Abstract。 A multi-body dynamic model of the suspension system was built in this paper。 The vibration displacement of wheel center on running pavement was obtained by experiment and applied it into the multi-body dynamic model to simulate actual operation conditions。 Then, vibration acceleration of suspension axle was extracted and compared with the experimental result。 The dynamic load acting on the suspension jounce bumper was acquired by the multi-body dynamic model and applied to the finite element model of the jounce bumper。 Then, the stress in the loading position was computed and imported into NASTRAN to conduct fatigue durability analysis of the jounce bumper。 Afterwards, the dynamic characteristic and fatigue life of the jounce bumper were optimized based on the improved genetic algorithm。 Finally, vibration isolation ratios of the suspension system before and after optimization were compared to verify optimization effect。 In this way, the suspension system has a better dynamic characteristics and higher fatigue life。76212

Keywords: suspension system, multi-body dynamic model, dynamic characteristics, improved genetic algorithm, fatigue life。

1。 Introduction

As the elastic connecting link in a vehicle structure, suspension was a complicated mechanical system, which was composed of numerous parts。 It directly affected the ride comfort and operation stability of the vehicle。 While the running speed of the vehicle increased, the requirements for ride comfort and operation stability of vehicles was increasingly high。 The dynamic study on the suspension system has attracted wide attention [1]。 Macpherson suspension creatively combined shock absorber with helical spring together, and they were mounted on the front axle。 This suspension had a simple structure, less occupation space and good maneuverability。 Therefore, it was widely used in the front axle of vehicles。 The multi-link suspension had a compact structure, and its wheel occupied a relatively small area of the body [2]。 As a result, it made the rear space of vehicle larger。 In addition, it had good maneuverability and stability。 However, it was usually used on the rear axle of the luxury vehicle。

However, there were also defects in the Macpherson suspension which was widely used。 It can’t provide enough support to the lateral force。 Therefore, once the vehicle was making a turn, it will have a roll easily。 As a result, it was necessary to re-design the dynamic characteristic of the suspension based on this problem。论文网

The vehicle designers have taken suspension optimization design as one of the key issues。 Currently, optimization design of suspension is pided into two types。 One type aims at realizing optimization via programming。 The other type realizes optimize by virtual prototyping platform。 The former one is tedious and complicated to operate, wherein elastoplasticity of the components is often neglected。 The latter is convenient to operate。 Pan [3] combined the least square method with the optimal control method to optimize Macpherson suspension, but they failed to consider the roll。 The dynamic characteristics of Macpherson suspension were evaluated by Beale。 However, during building the simulation model, the suspension was seemed as a rigid body, which was not consistent with the actual situation。 Sancibrian optimized the kinematics of the suspension system by the multi-objective optimization algorithm, but the process had not been verified by experiments。 Therefore, the final results may not be accurate。 Chen [4] applied genetic algorithm

in optimization for five-link suspension to analyze the kinematic characteristics of the wheel camber during the bouncing process of the wheels。 However, the optimization of five-link suspension system is mainly single object optimization at present。 In the above researches, fatigue life of suspension is not considered comprehensively and several major parameters cannot be harmonized very well。 In addition, most optimization process is not verified through experiments, and the roll of Macpherson suspension was still not improved。