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Demonstrates improved parameter estimation in lithium-ion batteries, suggesting enhanced accuracy for battery management systems.
This paper presents a novel Decoupled Optimization Algorithm (DOA) to estimate lithium‐ion battery equivalent circuit parameters. The algorithm precisely models the dynamic behavior of LIBs during both the discharge and relaxation phases. Its main innovation lies in its ability to estimate parameters for each operating state independently, resulting in a more accurate model. The DOA is notably robust, as it naturally avoids premature convergence without requiring empirical hyperparameter tuning or training data. In addition, the model includes boundary conditions that guarantee a mathematically and physically sound solution, which streamlines the search process. Experimental validation in five different discharge rates confirmed that the DOA achieves superior accuracy in parameter estimation compared to established algorithms such as GA, PSO, CSA, and VLCS. These results underscore its potential for practical battery management applications.
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Santos et al. (2026) studied this question.
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