CN114889449A - Torque distribution method and system based on torque loss - Google Patents

Torque distribution method and system based on torque loss Download PDF

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Publication number
CN114889449A
CN114889449A CN202210711933.6A CN202210711933A CN114889449A CN 114889449 A CN114889449 A CN 114889449A CN 202210711933 A CN202210711933 A CN 202210711933A CN 114889449 A CN114889449 A CN 114889449A
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automobile
torque
tire
wheel
constraint
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汪洪波
胡金芳
张博阳
赵林峰
周俊涛
汪旭辉
王梓
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Hefei University of Technology
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Hefei University of Technology
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L15/00—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles
    • B60L15/20—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles for control of the vehicle or its driving motor to achieve a desired performance, e.g. speed, torque, programmed variation of speed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L15/00—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles
    • B60L15/32—Control or regulation of multiple-unit electrically-propelled vehicles
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2220/00—Electrical machine types; Structures or applications thereof
    • B60L2220/40—Electrical machine applications
    • B60L2220/42—Electrical machine applications with use of more than one motor
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2220/00—Electrical machine types; Structures or applications thereof
    • B60L2220/40—Electrical machine applications
    • B60L2220/44—Wheel Hub motors, i.e. integrated in the wheel hub
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/40—Drive Train control parameters
    • B60L2240/42—Drive Train control parameters related to electric machines
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/40—Drive Train control parameters
    • B60L2240/42—Drive Train control parameters related to electric machines
    • B60L2240/421—Speed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/40—Drive Train control parameters
    • B60L2240/42—Drive Train control parameters related to electric machines
    • B60L2240/423—Torque
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/40—Drive Train control parameters
    • B60L2240/46—Drive Train control parameters related to wheels
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2260/00—Operating Modes
    • B60L2260/20—Drive modes; Transition between modes
    • B60L2260/28—Four wheel or all wheel drive
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2260/00—Operating Modes
    • B60L2260/40—Control modes
    • B60L2260/42—Control modes by adaptive correction
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2260/00—Operating Modes
    • B60L2260/40—Control modes
    • B60L2260/48—Control modes by fuzzy logic
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/72—Electric energy management in electromobility

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Arrangement And Driving Of Transmission Devices (AREA)

Abstract

The invention relates to a torque distribution method and system based on torque loss. The torque distribution method based on the torque loss comprises the following steps: establishing an equality constraint state matrix A according to the additional yaw moment delta M of the automobile and the torque loss coefficient of the automobile eq And equality constraint vector b eq (ii) a Establishing a quadratic state matrix H and a quadratic state vector c according to the constraint condition of the optimized distribution of the automobile; constraining a state matrix A according to the equation eq Equality constraint vector b eq Calculating the tire longitudinal force x of the automobile through a quadratic programming function by using the quadratic state matrix H and the quadratic state vector c; and calculating the longitudinal force x of the tire of the automobile and the radius of the wheel by multiplication to obtain a driving torque distribution value of the wheel. The present invention reconstructs four-wheel drive torque distribution based on the torque loss factor.

Description

Torque distribution method and system based on torque loss
Technical Field
The invention relates to the technical field of electric automobiles, in particular to a torque distribution method based on torque loss and a torque distribution system based on torque loss.
Background
The distributed hub motor driven automobile has the advantages that the space in the hub is small, the motor is prone to generating faults, accordingly, the driving performance of the distributed hub motor driven automobile is affected, and the driving stability of the distributed hub motor driven automobile is affected in severe cases. Particularly, the torque loss working condition of the hub motor of the automobile under a low-adhesion road surface seriously influences the operation stability and the driving safety of the automobile, the torque distribution can be carried out on the four-wheel drive torque of the distributed drive automobile according to the additional yaw moment required by the stability of the automobile, although the torque distribution has the function of stabilizing the automobile, the torque loss condition is not considered, so that the torque distribution still has defects, and the effect of optimizing the distribution is not achieved.
Disclosure of Invention
Based on this, it is necessary to provide a torque distribution method based on torque loss and a torque distribution system based on torque loss, which are directed to the problem that torque distribution cannot be optimally distributed without considering torque loss.
In order to achieve the purpose, the invention adopts the following technical scheme:
a torque distribution method based on torque loss for providing respective driving torque distribution values to a plurality of wheels of an automobile to maintain lateral stability of the automobile, the torque distribution method based on torque loss comprising the steps of:
establishing an equality constraint state matrix A according to the additional yaw moment delta M of the automobile and the torque loss coefficient of the automobile eq And equality constraint vector b eq ；
Establishing a quadratic state matrix H and a quadratic state vector c according to the constraint condition of the optimized distribution of the automobile;
constraining a state matrix A according to the equation eq Equality constraint vector b eq The quadratic state matrix H and the quadratic state vector c are calculated by a quadratic programming functionObtaining the tire longitudinal force x of the automobile, and obtaining a quadratic programming function
Figure BDA0003707128750000011
Figure BDA0003707128750000012
Wherein A is an inequality constraint function state matrix, and b is an inequality constraint vector;
and calculating the longitudinal force x of the tire of the automobile and the radius of the wheel by multiplication to obtain a driving torque distribution value of the wheel.
Further, the method for calculating the constraint condition of the optimized distribution comprises the following steps:
obtaining the longitudinal force F of the front right tire of the automobile xfr The front left tire longitudinal force F of the automobile xfl The longitudinal force F of the rear right tire of the automobile xrr The longitudinal force F of the rear left tire of the automobile xrl The distance l from the center of mass to the front axle of the automobile f And the distance l from the center of mass to the rear axle of the automobile r ；
Calculating an additional yaw moment constraint for the vehicle:
ΔM＝(F xfr -F xfl )l f +(F xrr -F xrl )l r ；
calculating a total driving force constraint of the automobile: f x ＝F xfl +F xfr +F xrl +F xrr ；
Calculating a driving torque expected value constraint of the wheels of the automobile according to the driving torque maximum value of the wheels: t is m ≤T max 。
Further, the method for calculating the maximum value of the driving torque of the wheel includes the steps of:
obtaining the rated power P of the hub motor of the automobile max And the rotation speed n of the hub motor of the automobile;
calculating a maximum value T of the driving torque of the wheel max ：
Figure BDA0003707128750000021
Further, the method for calculating the quadratic programming function comprises the following steps:
obtaining a tire longitudinal force F of the vehicle xih The tire side force F of the automobile yij Vertical load F of the tire of the automobile zij The ground adhesion coefficient mu of the wheel of the automobile;
calculating the constraint of the tire longitudinal force according to the road adhesion coefficient:
Figure BDA0003707128750000022
calculating the tire load rate ρ from the Dugoff tire model ij ：
Figure BDA0003707128750000023
Establishing a quadratic objective function according to the tire load rate of the automobile:
Figure BDA0003707128750000024
wherein the content of the first and second substances,
Figure BDA0003707128750000025
is the square of the tire load rate, E (rho) is the average mean value of the tire load rate, and eta is the weighting coefficient of the average automobile tire load rate;
and converting the quadratic objective function into the quadratic programming function according to the constraint condition of the optimized distribution.
Further, the method for calculating the quadratic state matrix H comprises the following steps:
obtaining the vertical load F of the front left tire of the automobile zfl The front right tire vertical load F of the automobile zfr The vertical load F of the rear left tire of the automobile zrl The vertical load F of the rear right tire of the automobile zrr ；
And (3) establishing a quadratic form state matrix H of yaw moment optimal distribution according to the road adhesion coefficient mu:
Figure BDA0003707128750000026
further, the method for calculating the quadratic programming vector c of the yaw moment optimization allocation comprises the following steps:
obtaining the vertical load F of the front left tire of the automobile zfl The front right tire vertical load F of the automobile zfr The vertical load F of the rear left tire of the automobile zrl The vertical load F of the rear right tire of the automobile zrr The weighting coefficient eta of the average automobile tire load rate;
and (3) establishing a quadratic programming vector c of the optimal distribution of the yaw moment according to the road adhesion coefficient mu:
Figure BDA0003707128750000031
further, the equation constrains the state matrix A eq The calculation method comprises the following steps:
obtaining a left front wheel torque loss coefficient epsilon of the automobile fl The right front wheel torque loss coefficient epsilon of the automobile fr The torque loss coefficient epsilon of the left rear wheel of the automobile rl The right rear wheel torque loss coefficient epsilon of the automobile rr ；
According to the distance l from the mass center of the automobile to the front axle f And the distance l from the center of mass to the rear axle of the automobile r Establishing an equality constraint state matrix A eq ：
Figure BDA0003707128750000032
Further, the equality constrains the vector b eq The calculation method comprises the following steps:
acquiring total driving force F of the automobile x ；
B is established according to the additional yaw moment delta M of the vehicle eq ：b eq ＝[ΔMF x ]。
Further, the method for calculating the state matrix a of the inequality constraint function and the inequality constraint vector b includes the following steps:
obtaining the radius r of the wheel and the maximum value T of the driving torque of the front left wheel of the automobile flmax The maximum value T of the driving torque of the front right wheel of the automobile frmax The maximum value T of the driving torque of the rear left wheel of the automobile rlmax The maximum value T of the driving torque of the rear right wheel of the automobile rrmax ；
Establishing an inequality constraint function state matrix A:
Figure BDA0003707128750000033
establishing an inequality constraint vector b: b ═ T flmax T frmax T rlmax T rrmax ]。
The present invention also includes a torque distribution system based on torque loss, which when in operation implements the above-described torque distribution method based on torque loss, the torque distribution system based on torque loss comprising:
a constraint coefficient matrix calculation module for establishing an equality constraint state matrix A according to the additional yaw moment delta M of the automobile and the torque loss coefficient of the automobile eq And equality constraint vector b eq ；
The quadratic form state matrix calculation module is used for establishing a quadratic form state matrix H and a quadratic form state vector c according to the constraint condition of the optimized distribution of the automobile;
a quadratic programming function calculation module for constraining a state matrix A according to the equation eq Equality constraint vector b eq Calculating the tire longitudinal force x of the automobile through a quadratic programming function by using the quadratic state matrix H and the quadratic state vector c, and calculating the quadratic programming function
Figure BDA0003707128750000041
Wherein A is an inequality constraint function state matrix, and b is an inequality constraint vector;
and the driving torque distribution value calculation module is used for calculating and obtaining a driving torque distribution value of the wheel of the automobile by multiplying the longitudinal force x of the tire of the automobile and the radius of the wheel of the automobile.
The technical scheme provided by the invention has the following beneficial effects:
the invention can reconstruct the torque distribution on the basis of available normal wheels according to the position of the torque loss, ensure the driving safety of the automobile, obtain the optimal driving torque of four wheels by quadratic programming optimization solution, reconstruct the four-wheel driving torque distribution according to the torque loss coefficient, and control the output torque of the hub motor, thereby promoting the automobile to still have the capability of stable driving after the torque loss of the motor.
Drawings
FIG. 1 is a flow chart of a torque distribution method based on torque loss of the present invention;
FIG. 2 is a schematic diagram of a configuration of the coordinated torque distribution system based on FIG. 1;
FIG. 3 is a three-dimensional simulation of the fuzzy rule of FIG. 1;
FIG. 4 is a schematic diagram of the structure of an extensible control domain based on the extensible control torque constraint of FIG. 2;
fig. 5 is a schematic structural diagram of a stable region of the yaw moment control system based on fig. 2;
FIG. 6 is a simulation of the torque distribution system based on FIG. 2 taking into account torque losses;
FIG. 7 is a simulation diagram of the single-wheel torque loss system based on FIG. 2;
FIG. 8 is a simulation diagram of the two-wheel torque loss system based on FIG. 2;
FIG. 9 is a logic diagram based on the torque coordinated distribution system of FIG. 2.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The torque distribution method based on the torque loss solves the problem that the torque distribution in the prior art cannot achieve optimal distribution because the torque loss is not considered. According to the invention, through the position of the occurrence of the torque loss, the torque distribution is reconstructed on the basis of available normal wheels, the driving safety of the automobile is ensured, the optimal driving torque of four wheels is obtained through quadratic programming optimization solution, the four-wheel driving torque distribution is reconstructed according to the torque loss coefficient, and the output torque of the hub motor is controlled, so that the automobile still has the capability of stable driving after the torque loss of the motor.
As shown in fig. 1, the present embodiment provides a torque distribution method based on torque loss, including the steps of:
establishing an equality constraint state matrix A according to the additional yaw moment delta M of the automobile and the torque loss coefficient of the automobile eq And equality constraint vector b eq ；
Establishing a quadratic state matrix H and a quadratic state vector c according to the constraint condition of the optimized distribution of the automobile;
constraining a state matrix A according to the equation eq Equality constraint vector b eq Calculating the tire longitudinal force x of the automobile through a quadratic programming function by using the quadratic state matrix H and the quadratic state vector c, and calculating the quadratic programming function
Figure BDA0003707128750000051
Figure BDA0003707128750000052
Wherein A is an inequality constraint function state matrix, and b is an inequality constraint vector;
and calculating the longitudinal force x of the tire of the automobile and the radius of the wheel by multiplication to obtain a driving torque distribution value of the wheel.
The embodiment also provides a torque distribution system based on torque loss, which realizes the torque distribution method based on torque loss during system operation, and the system comprises a constraint coefficient matrix calculation module which is used for calculating the constraint coefficient matrix according toEstablishing an equality constraint state matrix A by the additional yaw moment Delta M of the automobile and the torque loss coefficient of the automobile eq And equality constraint vector b eq (ii) a The quadratic form state matrix calculation module is used for establishing a quadratic form state matrix H and a quadratic form state vector c according to the constraint condition of the optimized distribution of the automobile; a quadratic programming function calculation module for constraining a state matrix A according to the equation eq Equality constraint vector b eq Calculating the tire longitudinal force x of the automobile through a quadratic programming function by using the quadratic state matrix H and the quadratic state vector c, and calculating the quadratic programming function
Figure BDA0003707128750000053
Wherein A is an inequality constraint function state matrix, and b is an inequality constraint vector; and the driving torque distribution value calculation module is used for calculating and obtaining a driving torque distribution value of the wheel of the automobile by multiplying the longitudinal force x of the tire of the automobile and the radius of the wheel of the automobile.
The torque distribution method based on the torque loss is applied to a torque distribution system based on the torque loss, which is included in a coordinated torque distribution system, and the coordinated torque distribution system will be described in detail below.
As shown in fig. 2, a torque coordination distribution system is designed for the condition that the torque loss of a hub motor of a distributed drive automobile under a low-adhesion road surface seriously affects the operation stability and the driving safety of the automobile, and mainly comprises a nonlinear error feedback torque control system, a particle swarm extension control torque constraint system, an automobile stability-based yaw moment control system and a torque distribution system based on torque loss. When the nonlinear error feedback torque control system works, the nonlinear error feedback torque control method is adopted.
The following is a detailed description of the non-linear error feedback torque control system:
as the road condition may change all the time, in order to prevent the tires of the automobile from skidding and increase the applicable working condition range of the stability control strategy, a fuzzy control algorithm is adopted to adaptively adjust the wheel slip rate threshold value.
By the deviation delta omega of the actual value of the yaw rate of the vehicle from the reference value z (Δω z ＝ω z -ω z ') and a current wheel slip value s, a slip threshold value s max As the output, fuzzy rule setting of the slip rate threshold value is carried out, for example, when the wheel slip rate value s and the yaw rate are larger, the automobile needs to reduce the wheel slip to ensure the stability of the automobile, and the wheel slip rate threshold value output by fuzzy control is smaller at the moment. The fuzzy logic rule table established according to the multiple simulation tests is shown in the following table.
Fuzzy rule table for slip rate threshold value
Figure BDA0003707128750000061
The fuzzy rule three-dimensional effect graph obtained by the fuzzy rule and the corresponding input and output membership function can judge and output the slip rate threshold value adaptive to the current working condition according to the parameter estimation condition as shown in fig. 3, and further carry out wheel anti-slip control to restrict the wheel driving torque.
Based on the slip threshold value of the fuzzy control, a non-linear error feedback torque control system is designed to obtain a desired torque to prevent the wheel from slipping. The nonlinear error feedback control principle is to make nonlinear combination of errors and then output the torque control demand, as shown in fig. 1, wherein the input of the nonlinear negative feedback control is the deviation e between the wheel slip ratio estimated value and the slip ratio threshold value 1 Deviation e between actual value of wheel drive torque and expected value of torque 2 Calculating the driving torque adjusting value T by combining the errors of the two through nonlinearity e To prevent the wheel from slipping. Beta is a centroid slip angle, and the designed nonlinear error feedback control mathematical expression is as follows:
Figure BDA0003707128750000062
wherein u is 0 For the nonlinear control law, k 0 Is a gain coefficient, c 0 Is a damping coefficient, h 0 For the sampling time, a factor b is compensated 0 ＝1/J ω (inertia of wheel 0.9kg · m2), coefficient of regulation r 0 ＝0.05/h 0 ，r 0 The function of (a) is to adjust the control force of the nonlinear feedback control system, the value can be determined by empirical value or multiple tests, fst (·) is the synthesized function of the fastest control, and
Figure BDA0003707128750000071
the following describes a torque constraint system based on particle swarm extension control specifically:
designing torque constraint control by considering wheel slip prevention, wherein the wheel torque output constraint requirements under different working conditions are different, so that extension control domains are respectively divided by adopting an extension control theory, and an adaptive vehicle wheel torque constraint mode along with the change of the road working conditions is realized; the extension control domain is divided as shown in fig. 4, and the intersection points of the connecting line of the original point and the feature quantity in the extension set and the boundary of the extension domain and the classical domain from left to right are Q 1 、Q 2 、Q 3 、Q 4 And the slip rate of the automobile wheels in the classical domain is small, the mass center slip angle of the automobile is small, the automobile is in a working condition with good road adhesion condition, and the torque restriction of wheel slip is not needed at the moment. The slip rate and the centroid slip angle of the automobile wheel in the extension domain tend to increase, at the moment, constraint limitation needs to be applied to torque distribution, the state is kept to be the best in the extension domain, and the torque is prevented from continuously increasing to enter the non-domain. The slip ratio and the mass center slip angle of the wheels in the non-domain are large, the automobile is about to be unstable or enters an unstable state, the torque of the wheels needs to be strictly restricted at the moment, and the safety and the stability of the automobile are ensured as far as possible.
The method comprises the following steps that an extension set is required to be divided in an extension control domain, the boundary of each region is determined, and then the wheel torque constraint mode of each control region is determined, wherein the design steps are as follows:
(1) selecting characteristic quantities
The characteristic quantities are used to indicate a wheel slip condition and a vehicle steady state. Therefore, in order to distinguish the wheel slip and driving stability boundaries and regions of the classical domain, the extension domain and the non-domain, the wheel slip value s and the actual centroid slip angle β of the automobile are selected as characteristic quantities, and the two values form Q (s, β).
(2) Partitioning of scalable sets
The method comprises the following steps of firstly dividing a classical domain boundary, wherein the classical domain boundary is relatively easy to divide, and a linear region boundary of a yaw velocity gain is used as an actual centroid yaw angle classical domain boundary. Calculating the maximum value of the actual centroid slip angle of the linear region through the fitting relation, wherein the value of the actual centroid slip angle is the classical domain boundary beta 1 . The empirical formula of the front wheel steering angle limit value and the vehicle speed is as follows:
Figure BDA0003707128750000072
wherein, a 10 ，b 10 ，c 10 And d 10 As fitting parameters, 0.05, 0.07, 0.6 and 13.3, respectively; calculating the maximum value delta of the front wheel rotation angle in the linear region max Substituting the two-degree-of-freedom model of the vehicle can calculate the classical domain boundary beta 1 。
Classical domain boundary s of wheel slip 1 Bounded by a slip threshold value of the fuzzy control output, i.e. s 1 ＝s max . And when the wheel slip rate is smaller than the slip rate threshold value, the wheel slip state is considered to be stable and is in the classical domain.
And secondly, dividing the extension domain boundary. The particle swarm algorithm does not depend on strict mathematics of the optimization problem and accurate mathematical description of a target function and a constraint condition, only a corresponding evaluation function needs to be designed, and the extension domain boundary is a two-dimensional boundary with small dimension, so that the particle swarm algorithm is adopted for dividing the extension domain boundary to iteratively search the optimal boundary. In each iteration of the algorithm, the particles continuously solve the optimal solution p according to the individual i And the population optimal solution p so far g Both extrema update themselves. Further, the particle velocity and position are updated according to the following formula:
Figure BDA0003707128750000081
Figure BDA0003707128750000082
Figure BDA0003707128750000083
wherein the content of the first and second substances,
Figure BDA0003707128750000084
is the velocity and position of the particle in the k-th generation,
Figure BDA0003707128750000085
is the maximum velocity of the particle, whose value is too large to fly through the optimal solution, rand () is a random number greater than 0 and less than 1, and the learning factor is c 1 ＝c 2 τ is an inertial weight that balances the local and global optima, and is designed as shown by:
Figure BDA0003707128750000086
wherein the maximum weight τ max 1.4, minimum weight τ min ＝0.4，t gen Is the number of iterations.
The fitness function is set as:
Figure BDA0003707128750000087
therefore, the specific process of determining the extension domain boundary by the particle swarm algorithm is as follows:
step 1, obtaining an actual yaw velocity value omega of the wheel z According to the actual value omega of the yaw angular velocity z And setting a fitness function according to the actual centroid slip angle beta
Figure BDA0003707128750000088
Wherein v is x Is the vehicle speed of the wheel, μ is the road adhesion coefficient, g is the gravitational acceleration;
step 2. the automobileOne wheel of the automobile is used as a target individual, all wheels of the automobile are used as a population, and the actual value omega of the yaw rate of each wheel is used z Forming particles by taking the corresponding actual centroid side deflection angle beta as a particle parameter, and forming particle groups by all the particles;
step 3, acquiring particle parameters of the population in the historical optimal state under the actual road adhesion coefficient to serve as the optimal solution of the historical population, and acquiring particle parameters of the target individual in the historical optimal state under the actual road adhesion coefficient to serve as the optimal solution of the historical individual;
step 4, taking the actual particle parameters of the target individual as target particles, and calculating the adaptive value of the target particles through the fitness function by the target particles;
step 5, comparing the adaptive value of the target particle with the adaptive value of the historical individual optimal solution, if the adaptive value of the target particle is greater than the adaptive value of the historical individual optimal solution, replacing the particle parameter of the historical individual optimal solution with the particle parameter of the target particle, updating the individual optimal solution, and if the adaptive value of the target particle is less than the adaptive value of the historical individual optimal solution, keeping the particle parameter of the historical individual optimal solution inconvenient;
step 6, comparing the adaptive value of the target particle with the adaptive value of the historical population optimal solution, if the adaptive value of the target particle is greater than the adaptive value of the historical population optimal solution, replacing the particle parameter of the historical population optimal solution with the particle parameter of the target particle, updating the population optimal solution, and if the adaptive value of the target particle is less than the adaptive value of the historical population optimal solution, keeping the particle parameter of the historical population optimal solution inconvenient;
and 7, carrying out iterative updating on the particle parameters of the target particles according to the individual optimal solution and the new population optimal solution, judging whether the iteration times reach a preset maximum iteration number, if not, returning the updated target particles to the step 3, if so, stopping the iteration, and calculating the optimal value s of the slip rate according to the actual value of the yaw velocity after the target particle iteration is finished through a slip rate calculation formula 2 Taking the actual centroid slip angle after the target particle iteration is finished as the optimal centroid slip angle beta 2 。
(3) Design of relevance function
Designing a correlation function according to the position and the distance of the characteristic quantity in the control domain, wherein the extension distance from the characteristic point to the extension domain is as follows:
Figure BDA0003707128750000091
wherein, C k If the extension range is, the correlation function k(s) is:
Figure BDA0003707128750000092
wherein, C j The domain is a classical domain interval, so that the domain where the characteristic quantity is located can be judged more conveniently through the calculation result of the correlation function K (S).
(4) Measure pattern partitioning
The measure mode of the characteristic quantity, namely the measure mode M, can be judged by the correlation function K (S) 1 When { S | k (S) > 1} the feature is in the classical domain; measure mode M 2 When the feature quantity is in an extension domain, the { S |0K (S) ≦ 1 }; measure mode M 3 When { S | k (S) < 0}, the feature quantity is in the non-domain.
Thus at M 1 Under the measure mode, the torque constraint limitation of wheel slip does not need to be considered, and the torque is only constrained by the peak torque of the hub motor, namely
Figure BDA0003707128750000093
P max The rated power of the hub motor is shown, and n is the rotating speed of the motor.
At M 2 In the measure mode, a certain degree of wheel slip needs to be considered. Driving torque regulating value T output by feedback torque control system according to non-linear error e Design torque maximum constraint T max Comprises the following steps: t is max ＝[K(S)+1]T e 。
At M 3 In the measure mode, the wheel slip condition is serious, and the centroid slip angle is seriousAnd entering a destabilizing state, wherein the maximum value of the design torque is restricted by T max Comprises the following steps: t is max ＝T e 。
The constraint mode of the wheel output torque is judged through the extension domain division of the wheel slip rate value and the actual centroid slip angle, and the optimal extension domain boundary is searched for the road surfaces under different attachment conditions through the particle swarm optimization.
The following is a detailed description of a yaw moment control system based on vehicle stability:
the loss of the output torque of the hub motor can cause sudden change of the yaw moment of the automobile. An excessive yaw moment is generated in the process, so that the automobile can possibly change the course angle and the driving track rapidly and enter an unstable working condition, and further the driving danger is increased. Therefore, the adaptive yaw moment constraint should be provided for the optimal control of the yaw motion of the automobile and the control strategy of the distribution of the driving torque, so as to ensure the driving stability of the automobile.
Firstly, a control boundary is determined according to the automobile state, namely a stability control criterion is determined, the automobile stability criterion determines whether a yaw moment control system is started or not, and an actual mass center slip angle-an actual mass center slip angular velocity (beta-v) is adopted β ) The phase plane is used as the criterion of the stability of the automobile.
Dividing the automobile stable region by using a bilinear method and a limit cycle method, namely adding an ellipse tangent to two straight lines in the region divided by the bilinear method, taking the ellipse as the stable region, wherein the schematic diagram is shown in FIG. 5, and the straight line l 1 And l 2 Phase plane stability boundaries determined for bilinear methods, while ellipses and/ 1 And l 2 The tangency is realized, a finally determined stable domain is formed in the tangent, so that two tangent points are formed by the simultaneous connection of two straight lines and an ellipse equation, and the major and minor semiaxes a and b of the ellipse are finally calculated:
Figure BDA0003707128750000101
wherein, c 11 And c 22 The vehicle stability criterion is obtained by the method according to the actual phase diagram, namely if the vehicle is determinedAnd the state is outside an elliptical stable region, and the yaw moment control system is required to act to output an additional yaw moment for recovering stability, so that the torque distribution layer distributes the torque to enable the automobile to recover stability. The lengths of the semiaxes of the stable area ellipses under different road adhesion coefficients obtained by the method are shown in the following table:
stable boundary parameter table
Figure BDA0003707128750000102
The fitting formula for obtaining the change of the stable boundary ellipse semi-axis along with the road adhesion coefficient according to the parameters in the table is as follows:
Figure BDA0003707128750000111
and (3) calculating the additional yaw moment required by the stability of the automobile by adopting a sliding mode control algorithm, wherein the sliding mode control law and the sliding mode surface can be changed according to the characteristic requirements of the controlled system and are unrelated to the disturbance and other parameters of the system.
Firstly, calculating a reference yaw moment of the automobile, wherein the road conditions are various, and the road adhesion coefficient of the automobile is also constantly changed, so that the automobile theory can know that the yaw velocity and the centroid slip angle of the automobile are constrained by the adhesion conditions, and the two are constrained as follows according to the adhesion conditions:
Figure BDA0003707128750000112
then the ideal centroid slip angle beta of the automobile d And yaw angular velocity ω d Respectively as follows:
Figure BDA0003707128750000113
Figure BDA0003707128750000114
wherein
Figure BDA0003707128750000115
Is the coefficient of stability, v, of the vehicle x Is the speed of the vehicle, delta is the angle of rotation of the front wheel, l r Is the distance from the center of mass to the rear axis,/ f Is the distance from the center of mass of the automobile to the front axle, L is the wheelbase of the wheels of the automobile, k 2 Is the rear wheel side yaw stiffness k of the automobile 2 ，k 1 Is the front wheel side deflection rigidity of the automobile, and m is the whole automobile mass
The designed sliding mode function is as follows: u ═ ω (ω) z -ω d )+h 2 (β-β d )，
And (3) carrying out derivation on the sliding mode control rate u, wherein the derivation formula is as follows:
Figure BDA0003707128750000116
the approach law of the sliding mode controller is as follows:
Figure BDA0003707128750000117
wherein beta is the actual centroid slip angle of the automobile, epsilon is the torque loss coefficient of the automobile, and h 1 Is a weighting factor, h, of the sliding mode control rate calculation 2 Is a weighting coefficient h calculated by a sliding mode control approach rate 2 。
Because the sliding mode control has the buffeting problem, a filtering method can be adopted, a low-pass filter is used for a switching function of the sliding mode control, a smooth signal is obtained, and the buffeting of the system is reduced. And finally obtaining an additional yaw moment for maintaining the stable running requirement of the automobile by a simultaneous three-degree-of-freedom model of the automobile body as follows:
Figure BDA0003707128750000118
Figure BDA0003707128750000119
where Fyfr is the front right tire lateral force, Fyrr is the rear right tire lateral force, Fyfl is the front left tire lateral force, F yrl Is the rear left tire lateral force.
The torque distribution system based on torque loss is described in detail below:
in order to ensure the yaw stability of the automobile, the torque distribution is carried out on the four-wheel drive torque of the distributed drive automobile according to the additional yaw moment required by the stability of the automobile, which is obtained by a yaw moment control system based on the stability of the automobile. The four-wheel torque distribution adopts a quadratic programming algorithm. According to the theory of wheel dynamics, the tire force of the wheel is limited by the adhesion ellipse, the larger the longitudinal force of the wheel, the smaller the margin for the lateral force, and the lateral stability of the automobile during steering is affected. Therefore, the tire load rate is adopted to restrain the wheel torque, so that the lateral stability of the automobile is ensured, and the automobile is provided with four wheels as an example.
First, an optimization objective function is determined, and tire force is calculated according to a Dugoff tire model, and the relationship between the tire force and the tire adhesion force is as follows:
Figure BDA0003707128750000121
wherein, F xij Is the longitudinal force of the tire, F yij Is the tire lateral force, F zij Is the vertical load of the tyre
The tire load rate is set as follows:
Figure BDA0003707128750000122
where i ∈ { f, r } denotes front and back, and j ∈ { l, r } denotes left and right.
The driving torque of the hub motor can be directly controlled, the longitudinal force and the lateral force of the tire are provided by the adhesive force, the transverse force is ensured to reduce the longitudinal force, and therefore, the longitudinal force is mainly used for setting a quadratic objective function as follows:
Figure BDA0003707128750000123
wherein E (rho) represents the average mean value of the tire load rates, the E (rho) is added to enable each tire load rate to be close, the utilization rate of each tire can be improved, and eta is a weighting coefficient used for coordinating the two-part optimization target ratio.
Constraints for optimal allocation are then determined, mainly the equality constraint of the additional yaw moment with the longitudinal driver model output driving force and the inequality constraint of the maximum torque constraint taking into account wheel slip, the constraints established being as follows:
Figure BDA0003707128750000124
wherein F x For total driving force for vehicle running, P max Is the rated power of the hub motor, n is the motor speed, s is the wheel slip ratio, T m Actual value of drive torque, F xfr Is the front right tire longitudinal force, F xrr Is the rear right tire longitudinal force, F xfl Is the front left tire longitudinal force, F xrl Is the rear left tire longitudinal force.
And finally, determining an optimal distribution algorithm, optimally distributing the upper layer yaw moment by utilizing a quadratic programming theory, converting the target function into a standard quadratic form, wherein the quadratic programming function is as follows:
Figure BDA0003707128750000125
wherein x ═ F xfl ,F xfr ,F xrl ,F xrr ] T Expressing matrix transposition, and deducing a quadratic programming H matrix and a quadratic programming c matrix as follows by inequality constraint and a quadratic programming function:
Figure BDA0003707128750000131
Figure BDA0003707128750000132
F zfl is the vertical load of the front left tire of the automobile, F zfr Is the vertical load of the front and right tires of the automobile, F zrl Is the rear left tire vertical load of the automobile, F zrr Is the rear right tire of the automobile is verticalThe load is obtained by an inequality constraint function, A and b are respectively:
Figure BDA0003707128750000133
where r radius of the wheel, T flmax Is the maximum value of the driving torque, T, of the front left wheel of the automobile frmax Is the maximum value of the driving torque, T, of the front right wheel of the automobile rlmax Is the maximum value of the driving torque, T, of the rear left wheel of the automobile rrmax Is the maximum value of the driving torque of the rear right wheel of the automobile, therefore, the constraint of the inequality Ax is less than or equal to b is an affine function, A eq x＝b eq The equality constraint is also an affine function, which is consistent with the characteristics of the convex quadratic programming problem, which is thus a convex quadratic programming problem.
In addition, since the four-wheel hub motor has torque loss, it is necessary to reconstruct torque distribution according to the degree of torque loss, where ∈ ═ epsilon fl ,ε fr ,ε rl ,ε rr ] T For quadratic programming function, the function is constrained according to inequality and epsilon is integrated to constraint coefficient matrix A eq And b eq To get
Figure BDA0003707128750000134
b eq ＝[ΔM F x ]
After the quadratic programming function is solved to obtain the optimal driving torque of the four wheels, the four-wheel driving torque distribution is further reconstructed according to the torque loss coefficient, and the output torque of the hub motor is controlled, so that the automobile can still have the capability of stable running after the motor torque is lost.
For the simulation analysis of the torque coordination distribution system, firstly, whether the torque distribution strategy considering the torque loss can ensure the driving stability of the automobile when the torque of the in-wheel motor is lost is preliminarily verified. And selecting a double-shift-line working condition, setting the road adhesion coefficient to be 0.85, setting the loss of the right front hub motor to be reduced to 60% of torque output by simulation, and setting the simulation starting vehicle speed and the target vehicle speed to be 60 km/h. The results are shown in FIG. 6. The Torque Distribution strategy in which the Torque loss is taken into account is denoted as tdtl (Torque Distribution fire Torque loss). As can be seen from fig. 6(a), the loss of the torque of the right front wheel causes the vehicle to have a yaw rate for driving to the right, and after the torque is redistributed to the four wheels, the yaw rate of the vehicle can follow the desired value and the vehicle can be safely driven, thereby improving the maneuverability of the vehicle. As can be seen from fig. 6(b), the centroid slip angle starts to increase after the torque loss of the right front wheel of the automobile, which seriously affects the stability of the automobile, and the torque distribution strategy considering the torque loss reconstructs the four-wheel torque, so that the error between the actual value of the centroid slip angle and the reference value is reduced, and the stability of the automobile is greatly increased. As can be seen from fig. 6(c), when the torque loss occurs in the right front wheel of the vehicle, the vehicle not only has poor steering stability, but also has a certain loss in vehicle speed, and the torque distribution strategy considering the torque loss can make the vehicle speed decrease relatively smaller in the double-lane action, thereby improving the dynamic performance of the vehicle to a certain extent. Therefore, the torque distribution strategy considering the torque loss can be analyzed and obtained, and the torque distribution strategy can play a role in ensuring the driving safety, the operation stability and certain dynamic property of the automobile on a road surface with good adhesion conditions.
When single-wheel torque loss simulation verification is carried out, a double-traverse-line working condition simulation test is selected, the torque loss of the right front wheel is reduced to 60%, the road adhesion coefficient is set to be 0.3, the initial vehicle speed and the target vehicle speed are both 60km/h, and the simulation result is shown in fig. 7. The torque distribution strategy in which the torque losses are taken into account is denoted TDTL. The wheel Slip constrained Torque coordinated Distribution strategy taking into account Torque losses is denoted as TDSRTL (Torque Distribution for Slip braking while Torque loss). As can be seen from the comparative simulation results of the two control strategies, in fig. 7(b), the torque coordinated split strategy (TDSRTL) that takes into account the wheel slip constraint can make the vehicle yaw rate response faster, and the vehicle drivability better, i.e., can respond faster to the driver's steering demand, than the torque split strategy (TDTL) that does not take into account the torque constraint. In the torque distribution strategy in FIG. 7(c), the centroid slip angle of the torque distribution strategy without considering the torque constraint at the time of 10.45s is-2.845 degrees, while the centroid slip angle of the torque coordination distribution control strategy with considering the wheel slip constraint is-2.446 degrees, so that 14.02 percent is reduced, the jitter of the centroid slip angle of the automobile can be eliminated, and the driving stability of the automobile is improved. As can be seen from the four-wheel torque output curve in fig. 7(d), after the torque of the right front wheel is lost, the drive torque of the left front wheel is reduced, and the drive torque of the right rear wheel is correspondingly increased according to the yaw moment control demand, but under the constraint control considering the wheel slip, the drive torque of the right rear wheel is reduced at any time in the process of increasing the torque so as to prevent the wheel slip, and the running safety of the automobile is ensured. In fig. 7(e), although the wheel torque is limited and the vehicle driving torque is reduced to some extent, the vehicle speed is reduced little and is reduced by about 0.5km/h only during the double lane shifting operation. In general, when the right front wheel has torque loss, the proposed coordinated torque distribution control strategy considering wheel slip redistributes the torque, ensures the yaw moment required by the stability of the automobile, and ensures the driving safety of the automobile.
And when the two-wheel torque loss simulation verification is carried out, the working condition that the two wheels generate the torque loss is designed, and the proposed torque coordination distribution control strategy is verified. And selecting a double-shift-line simulation test. The torque loss of the two wheels on the same side is set, the torque loss of the right front wheel is reduced to 80%, the torque loss of the right rear wheel is reduced to 50%, the road adhesion coefficient is 0.3, the initial vehicle speed and the target vehicle speed are both 60km/h, and the simulation result is shown in FIG. 8. From the simulation comparison result of the torque loss of the two wheels on the same side, it is seen that the torque distribution strategy (TDTL) in fig. 8(b) without considering the torque constraint generates a certain degree of sideslip when the lane is changed for the second time in the double lane shifting action, so that the automobile is in a dangerous driving state in the period of time, and the torque coordination distribution control strategy (TDSRTL) considering the wheel slip improves the sideslip phenomenon and ensures the driving safety of the automobile. As can be seen from fig. 8(c), although the torque distribution strategy without considering the torque constraint can reduce the centroid slip angle of the vehicle before 10s to ensure the stability of the vehicle, the centroid slip angle is increased instead to cause the wheel slip during the second lane change, and the torque coordination distribution control restrains the torque output to a certain extent under the extension judgment, but controls the wheel slip at the same time to ensure the stability of the vehicle as a whole. As can be seen from the four-wheel torque in fig. 8(d), since the torque loss occurs in both right two wheels, the yaw moment cannot be compensated by increasing the torque on the different-axis side as in the case of the single-wheel loss. The left wheel torque also decreases and follows the change in the right wheel torque while the left wheel fine tuning torque output maintains the yaw moment stable. As can be seen from FIG. 8(e), the lowest vehicle speed of the torque distribution strategy without considering the torque constraint is 56.5km/h, and the vehicle speed under the torque coordination distribution control can be kept between 57 km/h and 60km/h, so that the dynamic property of the vehicle is ensured to a certain extent.
The verification proves that the whole torque coordination distribution system can ensure that the automobile can stably and safely run when the motor torque is lost by distributing the torque of the four-wheel motor of the automobile.
All possible combinations of the technical features of the above embodiments may not be described for the sake of brevity, but should be considered as within the scope of the present disclosure as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims (10)

1. A torque distribution method based on torque loss for providing respective driving torque distribution values to a plurality of wheels of an automobile for maintaining lateral stability of the automobile, characterized in that the torque distribution method based on torque loss comprises the steps of:
establishing an equality constraint state matrix A according to the additional yaw moment delta M of the automobile and the torque loss coefficient of the automobile eq And equality constraint vector b eq ；
Establishing a quadratic state matrix H and a quadratic state vector c according to the constraint condition of the optimized distribution of the automobile;
constraining a state matrix A according to the equation eq Equality constraint vector b eq Calculating the tire longitudinal force x of the automobile through a quadratic programming function by using the quadratic state matrix H and the quadratic state vector c, and calculating the quadratic programming function
Figure FDA0003707128740000011
Figure FDA0003707128740000012
Wherein A is an inequality constraint function state matrix, and b is an inequality constraint vector;
and calculating the longitudinal force x of the tire of the automobile and the radius of the wheel by multiplication to obtain a driving torque distribution value of the wheel.
2. The torque distribution method based on torque loss according to claim 1, characterized in that the calculation method of the constraint conditions of the optimal distribution comprises the following steps:
obtaining the longitudinal force F of the front right tire of the automobile xfr The front left tire longitudinal force F of the automobile xfl The longitudinal force F of the rear right tire of the automobile xrr The longitudinal force F of the rear left tire of the automobile xrl The distance l from the center of mass to the front axle of the automobile f And the distance l from the center of mass to the rear axle of the automobile r ；
Calculating an additional yaw moment constraint for the vehicle:
ΔM＝(F xfr -F xfl )l f +(F xrr -F xrl )l r ；
calculating a total driving force constraint of the automobile: f x ＝F xfl +F xfr +F xrl +F xrr ；
Calculating a driving torque expected value constraint of the wheels of the automobile according to the driving torque maximum value of the wheels: t is m ≤T max 。
3. The torque distribution method based on torque loss according to claim 2, wherein the calculation method of the maximum value of the driving torque of the wheel includes the steps of:
obtaining the rated power P of the hub motor of the automobile max And the rotation speed n of the hub motor of the automobile;
calculating a maximum value T of the driving torque of the wheel max ：
Figure FDA0003707128740000013
4. The torque distribution method based on torque loss according to claim 1, wherein the calculation method of the quadratic programming function comprises the steps of:
obtaining a tire longitudinal force F of the vehicle xij The tire side force F of the automobile yij Vertical load F of the tire of the automobile zij The ground adhesion coefficient mu of the wheel of the automobile;
calculating the constraint of the tire longitudinal force according to the road adhesion coefficient:
Figure FDA0003707128740000021
calculating the tire load rate ρ from the Dugoff tire model ij ：
Figure FDA0003707128740000022
Establishing a quadratic objective function according to the tire load rate of the automobile:
Figure FDA0003707128740000023
wherein the content of the first and second substances,
Figure FDA0003707128740000024
is a tireThe square of the load rate, E (rho) is the average mean value of the tire load rate, and eta is the weighting coefficient of the average automobile tire load rate;
and converting the quadratic objective function into the quadratic programming function according to the constraint condition of the optimized distribution.
5. The torque distribution method based on torque loss according to claim 1, wherein the calculation method of the quadratic state matrix H comprises the steps of:
obtaining the vertical load F of the front left tire of the automobile zfl The front right tire vertical load F of the automobile zfr The vertical load F of the rear left tire of the automobile zrl The vertical load F of the rear right tire of the automobile zrr ；
And (3) establishing a quadratic form state matrix H of yaw moment optimal distribution according to the road adhesion coefficient mu:
Figure FDA0003707128740000025
6. the torque distribution method based on torque loss according to claim 1, characterized in that the calculation method of the quadratic programming vector c of the yaw moment optimization distribution comprises the following steps:
obtaining the vertical load F of the front left tire of the automobile zfl The front right tire vertical load F of the automobile zfr The vertical load F of the rear left tire of the automobile zrl The vertical load F of the rear right tire of the automobile zrr The weighting coefficient eta of the average automobile tire load rate;
and (3) establishing a quadratic programming vector c of the optimal distribution of the yaw moment according to the road adhesion coefficient mu:
Figure FDA0003707128740000026
7. the method of claim 1Torque distribution method based on torque loss, characterized in that said equality constrains the state matrix A eq The calculation method comprises the following steps:
obtaining a left front wheel torque loss coefficient epsilon of the automobile fl The right front wheel torque loss coefficient epsilon of the automobile fr The torque loss coefficient epsilon of the left rear wheel of the automobile rl The right rear wheel torque loss coefficient epsilon of the automobile rr ；
According to the distance l from the mass center of the automobile to the front axle f And the distance l from the center of mass to the rear axle of the automobile r Establishing an equality constraint state matrix A eq ：
Figure FDA0003707128740000031
8. The torque distribution method based on torque loss according to claim 1, wherein the equality constraint vector b eq The calculation method comprises the following steps:
acquiring total driving force F of the automobile x ；
B is established according to the additional yaw moment delta M of the vehicle eq ：b eq ＝[ΔM F x ]。
9. The torque distribution method based on torque loss according to claim 1, wherein the calculation method of the state matrix a of the inequality constraint function and the inequality constraint vector b comprises the steps of:
obtaining the radius r of the wheel and the maximum value T of the driving torque of the front left wheel of the automobile flmax The maximum value T of the driving torque of the front right wheel of the automobile frmax The maximum value T of the driving torque of the rear left wheel of the automobile rlmax The maximum value T of the driving torque of the rear right wheel of the automobile rrmax ；
Establishing an inequality constraint function state matrix A:
Figure FDA0003707128740000032
establishing an inequality constraint vector b: b ═ T flmax T frmax T rlmax T rrmax ]。
10. A torque distribution system based on torque loss for providing respective driving torque distribution values to a plurality of wheels of an automobile for maintaining lateral stability of the automobile, characterized in that it employs a torque distribution method based on torque loss according to any one of claims 1 to 9, the torque distribution system based on torque loss comprising:
a constraint coefficient matrix calculation module for establishing an equality constraint state matrix A according to the additional yaw moment delta M of the automobile and the torque loss coefficient of the automobile eq And equality constraint vector b eq ；
The quadratic form state matrix calculation module is used for establishing a quadratic form state matrix H and a quadratic form state vector c according to the constraint condition of the optimized distribution of the automobile;
a quadratic programming function calculation module for constraining a state matrix A according to the equation eq Equality constraint vector b eq Calculating the tire longitudinal force x of the automobile through a quadratic programming function by using the quadratic state matrix H and the quadratic state vector c, and calculating the quadratic programming function
Figure FDA0003707128740000033
Wherein A is an inequality constraint function state matrix, and b is an inequality constraint vector;
and the driving torque distribution value calculation module is used for calculating and obtaining a driving torque distribution value of the wheel of the automobile by multiplying the longitudinal force x of the tire of the automobile and the radius of the wheel of the automobile.
CN202210711933.6A 2022-06-22 2022-06-22 Torque distribution method and system based on torque loss Pending CN114889449A (en)

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