invention, many modifications and variations will be apparent to those skilled in the art without departing from the spirit and scope of the invention. The technical scope of the present invention is not limited to the contents of the specification, and must be determined according to the scope of the claims.

Claims (9)

1. A four-wheel independent drive electric vehicle torque real-time optimization distribution control method facing a straight line running working condition is characterized in that: the method comprises the following steps:

the first step is as follows: acquiring real-time required torque and real-time speed of the electric automobile through a vehicle control unit of the electric automobile;

the second step is that: judging a rotating speed interval where the rotating speed of the motor corresponding to the acquired real-time vehicle speed is located, taking a minimum interval, and forming a rotating speed vector by using the endpoint of the minimum interval;

the third step: judging the real-time state of the electric automobile according to the acquired real-time required torque, wherein when the real-time required torque is zero, the electric automobile is judged to be in a zero output mode, when the real-time required torque is larger than zero, the electric automobile is judged to be in a driving mode, and when the real-time required torque is smaller than zero, the electric automobile is judged to be in a braking mode;

the fourth step: acquiring an optimized distribution coefficient vector corresponding to the rotating speed vector and a matched vehicle speed vector according to the judged real-time state of the electric vehicle;

the fifth step: calculating a real-time optimal distribution coefficient corresponding to the real-time vehicle speed by utilizing linear interpolation according to the optimal distribution coefficient vector obtained in the fourth step and the matched vehicle speed vector;

and a sixth step: modifying the real-time optimal distribution coefficient obtained in the fifth step by using an energy optimal torque distribution coefficient table manufactured off-line, and obtaining the optimal torque distribution coefficient under the real-time vehicle speed through a preferred decision function;

the seventh step: and transmitting the optimal torque distribution coefficient obtained in the sixth step to a torque output calculation function to obtain a final torque output instruction, and then respectively sending the obtained final torque output instruction to a motor controller of the hub motor corresponding to the electric automobile.

2. The real-time torque optimal distribution control method for the four-wheel independent drive electric vehicle facing the straight-line running working condition according to claim 1, characterized by comprising the following steps of:

defining the real-time required torque of the electric automobile as T _d The real-time speed is V _x Composition of minimum interval end pointsHas a rotational speed vector of [ n ] ₁ ,n ₂ ]The subscript t represents that the electric vehicle is in a driving mode, the subscript g represents that the electric vehicle is in a braking mode, and the subscript t/g represents the driving mode or the braking mode;

when the automobile is in a driving mode, acquiring upper and lower distribution coefficient limits Kmin and t and Kmax and t according to a driving constraint calculation function, and then solving a rotating speed vector [ n ] according to an adhesion-energy combined optimization function ₁ ,n ₂ ]Corresponding optimized distribution coefficient vector [ K _t,1 ,K _t,2 ]And the matched vehicle speed vector V _x1 ,V _x2 ]Wherein n is _i In revolutions per minute, subscript i is 1 or 2;

when the automobile is in a braking mode, obtaining an upper limit K and a lower limit K of a distribution coefficient according to a braking constraint calculation function _min,g And K _max,g Then, the rotation speed vector [ n ] is solved according to the adhesion-energy combined optimization function ₁ ,n ₂ ]Corresponding optimized distribution coefficient vector [ K _g,1 ,K _g,2 ]And vehicle speed vector [ V ] _x1 ,V _x2 ]Wherein n is _i Indicating the motor speed in revolutions per minute, with index i being 1 or 2.

3. The real-time torque optimal distribution control method for the four-wheel independent drive electric vehicle facing the straight-line running working condition as claimed in claim 2, wherein:

when the automobile is in a driving mode, acquiring an upper limit K and a lower limit K of a distribution coefficient according to a driving constraint calculation function _min,t And K _max,t Said driving constraint calculation function being formed by equation (2),

wherein T is _f,max (n _i ) And T _r,max (n _i ) Maximum torque determined for the motor characteristics, obtained from the motor external characteristic curve, n _i The rotating speed of the motor is represented, and the rotating speeds are considered to be approximately equal under the working condition of straight line running because the front wheel and the rear wheel adopt the same hub motor; for electric machinesFor the in-wheel motor with the controller capable of feeding back the maximum torque signal, T _f,max (n _i ) And T _r,max (n _i ) Or directly obtaining the feedback signals, and when the maximum torque signals fed back by the left and right hub motors on the same shaft are inconsistent, calculating by taking a smaller value;

when the automobile is in a braking mode, obtaining an upper limit K and a lower limit K of a distribution coefficient according to a braking constraint calculation function _min,g And K _max,g The brake constraint calculation function is formed by formulas (3) and (4),

wherein, K _I Denotes a front and rear axle brake force distribution coefficient, K, obtained from a simultaneous locking condition of the front and rear wheels at the time of braking _I Lower limit K of participating brake distribution coefficient _min,g Calculation of (A), K _ECE Indicating the front and rear axle brake force distribution coefficient, L, derived from the ECE regulation _r Is the distance from the center of mass of the whole vehicle to the rear axle, h _g Is the height of mass center, L is the wheel base of the vehicle, M is the mass of the whole vehicle, G is the acceleration of gravity, G is the gravity of the whole vehicle, R _w Is the rolling radius of the wheel, T _f,min (n _i ) And T _r,min (n _i ) Algebraic minimum torque determined for the motor characteristics, in which the regenerative braking is specified as negative torque, obtained from the motor external characteristic curve, n _i The rotating speeds of the motors are represented, and the rotating speeds are considered to be approximately equal under the working condition of linear running because the front wheels and the rear wheels adopt the same hub motors;

for in-wheel motors where the motor controller can feed back a minimum torque signal, T _f,min (n _i ) And T _r,min (n _i ) Or directly obtaining the maximum torque value by the feedback signal, and taking a larger value to count when the maximum torque signals fed back by the left and right hub motors on the same shaft are inconsistentAnd (4) calculating.

4. The four-wheel independent drive electric vehicle torque real-time optimization distribution control method facing the straight line running working condition according to claim 3, characterized in that: the analytical form of the optimal solution of the optimization index function consumed in the attachment-energy joint optimization function comprises the following steps,

step 4.1: the optimization index function is shown in equation (5),

wherein λ is ₁ And λ ₂ Respectively representing the optimal weight of road adhesion utilization and the optimal weight of motor energy consumption, F _zf And F _zr Representing the loads of the front and rear axles of the vehicle, Σ P, respectively _hub Represents the sum of the power consumptions of the four in-wheel motors, T _fl 、T _fr Respectively, the left and right wheel output torques of the front axle, T _rl 、T _rr Output torque, T, of the left and right wheels of the rear axle, respectively _d For real-time torque demand, T _i For the output torque of each wheel, the index i indicates fl, fr, rl, rr, R _w Is the rolling radius of the wheel, J _EAA To optimize an index function;

step 4.2: the power loss characteristic field obtained by the motor bench test is calculated by adopting a formula (6) to obtain a motor power consumption characteristic field,

wherein T represents the motor torque measured by the test and the unit is N m; n represents the motor rotating speed measured by the test, and the unit is revolutions per minute, namely rpm; p _loss The loss power measured under each group (T, n) is obtained by subtracting the mechanical power output by the wheel end from the input direct current electric power, and the unit is kw; p _hub Represents the electric power consumption of the in-wheel motor in kw, the specified positive torque represents the drive, and the negative torque represents the torqueThe torque represents braking, the positive power represents the power consumed by the motor from the battery, the negative power represents the power fed back to the battery by the motor, and the test rotating speed data in the characteristic field is made into a motor rotating speed working condition point data table according to the test result;

and 4.3, step: according to two modes of braking and driving, the relationship of the power consumption of the motor with the change of torque under different rotating speeds is respectively fitted by adopting a cubic polynomial mode, the fitting formula is shown as (7), wherein a, b, c and d are parameters to be fitted and correspond to a rotating speed working condition point data table manufactured in the step 4.2

P _hub ＝a(n)T _i ³ +b(n)T _i ² +c(n)T _i +d(n) (7)

Step 4.4: since the torque outputs of the left and right wheels should be the same under the straight-line driving condition, the output torque of the left and right wheels of the front axle is T _fl ＝T _fr ＝T _f The output torque of the left and right wheels of the rear axle is T _rl ＝T _rr ＝T _r The specific expression is shown as (8);

wherein, K is defined as the proportion of the output torque of the front wheel accounting for 50 percent of the required torque, the proportion is the distribution coefficient of the torque of the front axle and the rear axle, T _d Torque is demanded in real time;

step 4.5: substituting the formulas (6), (7) and (8) into the formula (5), obtaining an analytic expression of a quadratic polynomial about K of the real-time optimization distribution control method, wherein coefficients are shown in formulas (10) - (12) as shown in (9);

J _EAA (K)＝τ ₁ K ² -τ ₂ K+ε (9)

wherein, T _d For real-time torque demand, λ ₁ And λ ₂ Respectively representing the optimal weight of road adhesion utilization and the optimal weight of motor energy consumption, F _zf And F _zr Respectively representing the loads of the front axle and the rear axle of the vehicle, a, b, c, d are parameters to be fitted, R _w Is the rolling radius of the wheel, J _EAA Representing an optimization index function; tau is ₁ Is J _EAA (K) Coefficient of quadratic term of function, its concrete calculation method is shown in formula (10) < tau > ₂ Is J _EAA (K) The coefficient of the first order term of the function is calculated by the formula (11) and epsilon is J _EAA (K) The coefficient of the constant term of the function is calculated by the formula (12);

step 4.6: for J in the formula (9) _EAA (K) Solving a first order partial derivative related to K and making the first order partial derivative equal to zero to obtain an extreme point of the function, and solving a second order partial derivative related to K for the function to obtain monotonicity information of the function, wherein the results of the extreme point and the second order partial derivative are shown in formulas (13) and (14);

express pair optimization index function J _EAA Solving a second order partial derivative with respect to K, K _ex Denotes J _EAA One possible extreme point of the function;

step 4.7: according to the minimum value principle, the global minimum value point of the optimization problem can be obtained in a classification discussion mode, and the specific method is as follows,

4.7.1 when τ ₁ <When 0, judge K _ex Denotes J _EAA The distance between one possible extreme point of the function and the partition coefficient boundary,

if K is _ex ≥K _max,t/g Then let K _t/g,i ＝K _min,t/g ；

If K is _ex ≤K _min,t/g Let K _t/g,i ＝K _max,t/g ；

If K is _min,t/g <K _ex <K _max,t/g Let K _t/g,i ＝argmax|κ-K _ex |(κ∈{K _min,t/g ,K _max,t/g Where κ is the mathematical notation of the collection element, meaning that it takes on only two values, respectively K _min,t/g And K _max,t/g ；

4.7.2 when τ ₁ >When 0, K is judged _ex Whether it is within the feasible domain, if K _ex >K _max,t/g Let K _t/g,i ＝K _max,t/g (ii) a If K is _ex <K _min,t/g Let K _t/g,i ＝K _min,t/g (ii) a Otherwise, let K _t/g,i ＝K _ex ；

4.7.3 when τ is greater ₁ When equal to 0, judge tau ₂ If τ is ₂ >0, order K _t/g,i ＝K _max,t/g (ii) a Otherwise, let K _t/g,i ＝K _min,t/g ；

Wherein, K _t/g,i Expressing that the optimization index function (5) in the step 4.1 obtains a value K of a global minimum value under a driving mode or a braking mode, wherein the subscript i is 1 or 2, and when the automobile is in the driving mode, K _min,t And K _max,t For the upper and lower limits of the distribution coefficient obtained from the driving constraint calculation function, when the vehicle is in the braking mode, K _min,g And K _max,g The upper and lower limits of the distribution coefficient are obtained according to a brake constraint calculation function.

5. The real-time torque optimal distribution control method for the four-wheel independent drive electric vehicle facing the straight-line running working condition according to claim 4, characterized by comprising the following steps of: through the analytical form of the optimal solution of the optimization index function, the rotating speed vector [ n ] is solved ₁ ,n ₂ ]Corresponding optimized distribution coefficient vector [ K _t/g,1 ,K _t/g,2 ]And matched vehicle speed vector [ V _x1 ,V _x2 ]The method comprises the following steps:

step 5.1: the rotation speed vector formed by the endpoints of the minimum interval is n ₁ ,n ₂ ]；

Step 5.2: judging whether the input data meets the solving requirement of the optimization problem,

if the motor is in the driving mode and the required torque exceeds the total peak torque of the motor, correcting the required torque into the sum of all the peak torques, and then solving the rotating speed n according to the optimization solving method in the step 4.7 and the fitting data in the step 4.3 ₁ ,n ₂ Corresponding optimized distribution coefficient vector [ K _t,1 ,K _t,2 ]；

If in the braking mode, when the total required torque is smaller than the total regenerative braking torque which can be provided by the motor or the feasible region obtained by the braking constraint calculation function is an empty set, K is enabled _g,i ＝K _I Where the index i represents 1 or 2; otherwise, according to the optimization solving method in the step 4.7 and the fitting data in the step 4.3, the corresponding optimized distribution coefficient vector [ K ] is solved _g,1 ,K _g,2 ]；

Step 5.3: the rotation speed vector [ n ₁ ,n ₂ ]Converted to a matched vehicle speed vector [ V ] according to equation (15) _x1 ,V _x2 ]

Wherein R is _w Is the rolling radius of the wheel, n _i Indicating the motor speed, subscript i being 1 or 2, n ₁ ,n ₂ And obtaining the real-time vehicle speed.

6. The real-time torque optimal distribution control method for the four-wheel independent drive electric vehicle facing the straight-line running working condition according to claim 5, characterized by comprising the following steps of: in the fifth step, the calculation formula of the real-time optimized distribution coefficient corresponding to the real-time vehicle speed by utilizing linear interpolation is as follows:

wherein, K _t/g,i Expressing that the optimization index function (5) in the step 4.1 obtains the value K of the global minimum value under the driving mode or the braking mode, the subscript i is 1 or 2, and V _x For real-time vehicle speed, V _xi For a matching vehicle speed vector, index i is 1 or 2.

7. The four-wheel independent drive electric vehicle torque real-time optimization distribution control method facing the straight line running working condition according to claim 6, characterized in that: in the sixth step, the step of forming the off-line manufactured energy optimal torque distribution coefficient table includes the following steps:

step 7.1: the energy-optimal torque distribution coefficient calculation method is shown in equation (16),

wherein J _E An optimization index function for torque distribution targeting energy optimization, defined as equation (16), P _d ( K,T _d ,V _x ) Calculating a Map of a function Map for the motor power, the parameters of the function being the energy-optimal torque distribution factor K to be determined and the desired torque T _d And longitudinal vehicle speed V _x (ii) a Can be obtained by calculating the motor power consumption characteristic field in the step 4.2 by using a linear interpolation method, and the calculation formula of the constraint is the formulas (2) - (4), V _x For real-time vehicle speed, T _d The real-time torque demand of the electric automobile is shown, and K is the proportion of the output torque of the front wheel accounting for 50% of the demand torque;

step 7.2: using Matlab to optimize inheritance provided by a toolkitThe algorithm optimizing function for the above problem at each vehicle speed V _x And the required torque T _d Under the condition, corresponding energy optimal distribution coefficients are respectively obtained, and a two-dimensional number table about the vehicle speed and the required torque is made.

8. The real-time torque optimal distribution control method for the four-wheel independent drive electric vehicle facing the straight-line running working condition according to claim 7, characterized in that: the preferred decision function in the sixth step is formed by equation (17),

K _opt ＝arg minJ _EAA (κ) (κ∈{K _t/g ,Ko _ff }) (17)

wherein, K _opt Is the resulting final torque-optimized distribution coefficient, calculated from equation (17), function J _EAA As can be seen from equation (5), the motor power consumption part is directly obtained by interpolation calculation of the motor power consumption characteristic field; k _off Is obtained by an energy optimal torque distribution coefficient calculation method according to the current demand torque T _d And vehicle speed V _x Looking up a table to obtain; k _t/g From equation (1).

9. The real-time torque optimal distribution control method for the four-wheel independent drive electric vehicle facing the straight-line running working condition according to claim 8, characterized by comprising the following steps of:

in the seventh step, the torque output calculation function includes the steps of:

step 9.1, determining torque request commands of hub motors of front and rear axles according to a formula (18), wherein the output torques of the left and right wheels are the same due to the fact that the hub motors belong to the straight-line driving working condition

Wherein, T _d For the real-time torque demand of the electric automobile, the torque output of the left wheel and the torque output of the right wheel under the linear running working condition are the same, so the output torque of the left wheel and the right wheel of the front axle is regulated to be T _fl ＝T _fr ＝T _f Rear axle left and right wheel output rotationMoment of T _rl ＝T _rr ＝T _r ；

Step 9.2, if the driving mode is adopted, the result is directly output;

if the motor is in the braking mode, further judging whether the torque output calculated by the formula (18) exceeds the regenerative braking torque boundary of the motor;

if the electric machine is unable to provide sufficient braking torque, the remaining torque is made up by friction braking in accordance with the currently allowable maximum regenerative torque output;

if the motor can provide the torque calculated by the formula (18), the output calculation result is directly output.

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