Cabinet Location Optimization for E-bike Battery Swapping Systems

A new type of shared battery cabinet for e-bikes is emerging in China, enabling e-bike users to conveniently replace their low-power battery with a fully charged one outdoors. In such an e-bike battery swapping system, the location of the shared battery cabinet is crucial because it affects the system’s operation and user experience. This paper solves the problem of locating the battery cabinet considering the travel habits of riders and the change of battery status in the cabinet over time. This problem is modeled as an optimization model for a p-median location problem. A genetic algorithm incorporating system simulation is proposed for solving the problem. The algorithm’s performance is verified by comparing it with the results of the commercial solver on small-scale problems. Experiments on a real-world case are also conducted.