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.

Language

  • English

Project

  • Status: Completed
  • Funding: $98000.00
  • Contract Numbers:

    DTRT13-G-UTC37

  • Sponsor Organizations:

    Wichita State University

    1845 Fairmount
    Wichita, KS  United States  67260

    Department of Transportation

    Office of the Assistant Secretary for Research and Technology
    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590

    Midwest Transportation Center

    Iowa State University
    2711 S Loop Drive, Suite 4700
    Ames, IA  United States  50010-8664
  • Managing Organizations:

    Midwest Transportation Center

    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

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