Abstract
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.
Highlights
The vehicle suspension system is a key component of improving the ride comfort and handling stability of vehicles [1]
For the electric vehicle (EV) driven by in-wheel motors (IWMs), the excitation in the vertical direction acted on the vehicle is from the road surface roughness (RSR), and from the electromagnetic force (EMF) produced by the motor magnet gap deformation which is caused by the RSR, uneven load, etc. [13]
To reduce the shock and the vibration of the vehicle body caused by the RSR and the EMF, a dual-loop proportion integration differentiation (PID) control structure with a particle swarm optimization (PSO) algorithm is proposed for the active suspension control of EVs driven by IWMs in this paper
Summary
The vehicle suspension system is a key component of improving the ride comfort and handling stability of vehicles [1]. In [9, 10], the effectiveness of active suspension with a PID controller and a neural PID controller is verified based on the comparative analysis. The above studies were all designed on the basis of traditional vehicles using a single-loop PID structure to control the active suspension. Focusing on the issue above, a dual-loop active suspension control structure that is based on the particle swarm optimization (PSO) algorithm and PID control is proposed in this paper. The control structure is applied to the active suspension control of EVs to reduce the shock and the vibration of the vehicle body from the RSR and EMF and to improve the ride comfort of the vehicle. To verify the effectiveness of the control structure proposed in this paper, a passive suspension and a dual-loop PID controller without the PSO algorithm are compared
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