Optimising Electric Flex-Route Feeder Transit Service with Dynamic Wireless Charging Technology

Tianyang GAO; Dawei HU; Gang CHEN; Steven CHIEN; Bingshan MA

doi:10.7307/ptt.v36i4.494

Authors

Tianyang GAO Chang’an University, School of Transportation Engineering
Dawei HU Chang’an University, School of Transportation Engineering
Gang CHEN Zhejiang Scientific Research Institute of Transport
Steven CHIEN Chang’an University, School of Transportation Engineering; New Jersey Institute of Technology, Department of Civil and Environmental Engineering
Bingshan MA Zhejiang Scientific Research Institute of Transport

DOI:

https://doi.org/10.7307/ptt.v36i4.494

Keywords:

flex-route feeder transit, electric bus, dynamic wireless charging, opportunity charging, hybrid variable neighbourhood search

Abstract

The emergence of battery electric buses (BEBs) can alleviate environmental problems caused by tailpipe emissions in transit system. However, the high cost of on-board batteries and range anxiety hinder its further development. Recently, the advent of dynamic wireless power transfer technology (DWPT) has become a potential solution to promote the development of BEBs. Hence, this study focuses on the application of DWPT in flex-route transit system. A mixed integer non-linear model is proposed to simultaneously optimise the bus routing and the selection of corresponding bus types considering the constraints of passengers’ travel time, battery size and bus capacity. The objective is to minimise both transit agency cost and passengers’ travel time cost. A tangible hybrid variable neighbourhood search (HVNS) consisting of simulated annealing (SA) and variable neighbourhood search (VNS) is developed to solve the proposed model efficiently. Compared with GAMS (DICOPT solver) and VNS, the proposed algorithm can considerably improve computational efficiency. The results suggest that the proposed model can effectively determine the BEBs’ routing and bus type for flex-route transit system powered by DWPT through a case study in Xi’an China. A comparative analysis shows the proposed model takes 12.97% less total cost than the alternative model with terminal charging technology (TCT).

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