Comprehensive analysis for influence of complex coupling effect and controllable suspension time delay on hub-driving electric vehicle performance

Abstract

For in-wheel driving vehicle electric vehicles (EVs), mechanical electromagnetic coupling effect caused by the air gap deformation in permanent magnet synchronous hub motor and intensified by the road excitation deteriorates the EVs performance. In this paper, after studying the numerical method for multi-field coupling problems of hub-driving vehicle under the coupled action of electromagnetic field and mechanical field. The experimental validation is investigated. The results indicate that the multi-field coupling effect in hub-driving motor worsens the dynamics performance of the vehicle. To enhance the vehicle performance, suppress mechanical electromagnetic coupling effect and, at same time, reduce the influence of controllable suspension time delay, a delay-dependent H∞ controller is designed based on Lyapunov theory. By applying the particle swarm optimization (PSO) algorithm and the linear matrix inequality theory, the desired output controller gain is derived. Numerical simulations reflect that the active suspension controller considering control time delay not only achieves the favorable riding comfort performance and restrains the coupling effect in hub driving motor but also ensures the suspension deflection and the safety performance requirement. Moreover, it maintains the closed-loop asymptotically stability regardless of t the variation on the sprung mass and control time delay.

Neural Network-Based Adaptive Height Tracking Control of Active Air Suspension System with Magnetorheological Fluid Damper Subject to Uncertain Mass and Input Delay

“…The paper [ 15 ] investigated the nonlinear dynamics of a constant coefficient time lag vibration control system in detail, and obtained a series of important criteria such as the ability of the system to remain stable in a smaller interval of time delay feedback. The authors of [ 16 ] used a locally optimal hybrid PSO/LMI algorithm for perturbations and time delays and tuned the continuous saturation controller by adjusting the feedback gain, but they did not consider the effect of sprung mass variations from the controller. Thus, inspired by the above, a predictor-based compensation scheme is used in this work to address the effects of input delay and uncertainty.…”