Ursúa Rubio, Alfredo
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Ursúa Rubio
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Alfredo
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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 Applied method to model the thermal runaway of lithium-ion batteries(IEEE, 2021) Lalinde Sainz, Iñaki; Berrueta Irigoyen, Alberto; Sanchis Gúrpide, Pablo; Ursúa Rubio, Alfredo; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación; Universidad Pública de Navarra / Nafarroako Unibertsitate PublikoaThe thermal runaway (TR) is one of the most dangerous phenomena related to lithium-ion batteries. For this reason, there are different proposals in the literature for its modelling. Most of these proposed models take into account the decomposition reactions between the internal components of the cell, and base the adjustment of the parameters on numerous abuse tests that lead to the appearance of TR. However, these tests are destructive, require specific equipment, present a high economic cost and are very time consuming. This paper proposes a modelling method which enables the development of TR models with the use of fewer resources. This method is based on chemical kinetics, which allow a simplification of the general modelling process published in the literature. At the same time it maintains good accuracy and makes it possible to define the TR behavior of any type of cell, regardless of its chemistry, shape or size. Furthermore, the proposed method allows the use of the experimental results most commonly presented in the specialized literature, which significantly reduces the need for destructive testing. The presented modelling method achieves a good compromise between accuracy and applicability in the validations shown in the paper.Publication Open Access Health indicator selection for state of health estimation of second-life lithium-ion batteries under extended ageing(Elsevier, 2022) Braco Sola, Elisa; San Martín Biurrun, Idoia; Sanchis Gúrpide, Pablo; Ursúa Rubio, Alfredo; Stroe, Daniel-Ioan; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación; Gobierno de Navarra / Nafarroako Gobernua; Universidad Pública de Navarra / Nafarroako Unibertsitate PublikoaNowadays, the economic viability of second-life (SL) Li-ion batteries from electric vehicles is still uncertain. Degradation assessment optimization is key to reduce costs in SL market not only at the repurposing stage, but also during SL lifetime. As an indicator of the ageing condition of the batteries, state of health (SOH) is currently a major research topic, and its estimation has emerged as an alternative to traditional characterization tests. In an initial stage, all SOH estimation methods require the extraction of health indicators (HIs), which influence algorithm complexity and on-board implementation. Nevertheless, a literature gap has been identified in the assessment of HIs for reused Li-ion batteries. This contribution targets this issue by analysing 58 HIs obtained from incremental capacity analysis, partial charging, constant current and constant voltage stage, and internal resistance. Six Nissan Leaf SL modules were aged under extended cycling testing, covering a SOH range from 71.2 % to 24.4 %. Results show that the best HI at the repurposing stage was obtained through incremental capacity analysis, with 0.2 % of RMSE. During all SL use, partial charge is found to be the best method, with less than 2.0 % of RMSE. SOH is also estimated using the best HI and different algorithms. Linear regression is found to overcome more complex options with similar estimation accuracy and significantly lower computation times. Hence, the importance of analysing and selecting a good SL HI is highlighted, given that this made it possible to obtain accurate SOH estimation results with a simple algorithm.