CN109747434B - Distributed driving electric vehicle torque vector distribution control method - Google Patents

Distributed driving electric vehicle torque vector distribution control method Download PDF

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CN109747434B
CN109747434B CN201910039678.3A CN201910039678A CN109747434B CN 109747434 B CN109747434 B CN 109747434B CN 201910039678 A CN201910039678 A CN 201910039678A CN 109747434 B CN109747434 B CN 109747434B
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CN109747434A (en
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李强
张新闻
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State Grid Shanghai Electric Power Co Ltd
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Zhejiang Lover Health Science and Technology Development Co Ltd
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Abstract

The invention discloses a distributed driving electric vehicle torque vector distribution control method, which comprises the steps of calculating an ideal motion state of a vehicle under a generalized additional yaw moment through the relationship between the stability of a vehicle running state and an expected yaw velocity in a vehicle dynamics model, and judging and analyzing the operation stability of a system through the expected yaw velocity to decide whether yaw moment control is needed or not; the longitudinal slip ratio of the tire is set to a specific value in a stable state, the driving torque is accurately distributed under the condition of meeting the road adhesion coefficient, and the driving or braking torque of the front axle and the rear axle is reasonably distributed. The invention can obviously improve the response speed of the expected yaw velocity, so that the vehicle has an ideal motion state when passing a bend, effectively inhibits the problem of difficult steering of the vehicle when the acceleration is insufficient, improves the efficiency of passing the bend, improves the running stability and smoothness of the vehicle, obviously reduces the operation burden of a driver and improves the running safety.

Description

Distributed driving electric vehicle torque vector distribution control method
Technical Field
The invention relates to the field of electric vehicle control, in particular to a distributed driving electric vehicle torque vector distribution control method.
Background
The research and development of the traditional internal combustion engine automobile driving dynamics control system have achieved fruitful results, mainly adopt the measures of applying brake torque to wheels and sacrificing dynamic property to control the motion state of the automobile, such as dynamics control systems of ABS, ESP, DYC and the like, also have the complex mechanical device which fully utilizes the road adhesion condition and applies brake torque to the output end of a differential mechanism to vector-distribute driving Torque (TVC), and can make up the control dead zone caused by threshold judgment to a certain extent. The conventional vehicle generally adopts differential braking or differential torque vector distribution to control the steering characteristic, but the differential braking is relatively rough and the working frequency is low, so that the comfort of the vehicle is greatly reduced, and the differential vector control structure is complex, so that the comfort is deteriorated due to the rough working and frequent starting of a hydraulic braking system. Electric vehicle driving methods can be generally classified into a centralized type and a distributed type. The distributed driving is to directly arrange the motor to each wheel, and has the characteristics of compact structure space, high transmission efficiency, high response speed, strong independent controllability of torque and the like. However, only the driving motor is taken as an execution system, and the output range of the driving torque is limited, so that the control requirement of the whole region cannot be met when the vehicle is steered, the vehicle is not steered stably, and the operation burden of a driver on the vehicle is increased.
Disclosure of Invention
The invention aims to provide a distributed driving electric vehicle torque vector distribution control method. The invention can effectively carry out vector distribution on the automobile torque, improve the running stability and smoothness of the automobile, obviously reduce the operation burden of a driver and improve the running safety.
The technical scheme of the invention is as follows: the distributed driving electric vehicle torque vector distribution control method comprises the following steps:
a. establishing a vehicle dynamic model for representing the relation between the stability of the vehicle running state and the expected yaw rate, and calculating the longitudinal slip rate of the tire by using a Dugoff tire model;
b. designing a yaw moment controller by utilizing a vehicle dynamic model, and inputting the expected yaw velocity into the yaw moment controller to calculate an additional yaw moment; the generalized additional yaw moment is the minimum value between the maximum value of the driving torque which can be generated by the current left and right driving wheel motors and the additional yaw moment, and is specifically Mz_sat＝min(Mz,Mmax) In the formula (1)
In the formula: mz_satAdding a yaw moment for a generalized purpose; mzAn additional yaw moment; mmaxThe maximum value of the driving torque which can be generated by the motor of the driving wheel;
c. obtaining the driving torque of a motor required by the running of the vehicle according to the opening degree of an accelerator pedal and the turning angle of a steering wheel input by a driver, and calculating the torque of left and right driving wheels according to the generalized additional yaw moment: t isL＝Mθ/2-Mz_sat·rwD/2, formula (2)
TR＝Mθ/2+Mz_sat·rwD/2, formula (3)
In the formula: t isLIs the left drive wheel torque; t isRRight drive wheel torque; mθD is the rear wheel track, r, for the driving torque required for the acceleration purposewIs the wheel rolling radius;
d. setting the longitudinal slip ratio of the tire to a specific value, and outputting the driving torque T of each driving wheel under the longitudinal slip ratio of the tire by using sliding mode controld；
e. Torque vector distribution using a drive torque vector distribution algorithm, said driveThe dynamic torque vector allocation algorithm specifically comprises the following steps: inputting generalized additional yaw moment, respectively obtaining T according to torque of left and right driving wheelsLAnd TRSimultaneously judging the torque of the driving wheels at both sides, if both are smaller than the driving torque T at the longitudinal slip ratio set as a constant valued，LAnd Td，RThe torque output value of the left driving wheel is TLThe torque output value of the left driving wheel is TR(ii) a But if one or both sides are greater than Td，LOr Td，RThen, T is comparedLAnd TRIf T isRThe torque output value of the large right driving wheel is TRAnd Td，RMinimum value therebetween, left drive wheel torque output value is TLAnd TRAnd Td，RAbsolute value of difference between differences, if TRThe torque output value of the small left driving wheel is TLAnd Td，LMinimum value therebetween, right driving wheel torque output value is TRAnd TLAnd Td，LThe absolute value of the difference between the differences.
In the above distributed driving electric vehicle torque vector distribution control method, the vehicle dynamics model established in step a includes a two-degree-of-freedom wheel steering model; the two-degree-of-freedom wheel steering model comprises two degrees of freedom of lateral motion and yaw motion; the state equations of the front wheel corner and the yaw moment of the two-degree-of-freedom wheel steering model are
Figure GDA0002457587300000031
Wherein
Figure GDA0002457587300000032
Figure GDA0002457587300000033
In the formula: i iszIs moment of inertia about the z-axis; omegaris the desired yaw rate, β centroid slip angle, delta is the equivalent front wheel angle, kfAnd krThe front and rear tire total cornering stiffness; laAnd lbIs the centroid to fore-aft wheelbaseSeparating; u is the component of the centroid velocity on the x-axis;
through Laplace transform, the expected yaw angular velocity omega is deducedrEquivalent front wheel angle delta and additional yaw moment MzCoupling; the desired yaw rate ωrResulting from the front wheel steering and the additional yaw moment, the transfer function of which is:
Figure GDA00024575873000000414
in the formula:
Figure GDA0002457587300000042
a yaw rate steady state response gain;
Figure GDA0002457587300000043
a yaw moment steady state response gain; delta is the angle of rotation of the front wheel, MzAn additional yaw moment;
wherein yaw rate steady state response gain
Figure GDA0002457587300000044
And desired yaw moment steady state response gain
Figure GDA0002457587300000045
Respectively as follows:
Figure GDA0002457587300000046
Figure GDA0002457587300000047
in the method for controlling the torque vector distribution of the distributed drive electric vehicle, the vehicle dynamics model established in the step a further comprises a seven-degree-of-freedom wheel steering model; the seven-degree-of-freedom wheel steering model comprises seven degrees of freedom of longitudinal motion, lateral motion, vertical yaw and four-wheel rotation, and the kinetic equation is as follows:
Figure GDA0002457587300000048
Figure GDA0002457587300000049
Figure GDA00024575873000000410
in the formula:
Figure GDA00024575873000000411
is the component of the centroid velocity in the y-axis; sigma FxIs the sum of the longitudinal forces experienced by the vehicle; sigma FyIs the sum of the lateral forces experienced by the vehicle; sigma MzIs the sum of the yaw moment experienced by the vehicle about the z-axis;
by analyzing the stress of the driving wheel, the motion balance equation of the driving wheel is as follows:
Figure GDA00024575873000000412
in the formula: fxIs the wheel longitudinal force;
Figure GDA00024575873000000413
is the wheel rotational angular velocity; fzSubjecting the wheel to a ground vertical load; t isdIs the driving torque; i iswIs the rotational inertia of the wheel; r iswIs the wheel rolling radius; f. ofwIs the rolling resistance coefficient.
In the foregoing method for controlling torque vector distribution of a distributed drive electric vehicle, the method for calculating the longitudinal slip ratio of the tire by the Dugoff tire model in step a includes: total slip ratio lambdaresAnd the resultant force F of the longitudinal force and the lateral force of the wheelresRespectively as follows:
Figure GDA0002457587300000051
Figure GDA0002457587300000052
wherein α is a slip angle and lambdaxIs the longitudinal slip ratio of the tire, FzIn order to apply a vertical load to the tire,
Figure GDA0002457587300000053
is the road adhesion coefficient, wherein the resultant vector force of the longitudinal force and the lateral force to which the tire is subjected cannot exceed the product of the road adhesion coefficient and the vertical load of the tire;
the longitudinal force of the wheel is
Figure GDA0002457587300000054
In the formula: bxAnd cxIs a longitudinal force parameter of the wheel;
the longitudinal slip ratio lambda of the wheel is reversely solved by the formula (14) and the formula (13) in a combined mode (12)xand slip angle α:
Figure GDA0002457587300000055
Figure GDA0002457587300000056
in the aforementioned torque vector distribution control method for a distributed drive electric vehicle, the yaw moment controller includes a feed-forward controller and a feedback controller:
the feedforward controller is used for controlling the running state of the automobile in real time, specifically the gain of the actual yaw rate to the front wheel turning angle, and the gain process is gained by the steady-state response of the yaw rate
Figure GDA0002457587300000061
Sum yaw moment steady state response gain
Figure GDA0002457587300000062
And transient process response gain, the transfer function of the transient process response gain being:
Figure GDA0002457587300000063
wherein:
Figure GDA0002457587300000064
in the formula: k is a stability factor;
Figure GDA0002457587300000065
is a time constant;
Figure GDA0002457587300000066
responding to the gain for the transient process;
the combined equation (5) and equation (17) are used to derive the transfer function of the yaw moment of the feedforward controller as
Figure GDA0002457587300000067
The feedback controller is used for correcting system characteristic errors and other external interference factors to form a closed-loop system; the feedback controller adopts a sliding mode variable structure controller, an integral operator is added in a sliding mode surface, and the yaw velocity tracking error is as follows:
e＝ωr-ωr_dequation (19)
In the formula: omegarTo desired yaw rate, ωr_dThe actual yaw rate;
the sliding mode surface linear switching function is as follows:
Figure GDA0002457587300000068
in the formula: c. C0And c1The undetermined coefficients ensure that all characteristic root values of a characteristic equation formed by the undetermined coefficients are on the left side of the complex plane, namely in a stable state;
adopting an exponential approach law:
Figure GDA0002457587300000069
from formula (4):
Figure GDA0002457587300000071
in the formula, beta is a system characteristic error, and delta is other external interference factors;
the yaw moment controller designed in this way compensates for this, with the additional yaw moment MzComprises the following steps:
Figure GDA0002457587300000072
in the distributed driving electric vehicle torque vector distribution control method, the tire longitudinal slip rate is 10 to 30%, and the tire longitudinal slip rate function and the derivative thereof are respectively as follows:
Figure GDA0002457587300000073
Figure GDA0002457587300000074
in the driving process, lambda is 0 when pure rolling is carried out; λ 1 at pure slip;
actual slip ratio lambda between tire and road surfacedThe tracking error of the tire slip ratio λ with a specific value is e ═ λ - λdOf the formula (25-1)
Defining the sliding mode surface function and the derivative thereof as:
s ═ e + γ ^ edt, formula (25-2)
Figure GDA0002457587300000075
wherein gamma is a relative weight coefficient of the error and the integral accumulation of the error, and α and β are undetermined coefficients;
the drive torque T was calculated by substituting the expressions (25-1), (25-2) and (26) for the expression (11)dComprises the following steps:
Figure GDA0002457587300000076
in the distributed driving electric vehicle torque vector distribution control method, the sliding-mode surface function is a saturation function module, and the saturation function module is:
Figure GDA0002457587300000082
in the formula: zeta is the boundary layer thickness of the sliding mode surface;
wherein the error range [ - ζ, ζ ] is satisfied within the boundary layer, i.e., the closed-loop system is considered to be in a steady state.
In the above method for controlling the torque vector distribution of the distributed drive electric vehicle, the analytic strategy function of the motor drive torque required for the vehicle to travel in step c is represented as:
Tm＝f(θaccn, η), formula (29)
In the formula: t ismis the driving torque of the motor, η is the rotation speed of the motor, eta is the efficiency of the motor, thetaaccIs the accelerator opening.
The distributed driving electric vehicle torque vector distribution control method is characterized in that: the upper limit of the desired yaw rate is:
Figure GDA0002457587300000083
in the formula: mu is the coefficient of road surface adhesion, g is the acceleration of gravity, v is the speed of mass center, axIs the component of the acceleration of the vehicle on the x-axis, ayIs the component of the vehicle acceleration on the y-axis.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the method, the ideal motion state which the vehicle should have under the generalized additional yaw moment is calculated through the relationship between the stability of the vehicle running state and the expected yaw velocity under a vehicle dynamic model, and whether yaw moment control is needed or not is determined through the expected yaw velocity to judge and analyze the operation stability of a system; the tire longitudinal slip rate is set to be a specific value in a stable state, the driving torque is accurately distributed under the condition of meeting the road adhesion coefficient, the expected yaw velocity response speed is obviously improved by reasonably distributing the driving or braking torque of the front and rear shafts, so that the vehicle has an ideal motion state when passing a bend, the problem of difficult steering of the vehicle when the acceleration is insufficient is effectively inhibited, the passing efficiency is improved, the running stability and smoothness of the vehicle are improved, the operation burden of a driver is obviously reduced, and the driving safety is improved.
2. The method comprises the steps of analyzing a generation mode of an expected yaw rate by establishing a two-degree-of-freedom wheel steering model, deducing and calculating a steady-state response gain of the yaw rate and a steady-state response gain of an expected yaw moment; the running state of the distributed driving electric automobile is more accurately reflected by establishing a seven-degree-of-freedom wheel steering model, the dynamic equation of the whole automobile is simplified, and the stability of the automobile and the control method are conveniently analyzed in real time.
3. According to the invention, the longitudinal slip rate of the tire is calculated by the Dugoff tire model which is convenient for pushing the inverse model, the parameter number of experimental identification is reduced, the non-linear degree and the calculated amount are reduced, so that the distributed electric automobile can apply different driving forces to adjust the yaw moment under the premise of ensuring that the total power is not changed, particularly under the condition of tire adhesion limit, the slip rate of each driving wheel is controlled within a stable range, and the running stability of the vehicle is improved.
4. The yaw moment controller is designed into a feedforward controller and a feedback controller, the feedforward controller is used for controlling the running state of the automobile in real time, and the feedback controller is used for correcting system characteristic errors and other external interference factors to form a closed-loop system; on the premise of ensuring the requirement of longitudinal dynamic property, the vehicle can meet the requirement of maximum lateral acceleration, and then the yaw moment controller can compensate the vehicle, and remove system characteristic errors and other external interference factors, so that the stability and the anti-interference capability of the system in the yaw moment controller can be improved, and the running stability of the vehicle can be improved.
5. The sliding mode surface function is defined as a saturation function module, so that the phenomenon of high-speed buffeting of the vehicle when the characteristic error of the system is zero is avoided; the invention also designs a yaw moment controller to better accord with the actual driving condition of the vehicle by optimizing the upper limit of the expected yaw velocity, and further optimizes the algorithm of the driving torque distribution.
Drawings
FIG. 1 is a schematic illustration of the drive torque vector distribution algorithm of the present invention;
FIG. 2 is a schematic view of a two degree-of-freedom wheel steering model of the present invention;
FIG. 3 is a schematic diagram of a seven degree-of-freedom wheel steering model of the present invention;
FIG. 4 is a force analysis diagram of the drive wheel of the present invention;
FIG. 5 is a schematic diagram of the yaw moment controller of the present invention;
FIG. 6 is a diagram of an analysis of the dynamics model and controller simulation behavior of the present invention;
FIG. 7 is a three-dimensional graph of a pedal input resolution strategy function of the present invention;
FIG. 8 is a plot of desired yaw rate versus vehicle state characteristics in accordance with the present invention;
FIG. 9 is a plot of desired yaw rate versus vehicle steering characteristics for a conventional vehicle;
fig. 10 is a graph of a desired yaw rate versus vehicle steering characteristics of the present invention.
Detailed Description
The invention is further illustrated by the following figures and examples, which are not to be construed as limiting the invention.
Example (b): the distributed driving electric vehicle torque vector distribution control method comprises the following steps:
a. establishing a vehicle dynamic model for representing the relation between the stability of the vehicle running state and the expected yaw rate, and calculating the longitudinal slip rate of the tire by using a Dugoff tire model;
b. the yaw moment controller is designed by utilizing a vehicle dynamic modelInputting the expected yaw velocity into a yaw moment controller to calculate an additional yaw moment; the generalized additional yaw moment is the minimum value between the maximum value of the driving torque which can be generated by the current left and right driving wheel motors and the additional yaw moment, and is specifically Mz_sat＝min(Mz,Mmax) In the formula (1)
In the formula: mz_satAdding a yaw moment for a generalized purpose; mzAn additional yaw moment; mmaxThe maximum value of the driving torque which can be generated by the motor of the driving wheel;
c. obtaining a motor driving torque required by the running of the vehicle according to an accelerator opening degree and a steering wheel angle input by a driver, calculating an ideal motion state which the vehicle should have by using a reference vehicle model according to a current vehicle speed and road adhesion coefficient information, serving as a control target of the system, comprising reference to a desired yaw rate, judging and analyzing the steering stability of the system to decide whether yaw moment control is required or not so that the vehicle has the ideal motion state, and calculating an accurate distribution of wheel driving torques of the vehicle by applying an additional yaw moment, wherein the calculated torques of left and right driving wheels are as follows: t isL＝Mθ/2-Mz_sat·rwD/2, formula (2)
TR＝Mθ/2+Mz_sat·rwD/2, formula (3)
In the formula: t isLIs the left drive wheel torque; t isRRight drive wheel torque; mθD is the rear wheel track, r, for the driving torque required for the acceleration purposewIs the wheel rolling radius;
d. setting the longitudinal slip ratio of the tire to a specific value, and outputting the driving torque T of each driving wheel under the longitudinal slip ratio of the tire by using sliding mode controld；
e. The torque vector is distributed by using a driving torque vector distribution algorithm, as shown in fig. 1, the driving torque vector distribution algorithm specifically comprises: inputting generalized additional yaw moment, respectively obtaining T according to torque of left and right driving wheelsLAnd TRSimultaneously judging the torque of the driving wheels at both sides, and if both are smaller than a set valueDriving torque T at longitudinal slip ratio ofd，LAnd Td，RThe torque output value of the left driving wheel is TLThe torque output value of the left driving wheel is TR(ii) a But if one or both sides are greater than Td，LOr Td，RThen, T is comparedLAnd TRIf T isRThe torque output value of the large right driving wheel is TRAnd Td，RMinimum value therebetween, left drive wheel torque output value is TLAnd TRAnd Td，RAbsolute value of difference between differences, if TRThe torque output value of the small left driving wheel is TLAnd Td，LMinimum value therebetween, right driving wheel torque output value is TRAnd TLAnd Td，LThe absolute value of the difference between the differences. The distributed driving electric vehicle torque vector control process is that a mapping from a generalized yaw moment to each driving wheel torque is established, the driving wheel torques are balanced and reasonably distributed according to the maximum driving force and the optimal longitudinal slip ratio which can be provided by the tire adhesion circle, and meanwhile, the driving torque value and the load change, the tire characteristics, the road adhesion coefficient, the motor driving power limitation and other factors need to be considered for real-time adjustment, so that the driving torque distributed to each wheel is accurately coordinated and controlled.
The vehicle dynamic model established in the step a comprises a two-degree-of-freedom wheel steering model; as shown in fig. 2, the two-degree-of-freedom wheel steering model includes two degrees of freedom of lateral motion and yaw motion; the state equations of the front wheel corner and the yaw moment of the two-degree-of-freedom wheel steering model are
Figure GDA0002457587300000121
Wherein
Figure GDA0002457587300000122
Figure GDA0002457587300000123
In the formula: i iszIs moment of inertia about the z-axis; omegarto a desired yaw rate, betaIs the centroid slip angle; delta is the equivalent front wheel corner; k is a radical offAnd krThe front and rear tire total cornering stiffness; laAnd lbIs the distance from the center of mass to the front and rear axes; u is the component of the centroid velocity on the x-axis;
through Laplace transform, the expected yaw angular velocity omega is deducedrEquivalent front wheel angle delta and additional yaw moment MzCoupling; the desired yaw rate ωrResulting from the front wheel steering and the additional yaw moment, the transfer function of which is:
Figure GDA0002457587300000124
in the formula:
Figure GDA0002457587300000125
a yaw rate steady state response gain;
Figure GDA0002457587300000126
a yaw moment steady state response gain; delta is the angle of rotation of the front wheel, MzAn additional yaw moment;
wherein yaw rate steady state response gain
Figure GDA0002457587300000127
And desired yaw moment steady state response gain
Figure GDA0002457587300000128
Respectively as follows:
Figure GDA0002457587300000129
Figure GDA0002457587300000131
the vehicle dynamics model established in the step a further comprises a seven-degree-of-freedom wheel steering model; as shown in fig. 3, the seven-degree-of-freedom wheel steering model comprises seven degrees of freedom of longitudinal motion, lateral motion and vertical yaw and four-wheel rotation, and the kinetic equation is as follows:
Figure GDA0002457587300000132
Figure GDA0002457587300000133
Figure GDA0002457587300000134
in the formula:
Figure GDA0002457587300000135
is the component of the centroid velocity in the y-axis; sigma FxIs the sum of the longitudinal forces experienced by the vehicle; sigma FyIs the sum of the lateral forces experienced by the vehicle; sigma MzIs the sum of the yaw moment experienced by the vehicle about the z-axis;
as shown in fig. 4, the driving wheel force analysis shows that the motion balance equation of the driving wheel is:
Figure GDA0002457587300000136
in the figure: fxIs the wheel longitudinal force;
Figure GDA0002457587300000137
is the wheel rotational angular velocity; fzSubjecting the wheel to a ground vertical load; e.g. of the typezIs a drag distance, TdIs the driving torque; t isfIs friction rolling resistance moment, IwIs the rotational inertia of the wheel; r iswIs the wheel rolling radius; f. ofwIs the rolling resistance coefficient.
The method for calculating the longitudinal slip rate of the tire by the Dugoff tire model in the step a comprises the following steps: total slip ratio lambdaresAnd the resultant force F of the longitudinal force and the lateral force of the wheelresRespectively as follows:
Figure GDA0002457587300000138
Figure GDA0002457587300000139
wherein α is a slip angle and lambdaxIs the longitudinal slip ratio of the tire, FzIn order to apply a vertical load to the tire,
Figure GDA00024575873000001310
is the road adhesion coefficient, wherein the resultant vector force of the longitudinal force and the lateral force to which the tire is subjected cannot exceed the product of the road adhesion coefficient and the vertical load of the tire;
the longitudinal force of the wheel is
Figure GDA0002457587300000141
In the formula: bxAnd cxIs a longitudinal force parameter of the wheel;
the longitudinal slip ratio lambda of the wheel is reversely solved by the formula (14) and the formula (13) in a combined mode (12)xand slip angle α:
Figure GDA0002457587300000142
Figure GDA0002457587300000143
the yaw moment controller includes a feedforward controller and a feedback controller:
the feedforward controller is used for controlling the running state of the automobile in real time, the expected yaw rate is in positive correlation with the corner of the front wheel under a certain speed, the gain of the expected yaw rate to the corner of the front wheel is decreased gradually along with the increase of the speed of the automobile, specifically the gain of the actual yaw rate to the corner of the front wheel, and the gain process is the steady-state response gain of the yaw rate
Figure GDA0002457587300000144
Sum yaw moment steady state response gain
Figure GDA0002457587300000145
And transient process response gain, wherein the transient process response gain can be regarded as a first-order link, and the transfer function of the transient process response gain is as follows:
Figure GDA0002457587300000146
wherein:
Figure GDA0002457587300000147
in the formula: k is a stability factor;
Figure GDA0002457587300000148
is a time constant;
Figure GDA0002457587300000149
responding to the gain for the transient process;
the combined equation (5) and equation (17) are used to derive the transfer function of the yaw moment of the feedforward controller as
Figure GDA0002457587300000151
The feedback controller is used for correcting system characteristic errors and other external interference factors to form a closed-loop system; the feedforward controller calculates the required control input quantity in advance under the current vehicle speed condition, corrects the system, has fast response speed because the feedback is realized without a closed-loop system, but can not ensure that the system can reach the expected ideal operation stable state only by adopting the feedforward controller because of the error of the system characteristic and other external interference factors, and adopts the feedback controller which utilizes the deviation of the actual state and the stable state of the vehicle as the feedback input quantity to form the closed-loop system to control and output the yaw torque in order to ensure the quick response of the additional yaw moment and improve the stability and the anti-interference capability of the system. The feedback controller adopts a sliding mode variable structure controller, an integral operator is added in a sliding mode surface, and the yaw velocity tracking error is as follows:
e＝ωr-ωr_dequation (19)
In the formula: omegarTo desired yaw rate, ωr_dThe actual yaw rate;
the sliding mode surface linear switching function is as follows:
Figure GDA0002457587300000152
in the formula: c. C0And c1The undetermined coefficients ensure that all characteristic root values of a characteristic equation formed by the undetermined coefficients are on the left side of the complex plane, namely in a stable state;
adopting an exponential approach law:
Figure GDA0002457587300000153
from formula (4):
Figure GDA0002457587300000161
in the formula, beta is a system characteristic error, and delta is other external interference factors;
the yaw moment controller designed in this way compensates for this, with the additional yaw moment MzComprises the following steps:
Figure GDA0002457587300000162
the feedforward controller is combined with the feedback controller to form an additional yaw moment sum, and the additional yaw moment sum is used as a yaw moment meeting the vehicle operation stability performance requirement to improve the operation stability of the vehicle. In order to verify the accuracy and effectiveness of the additional yaw moment control method, a dynamic model and a controller are established, simulation analysis is carried out in a MATLAB/Simulink environment, and a control block diagram is shown in FIG. 5.
Road surface with high adhesion coefficient under simulation working condition
Figure GDA0002457587300000163
Snake test ofThe vehicle operation stability is represented, the vehicle speed is 80km/h, the corner of a steering wheel is input by Sinewave (the amplitude is 30 degrees and the frequency is pi/2), motors on two sides of a rear wheel are driven by equal torque, the maximum limit is 800Nm, and the simulation result is shown in figure 6. As can be seen from fig. 6, as the reference yaw rate, the two-degree-of-freedom automobile model is regarded as a first-order link without considering the input of the additional yaw torque, and it is also shown that equation (17) can be simplified to a first-order transfer function related to the vehicle speed, and is maintained at 0.409rad/s after the steady state; under the control of not applying a yaw moment, the yaw velocity of the seven-degree-of-freedom automobile obviously has certain deviation with a reference yaw velocity in the initial stage (within 15 seconds), but is basically kept constant after passing through a steady state, and the difference is within 5 percent, so that the model can be completely applied to a torque vector control algorithm; the overshoot of the yaw rate of the vehicle under the additional yaw moment control is reduced to a certain extent compared with that without the control, and the transition time is reduced, so that the steady-state value can be reached more quickly, and meanwhile, the reference yaw rate can be tracked better.
The tire adhesion circle, also called friction circle, the coupling relationship between longitudinal force and lateral force, and the influence of the driving steering process on the tire cornering performance and the steering performance. The longitudinal slip ratio of the tire has a great influence on the tire lateral deflection rigidity, namely, the longitudinal slip ratio is increased, the lateral deflection force generated by the tire is reduced, and the longitudinal slip ratio is different due to different driving forces of the left and right rear wheels, so that the steering characteristic of the vehicle is finally influenced. Under the high adhesion coefficient, the vehicle sliding component is smaller, the steering inner side load is transferred to the outer side, the lateral deflection rigidity of an inner side wheel is reduced, the lateral deflection rigidity of an outer wheel is increased, the vehicle has the tendency of multi-degree steering, and if the wheelbase is short, the vehicle with a high center of mass is transferred more, so that the influence is more obvious. On the premise of ensuring that the total power is not changed, the distributed driving wheels exert different driving forces to adjust the yaw moment particularly under the tire adhesion limit, so that the slip rate of each wheel is controlled in a stable range, and the vehicle running stability is improved. The longitudinal sliding rate of the tire is not 10% -30%, and the tire can provide maximum longitudinal driving force.
The tire longitudinal slip rate function and the derivative thereof are respectively as follows:
Figure GDA0002457587300000171
Figure GDA0002457587300000172
in the driving process, lambda is 0 when pure rolling is carried out; λ 1 at pure slip;
actual slip ratio lambda between tire and road surfacedThe tracking error of the tire slip ratio λ with a specific value is e ═ λ - λdOf the formula (25-1)
Defining the sliding mode surface function and the derivative thereof as:
s ═ e + γ ^ edt, formula (25-2)
Figure GDA0002457587300000173
wherein gamma is a relative weight coefficient of the error and the integral accumulation of the error, and α and β are undetermined coefficients;
the drive torque T was calculated by substituting the expressions (25-1), (25-2) and (26) for the expression (11)dComprises the following steps:
Figure GDA0002457587300000181
the sliding mode surface function is a saturation function module, and the saturation function module is as follows:
Figure GDA0002457587300000182
in the formula: zeta is the boundary layer thickness of the sliding mode surface;
wherein the error range [ - ζ, ζ ] is satisfied within the boundary layer, i.e., the closed-loop system is considered to be in a steady state.
The analytic strategy function of the motor driving torque required by the vehicle running in the step c is represented as follows:
Tm＝f(θaccn, η), formula (29)
In the formula: t ismAs an electric motordriving torque, n is motor speed, η motor efficiency, thetaaccThe range change is [0,100 ] for the accelerator pedal opening]And the total torque requirement is met.
The output motor torque is determined by a pedal input analytic strategy function, the three-dimensional curve of which is shown in fig. 7.
The upper limit of the desired yaw rate is:
Figure GDA0002457587300000183
in the formula: mu is the coefficient of road surface adhesion, g is the acceleration of gravity, v is the speed of mass center, axIs the component of the acceleration of the vehicle on the x-axis, ayIs the component of the vehicle acceleration on the y-axis.
After the distributed driving electric vehicle torque vector distribution control method is set, a sample vehicle is used for carrying out simulation test, the sample vehicle is a rear-driving pure electric vehicle, the whole vehicle has the weight of 750kg, the wheelbase is 1.9m, the rear wheelbase is 1.2m, the nominal voltage of a loaded lithium battery monomer is 3.2V, the capacity is 50Ah, 24 series connection is adopted to form a power unit to respectively provide energy for a driving motor, the driving motor adopts a permanent magnet synchronous motor ME0709, the rated power is 7028W, the rated voltage is 72V, the rated rotating speed is 3300 +/-250 r/min, the motor and a wheel hub are connected by a planetary reducer, and the speed ratio is 7. The rated torque of the motor is 38Nm, and the maximum torque T of the driving wheel can be reachedmaxIs 817 Nm.
Fig. 8 shows the relationship between the desired yaw rate and the vehicle state characteristics, and shows the characteristic state of the vehicle in which the desired yaw rate and the front wheel torque are positively correlated at a certain vehicle speed. The state characteristics of automobile tires are expressed through the driving force of the tires, the traditional vehicle adopts differential braking or differential braking to distribute torque vectors to control the steering characteristics of the vehicle, and the simulation curve is shown in FIG. 9; the simulation curve of the driving wheels of the vehicle after torque vector distribution by the driving torque vector distribution algorithm is shown in fig. 10. Comparing fig. 9 and fig. 10, it is obvious that the differential braking is relatively rough and the working frequency is low, the driving force of the wheels is complex and tortuous because of the frequent start and change of the hydraulic braking system, and the comfort of the vehicle is greatly reduced.
In conclusion, the ideal motion state which the vehicle should have under the generalized additional yaw moment is calculated through the relationship between the stability of the vehicle running state and the expected yaw rate under the vehicle dynamic model, and whether the yaw moment control is needed or not is determined through the operation stability of the expected yaw rate judgment and analysis system; the tire longitudinal slip rate is set to be a specific value in a stable state, the driving torque is accurately distributed under the condition of meeting the road adhesion coefficient, the expected yaw velocity response speed is obviously improved by reasonably distributing the driving or braking torque of the front and rear shafts, so that the vehicle has an ideal motion state when passing a bend, the problem of difficult steering of the vehicle when the acceleration is insufficient is effectively inhibited, the passing efficiency is improved, the running stability and smoothness of the vehicle are improved, the operation burden of a driver is obviously reduced, and the driving safety is improved.

Claims (9)

1. The distributed driving electric vehicle torque vector distribution control method is characterized in that: the method comprises the following steps:
a. establishing a vehicle dynamic model for representing the relation between the stability of the vehicle running state and the expected yaw rate, and calculating the longitudinal slip rate of the tire by using a Dugoff tire model;
b. designing a yaw moment controller by utilizing a vehicle dynamic model, and inputting the expected yaw velocity into the yaw moment controller to calculate an additional yaw moment; the generalized additional yaw moment is the minimum value between the maximum value of the driving torque which can be generated by the current left and right driving wheel motors and the additional yaw moment, and is specifically Mz_sat＝min(Mz,Mmax) In the formula (1)
In the formula: mz_satAdding a yaw moment for a generalized purpose; mzAn additional yaw moment; mmaxFor driving the wheel motor to generate drive torqueMaximum value of (d);
c. obtaining the driving torque of a motor required by the running of the vehicle according to the opening degree of an accelerator pedal and the turning angle of a steering wheel input by a driver, and calculating the torque of left and right driving wheels according to the generalized additional yaw moment: t isL＝Mθ/2-Mz_sat·rwD/2, formula (2)
TR＝Mθ/2+Mz_sat·rwD/2, formula (3)
In the formula: t isLIs the left drive wheel torque; t isRRight drive wheel torque; mθD is the rear wheel track, r, for the driving torque required for the acceleration purposewIs the wheel rolling radius;
d. setting the longitudinal slip ratio of the tire to a specific value, and outputting the driving torque T of each driving wheel under the longitudinal slip ratio of the tire by using sliding mode controld；
e. Carrying out torque vector distribution by using a driving torque vector distribution algorithm, wherein the driving torque vector distribution algorithm specifically comprises the following steps: inputting generalized additional yaw moment, respectively obtaining T according to torque of left and right driving wheelsLAnd TRSimultaneously judging the torque of the driving wheels at both sides, if both are smaller than the driving torque T at the longitudinal slip ratio set as a constant valued，LAnd Td，RThe torque output value of the left driving wheel is TLThe torque output value of the left driving wheel is TR(ii) a But if one or both sides are greater than Td，LOr Td，RThen, T is comparedLAnd TRIf T isRThe torque output value of the large right driving wheel is TRAnd Td，RMinimum value therebetween, left drive wheel torque output value is TLAnd TRAnd Td，RAbsolute value of difference between differences, if TRThe torque output value of the small left driving wheel is TLAnd Td，LMinimum value therebetween, right driving wheel torque output value is TRAnd TLAnd Td，LThe absolute value of the difference between the differences.
2. The distributed drive electric vehicle of claim 1A torque vector distribution control method characterized by: the vehicle dynamic model established in the step a comprises a two-degree-of-freedom wheel steering model; the two-degree-of-freedom wheel steering model comprises two degrees of freedom of lateral motion and yaw motion; the state equations of the front wheel corner and the yaw moment of the two-degree-of-freedom wheel steering model are
Figure FDA0002457587290000021
Wherein
Figure FDA0002457587290000022
Figure FDA0002457587290000023
b12＝0，
Figure FDA0002457587290000024
In the formula: i iszIs moment of inertia about the z-axis; omegaris the desired yaw rate, β centroid slip angle, delta is the equivalent front wheel angle, kfAnd krThe front and rear tire total cornering stiffness; laAnd lbIs the distance from the center of mass to the front and rear axes; u is the component of the centroid velocity on the x-axis;
through Laplace transform, the expected yaw angular velocity omega is deducedrEquivalent front wheel angle delta and additional yaw moment MzCoupling; the desired yaw rate ωrResulting from the front wheel steering and the additional yaw moment, the transfer function of which is:
Figure FDA0002457587290000031
in the formula:
Figure FDA0002457587290000032
a yaw rate steady state response gain;
Figure FDA0002457587290000033
a yaw moment steady state response gain; delta is the angle of rotation of the front wheel, MzAn additional yaw moment;
wherein yaw rate steady state response gain
Figure FDA0002457587290000034
And desired yaw moment steady state response gain
Figure FDA0002457587290000035
Respectively as follows:
Figure FDA0002457587290000036
Figure FDA0002457587290000037
3. the distributed drive electric vehicle torque vector distribution control method according to claim 2, characterized in that: the vehicle dynamics model established in the step a further comprises a seven-degree-of-freedom wheel steering model; the seven-degree-of-freedom wheel steering model comprises seven degrees of freedom of longitudinal motion, lateral motion, vertical yaw and four-wheel rotation, and the kinetic equation is as follows:
Figure FDA0002457587290000038
Figure FDA0002457587290000039
Figure FDA00024575872900000310
in the formula:
Figure FDA00024575872900000311
is the component of the centroid velocity in the y-axis; sigma FxIs the sum of the longitudinal forces experienced by the vehicle; sigma FyIs the sum of the lateral forces experienced by the vehicle; Sigma-MzIs the sum of the yaw moment experienced by the vehicle about the z-axis;
by analyzing the stress of the driving wheel, the motion balance equation of the driving wheel is as follows:
Figure FDA00024575872900000312
in the formula: fxIs the wheel longitudinal force;
Figure FDA0002457587290000041
is the wheel rotational angular velocity; fzSubjecting the wheel to a ground vertical load; t isdIs the driving torque; i iswIs the rotational inertia of the wheel; r iswIs the wheel rolling radius; f. ofwIs the rolling resistance coefficient.
4. The distributed drive electric vehicle torque vector distribution control method according to claim 3, characterized in that: the method for calculating the longitudinal slip rate of the tire by the Dugoff tire model in the step a comprises the following steps: total slip ratio lambdaresAnd the resultant force F of the longitudinal force and the lateral force of the wheelresRespectively as follows:
Figure FDA0002457587290000042
Figure FDA0002457587290000043
wherein α is a slip angle and lambdaxIs the longitudinal slip ratio of the tire, FzIn order to apply a vertical load to the tire,
Figure FDA0002457587290000044
the road adhesion coefficient being the coefficient at which the resultant of the longitudinal and lateral forces experienced by the tyre cannot exceed the roadThe product of the surface adhesion coefficient and the tire vertical load;
the longitudinal force of the wheel is
Figure FDA0002457587290000045
In the formula: bxAnd cxIs a longitudinal force parameter of the wheel;
the longitudinal slip ratio lambda of the wheel is reversely solved by the formula (14) and the formula (13) in a combined mode (12)xand slip angle α:
Figure FDA0002457587290000046
Figure FDA0002457587290000047
5. the distributed drive electric vehicle torque vector distribution control method according to claim 3, characterized in that: the yaw moment controller includes a feedforward controller and a feedback controller:
the feedforward controller is used for controlling the running state of the automobile in real time, specifically the gain of the actual yaw rate to the front wheel turning angle, and the gain process is gained by the steady-state response of the yaw rate
Figure FDA0002457587290000051
Sum yaw moment steady state response gain
Figure FDA0002457587290000052
And transient process response gain, the transfer function of the transient process response gain being:
Figure FDA0002457587290000053
wherein:
Figure FDA0002457587290000054
in the formula: k is a stability factor;
Figure FDA0002457587290000055
is a time constant;
Figure FDA0002457587290000056
responding to the gain for the transient process;
the combined equation (5) and equation (17) are used to derive the transfer function of the yaw moment of the feedforward controller as
Figure FDA0002457587290000057
The feedback controller is used for correcting system characteristic errors and other external interference factors to form a closed-loop system; the feedback controller adopts a sliding mode variable structure controller, an integral operator is added in a sliding mode surface, and the yaw velocity tracking error is as follows:
e＝ωr-ωr_dequation (19)
In the formula: omegarTo desired yaw rate, ωr_dThe actual yaw rate;
the sliding mode surface linear switching function is as follows:
Figure FDA0002457587290000058
in the formula: c. C0And c1The undetermined coefficients ensure that all characteristic root values of a characteristic equation formed by the undetermined coefficients are on the left side of the complex plane, namely in a stable state;
adopting an exponential approach law:
Figure FDA0002457587290000061
from formula (4):
Figure FDA0002457587290000062
in the formula, beta is a system characteristic error, and delta is other external interference factors;
the yaw moment controller designed in this way compensates for this, with the additional yaw moment MzComprises the following steps:
Figure FDA0002457587290000063
6. the distributed drive electric vehicle torque vector distribution control method according to claim 4, characterized in that: the longitudinal slip rate of the tire is 10-30%, and the longitudinal slip rate function and the derivative thereof are respectively as follows:
Figure FDA0002457587290000064
Figure FDA0002457587290000065
in the driving process, lambda is 0 when pure rolling is carried out; λ 1 at pure slip;
actual slip ratio lambda between tire and road surfacedThe tracking error of the tire slip ratio λ with a specific value is e ═ λ - λdOf the formula (25-1)
Defining the sliding mode surface function and the derivative thereof as:
s ═ e + γ ^ edt, formula (25-2)
Figure FDA0002457587290000066
wherein gamma is a relative weight coefficient of the error and the integral accumulation of the error, and α and β are undetermined coefficients;
the drive torque T was calculated by substituting the expressions (25-1), (25-2) and (26) for the expression (11)dComprises the following steps:
7. the distributed drive electric vehicle torque vector distribution control method according to claim 6, characterized in that: the sliding mode surface function is a saturation function module, and the saturation function module is as follows:
Figure FDA0002457587290000072
in the formula: zeta is the boundary layer thickness of the sliding mode surface;
wherein the error range [ - ζ, ζ ] is satisfied within the boundary layer, i.e., the closed-loop system is considered to be in a steady state.
8. The distributed drive electric vehicle torque vector distribution control method according to claim 1, characterized in that: the analytic strategy function of the motor driving torque required by the vehicle running in the step c is represented as follows:
Tm＝f(θaccn, η), formula (29)
In the formula: t ismis the driving torque of the motor, η is the rotation speed of the motor, eta is the efficiency of the motor, thetaaccIs the accelerator opening.
9. The distributed drive electric vehicle torque vector distribution control method according to claim 1, characterized in that: the upper limit of the desired yaw rate is:
Figure FDA0002457587290000073
in the formula: mu is the coefficient of road surface adhesion, g is the acceleration of gravity, v is the speed of mass center, axIs the component of the acceleration of the vehicle on the x-axis, ayIs the component of the vehicle acceleration on the y-axis.
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