A Robust Regenerative-Braking Control of Induction Motors for EVs Applications

IF 1.9 4区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Omar E. M. Youssef, Mohamed G. Hussien, Abd El-Wahab Hassan
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引用次数: 0

Abstract

EVs suffer from short driving range because of limited capacity of the battery. An advantage of EVs over internal-combustion vehicles is the ability of regenerative braking (RB). By this advantage, EVs can develop energy by RB which can be stored in the battery for later use to increase the driving range of EVs. There are different motors that can be used in EVs, and the control during RB mode is dedicated for certain motor types. However, the previous studies for EV-based IM drives consider the motor-speed control without considering its RB. This paper proposes a robust control of induction motor (IM) during RB mode of EVs. The proposed control system is simple and depends only on mathematical calculations. The obtained results confirm the effectiveness and accuracy of the suggested control strategy with a good dynamic behavior under different operating conditions. Also, the results assure the robustness of control capabilities under parameters uncertainties during the RB mode of EV-based IM drives.

电动汽车应用中感应电机的鲁棒再生制动控制
由于电池容量有限,电动汽车的行驶里程较短。与内燃汽车相比,电动汽车的一个优势是再生制动(RB)能力。利用这一优势,电动汽车可以通过再生制动产生能量,这些能量可以储存在电池中,供以后使用,从而增加电动汽车的行驶里程。电动汽车可以使用不同的电机,而再生制动模式下的控制是专门针对某些电机类型的。然而,之前针对电动汽车 IM 驱动器的研究只考虑了电机速度控制,而没有考虑其 RB。本文提出了电动汽车 RB 模式下感应电机 (IM) 的鲁棒控制。所提出的控制系统非常简单,仅依赖于数学计算。所获得的结果证实了所建议的控制策略的有效性和准确性,并在不同的运行条件下具有良好的动态特性。此外,结果还保证了基于电动汽车的 IM 驱动器在 RB 模式下,在参数不确定的情况下控制能力的稳健性。
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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来源期刊
International Transactions on Electrical Energy Systems
International Transactions on Electrical Energy Systems ENGINEERING, ELECTRICAL & ELECTRONIC-
CiteScore
6.70
自引率
8.70%
发文量
342
期刊介绍: International Transactions on Electrical Energy Systems publishes original research results on key advances in the generation, transmission, and distribution of electrical energy systems. Of particular interest are submissions concerning the modeling, analysis, optimization and control of advanced electric power systems. Manuscripts on topics of economics, finance, policies, insulation materials, low-voltage power electronics, plasmas, and magnetics will generally not be considered for review.
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