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

Abstract

Correct information of battery internal variables is crucial for health-conscious and optimal battery management. Because of lack of measurements, advanced Battery Management Systems (BMS) rely heavily on estimation algorithms that provide such internal information. Although algorithms for cell-level charge and health estimation have been widely explored in literature, algorithms for electrode-level quantities are almost non-existent. 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, we propose a real-time algorithm that estimates the available charge and health of individual electrodes. We halt 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.

Authors:
 [1]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [2];  [2]
  1. Univ. of Colorado, Denver, CO (United States)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)
OSTI Identifier:
1544997
Report Number(s):
NREL/JA-5400-71789
Journal ID: ISSN 0278-0046
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
IEEE Translations on Industrial Electronics
Additional Journal Information:
Journal Volume: 67; Journal Issue: 3; Journal ID: ISSN 0278-0046
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
25 ENERGY STORAGE; batteries; electrode-level estimation; state-of-charge; capacity; state-of-health

Citation Formats

Dey, Satadru, Shi, Ying, Smith, Kandler, Colclasure, Andrew, and Li, Xuemin. From Battery Cell to Electrodes: Real-time Estimation of Charge and Health of Individual Battery Electrodes. United States: N. p., 2019. Web. doi:10.1109/TIE.2019.2907514.
Dey, Satadru, Shi, Ying, Smith, Kandler, Colclasure, Andrew, & Li, Xuemin. From Battery Cell to Electrodes: Real-time Estimation of Charge and Health of Individual Battery Electrodes. United States. doi:10.1109/TIE.2019.2907514.
Dey, Satadru, Shi, Ying, Smith, Kandler, Colclasure, Andrew, and Li, Xuemin. Mon . "From Battery Cell to Electrodes: Real-time Estimation of Charge and Health of Individual Battery Electrodes". United States. doi:10.1109/TIE.2019.2907514. https://www.osti.gov/servlets/purl/1544997.
@article{osti_1544997,
title = {From Battery Cell to Electrodes: Real-time Estimation of Charge and Health of Individual Battery Electrodes},
author = {Dey, Satadru and Shi, Ying and Smith, Kandler and Colclasure, Andrew and Li, Xuemin},
abstractNote = {Correct information of battery internal variables is crucial for health-conscious and optimal battery management. Because of lack of measurements, advanced Battery Management Systems (BMS) rely heavily on estimation algorithms that provide such internal information. Although algorithms for cell-level charge and health estimation have been widely explored in literature, algorithms for electrode-level quantities are almost non-existent. 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, we propose a real-time algorithm that estimates the available charge and health of individual electrodes. We halt 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.},
doi = {10.1109/TIE.2019.2907514},
journal = {IEEE Translations on Industrial Electronics},
issn = {0278-0046},
number = 3,
volume = 67,
place = {United States},
year = {2019},
month = {4}
}

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