Citation

Ghazali, Anith Khairunnisa and Aziz, Nor Azlina Ab. and Hassan, Mohd Khair (2025) Advanced Algorithms in Battery Management Systems for Electric Vehicles: A Comprehensive Review. Symmetry, 17 (3). p. 321. ISSN 2073-8994

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Abstract

Electric vehicles and hybrid electric vehicles (EV) are increasingly common on roads today compared to a decade ago, driven by advancements in technology and a growing focus on sustainable transportation. These vehicles are powered by rechargeable lithium-ion batteries. A battery management system (BMS) is indispensable for ensuring the optimal performance, safety, and longevity of the EV’s batteries. In this review, the latest algorithm trends for BMS software are discussed. This work also focuses on several key functionalities of BMS like the state of charge (SOC) estimation, state of health (SOH) monitoring, state of energy (SOE), and state of power (SOP). Advanced algorithms for BMS are comprehensively reviewed, including those designed for specific functionalities, as well as those developed based on existing optimization, artificial intelligence, and estimation algorithms. These algorithms address critical challenges such as maintaining symmetry during charging and discharging, preventing thermal runaway, and managing battery faults in EV systems. This work provides valuable insights for researchers and practitioners in the field of EV design and development, particularly those focusing on the advancement of BMS technologies.

Item Type:	Article
Uncontrolled Keywords:	battery management system; electric vehicle; hybrid electric vehicle; lithium-ion batteries
Subjects:	T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL1-484 Motor vehicles. Cycles
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	29 Apr 2025 07:56
Last Modified:	29 Apr 2025 07:56
URII:	http://shdl.mmu.edu.my/id/eprint/13686

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