Optimal electric bus fleet scheduling considering battery degradation and non-linear charging profile
Journal article, 2021

This study aims to determine the battery electric bus service and charging strategy to minimize the total operational cost of transit system, where the cost incurred by battery degradation and non-linear charging profile is taken into account. We formulate a set partitioning model for this problem, subject to predefined trip schedule and limited charging facilities. A tailored branch-and-price approach is then proposed to find the global optimal solution. In particular, we develop an effective multi-label correcting method to deal with the pricing problem (i.e., generating columns) in column generation procedure within the branch-and-price framework, coupled with a dual stabilization technique with an aim to accelerate the convergence rate. Meanwhile, a branch-and-bound solution approach is adopted to guarantee optimal integer solutions. Numerical experiments and a case study arising from real transit network are conducted to further assess the efficiency and applicability of the proposed method. Our experiments confirm that, despite the complexity of the considered problem, optimal solution can still be generated within reasonable computational time using the proposed algorithm. The results also show considerable cost saving (about 10.1–27.3% less) if this optimization model is implemented, mainly contributed by the substantial extension of battery life. A number of managerial insights stemmed from the numerical case study are outlined, which can help transit operators formulate more cost-efficient electric bus fleet scheduling plans.

Electric bus scheduling

Nonlinear charging profile

Branch-and-price approach

Battery degradation

Limited charging facilities

Author

Le Zhang

Nanjing University of Science and Technology

Chalmers, Architecture and Civil Engineering, Geology and Geotechnics

Shuaian Wang

Hong Kong Polytechnic University

Xiaobo Qu

Chalmers, Architecture and Civil Engineering, Geology and Geotechnics

Transportation Research Part E: Logistics and Transportation Review

1366-5545 (ISSN)

Vol. 154 102445

Subject Categories

Computational Mathematics

Control Engineering

Computer Science

DOI

10.1016/j.tre.2021.102445

More information

Latest update

9/16/2021