Implementing Intelligent Cell-to-Cell Charging Strategies to Enhance Performance and Lifespan in EV Battery Systems

Abstract

The accelerating shift toward electrification in the global transportation sector has placed electric vehicle (EV) battery performance, safety, and longevity at the forefront of technical challenges facing the industry. Conventional Battery Management Systems (BMS) often rely on coarse, pack-level control strategies that fail to capture the heterogeneous aging and degradation behavior of individual cells, leaving batteries vulnerable to imbalance, inefficiency, and safety risks such as overcharging or thermal stress. Addressing this gap is critical, as an effective BMS is not merely a supporting subsystem but the central determinant of battery safety, efficiency, and usable lifespan in modern EVs. This paper proposes a "Smart Battery" architecture that integrates an advanced BMS framework capable of fine-grained, cell-level intelligence. The architecture combines a dedicated monitoring network with an adaptive control mechanism, enabling the system to continuously assess cell-level health indicators and dynamically regulate charging and discharging behavior accordingly. A custom decision-making algorithm governs this process to keep individual cells within safe and optimal operating conditions. Experimental evaluation shows that this approach substantially reduces cell imbalance and associated hazardous conditions compared to conventional methods, while improving overall energy utilization and extending battery service life. The findings underscore the pivotal role of intelligent BMS design in enhancing the economic viability, reliability, and safety of next-generation electric vehicles.