Quarter and Full Car Models Optimisation of Passive and Active Suspension System Using Genetic Algorithm

Abstract

This study evaluates a suspension design of a passenger car to obtain maximum rider's comfort when the vehicle is subjected to different road profile or road surface condition. The challenge will be on finding a balance between the rider's comfort and vehicle handling to optimize design parameters. The study uses a simple passive suspension system and an active suspension model integrated with a pneumatic actuator controlled by proportional integral derivative (PID) controller in both quarter car and full car models having a different degree of freedoms (DOF) and increasing degrees of complexities. The quarter car considered as a 2-DOF model, while the full car model is a 7-DOF model. The design process set to optimise the spring stiffnesses, damping coefficients and actuator PID controller gains. For optimisation, the research featured genetic algorithm optimisation technique to obtain a balanced response of the vehicle as evaluated from the displacement, velocity and acceleration of sprung and unsprung masses along with different human comfort and vehicle performance criteria. The results revealed that the active suspension system with optimised spring stiffness, damping coefficients and PID gains demonstrated the superior riding comfort and road holding compared to a passive suspension system.