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The direct torque control research of pure electric vehicles motor based on PSO-FC mixed-control model

机译:基于PSO-FC混合控制模型的纯电动汽车电机直接转矩控制研究

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In the control of induction motor, due to the nonlinear and time-varying, flux observer has always been the difficult point of the control algorithm design. Bang-Bang control methods which used in traditional direct torque control, selects the same space voltage vector whether the error is too large or too small. It makes the pulsation problem of flux and torque in control. Particle Swarm Optimization (PSO) algorithm has the characteristics of random search optimal solution in the global. Combine PSO algorithm with BP (Back Propagation) neural network algorithm, alternative to the stator flux observer of traditional induction motor direct torque control, fuzzy controller replace the hysteresis comparator and Switch Vector Table of traditional direct torque control system, to reduce the pulsation of motor flux and torque. The simulation results indicate that, when the motor torque sudden change, the response of the system is quicker, the pulsation of flux and torque is smaller, achieve the expected results.
机译:在异步电动机的控制中,由于其非线性和时变特性,磁通观测器一直是控制算法设计的难点。传统的直接转矩控制中使用的Bang-Bang控制方法,无论误差太大还是太小,都选择相同的空间电压矢量。它使磁通和转矩的脉动问题得到控制。粒子群优化算法(PSO)具有全局范围内随机搜索最优解的特点。将PSO算法与BP(反向传播)神经网络算法相结合,替代传统感应电动机直接转矩控制的定子磁通观测器,用模糊控制器代替传统直接转矩控制系统的磁滞比较器和Switch Vector Table,以减少电动机的脉动磁通和转矩。仿真结果表明,当电动机转矩突然变化时,系统的响应速度更快,磁通和转矩的脉动较小,达到了预期的效果。

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