Data-Driven Modeling and Open-Circuit Voltage Estimation of Lithium-Ion Batteries

Edgar D. Silva-Vera, Jesus E. Valdez-Resendiz (), Gerardo Escobar, Daniel Guillen, Julio C. Rosas-Caro () and Jose M. Sosa
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Edgar D. Silva-Vera: School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64700, Mexico
Jesus E. Valdez-Resendiz: School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64700, Mexico
Gerardo Escobar: School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64700, Mexico
Daniel Guillen: School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64700, Mexico
Julio C. Rosas-Caro: Facultad de Ingenieria, Universidad Panamericana, Zapopan 45010, Mexico
Jose M. Sosa: Laboratory of Electrical and Power Electronics, Instituto Tecnológico Superior de Irapuato, Irapuato 36821, Mexico

Mathematics, 2024, vol. 12, issue 18, 1-16

Abstract: This article presents a data-driven methodology for modeling lithium-ion batteries, which includes the estimation of the open-circuit voltage and state of charge. Using the proposed methodology, the dynamics of a battery cell can be captured without the need for explicit theoretical models. This approach only requires the acquisition of two easily measurable variables: the discharge current and the terminal voltage. The acquired data are used to build a linear differential system, which is algebraically manipulated to form a space-state representation of the battery cell. The resulting model was tested and compared against real discharging curves. Preliminary results showed that the battery’s state of charge can be computed with limited precision using a model that considers a constant open-circuit voltage. To improve the accuracy of the identified model, a modified recursive least-squares algorithm is implemented inside the data-driven method to estimate the battery’s open-circuit voltage. These last results showed a very precise tracking of the real battery discharging dynamics, including the terminal voltage and state of charge. The proposed data-driven methodology could simplify the implementation of adaptive control strategies in larger-scale solutions and battery management systems with the interconnection of multiple battery cells.

Keywords: data-driven modeling; energy storage; lithium-ion batteries; battery modeling; open-circuit voltage estimation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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