Academic literature on the topic 'Batteries 18650 usagées'

This paper focuses on studying the influence of temperature on the working process of Panasonic NCR-18650B electric vehicle battery. Through the Matlab - Simulink simulation tool, the effects related to the charging/discharging process of electric vehicle batteries such as voltage, current and state of charge (SOC) have been considered at different temperature of 0, 25, 50 degrees Celsius. Research results contribute to optimizing battery usage, thereby minimizing the impact of batteries on the environment, contributing to the development of the current electric car industry.

<span>Electric bike (E-Bike) is a bicycle driven using an electric motor and uses batteries as the energy source. It is environmentally friendly as no exhaust gas is resulted during its operation. More than one battery is normally required, being arranged in series or in parallel connection. Over limit or overloaded conditions of battery usage will reduce the lifecycle of battery, speed up its replacement and add to the maintenance cost of electric bike. This paper proposes the prevention of such degrading condition using a tool to manage the battery usage both during the charging and discharging process. The proposed electronic Battery Management System (BMS) serves to regulate, monitor, and maintain the condition of batteries to prevent any possible damage. The resulted BMS design could provide a well balancing action in a battery system consisting of 13 cells utilizing the cell-to-cell active balancing method. The test results showed that the proposed BMS could monitor the individual cell voltage with an average error of 0.032 V (0.824</span><span lang="IN">%</span><span>), while reading the charge and discharge current with an average error of 0.04 A (</span><span lang="IN">6.25%</span><span>), and the battery pack temperature with an average error of 1.21^oC (</span><span lang="IN">2.9%</span><span>). Additionally, the BMS could offer a functional battery pack protection system from conditions such as undervoltage, overvoltage, overheat, and overcurrent.</span>

This article introduces a novel approach for developing an electrical model of the lithium batteries used in an electric ultralight aircraft. Currently, no method exists in the technical literature for accurately modeling the electrical characteristics of batteries in an electric aircraft, making this study a valuable contribution to the field. The proposed method was validated with an all-electric ultralight aircraft designed and constructed at the Pascual Bravo University Institution. To build the detailed model, a kinematic analysis was first conducted through takeoff tests, where data on the speed, acceleration, time, and distance required for takeoff were collected, along with measurements of the current and power consumed by the batteries. The maximum speed and acceleration of the aircraft were also recorded. These kinematic results were obtained using two batteries made from Samsung INR-18650-35E lithium-ion cells, and different wing configurations of the aircraft were analyzed to assess their impacts on the battery energy consumption. Additionally, the discharge cycles of the batteries were evaluated. In the second phase, laboratory tests were performed on the individual battery cells, and the Peukert coefficient was estimated based on the experimental data. Finally, using the Peukert coefficient and the kinematic results from the takeoff tests, the electrical model of the battery was fine tuned. This model allows for the creation of charging and discharging equations for ultralight lithium batteries. With the final electrical model and energy consumption data during takeoff, it becomes possible to determine the energy usage and flight range of an electric aircraft. The model indicated that the aircraft did not require a long distance to takeoff, as it reached the necessary takeoff speed in a very short time. The equations used to simulate the discharge cycles of the batteries and lithium cells accurately described their energy capacities.

The sources of performance loss in lithium-ion batteries are many and can vary widely dependent on battery usage [1]. Understanding these mechanisms and coupling usage patterns to dominating degradation phenomena can allow smarter use and longer lifetime of the batteries. This can especially bring value in stationary applications, as the usage patterns have different characteristics and second life applications for batteries are considered as well [2]. Driven by the development of battery electric vehicles, batteries with higher power and energy densities have revolutionized the market. The lifetime of the batteries is another crucial criterion. A significant amount of work has been performed studying the degradation phenomena and evaluating stress factors. High/low potentials, high C-rates, and temperature deviations from room temperature should be avoided to keep the degradation rate low [3-5]. The power demand for batteries in stationary energy storage systems is lower than vehicle applications and some of these extremes could therefore be avoided [6]. Finding optimal sizing of the batteries, with high energy throughput and low degradation rate, is therefore of interest. The energy delivered by the storage system is further part of the power trading market, hence motivating the need to accurately correlate delivered energy and battery performance loss from different services. In this work the degradation of commercial 18650-type Nickel Cobalt Manganese (NCM)/Graphite cells, in stationary applications is studied. Different scenarios including type of service, sizing, and second-life applications are studied through accelerated testing. The work expands upon a previous study focusing on the degradation effects of combining services [7]. The degradation analysis involves different techniques such as the capacity evolution (Figure 1), electrochemical impedance spectroscopy (EIS), as well as changes in the electrodes revealed by differential voltage analysis (DVA). The electrode balancing, capacity and cell polarization is evaluated in terms of battery state-of-health and important characteristics highlighted. Preliminary results show no additional degradation introduced by scaling the current amplitude 50%. A clear relationship between state-of-charge window and degradation rate is shown, where the graphite two-phase regions are of importance. These regions are also affected by the electrode slippage observed in the DVA. Strategies for battery characterization and operation strategies for second-life applications will be further investigated. Figure 1. Preliminary results of the normalized capacity development of the cells in the study, as an averaged value of duplicate cells. Frequency regulation (FR) is a mild cycle around 50% SOC, current maximum 1C. FR_high has a current maximum of 1.5C. Peak shaving (PS) is a 1C constant current cycling between 22-78% SOC, PS_low has a 0.5C constant current cycling. FRPS is the two cycles combined. References Birkl, C. R.; Roberts, M. R.; McTurk, E.; Bruce, P. G.; Howey, D. A., Degradation diagnostics for lithium ion cells. Journal of Power Sources 2017, 341, 373-386. Martinez-Laserna, E.; Gandiaga, I.; Sarasketa-Zabala, E.; Badeda, J.; Stroe, D. I.; Swierczynski, M.; Goikoetxea, A., Battery second life: Hype, hope or reality? A critical review of the state of the art. Renewable and Sustainable Energy Reviews 2018, 93, 701-718. Baure, G.; Dubarry, M., Battery durability and reliability under electric utility grid operations: 20-year forecast under different grid applications. Journal of Energy Storage 2020, 29. Keil, P.; Schuster, S. F.; Wilhelm, J.; Travi, J.; Hauser, A.; Karl, R. C.; Jossen, A., Calendar Aging of Lithium-Ion Batteries. Journal of The Electrochemical Society 2016, 163 (9), A1872-A1880. Ecker, M.; Nieto, N.; Käbitz, S.; Schmalstieg, J.; Blanke, H.; Warnecke, A.; Sauer, D. U., Calendar and cycle life study of Li(NiMnCo)O2-based 18650 lithium-ion batteries. Journal of Power Sources 2014, 248, 839-851. Dubarry, M.; Devie, A.; Stein, K.; Tun, M.; Matsuura, M.; Rocheleau, R., Battery Energy Storage System battery durability and reliability under electric utility grid operations: Analysis of 3 years of real usage. Journal of Power Sources 2017, 338, 65-73. Ohrelius, M.; Berg, M.; Wreland Lindström, R.; Lindbergh, G., Lifetime Limitations in Multi-Service Battery Energy Storage Systems. Energies 2023, 16 (7). Figure 1

In this study, we investigate the use of the ohmic drop compensation method during battery discharges at different rates. Four different types of NMC Li-ion batteries are compared and three 18,650 cells of each type are tested to evaluate the performance dispersion. The cell type that shows significant performance improvement thanks to ohmic drop compensation in this first experimental part is then selected to complete the exploration. A drone-type usage profile is set up and demonstrates without any doubt the interest of using this type of protocol in such usage. Finally, a preliminary aging study is also performed on this type of cells: ohmic drop compensation use has no effect on low-power performance decrease during aging and has a moderate impact on high-power performances.

Typical usage scenarios for energy storage and electric vehicles (EVs) require lithium-ion batteries (LIBs) to operate under extreme conditions, including varying temperatures, high charge/discharge rates, and various depths of charge and discharge, while also fulfilling vehicle-to-grid (V2G) interaction requirements. This study empirically investigates the impact of ambient temperature, charge/discharge rate, and charge/discharge cut-off voltage on the capacity degradation rate and internal resistance growth of 18,650 commercial LIBs. The charge/discharge rate was found to have the most significant influence on these parameters, particularly the charging rate. These insights contribute to a better understanding of the risks associated with low-temperature aging and can aid in the prevention or mitigation of safety incidents.

Accurate monitoring of lithium-ion battery temperature is essential to ensure these batteries’ efficient and safe operation. This paper proposes a relevance-based reconstruction-oriented EMD-Informer machine learning model, which combines empirical mode decomposition (EMD) and the Informer framework to estimate the surface temperature of 18,650 lithium-ion batteries during charging and discharging processes under complex operating conditions. Initially, based on 9000 data points from the U.S. NASA Prognostics Center of Excellence’s random battery-usage dataset, where each data point includes three features: temperature, voltage, and current, EMD is used to decompose the temperature data into intrinsic mode functions (IMFs). Subsequently, the IMFs are reconstructed into low-, medium-, and high-correlation components based on their correlation with the original data. These components, along with voltage and current data, are fed into sub-models. Finally, the model captures the long-term dependencies among temperature, voltage, and current. The experimental results show that, in single-step prediction, the mean squared error, mean absolute error, and maximum absolute error of the model’s predictions are 0.00095, 0.02114, and 0.32164 °C; these metrics indicate the accurate prediction of the surface temperature of lithium-ion batteries. In multi-step predictions, when the prediction horizon is set to 12 steps, the model achieves a hit rate of 93.57% where the maximum absolute error is within 0.5 °C; under these conditions, the model combines high predictive accuracy with a broad predictive range, which is conducive to the effective prevention of thermal runaway in lithium-ion batteries.

The design and operation of performant and safe electric vehicles depend on precise knowledge of the behavior of their electrochemical energy storage systems. The performance of the battery management systems often relies on the discrete-time battery models, which can correctly emulate the battery characteristics. Among the available methods, electric circuit-based equations have shown to be especially useful in describing the electrical characteristics of batteries. To overcome the existing drawbacks, such as discrete-time simulations for parameter estimation and the usage of look-up tables, a set of equations has been developed in this study that solely relies on the open-circuit voltage and the internal resistance of a battery. The parameters can be obtained from typical cell datasheets or can be easily extracted via standard measurements. The proposed equations allow for the direct analytical determination of available discharge capacity and the available energy content depending on the discharge current, as well as the Peukert exponent. The fidelity of the proposed system was validated experimentally using 18650 NMC and LFP lithium-ion cells, and the results are in close agreement with the datasheet.

Degradation of lithium-ion batteries is the result of many complex phenomena occurring simultaneously at varying time and length scales. The underlying electrochemical and mechanical phenomena have received much attention from researchers [1]. Physics-based models of these effects support the mechanistic understanding of degradation modes and can thereby help reduce their severity. Few studies target changing electrochemical parameters such as diffusion coefficients or reaction rate constants that have a direct impact on model accuracy and manifest themselves in observable aging. Lyu et al. [2] used a simplified electrochemical model and monitored battery degradation by following changes in diffusion time constants, electrode balancing, reaction rate coefficients, and ohmic resistance. However, several of the parameters they attempted to track could only be identified with low accuracy as they used the same data-set to identify all parameters. In this study, we investigate parameters of a full order Newman-type model [3] over the course of a batteries lifetime under real-world load-cycles. To ensure parameter identifiability, optimally designed experiments are used for parameter estimation. In a previous study [4] the feasibility of optimal experiment design for parametrization of electrochemical battery models was demonstrated. We now extend this work and re-evaluate key parameters over the course of an aging study on commercial, nickel-rich 18650 lithium-ion batteries. We highlight how quantifying changes in physical battery parameters can extend standard performance metrics for a batteries state-of-health by, e.g., including degradation in rate-capability. Additionally, the importance of battery usage conditions such as C-rate or state-of-charge window on model parameter trajectories is investigated and their relationship with conventional performance metrics such as the bulk cell resistance or rate-capability determined. Quantifying how specific mechanisms contribute to apparent capacity or power fade is a major step towards battery lifetime optimization. This could enable designs more tailored for specific applications and significantly extend batteries useful lifetime. Furthermore, updating parameters is essential for electrochemical control strategies relying on accurate model predictions of battery states as illustrated in Figure 1. This re-calibration would make a battery management system aging-sensitive and enable more efficient utilization and a physics-informed state-of-health. Figure 1: The central plot shows how parameters change during aging. If this change is not considered, model performance deteriorates between beginning-of-life (BOL) and end-of-life (EOL) (in blue, right-hand side). This is normally handled by using conservative battery management systems and over-sizing systems. The proposed strategy (orange) achieves higher model accuracy during the entire useful life and the parameter estimates can be used to formulate an extended state-of-health. References: [1] J. Vetter, P. Novák, M.R. Wagner, C. Veit, K.C. Möller, J.O. Besenhard, M. Winter, M. Wohlfahrt-Mehrens, C. Vogler, A. Hammouche, Ageing mechanisms in lithium-ion batteries, J. Power Sources. 147 (2005) 269–281. https://doi.org/10.1016/j.jpowsour.2005.01.006. [2] C. Lyu, Y. Song, J. Zheng, W. Luo, G. Hinds, J. Li, L. Wang, In situ monitoring of lithium-ion battery degradation using an electrochemical model, Appl. Energy. 250 (2019) 685–696. https://doi.org/10.1016/j.apenergy.2019.05.038. [3] M. Doyle, T. Fuller, J. Newman, Modelling of the Galvanostatic Charge and Discharge of the Lithium/Polymer/Insertion Cell, J. Electrochem. Soc. 140 (1993) 1526–1533. https://doi.org/10.1149/1.2221597. [4] M. Streb, M. Ohrelius, M. Klett, G. Lindbergh, Improving Li-ion Battery Parameter Estimation by Global Optimal Experiment Design (Manuscript submitted), (2022). Figure 1

The electrification of transportation is experiencing rapid development. Electric bicycles (e-bikes) are commonly employed as convenient modes of transportation. Thanks to the advantages of long life and high energy density, lithium-ion batteries (LIBs) are widely used in e-bikes. In certain business models, e-bikes can utilize rental LIBs, which are centrally managed at charging stations. The low-temperature charging and discharging performance of the LIB system poses a significant challenge during usage. Among various heating methods, alternating current (AC) heating has garnered attention due to its high efficiency and has been applied to quickly warm up the LIB system. To address this issue, an AC heating model was established to determine the appropriate frequency and magnitude of the current, and a prototype AC heating system for the LIB modules used in e-bikes was designed. A full-bridge topology system model was established, and an experimental platform was constructed to test the effectiveness of the proposed AC heating topology and thermoelectric model under different AC heating frequencies and currents. The results show that the proposed AC heating system can heat an 18650 battery module within 20 min. Under an ambient temperature of −20 °C, using a 10 A, a 100 Hz excitation current achieves a heating rate of 1.3 °C per minute, with minimum power losses. The prototype also has a fast response time of only 70 ms. Finally, the strategies of LIB heating and insulation are proposed for the scenario of a battery swapping station. This research holds great significance in resolving the problem of low-temperature heating for e-bikes in cold regions.

Les batteries lithium-ion (LIB) ont révolutionné l'électronique portable et se sont étendues au secteur de la mobilité grâce aux progrès des matériaux d'électrodes, des électrolytes et des processus de production. Cependant, la demande croissante de LIB pose des défis mondiaux en matière de gestion des déchets. En tant que ressources critiques, les matériaux LIB nécessitent un recyclage efficace dans le contexte de l'économie circulaire tout en répondant aux objectifs de durabilité et de neutralité carbone. Les méthodes de recyclage conventionnelles, telles que la pyrométallurgie et l'hydrométallurgie, ne parviennent pas à récupérer entièrement les composants LIB, en particulier lorsque des déchets de production - un nouveau flux de déchets vierges - apparaissent. Le recyclage direct, une stratégie nouvelle et efficace, préserve les propriétés des matériaux telles que la composition, la structure et les propriétés, améliorant ainsi les taux de récupération. Cette thèse explore le recyclage direct des déchets de production et évalue le potentiel de recyclage des cellules 18650 usagées à différents niveaux de dégradation. Un nouveau procédé à base de CO2 a été développé pour le recyclage direct des déchets de production d'électrodes LIB. En utilisant un mélange de solvants de phosphate de triéthyle, d'acétone et de CO2, la dissolution du liant a été améliorée et la délamination des matériaux d'électrode positive a été accélérée, séparant efficacement LiNi0,6Mn0,2Co0,2O2 (NMC622) du collecteur de courant. L'étude explore également la dégradation dans les cellules 18650 avec cathode NMC622, anode en graphite et électrolyte à base d'EC sous divers protocoles de vieillissement, révélant des changements de matériaux importants, notamment la perte de Li, la décomposition de l'électrolyte et la migration du Mn. Le CO2 liquide et l'acétonitrile ont été utilisés pour extraire les carbonates et les produits de dégradation liquides, tandis que le carbonate de diméthyle comme cosolvant avec le CO2 liquide a permis une récupération élevée du lithium. Ces résultats fournissent des informations précieuses sur le vieillissement des batteries et mettent en évidence les défis d'un recyclage direct efficace, soulignant la nécessité de stratégies innovantes pour faire face à ces processus de dégradation complexes
Lithium-ion batteries (LIBs) have revolutionized portable electronics and expanded into the mobility sector through advancements in electrode materials, electrolytes, and production processes. However, the growing LIB demand poses global waste management challenges. As critical resources, LIB materials require efficient recycling within the context of circular economy while meeting sustainability and carbon-neutrality goals. Conventional recycling methods, such as pyrometallurgy and hydrometallurgy, fall short in fully recovering LIB components, particularly as production scraps—a new, pristine waste stream—emerge. Direct recycling, a novel and efficient strategy, preserves material properties such as composition, structure, and properties, improving the recovery rates. This dissertation explores direct recycling of production scraps and evaluate spent 18650 cells their recycling potential across varying levels of degradation. A novel CO2-based process was developed for the direct recycling of LIB electrode production scrap. Using a solvent mixture of triethyl phosphate, acetone, and CO2, binder dissolution was enhanced and the delamination of positive electrode materials was accelerated, efficiently separating LiNi0.6Mn0.2Co0.2O2 (NMC622) from the current collector. The study also explores the degradation in 18650 cells with NMC622 cathode, graphite anode, and EC-based electrolyte under various ageing protocols, revealing significant material changes, including Li loss, electrolyte decomposition, and Mn migration. Liquid CO2 and acetonitrile were used to extract carbonates and liquid degradation products, while dimethyl carbonate as a cosolvent with liquid CO2 allowed high lithium recovery. These findings provide valuable insights into battery aging and highlight challenges for effective direct recycling, emphasizing the need for innovative strategies to address this complex degradation processes

<div class="section abstract"><div class="htmlview paragraph">With advancement and increase in usage of Li-ion batteries in sectors such as electronic equipment’s, Electric Vehicles etc battery lifetime is critical for estimation of product life. It is well known that temperature and voltage strongly influence the degradation of lithium-ion batteries and that it depends on the chemical composition and structure of the positive and negative electrodes. Lithium batteries are continuously subjected to various load cycles and ambient temperatures depending on application of battery. Thus, in many applications Cycle aging could be the main contributor or factor for battery degradation, thus reduction in life of product. Thus, there is strong need for researchers and engineers to help improve life of cells or batteries being used in electric vehicles.</div><div class="htmlview paragraph">In this present work, cycle aging of commercial 18650 cell is studied at ambient temperature. Experimental data shows that about nearly 20 % cell capacity degrades at ambient temperature. A numerical model is built using GT-Auto lion and validation study is conducted.</div><div class="htmlview paragraph">Further the work is extended numerically for different ambient temperatures. Ambient temperatures of 45degC, 5 degC and 25 deg C have been studied in the present work. Effect of parameters such as ambient temperature on SEI growth of electrode has been studied. Findings provide critical design insight to help cell manufacturers to come up with proper methodology that can be adapted to help prevent capacity degradation of cell. Thus, help improve life span of a product.</div></div>

Objective Battery Management System (BMS), an integral part of EVs and HEVs. Development of reliable BMS requires a lot of cell data and its characterization. A comprehensive BMS shall be capable of handling any type of Li-ion battery chemistry. Such requirements pose challenges for BMS development. A BMS can be ascertained reliable and safe, once the defined functionalities and requirements are proven, but the scale of hardware, data and cost involved to develop and prove is enormous. This paper describes a HIL based approach for Development and Validation of BMS. This method proves to be cost and time effective. Introduction: Challenging emission targets and quest for sustainable mobility, keeps the EV requirement rising. By 2030, the market share of EV is expected to be around 30% excluding two-wheelers. The need for safer and smarter mobility is also growing in tandem. Li-ion batteries has proven to be the promising solution for energy reservoir requirements in EV/HEV. Unaddressed Li-ion battery pack is a potential hazard in EV/HEV. The need of BMS now is not only to address safety of the pack but also support in effective usage of the pack’s potential. Hence a BMS, plays a vital role in any EV/HEV and its development poses multiple challenges. This paper describes a methodology for verification and validation of BMS functionalities through Hardware in Loop (HIL) approach. HIL based validation reduces the cost of development as it eliminates the need of actual Li-ion cells and packs. Any cell characteristics and Pack configuration can be emulated and the BMS functions can be validated. Methodology  Cell model characterization and Validation 18650 cell with NCA chemistry was configured in the simulation model and its characteristics was validated  Development of Controller Model Graphical based programming approach was used for development of the BMS controller model.  MIL (Model in Loop) Here both the Plant model and Controller model was validated in closed loop  RPT hardware as ECU Generic Rapid Prototyping hardware is used for realization of controller  Parameterization of Cell Emulators The 18650 cell with NCA chemistry was then configured in the Cell emulator.  HIL validation The RPT hardware was used in loop with HIL Cell Emulator and the BMS functions were validated. Results The results of Model in Loop simulation was compared with Hardware in Loop Simulation to understand real time performance.