A novel ranking method based on semi-SPO for battery swapping allocation optimization in a hybrid electric transit system

Document Type

Journal Article

Publication Date

2024

Subject Area

place - asia, mode - bus, infrastructure - fleet management, infrastructure - vehicle, technology - alternative fuels

Keywords

electric bus (EB), state of charge (SOC), battery swapping

Abstract

The allocation of batteries in hybrid charging stations has consistently played a significant role in the decision-making process for plug-in charging and battery swapping. Predicting the state of charge (SOC) for each electric bus (EB) in advance is crucial to assist in making future battery allocation decisions. This paper proposes a semi-Smart “Predict, then Optimize” (semi-SPO) framework for the battery allocation scheduling problem. The battery allocation optimization problem is reduced to a ranking problem with respect to SOC and integrated into the prediction model. The rank of SOC is determined from both pairwise and listwise perspectives. Considering the inherent characteristics of rankwise regression, such as missing parameters and infinite number of optimal solutions, a geometric analysis is conducted. A model enhancement approach is then proposed to ensure the accuracy of both prediction and optimization models. This enhancement facilitates optimal decision-making while preserving the interpretability of predicted values. A case study is conducted using the real-world data of Nanjing, China. The result shows that the proposed semi-SPO framework offers superior decision-making outcomes in the battery allocation pro.

Rights

Permission to publish the abstract has been given by Elsevier, copyright remains with them.

Comments

Transportation Research Part E Home Page:

http://www.sciencedirect.com/science/journal/13665545

Link to Full Text

Share

COinS