Journal of Vibroengineering · 2016 · 25 citations · 15 references
EngineeringElectrical EngineeringMechanical EngineeringElectric Vehicle EngineeringElectric Vehicle TechnologyVehicle DynamicsActive Suspension SystemsSuspension DynamicsSuspension SystemsVehicle Control SystemsVehicle VibrationVibration ControlActive SuspensionActive Suspension ControlParticle Swarm ControlPassive SuspensionSuspension ControlSuspension Control SystemsVehicle Body AccelerationVehicle Body Vibration
Using the active suspension system of an electric vehicle driven by two rear in-wheel motors as the research object, a 14-degree of freedom coupled vehicle dynamic model is established. Based on the model, a dual-loop proportion integration differentiation controller based on the particle swarm algorithm is designed to control the active suspension in this paper. The designed controller can not only ease the vibration of the vehicle body from the road surface roughness and the unbalanced electromagnetic force but also can improve the ride comfort of the vehicle. To further verify the effectiveness of the control method, the control effect of the active suspension controller designed in this paper is compared with that of a passive suspension and a dual-loop proportion integration differentiation controller without the particle swarm algorithm. The results show that the vertical vibration acceleration, the roller angle and the pitch angle of the vehicle body are significantly improved with the dual-loop proportion integration differentiation controller based on the particle swarm algorithm. Compared with the passive suspension and the dual-loop proportion integration differentiation controller without the particle swarm algorithm, the improvement ratio of the vertical vibration acceleration is 20.92 % and 11.93 %, respectively; the roll angle improvement ratio can reach 57.23 % and 22.02 %, respectively; and the improvement ratio of the pitch angle is 30.23 % and 18.94 %, respectively. The comparison results show that the dual-loop proportion integration differentiation controller optimized with the particle swarm algorithm can better improve the ride comfort of the vehicle.
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A modified particle swarm optimizer
Yibing Shi, R.C. Eberhart · 2002 · 10.2K citations
Empirical study of particle swarm optimization
Yibing Shi, R.C. Eberhart · 2003 · 3.9K citations
Proceedings Congress on Evolutionary Computation 2001
2001 · 1.1K citations