CN119176186A - Electric automobile steering motor control optimization method considering communication delay - Google Patents

Abstract

The invention discloses an electric automobile steering motor control optimization method considering communication delay, which comprises the steps of obtaining an expected value of a motor steering angle, obtaining expected values of steering angular speed and steering angular acceleration of a motor according to the expected value of the motor steering angle, inputting the expected values of the steering angle, the steering angular speed and the steering angular acceleration of the motor into a feedforward control module, outputting feedforward control quantity signals by the feedforward control module, obtaining motor operation signals through a motor sensor, inputting the motor operation signals into a delay observer, outputting observed values of the steering angle, the steering angular speed and the steering angular acceleration with delay by the delay observer, inputting signals output by the delay observer, the switching function module and the external disturbance module into a feedback control module, outputting feedback control quantity signals by the feedback control module, and adding the feedforward control quantity and the feedback control quantity to obtain a current expected value.

Description

Electric automobile steering motor control optimization method considering communication delay

Technical Field

The invention belongs to the field of distributed wire control intelligent vehicle wire control steering, and particularly relates to an electric vehicle steering motor control optimization method considering communication delay.

Background

Under the background of removing the drive train from the automobile chassis, the drive-by-wire chassis technology gradually replaces the position of the traditional chassis, the drive-by-wire steering is used as one of the core technologies of the drive-by-wire chassis, the complicated and huge mechanical structure of the traditional drive train can be omitted, the drive efficiency and the response time are improved, and the stability of the automobile is ensured.

On the basis, the physical delay can influence the efficiency of the actuator to a certain extent because the signal directly reaches the actuator from the sensor, and the traditional steering motor control strategy adopts a three-closed-loop PID control method which adopts PID control in a position loop, a speed loop and a current loop.

Disclosure of Invention

The invention aims to provide an electric automobile steering motor control optimization method considering communication delay, which overcomes the defects caused by signal delay and improves the stability and accuracy of steering control by introducing a delay observer and a robust self-adaptive sliding mode method combining feedforward control and feedback control.

The technical scheme provided by the invention is as follows:

An electric automobile steering motor control optimization method considering communication delay comprises the following steps:

acquiring an expected value of a motor steering angle, and acquiring an expected value of a steering angular speed and a steering angular acceleration of the motor according to the expected value of the motor steering angle;

inputting expected values of steering angle, steering angular speed and steering angular acceleration of the motor into a feedforward control module, wherein the feedforward control module outputs feedforward control quantity signals;

Acquiring a motor operation signal through a motor sensor, and inputting the motor operation signal into a delay observer, wherein the delay observer outputs observed values of a steering angle, a steering angular speed and a steering angular acceleration with delay;

The method comprises the steps of inputting expected values and observed values of steering angles, steering angular speeds and steering angular accelerations of the motor into a switching function module and a feedback control module, wherein signals output by the switching function module are input into an exogenous interference module;

inputting signals output by the delay observer, the switching function module and the exogenous interference module into the feedback control module, and outputting feedback control quantity signals by the feedback control module;

and adding the feedforward control quantity and the feedback control quantity to obtain a current expected value.

Preferably, the feedback control module obtains the feedback control amount signal by the following formula:

;

Wherein: Is a feedback control quantity signal; the motor moment of inertia is from a motor sensor; Is the friction viscosity coefficient; a motor torque coefficient; Is a switching function; Error between observed value and expected value of motor steering angle; Is that Is a derivative of (2); As defined auxiliary variables; the coefficients of the switching function in the speed loop controller and the parameters to be optimized; Defining coefficients in the process for auxiliary variables in the speed loop controller and as parameters to be optimized; The sliding mode term coefficient in the speed loop controller is the parameter to be optimized; Is a switching term coefficient; perturbation and exogenous interference for motor parameters; For motor parameter perturbation and exogenous interference Is a function of the estimated value of (2); is a sign function; Is an optimization function; , for the motor steering angle and the motor steering angular velocity observations output by the delay observer, Is thatIs a component of (1); is the steering angle of the motor and is used for controlling the motor to rotate, from a motor sensor; To be about Is a function of (2); The steering angular speed of the motor; To be about Is a function of (2); The steering angular speed of the motor; , for a given desired value of motor steering angle and motor steering angular speed, from the demand of the driver while driving, Is thatIs included in the (a) and (b) is included in the (b) component.

Preferably, the feedback control module is further configured to optimize:

Establishing a performance index and an error function:

;

Wherein: Is a performance index; Is an error function; Is a delay-free time; Is the expected value of the steering angle of the motor; Is the expected value of the steering angular speed of the motor;

The constraint conditions are as follows:

;

Wherein: is an auxiliary matrix;

With minimum performance index as optimization target, for parameters 、AndOptimizing to obtain optimal parameters、AndTo adjust the feedback control quantity signal。

Preferably, the calculation formula of the switching function is:

。

Preferably, the exogenous interference is estimated using an adaptive law:

;

Wherein: Is that Is a derivative of (2); Coefficients are estimated for adaptation.

Preferably, the feedforward control module obtains the feedforward control amount signal by the following formula:

;

Wherein: Is a feedforward control quantity signal; for steering motor load torque, from a motor sensor; , for a given desired value of motor steering angular velocity and motor steering angular acceleration, the motor steering angular velocity and motor steering angular acceleration are calculated from the requirements of the driver while driving, Is thatIs a component of (1); is the desired value of the motor steering angular acceleration.

Preferably, the delay observer state space expression is designed as:

Wherein: , For the observed values of the motor steering angular velocity and the motor steering angular acceleration output by the delay observer, Is thatIs a component of (1); A coefficient matrix that is a state space expression of the delay observer; Is an output matrix; Is an observer gain matrix; is a constant; To output a delay signal; The steering angle value with time delay is fed back to the motor encoder; is a time-varying delay time; Is an observed quantity of the delay signal; Output torque for the motor from the motor sensor; Is the motor control quantity.

Preferably, the state space equation of the delay observer with respect to the speed loop controller is

;

Wherein: a coefficient matrix of a state space equation of the speed loop controller; Is a control amount; Is the current expected value.

The beneficial effects of the invention are as follows:

The control optimization method for the electric automobile steering motor considering communication delay is based on the traditional three-closed-loop PID, a delay observer is introduced at an actuator end, signal delay is monitored and processed in real time, control accuracy of the steering motor is effectively improved, a robust self-adaptive sliding mode method combining feedforward control and feedback control is adopted to control a speed loop controller, various interference factors are overcome, robustness and stability of a system are remarkably improved, parameters of the speed loop controller are optimized, optimality of the speed loop controller parameters is guaranteed, control performance is improved, a designed speed loop controller model is simple and efficient, processing speed of the speed loop controller is improved, and complexity of the system is reduced.

Drawings

Fig. 1 is a flowchart of an electric vehicle steering motor control optimization method considering communication delay according to the present invention.

FIG. 2 is a flow chart of a speed loop controller according to the present invention.

FIG. 3 is a flow chart of the BEO algorithm according to the present invention.

Detailed Description

The present invention is described in further detail below with reference to the drawings to enable those skilled in the art to practice the invention by referring to the description.

As shown in fig. 1, the invention provides a method for optimizing control of an electric automobile steering motor by considering communication delay, which comprises the following steps:

According to the working principle and the overall control architecture of a steering system of a distributed drive-by-wire vehicle, a delay observer aiming at a time-varying delay signal is designed to process hazards caused by the delay signal, the delay observer is arranged at the rear end of a lower-layer controller and an actuator, signal delay is monitored in real time, the actual state of a steering motor is determined and fed back to the speed loop controller, a speed loop control model comprising electromechanical coupling interference and delay signal interference is constructed, the speed loop controller is controlled by adopting a robust self-adaptive sliding mode method combining feedforward control and feedback control, the expected steering angle of a steering motor is obtained from the upper-layer controller, performance indexes, error functions and constraint conditions are established, optimal speed loop controller parameters are obtained through BEO algorithm iterative optimization, the lower-layer controller and the actuator receive current expected values and execute steering operation, the delay signal and the external interference provided by the delay observer are integrated through the speed loop controller, the current expected values are calculated and output, the steering angle expected values of the steering motor are enabled to be converted into current expected values required by the lower-layer controller and the actuator, the lower-layer controller and the upper-layer controller and the actuator are enabled to provide the steering angle expected values for the steering motor through the upper-layer controller, the VCU-layer controller and the steering motor expected values are enabled to be transmitted to the driver through the hardware and the steering wheel controller and the driver is expected to make the steering angle.

The invention provides an electric automobile steering motor control optimization method considering communication delay, which comprises the steps of obtaining expected values of a steering angle of a motor, obtaining expected values of steering angular speed and steering angular acceleration of the motor according to the expected values of the steering angle of the motor, inputting the expected values of the steering angle, the steering angular speed and the steering angular acceleration of the motor into a feedforward control module, outputting feedforward control quantity signals by the feedforward control module, obtaining motor operation signals through a motor sensor, inputting the motor operation signals into a delay observer, outputting observed values of the steering angle, the steering angular speed and the steering angular acceleration with delay by the delay observer, inputting the expected values and the observed values of the steering angle, the steering angular speed and the steering angular acceleration of the motor into a switching function module and a feedback control module, inputting signals output by the switching function module into an external disturbance module, inputting signals output by the delay observer, the switching function module and the external disturbance module into the feedback control module, outputting feedback control quantity signals and adding the feedforward control quantity and the expected feedback control quantity.

The invention provides a control optimization method of an electric automobile steering motor considering communication delay, which designs a delay observer aiming at a time-varying delay signal according to the working principle and the whole control framework of a steering system of a distributed drive-by-wire vehicle, constructs a speed loop control model comprising electromechanical coupling interference and delay signal interference, adopts a robust self-adaptive sliding mode method combining feedforward control and feedback control to replace a traditional PID method for controlling a speed loop controller, monitors external interference in real time by utilizing a self-adaptive law, enables the speed loop controller to adjust control output according to the monitoring result of a self-adaptive law module, overcomes various interferences based on robust sliding mode control and realizes control performance optimization.

Design of a delay observer:

In a distributed steer-by-wire vehicle steering system, the signal goes through the sensor, CAN bus, controller to the actuator, and its physical delay CAN significantly impair the performance of the actuator.

Therefore, the invention provides a time-varying delay observer which is used for monitoring signal delay among a controller, a motor encoder and a CAN communication network in real time and shielding damage caused by delay characteristics through processing observed signals in a bottom-layer controller.

In the steering actuating mechanism, the core driving unit is a permanent magnet servo motor, and the mechanical characteristic equation of the steering actuating mechanism can be obtained based on the working principle and the electromechanical coupling characteristic of the permanent magnet servo motor used by the steering system of the distributed drive-by-wire vehicle:

;

Wherein:

Outputting torque for the steering motor from the motor sensor as a control input;

for steering motor load torque, from a motor sensor;

For steering motor moment of inertia, from the motor sensor;

Is the friction viscosity coefficient;

Is a delay-free time;

is the steering angle of the motor and is used for controlling the motor to rotate, from a motor sensor; To be about Is a function of (2);

The steering angular speed of the motor; To be about Is a function of (2);

is the motor steering angular acceleration.

The state space expression for the motor steering angle is:

;

Wherein:

, as a state variable, a state variable is used, Is thatIs a component of (1);

, Is that Is used for the purpose of determining the derivative of (c),Is thatIs a component of (1);

Outputting torque for the steering motor from the motor sensor as a control input;

To output a delay signal as a control output;

The steering angle value with time delay is fed back to the motor encoder;

is a time-varying delay time;

A coefficient matrix that is a state space expression for the steering angle of the motor.

The state space expression of the delay observer is designed based on the state space expression of the motor steering angle as follows:

;

Wherein:

, the motor steering angle and the motor steering angular velocity output by the delay observer, Is thatIs a component of (1);

, For the observed values of the motor steering angular velocity and the motor steering angular acceleration output by the delay observer, Is thatIs a component of (1);

A coefficient matrix that is a state space expression of the delay observer;

Is an output matrix;

Is an observer gain matrix;

is a constant;

Is an observed quantity of the delay signal;

Is the motor control quantity;

By controlling To changeFor observingAlong with itIs a changing relationship of (a).

The conditions for the convergence of the state space expression of the delay observer are: satisfying the Hurwitz condition, wherein: is a convergence judging matrix;

The characteristic equation of (2) is:

;

Wherein:

Is a characteristic value;

Is a unit diagonal matrix;

By adjusting Thereby adjustingMake the followingThe Hurwitz convergence condition is satisfied, and the stability of the system is ensured.

Design of a speed loop controller:

the speed loop controller aims to overcome control performance degradation, exogenous input interference and internal parameter perturbation caused by signal transmission delay and ensure the robustness and the accuracy of a steering actuator.

The mechanical characteristics of the steering actuating mechanism are influenced by exogenous interference, assembly errors and other factors, the rotational inertia and the viscosity coefficient are changed, and the perturbation characterization of the parameters can be obtained in a mechanical characteristic equation:

;

Wherein:

a perturbation value representing the rotational inertia of the steering motor;

Is the perturbation value of the friction coefficient;

an interference value is input for the outside.

The delay observer establishes a state space expression for the speed loop controller as:

;

Wherein:

as a motor torque coefficient, the torque coefficient of the motor,

Is a control amount;

Is the expected value of the current;

Is a feedforward control quantity signal;

Is a feedback control quantity signal;

perturbation and exogenous interference for motor parameters;

A coefficient matrix that is a state space expression of the delay observer with respect to the speed loop controller.

Characterization of perturbation is available within the mechanical property equation:

;

state space expression for a given motor steering angle expectation value:

;

Wherein:

, for a given desired value of motor steering angle and motor steering angular speed, from the demand of the driver while driving, Is thatIs a component of (1);

, for a given desired value of motor steering angular velocity and motor steering angular acceleration, the motor steering angular velocity and motor steering angular acceleration are calculated from the requirements of the driver while driving, Is thatIs a component of (1);

Is the expected value of the steering angle of the motor;

Is the expected value of the steering angular speed of the motor;

is the expected value of the steering angular acceleration of the motor;

A coefficient matrix of the state space expression for a given motor steering angle desired value.

Further, a feedforward control module within a speed loop controller within the speed loop controller obtains a feedforward control quantity signal by the following formula:

;

In order to further overcome the interference of factors such as signal transmission delay, parameter perturbation and the like, the feedback control quantity is needed to be solved, the feedforward control quantity in the speed loop controller is substituted into the state space expression which is established by the delay observer and related to the speed loop controller, and the state space expression which is obtained by the observed value of the steering angle and the feedback control quantity of the motor is as follows:

Wherein:

for motor steering angle observation value and feedback control quantity Coefficient matrices of state space expressions of (c).

Setting auxiliary variables:

;

Wherein:

As defined auxiliary variables;

Error between observed value and expected value of motor steering angle;

let the first Lyapunov function be :

For a pair ofDeriving and obtaining:

Wherein:

Is that Is a derivative of (2);

Is that Is a derivative of (2);

based on the lyapunov stability principle, let Then needAndConverging to 0.

Setting the switching function asThe calculation formula of the switching function is:

;

Wherein:

Is a switching function;

The coefficients of the switching function in the speed loop controller are the parameters to be optimized;

The expected values and the observed values of the steering angle, the steering angular speed and the steering angular acceleration of the motor are input into the switching function module to obtain a switching function signal, the switching function signal is a smooth curve, so that the feedback sliding mode control is more stable, and the system can have excellent control performance under different working conditions by changing the value of the control parameter.

Let the second Lyapunov function be:

;

;

Wherein:

Is an interference convergence speed coefficient;

For motor parameter perturbation and exogenous interference Is a function of the estimated value of (2);

Estimating an error for the interference;

For a pair of Deriving and obtaining:

;

Wherein:

Is that Is a derivative of (2);

Is that Is a derivative of (2);

Is that Is a derivative of (2);

Is that Is a derivative of (2);

Is that Is a derivative of (2);

Is that Is a derivative of (2);

In the case of slow exogenous disturbance, it is visible 。

Substituting the above conclusion intoIn the expression of (2), we get:

;

The feedback control module in the speed loop controller obtains a feedback control quantity signal through the following formula:

;

Wherein:

is a sign function;

Defining in-process coefficients for auxiliary variables in the speed loop controller and parameters to be optimized;

the sliding mode term coefficient in the speed loop controller is the parameter to be optimized;

Is a switching term coefficient;

Is an optimization function;

The following approach law optimization function is set:

;

;

Wherein:

Is a sliding mode function;

Is that Is a derivative of (2);

Representing an absolute value;

Is a natural constant;

Is an approach law coefficient;

an optimization function for the approach law;

is a constant;

With respect to Is an optimization function of (a)The method comprises the following steps:

;

the adaptive law is adopted to interfere with the external source And (3) estimating:

;

Wherein:

Estimating coefficients for the adaptation;

The sensor generates fluctuation due to the physical reasons of hardware, and the external environment influences signal acquisition, such as the external static electricity influences the accuracy of the sensor;

The second lyapunov function derivative of this system is:

Providing an auxiliary matrix The method comprises the following steps:

Based on auxiliary matrix The method can obtain the following steps:

let the auxiliary vector be :

Wherein:

Is that Is a transpose of (2);

If order Is positive and definite matrix, can meet。

Output variable of speed loop controller as input into current expectation value of lower controller and actuatorThrough the lower controller and the actuator, the output quantity of the actuator is updatedAnd delay observer output。

Establishing a performance index and an error function, and optimizing a feedback control module:

;

Wherein:

Is a performance index;

Is an error function;

To be about Is a function of (2).

Iterative optimization of parameters of a speed loop controller by BEO algorithm、AndMeets the constraint conditionAnd make (1) andFor positive definite matrix, obtaining optimized speed loop controller parameters、AndThrough optimization、AndTo adjust the feedback signalThereby changing the control amount of the delay observer in the state space expression of the speed loop controllerAdjusting state quantity by control quantity、The aim of controlling steering precision is achieved.

As shown in fig. 3, the BEO algorithm constructs a mathematical model based on the behavior of black eagle, and performs iterative optimization through the behaviors of tracking, coiling, capturing, robbing, warning, migration, coupling, hatching and the like, so as to find an optimal solution in a large-scale iterative space. Initialization, which is used to set the population number, dimension of the optimization variables, and matrix simulating black eagle position. And judging, wherein the judging is used for judging the relation among the current iteration times, the maximum iteration times and the times of stopping updating, and executing corresponding updating steps according to the judging result.

In the invention, as for the performance index, the BEO algorithm is adopted to carry out iterative optimization, and the optimal solution is searched in a large-range iterative space.

Initializing:

Firstly, setting the population quantity as the dimension of the variable to be optimized as ,,Is a black eagle population matrix:

Wherein:

Representing different black eagle individuals to be optimized;

For each column of the population matrix, namely different black eagle individuals;

Is the upper bound of the optimization variables;

is the lower bound of the optimization variable;

A column vector with dimension 3, and the element is a random value of 0 to 1;

the fitness value of the individual;

In the present invention, 。

Tracking:

Wherein:

Is the first Secondary auxiliary tracking population matrix;

Is the firstSub-tracking population matrix;

Is the firstSub-tracking population matrix;

Is a random location in the search space;

Is the first Random locations in the secondary search space;

a location that is a random individual;

Is the first Sub-random individual location;

is the current best solution set;

Is the first Optimal solution of the secondary iteration;

Is that The furthest distance from the search boundary;

The iteration times;

A random number of 0 to 1;

a random number between 0 and 1 generated by (tent map);

The auxiliary function is updated for tracking.

Calculating candidate solutions and fitness values as by trackingAnd temporarily record it as the current best fit value。

Wherein:

;

for any input quantity Generation of corresponding from tent map。

And (5) coiling:

;

Wherein:

a 3-dimensional spiral matrix;

is the spiral angle;

Is a random number of 0 to 1.

Calculating candidate solutions and fitness values as by' coilingAnd replaced by smaller fitness values thereinAnd record the candidate solution set.

The role of the "hover" operation is to perform a rotational search to further refine the range of globally optimal locations. The "hover" strategy performs a rotational search within a globally optimal location range initially determined by the tracking strategy.

Capturing:

is an auxiliary matrix;

Is the first Secondary capture updates the auxiliary matrix;

is a position adjustment factor of 1;

is a position adjustment factor of 2;

For a column vector of dimension 3, the elements are between 0.5 and 1.

Calculating candidate solutions and fitness values as by' capturingAnd replaced by smaller fitness values thereinAnd record the candidate solution set.

Robbing:

;

Wherein, The values of the elements of each dimension are subjected to normal distribution as random vectors with the dimension of 3.

Calculating candidate solution and fitness value as by' robbingAnd replaced by smaller fitness values thereinAnd record the candidate solution set.

The "robbing" behavior is reduced to a black eagle flying from one point curve to another, and then the jumping motion of the points is used to simulate the robbing behavior of the black eagle. The "robbery" strategy is a jump search method that aims to perform a jump search on the position adjusted by the previous strategy to increase the probability of finding the globally optimal position.

Warning:

Wherein:

Is the first In dimensional spaceA distance from a search space center;

To be minimum ;

Is at maximum;

Is a weighted displacement;

Is that According to the approachA position matrix after rearrangement of the order of (a);

Is the first Updating the auxiliary matrix by the secondary warning;

Is a boundary auxiliary function;

is a first sinusoidal auxiliary function;

Is a second sinusoidal auxiliary function;

Represent the first Line 1A column;

is a probability density function of poisson distribution.

Calculating candidate solutions and fitness values as by' warningAnd replaced by smaller fitness values thereinAnd record the candidate solution set.

"Warning" uses poisson distribution to guide particle movement, generating newTo replace solutions that exceed the search boundaries.

And (3) migration:

Wherein:

Is an auxiliary migration function;

the current best fit value;

Is the first An adaptation value for the individual;

for a column vector of dimension 3, the elements are between-1 and 1;

A random number from 0.4 to 1 formed by tent map;

is constant.

Calculating candidate solutions and fitness values as by migrationAnd replaced by smaller fitness values thereinAnd record the candidate solution set.

"Migration" uses fitness function value to represent the fitness of black eagle to environment, and constructs migration functionThe migration rule is further comprehensively simulated, namely, the migration distance is further the lower the fitness is. The migration mechanism aims to migrate individuals with low fitness to a location far from the current optimal location to reduce the likelihood of getting trapped in a local optimum.

And (3) puppet:

Wherein:

Is the first Updating the auxiliary matrix by secondary coupling;

Is the first Updating the auxiliary matrix by secondary coupling;

the function expression of the step factor is from the deformation of the Sigmoid function;

And A random number of 0 to 1;

And The element of the column vector is a column vector with the dimension of 3 and obeys normal distribution;

the maximum iteration number;

Representation of Dividing by 2 takes the remainder, for example: Representation of Dividing by 2 to obtain remainder 1, i.e. representingOdd.

Calculating candidate solutions and fitness values as by' couplingAnd replaced by smaller fitness values thereinAnd record the candidate solution set.

The 'puppet' simulates the interaction behavior of the male and female hawks in the puppet process by using similar fluctuation between sine and cosine functions and an alternating mode between odd numbers and even numbers.

Hatching:

Wherein:

is a group of normally distributed arrays;

Is a group position matrix obtained by rearranging group positions from nearest to farthest from nest 。

Calculating candidate solution and fitness value as by hatchingAnd replaced by smaller fitness values thereinAnd record the candidate solution set.

"Hatching" simulates, according to a normal distribution, the situation in which a male black eagle is more active near the nest and less active farther away during hatching due to the conservation of female black eagle hatching. Hatching strategy is a diffusion search method that allows some individuals to continue to approach the current optimum while others diffuse outward, thereby preventing sinking into the local optimum.

The BEO algorithm flow is initialized at the beginning, sets up the matrix of population quantity, dimension of optimized variable and simulated black eagle position, sets upFor the maximum number of iterations to be performed,Is the number of black eagle individuals,After initialization, the fitness value of the population is estimated by tracking, and the current optimal solution is found outAnd temporarily record it as the current best fit valueJudgingIf the search boundary is reached, executing a warning step to generate a new candidate solution current best fit valueInstead of the out-of-bounds solution, if not, performing the "hover", "capture", "rob" steps to update the current best-fit valueJudging the current iteration timesMaximum number of iterationsNumber of times update is stoppedWhether the relationship between them satisfies: if yes, executing a migration step to update the current best-fit value If not, executing the steps of 'coupling' and 'hatching' to update the current best-fit valueAfter finishing the cycle, updating the current best-fit value in the step of executing migrationThen, judging whether the following conditions are satisfied: if yes, executing the steps of 'coupling' and 'hatching' to update the current best fit value And if the cycle is not satisfied, the cycle is restarted after the initialization is skipped.

Ending the BEO algorithm flow, finishing iteration, and obtaining the optimal solution by the BEO algorithmSequentially judging whether the optimal solution meetsAndRemoving the optimal solution which does not meet the above formula and leaving the solution which meets the constraint, if the optimal solution is finally obtainedMore than one group is obtained, namely, a group of optimal solution sets are obtained, and the solution sets meeting the performance index are obtainedThe smallest solution is taken as the optimal solution, wherein:

the equivalent resistance of the motor is represented and is a parameter of the motor;

The performance index of the consumed power of the motor, namely the economical index is expressed.

The invention develops an electric automobile steering motor control optimization method considering communication delay, in the traditional motor steering process, the signal delay phenomenon between a controller and an actuator is usually ignored, thereby bringing the defect of reduced steering precision, or a more redundant multi-degree-of-freedom model is built, so that the over-constraint phenomenon exists in the model, the controller is more complex, and the phenomenon of overlong processing time is easy to occur when the complex problem is processed. The method is based on the traditional three-closed-loop PID, a delay observer is introduced at an actuator end, signal delay is monitored and processed in real time, control accuracy of a steering motor is effectively improved, a feedforward and feedback self-adaptive robust sliding mode control method is adopted, various interference factors are overcome, robustness and stability of a system are remarkably improved, BEO algorithm is utilized for parameter optimization, optimality of controller setting parameters is guaranteed, control performance is further improved, a designed controller model is simple and efficient, processing speed of the controller is improved, and complexity of the system is reduced.

Although embodiments of the present invention have been disclosed above, it is not limited to the details and embodiments shown and described, it is well suited to various fields of use for which the invention would be readily apparent to those skilled in the art, and accordingly, the invention is not limited to the specific details and illustrations shown and described herein, without departing from the general concepts defined in the claims and their equivalents.

Claims (8)

1. The electric automobile steering motor control optimization method taking communication delay into consideration is characterized by comprising the following steps of:

acquiring an expected value of a motor steering angle, and acquiring an expected value of a steering angular speed and a steering angular acceleration of the motor according to the expected value of the motor steering angle;

inputting expected values of steering angle, steering angular speed and steering angular acceleration of the motor into a feedforward control module, wherein the feedforward control module outputs feedforward control quantity signals;

Acquiring a motor operation signal through a motor sensor, and inputting the motor operation signal into a delay observer, wherein the delay observer outputs observed values of a steering angle, a steering angular speed and a steering angular acceleration with delay;

The method comprises the steps of inputting expected values and observed values of steering angles, steering angular speeds and steering angular accelerations of the motor into a switching function module and a feedback control module, wherein signals output by the switching function module are input into an exogenous interference module;

inputting signals output by the delay observer, the switching function module and the exogenous interference module into the feedback control module, and outputting feedback control quantity signals by the feedback control module;

and adding the feedforward control quantity and the feedback control quantity to obtain a current expected value.

2. The optimization method for controlling the steering motor of the electric vehicle taking the communication delay into consideration as set forth in claim 1, wherein the feedback control module obtains the feedback control amount signal by the following formula:

;

Wherein: Is a feedback control quantity signal; the motor moment of inertia is from a motor sensor; Is the friction viscosity coefficient; a motor torque coefficient; Is a switching function; Error between observed value and expected value of motor steering angle; Is that Is a derivative of (2); As defined auxiliary variables; the coefficients of the switching function in the speed loop controller and the parameters to be optimized; Defining coefficients in the process for auxiliary variables in the speed loop controller and as parameters to be optimized; The sliding mode term coefficient in the speed loop controller is the parameter to be optimized; Is a switching term coefficient; perturbation and exogenous interference for motor parameters; For motor parameter perturbation and exogenous interference Is a function of the estimated value of (2); is a sign function; Is an optimization function; , for the motor steering angle and the motor steering angular velocity observations output by the delay observer, Is thatIs a component of (1); is the steering angle of the motor and is used for controlling the motor to rotate, from a motor sensor; To be about Is a function of (2); The steering angular speed of the motor; To be about Is a function of (2); The steering angular speed of the motor; , for a given desired value of motor steering angle and motor steering angular speed, from the demand of the driver while driving, Is thatIs included in the (a) and (b) is included in the (b) component.

3. The method for optimizing control of an electric vehicle steering motor taking into account communication delay according to claim 2, further comprising optimizing the feedback control module:

Establishing a performance index and an error function:

;

Wherein: Is a performance index; Is an error function; Is a delay-free time; Is the expected value of the steering angle of the motor; Is the expected value of the steering angular speed of the motor;

The constraint conditions are as follows:

Wherein: is an auxiliary matrix;

With minimum performance index as optimization target, for parameters 、AndOptimizing to obtain optimal parameters、AndTo adjust the feedback control quantity signal。

4. The optimization method for controlling the steering motor of the electric automobile taking the communication delay into consideration as set forth in claim 2, wherein the calculation formula of the switching function is:

。

5. the optimization method for controlling the steering motor of the electric automobile considering communication delay according to claim 4, wherein the self-adaptive law is adopted to estimate the external interference:

Wherein: Is that Is a derivative of (2); Coefficients are estimated for adaptation.

6. The optimization method of electric vehicle steering motor control taking communication delay into consideration according to claim 2, wherein the feedforward control module obtains the feedforward control amount signal by the following formula:

Wherein: Is a feedforward control quantity signal; for steering motor load torque, from a motor sensor; , for a given desired value of motor steering angular velocity and motor steering angular acceleration, the motor steering angular velocity and motor steering angular acceleration are calculated from the requirements of the driver while driving, Is thatIs a component of (1); is the desired value of the motor steering angular acceleration.

7. The method for optimizing control of an electric vehicle steering motor taking into account communication delay according to claim 6, wherein the delay observer state space expression is designed as:

;

Wherein: , For the observed values of the motor steering angular velocity and the motor steering angular acceleration output by the delay observer, Is thatIs a component of (1); A coefficient matrix that is a state space expression of the delay observer; Is an output matrix; Is an observer gain matrix; is a constant; To output a delay signal; The steering angle value with time delay is fed back to the motor encoder; is a time-varying delay time; Is an observed quantity of the delay signal; Output torque for the motor from the motor sensor; Is the motor control quantity.

8. The optimization method for controlling a steering motor of an electric vehicle in consideration of communication delay according to claim 7, wherein a state space equation of a delay observer with respect to a speed loop controller is:

;

Wherein: a coefficient matrix of a state space equation of the speed loop controller; Is a control amount; Is the current expected value.