| Abstract: | This paper presents a method to optimise a car chassis fitted either with passive or active suspensions. Provided that a full vehicle model is available for accurate simulations of many different driving situations (J-turn, lane-change, power-on/power-off on even/rough, dry/wet roads), the method allows to tune the parameters of the chassis system (suspension elastokinematics, stiffnesses, dampings, actuator gains, tyre pressures...) in order to achieve the desired dynamic behaviour of the car in all of the considered driving situations. According with the Global Approximation approach, the original physical car model is substituted by another purely numerical mathematical model (backpropagating Artificial Neural Network). This reduces the simulation time dramatically and enables the optimisation process to come to successful results. The computation of the Pareto-optimal set is performed by using Genetic Algorithms. The method is validated by optimising the parameters of the suspension system of an actual car. |
