System Identification of Switched Reluctance Motor (SRM) Using Black Box Method for Electric Vehicle Speed Control System

Muhammad Rizalul Wahid, E. Joelianto, Nadana Ayzah Azis
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引用次数: 2

Abstract

Switched reluctance motor (SRM) as a driving force has a very important role in an electric vehicle because of the ability to produce large torque about 12.3 Nm and speed about 9600 rpm. Currently, there is no suitable model that represents the real SRM motor. This paper presents model identification of the SRM motor using the Black Box method in the Matlab System Identification Toolbox (SIT). The speed output of the SRM motor is measured externally by a sensor based on the hall effect principle, which gives a high pulse of 4.27 volts every detection of an existing magnet at the motor rotation. The speed sensor of motor is simulated and validated using the Intelligent Schematic Input System (ISIS) software on the Proteus before it is implemented into the SRM motor. The results are obtained in the form of transfer function system with order 1 and order 2. The first order and second order models result in 93.65% and 93.7% approximation to the real data respectively.
基于黑盒法的开关磁阻电机(SRM)电动汽车速度控制系统辨识
开关磁阻电机(SRM)作为电动汽车的驱动力,能够产生约12.3 Nm的大扭矩和约9600 rpm的转速,在电动汽车中起着非常重要的作用。目前,还没有合适的模型来代表真正的SRM电机。本文利用Matlab系统识别工具箱(SIT)中的黑盒法对SRM电机进行了模型识别。SRM电机的速度输出由一个基于霍尔效应原理的传感器在外部测量,该传感器在电机旋转时每检测到一个现有磁铁,就会产生4.27伏的高脉冲。采用Proteus上的智能原理图输入系统(ISIS)软件对电机的速度传感器进行仿真和验证,然后将其实现到SRM电机中。结果以1阶和2阶传递函数系统的形式得到。一阶和二阶模型对实际数据的逼近率分别为93.65%和93.7%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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