Research On Optimization Of Vehicle Suspension Parameters Based On Ride Comfort

With the improvement of people’s living standards,the requirements for car smoothness are also constantly increasing.Therefore,many experts and scholars have tried different methods to improve car smoothness and have achieved many excellent results.The vibration of a car is mainly caused by the unevenness of the road surface,and the suspension is the connecting device between the body and tires,thus playing a significant role in the smoothness of the car.The performance of suspension is determined by its form and parameters,namely the size of suspension stiffness and damping,as well as their matching.Therefore,after the form of suspension is determined,optimization methods can be used to optimize its design and select more suitable parameters to improve the driving smoothness of the car.This article uses the cuckoo bird search algorithm to optimize the parameters of the suspension,providing a new method for the study of vehicle ride comfort.The main research content includes the following aspects.Firstly,based on the theoretical requirements of vehicle ride comfort,the random road excitation model and the evaluation method of vehicle ride comfort are introduced.The random road excitation model is established by using the filtered white noise method,and the time domain simulation of the random road under the uniform speed condition is carried out.Based on the Mac Pherson independent suspension vehicle,an eight degree of freedom semi vehicle mechanical model and corresponding mathematical model were established,and the model was simulated in the time domain to lay a foundation for subsequent simulations.Secondly,based on the degree of influence of vehicle suspension related parameters on driving smoothness,the stiffness and damping of the suspension are selected as design variables,and the objective function is determined using the root mean square values of suspension dynamic deflection,vehicle acceleration,and tire dynamic load as evaluation indicators.The three evaluation indicators are given the same weight,and the established road excitation model and vehicle model are optimized using the cuckoo search algorithm,A comparative analysis of the results before and after optimization was conducted in both time and frequency domains.The results showed that after optimization by the cuckoo search algorithm,the values of each response quantity of the automotive vibration system were reduced to varying degrees,indicating that the cuckoo search algorithm played a role in weakening automotive vibration and improving the smoothness of the vehicle.Finally,by adjusting the weights of each evaluation indicator in the objective function,three different weight combinations were manually adjusted in this article,and the group with better optimization results was selected for analysis in both time-domain and frequency-domain aspects.A comparative analysis was conducted in both time-domain and frequency-domain aspects with the same weights.The results show that under the adjusted weight,the values of each response quantity in the vehicle vibration system have decreased to a certain extent,indicating that the driving smoothness of the vehicle has been further improved after the weight adjustment.