Advanced Electric Vehicle Battery Management Systems: Optimizing Performance, Safety, and Longevity in Modern Transportation
Keywords:
Battery Management System, Electric Vehicle, Thermal Regulation, Safety Protection, Battery DegradationAbstract
The advancement of Battery Management Systems (BMS) is pivotal to ensuring the performance, safety, and longevity of electric vehicle (EV) battery packs. This study presents an in-depth analysis of modern BMS technologies, focusing on their structural architectures, safety features, thermal behaviour, and economic efficiency. The primary objective is to evaluate how advanced BMS designs enhance battery reliability and sustainability in various EV applications. A combination of experimental data analysis and comparative review methods was employed to assess battery degradation patterns, thermal distribution, safety response times, market adoption, and cost structures. The results indicate that battery capacity retention decreases from 100% to 70% after 5,000 charging cycles, necessitating intelligent BMS intervention to extend battery lifespan. Temperature distribution analysis reveals that 35% of EV battery operation occurs between 10°C and 25°C, while only 8% occurs above 40°C, highlighting the critical role of thermal regulation. Market data shows Centralised BMS holds a 32% share, followed by Distributed (28%) and Modular (22%) systems. Although Premium BMS systems cost $1,165 per kWh, they offer advanced safety controls, faster diagnostics, and a competitive return on investment of 3.1 years. Safety feature evaluation shows that short-circuit protection responds within 1 ms, and overcurrent protection within 5 ms. This research introduces a comprehensive view of recent innovations, particularly the adaptation of BMS to high-performance battery chemistries like solid-state cells with 400 Wh/kg energy density and 10,000 cycle life. In conclusion, next-generation BMS is essential to achieving safe, cost-effective, and high-performance EV battery operation, supported by data-driven optimisation strategies and intelligent architecture selection.
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