A Smart Battery Management System (BMS) Development for Electric Vehicles to Improve Energy and Power Management Structure

The development of a Smart Battery Management System (BMS) for electric vehicles (EVs) focuses on enhancing energy and power management by ensuring accurate State of Charge (SOC) estimation, efficient temperature control, voltage balancing, and optimized charging/discharging processes. This study implemented real-time monitoring and predictive algorithms, including neural networks optimized with genetic algorithms, to improve the accuracy of SOC estimation. The results indicated that the SOC estimation had a minimal error of 0.5% or less, with the predicted SOC closely aligning with actual values across different test scenarios. The system also effectively managed temperature, maintaining battery pack temperatures below <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$52^{\circ}\mathrm{C}$</tex> under high loads. Voltage balancing reduced discrepancies between cells, achieving a final voltage difference of less than 0.01V. Charging and discharging efficiency remained high, with an energy efficiency of 95% at lower loads and 85% at higher loads. These findings demonstrate the potential of the Smart BMS to significantly enhance the performance, safety, and lifespan of EV batteries. The system's integration of advanced algorithms and real-time data processing paves the way for more efficient battery management in EVs, making it a critical component for future sustainable transportation.