Data-Driven Health Management of Electrical Vehicle Battery Systems

The objectives of this project are 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 alarming system for early awareness of these potential impending failures. The proposed battery health management paradigm consists of an intelligent system modeler and an estimator, with the goal to perceive performance characteristics of the true dynamic system. Multi-physics-based battery failure simulation and laboratory experimental investigations will be used to demonstrate and validate the proposed new battery health management paradigm. Experiments of battery failures will be conducted in collaboration with an industry partner. The experimental results will be used to validate the proposed SCDS battery health management technique and demonstrate the anticipated performance.

Language

  • English

Project

  • Status: Active
  • 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: 0
  • 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