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Open AccessArticle

Optimizing Wireless Charging Locations for Battery Electric Bus Transit with a Genetic Algorithm

1
School of Transportation Engineering, Chang’an University, 710054 Xi’an, China
2
John A. Reif, Jr. Department of Civil and Environmental Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA
3
Systems Engineering Institute, AMS, 100071 Beijing, China
*
Authors to whom correspondence should be addressed.
Sustainability 2020, 12(21), 8971; https://doi.org/10.3390/su12218971
Received: 21 September 2020 / Revised: 20 October 2020 / Accepted: 22 October 2020 / Published: 29 October 2020
(This article belongs to the Section Sustainable Transportation)
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. View Full-Text
Keywords: dynamic wireless power transfer; electric bus; transportation network planning; genetic algorithm dynamic wireless power transfer; electric bus; transportation network planning; genetic algorithm
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MDPI and ACS Style

Chen, G.; Hu, D.; Chien, S.; Guo, L.; Liu, M. Optimizing Wireless Charging Locations for Battery Electric Bus Transit with a Genetic Algorithm. Sustainability 2020, 12, 8971.

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