Joint Optimization of Battery Swapping Scheduling for Electric Taxis

Zilong Zhao, Daxin Tian (), Xuting Duan and Randong Xiao ()
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Zilong Zhao: School of Transportation Science and Engineering, Beihang University, Beijing 100083, China
Daxin Tian: School of Transportation Science and Engineering, Beihang University, Beijing 100083, China
Xuting Duan: School of Transportation Science and Engineering, Beihang University, Beijing 100083, China
Randong Xiao: Beijing Key Laboratory for Comprehensive Traffific Operation Monitoring and Service, Beijing 100161, China

Sustainability, 2023, vol. 15, issue 18, 1-11

Abstract: Electric taxis are of great benefit to reduce urban polluting gas emissions. Currently, there is a problem of uneven utilization among charging stations in the battery swapping activities of electric taxis, resulting in long battery swapping times for some taxis, which seriously affects operational efficiency. This study examines the real-time joint scheduling of electric taxis for battery swapping. The expense due to battery swapping for each electric taxi was measured as the sum of driving duration before battery swapping, queuing and operating duration during battery swapping, and cruising duration after battery swapping; to our knowledge, these have not been combined in the existing literature. A mathematical model was proposed with the objective of minimizing the total expense of all electric taxis, subject to the battery state-of-charge (SoC) constraint. The proposed model was transformed into a mixed-integer linear program and solved to global optimality by CPLEX. Numerical results validated the performance of our methodology. The results indicate that our proposed methodology can save total expenses by up to 7.61%.

Keywords: battery swapping; cruising duration; electric taxis; queuing duration (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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