User-based Battery Swapping Strategy in an Electric Bike-sharing System

With the recent popularity of shared electric bikes, the operators have been widely concerned about the high cost of battery swapping. At present, most platforms use trucks to visit the parking stations to swap the batteries of electric bikes with low power, which is inefficient and environmentally unfriendly. This paper proposes a user-based battery swapping strategy to rationalize users’ riding behavior through incentives. Specifically, e-bikes with low power are recommended to selected users according to their destination to realize the concentration of low-power e-bikes at certain stations, which will relieve the task of battery-swapping trucks. This strategy is modeled as an integer programming problem to decide station selection, user relocation, and truck routing. A variable neighborhood search algorithm is designed to solve the problem. Numerical results on different instances and a real-world case verify the effectiveness of our model and method.