Calculating Available Charge and Energy of Lithium-Ion Cells Based on OCV and Internal Resistance

Fabian Steger, Jonathan Krogh, Lasantha Meegahapola and Hans-Georg Schweiger
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Fabian Steger: CARISSMA Institute of Electric, Connected, and Secure Mobility, Technische Hochschule Ingolstadt, 85049 Ingolstadt, Germany
Jonathan Krogh: Department of Mechanical and Electrical Engineering, University of Southern Denmark, Campusvej 55, 5220 Odense, Denmark
Lasantha Meegahapola: School of Engineering, Royal Melbourne Institute of Technology, 124 La Trobe Street, Melbourne, VIC 3000, Australia
Hans-Georg Schweiger: CARISSMA Institute of Electric, Connected, and Secure Mobility, Technische Hochschule Ingolstadt, 85049 Ingolstadt, Germany

Energies, 2022, vol. 15, issue 21, 1-23

Abstract: The design and operation of performant and safe electric vehicles depend on precise knowledge of the behavior of their electrochemical energy storage systems. The performance of the battery management systems often relies on the discrete-time battery models, which can correctly emulate the battery characteristics. Among the available methods, electric circuit-based equations have shown to be especially useful in describing the electrical characteristics of batteries. To overcome the existing drawbacks, such as discrete-time simulations for parameter estimation and the usage of look-up tables, a set of equations has been developed in this study that solely relies on the open-circuit voltage and the internal resistance of a battery. The parameters can be obtained from typical cell datasheets or can be easily extracted via standard measurements. The proposed equations allow for the direct analytical determination of available discharge capacity and the available energy content depending on the discharge current, as well as the Peukert exponent. The fidelity of the proposed system was validated experimentally using 18650 NMC and LFP lithium-ion cells, and the results are in close agreement with the datasheet.

Keywords: battery management system; electric vehicles; state-of-charge; energy content; mathematical model; Peukert exponent (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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