Data-Driven Health Management of Electrical Vehicle Battery Systems
The objectives of this research were to conduct theoretical and experimental investigations to develop a new battery health management paradigm based on a novel, self-cognizant dynamic system (SCDS) approach to predict and prevent failures of safety-critical battery systems (e.g., lithium plating and thermal runaway) for electric vehicles (EVs) and hybrid electric vehicles (HEVs) and develop an onboard diagnostics tool and alarm system for early awareness of these potential impending failures. This research developed a technique that can adaptively recognize the dynamic characteristics of an operating battery system over time without relying on expensive, time-consuming battery tests for the prediction and prevention of safety-critical battery system failures. Battery failure prognostics employing the proposed SCDS-based health management paradigm can not only account for normal battery capacity fading over time but also identify abnormal safety-critical failures that usually happen in a relatively shorter time period.
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Supplemental Notes:
- Midwest Transportation Center USDOT/OST-R ($49,000.00) Wichita State University ($49,000.00)
Language
- English
Project
- Status: Completed
- Funding: $98000.00
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Contract Numbers:
DTRT13-G-UTC37
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Sponsor Organizations:
Wichita State University
1845 Fairmount
Wichita, KS United States 67260 Office of the Assistant Secretary for Research and Technology
1200 New Jersey Avenue, SE
Washington, DC United States 20590 Iowa State University
2711 S Loop Drive, Suite 4700
Ames, IA United States 50010-8664 -
Managing Organizations:
Iowa State University
2711 S Loop Drive, Suite 4700
Ames, IA United States 50010-8664 -
Performing Organizations:
Wichita State University
1845 Fairmount
Wichita, KS United States 67260 -
Principal Investigators:
Krishnan, Krishna
Wang, Pingfeng
- Start Date: 20141001
- Expected Completion Date: 20170930
- Actual Completion Date: 20180629
- Source Data: RiP Project 39622
Subject/Index Terms
- TRT Terms: Electric vehicle charging; Electric vehicles; Energy storage systems; Hybrid vehicles; Intelligent transportation systems; Intelligent vehicles; Lithium batteries
- Subject Areas: Highways; Vehicles and Equipment;
Filing Info
- Accession Number: 01562684
- Record Type: Research project
- Source Agency: Midwest Transportation Center
- Contract Numbers: DTRT13-G-UTC37
- Files: UTC, RiP
- Created Date: May 2 2015 1:00AM