From Battery Cell to Electrodes: Real-Time Estimation of Charge and Health of Individual Battery Electrodes

Satadru Dey, Ying Shi, Kandler Smith, Andrew Colclasure, Xuemin Li

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Accurate information of battery internal variables is crucial for health-conscious and optimal battery management. Due to lack of measurements, advanced battery management systems rely heavily on estimation algorithms that provide such internal information. Although algorithms for cell-level charge and health estimation have been widely explored in the literature, algorithms for electrode-level quantities are almost nonexistent. The main obstacle in electrode-level estimation is the observability problem where the individual electrode states are not observable from terminal voltage output. However, if available, real-time feedback of electrode-level charge and health can be highly beneficial in maximizing energy utilization and battery life. Motivated by this scenario, in this paper we propose a real-time algorithm that estimates the available charge and health of individual electrodes. We circumvent the aforementioned observability problem by proposing an uncertain model-based cascaded estimation framework. The design and analysis of the proposed scheme are aided by a combination of Lyapunov's stability theory, adaptive observer theory, and interconnected systems theory. Finally, we illustrate the effectiveness of the estimation scheme by performing extensive simulation and experimental studies.

Original languageEnglish (US)
Article number8678658
Pages (from-to)2167-2175
Number of pages9
JournalIEEE Transactions on Industrial Electronics
Volume67
Issue number3
DOIs
StatePublished - Mar 2020

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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