Modelling, Parameter Identification, and Experimental Validation of a Lead Acid Battery Bank Using Evolutionary Algorithms

H. Eduardo Ariza Chacón, Edison Banguero, Antonio Correcher, Ángel Pérez-Navarro and Francisco Morant
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H. Eduardo Ariza Chacón: Grupo de Investigación en Sistemas Inteligentes, Corporación Universitaria Comfacauca, Popayán CP 190003, Colombia
Edison Banguero: Instituto de Automática e Informática Industrial-ai2, Universitat Politècnica de València, CP 46022 Valencia, Spain
Antonio Correcher: Instituto de Automática e Informática Industrial-ai2, Universitat Politècnica de València, CP 46022 Valencia, Spain
Ángel Pérez-Navarro: Instituto Universitario de Ingeniería Energética—IUIIE, Universitat Politècnica de València, CP 46022 Valencia, Spain
Francisco Morant: Instituto de Automática e Informática Industrial-ai2, Universitat Politècnica de València, CP 46022 Valencia, Spain

Energies, 2018, vol. 11, issue 9, 1-14

Abstract: Accurate and efficient battery modeling is essential to maximize the performance of isolated energy systems and to extend battery lifetime. This paper proposes a battery model that represents the charging and discharging process of a lead-acid battery bank. This model is validated over real measures taken from a battery bank installed in a research center placed at “El Chocó”, Colombia. In order to fit the model, three optimization algorithms (particle swarm optimization, cuckoo search, and particle swarm optimization + perturbation) are implemented and compared, the last one being a new proposal. This research shows that the identified model is able to estimate real battery features, such as state of charge (SOC) and charging/discharging voltage. The comparison between simulations and real measures shows that the model is able to absorb reading problems, signal delays, and scaling errors. The approach we present can be implemented in other types of batteries, especially those used in stand-alone systems.

Keywords: modelling; lead-acid battery; parameter identification; genetic algorithms; experimental validation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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