Optimal Capacity Estimation of Energy Storage Systems in Electric Vehicles (EVs)

Designing an Electric Vehicle (EV) Energy Storage System (ESS) involves several factors, including driving range, acceleration, fast charging, longevity, weight, and capacity. Research on multi-objective optimization is necessary to successfully balance these variables and arrive at the ideal EV ESS size. Accurate capacity estimation guarantees that the ESS balances driving range cost and weight while meeting power and energy requirements. The trade-off varies based on the EV type, size, and use scenario. A hybridized ESS with high-energy and high-power cells can meet various customer needs. This paper presents a power-based approach and optimization method for ESS sizing in electric vehicles (EVs). In order to balance system constraints, cost-effectiveness, and energy efficiency, the optimization-based approach uses different algorithms. Conversely, the power-based approach matches the ESS size to the vehicle’s power needs, guaranteeing a sufficient supply at steady-state and peak loads. The findings provide critical insights into designing ESS combinations, such as hybrid energy storage systems (HESS), for maximum performance and economic feasibility in the next generation of EVs.