Optimization And Research Of Vehicle Suspension Parameters Based On Approximate Model

On the basis of considering the handling stability, in order to improve the ride comfort of the car, the vehicle’s suspension system was optimized by the multi-objective optimization method, then make the vehicle’s ride comfort improved under the condition of guaranteeing the handling stability. At the same time, through a series of research methods and means, providing a new train of thought of suspension optimum design, providing a beneficial reference of the research in this field. The concrete research methods and content of this article includes:Firstly, according to the current international and domestic standards and research achievements of predecessors, a summary about the testing methods and evaluation indicators of handling stability and ride comfort were made. Weighing the test methods and evaluation indicators, a set of suitable evaluation indicators were put forward.Secondly, according to the relevant data of the vehicle, by using multi-body dynamics software ADAMS/CAR, a accurate vehicle rigid-flexible coupled model was established. Specially, in order to evaluate the vibration effects on human comfort and health, driver and seat model were established.Then, according to the evaluation method in this paper, for handling stability, a double lane change test was made, for ride comfort, random input simulation and pulse input test were carried out. In particular, the comprehensive evaluation about ride comfort was carried out.Using the characteristic parameters of suspension system (suspension spring stiffness and shock absorber damping) as the experimental factor, the handling stability and ride comfort evaluation indicators as the output response. The design of experiment of system’s input and output were carried out by using Opt LHD, LHD, Orthogonal Arrays, CCD, Box-Behnken respectively. The five kinds of experimental design methods were compared, the Opt LHD’s design superiority was proved.On the basis of experimental design, the input and output’s approximate model of the system were built by using RSM, RBF neural netword and Kriging separately. Through the modeling error analysis, proving that the Kring model’s modeling accuracy was the best one. So in this article, using Kring method as the approximate modeling method.Based on the Kring model, in order to improve the vehicle’s ride comfort, handing stability was considered simultaneously, using multi-objective particle swarm optimization algorithm, using r.m.s. value of weighted body acceleration, the suspension dynamic deflection and dynamic tyre load as optimization objectives, suspension spring stiffness and shock absorber damping as the design variables, the suspension system was optimized.Finally, through comparison of optimized and un-optimized, the results show that: while ensured the handling stability, one of the ride comfort indicators, r.m.s. value of weighted body acceleration dropped9%on average at different speeds, were significantly improved. At the same time, the suspension dynamic deflection was optimized to a reasonable range. These verified the effectiveness of the suspension optimization.