Sanchis Gúrpide, Pablo
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Sanchis Gúrpide
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Pablo
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Ingeniería Eléctrica, Electrónica y de Comunicación
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ISC. Institute of Smart Cities
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Publication Open Access Influence of the aging model of lithium-ion batteries on the management of PV self-consumption systems(IEEE, 2018) Berrueta Irigoyen, Alberto; Pascual Miqueleiz, Julio María; San Martín Biurrun, Idoia; Sanchis Gúrpide, Pablo; Ursúa Rubio, Alfredo; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación; Gobierno de Navarra / Nafarroako Gobernua, PI038 INTEGRA-RENOVABLESLithium-ion batteries are gaining importance for a variety of applications due to their improving characteristics and decreasing price. An accurate knowledge of their aging is required for a successful use of these ESSs. The vast number of models that has been proposed to predict these phenomena raise doubts about the suitability of a model for a particular battery application. The performance of three models published for a Sanyo 18650 cylindrical cell in a self-consumption system are compared in this work. Measured photovoltaic production and home consumption with a sampling frequency of 15 minutes are used for this comparison. The different aging predictions calculated by these three models are analyzed, compared and discussed. These comparison is particularized for two management strategies. The first of them maximizes the self-consumption PV energy, while the second reduces the maximum power peak demanded from the grid.Publication Open Access A novel aging modeling approach for second-life lithium-ion batteries(Elsevier, 2025-02-10) Pérez Ibarrola, Ane; San Martín Biurrun, Idoia; Sanchis Gúrpide, Pablo; Ursúa Rubio, Alfredo; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza; Institute of Smart Cities - ISC; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa; Gobierno de Navarra / Nafarroako GobernuaThe electric mobility industry is booming. In order to reduce the environmental impact of this boom, there is the potential to reuse the batteries from electric vehicles. However, the technical and economic feasibility of the second-life of lithium-ion batteries remains in question. This is due to the intricate non-linear mechanisms that occur during battery degradation, leading to capacity and power loss. Ongoing research aims to create models that can predict the state of battery degradation. However, most studies have focused on the battery's first life, operating within a limited state of health range and requiring constant monitoring of the battery's exposure conditions. While these models provide satisfactory results for the battery's performance in vehicles, they cannot be directly applied to second-life scenarios. In response to this issue, this article proposes a degradation modeling method for second-life batteries based on identifying and linearizing different degradation trends within the battery. This approach allows the application of the model without prior knowledge of the battery's history. It has been validated for a state of health range of 95% to 20%, through both conventional charge-discharge tests and a real-world scenario involving a smart charging station for urban buses. The results obtained with the developed model are overall satisfactory, achieving a MAPE below 3% for capacity and 1.4% for internal resistance in the real-world scenario.