CN-116674334-B - Suspension control system and control method thereof

CN116674334BCN 116674334 BCN116674334 BCN 116674334BCN-116674334-B

Abstract

The invention discloses a suspension control system and a control method thereof, wherein the suspension control system comprises a suspension system, a fuzzy self-adaptive PID controller, a magneto-rheological damping force limiter, a magneto-rheological damper controller and an inertial coefficient adjusting unit, and an inertial container is a variable inertial container; the sprung mass acceleration sensor transmits a signal to the fuzzy controller to obtain a target damping force, the target damping force is input to the magnetorheological damper controller after passing through the magnetorheological damping force limiter, the magnetorheological damper controller provides an actual damping force for the suspension system, and the optimal inertial capacity coefficient under the current road surface condition is obtained by weighting the unsprung mass acceleration x t ', the displacement x t -x b 、x b -x r and the actual damping force through designing the optimal controller. The system and the method can convert the resonance of the wheels into the resonance of the inertial container, the control method is favorable for independently controlling the inertial coefficient under different road conditions, and can perform combined control with the magnetorheological damper to adjust parameters in real time, so that the comprehensive performance of the all-road-condition system is optimal.

Inventors

WANG RUOCHEN
SU ZHAORUI
JIANG YU
DING RENKAI
TANG JIAJIA
Shi Xuhuan

Assignees

江苏大学

Dates

Publication Date: 20260512
Application Date: 20230605

Claims (6)

1. A suspension control system, comprising The suspension system comprises an inertial container (6), a spring (7) and a damper (8) which are connected in parallel between the unsprung mass (5) and the equivalent spring (9) of the tire, and a suspension spring (2), a zero magnetic field damper (3) and a magnetorheological damper (4) which are connected in parallel between the unsprung mass (5) and the sprung mass (1), wherein the inertial container (6) is a variable inertial container; The fuzzy self-adaptive PID controller receives the vehicle body vertical vibration acceleration on the sprung mass in the suspension system, and the fuzzy self-adaptive PID controller is internally matched with the vehicle body vertical vibration acceleration on the sprung mass in the suspension system 、、 The 3 parameters are subjected to real-time nonlinear regulation to calculate the expected damping force, and the self-adjusting formulas of the 3 parameters in the fuzzy self-adaptive PID controller are respectively expressed as follows: ; Wherein, the 、、 Parameters of the fuzzy self-adaptive PID controller; 、、 Parameters of a standard PID controller; 、、 the adjustment quantity of the PID controller; 、、 The correction coefficient is the correction coefficient of the fuzzy self-adaptive PID controller; to error the state of a suspension system And rate of change of state error As input to a fuzzy adaptive PID controller; consider a standard PID controller 、、 The mutual influence and restriction relation among the 3 parameters correspond to different state errors e and the change rates ec of the state errors, so the PID controller parameter setting principle is as follows: If it is Illustrating that the system state error changes in a direction of increasing to an absolute value; If it is Illustrating the change in error in the direction of decreasing absolute value, When (1) Is greater than A kind of electronic device And (2) and When (1) The value is also smaller than When (1) The value, while avoiding major overshoot in the system response in order to prevent differential saturation, should the differential effect be removed, i.e ; The 2 input quantities in the fuzzy self-adaptive PID controller are described by 7 fuzzy language subsets, namely negative large NB, negative medium NM, negative small NS, zero ZO, positive small PS, medium PM and positive large PB, meanwhile, the 3 output quantities of the fuzzy controller are also described by 7 fuzzy language subsets, namely negative large NB, negative medium NM, negative small NS, zero ZO, positive small PS, medium PM and positive large PB, and the basic domain is normalized interval [ -1,1]; The magnetorheological damping force limiter receives the expected damping force output by the fuzzy self-adaptive PID controller, and limits the damping force in the magnetorheological damping force limiter to output the limited expected damping force; a magnetorheological damper controller which outputs an actual damping force to a magnetorheological damper (4) of the suspension system according to the limited desired damping force; The inertial coefficient adjusting unit comprises a road condition identifying unit and an optimal controller, wherein the road condition identifying unit is used for acquiring unsprung mass acceleration Displacement of 、 , In order for the unsprung mass to be displaced, For the displacement of the inertial container, For road surface excitation, optimal controller acquisition 、、 And the actual damping force, and to 、、 And the squares of the 4 parameters of the actual damping force are weighted to obtain the optimal inertial capacity coefficient under the current road surface condition, and the optimal inertial capacity coefficient is transmitted to the inertial container to realize the adjustment of the inertial capacity coefficient of the inertial container.
2. Suspension control system according to claim 1, characterized in that the chambers on both sides of the inertial container (6) are respectively connected with the hydraulic motor (10) through a superposition type hydraulic control one-way valve (13), 2 hydraulic conveying branches provided with the superposition type hydraulic control one-way valve (13) are respectively provided with a superposition type double one-way throttle valve (12), and a proportional valve (11) is connected between the 2 hydraulic conveying branches.
3. A suspension control system as claimed in claim 1 wherein the control of the magnetorheological damper controller is an integral-split PI algorithm.
4. The suspension control system of claim 1, wherein establishing the performance index of the LQR controller is: ; Wherein, the Respectively is 、、 And a weighting coefficient corresponding to the actual damping force; Is composed of The diagonal matrix is constructed, expressed as , For system input, y is the model state space, The actual damping force is output by the magneto-rheological damper.
5. The suspension control system according to claim 4, wherein in the optimal control law design, the model state space of the ISD semi-active suspension with variable inertia is calculated Substituting the performance index of the LQR controller is expanded into: ; wherein the weighting matrix of the state variables For semi-positive definite symmetrical constant matrix, control input weighting matrix Cross terms For positive symmetry constant, the optimal control law is: ; the feedback gain matrix is expressed as: , for the solution of the Riccati equation, P satisfies the Riccati equation: ; And obtaining an optimal feedback gain matrix K by using an LQR function provided by Matlab software, so as to obtain an optimal inertial capacity coefficient A, B, C, D serving as a matrix.
6. A suspension control method characterized by comprising the steps of: step 1, constructing a suspension control system according to claim 1; step 2, based on the suspension system in the suspension control system in step 1, collecting the vertical vibration acceleration and the unsprung mass acceleration of the vehicle body from the suspension system Displacement of 、 , In order for the unsprung mass to be displaced, For the displacement of the inertial container, Exciting the road surface; Step 3, the fuzzy self-adaptive PID controller outputs expected damping force based on the vertical vibration acceleration of the vehicle body, the magnetorheological damping force limiter limits the expected damping force and inputs the limited expected damping force into the magnetorheological damper controller, and the magnetorheological damper controller outputs actual damping force to the magnetorheological damper (4) of the suspension system according to the limited expected damping force to realize the adjustment of damping force in the suspension system; Step 4, the inertia capacity coefficient adjusting unit is based on 、、 And the actual damping force, and to 、、 And weighting squares of the 4 parameters of the actual damping force to obtain an optimal inertial coefficient under the current road surface condition, and transmitting the optimal inertial coefficient to the inertial container to realize adjustment of the inertial coefficient of the inertial container.

Description

Suspension control system and control method thereof Technical Field The invention belongs to the field of vehicle vibration control, and particularly relates to a suspension control system and a control method thereof. Background The suspension system is an important component of the vehicle and can transmit vertical acting force which is introduced from the road surface and acts between the vehicle body and the wheels, so as to attenuate the vibration of the vehicle body caused by road surface excitation. Suspension systems are classified into passive suspensions, semi-active suspensions, and active suspensions according to whether damping and stiffness vary with a change in running conditions. The passive suspension is not adjustable in spring stiffness and damping coefficient of the shock absorber, cannot be changed along with the external road conditions, and is difficult to adapt to different road conditions, so that the shock absorbing performance is limited. In addition, conventional passive suspensions dissipate vehicle vibration energy in the form of thermal energy, resulting in a significant amount of energy waste. The active suspension can output control force in real time according to road conditions, but energy is required to be provided externally, so that energy consumption is huge. Although the semi-active suspension can not output damping force in real time, the damping or rigidity can be adjusted in real time, so that the energy consumption is greatly reduced. The typical representative of the semi-active suspension is a magneto-rheological semi-active suspension, which has simple structure and convenient control, and the combination of vibration energy recovery and magneto-rheological damper technology can reduce the energy consumption to the greatest extent and improve the vehicle dynamics performance. The main control algorithms of the current vehicle suspension comprise a control algorithm based on vehicle state judgment, a control algorithm based on a classical control theory, a control algorithm based on an optimal control theory and a control algorithm based on an intelligent optimization theory. The most common control strategies are fuzzy control, sliding mode variable structure control, ceiling, ground and canopy, derivative control, optimal control and the like. And (3) listing a performance functional according to a control target by linear quadratic form optimal control (LQR) in optimal control, and then solving an optimal control quantity by adopting a variation theory so as to minimize the functional value. The fuzzy control can effectively solve the problem of multi-parameter nonlinearity of the semi-active system, and has good robustness and strong universality. The problem of suppressing the negative effect of the vertical vibration of the automobile belongs to a vehicle suspension system, and the lack of an effective inertial element in a traditional suspension spring-damper structure restricts the improvement of the integrity of the suspension. Although inertial containers are introduced into a vehicle suspension in the prior art to form an inertial container-spring-damper dynamic inertial suspension structure system, how to realize active adjustment of hydraulic inertial Rong Li of the inertial container through a basic ideal inertial container model and how to achieve ideal smoothness and comfort effects on inertial container-spring-damper dynamic inertial suspension control is a current technical problem. Disclosure of Invention The application provides a suspension control system and a control method thereof, which aim to solve the defects in the prior art, wherein the system can independently control an inertial container with variable inertial capacity when road conditions are changed, and can also carry out combined control with a magneto-rheological damper, a sprung mass acceleration sensor transmits signals to a fuzzy controller to obtain expected damping force, the expected damping force is input to the magneto-rheological damper controller after passing through a magneto-rheological damping force limiter, the magneto-rheological damper controller provides actual damping force for the suspension system, and the optimal controller of the suspension system is designed, wherein the control target is that the sum of the square of four parameters of the output variable non-sprung mass acceleration, displacement and the magneto-rheological damper control force of the system is minimum according to a certain weight, and the optimal inertial capacity coefficient under the current road conditions is obtained and is transmitted to the inertial container. The suspension system designed by the application can convert wheel resonance into resonance of the inertial container, and the control method is favorable for independently controlling the inertial coefficient under different road conditions, and can perform combined control with the magnetorheological damper to reali