Controller design and multi-objective optimization of heavy goods vehicle suspension system by geometry-inspired GA

Abstract

This paper presents the design of a suspension system for a Heavy Goods Vehicle (HGV). Four types of linear and non-linear, passive and semi-active suspension systems are modelled with Quarter Vehicle Model (QVM). A modified control law is proposed for the semi-active suspension system that uses a Proportional, Integral, Derivative (PID) controller. Suspension systems are designed by performing multi-objective optimization with road damage and goods damage as design criteria. In current optimization problems, objective function calculation is costly in terms of computational resources and time. Thus, it is necessary to reach actual optimal values in fewer generations with a small population. A fast-converging optimization algorithm is proposed to save computational cost and is used to design suspension systems. The results of the proposed algorithm are compared with the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The proposed algorithm saves a substantial amount of computational cost by fast convergence with a small population. Our results show that the semi-active suspension system with proposed control law performs better in terms of road-friendliness and goods safety.