CN110126640A - A kind of four-wheeled electric vehicle variable element antiskid control system and method based on pavement self-adaptive - Google Patents
A kind of four-wheeled electric vehicle variable element antiskid control system and method based on pavement self-adaptive Download PDFInfo
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- B60L2240/00—Control parameters of input or output; Target parameters
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- B60L2240/00—Control parameters of input or output; Target parameters
- B60L2240/10—Vehicle control parameters
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- B60L2240/00—Control parameters of input or output; Target parameters
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- B60L2240/00—Control parameters of input or output; Target parameters
- B60L2240/40—Drive Train control parameters
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Abstract
The present invention relates to a kind of four-wheeled electric vehicle variable element antiskid control system and method based on pavement self-adaptive, the system includes electric machine controller, onboard sensor unit, tire-road adheres to estimation unit, variable element Anti-slip regulation control unit, tire-road attachment estimation unit is used to obtain the peak value of road adhesion coefficient of each wheel, the measured data of peak value of road adhesion coefficient and onboard sensor unit that variable element Anti-slip regulation control unit adheres to the wheel that estimation unit obtains according to tire-road carries out anti-sliding control and exports control moment, electric machine controller controls 4 driving motor movements.Anti-slip regulation control of the present invention can control accuracy height, vehicle safety and drive efficiency can be improved in good antiskid effect in real time according to the estimated result automatic adjusument of current road.
Description
Technical Field
The invention relates to a distributed type drive electric vehicle antiskid control system and a method, in particular to a road self-adaptive four-wheel drive electric vehicle variable parameter antiskid control system and a method.
Background
The distributed driving electric automobile is driven by a wheel-side motor or a wheel-hub motor, and components such as a clutch, a transmission, a main speed reducer, a differential mechanism and the like of the traditional internal combustion engine automobile are not needed, so that the structure of the whole automobile is simplified, and the transmission efficiency is improved. Meanwhile, the current rotating speed and torque output by the motor can be accurately acquired through the motor controller, and the response time of the motor is generally in millisecond level. The excessive slip of the driving wheel of the automobile in the starting or accelerating stage is caused by the fact that the driving torque exceeds the adhesion limit between the tire and the ground, the tire is abraded due to the excessive slip, the driving efficiency is reduced, and the lateral stability is reduced. Therefore, in order to avoid an excessive slip ratio during running, it is necessary to adopt a reasonable control method for reducing the driving torque on the drive wheels so as to control the slip ratio within an optimum range.
The method for driving the antiskid control at the present stage has various control strategies such as logic threshold value control, PID control, fuzzy control, optimal control, neural network control, sliding mode variable structure control and the like, and has the advantages and the disadvantages that:
(1) the logic threshold value control does not relate to a specific mathematical model of a controlled system, so that the control of a nonlinear system is convenient to realize, but the control logic of the logic threshold value control is complex and has large fluctuation.
(2) The PID control can control the slip ratio to a set value, but requires different parameters to be set on different road surfaces, so that the PID control is required to realize online adaptive adjustment.
(3) Fuzzy control carries out judgment and decision through fuzzy reasoning, and achieves the control effect. However, the method is difficult to establish the fuzzy control rule and difficult to debug.
(4) The optimal control solves the optimal index of the driving anti-skid control system according to the optimal principle, the effect of the optimal control depends on the precision of a mathematical model of the system, and the optimal control is difficult to realize in practical application.
(5) The sliding mode variable structure control enables the phase locus of the system control variable to slide to a control target along a switching line, the control method has strong robustness, but near the sliding mode surface, high-frequency jitter can be generated by control torque.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a road-surface-adaptive variable parameter anti-skid control system and method for a four-wheel-drive electric vehicle.
The purpose of the invention can be realized by the following technical scheme:
the utility model provides a four-wheel drive electric motor car variable parameter antiskid control system based on road self-adaptation, includes motor controller and motor moment distributor, motor controller set up 4 driving motor who connects the wheel respectively, its characterized in that: the variable parameter driving antiskid control unit is connected with the motor torque distributor, obtains the distribution torque of 4 driving motors and sends the distribution torque to the motor controller, and the motor controller respectively controls the 4 driving motors to move; the vehicle-mounted sensor unit is connected with a tire-road surface adhesion estimation unit and a variable parameter drive antiskid control unit, the tire-road surface adhesion estimation unit dynamically acquires the road surface peak adhesion coefficient of each wheel according to the actual measurement data of the vehicle-mounted sensor unit and sends the road surface peak adhesion coefficient to the variable parameter drive antiskid control unit, the variable parameter drive antiskid control unit calculates to obtain a control moment according to the road surface peak adhesion coefficient of each wheel and the actual measurement data of the vehicle-mounted sensor unit, whether drive antiskid control is needed or not is judged according to the control range requirement of the wheel slip rate, if the drive antiskid control is needed, the control moment is output to a motor controller, and the motor controller respectively implements antiskid control on 4 drive motors.
The vehicle-mounted sensor unit comprises a vehicle speed sensor for measuring vehicle speed, an acceleration sensor for measuring longitudinal and lateral acceleration, a wheel speed acquisition subunit for acquiring actual wheel speeds of 4 wheels, and a torque acquisition subunit for acquiring torques of 4 driving motors.
The variable parameter drive antiskid control unit comprises an optimal slip rate acquisition unit, a reference wheel speed calculation unit, a wheel speed difference calculation unit and a variable parameter drive antiskid controller; the input end of the optimal slip rate acquisition unit is connected with a tire-road adhesion estimation unit so as to acquire a dynamic road peak adhesion coefficient of each wheel, the output end of the optimal slip rate acquisition unit is connected with the input end of a reference wheel speed calculation unit, the input end of the reference wheel speed calculation unit is connected with a vehicle speed sensor, the output end of the reference wheel speed calculation unit is connected with the input end of a wheel speed difference value calculation unit, the positive input end of the wheel speed difference value calculation unit is connected with a wheel speed acquisition sub-unit, and the output end of the wheel speed difference value calculation unit is connected with the; the input end of the variable parameter drive antiskid controller is also connected with a motor torque distributor; the optimal slip rate obtaining unit is preset with a comparison graph of the road surface peak value attachment coefficient and the optimal slip rate in one-to-one correspondence; the optimal slip rate obtaining unit searches for a corresponding optimal slip rate in a comparison graph according to road surface peak value adhesion coefficients of 4 wheels sent by the tire-road surface adhesion estimating unit and sends the optimal slip rate to a reference wheel speed calculating unit, the reference wheel speed calculating unit calculates a reference wheel speed of each wheel according to the optimal slip rate and a vehicle speed obtained in real time from a vehicle speed sensor and provides the reference wheel speed to a wheel speed difference calculating unit, the wheel speed difference calculating unit calculates a difference according to an actual wheel speed obtained by the wheel speed obtaining subunit and the reference wheel speed calculated by the reference wheel speed calculating unit, the difference is input to a variable parameter drive anti-slip controller to obtain a control torque, whether drive anti-slip control is needed or not is judged according to the requirement of a wheel slip rate control range, and if the control torque is needed, the control torque is output to a motor controller.
The reference wheel speed calculating unit is specifically as follows:
wherein, ω isrFor reference wheel speed, λrFor optimum slip ratio, v is the vehicle speed and r is the wheel rolling radius.
The variable parameter driving antiskid controller is specifically as follows:
wherein, KpAnd KiRespectively, an error proportional term and an integral gain function, formed on the basis of a Gauss function, KpIs taken as 1 to ensure thatLarge proportional gain in a large range; kiThe width of the system is 1, and the integral effect is increased near a steady-state value, so that the system has higher response speed and integral saturation can be avoided; e-omegarω is the actual wheel speed, ωrIs the reference wheel speed; kp0,Kp1,Ki0,Ki1,Ti,TdAll parameters are controller parameters and are selected through real vehicle or simulation calibration.
The tire-road surface adhesion estimation unit comprises a road surface peak adhesion coefficient estimator and a vertical force estimator, wherein the input end of the road surface peak adhesion coefficient estimator is connected with a vehicle speed sensor, a wheel speed acquisition subunit, a torque acquisition subunit and the vertical force estimator, and the output end of the road surface peak adhesion coefficient estimator is connected with a variable parameter driving anti-skid control unit and sends dynamic road surface peak adhesion coefficients of each wheel to the variable parameter driving anti-skid control unit; the acceleration sensor also sends the measured longitudinal and lateral accelerations to the vertical force estimator.
The vertical force estimator comprises the following specific steps:
andare the vertical forces of the left front wheel, the right front wheel, the left rear wheel and the right rear wheel respectively, m is the mass of the whole vehicle, g is the gravity acceleration, l is the wheelbase and lfIs the distance from the center of mass to the front axis,/rIs the distance h from the center of mass to the rear axlegIs the height of the center of mass, axFor longitudinal acceleration, ayFor lateral acceleration, BfFor front track, BrIs the rear track width.
The road surface peak adhesion coefficient estimator specifically comprises:
wherein z is an intermediate variable, I is equivalent rotational inertia of the wheel, and TmIs the motor torque, r is the wheel rolling radius,as wheel longitudinal force estimate, FzThe wheel vertical force estimated for the vertical force estimator,for the road surface peak adhesion coefficient estimation value, λ is the wheel slip ratio, λ is (ω r-v)/v, ω is the actual wheel speed acquired by the wheel speed acquisition subunit, v is the vehicle speed measured by the vehicle speed sensor, and θ is*Is an equation of equationNumerical solution of (a), k1And γ is the estimator design parameter, k1And gamma are constants, mu (lambda, theta) is a modified Burckhardt tire model,is a middle order of μ (λ, θ)The resulting model function, in particular, μ (λ, θ) is:
wherein theta is the peak adhesion coefficient of the road surface, and theta2、θ3、θ4And theta5Are all constant parameters, exp is an exponential function with a natural constant e as a base, and sgn is a sign function.
A four-wheel drive electric vehicle variable parameter antiskid control method based on road surface self-adaptation comprises a variable parameter antiskid control system, wherein the system comprises a motor controller, a vehicle-mounted sensor unit, a tire-road surface adhesion estimation unit and a variable parameter drive antiskid control unit, the motor controller is provided with 4 drive motors which are respectively connected with wheels, the vehicle-mounted sensor unit is connected with the tire-road surface adhesion estimation unit and the variable parameter drive antiskid control unit, and the vehicle-mounted sensor unit comprises a vehicle speed sensor for measuring vehicle speed, an acceleration sensor for measuring longitudinal and lateral acceleration, a wheel speed acquisition subunit for acquiring the actual wheel speeds of 4 wheels and a torque acquisition subunit for acquiring the torques of 4 drive motors; the variable parameter drive antiskid control unit comprises an optimal slip rate acquisition unit, a reference wheel speed calculation unit, a wheel speed difference calculation unit and a variable parameter drive antiskid controller; the optimal slip rate obtaining unit is preset with a comparison graph of the road surface peak value attachment coefficient and the optimal slip rate in one-to-one correspondence; the method specifically comprises the following control steps:
step 1, acquiring actual wheel speeds omega of 4 wheels, corresponding torques of driving motors, and vehicle speeds v, longitudinal accelerations and lateral accelerations of a whole vehicle in real time;
step 2, inputting the data collected in the step 1 into a tire-road adhesion estimation unit to estimate and obtain road surface peak adhesion coefficients corresponding to 4 wheels;
step 3, searching a comparison graph in which the road surface peak value adhesion coefficients preset by the optimal slip rate obtaining unit correspond to the optimal slip rates one by one to obtain the optimal slip rate matched with the road surface peak value adhesion coefficients obtained in the step 2;
step 4, the reference wheel speed calculating unit calculates the reference wheel speed omega corresponding to each wheel according to the optimal slip rate and the actually measured vehicle speed vr；
Step 5, the wheel speed difference value calculation unit compares the actual wheel speed omega with the reference wheel speed omegarIs equal to ω - ωrInputting the variable parameters to a variable parameter driving antiskid controller to obtain a control torque;
and 6, judging whether the driving antiskid control is needed or not by the variable parameter driving antiskid controller according to the control range requirement of the wheel slip rate, if so, outputting control torque to the motor controller, and respectively implementing the antiskid control on 4 driving motors by the motor controller.
Compared with the prior art, the invention has the following advantages:
(1) the variable parameter driving anti-skid controller adopts a variable parameter PI controller, is formed on the basis of Gauss function, can be adjusted on line according to the deviation by introducing a nonlinear function to improve the control performance, and enables K to be changedpThe width of (1) is taken as 1 to ensure that the gain has larger proportional gain in a larger range; will KiThe width of the controller is 1, and the integral effect is increased near a steady state value, so that the system has higher response speed, the integral saturation can be avoided, the control accuracy of the controller is ensured, and the anti-skid control effect is improved.
(2) The invention designs a tire-road surface adhesion estimation unit by combining wheel dynamics, acquires the optimal slip rate in real time by acquiring the state of a vehicle in the running process, adjusts the control moment of a driving motor by the optimal slip rate, further changes the running state of the vehicle and forms a self-adaptive driving anti-slip control system.
Drawings
FIG. 1 is a block diagram of a road surface adaptive anti-skid control system of a four-wheel drive electric vehicle according to the present invention;
FIG. 2 is a comparison graph of the peak road surface adhesion coefficient and the optimal slip ratio in one-to-one correspondence.
In the figure, 1 is a motor controller, 2 is a motor torque distributor, 3 is a variable parameter drive antiskid controller, 4 is a vehicle speed sensor, 5 is a road surface peak adhesion coefficient estimator, 6 is a vertical force estimator, 7 is an optimal slip rate acquisition unit, 8 is a reference wheel speed calculation unit, and 9 is an acceleration sensor.
The invention is described in detail below with reference to the figures and specific embodiments.
Detailed Description
As shown in fig. 1, a four-wheel drive electric vehicle variable parameter anti-skid control system based on road surface self-adaptation comprises a motor controller 1, a motor torque distributor 2, a vehicle-mounted sensor unit, a tire-road surface adhesion estimation unit and a variable parameter drive anti-skid control unit, wherein the motor controller 1 is provided with 4 drive motors respectively connected with wheels, the variable parameter drive anti-skid control unit is connected with the motor torque distributor 2, obtains the distribution torque of the 4 drive motors and sends the distribution torque to the motor controller 1, and the motor controller 1 respectively controls the motion of the 4 drive motors; the vehicle-mounted sensor unit is connected with a tire-road surface adhesion estimation unit and a variable parameter drive antiskid control unit, the tire-road surface adhesion estimation unit is used for acquiring a road surface peak adhesion coefficient of each wheel, the tire-road surface adhesion estimation unit is connected with a variable parameter drive antiskid control unit, the variable parameter drive antiskid control unit calculates a control moment according to the road surface peak adhesion coefficient of each wheel acquired by the tire-road surface adhesion estimation unit and actual measurement data of the vehicle-mounted sensor unit, judges whether drive antiskid control is needed or not according to the requirement of a wheel slip rate control range, outputs the control moment to the motor controller 1 if the control moment is needed, and the motor controller 1 respectively carries out antiskid control on 4 drive motors.
The vehicle-mounted sensor unit comprises a vehicle speed sensor 4 for measuring vehicle speed, an acceleration sensor 9 for measuring longitudinal and lateral acceleration, a wheel speed acquisition subunit for acquiring actual wheel speeds of 4 wheels and a torque acquisition subunit for acquiring torques of 4 driving motors, wherein the vehicle speed sensor 4, the acceleration sensor 9, the wheel speed acquisition subunit and the torque acquisition subunit are all connected to a tire-road surface adhesion estimation unit, and the vehicle speed sensor 4 and the wheel speed acquisition subunit are also connected to a variable parameter driving antiskid control unit.
The tire-road surface adhesion estimation unit comprises a road surface peak adhesion coefficient estimator 5 and a vertical force estimator 6, wherein the input end of the road surface peak adhesion coefficient estimator 5 is connected with a vehicle speed sensor 4, a wheel speed acquisition subunit, a torque acquisition subunit and the vertical force estimator 6, and the output end of the road surface peak adhesion coefficient estimator 5 is connected with a variable parameter driving antiskid control unit and sends dynamic road surface peak adhesion coefficients of each wheel to the variable parameter driving antiskid control unit; the acceleration sensor also sends the measured longitudinal and lateral accelerations to the vertical force estimator 6.
The vertical force estimator 6 is specifically represented by the following equation:
wherein,andare the vertical forces of the left front wheel, the right front wheel, the left rear wheel and the right rear wheel respectively, m is the mass of the whole vehicle, g is the gravity acceleration, l is the wheelbase and lfIs the distance from the center of mass to the front axis,/rIs the distance h from the center of mass to the rear axlegIs the height of the center of mass, axFor longitudinal acceleration, ayFor lateral acceleration, BfFor front track, BrIs the rear track width.
The road surface peak adhesion coefficient estimator 5 is specifically represented by the following formula:
wherein z is an intermediate variable,the first derivative of z is obtained, I is equivalent rotational inertia of the wheel,Tmis the motor torque, r is the wheel rolling radius,as wheel longitudinal force estimate, FzFor the wheel vertical force estimated by the vertical force estimator 6,is an estimated value of the peak value adhesion coefficient of the road surface,presentation pairThe first derivative is obtained, λ is the wheel slip ratio, (ω r-v)/v, ω is the actual wheel speed obtained by the wheel speed obtaining subunit, v is the vehicle speed measured by the vehicle speed sensor 4, θ*Is an equation of equationNumerical solution of (a), k1And γ is the estimator design parameter, k1And gamma are constants, mu (lambda, theta) is a modified Burckhardt tire model,is a middle order of μ (λ, θ)And obtaining the model function.
The conventional Burckhardt tire model can describe the relationship between the tire slip rate and the longitudinal force more simply:
μ(λ)＝c1[1-exp(-c2λ)]-c3λ (3)
in the formula, ciI-1, 2,3 varies with the road surface condition, obtained by fitting experimental test data, and now to better describe the curve shape of μ - λ at high slip rate (λ is the wheel slip rate), the tire model parameters were increased from three to five, and takenUsing a modified Burckhardt tire model μ (λ, θ):
wherein theta is the peak adhesion coefficient of the road surface, and theta2、θ3、θ4And theta5Are all constant parameters, exp is an exponential function with a natural constant e as a base, and sgn is a sign function.
It is assumed that under the other parameters taken,andare in one-to-one correspondence, the parameter estimation error is generated when the road surface peak adhesion coefficient estimator 5 performs estimation updatingIs globally asymptotically stable and locally exponentially stable. But when the lambda is very small, it is,tends to 0, so in the above conclusionAnddegradation occurs in this condition on a one-to-one basis. At this time, if the parameter estimation is continued, the stability of the estimator is difficult to guarantee, so that a parameter updating mechanism is added:
where ε ∈ (0,1), here 0.8. Indicating phase only when wheel slip rate is in operationPeak slip ratio to the currently estimated road surfaceThe estimation is started when it is sufficiently large.
The variable parameter drive antiskid control unit comprises an optimal slip rate acquisition unit 7, a reference wheel speed calculation unit 8, a wheel speed difference value calculation unit and a variable parameter drive antiskid controller 3; the input end of the optimal slip rate acquisition unit 7 is connected with a road surface peak adhesion coefficient estimator 5 of a tire-road surface adhesion estimation unit to acquire a dynamic road surface peak adhesion coefficient of each wheel, the output end of the optimal slip rate acquisition unit 7 is connected with the input end of a reference wheel speed calculation unit 8, the input end of the reference wheel speed calculation unit 8 is also connected with a vehicle speed sensor 4, the output end of the reference wheel speed calculation unit 8 is connected with the input end of a wheel speed difference calculation unit, the positive input end of the wheel speed difference calculation unit is connected with a wheel speed acquisition subunit, and the output end of the wheel speed difference calculation unit is connected with the input end of a; the input end of the variable parameter drive antiskid controller 3 is also connected with the motor torque distributor 2 so as to obtain the distribution torque of 4 drive motors given by the motor torque distributor 2, and the motor controller 1 respectively controls the 4 drive motors to move; the optimal slip rate obtaining unit 7 is preset with a comparison graph in which the peak road adhesion coefficient and the optimal slip rate are in one-to-one correspondence; the optimal slip rate obtaining unit 7 searches a corresponding optimal slip rate in a comparison graph according to the road surface peak adhesion coefficient of 4 wheels sent by the tire-road surface adhesion estimation unit and sends the optimal slip rate to a reference wheel speed calculation unit 8, the reference wheel speed calculation unit 8 calculates a reference wheel speed of each wheel according to the optimal slip rate and the vehicle speed obtained in real time from the vehicle speed sensor 4 and provides the reference wheel speed to a wheel speed difference value calculation unit, the wheel speed difference value calculation unit calculates a difference value according to the actual wheel speed obtained by the wheel speed obtaining sub-unit and the reference wheel speed calculated by the reference wheel speed calculation unit 8, inputs the difference value to the variable parameter drive anti-slip controller 3 to obtain a control torque, judges whether the drive anti-slip control is needed or not according to the wheel slip rate control range requirement, and outputs the control torque to the motor controller 1 if the drive anti-slip control is needed, the motor controller 1 performs antiskid control on the 4 drive motors, respectively.
The optimal slip ratio obtaining unit 7 corrects the optimal slip ratio according to the road surface peak adhesion coefficient update result output by the tire-road surface adhesion estimation unit, so that the self-adaptive adjustment of slip ratio control under different road surface peak adhesion coefficients can be realized, and the specific method is as follows:
utilizing an improved Burckhardt tire model to conduct derivation on the slip ratio to obtain:
the lambda value when the formula is 0 is the optimal slip ratio under the road surface, and the parameter representing the peak value adhesion coefficient of the road surfaceAnd (3) carrying out value calculation from 0.1 to 1 at intervals of 0.1 to obtain a comparison graph of the peak value adhesion coefficient of the road surface and the optimal slip ratio in one-to-one correspondence shown in the graph 2.
The reference wheel speed calculating unit 8 is specifically:
wherein, ω isrFor reference wheel speed, λrFor optimum slip ratio, v is the vehicle speed and r is the wheel rolling radius.
The variable parameter drive antiskid controller 3 is specifically:
wherein, KpAnd KiRespectively an error proportional term and an integral gain function, based on a Gauss functionThe over-introduced non-linear function can be adjusted on line according to the deviation magnitude to improve the control performance. KpThe width of (1) is taken as 1 to ensure that the gain has larger proportional gain in a larger range; kiThe width of the system is 1, and the integral effect is increased near a steady-state value, so that the system has higher response speed and integral saturation can be avoided; e-omegarω is the actual wheel speed, ωrIs the reference wheel speed; kp0,Kp1,Ki0,Ki1,Ti,TdAll parameters are controller parameters and are selected through real vehicle or simulation calibration.
The control method of the road-surface-adaptive-based variable-parameter anti-skid control system for the four-wheel-drive electric vehicle comprises the following steps of:
step 1, acquiring actual wheel speeds omega of 4 wheels, corresponding torques of driving motors, and vehicle speeds v, longitudinal accelerations and lateral accelerations of a whole vehicle in real time;
step 2, inputting the data collected in the step 1 into a tire-road adhesion estimation unit to estimate and obtain road surface peak adhesion coefficients corresponding to 4 wheels;
step 3, searching a preset comparison graph in which the peak road adhesion coefficients correspond to the optimal slip rates one by one to obtain the optimal slip rates matched with the peak road adhesion coefficients obtained in the step 2;
step 4, solving a reference wheel speed omega corresponding to each wheel according to the optimal slip ratio and the actually measured vehicle speed vr；
Step 5, comparing the actual wheel speed omega with the reference wheel speed omegarIs equal to ω - ωrInput to the variable parameter drive antiskid controller 3 to obtain a control torque Tctr；
Step 6, the variable parameter drive antiskid controller 3 judges whether the drive antiskid control is needed according to the control range requirement of the wheel slip rate, and if so, outputs a control torque TctrFor the motor controller 1, the motor controller 1 respectively implements anti-skid control on the 4 driving motors.
Claims (9)
1. The utility model provides a four-wheel drive electric motor car variable parameter antiskid control system based on road self-adaptation, includes motor controller and motor moment distributor, motor controller set up 4 driving motor who connects the wheel respectively, its characterized in that: the variable parameter driving antiskid control unit is connected with the motor torque distributor, obtains the distribution torque of 4 driving motors and sends the distribution torque to the motor controller, and the motor controller respectively controls the 4 driving motors to move; the vehicle-mounted sensor unit is connected with a tire-road surface adhesion estimation unit and a variable parameter drive antiskid control unit, the tire-road surface adhesion estimation unit dynamically acquires the road surface peak adhesion coefficient of each wheel according to the actual measurement data of the vehicle-mounted sensor unit and sends the road surface peak adhesion coefficient to the variable parameter drive antiskid control unit, the variable parameter drive antiskid control unit calculates to obtain a control moment according to the road surface peak adhesion coefficient of each wheel and the actual measurement data of the vehicle-mounted sensor unit, whether drive antiskid control is needed or not is judged according to the control range requirement of the wheel slip rate, if the drive antiskid control is needed, the control moment is output to a motor controller, and the motor controller respectively implements antiskid control on 4 drive motors.
2. The variable parameter anti-skid control system of the four-wheel drive electric vehicle based on the road surface self-adaptation as claimed in claim 1, characterized in that: the vehicle-mounted sensor unit comprises a vehicle speed sensor for measuring vehicle speed, an acceleration sensor for measuring longitudinal and lateral acceleration, a wheel speed acquisition subunit for acquiring actual wheel speeds of 4 wheels, and a torque acquisition subunit for acquiring torques of 4 driving motors.
3. The variable parameter anti-skid control system of the four-wheel drive electric vehicle based on the road surface self-adaptation as claimed in claim 2, characterized in that: the variable parameter drive antiskid control unit comprises an optimal slip rate acquisition unit, a reference wheel speed calculation unit, a wheel speed difference calculation unit and a variable parameter drive antiskid controller; the input end of the optimal slip rate acquisition unit is connected with a tire-road adhesion estimation unit so as to acquire a dynamic road peak adhesion coefficient of each wheel, the output end of the optimal slip rate acquisition unit is connected with the input end of a reference wheel speed calculation unit, the input end of the reference wheel speed calculation unit is connected with a vehicle speed sensor, the output end of the reference wheel speed calculation unit is connected with the input end of a wheel speed difference value calculation unit, the positive input end of the wheel speed difference value calculation unit is connected with a wheel speed acquisition sub-unit, and the output end of the wheel speed difference value calculation unit is connected with the; the input end of the variable parameter drive antiskid controller is also connected with a motor torque distributor; the optimal slip rate obtaining unit is preset with a comparison graph of the road surface peak value attachment coefficient and the optimal slip rate in one-to-one correspondence; the optimal slip rate obtaining unit searches for a corresponding optimal slip rate in a comparison graph according to road surface peak value adhesion coefficients of 4 wheels sent by the tire-road surface adhesion estimating unit and sends the optimal slip rate to a reference wheel speed calculating unit, the reference wheel speed calculating unit calculates a reference wheel speed of each wheel according to the optimal slip rate and a vehicle speed obtained in real time from a vehicle speed sensor and provides the reference wheel speed to a wheel speed difference calculating unit, the wheel speed difference calculating unit calculates a difference according to an actual wheel speed obtained by the wheel speed obtaining subunit and the reference wheel speed calculated by the reference wheel speed calculating unit, the difference is input to a variable parameter drive anti-slip controller to obtain a control torque, whether drive anti-slip control is needed or not is judged according to the requirement of a wheel slip rate control range, and if the control torque is needed, the control torque is output to a motor controller.
4. The road-based adaptive four-wheel drive electric vehicle variable parameter anti-skid control system according to claim 3, wherein the reference wheel speed calculation unit is specifically:
wherein, ω isrFor reference wheel speed, λrFor optimum slip ratio, v is the vehicle speed and r is the wheel rolling radius.
5. The road surface adaptive four-wheel drive electric vehicle variable parameter anti-skid control system according to claim 3, characterized in that the variable parameter drive anti-skid controller is specifically:
wherein, KpAnd KiRespectively, an error proportional term and an integral gain functionConstructed on the basis of Gauss functions, KpThe width of (1) is taken as 1 to ensure that the gain has larger proportional gain in a larger range; kiThe width of the system is 1, and the integral effect is increased near a steady-state value, so that the system has higher response speed and integral saturation can be avoided; e-omegarω is the actual wheel speed, ωrIs the reference wheel speed; kp0,Kp1,Ki0,Ki1,Ti,TdAll parameters are controller parameters and are selected through real vehicle or simulation calibration.
6. The variable parameter anti-skid control system of the four-wheel drive electric vehicle based on the road surface self-adaptation as claimed in claim 2, characterized in that: the tire-road surface adhesion estimation unit comprises a road surface peak adhesion coefficient estimator and a vertical force estimator, wherein the input end of the road surface peak adhesion coefficient estimator is connected with a vehicle speed sensor, a wheel speed acquisition subunit, a torque acquisition subunit and the vertical force estimator, and the output end of the road surface peak adhesion coefficient estimator is connected with a variable parameter driving anti-skid control unit and sends dynamic road surface peak adhesion coefficients of each wheel to the variable parameter driving anti-skid control unit; the acceleration sensor also sends the measured longitudinal and lateral accelerations to the vertical force estimator.
7. The variable parameter anti-skid control system of four-wheel drive electric vehicle based on road surface self-adaptation according to claim 6, characterized in that the vertical force estimator is specifically:
andare respectively the vertical forces of the left front wheel, the right front wheel, the left rear wheel and the right rear wheel, and m is the whole vehicle massAmount, g is the acceleration of gravity, l is the wheelbase, lfIs the distance from the center of mass to the front axis,/rIs the distance h from the center of mass to the rear axlegIs the height of the center of mass, axFor longitudinal acceleration, ayFor lateral acceleration, BfFor front track, BrIs the rear track width.
8. The variable parameter anti-skid control system of four-wheel drive electric vehicle based on road surface self-adaptation according to claim 6, characterized in that the road surface peak adhesion coefficient estimator is specifically:
wherein z is an intermediate variable, I is equivalent rotational inertia of the wheel, and TmIs the motor torque, r is the wheel rolling radius,as wheel longitudinal force estimate, FzThe wheel vertical force estimated for the vertical force estimator,for the road surface peak adhesion coefficient estimation value, λ is the wheel slip ratio, λ is (ω r-v)/v, ω is the actual wheel speed acquired by the wheel speed acquisition subunit, v is the vehicle speed measured by the vehicle speed sensor, and θ is*Is an equation of equationNumerical solution of (a), k1And γ is the estimator design parameter, k1And gamma are constants, mu (lambda, theta) is a modified Burckhardt tire model,is a middle order of μ (λ, θ)To obtainIn particular, μ (λ, θ) is:
wherein theta is the peak adhesion coefficient of the road surface, and theta2、θ3、θ4And theta5Are all constant parameters, exp is an exponential function with a natural constant e as a base, and sgn is a sign function.
9. A four-wheel drive electric vehicle variable parameter antiskid control method based on road surface self-adaptation is characterized by comprising a variable parameter antiskid control system, wherein the system comprises a motor controller, a vehicle-mounted sensor unit, a tire-road surface adhesion estimation unit and a variable parameter drive antiskid control unit, the motor controller is provided with 4 drive motors which are respectively connected with wheels, the vehicle-mounted sensor unit is connected with the tire-road surface adhesion estimation unit and the variable parameter drive antiskid control unit, and the vehicle-mounted sensor unit comprises a vehicle speed sensor for measuring vehicle speed, an acceleration sensor for measuring longitudinal and lateral acceleration, a wheel speed acquisition subunit for acquiring the actual wheel speeds of 4 wheels and a torque acquisition subunit for acquiring the torques of 4 drive motors; the variable parameter drive antiskid control unit comprises an optimal slip rate acquisition unit, a reference wheel speed calculation unit, a wheel speed difference calculation unit and a variable parameter drive antiskid controller; the optimal slip rate obtaining unit is preset with a comparison graph of the road surface peak value attachment coefficient and the optimal slip rate in one-to-one correspondence; the method specifically comprises the following control steps:
step 1, acquiring actual wheel speeds omega of 4 wheels, corresponding torques of driving motors, and vehicle speeds v, longitudinal accelerations and lateral accelerations of a whole vehicle in real time;
step 2, inputting the data collected in the step 1 into a tire-road adhesion estimation unit to estimate and obtain road surface peak adhesion coefficients corresponding to 4 wheels;
step 3, searching a comparison graph in which the road surface peak value adhesion coefficients preset by the optimal slip rate obtaining unit correspond to the optimal slip rates one by one to obtain the optimal slip rate matched with the road surface peak value adhesion coefficients obtained in the step 2;
step 4, the reference wheel speed calculating unit calculates the reference wheel speed omega corresponding to each wheel according to the optimal slip rate and the actually measured vehicle speed vr；
Step 5, the wheel speed difference value calculation unit compares the actual wheel speed omega with the reference wheel speed omegarIs equal to ω - ωrInputting the variable parameters to a variable parameter driving antiskid controller to obtain a control torque;
and 6, judging whether the driving antiskid control is needed or not by the variable parameter driving antiskid controller according to the control range requirement of the wheel slip rate, if so, outputting control torque to the motor controller, and respectively implementing the antiskid control on 4 driving motors by the motor controller.
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