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Detection of Low Electrolyte Level for Vented Lead–Acid Batteries Based on Electrical Measurements

Author

Listed:
  • Eugenio Camargo

    (Faculty of Engineering, University of San Luis Potosí, San Luis Potosí 78290, Mexico)

  • Nancy Visairo

    (Faculty of Engineering, University of San Luis Potosí, San Luis Potosí 78290, Mexico)

  • Ciro Núñez

    (Faculty of Engineering, University of San Luis Potosí, San Luis Potosí 78290, Mexico)

  • Juan Segundo

    (Faculty of Engineering, University of San Luis Potosí, San Luis Potosí 78290, Mexico)

  • Juan Cuevas

    (Faculty of Engineering, University of San Luis Potosí, San Luis Potosí 78290, Mexico)

  • Dante Mora

    (Faculty of Engineering, University of San Luis Potosí, San Luis Potosí 78290, Mexico)

Abstract

It is well known that a low level of electrolytes in batteries produces a malfunction or even failure and irreversible damage. There are several kinds of sensors to detect the electrolyte level. Some of them are non-invasive, such as optical sensors of level, while some others are invasive; but both require one sensor per battery. This paper proposes a different approach to detect the low electrolyte level, which neither requires invasive sensors nor one sensor for each battery. The approach is based on the estimation of the internal resistance of an equivalent electrical circuit (EEC) model of the battery. To establish the detection criterion of the low level of electrolytes, a statistical analysis is proposed. To demonstrate the feasibility of this approach to be considered a valid method, multiple experiments were performed. The experiments consisted of determining how the internal resistance is affected at eight different levels of electrolyte at different aging levels of vented lead–acid (VLA) batteries. The results have demonstrated the feasibility of this approach. Hence, this approach has the potential to be used for the reducing of sensors and avoiding invasive methods to determine the low level of electrolytes.

Suggested Citation

  • Eugenio Camargo & Nancy Visairo & Ciro Núñez & Juan Segundo & Juan Cuevas & Dante Mora, 2019. "Detection of Low Electrolyte Level for Vented Lead–Acid Batteries Based on Electrical Measurements," Energies, MDPI, vol. 12(23), pages 1-14, November.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:23:p:4435-:d:289645
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    References listed on IDEAS

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    1. Tao, Laifa & Ma, Jian & Cheng, Yujie & Noktehdan, Azadeh & Chong, Jin & Lu, Chen, 2017. "A review of stochastic battery models and health management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 716-732.
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