Nowadays an effective Energy Storage System (ESS) is a fundamental requirement for any effective innovation in the fields of energetic and transportation sustainability. One of the most important device for obtaining efficient ESSs is the Battery Management System (BMS). It includes all the electronic components and algorithms for the monitoring and management of the ESS status. The key task of the BMS is the estimation of the State of Charge. Currently the most promising methods are based on state observers, which require an accurate model of the cell. In this paper a novel technique for modeling the transient behavior of the cell is proposed. It is based on a single nonlinear dipole composed of a standard linear resistor and a nonlinear voltage driven capacitor connected in parallel. A method for the parameters identification based on a Particle Swarm Optimization algorithm has been developed. Both the identification algorithm and the proposed model are validated on a A123 cell obtaining very stable solution and better accuracy with respect to models based on linear components.

A PSO algorithm for transient dynamic modeling of lithium cells through a nonlinear RC filter / Luzi, Massimiliano; Paschero, Maurizio; Rizzi, Antonello; FRATTALE MASCIOLI, Fabio Massimo. - ELETTRONICO. - (2016), pp. 279-286. (Intervento presentato al convegno 2016 IEEE Congress on Evolutionary Computation, CEC 2016 tenutosi a Vancouver, Canada) [10.1109/CEC.2016.7743806].

A PSO algorithm for transient dynamic modeling of lithium cells through a nonlinear RC filter

LUZI, MASSIMILIANO;PASCHERO, Maurizio;RIZZI, Antonello;FRATTALE MASCIOLI, Fabio Massimo
2016

Abstract

Nowadays an effective Energy Storage System (ESS) is a fundamental requirement for any effective innovation in the fields of energetic and transportation sustainability. One of the most important device for obtaining efficient ESSs is the Battery Management System (BMS). It includes all the electronic components and algorithms for the monitoring and management of the ESS status. The key task of the BMS is the estimation of the State of Charge. Currently the most promising methods are based on state observers, which require an accurate model of the cell. In this paper a novel technique for modeling the transient behavior of the cell is proposed. It is based on a single nonlinear dipole composed of a standard linear resistor and a nonlinear voltage driven capacitor connected in parallel. A method for the parameters identification based on a Particle Swarm Optimization algorithm has been developed. Both the identification algorithm and the proposed model are validated on a A123 cell obtaining very stable solution and better accuracy with respect to models based on linear components.
2016
2016 IEEE Congress on Evolutionary Computation, CEC 2016
battery management systems; lithium cells modelling; transient behavior; transient dynamics; parameters identification; identification algorithms; passive filters; bandpass filters; particle swarm optimization (PSO); evolutionary algorithms; energetic sustainability
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
A PSO algorithm for transient dynamic modeling of lithium cells through a nonlinear RC filter / Luzi, Massimiliano; Paschero, Maurizio; Rizzi, Antonello; FRATTALE MASCIOLI, Fabio Massimo. - ELETTRONICO. - (2016), pp. 279-286. (Intervento presentato al convegno 2016 IEEE Congress on Evolutionary Computation, CEC 2016 tenutosi a Vancouver, Canada) [10.1109/CEC.2016.7743806].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/927640
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