Joint planning of dynamic wireless charging lanes and power delivery infrastructure for heavy-duty drayage trucks

Heavy-duty drayage trucks pose a considerable emission burden and health risk, primarily due to their operation in densely populated areas around seaports and intermodal terminals. In response to these concerns, governments are setting ambitious targets for zero-emissions drayage truck transition. As such, the widespread adoption of electric drayage trucks is on the horizon. However, one of the main challenges hindering the mass electrification of drayage trucks is the low readiness of charging infrastructure. Traditional charging stations can lead to long waiting times for truck drivers, which can be detrimental to an industry where timely pickup and delivery are crucial. Dynamic wireless charging lanes (DWCLs) have emerged as a promising alternative or supplement to stationary charging stations by enabling charging-on-the-move. Although electric drayage trucks are potentially the most benefited vehicles from DWCLs, the optimal deployment of DWCLs for them is rarely studied. To address this problem, we propose a framework that focuses on the deployment of DWCLs with special attention paid to drayage trucks, while jointly planning the associated power delivery infrastructure. The proposed planning model identifies the optimal locations of DWCLs in a given transportation network and determines how they will be powered by nearby electrical substations. Additionally, the framework also evaluates whether an upgrade of the electrical substation is needed. A large-scale Global Positioning System (GPS) dataset and an electrical substation dataset, which contain more than 7,000 heavy-duty drayage trucks that span over a period of 12 months and over 255 substations, are utilized to provide the necessary input to the proposed framework. We demonstrate the effectiveness of the proposed framework through a case study conducted on a highway network of more than 1,000 miles around the Greater Los Angeles area, home to two of the world’s busiest seaports, Port of Los Angeles and Port of Long Beach.

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Publication Details

Journal
Applied Energy
Published
2024-08-05
DOI
https://doi.org/10.1016/j.apenergy.2024.124029
Citations
9
Primary Topic
Wireless Power Transfer Systems
Type
article
Field-Weighted Citation Impact
1.88
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article

Joint planning of dynamic wireless charging lanes and power delivery infrastructure for heavy-duty drayage trucks

Ran Wei, Mikhail A. Bragin, Nanpeng Yu, Zuzhao Ye
9 citations
Applied Energy
Wireless Power Transfer Systems
1.88
article

Joint planning of dynamic wireless charging lanes and power delivery infrastructure for heavy-duty drayage trucks

Ran Wei, Mikhail A. Bragin, Nanpeng Yu, Zuzhao Ye
article en
9 citations

Abstract

Heavy-duty drayage trucks pose a considerable emission burden and health risk, primarily due to their operation in densely populated areas around seaports and intermodal terminals. In response to these concerns, governments are setting ambitious targets for zero-emissions drayage truck transition. As such, the widespread adoption of electric drayage trucks is on the horizon. However, one of the main challenges hindering the mass electrification of drayage trucks is the low readiness of charging infrastructure. Traditional charging stations can lead to long waiting times for truck drivers, which can be detrimental to an industry where timely pickup and delivery are crucial. Dynamic wireless charging lanes (DWCLs) have emerged as a promising alternative or supplement to stationary charging stations by enabling charging-on-the-move. Although electric drayage trucks are potentially the most benefited vehicles from DWCLs, the optimal deployment of DWCLs for them is rarely studied. To address this problem, we propose a framework that focuses on the deployment of DWCLs with special attention paid to drayage trucks, while jointly planning the associated power delivery infrastructure. The proposed planning model identifies the optimal locations of DWCLs in a given transportation network and determines how they will be powered by nearby electrical substations. Additionally, the framework also evaluates whether an upgrade of the electrical substation is needed. A large-scale Global Positioning System (GPS) dataset and an electrical substation dataset, which contain more than 7,000 heavy-duty drayage trucks that span over a period of 12 months and over 255 substations, are utilized to provide the necessary input to the proposed framework. We demonstrate the effectiveness of the proposed framework through a case study conducted on a highway network of more than 1,000 miles around the Greater Los Angeles area, home to two of the world’s busiest seaports, Port of Los Angeles and Port of Long Beach.

Applied EnergyVol. 375
University of California, Riverside (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 14%
Wireless Power Transfer Systems
1.88
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