The influence of temperature and charge-discharge rate on open circuit voltage hysteresis of an LFP Li-ion battery

Barai, Anup; Widanage, Widanalage Dhammika; McGordon, Andrew; Jennings, Paul

doi:10.1109/itec.2016.7520299

Cited by 12 publications

(5 citation statements)

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“…From Figure 6, we can observe a significant voltage drop, which is due to the internal resistance of the battery. The differences in temperature lead to differences in the internal resistance of the battery, which further leads to differences in voltage drops [39,40].…”

Section: High Rate Pulse Discharge Condition Dataset Collectionmentioning

confidence: 99%

An Approach to State of Charge Estimation of Lithium-Ion Batteries Based on Recurrent Neural Networks with Gated Recurrent Unit

2019

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State of charge (SOC) represents the amount of electricity stored and is calculated and used by battery management systems (BMSs). However, SOC cannot be observed directly, and SOC estimation is a challenging task due to the battery’s nonlinear characteristics when operating in complex conditions. In this paper, based on the new advanced deep learning techniques, a SOC estimation approach for Lithium-ion batteries using a recurrent neural network with gated recurrent unit (GRU-RNN) is introduced where observable variables such as voltage, current, and temperature are directly mapped to SOC estimation. The proposed technique requires no model or knowledge of the battery’s internal parameters and is able to estimate SOC at various temperatures by using a single set of self-learned network parameters. The proposed method is evaluated on two public datasets of vehicle drive cycles and another high rate pulse discharge condition dataset with mean absolute errors (MAEs) of 0.86%, 1.75%, and 1.05%. Experiment results show that the proposed method is accurate and robust.

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Section: High Rate Pulse Discharge Condition Dataset Collectionmentioning

confidence: 99%

An Approach to State of Charge Estimation of Lithium-Ion Batteries Based on Recurrent Neural Networks with Gated Recurrent Unit

2019

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“…[6,9] These adverse properties are attributed to the broken FeO 6 networks in the LFP crystal structure, which hinder electron conduction and Li-ion diffusion. [6] Moreover, LFP suffers from a relatively low operating voltage (3.2 V vs Li/Li þ ) and theoretical specific capacity (≈170 mAh g À1 ), [10][11][12] leading to lower energy density compared to Li[Ni 1-x-y Mn x Co y ] O 2 (NMC) and NCA counterparts. Therefore, it is necessary to overcome the low energy density of LFP for practical applications.Among various efforts to improve energy density of LFP, constructing electrodes with a high loading of active materials is regarded as an effective approach because it can reduce the…”

mentioning

confidence: 99%

Low‐Resistance LiFePO₄Thick Film Electrode Processed with Dry Electrode Technology for High‐Energy‐Density Lithium‐Ion Batteries

Kwon,

Kim,

Han

et al. 2024

Small Science

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LiFePO4 emerges as a viable alternative to cobalt‐containing cathodes, such as Li[Ni1–x–yMnxCoy]O2 and Li[Ni1−x−yCoxAly]O2. As Fe is abundant in nature, LiFePO4 is a low‐cost material. Moreover, stable structure of LiFePO4 imparts long service life and thermal stability. However, the practical implementation of LiFePO4 cathode in energy storage devices is impeded by its low energy density and high ionic/electrical resistance. Herein, the LiFePO4 electrode with high active material loading and low ionic/electrical resistance through the dry process is reported for the first time. The dry process not only enables the uniform distribution of the polymeric binders and conductive additives within the thick electrode but also inhibits the formation of cracks. Furthermore, the bridge‐like connection of polytetrafluoroethylene facilitates the insertion and extraction of Li ions to the LiFePO4 crystal. Hence, the dry‐processed LiFePO4 electrode with high areal capacity (7.8 mAh cm−2) exhibits excellent cycle stability over 300 cycles in full‐cell operation. In addition, it is demonstrated that the estimated energy density of prismatic cell with the dry‐processed LiFePO4 electrode is competitive with state‐of‐the‐art Li[Ni1–x–yMnxCoy]O2‐based battery.

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“…Moreover, no variation with aging was appreciated, only a slight difference at SoCs above 70 %. Nevertheless, two local maxima were also found in references [144] and [162].…”

Section: Ocv and Hysteresismentioning

confidence: 73%

“…Hysteresis evolution during the battery lifetime was not considered in their study. In addition, in reference [144], the local maxims were found around SoC = 30 % and SoC = 68 % with maximum values of 33 mV and 15 mV, respectively.…”

Section: Ocv and Hysteresismentioning

confidence: 95%

“…GITT measurements were carried out during charge and discharge so two OCV curves were obtained: one for the charge and one for discharge. The difference between them can be attributed to kinetics introduced by the measurement or hysteresis introduced by the cell itself [86,144,145]. In particular, hysteresis corresponds to the existence of several possible thermodynamic equilibrium potentials for a particular SoC [86,146].…”

Section: Open Circuit Voltage (Ocv) Measurementmentioning

confidence: 99%

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Determination of the state of health of Li-ion batteries : the irreversible entropy production approach

Ovejas Benedicto

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In recent years, portable applications have experienced an exponential growth and consequently, the demand of batteries has increased accordingly. It is widely known, though, that the performance of batteries decreases with time and use. This loss of performance is easured by the State-of-Health (SoH) of the cells. However, there is no consensus in defining this parameter. Experimental, theoretical or even heuristic approaches can be found in literature and commercial systems, but usually, they only work for particular conditions and they are not linked to the degradation suffered by the cells themselves. The aim of this study is to find a parameter directly related to this degradation. For this purpose, we investigate the irreversible entropy production in Li-ion cells because irreversible entropy is related to energy dissipation and thus, to irrversibilities due to system or energy degradation. In order to evaluate the degradation of the cells and its correspondence to irreversible entropy generation, we studied different Li-ion chemistries (NMC, LFP and LCO). Batteries were cycled at different discharge rates (close to and far from equilibrium) and evaluated at different SoHs. Therefore, capacity fade and impedance rise (the most commonly used techniques in SoH determination) were characterized and related to irreversible entropy generation. In addition, post-mortem analysis was carried out to achieve a deeper knowledge of the causes and effects of degradation. As a result of this study, we introduced a new parameter for system degradation characterization, the Relative-Entropy-Production (REP), defined as the irreversible entropy generation ratio at actual state and the initial state. In particular, we found irreversible entropy production evaluated at low discharge rates was higher as more degraded were the NMC cells. In the case of LFP cells, irreversible entropy production decreased during initial cycles but then increased towards the EoL. This behavior coincided with a capacity increase during initial cycles. In addition, we found a relationship between irreversible entropy generation and the phase transformations taking place during the discharge processes in all the evaluated cells because the materials undergoing phase transformations expand and contract yielding to cracks and other structural. Irreversible entropy production is found to be a promising magnitude to characterize battery aging. Even though much research has still to be carried out, the idea is to define, in the future, a threshold in irreversible entropy production that the cells can stand before considering their EoL is reached. En els darrers anys, la demanda de bateries ha augmentat considerablement gràcies a la creixent proliferació de dispositius portàtils. Tot i això, és ben sabut que el funcionament de les bateries empitjora amb el temps i l'ús. Aquesta pèrdua de rendiment es mesura amb un paràmetre anomenat State-oh-Health (SoH) encara que, avui dia, no s'ha arribat a un consens per a definir-lo. A la literatura o als mateixos sistemes comercials s'hi poden trobar aproximacions experimentals, teòriques o heurístiques, que generalment funcionen en situacions particulars i que, moltes sovint, no estan directament relacionades amb la degradació que pateixen les cel·les. L'objectiu d'aquest estudi és trobar un paràmetre que estigui directament relacionat amb la degradació patida per les cel·les. Per aquest motiu, ens hem centrat en la producció d'entropia irreversible perquè aquesta està relacionada amb la dissipació d'energia i, per tant, amb les irreversibilitats degudes a la degradació del sistema o de l'energia. Es va treballar amb vàries químiques de bateries d'ions de liti (NMC, LFP i LCO) per tal d’avaluar la degradació patida per aquestes i la correspondència amb la generació d'entropia irreversible. Aquestes cel·les van ser avaluades a taxes baixes i elevades a diferents nivells de SoH. En particular, la disminució de capacitat i l’augment d’impedància, que són les tècniques més utilitzades per a determinar el SoH, van ser determinades i posteriorment relacionades amb la generació d’entropia irreversible. A més a més, l’anàlisi post-mortem de les cel·les ens va permetre obtenir un coneixement major de les causes i els efectes de la degradació. Com a resultat d’aquest estudi, hem introduït un nou paràmetre per a la caracterització de la degradació d’un sistema. Aquest paràmetre l’hem anomenat Relative-Entropy-Production (REP) i l’hem definit com la relació entre la generació d’entropia irreversible en el moment actual i l’estat inicial. En particular, hem trobat que la producció d’entropia irreversible a taxes baixes de descàrrega és més gran com més degradades estan les cel·les de NMC. En canvi, en el cas de les cel·les de LFP, hem trobat que la generació d’entropia irreversible disminueix durant els primers cicles per després augmentar fins al final de la seva vida útil. S’ha vist que aquesta disminució coincideix amb un increment de la capacitat. A més a més, a totes les cel·les amb les que hem treballat, hem trobat una relació entre la producció d’entropia irreversible i les transformacions de fase que tenen lloc als elèctrodes durant la descàrrega. Aquesta relació ha sigut associada al fet de que els materials que pateixen una canvi de fase s’expandeixen i es contrauen el que fa que es produeixin fractures o esquerdes o altres modificacions estructurals. Totes elles produeixen degradació i, per tant, generen entropia irreversible. S’ha trobat que REP i la generació d’entropia irreversible són magnituds prometedores per a caracteritzar l’envelliment de bateries. Encara que queda molta feina per fer, la idea és, en un futur, poder definir un llindar de REP o de generació d’entropia irreversible que les cel·les siguin capaces de suportar abans no es consideri que han assolit el final de les seves vides útils.

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The influence of temperature and charge-discharge rate on open circuit voltage hysteresis of an LFP Li-ion battery

Cited by 12 publications

References 15 publications

An Approach to State of Charge Estimation of Lithium-Ion Batteries Based on Recurrent Neural Networks with Gated Recurrent Unit

An Approach to State of Charge Estimation of Lithium-Ion Batteries Based on Recurrent Neural Networks with Gated Recurrent Unit

Low‐Resistance LiFePO₄Thick Film Electrode Processed with Dry Electrode Technology for High‐Energy‐Density Lithium‐Ion Batteries

Determination of the state of health of Li-ion batteries : the irreversible entropy production approach

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The influence of temperature and charge-discharge rate on open circuit voltage hysteresis of an LFP Li-ion battery

Cited by 12 publications

References 15 publications

An Approach to State of Charge Estimation of Lithium-Ion Batteries Based on Recurrent Neural Networks with Gated Recurrent Unit

An Approach to State of Charge Estimation of Lithium-Ion Batteries Based on Recurrent Neural Networks with Gated Recurrent Unit

Low‐Resistance LiFePO4Thick Film Electrode Processed with Dry Electrode Technology for High‐Energy‐Density Lithium‐Ion Batteries

Determination of the state of health of Li-ion batteries : the irreversible entropy production approach

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Low‐Resistance LiFePO₄Thick Film Electrode Processed with Dry Electrode Technology for High‐Energy‐Density Lithium‐Ion Batteries