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Title: An Electric Vehicle Routing Optimization Model With Hybrid Plug-In and Wireless Charging Systems

Abstract

In order to address the inconvenience of having to stop to charge the battery of an electric vehicle, wireless on-road charging technology, also known as charge-while-driving, has garnered much attention in recent studies. However, wireless charging devices may have a higher charge cost than traditional plug-in charging devices. Therefore, a multi-objective route optimization model based on model predictive control is established in this paper to determine an optimal route for drivers to coordinate wireless and plug-in charging strategies. To reduce the complexity of the proposed model due to its bilinear terms, the Big-M approach is employed to exactly linearize the bilinear terms by introducing dummy variables and additional constraints, which leads to a mixed integer linear programming model that can be solved efficiently. Lastly, two systems are tested, including a real-world road map in Xi'an city to demonstrate the effectiveness of the proposed model.

Authors:
 [1]; ORCiD logo [1];  [1];  [2]
  1. Xi'an Jiaotong Univ., Xi'an (China)
  2. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1477823
Report Number(s):
LLNL-JRNL-750227
Journal ID: ISSN 2169-3536; 935181
Grant/Contract Number:  
AC52-07NA27344
Resource Type:
Accepted Manuscript
Journal Name:
IEEE Access
Additional Journal Information:
Journal Volume: 6; Journal Issue: na; Journal ID: ISSN 2169-3536
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; electric vehicles; mixed integer linear programming; plug-in charging; route optimization; wireless charging

Citation Formats

Li, Cheng, Ding, Tao, Liu, Xiyuan, and Huang, Can. An Electric Vehicle Routing Optimization Model With Hybrid Plug-In and Wireless Charging Systems. United States: N. p., 2018. Web. doi:10.1109/ACCESS.2018.2832187.
Li, Cheng, Ding, Tao, Liu, Xiyuan, & Huang, Can. An Electric Vehicle Routing Optimization Model With Hybrid Plug-In and Wireless Charging Systems. United States. doi:10.1109/ACCESS.2018.2832187.
Li, Cheng, Ding, Tao, Liu, Xiyuan, and Huang, Can. Wed . "An Electric Vehicle Routing Optimization Model With Hybrid Plug-In and Wireless Charging Systems". United States. doi:10.1109/ACCESS.2018.2832187. https://www.osti.gov/servlets/purl/1477823.
@article{osti_1477823,
title = {An Electric Vehicle Routing Optimization Model With Hybrid Plug-In and Wireless Charging Systems},
author = {Li, Cheng and Ding, Tao and Liu, Xiyuan and Huang, Can},
abstractNote = {In order to address the inconvenience of having to stop to charge the battery of an electric vehicle, wireless on-road charging technology, also known as charge-while-driving, has garnered much attention in recent studies. However, wireless charging devices may have a higher charge cost than traditional plug-in charging devices. Therefore, a multi-objective route optimization model based on model predictive control is established in this paper to determine an optimal route for drivers to coordinate wireless and plug-in charging strategies. To reduce the complexity of the proposed model due to its bilinear terms, the Big-M approach is employed to exactly linearize the bilinear terms by introducing dummy variables and additional constraints, which leads to a mixed integer linear programming model that can be solved efficiently. Lastly, two systems are tested, including a real-world road map in Xi'an city to demonstrate the effectiveness of the proposed model.},
doi = {10.1109/ACCESS.2018.2832187},
journal = {IEEE Access},
number = na,
volume = 6,
place = {United States},
year = {2018},
month = {5}
}

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