Experimental Evaluation of Improved Battery Management System Design for Electric Vehicles to Resist Performance over Long Duration

The study utilized real-world data obtained from various sources, including fleet management systems, telematics, onboard diagnostics, and environmental sensors. Through rigorous analysis and algorithm development, the research focused on identifying potential risks affecting battery performance and implementing strategies to mitigate these risks. Advanced BMS algorithms were designed to adapt to changing environmental conditions, predict potential battery degradation, and optimize charging and discharging processes. Hardware and sensor integration were crucial aspects, ensuring seamless compatibility with existing EV infrastructure and components. The developed BMS underwent extensive testing and validation under various operating conditions to assess its performance and reliability. Continuous improvement mechanisms were established to iteratively refine the algorithms and enhance system efficiency over time. The results demonstrated significant improvements in battery lifespan extension, capacity retention, thermal management effectiveness, and safety enhancements compared to previous models. Contributing to the broad adoption of electric cars and sustainable transportation solutions, the findings emphasize the significance of modern BMS technologies in optimizing the performance and lifespan of EV batteries.