DATA DRIVEN ANALYSIS OF ENERGY MANAGEMENT IN ELECTRIC VEHICLES
Sanket Sawant, Aniruddha Patil, Dipesh Solanki, Prof. Bhushan Save, "DATA DRIVEN ANALYSIS OF ENERGY MANAGEMENT IN ELECTRIC VEHICLES", VIVA-IJRI Volume 1, Issue 4, Article 142, pp. 1-6, 2021. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.
Inevitably, there has been a concerted policy push at the national level to promote electric vehicles. In electric vehicles, the progress stands and falls with the performance of the battery. Lithium-ion batteries are considered in this research project, as they are the most crucial component in the electric vehicle power system and require accurate monitoring and control. Proper battery optimization in electric vehicles requires a meticulous energy management system. The energy management system is bound for estimating the battery state of charge, state of health, various distinct factors in the system, and subsystems in real-time. The state of charge estimation accounts for the prevention of over-charge and over-discharge of batteries and provides cell balancing. Traditional SOC estimation approaches, such as open-circuit voltage (OCV) measurement and current integration (coulomb counting), are relatively accurate in some cases. However, estimating the SOC for Li-ion chemistries requires a modified approach. This project presents the Kalman filtering algorithm for the state of charge estimation that provides precise results for a fair computational effort.
Electric vehicles, Energy management systems (EMS), Hybrid EV, Lithium-Ion Batteries, State of Charge (SOC).
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