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

Journal Article · Mon Apr 01 00:00:00 EDT 2019 · IEEE Translations on Industrial Electronics

DOI:https://doi.org/10.1109/TIE.2019.2907514· OSTI ID:1544997

Dey, Satadru ^[1]; Shi, Ying  ^[2]; Smith, Kandler  ^[2]; Colclasure, Andrew  ^[2]; Li, Xuemin ^[2]

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1. Univ. of Colorado, Denver, CO (United States)
2. National Renewable Energy Lab. (NREL), Golden, CO (United States)

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.

• Research Organization: National Renewable Energy Lab. (NREL), Golden, CO (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)
• Grant/Contract Number: AC36-08GO28308
• OSTI ID: 1544997
• Report Number(s): NREL/JA-5400-71789
• Journal Information: IEEE Translations on Industrial Electronics, Vol. 67, Issue 3; ISSN 0278-0046
• Publisher: IEEE
• Country of Publication: United States
• Language: English

Related Subjects

25 ENERGY STORAGE
batteries
electrode-level estimation
state-of-charge
capacity
state-of-health