Application of improved particle swarm optimization algorithm in the proportional integral differential-controlled semi-active suspension system

Abstract

To enhance the control performance of semi-active suspension systems, this research proposes a particle swarm optimization algorithm (PSO) with adaptive nonlinear correction of inertia weights, which is then integrated with a proportional integral differential (PID) algorithm. To this end, this research establishes quarter semi-active and passive suspension models of automobiles by utilizing the Matlab/Simulink simulation platform. In this foundation, this research further compares the advantages and disadvantages regarding performance indexes of semi-active suspension controlled by the adaptive inertia weighted particle swarm optimization (APSO) algorithm and the PID algorithm, as well as the PID-controlled semi-active suspension and passive suspension through simulation. Simulation results indicate that performance indicator values for different suspension types increase with higher pavement grades. Compared with passive suspension, the semi-active suspension controlled by APSO and PID algorithms presents significantly improved performance indexes, with reductions of at least 31.61% in root mean square (RMS) concerning body vertical acceleration, 1.78% in suspension dynamic deflection, and 22.13% in tire dynamic loads. Moreover, analysis of suspension system frequency response characteristics demonstrates a significant decrease in droop acceleration transmission rate for the semi-active suspension with APSO and PID algorithms across the whole frequency range compared with that of the PID-controlled suspension and passive suspension. On the same note, despite the higher values of suspension dynamic deflection and tire dynamic load transfer rate in certain frequency bands, they are generally within acceptable suspension limits. Simply put, the findings confirm the feasibility of applying the APSO algorithm in PID-controlled semi-active suspension systems, which effectively improves both vehicle ride comfort and handling stability.