This study presents an optimisation framework for operating a battery swapping station (BSS) to enhance efficiency and sustainability in electric vehicle (EV) infrastructure. A hybrid modelling approach combines agent-based discrete event simulation and linear programming to model the dynamic behaviour of batteries and operational processes within the BSS. The model considers factors such as charging speed, battery degradation, grid power constraints, customer behaviour, and range anxiety. The agent-based model simulates the interaction between vehicles, batteries, and the station, capturing the stochastic nature of EVs’ arrivals and battery demand with the discrete event simulation. The linear programming component optimises battery state transitions to minimise degradation and ensure that the demand is met while respecting the power limits of the grid. Different battery types are considered based on vehicle category, each with specific capacity and usage patterns, reflecting real-world market conditions. The results demonstrate that the proposed optimisation framework can effectively manage the complex operational needs of a BSS. The proposed framework effectively balances service quality with resource efficiency by employing a strategic mix of charging modes and inventory management, reducing operational and degradation costs. This approach supports a more sustainable EV infrastructure, highlighting BSS as a viable solution to enhance the efficiency and sustainability of EV operations. Furthermore, the analysis highlights the critical role of power limits in determining charging strategies and their impact on operational efficiency. The findings suggest that with optimised operations, BSS can play a critical role in accelerating the adoption of EVs by offering a faster, more reliable, and sustainable alternative.
