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The Control of Brushless DC Motor for Electric Vehicle by Using Chaotic Synchronization Method

机译:电动汽车用无刷直流电动机的混沌同步控制

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Brushless DC motor (BLDC) used in electric vehicles can be operated in normal weather conditions and on straight roads, with chaotic dynamics of BLDC motor and high efficiency at a certain stable point. The dynamics of the BLDC motor applied on the electric car can be constantly changed according to the road conditions and wind speed. In this study, chaotic synchronization methods were developed to convert the BLDC motor into the desired reference chaotic dynamics. Synchronization method is developed based on sliding mode control (SMC), PI control and adaptive control methods. The artificial bee colony algorithm has been used to calculate the optimal values of the Kp and Ki coefficients of the PI controller. The numerical simulation results showing the performances of the controllers were obtained in MATLAB-Simulink environment. In order to better compare the performance of the controllers, the error performance indices have been provided according to these three control methods. All the three methods have shown that the chaotic based BLDC motor can be controlled, but sliding mode control method has proved to be a better performer.
机译:电动汽车中使用的无刷直流电动机(BLDC)可以在正常天气条件下和在直路上行驶,并且BLDC电动机具有混沌的动力学特性,并且在一定的稳定点上具有很高的效率。电动汽车上使用的BLDC电机的动力可以根据路况和风速不断变化。在这项研究中,开发了混沌同步方法将BLDC电机转换为所需的参考混沌动力学。基于滑模控制(SMC),PI控制和自适应控制方法开发了同步方法。人工蜂群算法已用于计算PI控制器的Kp和Ki系数的最佳值。在MATLAB-Simulink环境中获得了显示控制器性能的数值仿真结果。为了更好地比较控制器的性能,根据这三种控制方法提供了错误性能指标。这三种方法都表明可以控制基于混沌的BLDC电机,但是事实证明,滑模控制方法是一种更好的方法。

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