Evolutionary algorithms for passive suspension systems

This paper presents the evolutionary algorithms (EAs) to determine a set of optimum system parameters for the passive suspension system (PSS) so that the best performance of the system can be achieved. The selected fitness fu nctions are chosen according to the analysis of desired performance includi ng sprung mass acceleration (SMA), suspension deflection (SD) and tire defl ection (TD) in the frequency domain. Besides, we compare the evolution proc esses and search results of genetic algorithms (GAs) and evolutionary progr amming (EP), and find that both methods are effective. All the simulation r esults illustrate that the EAs can provide better ride comfort and road hol ding ability in comparison with the commonly used PSS.