Electric Bus Charging Scheduling for a Single Public Transport Route Considering Nonlinear Charging Profile and Battery Degradation Effect. (May 2022)

• Record Type: Journal Article
• Authors: Zhou, Yu; Meng, Qiang; Ong, Ghim Ping
• Is Part Of: Transportation research. Volume 159(2022)
• Page Start: 49
• Page End: 75
• Publication Date: 2022-05
• Subjects: Electric bus -- bus-to-trip assignment -- charging scheduling -- battery degradation -- mixed-integer linear programming -- valid inequalities; Transportation -- Research -- Periodicals; Transportation -- Mathematical models -- Periodicals
• DOI: 10.1016/j.trb.2022.03.002
• Languages: English
• ISSNs: 0191-2615

Abstract

Highlights: A mixed-integer non-linear and nonconvex programming (MINL&NCP) model, which captures the unique feature of the EBCS problem is developed. We further approximate it by two novel MILP models in a smart way. Non-linear charging profile and battery degradation effect are considered. Three tailored valid inequalities are proposed to enhance the solution efficiency. Extensive numerical experiments are carried out to seek valuable managerial insights for the public transport operators. Abstract: This study deals with a fundamental electric bus charging scheduling (EBCS) problem for a single public transport route by considering the nonlinear electric bus (EB) charging profile and battery degradation effect under the partial charging policy, which allows EBs to be charged any length of time and make good use of dwell times between consecutive trips. Given a group of trip tasks for an EB fleet and charger type, the problem is to minimize the total cost for a public transport operator of providing peak-hour bus services for a focal single public transport route by simultaneously determining the EB-to-trip assignment and EB charging schedule with charger type choice subject to the necessary EB operational constraints. We first build a mixed-integer nonlinear and nonconvex programming (MINL&NCP) model for the EBCS problem. To effectively solve the MINL&NCP model to global optimality, we subsequently develop two mixed-integer linear programming (MILP) models by means of linearization and approximation techniques. To accelerate the solution efficiency, we further create three families of valid inequalities depending on the unique features of the problem. A real case study based on the No.171 bus route in Singapore is conducted to demonstrate the performance of the developed models. Extensive numerical experiments are carried out to seek valuable managerial insights for public transport operators.