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
New design alternatives for a hybrid photovoltaic and doubly-fed induction wind plant to augment grid penetration of renewable energy
(IEEE, 2021) Goñi, Naiara; Sacristán Sillero, Javier; Berrueta Irigoyen, Alberto; Rodríguez Rabadan, José Luis; Ursúa Rubio, Alfredo; Sanchis Gúrpide, Pablo; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
Reducing carbon emissions is essential to stop climate change. The grid-share of renewable generation plants is increasing, being wind and photovoltaic plants the most common ones, whereas conventional plants are the only ones that provide the necessary services to maintain the grid stability and keep the generation-demand balance. However, with the aim of achieving carbon-neutral generation, conventional plants are being dismantled. This leads to the imminent need of providing these services with renewable plants. Due to this challenge, this proposal analyses a hybrid plant composed by wind and photovoltaic generation with two types of storage, lithium-ion batteries and a thermal storage system based on volcanic stones. In order to compare both strategies, a technoeconomic methodology is explained that allows to optimally size the plant, using the current prices of each technology. The most cost-competitive proposal turns to be the hybrid plant with thermal storage, composed by 623.9 MW installed power and 21.9 GWh of storage, which could replace a 100 MW, 24/7 conventional power plant, with an LCOHS (levelized cost of hybrid system) of 118.38 €/MWh, providing identical grid services and an equivalent inertia in a way committed with the environment. This is in turn a zero-carbon emissions solution perfectly matched to a second life plan for a conventional power plant.
Open Access
Identification of critical parameters for the design of energy management algorithms for Li-ion batteries operating in PV power plants
(IEEE, 2020) Berrueta Irigoyen, Alberto; Soto Cabria, Adrián; Marcos Álvarez, Javier; Parra Laita, Íñigo de la; 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 Publikoa, ReBMS PJUPNA1904; Gobierno de Navarra / Nafarroako Gobernua, 0011-1411-2018-000029 GERA
Lithium-ion batteries are gaining importance for a variety of applications due to their price decrease and characteristics improvement. For a proper use of such storage systems, an energy management algorithm (EMA) is required. A number of EMAs, with various characteristics, have been published recently, given the diverse nature of battery problems. The EMA of deterministic battery problems is usually based on an optimization algorithm. The selection of such an algorithm depends on a few problem characteristics, which need to be identified and closely analyzed. The aim of this article is to identify the critical optimization problem parameters that determine the most suitable EMA for a Li-ion battery. With this purpose, the starting point is a detailed model of a Li-ion battery. Three EMAs based on the algorithms used to face deterministic problems, namely dynamic, linear, and quadratic programming, are designed to optimize the energy dispatch of such a battery. Using real irradiation and power price data, the results of these EMAs are compared for various case studies. Given that none of the EMAs achieves the best results for all analyzed cases, the problem parameters that determine the most suitable algorithm are identified to be four, i.e., desired computation intensity, characteristics of the battery aging model, battery energy and power capabilities, and the number of optimization variables, which are determined by the number of energy storage systems, the length of the optimization problem, and the desired time step.
Open Access
Characterization and capacity dispersion of lithium-ion second-life batteries from electric vehicles
(IEEE, 2019) Braco Sola, Elisa; 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
Nowadays, electric vehicle batteries reutilization is considered such as a feasible alternative to recycling, as it allows to benefit from their remaining energy and to enlarge their lifetime. Stationary applications as self-consumption or isolated systems support are examples of possible second life uses for these batteries. However, the modules that compose these batteries have very heterogeneous properties, and therefore condition their performance. This paper aims to characterize and analyze the existing capacity dispersion of Nissan Leaf modules that have reached the end of their lifetime on their original application and of new modules of this Electric Vehicle, in order to establish a comparison between them.
Open Access
Critical comparison of energy management algorithms for lithium-ion batteries in renewable power plants
(IEEE, 2019) Berrueta Irigoyen, Alberto; Soto Cabria, Adrián; García Solano, Miguel; Parra Laita, Íñigo de la; 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 Publikoa
Lithium-ion batteries are gaining importance for a variety of applications due to their price decrease and characteristics improvement. A good energy management strategy is required in order to increase the profitability of an energy system using a Li-ion battery for storage. The vast number of management algorithms that has been proposed to optimize the achieved profit, with diverse computational power requirements and using models with different complexity, raise doubts about the suitability of an algorithm and the required computation power for a particular application. The performance of three energy management algorithms based on linear, quadratic, and dynamic programming are compared in this work. A realistic scenario of a medium-sized PV plant with a constraint of peak shaving is used for this comparison. The results achieved by the three algorithms are compared and the grounds of the differences are analyzed. Among the three compared algorithms, the quadratic one seems to be the most suitable for renewableenergy applications, given the undue simplification of the battery aging required by the linear algorithm and the discretization and computational power required by a dynamic algorithm.
Open Access
Onset of irreversible reactions in overcharging lithium-ion cells: an experimental and modeling approach
(IEEE, 2023) Irujo Izcue, Elisa; Berrueta Irigoyen, Alberto; Lalinde Sainz, Iñaki; Arza, Joseba; Sanchis Gúrpide, Pablo; Ursúa Rubio, Alfredo; Ingeniería Eléctrica, Electrónica y de Comunicación; Institute of Smart Cities - ISC; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
Lithium-ion batteries are energy storage systems used in an increasing number of applications. Due to their flammable materials, their use entails risks of fire and explosion. The study of the abuse operation of these batteries before reaching the thermal runaway is a relevant research topic to prevent safety issues. There are various studies in the bibliography providing exhaustive thermal studies of the safe operating area, as well as concerning the thermal runaway. However, the onset irreversible reactions, that take place at a SOC around 110%, have not been properly analyzed. We present in this contribution an experimental study of this onset reaction measured in pouch Li-ion cells under various conditions of charge current and temperature. We also propose a lumped-parameter thermal model for the cell, which allows a detailed characterization of this exothermic reaction. The results achieved in this contributions can be a key tool to prevent overcharge accidents that may arise due to malfunctioning of the battery charger or battery management system.
Open Access
State of health estimation of second-life lithium-ion batteries under real profile operation
(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 Publikoa
The economic viability of second-life (SL) Li-ion batteries from electric vehicles (EVs) is still uncertain nowadays. Assessing the internal state of reused cells is key not only at the repurposing stage but also during their SL operation. As an alternative of the traditional capacity tests used to this end, the estimation of State of Health (SOH) allows to reduce the testing time and the need of equipment, thereby reinforcing the economic success of SL batteries. However, the estimation of SOH in real SL operation has been rarely analysed in literature. This contribution aims thus to cover this gap, by focusing on the experimental assessment of SOH estimation in reused modules from Nissan Leaf EVs under two SL scenarios: a residential household with self-consumption and a fast charge station for EVs. By means of partial charge and experimental data from cycling and calendar ageing tests, accuracy and robustness of health indicators is firstly assessed. Then, SOH estimation is carried out using real profiles, covering a SOH range from 91.3 to 31%. Offline assessment led to RMSE values of 0.6% in the residential profile and 0.8% in the fast charge station, with a reduction in testing times of 85% compared to a full capacity test. In order to avoid the interruption of battery operation, online assessment in profiles was also analysed, obtaining RMSE values below 1.3% and 3.6% in the residential and charging station scenarios, respectively. Therefore, the feasibility of SOH estimation in SL profiles is highlighted, as it allows to get accurate results reducing testing times or even without interrupting normal operation.
Open Access
Fast capacity and internal resistance estimation method for second-life batteries from electric vehicles
(Elsevier, 2023) Braco Sola, Elisa; San Martín Biurrun, Idoia; Sanchis Gúrpide, Pablo; Ursúa Rubio, Alfredo; Ingeniería Eléctrica, Electrónica y de Comunicación; Institute of Smart Cities - ISC; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
The success of second-life (SL) Li-ion batteries from electric vehicles is still conditioned by their technical and economic viability. The knowledge of the internal parameters of retired batteries at the repurposing stage is key to ensure their adequate operation and to enlarge SL lifetime. However, traditional characterization methods require long testing times and specific equipment, which result in high costs that may jeopardize the economic viability of SL. In the seek of optimizing the repurposing stage, this contribution proposes a novel fast characterization method that allows to estimate capacity and internal resistance at various state of charge for reused cells, modules and battery packs. Three estimation models are proposed. The first of them is based on measurements of AC resistance, the second on DC resistance and the third combines both resistance types. These models are validated in 506 cells, 203 modules and 3 battery packs from different Nissan Leaf vehicles. The results achieved are satisfactory, with mean absolute percentage errors (MAPE) below 2.5% at cell and module level in capacity prediction and lower than 2.4% in resistance estimation. Considering battery pack level, MAPE is below 4.2% and 1.8% in capacity and resistance estimation respectively. With the proposed method, testing times are reduced from more than one day to 2 min per cell, while energy consumption is lowered from 1.4 kWh to 1 Wh. In short, this study contributes to the reduction of repurposing procedures and costs, and ultimately to the success of SL batteries business model.
Open Access
Comparison of State-of-Charge estimation methods for stationary Lithium-ion batteries
(IEEE, 2016) Berrueta Irigoyen, Alberto; San Martín Biurrun, Idoia; Sanchis Gúrpide, Pablo; Ursúa Rubio, Alfredo; Ingeniería Eléctrica y Electrónica; Ingeniaritza Elektrikoa eta Elektronikoa; Institute of Smart Cities - ISC
An accurate monitoring of the State of Charge (SoC) is mandatory for an efficient management of a Lithium-ion battery. Batteries of stationary systems barely have long resting periods when the cumulative errors can be reset. These special requirements make a robust and accurate SoC estimation algorithm necessary. A real stationary system including an experimental microgrid with renewable energy generation, home consumption and a 5.3 kWh Li-ion storage system is analyzed in this paper. Three representative SoC monitoring algorithms are applied and compared in terms of accuracy and robustness to battery aging and current measurement offset. A closed-loop method consisting of an adaptive filter and a state observer achieves best results while having a reasonable computational complexity.
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.