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Online stator and rotor resistance estimation scheme using swarm intelligence for induction motor drive in EV/HEV

机译:在EV / HEV中使用群体智能的在线定子和转子电阻估计方案

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The usage of niche copper-rotor induction motor (CRIM) in the Tesla Roadster electric vehicle has bolstered the technology of using copper-rotor induction motor for electrified transportation. Understanding the merits, demerits and state of art technology of induction motor and its drive in EV/HEV application, this research manuscript proposes an online stator and rotor resistance estimation scheme using particle swarm optimization (PSO) technique for efficient and accurate control of induction motors in the same application. Firstly, an insight is provided on the state or art CRIM technology in EV/HEV and the need for reliable online rotor and stator resistance estimation scheme. Secondly, a PSO based scheme for resistance estimation is developed through a mathematical model. The developed model is validated and tested on a 10hp CRIM thorough a computer programme. Thereafter, the calculated results obtained from numerical investigations are analyzed.
机译:在特斯拉跑车电动车中的利基铜转子感应电动机(CRIM)的用途使得使用铜转子感应电动机进行电气化运输的技术。理解感应电机的优点,缺点和现有技术在EV / HEV应用中的驱动器中,这项研究手稿采用了使用粒子群优化(PSO)技术的在线定子和转子电阻估计方案,以便高效控制感应电动机在同一申请中。首先,在EV / HEV中的状态或艺术CRIM技术中提供了洞察力,并且需要可靠的在线转子和定子电阻估计方案。其次,通过数学模型开发了一种用于电阻估计的PSO方案。开发的模型被验证并在10HP的Crim彻底进行计算机程序上进行测试。此后,分析了从数值研究获得的计算结果。

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