Battery Electric Vehicles and Plug-in Hybrid Electric Vehicles: Review of Integration, Machine Learning Applications, and Future Mobility Trends
Keywords:
Battery Electric Vehicle (BEV), Plug-in Hybrid Electric Vehicle (PHEV), Machine Learning (ML), Vehicle-to-Grid (V2G), Battery Management System (BMS)Abstract
Both Battery Electric Vehicles (BEVs) and Plug-in Hybrid Electric Vehicles (PHEVs) are redefining the foundation of smart mobility, have accelerated the transition toward sustainable transportation. A BEV operates entirely on electrical energy stored in high-density batteries managed by advanced Battery Management Systems (BMS), offering benefits such as zero emissions, minimal maintenance, and smooth operation. In contrast, a PHEV combines internal combustion power with an electric drive, using its BMS to balance power delivery and maximize fuel efficiency. Together, BEVs and PHEVs serve as essential enablers of smart mobility, ensuring cleaner transportation and energy-efficient operation. Recent progress in Battery Management System (BMS) technology, coupled with Machine Learning (ML) applications, has significantly improved the monitoring, control, and optimization of battery health and performance. ML algorithms enable predictive analytics for state-of-charge, state-of-health, and degradation patterns, extending the lifespan of BEVs and PHEVs. Furthermore, there is enhancement in energy efficiency associated with Vehicle-to-Grid (V2G) systems since it allows BEVs and PHEVs to exchange power dynamically with the grid and supports renewable energy integration and grid stability. Through V2G and integration of renewable energy, electric vehicles evolve from passive energy consumers to active participants in a smart mobility ecosystem. Integration of ML within BMS facilitates adaptive energy control and intelligent fault detection in BEVs and PHEVs. This synergy improves operational safety while reducing life-cycle emissions. Additionally, renewable energy integration through solar and wind-powered V2G systems further strengthens the sustainability of smart mobility infrastructures. Despite challenges such as high battery costs, recycling, and infrastructure limitations, the combination of ML, BMS optimization, V2G interaction, and renewable energy integration ensures that BEVs and PHEVs will remain at the forefront of the global shift toward intelligent, sustainable, and low-carbon smart mobility systems.
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Copyright (c) 2026 Muhammad Idris, Ahmad Sule, Fitra Ayuza, Anthony C. Opia, Akilu Yunusa-Kaltungo, April Lia Hananto, Olusegun D. Samuel, Muhammad Zacky Asy'ari, Randi Gusto Jiwinangun, Mohd Farid M. Said
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