Modeling and optimization of linear active and passive suspension systems for full vehicle

Abstract

A Suspension system plays a major role in automobiles to improve passenger comfort, passenger safety and road handling. It isolates the body of a vehicle from road disturbances. Passive suspensions are designed to satisfy the conflicting criteria of riding comfort and vehicle handling. An active suspension system attempts to overcome these compromises to provide the best performance for vehicle control. Different types of mathematical models have been used to study the suspension system of a vehicle. The quarter vehicle model has been used for the initial investigation. Later, the half vehicle and full vehicle models were used for the study, which is closer to the actual model of a vehicle suspension.In comparison to a linear passive suspension system, a nonlinear passive suspension system is suited for improving vehicle performance without a major change in suspension system cost and minimizing road damage. An HGV model of vehicle suspension has been used in the research. A cubical nonlinear spring and a linear damper are part of the suspension system under consideration. The fourth power of the tire dynamic load has been used to indicate road damage. A genetic algorithm has been used to optimize the half-vehicle model to minimize approx 6.93 % of road damage. The solution has been obtained using MATLAB and SIMULINK. newlineThe full vehicle model would be subjected to disturbances from all four wheels thus, a full-suspension model of the vehicle should be considered for the investigation to the idea of an enhanced control preview. A fully active suspension system aims to control the suspension over the full bandwidth, and to increase load carrying capacity, handling and ride quality. The behavior of a suspension system is analyzed using the full vehicle model. newlineThis research work aims to model a vehicle s dynamics when it uses an active suspension system. The mathematical modeling using a full vehicle suspension system is presented, and the equations are cast in both the state space form and transfer function forms.