Optimal Sizing and Adaptive Charging Strategy for the Battery Swapping Station

The limited driving range and long charging times of electric vehicles (EVs) have hindered their widespread adoption. Various attempts have been undertaken to address the trade-off problem between battery charging speed, range anxiety, battery lifetime, and charging time. Battery swapping stations (BSS) have emerged as a promising solution to address these concerns. BSS facilitates instant charging by quickly swapping depleted EV batteries with fully charged ones. The depleted EV batteries are kept for charging in the BSS. However, determining the optimal battery inventory is a complex problem that requires careful consideration of various factors such as demand patterns, time- of-arrival (ToA) of EVs, State-Of-Charge (SoC) of the arriving EVs, battery degradation, and operational costs. This paper proposes an optimization framework to evaluate the most efficient inventory capacity to be installed in a BSS while ensuring that customers do not have to wait long to get their batteries swapped. It also proposes a charging strategy for BSS that can reduce the cost to charge the batteries, improve the state-of-health (SoH) of batteries, and help in reducing the peak demand of the grid at high tariff times. Our results show that the proposed framework can significantly improve the operational efficiency and profitability of battery swapping stations