Data-Driven Health Management of Electrical Vehicle Battery Systems

Project status

In progress

Start date: 10/01/14
End date: 09/30/17


Principal investigator:

Co-principal investigator:

About the research

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.


Related publication: Battery System Safety and Health Management for Electric Vehicles Aug 2015



  • Midwest Transportation Center
  • Wichita State University