https://khub.utp.edu.my/scholars/id/eprint/20565 2026-05-05T03:41:11Z info:eu-repo/semantics/descriptiveMetadata https://khub.utp.edu.my/scholars/20565/ Recent Evolution of Intelligent Approach in Electric Motor Drive System for EV Applications: A Concise Review Sepeeh, Muhamad Syazmie Zulkifli, Shamsul Aizam Chiu, Huang-Jen Jamahori, Hanis Farhah The fast development of electric vehicles (EVs) has motivated major studies on smart management techniques for electric motors, which are essential for guaranteeing optimal performance, efficiency, and dependability. This brief paper offers a summary of recent advances in artificial intelligence (AI)-based techniques used in electric motor management inside EV applications. The conversation covers several artificial intelligence models, including fuzzy logic (FL) systems, evolutionary algorithms (EA), machine learning (ML), and deep learning (DL). Every approach is quickly examined in terms of its working principles, benefits, drawbacks, and appropriateness for particular motor control duties, including speed control, torque optimisation, defect identification, and adaptive control. Particular focus is on how AI methods combine with motor types often used in EVs, such as permanent magnet synchronous motor (PMSM) and induction motor (IM). The paper highlights current trends and research opportunities to provide researchers and practitioners a modest but instructive reference for enhancing intelligent motor control in modern EV systems. © 2025 IEEE. Institute of Electrical and Electronics Engineers Inc. 2025 Conference or Workshop Item PeerReviewed Sepeeh, Muhamad Syazmie and Zulkifli, Shamsul Aizam and Chiu, Huang-Jen and Jamahori, Hanis Farhah (2025) Recent Evolution of Intelligent Approach in Electric Motor Drive System for EV Applications: A Concise Review. In: UNSPECIFIED. https://www.scopus.com/inward/record.uri?eid=2-s2.0-105034127358&doi=10.1109%2fTENCON66050.2025.11375007&partnerID=40&md5=8a6217e1d1f35a86ae06c509a3deeac5 10.1109/TENCON66050.2025.11375007 10.1109/TENCON66050.2025.11375007 info:eu-repo/semantics/humanStartPage