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Linear parameter-varying model for a refuellable zinc–air battery
Author(s) -
Woranunt Lao-atiman,
Sorin Olaru,
D. Sette,
Sigurd Skogestad,
Amornchai Arpornwichanop,
Rongrong Cheacharoen,
Soorathep Kheawhom
Publication year - 2020
Publication title -
royal society open science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 51
ISSN - 2054-5703
DOI - 10.1098/rsos.201107
Subject(s) - nonlinear system , battery (electricity) , linear model , computer science , nonlinear model , control theory (sociology) , energy storage , scheduling (production processes) , mathematical optimization , mathematics , artificial intelligence , physics , power (physics) , control (management) , quantum mechanics , machine learning
Due to the increasing trend of using renewable energy, the development of an energy storage system (ESS) attracts great research interest. A zinc–air battery (ZAB) is a promising ESS due to its high capacity, low cost and high potential to support circular economy principles. However, despite ZABs' technological advancements, a generic dynamic model for a ZAB, which is a key component for effective battery management and monitoring, is still lacking. ZABs show nonlinear behaviour where the steady-state gain is strongly dependent on operating conditions. The present study aims to develop a dynamic model, being capable of predicting the nonlinear dynamic behaviour of a refuellable ZAB, using a linear parameter-varying (LPV) technique. The LPV model is constructed from a family of linear time-invariant models, where the discharge current level is used as a scheduling parameter. The developed LPV model is benchmarked against linear and nonlinear model counterparts. Herein, the LPV model performs remarkably well in capturing the nonlinear behaviour of a ZAB. It significantly outperforms the linear model. Overall, the LPV approach provides a systematic way to construct a robust dynamic model which well represents the nonlinear behaviour of a ZAB.

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