Optimization of PID Parameters Using Particle Swarm Optimization for Active Suspension System of Electric Vehicle
摘要
Researchers and designers place significant emphasis on enhancing the comfort of electric vehicles (EVs). This study establishes a dynamic model of an EV influenced by the in-wheel motor (IWM) and road surface irregularities. A PID controller is then implemented to manage the EVs active suspension system (ASS). To further improve ride performance, the parameters of the PID controller are optimized using the Particle Swarm Optimization (PSO) algorithm. Time-weighted root-mean-square (r.m.s.) acceleration of EV body, awzb is selected as the main objective function based on ISO 2631–1 (1997). The analysis results show that awzb values with the PID controller and the optimized PID controller through PSO respectively reduced by 18.92% and 33.33% compared to passive suspension system (PSS) of EV when EV moves on the ISO class B road surface at EV speed of 70 km/h and full load. Especially the optimized PID controller has achieved the best ride performance of EV under surveyed road surface conditions.