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Linear parameter-varying model for a refuellable zinc–air battery

pmid: 33489267
pmc: PMC7813229
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.
- CentraleSupélec France
- University of Paris-Saclay France
- CentraleSupélec France
- Royal Society United Kingdom
- Laboratoire des Signaux & Systèmes France
Artificial intelligence, Energy storage, Nonlinear model, FOS: Mechanical engineering, Engineering, Battery (electricity), Physics, Q, Mathematical optimization, Integration of Electric Vehicles in Power Systems, Power (physics), linear model, Chemistry, nonlinear model, Physical Sciences, Science, Linear model, Lithium-ion Battery Management in Electric Vehicles, Battery Management Systems, Control (management), dynamic model, Quantum mechanics, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Machine learning, FOS: Electrical engineering, electronic engineering, information engineering, Control theory (sociology), FOS: Mathematics, Aqueous Zinc-Ion Batteries, Electrical and Electronic Engineering, linear parameter-varying model, Aqueous Zinc-Ion Battery Technology, zinc–air battery, zinc-air battery, [SPI.NRJ]Engineering Sciences [physics]/Electric power, linear parameter varying model, Computer science, Automotive Engineering, Nonlinear system, Scheduling (production processes), Mathematics
Artificial intelligence, Energy storage, Nonlinear model, FOS: Mechanical engineering, Engineering, Battery (electricity), Physics, Q, Mathematical optimization, Integration of Electric Vehicles in Power Systems, Power (physics), linear model, Chemistry, nonlinear model, Physical Sciences, Science, Linear model, Lithium-ion Battery Management in Electric Vehicles, Battery Management Systems, Control (management), dynamic model, Quantum mechanics, [SPI.AUTO]Engineering Sciences [physics]/Automatic, Machine learning, FOS: Electrical engineering, electronic engineering, information engineering, Control theory (sociology), FOS: Mathematics, Aqueous Zinc-Ion Batteries, Electrical and Electronic Engineering, linear parameter-varying model, Aqueous Zinc-Ion Battery Technology, zinc–air battery, zinc-air battery, [SPI.NRJ]Engineering Sciences [physics]/Electric power, linear parameter varying model, Computer science, Automotive Engineering, Nonlinear system, Scheduling (production processes), Mathematics
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