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A semi-empirical model of the calendar ageing of lithium-ion batteries aimed at automotive and deep-space applications

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A semi-empirical model of the calendar ageing of lithium-ion batteries aimed at automotive and deep-space applications

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dc.contributor.author Torregrosa, A. J. es_ES
dc.contributor.author Broatch, A. es_ES
dc.contributor.author Olmeda, P. es_ES
dc.contributor.author Agizza, Luca es_ES
dc.date.accessioned 2024-07-01T18:37:53Z
dc.date.available 2024-07-01T18:37:53Z
dc.date.issued 2024-03-01 es_ES
dc.identifier.issn 2352-152X es_ES
dc.identifier.uri http://hdl.handle.net/10251/205669
dc.description.abstract [EN] Lithium-ion batteries are highly affected by calendar ageing effects, which can lead to capacity loss even when the battery is not used at all. The current literature proposes plenty of semi-empirical models to predict the calendar ageing of the lithium-ion batteries, which are mostly based on Arrhenius functions for temperature dependency, exponential models for state of charge dependency and power laws for time dependency. Those models are easy to calibrate, and they provide a sufficiently precise prediction of capacity loss over time. However, it might be difficult to find a physical meaning to the parameters determined in these models, due to their lumped nature and the optimization process used. Therefore, in this work a semi-empirical model able to predict the capacity degradation over time with physically meaningful parameters is proposed. The dependency on temperature is considered by a pre-exponential factor whereas the dependency on state of charge is considered by a power law coefficient. A two-step constrained optimization process is considered to calibrate the model parameters. The model allows to predict the capacity loss over a wide range of different temperature and state of charge conditions, and it is calibrated for 4 different cell chemistries: LMO-NMC, LFP, NCA, and NMC. It was found that the worst storing condition is given by the highest temperature and state of charge conditions. The capacity degradation is provided over a period of 50 years. Two end-of-life conditions were analyzed: a loss of capacity of 20 % as representative of an end-of-life condition for automotive applications, and a loss of capacity of 50 % as an end-of-life condition for deep-space applications. In both cases, it was observed that NMC provided the best performance (the slowest ageing over time) for storing temperatures below 15 degrees C and storing state of charge below 10 %, whereas for temperatures higher than 15 degrees C and state of charge higher than 10 %, the LFP chemistry resulted to be the most longevous. es_ES
dc.description.sponsorship This work was supported by Generalitat Valenciana - Agencia Valenciana de la Innovacio (AVI), within the framework of the R+D+i project "Demostrador Tecnologico de un paquete de baterias para Vehiculo Electrico (DETEBAT-VE)", reference INNEST/2021/120. Luca Agizza is supported by grant ACIF/2021/005 funded by Conselleria de Innovacion, Universidades, Ciencia y Sociedad Digital of the Generalitat Valenciana.r Vehiculo Electrico (DETEBAT-VE) ", reference INNEST/2021/120. Luca Agizza is supported by grant ACIF/2021/005 funded by Conselleria de Innovacion, Universidades, Ciencia y Sociedad Digital of the Generalitat Valenciana. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Journal of Energy Storage es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Lithium-ion batteries es_ES
dc.subject Calendar ageing es_ES
dc.subject Semi-empirical model es_ES
dc.subject Deep-space application es_ES
dc.subject End-of-life condition es_ES
dc.subject Temperature and state of charge dependencies es_ES
dc.subject.classification MAQUINAS Y MOTORES TERMICOS es_ES
dc.title A semi-empirical model of the calendar ageing of lithium-ion batteries aimed at automotive and deep-space applications es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.est.2023.110388 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//ACIF%2F2021%2F005/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AVI//INNEST%2F2021%2F120/ es_ES
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Torregrosa, AJ.; Broatch, A.; Olmeda, P.; Agizza, L. (2024). A semi-empirical model of the calendar ageing of lithium-ion batteries aimed at automotive and deep-space applications. Journal of Energy Storage. 80. https://doi.org/10.1016/j.est.2023.110388 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.est.2023.110388 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 80 es_ES
dc.relation.pasarela S\507690 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Agència Valenciana de la Innovació es_ES
dc.contributor.funder Universitat Politècnica de València es_ES


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