Using data to develop cost-effective battery-swap networks for electric vehicles

Abstract

Electric vehicle (EV) development faces the challenges of range anxiety and the high construction and operating costs of charging and battery-swap infrastructure. To address these issues, this paper describes a proposed battery-swap network (BSN) comprising battery-swapping van service points and battery-swap stations to provide local, fast and cost-effective battery-swapping services. A data-driven approach was developed to analyse and model vehicle trajectory data to obtain realistic battery-swap demand distributions. An optimisation model based on location cover was then developed to minimise the cost of a BSN using a greedy algorithm. Real traffic network driving distance was adopted to improve authenticity and accuracy. In a case study, a BSN used a 1 week trajectory data set of taxis in Beijing, China and tested the effects in eight scenarios. The results showed that the mesh size of service points, service radius and coverage rate all had an impact on service quality and cost. It is concluded that a BSN could be cost-effectively deployed by adjusting these parameters to suit the needs of EVs at different development stages. This paper provides a useful reference for decision makers and operators to formulate policies and strategies.