Open Access
Winding resistance measurement in power inductors - understanding the impact of the winding mutual resistance
(IEEE, 2021) Barrios Rípodas, Ernesto; Elizondo Martínez, David; Ursúa Rubio, Alfredo; Sanchis Gúrpide, Pablo; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
Inductors are cornerstone components in power electronics converters. Since winding loss is the dominant loss mechanism in these components, its accurate measurement is fundamental for the validation of the inductor's operation and design. The techniques for the winding resistance R_{w} measurement in power inductors can be classified into two groups, indirect and direct. Both techniques use coupled inductors to separate winding and core power losses. If coupled inductors with non-zero winding mutual resistances R_{w,m} are used, invalid results are obtained with these techniques. Understanding the meaning of R_{w,m} in coupled inductors is complex. In this paper, the impact of R_{w,m} on the inductor R_{w} measurement techniques is demonstrated and practical guidelines for the design of the zero R_{w,m} coupled inductors are given. Particularly, the location of the auxiliary winding for the direct technique is investigated. In order to compare the R_{w} measurement techniques and to validate the coupled inductor's R_{w,m} impact, two different inductors are built and tested. The results are compared with the values for R_{w} calculated by FEA simulation. It is found that only the direct technique with an auxiliary winding carefully designed and located following the guidelines given in this paper makes the accurate measurement of R_{w} in power inductors possible.
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
Energy management for an electro-thermal renewable based residential microgrid with energy balance forecasting and demand side management
(Elsevier, 2021) Pascual Miqueleiz, Julio María; Arcos Avilés, Diego; Ursúa Rubio, Alfredo; Sanchis Gúrpide, Pablo; Marroyo Palomo, Luis; Ingeniería Eléctrica, Electrónica y de Comunicación; Institute of Smart Cities - ISC; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
This paper proposes an energy management strategy for a residential microgrid comprising photovoltaic (PV) panels, a small wind turbine and solar thermal collectors. The microgrid can control the power exchanged with the grid thanks to a battery and a controllable electric water heater, which provide two degrees of freedom to the control strategy. As input data, the proposed control strategy uses the battery state of charge (SOC), the temperature of the hot water tank, the power of each microgrid element as well as the demand and renewable generation forecasts. By using forecasted data and by controlling the electric water heater, the strategy is able to achieve a better grid power profile while using a smaller battery than previous works, hence reducing the overall cost of the system. The strategy is tested by means of simulation with real data for one year and it is also experimentally validated in the microgrid built at the Renewable Energy Laboratory at the UPNA.
Open Access
Temperature indicators and overtemperature detection in lithium-ion batteries based on electrochemical impedance spectroscopy
(IEEE, 2023) Lalinde Sainz, Iñaki; Berrueta Irigoyen, Alberto; Soto Cabria, Adrián; 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 the leading technology for energy storage systems due to their attractive advantages. However, the safety of lithium-ion batteries is a major concern, as their operating conditions are limited in terms of temperature, voltage and state of charge. Therefore, it is important to monitor the conditions of lithium-ion batteries to guarantee safe operation. To this end, in the present work, we analyze electrochemical impedance spectroscopy (EIS) as a tool to estimate the temperature of batteries. Overtemperature abuse tests from 25 °C to 140 °C are performed at various states of charge, and EIS measurements are obtained during the tests. The influence of temperature on cell impedance at different frequencies is analyzed and new findings are revealed. The real part of the impedance is identified to be the best indicator for cell temperature estimation by EIS. In addition, the best frequency to achieve accurate temperature monitoring, avoiding disturbances produced by state of charge variations, is proposed based on experimental results. Finally, EIS is proven to be a reliable technique for overtemperature and thermal runaway detection.
Open Access
Analysis and modelling of calendar ageing in second-life lithium-ion batteries from electric vehicles
(IEEE, 2022) 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; Gobierno de NAVARRA / Nafarroako Gobernua
The reuse of Li-ion batteries from electric vehicles is a promising alternative to recycling nowadays. However, the technical and economic viability of these second-life (SL) batteries is not yet clear. Degradation assessment plays a key role not only to analyse the impact of ageing factors in reused batteries, but also to quantify their durability. In this context, this contribution aims to analyse calendar ageing behaviour in SL cells. 16 reused Nissan Leaf modules are aged during 750 days under three temperatures and four State of Charge (SOC), covering a State of Health range from 72.2 % to 13 %. The impact of temperature and SOC as stress factors is firstly analysed, concluding that their increase accelerates ageing. Temperature rise is found to have a major impact, accelerating up to 27 times capacity fade and almost 6 times resistance increase when compared to light ageing conditions, while increasing SOC nearly doubles ageing rates. The worst ageing case is found to be the combination of 60 ◦C and 66 % of SOC. Regarding degradation trends, they are proven to be constant during all SL lifetime. This work also proposes and validates a calendar ageing model for SL cells. Accuracy of validation results show a fitting Rsq of 0.9941 in capacity fade and 0.9557 in resistance increase, thereby tracking the heterogeneous degradation of the SL cells under calendar ageing.
Open Access
Incremental capacity analysis of lithium-ion second-life batteries from electric vehicles under cycling ageing
(IEEE, 2021) 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; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa; Gobierno de Navarra / Nafarroako Gobernua
Nowadays, the reuse of batteries from electric vehicles is considered a promising solution to benefit from their remaining energy and extend their lifespan. Yet, the economic viability of these second-life batteries is still uncertain, and the optimization of testing at their reconfiguration stage and during their lifetime is the key to ensure their success. This paper aims to assess Incremental Capacity Analysis technique in Nissan Leaf modules during their second-life use, in order to evaluate both its potential as an State of Health estimator and as a tool to identify underlying degradation mechanisms. Despite the different internal state and ageing rates observed between the tested modules, ICA is found to be consistent at similar SOH levels. The influence of ageing, current and temperature on ICA is evaluated through an accelerated cycling test. Results show that ICA is a promising alternative to estimate SOH during second life even at currents up to C/2 and testing temperatures of 45 °C. However, testing by accelerated currents and temperatures is not recommended for the identification of degradation mechanisms.
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 Publikoa
The 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.
Open Access
Dynamic modeling of a pressurized alkaline water electrolyzer: a multiphysics approach
(IEEE, 2023) Iribarren Zabalegui, Álvaro; Elizondo Martínez, David; Barrios Rípodas, Ernesto; Ibaiondo, Harkaitz; Sánchez Ruiz, Alain; 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
In this paper a dynamic model for the simulation of pressurized alkaline water electrolyzers is presented. The model has been developed following a multiphysics approach, integrating electrochemical, thermodynamic, heat transfer and gas evolution processes in order to faithfully reproduce the complete dynamical behavior of these systems. The model has been implemented on MATLAB/Simulink and validated through experimental data from a 1 Nm3/h commercial alkaline water electrolyzer. Validations have been performed under real scenarios where the electrolyzer is working with power profiles characteristic from renewable sources, wind and photovoltaic. The simulated results have been found to be consistent with the real measured values. This model has a great potential to predict the behavior of alkaline water electrolyzers coupled with renewable energy sources, making it a very useful tool for designing efficient green hydrogen production systems.
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
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 Publikoa
Nowadays, 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.