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Title: Life cycle assessment and tempo-spatial optimization of deploying dynamic wireless charging technology for electric cars

Abstract

Dynamic wireless power transfer (DWPT), or dynamic wireless charging technology, enables charging-while-driving and offers opportunities for eliminating range anxiety, stimulating market penetration of electric vehicles (EVs), and enhancing the sustainability performance of electrified transportation. However, the deployment of wireless charging lanes on highways and urban road networks can be costly and resource-intensive. A life cycle assessment (LCA) is conducted here to compare the sustainability performance of DWPT applied in a network of highways and urban roads for charging electric passenger cars. The assessment compares DWPT to stationary wireless charging and to conventional plug-in charging using a case study of Washtenaw County in Michigan, USA over 20 years. The LCA is based on three key sustainability metrics: costs, greenhouse gas (GHG) emissions, and energy burdens, encompassing not only the use-phase burdens from electricity and fuel, but also the upfront deployment burdens of DWPT infrastructure. A genetic algorithm is applied to optimize the rollout of DWPT infrastructure both spatially and temporally in order to minimize life cycle costs, GHG, and energy burdens: (1) spatial optimization selects road segments to deploy DWPT considering traffic volume, speed, and pavement remaining service life (RSL); (2) temporal optimization determines in which year to deploy DWPT onmore » a particular road segment considering EV market share growth as a function of DWPT coverage rate, future DWPT cost reduction, and charging efficiency improvement. Results indicate that optimal deployment of DWPT electrifying up to about 3% of total roadway lane-miles reduces life cycle GHG emissions and energy by up to 9.0% and 6.8%, respectively, and enables downsizing of the EV battery capacity by up to 48%, compared to the non-DWPT scenarios. Roadside solar panels and storage batteries are essential to significantly reduce life cycle energy and GHG burdens but bring additional costs. Breakeven analysis indicates a breakeven year for solar charging benefits to pay back the DWPT infrastructure burdens can be less than 20 years for GHG and energy burdens but longer than 20 years for costs. A monetization of carbon emissions of at least $250 per metric tonne of CO2 is required to shift the optimal “pro-cost” deployment to the optimal “pro-GHG” deployment. A roadway segment with volume greater than about 26,000 vehicle counts per day, speed slower than 55 miles per hour (1 mile ≈ 1.609 km), and pavement RSL shorter than 3 years should be given a high priority for early-stage DWPT deployment.« less

Authors:
ORCiD logo [1];  [1];  [2];  [1];  [3];  [4];  [3]
  1. Univ. of Michigan, Ann Arbor, MI (United States). School for Environment and Sustainability
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). National Transportation Research Center
  3. Tsinghua Univ., Beijing (China). State Key Lab. of Control and Simulation of Power System and Generation Equipments. Dept. of Electrical Engineering
  4. Beihang Univ., Beijing (China). School of Transportation Science and Engineering
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Univ. of Michigan, Ann Arbor, MI (United States); Tsinghua Univ., Beijing (China)
Sponsoring Org.:
USDOE; International Science & Technology Cooperation Program of China
OSTI Identifier:
1494872
Alternate Identifier(s):
OSTI ID: 1547852
Grant/Contract Number:  
AC05-00OR22725; AC02-06CH11357; 2016YFE0102200; 7F-30052
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Transportation Research Part C: Emerging Technologies
Additional Journal Information:
Journal Volume: 100; Journal ID: ISSN 0968-090X
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
33 ADVANCED PROPULSION SYSTEMS; wireless charging; dynamic wireless power transfer; optimization; deployment plan; life cycle assessment; electric vehicle

Citation Formats

Bi, Zicheng, Keoleian, Gregory A., Lin, Zhenhong, Moore, Michael R., Chen, Kainan, Song, Lingjun, and Zhao, Zhengming. Life cycle assessment and tempo-spatial optimization of deploying dynamic wireless charging technology for electric cars. United States: N. p., 2019. Web. doi:10.1016/j.trc.2019.01.002.
Bi, Zicheng, Keoleian, Gregory A., Lin, Zhenhong, Moore, Michael R., Chen, Kainan, Song, Lingjun, & Zhao, Zhengming. Life cycle assessment and tempo-spatial optimization of deploying dynamic wireless charging technology for electric cars. United States. https://doi.org/10.1016/j.trc.2019.01.002
Bi, Zicheng, Keoleian, Gregory A., Lin, Zhenhong, Moore, Michael R., Chen, Kainan, Song, Lingjun, and Zhao, Zhengming. 2019. "Life cycle assessment and tempo-spatial optimization of deploying dynamic wireless charging technology for electric cars". United States. https://doi.org/10.1016/j.trc.2019.01.002. https://www.osti.gov/servlets/purl/1494872.
@article{osti_1494872,
title = {Life cycle assessment and tempo-spatial optimization of deploying dynamic wireless charging technology for electric cars},
author = {Bi, Zicheng and Keoleian, Gregory A. and Lin, Zhenhong and Moore, Michael R. and Chen, Kainan and Song, Lingjun and Zhao, Zhengming},
abstractNote = {Dynamic wireless power transfer (DWPT), or dynamic wireless charging technology, enables charging-while-driving and offers opportunities for eliminating range anxiety, stimulating market penetration of electric vehicles (EVs), and enhancing the sustainability performance of electrified transportation. However, the deployment of wireless charging lanes on highways and urban road networks can be costly and resource-intensive. A life cycle assessment (LCA) is conducted here to compare the sustainability performance of DWPT applied in a network of highways and urban roads for charging electric passenger cars. The assessment compares DWPT to stationary wireless charging and to conventional plug-in charging using a case study of Washtenaw County in Michigan, USA over 20 years. The LCA is based on three key sustainability metrics: costs, greenhouse gas (GHG) emissions, and energy burdens, encompassing not only the use-phase burdens from electricity and fuel, but also the upfront deployment burdens of DWPT infrastructure. A genetic algorithm is applied to optimize the rollout of DWPT infrastructure both spatially and temporally in order to minimize life cycle costs, GHG, and energy burdens: (1) spatial optimization selects road segments to deploy DWPT considering traffic volume, speed, and pavement remaining service life (RSL); (2) temporal optimization determines in which year to deploy DWPT on a particular road segment considering EV market share growth as a function of DWPT coverage rate, future DWPT cost reduction, and charging efficiency improvement. Results indicate that optimal deployment of DWPT electrifying up to about 3% of total roadway lane-miles reduces life cycle GHG emissions and energy by up to 9.0% and 6.8%, respectively, and enables downsizing of the EV battery capacity by up to 48%, compared to the non-DWPT scenarios. Roadside solar panels and storage batteries are essential to significantly reduce life cycle energy and GHG burdens but bring additional costs. Breakeven analysis indicates a breakeven year for solar charging benefits to pay back the DWPT infrastructure burdens can be less than 20 years for GHG and energy burdens but longer than 20 years for costs. A monetization of carbon emissions of at least $250 per metric tonne of CO2 is required to shift the optimal “pro-cost” deployment to the optimal “pro-GHG” deployment. A roadway segment with volume greater than about 26,000 vehicle counts per day, speed slower than 55 miles per hour (1 mile ≈ 1.609 km), and pavement RSL shorter than 3 years should be given a high priority for early-stage DWPT deployment.},
doi = {10.1016/j.trc.2019.01.002},
url = {https://www.osti.gov/biblio/1494872}, journal = {Transportation Research Part C: Emerging Technologies},
issn = {0968-090X},
number = ,
volume = 100,
place = {United States},
year = {2019},
month = {1}
}

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Cited by: 4 works
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Works referenced in this record:

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Works referencing / citing this record:

Life Cycle Assessment of an On-Road Dynamic Charging Infrastructure
journal, August 2019