Open Access
Integrated lithium-ion battery model and experimental validation of a second-life prototype
(IEEE, 2023-08-31) 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; Gobierno de Navarra / Nafarroako Gobernua
A battery model predicts the battery performance, which can be a useful tool for optimizing battery design and preventing unsafe operation. This becomes especially significant in second-life batteries where the cells have already endured degradation and predicting the lifetime becomes challenging. The assessment of physical phenomena is often performed individually, but the overall battery behavior depends on their interaction. For this purpose, an integrated battery model is developed. Equivalent electric circuits are interconnected to represent the electrochemical reactions, thermodynamic phenomena, and heat transfer mechanisms of the battery. To consider cell degradation, calendar and cycling aging were represented using a semi-empirical model. A battery management system is included to oversee and remain within the safe limits of battery voltage, temperature, and current. Additionally, a passive cell balancing distributes charge evenly. The integrated model is applied to a second-life battery prototype with a nominal capacity and power of 45 Ah and 4 kW, respectively. Its performance is validated with constant current and power cycles, as well as in a microgrid with photovoltaic generation under a self-consumption profile. The model accurately reproduces experimental results of battery power, voltage, temperature, and state of charge.
Open Access
Lithium-ion second-life batteries: aging modeling and experimental validation
(IEEE, 2024-08-30) 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, PJUPNA2023-11380; Gobierno de Navarra / Nafarroako Gobernua
Re-utilizing lithium-ion batteries from electric vehicles reduces their environmental impact. To ensure their optimal sizing and safe use, identifying the current state of the battery and predicting its remaining useful life is essential. This work analyzes the degradation mechanisms involved and proposes an aging model that utilizes a semi-empirical approach to accurately reproduce the battery's state of health within a range of 75-45 %. Calendar aging includes dependencies on temperature and state of charge while cycling aging is modeled based on depth of discharge, medium SOC, temperature, and Crate. The model is validated against experimental data from 14 LMO/LNO cells previously used in actual Nissan Leaf vehicles and an RMSE bellow 2.5 % is achieved in every case.
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 Gobernua
The 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.

Pérez Ibarrola, Ane

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