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A High-Performance Control Method of Constant V/f-Controlled Induction Motor Drives for Electric Vehicles

机译:电动汽车恒V / f控制感应电动机驱动器的高性能控制方法

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摘要

A three-phase induction motor used as a propulsion system for the electric vehicle (EV) is a nonlinear, multi-input multi-output, and strong coupling system. For such a complicated model system with unmeasured and unavoidable disturbances, as well as parameter variations, the conventional vector control method cannot meet the demands of high-performance control. Therefore, a novel control strategy named least squares support vector machines (LSSVM) inverse control is presented in the paper. Invertibility of the induction motor in the constant V/f control mode is proved to confirm its feasibility. The LSSVM inverse is composed of an LSSVM approximating the nonlinear mapping of the induction motor and two integrators. The inverse model of the constant V/f-controlled induction motor drive is obtained by using LSSVM, and then the optimal parameters of LSSVM are determined automatically by applying a modified particle swarm optimization (MPSO). Cascading the LSSVM inverse with the induction motor drive system, the pseudolinear system can be obtained. Thus, it is easy to design the closed-loop linear regulator. The simulation results verify the effectiveness of the proposed method.
机译:用作电动汽车(EV)推进系统的三相感应电动机是一种非线性,多输入多输出,强耦合的系统。对于具有无法测量的和不可避免的干扰以及参数变化的复杂模型系统,传统的矢量控制方法不能满足高性能控制的要求。因此,本文提出了一种新颖的控制策略,即最小二乘支持向量机(LSSVM)逆控制。证明了在恒定V / f控制模式下感应电动机的可逆性证实了其可行性。 LSSVM逆由一个LSSVM组成,该LSSVM近似感应电动机和两个积分器的非线性映射。利用LSSVM获得恒V / f控制的感应电动机驱动的逆模型,然后通过应用改进的粒子群算法(MPSO)自动确定LSSVM的最优参数。将LSSVM逆与感应电动机驱动系统级联,可以获得伪线性系统。因此,很容易设计闭环线性稳压器。仿真结果验证了该方法的有效性。

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  • 来源
    《Mathematical Problems in Engineering》 |2014年第1期|386174.1-386174.10|共10页
  • 作者单位

    Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China;

    Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China;

    Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China;

    Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China;

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