Genetic Optimization of Fuzzy Active Suspension System Based on Full-Vehicle Model

One of the main purposes for active suspension (AS) system application in vehicles is the ride comfort enhancement. On the other hand, ride comfort, suspension travel, and energy consumption are conflicting parameters which should be compromised using a trade-off solution. Previous studies for optimization of fuzzy AS systems were base on simple quarter or half vehicle models in which many efficient degrees of freedom are neglected. Multi-objective optimization of vehicle AS based on the full-vehicle model is presented in this paper. For this purpose, a fuzzy logic controller (FLC) is first proposed for the AS system. The FLC is then applied to the full-vehicle model and its parameters are well tuned, using genetic algorithm. The optimizations are carried out based on a multi-objective fitness function incorporating transmitted accelerations to the body, suspension travels, and total energy consumption. The simulation results reveal the superior performance of the optimized AS system in ride comfort improvement as well as suspension travel and energy consumption reduction.

Keywords:

Active Suspension System , Fuzzy Control , Genetic Optimization , Full-Vehicle Model