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.

An improved PSO for flexible parameters identification of lithium cells equivalent circuit models / Luzi, Massimiliano; Paschero, Maurizio; Rizzi, Antonello; Mascioli, Fabio Massimo Frattale. - (2019), pp. 229-238. - SMART INNOVATION, SYSTEMS AND TECHNOLOGIES. [10.1007/978-3-319-95098-3_21].

An improved PSO for flexible parameters identification of lithium cells equivalent circuit models

Luzi, Massimiliano;Paschero, Maurizio;Rizzi, Antonello;Mascioli, Fabio Massimo Frattale
2019

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.
2019
Smart Innovation, Systems and Technologies
978-3-319-95097-6
978-3-319-95098-3
Lithium cells; equivalent circuit model; state of charge; parameters identification; particle swarm optimization; battery management system
02 Pubblicazione su volume::02a Capitolo o Articolo
An improved PSO for flexible parameters identification of lithium cells equivalent circuit models / Luzi, Massimiliano; Paschero, Maurizio; Rizzi, Antonello; Mascioli, Fabio Massimo Frattale. - (2019), pp. 229-238. - SMART INNOVATION, SYSTEMS AND TECHNOLOGIES. [10.1007/978-3-319-95098-3_21].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1215837
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