基于工况识别的IWM-EV主动悬架MOPSO模糊滑模控制

轮毂电机电动汽车(in-wheel motor electric vehicle,IWM-EV)的电机激励与车辆系统的耦合特性严重的恶化车辆的动力学性能以及电机的工作稳定性,针对这种振动负效应问题,建立了考虑机电耦合的车辆动力学耦合模型,并设计了工况识别的主动悬架多目标粒子群(multi-objective particle swarm optimization,MOPSO)模糊滑模控制器。基于傅里叶级数法建立了轮毂电机的垂向不平衡激励与电机转矩的电机模型;将电机模型与车辆动力学模型结合建立了电机与悬架联合的垂向-驱动非线性动力学耦合模型。基于耦合模型分析了车辆的机电耦合振动负效应特性,针对模型强非线性的特点,设计了耦合模型的非线性控制器。仿真结果表明,控制器能既能有效的减小电机的相对偏心率,抑制电机不平衡电磁力,又能提升车辆动力学性能,有效的抑制了轮毂电机电动汽车的振动负效应。

MOPSO fuzzy sliding mode control of an IWM-EV active suspension based on operating condition recognition

The adaptive sliding-mode control based on road identification was applied to inhibit the negative vibration effect caused by the in-wheel motor(IWM)in an electric vehicle(EV)and a multi-objective particle swarm optimization(MOPSO)fuzzy sliding-mode controller based on working condition identification was designed.Firstly,the electromechanical model of the vertical unbalance excitation and the driving torque was established.Combining the electromechanical model with the vehicle dynamics model,a vertical-driving nonlinear dynamics coupling model for the motor and suspension was established.Based on the coupling model,the characteristics of the negative vibration effect in the electric vehicle were analyzed.Aiming at the issues of strong nonlinearity of the model,the non-linear controller based on working condition identification was designed.The simulation results show that the controller can effectively reduce the relative eccentricity of the motor,mitigate the unbalanced electromagnetic force of the in-wheel motor,improve the dynamic performance of the vehicle and effectively suppress the vibration negative effect of the in-wheel motor in the electric vehicle.