Optimizing wireless charging locations for battery electric bus transit with a genetic algorithm

Document Type

Article

Publication Date

11-1-2020

Abstract

Electrifying bus transit has been deemed as an effective way to reduce the emissions of transit vehicles. However, some concerns about on-board battery hinder its further development. Recently, dynamic wireless power transfer (DWPT) technologies have been developed, which enable buses to charge in-motion and overcome the drawback (short service range) with opportunity charging. This paper proposes a mathematic model which optimizes the locations for DWPT devices deployed at stops and size of battery capacity for battery electric buses (BEB) in a multi-route network, which considers the battery’s service life, depth of discharge and weight. A tangible solution algorithm based on a genetic algorithm (GA) is developed to find the optimal solution. A case study based on the bus network from Xi’an China is conducted to investigate the relationship among optimized costs, greenhouse gas (GHG) emissions, battery service life, size of the battery capacity and the number of DWPT devices. The results demonstrated that a bus network powered by DWPT shows better performance in both costs (a 43.3% reduction) and emissions (a 14.4% reduction) compared to that with stationary charging at bus terminals.

Identifier

85094608611 (Scopus)

Publication Title

Sustainability Switzerland

External Full Text Location

https://doi.org/10.3390/su12218971

e-ISSN

20711050

First Page

1

Last Page

20

Issue

21

Volume

12

Grant

2019218514GXRC021CG022-GXYD21.5

Fund Ref

National Natural Science Foundation of China

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