Abstract
Nowadays, the equivalent circuit approach is one of the most used methods for modeling electrochemical cells. The main advantage consists in the beneficial trade-off between accuracy and complexity that makes these models very suitable for the State of Charge (SoC) estimation task. However, parameters identification could be difficult to perform, requiring very long and specific tests upon the cell. Thus, a more flexible identification procedure based on an improved Particle Swarm Optimization that does not require specific and time consuming measurements is proposed and validated. The results show that the proposed method achieves a robust parameters identification, resulting in very accurate performances both in the model accuracy and in the SoC estimation task.
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Luzi, M., Paschero, M., Rizzi, A., Mascioli, F.M.F. (2019). An Improved PSO for Flexible Parameters Identification of Lithium Cells Equivalent Circuit Models. In: Esposito, A., Faundez-Zanuy, M., Morabito, F., Pasero, E. (eds) Neural Advances in Processing Nonlinear Dynamic Signals. WIRN 2017 2017. Smart Innovation, Systems and Technologies, vol 102. Springer, Cham. https://doi.org/10.1007/978-3-319-95098-3_21
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