Abstract
This paper focuses on the development of a tool that includes an automated testbed with controls, protection, and communications integrated into a real-time system to provide a platform to generate data sets for failure modes and effects analysis. This tool establishes a value for automation of data generation for different scenarios and addresses the gap of nonexistent field data for different applications and use cases. The features of this tool can further be expanded to include multiple power electronics models, communication protocols, and scaled system architectures. This general framework was evaluated for a DC fast charger system use case to provide quantitative solution for resiliency.
Original language | English |
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Title of host publication | 2023 IEEE Transportation Electrification Conference and Expo, ITEC 2023 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9798350397420 |
DOIs | |
State | Published - 2023 |
Event | 2023 IEEE Transportation Electrification Conference and Expo, ITEC 2023 - Detroit, United States Duration: Jun 21 2023 → Jun 23 2023 |
Publication series
Name | 2023 IEEE Transportation Electrification Conference and Expo, ITEC 2023 |
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Conference
Conference | 2023 IEEE Transportation Electrification Conference and Expo, ITEC 2023 |
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Country/Territory | United States |
City | Detroit |
Period | 06/21/23 → 06/23/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
Funding
This work was funded by the U.S. Department of Energy, Office of Vehicle Technology under contract number DE-AC05-00OR22725. Notice: This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).
Funders | Funder number |
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Office of Vehicle Technology | DE-AC05-00OR22725 |
U.S. Department of Energy |
Keywords
- EV charging
- automation
- data analytics
- electric vehicles
- resilience