Balancing Cost and Service: Charging-Rate Optimization for Electric Vehicle Battery Swapping

Problem definition: Battery swapping allows electric vehicle (EV) drivers to exchange depleted batteries for fully charged ones at dedicated stations, avoiding the lengthy waits associated with plug-in charging. The viability of this service hinges on maintaining a high service level. Emerging charging technologies enable continuously adjustable rates, allowing stations to flexibly match charging speed with fluctuating demand and thereby, sustain high service levels under limited charging capacity. However, faster charging accelerates battery degradation, raising operational costs. Thus, the battery-swapping station (BSS) faces the central challenge of optimizing charging rate to jointly ensure service quality and cost efficiency. Methodology/results: In this paper, we formulate a stochastic dynamic program (DP) to optimize the charging rate of a BSS under service-level constraints, explicitly accounting for nonlinear battery degradation cost. We show that the optimal policy has a state‐dependent, multithreshold structure. Because solving the DP directly is intractable, we employ a resolving approach to periodically solve a tractable approximation based on robust satisficing, yielding high-quality charging decisions that balance service levels and operating costs. Calibrated with real-world data, extensive simulations show that our approach consistently outperforms a benchmark policy based on sample average approximation. Managerial implications: Our numerical results yield three key insights. (i) Introducing even limited flexibility (two charging rates) substantially improves service levels and reduces costs compared with a fixed-rate policy. (ii) Although fully continuous charging offers additional cost savings, its marginal benefit diminishes as battery costs decline. (iii) The potential investment required for advanced charging infrastructure can offset continuous‐charging benefits. Thus, BSS managers should carefully assess both operational‐cost savings and capital‐investment requirements before adopting advanced charging technologies. Funding: B. Feng was partially supported by the National Natural Science Foundation of China [Grant 72310107001]. H. Sun was supported by the National Natural Science Foundation of China [Grants 72301168, 72472098, and 72542012] and the Shanghai Pujiang Programme [Grant 23PJC062]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2024.1224 .

• 저널Manufacturing & Service Operations Management
• 토픽Electric Vehicles and Infrastructure · Electrical and Electronic Engineering
• DOI10.1287/msom.2024.1224
• 저자Bo Feng, Hailong Sun