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Continuous Battery Health Diagnosis by On-Line Internal Resistance Measuring

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  • Jaime de la Peña Llerandi

    (Dpto. Ingeniería Eléctrica, Electrónica, Control, Telemática y Química Aplicada a la Ingeniería, Universidad Nacional de Educación a Distancia (UNED), E.T.S. de Ingenieros Industriales, cl/Juan del Rosal, 12, 28040 Madrid, Spain)

  • Carlos Sancho de Mingo

    (Dpto. Ingeniería Eléctrica, Electrónica, Control, Telemática y Química Aplicada a la Ingeniería, Universidad Nacional de Educación a Distancia (UNED), E.T.S. de Ingenieros Industriales, cl/Juan del Rosal, 12, 28040 Madrid, Spain)

  • José Carpio Ibáñez

    (Dpto. Ingeniería Eléctrica, Electrónica, Control, Telemática y Química Aplicada a la Ingeniería, Universidad Nacional de Educación a Distancia (UNED), E.T.S. de Ingenieros Industriales, cl/Juan del Rosal, 12, 28040 Madrid, Spain)

Abstract

Energy storage in an uninterruptible power supply (UPS) is one of the most frequent applications of batteries. This can be found in hospitals, communication centers, public centers, ships, trains, etc. Most frequent industrial methods for battery state-of health estimation require a technician to move to the battery’s location and, in some cases, require the use of heavy equipment and disconnection of the battery from the UPS. For example, in railway applications, trains must stop at the maintenance depot producing significant total costs. This article proposes a new method to assess a battery’s health by measuring the battery’s internal resistance, based on the measurement of its voltage ripple in response to the current ripple imposed by the charger which in most UPS applications is permanently connected to the battery. Unlike most traditional methods, this system makes it possible a continuous on-line and on-board monitoring, and, therefore, it eases condition-based maintenance (CBM). To verify its viability, a low cost measuring prototype has been built and measurements in a railway battery with its charger have been carried out.

Suggested Citation

  • Jaime de la Peña Llerandi & Carlos Sancho de Mingo & José Carpio Ibáñez, 2019. "Continuous Battery Health Diagnosis by On-Line Internal Resistance Measuring," Energies, MDPI, vol. 12(14), pages 1-13, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:14:p:2836-:d:250916
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    References listed on IDEAS

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    1. Sergio Saponara, 2016. "Distributed Measuring System for Predictive Diagnosis of Uninterruptible Power Supplies in Safety-Critical Applications," Energies, MDPI, vol. 9(5), pages 1-18, April.
    2. Ng, Kong Soon & Moo, Chin-Sien & Chen, Yi-Ping & Hsieh, Yao-Ching, 2009. "Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries," Applied Energy, Elsevier, vol. 86(9), pages 1506-1511, September.
    3. Ming-Hui Chang & Han-Pang Huang & Shu-Wei Chang, 2013. "A New State of Charge Estimation Method for LiFePO 4 Battery Packs Used in Robots," Energies, MDPI, vol. 6(4), pages 1-24, April.
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    1. Péter Földesi & László T. Kóczy & Ferenc Szauter & Dániel Csikor & Szabolcs Kocsis Szürke, 2022. "Hierarchical Diagnostics and Risk Assessment for Energy Supply in Military Vehicles," Energies, MDPI, vol. 15(13), pages 1-16, June.

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