TY - JOUR
T1 - Electric vehicle fleet size for carsharing services considering on-demand charging strategy and battery degradation
AU - Xu, Min
AU - Wu, Ting
AU - Tan, Zhijia
N1 - Funding Information:
This research is supported by the National Natural Science Foundation of China (No. 71901189), the Research Grants Council of the Hong Kong Special Administrative Region, China (PolyU 25207319), and the Hong Kong Polytechnic University (UAHJ).
Publisher Copyright:
© 2021
PY - 2021/6
Y1 - 2021/6
N2 - 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.
AB - 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.
KW - Battery wear cost
KW - Electric vehicle fleet size
KW - Model linearization
KW - On-demand charging strategy
UR - http://www.scopus.com/inward/record.url?scp=85104346493&partnerID=8YFLogxK
U2 - 10.1016/j.trc.2021.103146
DO - 10.1016/j.trc.2021.103146
M3 - Journal article
AN - SCOPUS:85104346493
SN - 0968-090X
VL - 127
JO - Transportation Research Part C: Emerging Technologies
JF - Transportation Research Part C: Emerging Technologies
M1 - 103146
ER -