Scaling Up Electric-Vehicle Battery Swapping Services in Cities: A Joint Location and Repairable-Inventory Model.

This article focuses on scaling up electric vehicle (EV) battery swapping services in urban areas by modeling and optimizing a "swap-locally, charge-centrally" infrastructure network. It develops a joint location and repairable-inventory model that captures the stochastic operations of battery swapping, charging, stocking, and circulation between decentralized swapping stations and centralized charging hubs, addressing challenges of service proximity, battery availability, and grid capacity constraints. The authors propose an efficient algorithmic framework combining constraint generation and parameter search techniques to solve the resulting nonconvex, nonconcave optimization problem exactly, significantly outperforming commercial solvers. Numerical studies reveal that while pooling charging demands alone does not justify centralized charging due to order batching and transportation lead time effects, centralized charging becomes advantageous under urban grid capacity limits that restrict decentralized fast charging. The work also identifies operational flexibilities in reorder quantities and charging station deployment that allow adaptation to economic and urban complexities, contributing to the understanding of mobility-energy integration in smart city development.