Electric vehicle fleet size for carsharing services considering on-demand charging strategy and battery degradation

This study addresses the tactical electric vehicle fleet size (EVFS) problem faced by carsharing service (CSS) providers while considering the operational vehicle assignment, vehicle relocation, and vehicle charging strategies (i.e., the charging duration at each station) in pursuit of profit maximization. To alleviate battery degradation and achieve cost-saving in the long term, we propose the on-demand charging strategy to determine fleet size. The novelty of this study lies in the incorporation of nonlinear battery wear cost incurred during the battery charging and discharging processes. A mixed-integer nonlinear programming (MINLP) model with concave and convex terms in the objective function is first developed for the EVFS problem. Piecewise linear approximation approach and outer-approximation method are employed to linearize the proposed model. Numerical experiments based on EVCARD, a one-way electric carsharing operator in China, are conducted to demonstrate the efficiency of the proposed model and solution method, as well as the necessity of incorporating the battery degradation into the fleet size determination of CSSs. The impacts of several key parameters, i.e., the daily fixed cost of EV and battery price, battery cycle efficiency, service charge, and relocation cost on the performance of one-way electric CSSs are also analyzed.

Automated summary

This study proposes an on-demand charging strategy to determine the fleet size of electric vehicles for carsharing service providers, aiming to maximize profits and reduce battery degradation costs. Numerical experiments show the effectiveness of the proposed model and analyze the impact of key parameters on the performance of one-way electric carsharing services.