Parameter optimization of commercial vehicle suspension system based on sensitivity analysis
WANG Gengzhi1， WANG Tao1， ZOU Xiaojun2，3， YUAN Liukai3， WANG Liangmo1
1. School of Mechanical Engineering， Nanjing University of Science and Technology， Nanjing， Jiangsu 210014， China； 2. School of Mechanical Engineering， Southeast University， Nanjing， Jiangsu 211189， China； 3. Nanjing Iveco Automobile Co., Ltd.， Nanjing， Jiangsu 210028， China
Abstract：To improve the ride comfort of commercial vehicle, the parameters of the suspension system of commercial vehicle were optimized. Based on the actual test data of the air spring, the stiffness characteristic curve was fitted, and the multi-body dynamic model of the front and rear suspension and the entire vehicle was established. The smoothness of the vehicle under random input and pulse input conditions was simulated. The parametric multi-platform co-simulation model of the suspension system was built, and the degree of influence of the design parameters of the suspension system on ride comfort was obtained through the global sensitivity analysis. The multi-objective response surface approximation model for vehicle ride comfort was established, and the multi-objective genetic optimization algorithm was used to optimize the parameters in the feasible region. The results show that under the random input conditions, the root mean square(RMS) values of the weighted acceleration at the driver and passenger positions are respectively reduced by 12.50% and 29.71% when the vehicle speed is 100 km/h. Under pulse input conditions, the maximum vertical accelerations at the driver and passenger positions are respectively reduced by 14.69% and 31.28% when the vehicle speeds are respective 20 km/h and 30 km/h, and the optimization effect is obvious.
王耿之1， 王陶1， 邹小俊2,3， 袁刘凯3， 王良模1. 基于灵敏度分析的某商用车悬架系统参数优化[J]. 江苏大学学报（自然科学版）, 2024, 45(5): 528-534.
WANG Gengzhi1， WANG Tao1， ZOU Xiaojun2，3， YUAN Liukai3， WANG Liangmo1. Parameter optimization of commercial vehicle suspension system based on sensitivity analysis[J]. Journal of Jiangsu University(Natural Science Eidtion)
, 2024, 45(5): 528-534.
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2024, Vol. 45 
