Joint Optimization of Electric Bus Charging Infrastructure, Vehicle Scheduling, and Charging Management

Yi He, Zhaocai Liu, Ziqi Song

Research output: Contribution to journalArticlepeer-review

13 Scopus Citations

Abstract

High upfront costs of vehicles and charging infrastructure as well as the lack of knowledge related to infrastructure planning and electric bus system operation are major obstacles to the implementation of battery electric buses (BEBs). To tackle the obstacles and promote BEB adoption, a comprehensive optimization framework was developed to address the combined charging infrastructure planning, vehicle scheduling, and charging management problem for BEB systems, with the goal to minimize the total cost of ownership. The problem was formulated as a mixed-integer non-linear problem. A genetic algorithm-based approach was then proposed to solve the problem. Last, three alternative scenarios based on a sub-transit network in Salt Lake City, Utah, were analyzed and compared with the optimal scenario results in the numerical experiments. The comparison results demonstrate the effectiveness of the proposed model and solution algorithm in determining a cost-efficient planning strategy for BEB systems.

Original languageAmerican English
Article numberArticle No. 103653
Number of pages23
JournalTransportation Research Part D: Transport and Environment
Volume117
DOIs
StatePublished - Apr 2023

Bibliographical note

Publisher Copyright:
© 2023 Elsevier Ltd

NREL Publication Number

  • NREL/JA-2C00-85306

Keywords

  • charging infrastructure planning
  • charging management
  • comprehensive system optimization
  • electric buses
  • vehicle scheduling

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