Research On Vehicle Active Suspension Control Method Based On Intelligent Optimization Algorithm

With the development of social economy and science and technology,the performance of automobiles has been paid more and more attention as well as basically meeting the needs of people.As an important part of vehicle,suspension directly affects vehicle ride comfort and control stability.Compared with the traditional passive suspension and semi-active suspension,active suspension can actively adjust and change the required control output force according to the current road conditions and the state of the vehicle driving,taking into account the driving safety and ride comfort,and it is an important direction of the development of the suspension industry.In this paper,the key problem in the design of active suspension,that is,the control strategy,is studied.Based on the classic PID control and fuzzy control,the intelligent optimization algorithm is used to optimize the controller parameters to improve the ride comfort of the vehicle and ensure its safety performance.The following contents are mainly included:(1)According to the dynamic characteristics,the mathematical model of the two degree of freedom 1/4 automobile active suspension system is established;a random road and impact type road surface models are established based on the research needs;the performance of evaluation index of the active suspension system is given according to the suspension control target.(2)PID controller based on particle swarm optimization(PSO)algorithm and teaching-learning-based optimization(TLBO)algorithm are designed.On the basis of traditional TLBO,an improved teaching-learning-based optimization(MTLBO)algorithm is proposed by improving teaching factors and introducing reverse learning technology.Simulation results demonstrate the effectiveness of the PID controller based on the PSO and TLBO algorithm,and also prove the superiority of the TLBO algorithm in the control effect and time consuming of the active suspension.(3)Based on the traditional fuzzy control,the TLBO algorithm is used to optimize the membership function parameters,and then the fuzzy controller of active suspension based on TLBO algorithm is designed.The effectiveness of the designed controller is verified by the simulation results compared with the traditional fuzzy control and fuzzy control based on genetic algorithm(GA).(4)Considering the characteristics of the TLBO algorithm and the adaptive neuro fuzzy inference system(ANFIS),an active suspension ANFIS control method based on TLBO algorithm is proposed.The simulation results show that this control method can effectively improve the ride comfort of the vehicle,and it also has strong robustness for different types of road excitation.