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Characterization of a Practical-Based Ohmic Series Resistance Model under Life-Cycle Changes for a Lithium-Ion Battery

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  • Natthawuth Somakettarin

    (Department of Electrical Engineering, Rajamangala University of Technology Thanyaburi, 39 Klongluang, Patumthani 12110, Thailand)

  • Achara Pichetjamroen

    (Department of Electrical Engineering, Faculty of Engineering, Kasetsart University, 50 Chatuchak, Bangkok 10900, Thailand)

Abstract

Understanding battery characteristic behaviors is indispensable in designing and managing large-scale battery-based energy storage systems in high-power applications. This paper presents a practical-based characterization method to model the ohmic series resistance of lithium-ion batteries under life-cycle consideration. Aging cells were prepared in a controlled environment, and the testing information was automatically characterized using a developed computer-based battery test system. An experimental methodology based on the cycling of pulse tests is applied for modeling the ohmic series resistance. Several aspects of the testing parameters during the cycling operations, such as the characteristic changes of the ohmic series resistance, amplitudes of the periodic test current, cell capacity, state of charge, and the rate of change of the resistance increment, are also investigated and analyzed so as to fulfill the resistance model. The accuracy of the proposed model is verified by comparing the testing information, showing a satisfactory result.

Suggested Citation

  • Natthawuth Somakettarin & Achara Pichetjamroen, 2019. "Characterization of a Practical-Based Ohmic Series Resistance Model under Life-Cycle Changes for a Lithium-Ion Battery," Energies, MDPI, vol. 12(20), pages 1-11, October.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:20:p:3888-:d:276471
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    References listed on IDEAS

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    1. Haifeng Dai & Bo Jiang & Xuezhe Wei, 2018. "Impedance Characterization and Modeling of Lithium-Ion Batteries Considering the Internal Temperature Gradient," Energies, MDPI, vol. 11(1), pages 1-18, January.
    2. Xiangwei Guo & Longyun Kang & Yuan Yao & Zhizhen Huang & Wenbiao Li, 2016. "Joint Estimation of the Electric Vehicle Power Battery State of Charge Based on the Least Squares Method and the Kalman Filter Algorithm," Energies, MDPI, vol. 9(2), pages 1-16, February.
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    Cited by:

    1. Nickolay I. Shchurov & Sergey I. Dedov & Boris V. Malozyomov & Alexander A. Shtang & Nikita V. Martyushev & Roman V. Klyuev & Sergey N. Andriashin, 2021. "Degradation of Lithium-Ion Batteries in an Electric Transport Complex," Energies, MDPI, vol. 14(23), pages 1-33, December.
    2. Andrea Carloni & Federico Baronti & Roberto Di Rienzo & Roberto Roncella & Roberto Saletti, 2020. "Effect of the DC-Link Capacitor Size on the Wireless Inductive-Coupled Opportunity-Charging of a Drone Battery," Energies, MDPI, vol. 13(10), pages 1-13, May.

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