Design and optimization of electric vehicle battery swapping stations with integrated storage for enhanced efficiency

The growing adoption of electric vehicles (EVs) continues to face challenges, including extended charging durations and range anxiety, which restrict widespread integration. Battery swapping stations (BSS) mitigate these challenges by facilitating rapid battery exchanges; yet, their development necessitates the optimization of investments in batteries, chargers, servers, and queuing systems. This research presents an optimum sizing framework employing mixed-integer linear programming (MILP) and queuing theory to equilibrate cost and performance. This work models EV arrivals as a random process with set service times and looks at the station using queuing models for both unlimited and limited capacities. Simulation outcomes indicate that for 100 EVs with an arrival rate of 7 vehicles per hour, the addition of 16–26 batteries optimizes operations, allowing the station to accommodate between 100 and 350 EVs. The preliminary study suggests that the battery swapping station operates optimally at a 90% utilization rate, ensuring an 8% rejection chance for incoming EVs; beyond this threshold, the present study recommends the installation of additional stations. The findings offer practical insights for policymakers on the economical and scalable implementation of battery swapping stations, facilitating their acceptance in the transportation industry.