Study On Intelligent Suspension Control Algorithm

The active suspension can adapt to different road excitation by adjusting its own stiffness or damping,which effectively improves the ride comfort and handling stability of the vehicle.However,the active control of the suspension needs to consume a lot of energy.In order to reduce the energy consumption,the energy-regenerative suspension is applied.By recovering the energy dissipated in the vibration process of the suspension,the energy loss is reduced.On the basis of energy-regenerative active suspension,in order to meet the diversity of suspension performance requirements of vehicle users under different working conditions,this paper designed an intelligent suspension system to provide users with multiple functional modules of suspension.On the basis of the basic performance of the suspension achieved by the required modules,optional modules such as active control modules,energy-regenerative module and intelligent service modules were added,among which the active control modules include safety module,comfort module and comprehensiveness module.For the energy-regenerative module and active control modules,a multi-threshold module switching control strategy was designed based on the top-level control,and the corresponding functional modules were allocated for the suspension under different working conditions and the bottom controllers were designed.For the energy-regenerative module,the average recovery power of the suspension under different conditions was calculated.As the road condition deteriorates or the vehicle speed increases,the recovery power of the suspension increases.Therefore,in order to avoid conflicts with functional modules under other working conditions,it is effective to select the energy recovery of the suspension in the case of class A road surface with a high vehicle speed.For the safety module,the fuzzy control algorithm was used to design the safety controller with the tire dynamic displacement as the optimization target.The improvement effect of each performance indicator of the suspension at different speeds under class B road surface was analyzed.The simulation results show that the safety controller can effectively improve the driving safety;and the comprehensive performance of the vehicle can be further improved by increasing the speed appropriately.For the comfort module,the PID control algorithm combined with BP neural network algorithm was used to design the comfort controller with the body acceleration as the optimization target.The improvement effect of each performance indicator of the suspension at different speeds under the class C road surface was analyzed.The simulation results show that the comfort controller can significantly improve the ride comfort,and the control effect is better than that of a single PID controller.Moreover,the improvement effect of ride comfort can be better by increasing the speed appropriately.For the comprehensiveness module,the random optimal control algorithm was used to design the comprehensiveness controller with the body acceleration and tire dynamic displacement as the optimization targets.The weight coefficients of the controller were determined by the analytic hierarchy process(AHP)combined with genetic algorithm(GA).The improvement effect of each performance indicator of the suspension at a fixed vehicle speed under the class D road surface was analyzed.The simulation results show that the comprehensiveness controller can effectively improve the comprehensive performance of the vehicle,and the control effect of the compound algorithm is better than that of the single analytic hierarchy process in determining the weight coefficients.Through the design of the top-level module switching strategy and the bottom controller,the distribution of the intelligent suspension function modules is realized,the adaptability of the vehicle to the driving condition is improved,and the vibration energy of the suspension can be recovered while the vehicle performance is improved.