Joint optimization of electric bus charging infrastructure, vehicle scheduling, and charging management
Document Type
Journal Article
Publication Date
2023
Subject Area
place - north america, mode - bus, technology - alternative fuels, infrastructure - fleet management, infrastructure - vehicle, operations - scheduling
Keywords
Battery electric bus (BEB), charging infrastructure, vehicle scheduling
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.
Rights
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Recommended Citation
He, Y., Liu, Z., & Song, Z. (2023). Joint optimization of electric bus charging infrastructure, vehicle scheduling, and charging management. Transportation Research Part D: Transport and Environment, 117, 103653.
Comments
Transportation Research Part D Home Page:
http://www.sciencedirect.com/science/journal/13619209