State of health battery estimator enabling degradation diagnosis: Model and algorithm description

By Matthieu Dubarry, Maitane Berecibar, A. Devie, David Anseán, Noshin Omar, I. Villarreal. 2017

148 citations recorded by the source corpus.

Abstract This paper presents a novel approach for automated state of health estimation that offers similar advantages to the adaptive methods without being computation intensive. The onboard diagnosis uses a look-up table compiling the evolution of selected features of interest under any possible degradation paths. The look-up table is built from simulations of the impact of degradation on the cell electrochemical behavior. This multi-step method only requires intensive calculations prior to deployment. This approach is validated by experimental data from cells that underwent normal aging as well as plating and overcharge. Additional validation via modeling showed that the method is able to diagnose cells undergoing any degradation scenario automatically in close to 90% of cases.

Subfields: Automotive Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/282bf95e12c111b910c8c75acaf928c2ec8d8df7