Optimal design of experiment for parameter estimation of a Single Particle Model for lithium-ion batteries

Andrea Pozzi, Gabriele Ciaramella, Krishnakumar Gopalakrishnan, Stefan Volkwein, Davide M. Raimondo

Risultato della ricerca: Contributo in libroContributo a convegno

Abstract

Advanced battery management systems rely on dynamical models in order to provide safe and profitable battery operations. Such models need to be suitable for control and estimation purposes while, at the same time, as accurate as possible. This feature can be satisfied only if model parameters are accurately estimated. In this work we investigate the design of optimal experiments in order to minimize the uncertainty of the parameters of the Single Particle Model, in the context of Lithium-ion battery. Simulation results show the effectiveness of the proposed methodology when compared with standard current profiles (e.g. constant current).
Lingua originaleEnglish
Titolo della pubblicazione ospite2018 IEEE Conference on Decision and Control (CDC)
Pagine6482-6487
Numero di pagine6
DOI
Stato di pubblicazionePubblicato - 2018
Evento57th IEEE Conference on Decision and Control - United States
Durata: 17 dic 201819 dic 2018

Serie di pubblicazioni

NomePROCEEDINGS OF THE IEEE CONFERENCE ON DECISION & CONTROL

Convegno

Convegno57th IEEE Conference on Decision and Control
CittàUnited States
Periodo17/12/1819/12/18

Keywords

  • Optimal Experimental Design

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