Empirical electrical and degradation model for electric vehicle batteries

Battery degradation is one of the key barriers to the correct deployment of electric vehicle technology. Therefore, it is necessary to model, with sufficient precision, the State of Health (SoH) of batteries at every moment to know if they are useful as well as to develop operating strategies aimed...

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Detalhes bibliográficos
Autores: Saldaña Mulero, Gaizka, San Martín Díaz, José Ignacio, Zamora Belver, Inmaculada, Asensio De Miguel, Francisco Javier, González Pérez, Mikel
Tipo de documento: artigo
Data de publicação:2020
País:España
Recursos:Universidad del País Vasco
Repositório:Addi. Archivo Digital para la Docencia y la Investigación
OAI Identifier:oai:addi.ehu.eus:10810/78518
Acesso em linha:http://hdl.handle.net/10810/78518
Access Level:Acceso aberto
Palavra-chave:battery degradation
lifetime model
lithium-ion battery
electric vehicle
Descrição
Resumo:Battery degradation is one of the key barriers to the correct deployment of electric vehicle technology. Therefore, it is necessary to model, with sufficient precision, the State of Health (SoH) of batteries at every moment to know if they are useful as well as to develop operating strategies aimed at lifetime maximization. This paper presents a commercial electric vehicle with a nickel-cobalt-manganese (NCM) battery cell model that is composed of electrical and degradation submodels given by cycling aging. The studied cell is an LG Chem E63 cell, which is used in Renault Zoe electric vehicles. This degradation model is based on experimental results that are interpolated in the Hermite Cubic Interpolation Polynomial (PCHIP), with the exception of the number of cycles, whose impact is determined by a potential law. Temperature and C-rate are found to be the most influential factors in the aging of these batteries. The degradation model developed presents an RMSE of 1.12% in capacity fade and 2.63% in power fade. Furthermore, an application of the model is presented, in which high demanding (highway), average demanding (mixed), and low demanding (urban) driving environments are analyzed in terms of degradation.