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Thematische Bibliographien / Lithium-ion battery cells

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Auswahl der wissenschaftlichen Literatur zum Thema „Lithium-ion battery cells“

Autor: Grafiati

Veröffentlicht am 30. Juni 2021

Zuletzt aktualisiert am 15. Februar 2022

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Zeitschriftenartikel zum Thema "Lithium-ion battery cells"

1

Liu, Hong Rui, und Chao Ying Xia. „An Active Equalizer for Serially Connected Lithium-Ion Battery Cells“. Advanced Materials Research 732-733 (August 2013): 809–12. http://dx.doi.org/10.4028/www.scientific.net/amr.732-733.809.

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This paper proposes an equalizer for serially connected Lithium-ion battery cells. The battery cell with the lowest state of charge (SOC) is charged by the equalizer during the process of charging and discharging, and the balancing current is constant and controllable. Three unbalanced lithium-ion battery cells in series are selected as the experimental object by this paper. The discharging current under a certain UDDS and 20A charging current are used to complete respectively one time balancing experiment of discharging and charging to the three lithium-ion battery cells. The validity of the balancing strategy is confirmed in this paper according to the experimental results.

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2

Madani, Seyed Saeed, Erik Schaltz und Søren Knudsen Kær. „Applying Different Configurations for the Thermal Management of a Lithium Titanate Oxide Battery Pack“. Electrochem 2, Nr. 1 (23.01.2021): 50–63. http://dx.doi.org/10.3390/electrochem2010005.

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This investigation’s primary purpose was to illustrate the cooling mechanism within a lithium titanate oxide lithium-ion battery pack through the experimental measurement of heat generation inside lithium titanate oxide batteries. Dielectric water/glycol (50/50), air and dielectric mineral oil were selected for the lithium titanate oxide battery pack’s cooling purpose. Different flow configurations were considered to study their thermal effects. Within the lithium-ion battery cells in the lithium titanate oxide battery pack, a time-dependent amount of heat generation, which operated as a volumetric heat source, was employed. It was assumed that the lithium-ion batteries within the battery pack had identical initial temperature conditions in all of the simulations. The lithium-ion battery pack was simulated by ANSYS to determine the temperature gradient of the cooling system and lithium-ion batteries. Simulation outcomes demonstrated that the lithium-ion battery pack’s temperature distributions could be remarkably influenced by the flow arrangement and fluid coolant type.

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3

Madani, Seyed Saeed. „Characterization Investigation of Lithium-Ion Battery Cells“. ECS Transactions 99, Nr. 1 (12.12.2020): 65–73. http://dx.doi.org/10.1149/09901.0065ecst.

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4

Buga, Mihaela, Alexandru Rizoiu, Constantin Bubulinca, Silviu Badea, Mihai Balan, Alexandru Ciocan und Alin Chitu. „Study of LiFePO4 Electrode Morphology for Li-Ion Battery Performance“. Revista de Chimie 69, Nr. 3 (15.04.2018): 549–52. http://dx.doi.org/10.37358/rc.18.3.6146.

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The paper focuses on the development of lithium-ion battery cathode based on lithium iron phosphate (LiFePO4). Li-ion battery cathodes were manufactured using the new Battery R&D Production Line from ROM-EST Centre, the first and only facility in Romania, capable of fabricating the industry standard 18650 lithium-ion cells, customized pouch cells and CR2032 cells. The cathode configuration contains acetylene black (AB), LiFePO4, polyvinylidene fluoride (PVdF) as binder and N-Methyl-2-pyrrolidone (NMP) as solvent. X-ray diffraction measurements and SEM-EDS analysis were conducted to obtain structural and morphological information for the as-prepared electrodes.

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5

Kurfer, Jakob. „Design of Assembly Systems for Large-Scale Battery Cells“. Advanced Materials Research 769 (September 2013): 11–18. http://dx.doi.org/10.4028/www.scientific.net/amr.769.11.

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The social and technical trends regarding electro mobility and the turnaround in energy policy cause an increasing demand on large-scale and high-quality lithium-ion cells as core components for electrical storage systems. Within the production of lithium-ion cells, cell assembly has to deal with diverse challenges which result from product complexity and a lack of production experience. This paper covers the design of assembly systems for large-scale lithium-ion cells and presents the enhancement of conventional design processes by three add-on modules. The first one is an analysis of product structure and design focus points and is described in this paper. The modules two and three are outlined.

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6

Wang, Lizhi, Yusheng Sun, Xiaohong Wang, Zhuo Wang und Xuejiao Zhao. „Reliability Modeling Method for Lithium-ion Battery Packs Considering the Dependency of Cell Degradations Based on a Regression Model and Copulas“. Materials 12, Nr. 7 (30.03.2019): 1054. http://dx.doi.org/10.3390/ma12071054.

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Lithium-ion batteries are widely used as basic power supplies and storage units for large-scale electric drive products such as electric vehicles. Their reliability is directly related to the life and safe operation of the electric drive products. In fact, the cells have a dependent relationship with the degradation process and they affect the degradation rate of the entire battery pack, thereby affecting its reliability. At present, most research focuses on the reliability of battery packs and assumes that their cells are independent of each other, which may cause the reliability of the evaluation to deviate greatly from the actual level. In order to accurately assess the reliability of lithium-ion batteries, it is necessary to build a reliability model considering the dependency among cells for the overall degradation of lithium-ion battery packs. Therefore, in this study, based on a lithium-ion battery degradation test, the Wiener process is used to analyze the reliability of four basic configurations of lithium-ion battery packs. According to the degradation data of the battery packs, the Copula function is used to quantitatively describe the dependent relationship in the degradation process of a single battery, and the quantitative dependent relationship is combined with the reliability model to form a new reliability model. Finally, taking the battery system of Tesla S as an example, a feasible optimization method for battery pack design is provided based on the model constructed in this work.

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7

Wu, Yi, Youren Wang, Winco K. C. Yung und Michael Pecht. „Ultrasonic Health Monitoring of Lithium-Ion Batteries“. Electronics 8, Nr. 7 (03.07.2019): 751. http://dx.doi.org/10.3390/electronics8070751.

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Because of the complex physiochemical nature of the lithium-ion battery, it is difficult to identify the internal changes that lead to battery degradation and failure. This study develops an ultrasonic sensing technique for monitoring the commercial lithium-ion pouch cells and demonstrates this technique through experimental studies. Data fusion analysis is implemented using the ultrasonic sensing data to construct a new battery health indicator, thus extending the capabilities of traditional battery management systems. The combination of the ultrasonic sensing and data fusion approach is validated and shown to be effective for degradation assessment as well as early failure indication.

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8

Stuart, Thomas A., und Wei Zhu. „Modularized battery management for large lithium ion cells“. Journal of Power Sources 196, Nr. 1 (Januar 2011): 458–64. http://dx.doi.org/10.1016/j.jpowsour.2010.04.055.

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9

Duraisamy, Thiruvonasundari, und Kaliyaperumal Deepa. „Evaluation and Comparative Study of Cell Balancing Methods for Lithium-Ion Batteries Used in Electric Vehicles“. International Journal of Renewable Energy Development 10, Nr. 3 (10.02.2021): 471–79. http://dx.doi.org/10.14710/ijred.2021.34484.

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Vehicle manufacturers positioned electric vehicles (EVs) and hybrid electric vehicles (HEVs) as reliable, safe and environmental friendly alternative to traditional fuel based vehicles. Charging EVs using renewable energy resources reduce greenhouse emissions. The Lithium-ion (Li-ion) batteries used in EVs are susceptible to failure due to voltage imbalance when connected to form a pack. Hence, it requires a proper balancing system categorised into passive and active systems based on the working principle. It is the prerogative of a battery management system (BMS) designer to choose an appropriate system depending on the application. This study compares and evaluates passive balancing system against widely used inductor based active balancing system in order to select an appropriate balancing scheme addressing battery efficiency and balancing speed for E-vehicle segment (E-bike, E-car and E-truck). The balancing systems are implemented using “top-balancing” algorithm which balance the cells voltages near the end of charge for better accuracy and effective balancing. The most important characteristics of the balancing systems such as degree of imbalance, power loss and temperature variation are determined by their influence on battery performance and cost. To enhance the battery life, Matlab-Simscape simulation-based analysis is performed in order to fine tune the cell balancing system for the optimal usage of the battery pack. For the simulation requirements, the battery model parameters are obtained using least-square fitting algorithm on the data obtained through electro chemical impedance spectroscopy (EIS) test. The achieved balancing time of the passive and active cell balancer for fourteen cells were 48 and 20 min for the voltage deviation of 30 mV. Also, the recorded balancing time was 215 and 42 min for the voltage deviation of 200 mV.

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Duraisamy, Thiruvonasundari, und Kaliyaperumal Deepa. „Evaluation and Comparative Study of Cell Balancing Methods for Lithium-Ion Batteries Used in Electric Vehicles“. International Journal of Renewable Energy Development 10, Nr. 3 (10.02.2021): 471–79. http://dx.doi.org/10.14710/ijred.0.34484.

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Vehicle manufacturers positioned electric vehicles (EVs) and hybrid electric vehicles (HEVs) as reliable, safe and environmental friendly alternative to traditional fuel based vehicles. Charging EVs using renewable energy resources reduce greenhouse emissions. The Lithium-ion (Li-ion) batteries used in EVs are susceptible to failure due to voltage imbalance when connected to form a pack. Hence, it requires a proper balancing system categorised into passive and active systems based on the working principle. It is the prerogative of a battery management system (BMS) designer to choose an appropriate system depending on the application. This study compares and evaluates passive balancing system against widely used inductor based active balancing system in order to select an appropriate balancing scheme addressing battery efficiency and balancing speed for E-vehicle segment (E-bike, E-car and E-truck). The balancing systems are implemented using “top-balancing” algorithm which balance the cells voltages near the end of charge for better accuracy and effective balancing. The most important characteristics of the balancing systems such as degree of imbalance, power loss and temperature variation are determined by their influence on battery performance and cost. To enhance the battery life, Matlab-Simscape simulation-based analysis is performed in order to fine tune the cell balancing system for the optimal usage of the battery pack. For the simulation requirements, the battery model parameters are obtained using least-square fitting algorithm on the data obtained through electro chemical impedance spectroscopy (EIS) test. The achieved balancing time of the passive and active cell balancer for fourteen cells were 48 and 20 min for the voltage deviation of 30 mV. Also, the recorded balancing time was 215 and 42 min for the voltage deviation of 200 mV.

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Dissertationen zum Thema "Lithium-ion battery cells"

1

Zhao, Mingchuan. „Electrochemical Studies of Lithium-Ion Battery Anode Materials in Lithium-Ion Battery Electrolytes“. Ohio University / OhioLINK, 2001. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1004388277.

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2

Best, Adam Samuel 1976. „Lithium-ion conducting electrolytes for use in lithium battery applications“. Monash University, School of Physics and Materials Engineering, 2001. http://arrow.monash.edu.au/hdl/1959.1/9240.

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3

Choi, Seungdon. „Soft chemistry synthesis and structure-property relationships of lithium-ion battery cathodes“. Access restricted to users with UT Austin EID Full text (PDF) from UMI/Dissertation Abstracts International, 2001. http://wwwlib.umi.com/cr/utexas/fullcit?p3025204.

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Annavajjula, Vamsi Krishna. „A FAILURE ACCOMMODATING BATTERY MANAGEMENT SYSTEM WITH INDIVIDUAL CELL EQUALIZERS AND STATE OF CHARGE OBSERVERS“. University of Akron / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=akron1190318540.

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5

Zhu, Wei. „A Smart Battery Management System for Large Format Lithium Ion Cells“. University of Toledo / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1301687506.

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6

Limoge, Damas Wilks. „Reduced-order modeling and adaptive observer design for lithium-ion battery cells“. Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/111722.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 167-171).
This thesis discusses the design of a control-oriented modeling approach to Lithium- Ion battery modeling, as well as the application of adaptive observers to this structure. It begins by describing the fundamental problem statement of a battery management system (BMS), and why this is challenging to solve. It continues by describing, in brief, several different modeling techniques and their use cases, then fully expounds two separate high fidelity models. The first model, the ANCF, was initiated in previous work, and has been updated with novel features, such as dynamic diffusion coefficients. The second model, the ANCF II, was developed for this thesis and updates the previous model to better solve the problems facing the construction of an adaptive observer, while maintaining its model accuracy. The results of these models are presented as well. After establishing a model with the desired accuracy and complexity, foundational observers are designed to estimate the states and parameters of the time-varying ionic concentrations in the solid electrode and electrolyte, as well as an a-priori estimate of the molar flux. For the solid electrode, it is shown that a regressor matrix can be constructed for the observer using both spatial and temporal filters, limiting the amount of additional computation required for this purpose. For the molar flux estimate, it is shown that fast convergence is possible with coefficients pertaining to measurable inputs and outputs, and filters thereof. Finally, for the electrolyte observer, a novel structure is established to restrict learning only along unknown degrees of freedom of the model system, using a Jacobian steepest descent approach. Following the results of these observers, an outline is sketched for the application of a machine learning algorithm to estimate the nonlinear effects of cell dynamics.
by Damas Wilks Limoge.
S.M.

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7

Abaza, Ahmed. „Safety of automotive lithium-ion battery cells under abusive conditions : innovation report“. Thesis, University of Warwick, 2017. http://wrap.warwick.ac.uk/105583/.

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The research carried out in this report focuses on the topic of safety of Li-ion battery cells, specifically for automotive applications. Electric vehicle battery safety is a challenge that must be tackled, especially with the rapid electrification of vehicles. Cell abuse testing simulates their failure process under different scenarios. This helps develop a deeper understanding of the failure process, its root cause and associated mechanisms, hence enabling the improvement of their safety. This research has experimentally investigated four abusive conditions; mechanical penetration, external short circuit, cell swelling as a result of overcharge and overcharge in an adiabatic environment. A number of potential industrial applications based on the research findings are also discussed. During nail penetration testing the effect of nail material and diameter were investigated. Firstly, cells were fully penetrated using 10 mm diameter nails with three different materials; copper, steel and plastic. Secondly, cells were penetrated using 10 and 3 mm diameter copper nails. It was found that there was a clear distinction between the outcome of the conducting and non-conducting nails. However, the outcome of using electrically conductive nails suffered from poor reproducibility. Post-mortem examination showed that at the point of penetration the nail dragged the copper current collector in the direction of penetration along with the separator. The hole in the positive electrode looked less circular and the aluminium current collector was not dragged as deep as the copper one. During external short circuit testing the effect of the short resistance and the short duration was investigated. Firstly, cells were short-circuited using a range of resistance values. Secondly, a programmable power supply to control the shorting duration was used. It was found that the degree of damage experienced by a cell during a short is not only defined by the short resistance, but also its duration. The cells were cycleable after the short circuit event and their capacity and resistance increase depended on the short circuit current magnitude and the short duration. Opening the cells after testing and studying their components using SEM showed no change in the surface morphology of the electrodes. During the third set of experiments, purpose-built equipment was designed and built for in-situ volume measurement. The change in cell volume during cycling, overcharge and 10 cycles after the overcharge event was monitored and measured in-situ. The effect of the degree of overcharge and the magnitude of the charging current were studied. After the overcharge event the cycling behaviour of the cells was investigated. Electrochemical Impedance Spectroscopy (EIS) and Direct Current Internal Resistance (DCIR) were used to track the change in resistance. An Equivalent Circuit Model (ECM) was built to investigate the individual components contributing to the cell’s impedance. The overcharge-induced capacity fade was analysed using incremental capacity analysis (ICA). The reversibility of cell volume after swelling was also investigated. Results show that cell swelling and the extent of damage depended on the degree of overcharge and the C-rate. Cell swelling was partially reversible and the cells were cycleable after the overcharge event. Finally, cells were overcharged in ambient and adiabatic conditions. This was carried out to study the effect of heat dissipation on the outcome of an overcharge event. Results highlighted the critical role of heat dissipation from the cell in determining the outcome of the test. The same overcharge regime under different conditions resulted in very different outcomes. Cells overcharged in ambient conditions swelled significantly, but did not vent nor catch fire, whereas, all cells overcharged under adiabatic conditions either ruptured or caught fire. The magnitude of the overcharge current in adiabatic conditions determined the failure mode. Cells overcharged using 0.13 C current ruptured after swelling significantly, but did not catch fire. Cells overcharged with 0.33 and 1.3 C currents were completely combusted.

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Stephenson, David E. „Modeling of Electronic and Ionic Transport Resistances Within Lithium-Ion Battery Cathodes“. Diss., CLICK HERE for online access, 2008. http://contentdm.lib.byu.edu/ETD/image/etd2437.pdf.

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9

Chahwan, John A. „Vanadium-redox flow and lithium-ion battery modelling and performance in wind energy applications“. Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=100223.

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As wind energy penetration levels increase, there is a growing interest in using storage devices to aid in managing the fluctuations in wind turbine output power. Vanadium-Redox batteries (VRB) and Lithium-Ion (Li-Ion) batteries are two emerging technologies which can provide power smoothing in wind energy systems. However, there is an apparent gap when it comes to the data available regarding the design, integration and operation of these batteries in wind systems. This thesis presents suitable battery electrical models which will be used to assess system performance in wind energy applications, including efficiency under various operating conditions, transfer characteristics and transient operation. A design, sizing and testing methodology for battery integration in converter based systems is presented. Recommendations for the development of operating strategies are then provided based on the obtained results.

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Roselli, Eric (Eric J. ). „Design of a testing device for quasi-confined compression of lithium-ion battery cells“. Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/68922.

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Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 29).
The Impact and Crashworthiness Laboratory at MIT has formed a battery consortium to promote research concerning the crash characteristics of new lithium-ion battery technologies as used in automotive applications. Within a broad range of tests, there was a need to perform compression tests with a variable amount of confinement. A spring-loaded detainment device was designed which allows the battery to be confined in the axis perpendicular to compression without completely rigid walls. This provides a testing environment far more similar to the conditions of a real world crash situation. During an automobile crash event, the battery pack acts as a unit where each individual cell may experience a range of stresses from nearby cells or pack walls. An appropriate device was designed in Solidworks and used in the MIT ICL for testing with adjustable confinement during compression testing. MIT's research as a part of the consortium will continue for 3 more years beyond these initial tests. Never the less, the coming computational and constitutive models will be built using initial individual cell testing. Any model of a complete battery pack will use the material properties derived from cell testing.
by Eric Roselli.
S.B.

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Bücher zum Thema "Lithium-ion battery cells"

1

Battery management systems for large lithium-ion battery packs. Boston: Artech House, 2010.

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Arora, Ashish, und Sneha Arun Lele. Lithium-Ion Battery Failures in Consumer Electronics. Artech House, 2019.

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Handbook of Lithium-Ion Battery Pack Design: Chemistry, Components, Types and Terminology. Elsevier Science & Technology Books, 2015.

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Pistoia, Gianfranco, und Boryann Liaw. Behaviour of Lithium-Ion Batteries in Electric Vehicles: Battery Health, Performance, Safety, and Cost. Springer, 2019.

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Pistoia, Gianfranco, und Boryann Liaw. Behaviour of Lithium-Ion Batteries in Electric Vehicles: Battery Health, Performance, Safety, and Cost. Springer, 2018.

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Gulbinska, Malgorzata K. Lithium-ion Battery Materials and Engineering: Current Topics and Problems from the Manufacturing Perspective. Springer, 2014.

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Gulbinska, Malgorzata K. Lithium-ion Battery Materials and Engineering: Current Topics and Problems from the Manufacturing Perspective. Springer, 2016.

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Gulbinska, Malgorzata K. Lithium-ion Battery Materials and Engineering: Current Topics and Problems from the Manufacturing Perspective. Springer, 2014.

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LeVine, Steve. The powerhouse: America, China, and the great battery war. 2016.

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Buchteile zum Thema "Lithium-ion battery cells"

1

Santee, Stuart G., Boris Ravdel, Malgorzata K. Gulbinska, Joseph S. Gnanaraj und Joseph F. DiCarlo. „Optimizing Electrodes for Lithium-ion Cells“. In Lithium-ion Battery Materials and Engineering, 63–88. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-6548-4_3.

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Gulbinska, Malgorzata K., Arthur Dobley, Joseph S. Gnanaraj und Frank J. Puglia. „Lithium-ion Cells in Hybrid Systems“. In Lithium-ion Battery Materials and Engineering, 151–73. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-6548-4_6.

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Moore, Gregory J., Frank J. Puglia und Malgorzata K. Gulbinska. „Lithium-ion Cells for High-End Applications“. In Lithium-ion Battery Materials and Engineering, 89–113. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-6548-4_4.

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Wu, Ming-Hsiu, Chih-Ao Liao, Ngoc Thanh Thuy Tran und Wen-Dung Hsu. „Electrolytes for High-Voltage Lithium-Ion Battery“. In Lithium-Ion Batteries and Solar Cells, 103–15. First edition. | Boca Raton, FL : CRC Press/ Taylor & Francis Group, LLC, 2021.: CRC Press, 2020. http://dx.doi.org/10.1201/9781003138327-6.

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Hien Nguyen, Thi Dieu, Hai Duong Pham, Shih-Yang Lin, Ngoc Thanh Thuy Tran und Ming-Fa Lin. „Fundamental Properties of Li+-Based Battery Anode“. In Lithium-Ion Batteries and Solar Cells, 59–77. First edition. | Boca Raton, FL : CRC Press/ Taylor & Francis Group, LLC, 2021.: CRC Press, 2020. http://dx.doi.org/10.1201/9781003138327-4.

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Lin, Shih-Yang, Hsin-Yi Liu, Sing-Jyun Tsai und Ming-Fa Lin. „Geometric and Electronic Properties of Li+-Based Battery Cathode“. In Lithium-Ion Batteries and Solar Cells, 117–47. First edition. | Boca Raton, FL : CRC Press/ Taylor & Francis Group, LLC, 2021.: CRC Press, 2020. http://dx.doi.org/10.1201/9781003138327-7.

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Brahma, Sanjaya, Alex Chinghuan Lee und Jow-Lay Huang. „Graphene as an Anode Material in Lithium-Ion Battery“. In Lithium-Ion Batteries and Solar Cells, 149–66. First edition. | Boca Raton, FL : CRC Press/ Taylor & Francis Group, LLC, 2021.: CRC Press, 2020. http://dx.doi.org/10.1201/9781003138327-8.

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Sasso, Marco, Golam Newaz, Marco Rossi, Attilio Lattanzi und Sanket Mundhe. „Analysis of Deformations in Crush Tests of Lithium Ion Battery Cells“. In Residual Stress, Thermomechanics & Infrared Imaging and Inverse Problems, Volume 6, 123–29. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-30098-2_19.

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Feinauer, Julian, Daniel Westhoff, Klaus Kuchler und Volker Schmidt. „3D Microstructure Modeling and Simulation of Materials in Lithium-ion Battery Cells“. In Communications in Computer and Information Science, 128–44. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96271-9_8.

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Mueller, Karsten, Daniel Tittel, Lars Graube, Zecheng Sun und Feng Luo. „Optimizing BMS Operating Strategy Based on Precise SOH Determination of Lithium Ion Battery Cells“. In Lecture Notes in Electrical Engineering, 807–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33741-3_9.

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Konferenzberichte zum Thema "Lithium-ion battery cells"

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He, Liang, Eugene Kim und Kang G. Shin. „✲-Aware Charging of Lithium-Ion Battery Cells“. In 2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS). IEEE, 2016. http://dx.doi.org/10.1109/iccps.2016.7479067.

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Safi, Jariullah, Joel Anstrom, Sean Brennan und Hosam K. Fathy. „Differential Diagnostics for Lithium Ion Battery Cells Connected in Series“. In ASME 2014 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/dscc2014-6274.

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This paper presents a new method for estimating the capacity of a lithium ion battery cell in the presence of a reference cell — the parameters of which are well characterized — in series with it. The method assumes that both cells are cycled using the same current trajectory starting from the same state of charge (e.g. fully charged). Voltage measurements for both cells as well as current measurements for the series string constitute the input to a nonlinear least squares minimization problem. The goal of this problem is to estimate the capacity of the cell given the difference between its voltage and that of the reference cell. We refer to this as the differential estimation problem, and use Monte Carlo simulation to compare it to the more traditional approach of estimating the capacity of each cell in a battery string independently using its current/voltage measurements. Two key conclusions emerge from this simulation. Compared to traditional estimation, differential estimation results in capacity estimates whose variance is (i) twice as sensitive to voltage measurement noise but (ii) significantly less sensitive to current measurement noise. This makes differential estimation more appealing for battery packs with high current measurement noise and low voltage measurement noise.

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3

Zimmerman, Albert. „Self-Discharge Losses in Lithium Ion Battery Cells“. In 1st International Energy Conversion Engineering Conference (IECEC). Reston, Virigina: American Institute of Aeronautics and Astronautics, 2003. http://dx.doi.org/10.2514/6.2003-5985.

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4

Lee, S. Shawn, Tae H. Kim, S. Jack Hu, Wayne W. Cai und Jeffrey A. Abell. „Joining Technologies for Automotive Lithium-Ion Battery Manufacturing: A Review“. In ASME 2010 International Manufacturing Science and Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/msec2010-34168.

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Automotive battery packs for electric vehicles (EV), hybrid electric vehicles (HEV), and plug-in hybrid electric vehicles (PHEV) typically consist of a large number of battery cells. These cells must be assembled together with robust mechanical and electrical joints. Joining of battery cells presents several challenges such as welding of highly conductive and dissimilar materials, multiple sheets joining, and varying material thickness combinations. In addition, different cell types and pack configurations have implications for battery joining methods. This paper provides a comprehensive review of joining technologies and processes for automotive lithium-ion battery manufacturing. It details the advantages and disadvantages of the joining technologies as related to battery manufacturing, including resistance welding, laser welding, ultrasonic welding and mechanical joining, and discusses corresponding manufacturing issues. Joining processes for electrode-to-tab, tab-to-tab (tab-to-bus bar), and module-to-module assembly are discussed with respect to cell types and pack configuration.

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5

Vaidyanathan, H., und G. Rao. „Electrical and thermal characteristics of lithium-ion cells“. In Fourteenth Annual Battery Conference on Applications and Advances. Proceedings of the Conference (Cat. No.99TH8371). IEEE, 1999. http://dx.doi.org/10.1109/bcaa.1999.795970.

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6

Hoque, M. M., M. A. Hannan und A. Mohamed. „Voltage equalization for series connected lithium-ion battery cells“. In 2015 IEEE 3rd International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA). IEEE, 2015. http://dx.doi.org/10.1109/icsima.2015.7559015.

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7

Yurkovich, Benjamin J., und Yann Guezennec. „Lithium Ion Dynamic Battery Pack Model and Simulation for Automotive Applications“. In ASME 2009 Dynamic Systems and Control Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/dscc2009-2613.

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In this paper, we introduce a lumped parameter, distributed battery pack dynamic model which allows simulation of the electrical dynamics of all the cells in an arbitrarily configured series/parallel pack typical of those used in automotive applications. The dynamic pack simulator is based on the development of an analytical solution for the dynamic response of a single cell and an analytical development of such elemental solutions into a distributed dynamic pack model which can resolve the dynamics of each cell within the pack. This formulation leads to a computationally efficient simulation tool appropriate for application on large battery packs. This simulation tool is then used to perform Monte Carlo simulations on typical automotive current profiles for packs made of cells with a statistical distribution of parameters. A mild distribution of cell mismatch leads to cell unbalance development and statistical metrics for the growth unbalance, presented and related to both current severity and cell parameter distribution. The tool is ideally suited for studies in Battery Management System (BMS) algorithm development, as well as model-based fault propagation and diagnostics.

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Aljunid, Nur Adilah, Michelle A. K. Denlinger und Hosam K. Fathy. „Self-Balancing by Design in Hybrid Electrochemical Battery Packs“. In ASME 2018 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/dscc2018-9106.

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This paper explores the novel concept that a hybrid battery pack containing both lithium-ion (Li-ion) and vanadium redox flow (VRF) cells can self-balance automatically, by design. The proposed hybrid pack connects the Li-ion and VRF cells in parallel to form “hybrid cells”, then connects these hybrid cells into series strings. The basic idea is to exploit the recirculation and mixing of the VRF electrolytes to establish an internal feedback loop. This feedback loop attenuates state of charge (SOC) imbalances in both the VRF battery and the lithium-ion cells connected to it. This self-balancing occurs automatically, by design. This stands in sharp contrast to today’s battery pack balancing approaches, all of which require either (passive/active) power electronics or an external photovoltaic source to balance battery cell SOCs. The paper demonstrates this self-balancing property using a physics-based simulation of the proposed hybrid pack. To the best of the authors’ knowledge, this work represents the first report in the literature of self-balancing “by design” in electrochemical battery packs.

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9

Francis, Alex, Ilya Avdeev, Calvin Berceau, Hugo Pires Lage Martins, Luke Steinbach, Justin Mursch und Vincent Kanack. „Phantom Battery Pack for Destructive Testing of Li-Ion Batteries“. In ASME 2016 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/imece2016-67881.

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The objective of this study is to find a structural alternative to jellyroll in order to safely conduct experimental crash testing of lithium-ion battery packs in academic laboratory environment. A procedure for lateral impact experiments has been developed and conducted on cylindrical cells and phantom cells using a flat rigid drop cart in a custom-built impact test apparatus. The main component of a cylindrical cell, jellyroll, is a layered spiral structure which consists of thin layers of electrodes and separator material. We investigate various phantom materials — candidates to replace the layered jellyroll with a homogeneous anisotropic material. During our experimentation with various phantom cells, material properties and internal geometries of additively manufactured components such as in-fill pattern, density and voids were adjusted in order to develop accurate deformation response. The deformation of the phantom cell was characterized and compared after impact testing with the actual lithium-ion cells. The experimental results were also compared with explicit simulations (LS-DYNA). This work shows progress toward an accurate and safe experimental procedure for structural impact testing on the entire battery pack consisting of thousands of volatile cells. Understanding battery and battery pack structural response can influence design and improve safety of electric vehicles.

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LeBel, F. A., S. Wilke, B. Schweitzer, M. A. Roux, S. Al-Hallaj und J. P. F. Trovao. „A Lithium-Ion Battery Electro-Thermal Model of Parallellized Cells“. In 2016 IEEE 84th Vehicular Technology Conference (VTC-Fall). IEEE, 2016. http://dx.doi.org/10.1109/vtcfall.2016.7880858.

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Berichte der Organisationen zum Thema "Lithium-ion battery cells"

1

Santhanagopalan, Shriram, Chuanbo Yang und Ahmad Pesaran. Modeling Lithium Ion Battery Safety: Venting of Pouch Cells; NREL (National Renewable Energy Laboratory). Office of Scientific and Technical Information (OSTI), Juli 2013. http://dx.doi.org/10.2172/1214951.

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Trembacki, Bradley L., Jayathi Y. Murthy und Scott Alan Roberts. Fully Coupled Simulation of Lithium Ion Battery Cell Performance. Office of Scientific and Technical Information (OSTI), September 2015. http://dx.doi.org/10.2172/1221525.

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