Multi-objective optimization of the suspension system parameters of a full vehicle model

The development of a methodology that enables the optimization of passive suspension system parameters, providing a group of optimal solutions, could be an excellent approach to obtain a fast improvement tool during the design of suspension systems. Thus, this paper proposes a methodology for the multi-objective optimization of the passive suspension system of a full-car model travelling in a random road profile. For this purpose, a numerical-computational routine is developed, which integrates the NSGA-II with the vertical dynamic analysis, in the time domain, of an eight degrees-of-freedom vehicle model with a seat. Three objective functions, which take into account passenger comfort and safety, are considered. The proposed methodology provides a Pareto-optimal front, which consists of a set of non-dominated solutions that minimize the three objective functions. Comparing the results of the dynamic analyses of the vehicle model with optimized and non-optimized suspension systems, it was verified that the optimization allowed a reduction of up to 21.14% of the weighted RMS value of the driver seat vertical acceleration, a parameter directly related to comfort, while maintaining or improving the trade-off with safety. The Pareto-optimal front has proven to be an excellent support tool to aid the designer in the determination of the parameters that best fit the suspension system to produce the desired dynamic behavior in vehicles. Thus, the proposed optimization methodology can be recommended as an effective tool for the optimal design of passive suspension system parameters. Finally, this work shows that the design of suspension parameters can be done taking into account passenger comfort and safety at same time.