New battery model considering thermal transport and partial charge stationary effects in photovoltaic off-grid applications
Sanz-Gorrachategui, Iván ; Bernal, Carlos (Universidad de Zaragoza) ; Oyarbide, Estanis (Universidad de Zaragoza) ; Garayalde, Erik ; Aizpuru, Iosu ; Canales, Jose María ; Bono-Nuez, Antonio (Universidad de Zaragoza)
Resumen: The optimization of the battery pack in an off-grid Photovoltaic application must consider the minimum sizing that assures the availability of the system under the worst environmental conditions. Thus, it is necessary to predict the evolution of the state of charge of the battery under incomplete daily charging and discharging processes and fluctuating temperatures over day-night cycles.
Much of previous development work has been carried out in order to model the short term evolution of battery variables. Many works focus on the on-line parameter estimation of available charge, using standard or advanced estimators, but they are not focused on the development of a model with predictive capabilities. Moreover, normally stable environmental conditions and standard charge-discharge patterns are considered. As the actual cycle-patterns differ from the manufacturer's tests, batteries fail to perform as expected.
This paper proposes a novel methodology to model these issues, with predictive capabilities to estimate the remaining charge in a battery after several solar cycles. A new non-linear state space model is proposed as a basis, and the methodology to feed and train the model is introduced. The new methodology is validated using experimental data, providing only 5% of error at higher temperatures than the nominal one.
Idioma: Inglés
DOI: 10.1016/j.jpowsour.2017.12.058
Año: 2018
Publicado en: JOURNAL OF POWER SOURCES 378 (2018), 311-321
ISSN: 0378-7753
Factor impacto JCR: 7.467 (2018)
Categ. JCR: CHEMISTRY, PHYSICAL rank: 26 / 148 = 0.176 (2018) - Q1 - T1
Categ. JCR: MATERIALS SCIENCE, MULTIDISCIPLINARY rank: 32 / 293 = 0.109 (2018) - Q1 - T1
Categ. JCR: ENERGY & FUELS rank: 11 / 103 = 0.107 (2018) - Q1 - T1
Categ. JCR: ELECTROCHEMISTRY rank: 3 / 26 = 0.115 (2018) - Q1 - T1
Factor impacto SCIMAGO: 1.947 - Electrical and Electronic Engineering (Q1) - Renewable Energy, Sustainability and the Environment (Q1) - Physical and Theoretical Chemistry (Q1) - Energy Engineering and Power Technology (Q1)
Financiación: info:eu-repo/grantAgreement/ES/MINECO/RTC-2015-3358-5
Tipo y forma: Artículo (PostPrint)
Área (Departamento): Área Tecnología Electrónica (Dpto. Ingeniería Electrón.Com.)
Debe reconocer adecuadamente la autoría, proporcionar un enlace a la licencia e indicar si se han realizado cambios. Puede hacerlo de cualquier manera razonable, pero no de una manera que sugiera que tiene el apoyo del licenciador o lo recibe por el uso que hace. No puede utilizar el material para una finalidad comercial. Si remezcla, transforma o crea a partir del material, no puede difundir el material modificado.
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Much of previous development work has been carried out in order to model the short term evolution of battery variables. Many works focus on the on-line parameter estimation of available charge, using standard or advanced estimators, but they are not focused on the development of a model with predictive capabilities. Moreover, normally stable environmental conditions and standard charge-discharge patterns are considered. As the actual cycle-patterns differ from the manufacturer's tests, batteries fail to perform as expected.
This paper proposes a novel methodology to model these issues, with predictive capabilities to estimate the remaining charge in a battery after several solar cycles. A new non-linear state space model is proposed as a basis, and the methodology to feed and train the model is introduced. The new methodology is validated using experimental data, providing only 5% of error at higher temperatures than the nominal one.
Idioma: Inglés
DOI: 10.1016/j.jpowsour.2017.12.058
Año: 2018
Publicado en: JOURNAL OF POWER SOURCES 378 (2018), 311-321
ISSN: 0378-7753
Factor impacto JCR: 7.467 (2018)
Categ. JCR: CHEMISTRY, PHYSICAL rank: 26 / 148 = 0.176 (2018) - Q1 - T1
Categ. JCR: MATERIALS SCIENCE, MULTIDISCIPLINARY rank: 32 / 293 = 0.109 (2018) - Q1 - T1
Categ. JCR: ENERGY & FUELS rank: 11 / 103 = 0.107 (2018) - Q1 - T1
Categ. JCR: ELECTROCHEMISTRY rank: 3 / 26 = 0.115 (2018) - Q1 - T1
Factor impacto SCIMAGO: 1.947 - Electrical and Electronic Engineering (Q1) - Renewable Energy, Sustainability and the Environment (Q1) - Physical and Theoretical Chemistry (Q1) - Energy Engineering and Power Technology (Q1)
Financiación: info:eu-repo/grantAgreement/ES/MINECO/RTC-2015-3358-5
Tipo y forma: Artículo (PostPrint)
Área (Departamento): Área Tecnología Electrónica (Dpto. Ingeniería Electrón.Com.)
Debe reconocer adecuadamente la autoría, proporcionar un enlace a la licencia e indicar si se han realizado cambios. Puede hacerlo de cualquier manera razonable, pero no de una manera que sugiera que tiene el apoyo del licenciador o lo recibe por el uso que hace. No puede utilizar el material para una finalidad comercial. Si remezcla, transforma o crea a partir del material, no puede difundir el material modificado.Exportado de SIDERAL (2019-12-12-10:04:00)
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Registro creado el 2019-01-04, última modificación el 2019-12-12