Journal articles: 'Litium ion batteries'

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Gonggo, Siang Tandi, Anang Wahid M. Diah, and Reki Lanteene. "Pengaruh Kaolin Terhadap Membran Blend Kitosan Poli Vinil Alkohol-Litium Sebagai Membran Elektrolit Untuk Aplikasi Baterai Ion Litium." Jurnal Akademika Kimia 6, no. 1 (December 8, 2017): 55. http://dx.doi.org/10.22487/j24775185.2017.v6.i1.9229.

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Today, the battery is the most practical and in expensive energy storage device in a modern community. A variety of new materials technologies has been developed in the manufacture of the battery, especially the development of the solid electrolyte (solid). Polymer Electrolytes can be found in the polymer batteries form such as lithium ion polymer battery. A natural polymer such as chitosan is potential as polymer electrolyte membrane for battery applications. The chitosan has amino and hydroxyl groups that allow for modification. The modification of chitosan membrane is expected to produce the better membranes characters. The aim of this research is to study the effect of the addition of inorganic filler kaolin on the conductivity of the polymer electrolyte that made of chitosan-polyvinyl alcohol than was added to the lithium salt. The ionic conductivity of the polymer electrolyte chitosan-polyvinyl alcohol-lithium-kaolin was measured by using an impedance spectroscopy. The measurement results showed that the polymer electrolyte chitosan-polyvinyl alcohol-lithium with the addition of 4% kaolin provide the highest ionic conductivity is large 6.551x10-5 S/cm. In comparison, characteristics of batteries that made from polymer electrolyte chitosan-polyvinyl alcohol-lithium with the addition of kaolin have a voltage of 2.4 volts which have similarities to the commercial batteries. This result indicates that the kaolin can be used as a filler to increase the ionic conductivity of the polymer electrolyte chitosan-polyvinyl alcohol-lithium, and then it can be developed as a battery.

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Riyanto, Agus, Simon Sembiring, Megawati Megawati, Ni’matil Mabarroh, Junaidi Junaidi, and Ediman Ginting. "Analisis Transisi Fasa dan Sifat Dielektrik Pada Li2CoSiO4 yang Dipreparasi dari Silika Sekam Padi dan Produk Daur Ulang Katoda Baterai Ion Litium Bekas." ALCHEMY Jurnal Penelitian Kimia 15, no. 1 (March 14, 2019): 89. http://dx.doi.org/10.20961/alchemy.15.1.24622.89-103.

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Studi ini mendeskripsikan analisis transisi fasa dan sifat dielektrik pada bahan litium kobalt silikat (Li2CoSiO4) yang dipreparasi dari silika sekam padi dan produk daur ulang katoda baterai ion litium bekas dengan perbandingan massa 1:1. Transisi fasa pada sampel Li2CoSiO4 dipelajari menggunakan teknik termogravimetry/differential thermal analysis (TG/DTA). Sedangkan, nilai konstanta dielektrik pada sampel yang telah disinter pada suhu 600 – 900 oC dikarakterisasi menggunakan inductance, capacitance, dan resistance (LCR) meter. Hasilnya, pada rentang suhu 410 – 850 oC terjadi transisi polimorfik fasa menjadi fasa . Suhu 850 oC juga merupakan titik transisi dimana fasa berubah menjadi fasa . Transisi fasa yang terjadi pada sampel Li2CoSiO4 diikuti dengan peningkatan nilai konstanta dielektrik dalam rentang frekuensi 450 – 100.000 Hz.Analysis of Phase Transition and Dielectric Properties of Li2CoSiO4 Prepared from Rice Husk Silica and The Recycling Product of Used Lithium Ion Batteries Cathode. This study describes the analysis of the phase transition and dielectric properties of lithium cobalt silicate (Li2CoSiO4) prepared from rice husk silica and the recycling product of used lithium ion batteries cathode with mass ratio of 1:1. Phase transition in Li2CoSiO4 sample was studied using thermogravimetry/differential thermal analysis (TG/DTA) techniques. Meanwhile, the dielectric constant value in the samples sintered at temperature of 600 – 900 oC were characterized using inductance, capacitance, and resistance (LCR) meter. As a result, a polymorphic transition from phase to phase was occured in the temperature range of 410 – 850 oC. Temperature of 850 oC is a transition point from phase to phase. The phase transitions occured in the Li2CoSiO4 was followed by the increasing of the dielectric constant in the frequency range of 450 – 100,000 Hz.

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A’yuni, Qurrota, and Trisna Kumala Dhaniswara. "Sintesis Sol-Gel dan Karakterisasi Struktur Padatan FeF3 dengan Difraksi Sinar-X." Journal of Pharmacy and Science 4, no. 1 (January 30, 2019): 23–28. http://dx.doi.org/10.53342/pharmasci.v4i1.127.

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ABSTRAKMaterial FeF3 dapat diaplikasikan dalam berbagai bidang diantaranya sebagai material katoda untuk baterai ion litium dan katalis heterogen pada beberapa reaksi yang melibatkan sisi asam. Sintesis FeF3 dapat dilakukan melalui beberapa cara, salah satunya dengan metode sol-gel. Di dalam proses sol-gel adanya agen gelasi dapat mengontrol porositas dan sifat keasaman katalis. Pada penelitian ini dipilih agen gelasi dari senyawa alkohol yaitu metanol dan etanol. Masing-masing padatan yang telah disintesis kemudian dikarakterisasi struktur padatannya dengan difraksi sinar-X. Hasil penelitian menunjukkan bahwa padatan FeF3 telah berhasil disintesis melalui metode sol gel dengan agen gelasi yang berbeda yaitu metanol dan etanol yang masing-masing dituliskan sebagai FeF3(me) dan FeF3(et). Karakterisasi struktur padatan FeF3 menggunakan difraksi sinar-X menghasilkan difraktogram yang sesuai dengan PDF No. 85-0481 dan data ICSD kode 016671 yang memilikistruktur rhombohedral dengan space group R-3cR dan panjang kisi kristal sebesar a = b = c = 5,362 Å dengan sudut α = β = γ = 57,99°. Struktur kristal FeF3 disusun oleh ion Fe3+ dengan jari-jari 0,384 Å dan ion F- dengan jari-jari 0,798 Å dengan tipe ikatan ionik. Rasio besarnya kristalinitas FeF3(et) dibandingkan dengan kristalinitasFeF3(me) sebesar 5:4.Kata kunci: FeF3, sintesis sol-gel, difraksi sinar-X, struktur padatan. ABSTRACTFeF3 material can be applied in various fields including as cathode material for lithium ion batteries and heterogeneous catalysts in some reactions involving the acid side. Synthesis of FeF3 can be done in several ways, one of them is the sol-gel method. In the sol-gel process the gelation agent can control the porosity and acidity of the catalyst. In this study, gelation agents were selected from alcohol compounds, namely methanol and ethanol. The solids that has been synthesized was then solid structure characterized by X-ray diffraction. The results showed that FeF3 solids were successfully synthesized through the sol-gel method with different gelation agents, namely methanol and ethanol, each of which was written as FeF3(me) and FeF3(et). Characterization of the solid structure of FeF3 using X-ray diffraction produces a diffractogram according to the PDF No. 85-0481 and ICSD data code 016671 which has a rhombohedral structure with space group R-3cR andcrystal lattice length of a = b = c = 5.362 Å with an angle α = β = γ = 57.99°. The crystal structure of FeF3 is composed by Fe3+ ions with radius 0.384 Å and F- ions with radius 0.798 Å with ionic bond types. The ratio of the crystallinity of FeF3(et) compared to the crystallinity of FeF3(me) is 5:4.Keywords: FeF3, sol-gel synthesis, X-ray diffraction, solid structur.

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Galushkin, Nikolay E., Nataliya N. Yazvinskaya, and Dmitriy N. Galushkin. "Investigation of the Temperature Dependence of Parameters in the Generalized Peukert Equation Used to Estimate the Residual Capacity of Traction Lithium-Ion Batteries." Batteries 8, no. 12 (December 9, 2022): 280. http://dx.doi.org/10.3390/batteries8120280.

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The Peukert equation is widely used in various analytical models of lithium-ion batteries. However, the classical Peukert equation is applicable to lithium-ion batteries only in a limited range of discharge currents. Additionally, it does not take into account the temperature impact on a battery’s released capacity. In this paper, the applicability of the generalized Peukert equation C = Cm/(1 + (i/i0)n) is investigated for the residual capacity determination of lithium-ion batteries based on the Hausmann model. It is proved that all the parameters (Cm, i0, and n) of this equation depend on a battery’s temperature. That is why, for a battery-released capacity calculation, it is necessary to take into account the battery’s temperature. The equations are found to describe the temperature dependence of all the parameters of the generalized Peukert equation. The physical meaning of all the parameters is established and it is shown that the generalized Peukert equation obtained with temperature consideration is applicable to any current and temperature of a battery.

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Jiang, Shida, and Zhengxiang Song. "Estimating the State of Health of Lithium-Ion Batteries with a High Discharge Rate through Impedance." Energies 14, no. 16 (August 8, 2021): 4833. http://dx.doi.org/10.3390/en14164833.

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Lithium-ion batteries are an attractive power source in many scenarios. In some particular cases, including providing backup power for drones, frequency modulation, and powering electric tools, lithium-ion batteries are required to discharge at a high rate (2~20 C). In this work, we present a method to estimate the state of health (SOH) of lithium-ion batteries with a high discharge rate using the battery’s impedance at three characteristic frequencies. Firstly, a battery model is used to fit the impedance spectrum of twelve LiFePO4 batteries. Secondly, a basic estimation model is built to estimate the SOH of the batteries via the parameters of the battery model. The model is trained using the data of six batteries and is tested on another six. The RMS of relative error of the model is lower than 4.2% at 10 C and lower than 2.8% at 15 C, even when the low-frequency feature of the impedance spectrum is ignored. Thirdly, we adapt the basic model so that the SOH estimation can be performed only using the battery’s impedance at three characteristic frequencies without having to measure the entire impedance spectrum. The RMS of relative error of this adapted model at 10 C and 15 C is 3.11% and 4.25%, respectively.

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Lu, Wanyu, Zijie Wang, and Shuhang Zhong. "Sodium-ion battery technology: Advanced anodes, cathodes and electrolytes." Journal of Physics: Conference Series 2109, no. 1 (November 1, 2021): 012004. http://dx.doi.org/10.1088/1742-6596/2109/1/012004.

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Abstract The development of electric vehicles has made massive progress in recent years, and the battery part has been receiving constant attention. Although lithium-ion battery is a powerful energy storage technology contemporarily with great convenience in the field of electric vehicles and portable/stationary storage, the scantiness and increasing price of lithium have raised significant concerns about the battery’s developments; an alternative technology is needed to replace the expensive lithium-ion batteries at use. Therefore, the sodium-ion batteries (SIBs) were brought back to life. Sharing a similar mechanism as the lithium-ion batteries makes SIBs easier to understand and more effective in the research. In recent years, the developed materials for anode and cathode in the SIB have extensively promoted its advancements in increasing the energy density, power rate, and cyclability; multiple types of electrolytes, either in the form of aqueous, solid, or ions, offers safety and stability. Still, to rival the lithium-ion batteries, the SIB needs much more work to improve its performance, further expanding its application. Overall, the SIB has tremendous potential to be the future leading battery technology because of its abundance.

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Jafari, Sadiqa, Zeinab Shahbazi, and Yung-Cheol Byun. "Lithium-Ion Battery Health Prediction on Hybrid Vehicles Using Machine Learning Approach." Energies 15, no. 13 (June 28, 2022): 4753. http://dx.doi.org/10.3390/en15134753.

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Efforts to decarbonize the world have shown a quick increase in electric vehicles (EVs), limiting increasing pollution. During this electric transportation revolution, lithium-ion batteries (LIBs) play a vital role in storing energy. To determine the range of an electric vehicle (EV), the state of charge and the state of health (SOH) of the battery pack is essential. Access to high-quality data on battery parameters is a crucial challenge for researchers working in the energy storage domain due primarily to confidentiality constraints on manufacturers of batteries and EVs. This paper proposes a hybrid framework for predicting the state of a lithium-ion battery for electric vehicles (EV). Electric vehicles are growing worldwide because of their environmental and sustainability advantages. Batteries are replacing fossil fuels in electric vehicles. In order to prevent failure, Li-ion batteries in electric vehicles should be operated and controlled in a controlled and progressive manner to ensure increased efficiency and safety. An extreme gradient boosting (XGBoost) algorithm is used in this paper to estimate the state of health (SOH) of lithium-ion batteries used in electric vehicles. The model is subjected to error analysis to optimize the battery’s performance parameter. The model undergoes an error analysis to optimize its performance parameters. Furthermore, a state of health (SOH) estimation method based on the extreme gradient boosting algorithm with accuracy correction is proposed here to improve the accuracy of state of health (SOH) estimation for lithium-ion batteries. To describe the aging process of batteries, we extract several features such as average voltages, voltage differences, current differences, and temperature differences. The extreme gradient boosting (XGBoost) model for estimating the state of health (SOH) of lithium-ion batteries is based on the ensemble learning algorithm’s higher prediction accuracy and generalization ability. Experimental results suggest that the boundary gradient lifting algorithm model is capable of more accurate prediction.

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Grzeczka, Grzegorz, and Paweł Swoboda. "Analysis of the Possibility of Use Lithium - Ion as a Starting Battery on the Ship Engine Room." Solid State Phenomena 236 (July 2015): 106–12. http://dx.doi.org/10.4028/www.scientific.net/ssp.236.106.

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The most commonly used starter batteries for ship engine rooms are lead acid systems. Lead acid batters have the lowest electrochemical parameters from all other modern electrochemical systems. On the other hand their biggest advantage is the price of the cell which is much lower comparing to other electrochemical systems. Due to fact that the lithium – ion batteries are very widely used and constantly developed this technology is starting to be promising as an alternative for lead acid batteries for starter applications. Because of this there is a need to verify if the lithium - ion technology can be used for start-up and power backup systems and how will it affect the construction of the engine room and those systems. In order to determine the potential energetic requirements during the design of starter systems in an backup engine room with the use of lithium – ion batteries, in the article the analytic of their performance was conducted with comparison of other electrochemical systems.

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Chen, Pengfei, Ziwei Lin, Tian Tan, and Yongzheng Zhang. "Lithium-Ion Battery Development with High Energy Density." Highlights in Science, Engineering and Technology 27 (December 27, 2022): 806–13. http://dx.doi.org/10.54097/hset.v27i.3849.

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With the increasing development of technology, the battery's energy density has improved significantly, which led to improvements in numerous fields, such as the manufacture of electrical vehicles and phones. However, we found out that the battery's energy density is still not as high as expected. For example, electric aircraft are still not ready for mass production as the cost of the production is magnificent. This report will start with the introduction of batteries and how batteries are related to electrical cars to find out the energy density problems of batteries and how to solve those problems. Next, there will be an introduction to electrodes and electrolytes. We will focus on the different properties provided by different materials used to make them up and how to select them.

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Hynes, Toren. "Optimising 3-phenyl-1,4,2-dioxazol-5-one as an electrolyte additive for Lithium-Ion cells." Proceedings of the Nova Scotian Institute of Science (NSIS) 50, no. 2 (March 11, 2020): 373. http://dx.doi.org/10.15273/pnsis.v50i2.10006.

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An effective method to reduce carbon dioxide emissions is to switch to renewables for energy generation and transportation. Since current sources of renewable energy, such as wind and solar, are intermittent, it is essential to find ways to store energy to match supply and demand. If vehicles are to be powered by renewable energy, they need portable energy storage. Currently, lithium-ion batteries are one of the most viable solutions for energy storage. Extending the lifespan of lithium-ion batteries is the goal of this research, carried out with Dr. David Hall of Dr. Jeff Dahn’s research group at Dalhousie University in late 2017. We developed and tested a chemical compound, 3-phenyl-1,4,2-dioxazol-5-one (PDO), which greatly improves the lifespan of lithium-ion batteries. One percent of this by weight in a cell’s electrolyte, along with two percent ethylene sulfate, will extend a battery’s lifespan more than three-fold over those containing conventional vinylene carbonate-containing electrolyte.

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Wang, Xingxing, Yujie Zhang, Yelin Deng, Yinnan Yuan, Fubao Zhang, Shuaishuai Lv, Yu Zhu, and Hongjun Ni. "Effects of Different Charging Currents and Temperatures on the Voltage Plateau Behavior of Li-Ion Batteries." Batteries 9, no. 1 (January 5, 2023): 42. http://dx.doi.org/10.3390/batteries9010042.

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Lithium-ion power batteries, which are the foundation of electric cars and are expected to play a significant role in a variety of operating environments and application situations, have major development prospects. In order to obtain the optimal operation range of ternary Li-ion batteries under various current rates and test temperatures, the characteristics of the voltage plateau period (VPP) of batteries in different states are examined by piecewise fitting based on charging and discharging cycle experiments. The findings demonstrate that while charging at current rates of 0.10C, 0.25C, 0.50C, 0.75C, and 1.00C under temperatures of 40 °C, 25 °C, and 10 °C, the battery’s termination voltage changes seamlessly from 3.5−3.75 V, 3.55−3.8 V, 3.6−3.85 V, 3.7−4 V, and 3.85−4.05 V, the growth in surface temperature does not surpass its maximum level, and the charge capacity exceeds 50%. Batteries operate more effectively. When the test temperature is −20 °C, the voltage rebound stage that occurs in the initial period of charging at 0.50C, 0.75C, and 1.00C accounts for the highest charge capacity, close to 70%. The study’s findings can be used as a guide when designing a lithium-ion power battery’s model and control method for an electric vehicle’s energy storage system.

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Lu, Kaijia, Chuanshan Zhao, and Yifei Jiang. "Research Progress of Cathode Materials for Lithium-ion Batteries." E3S Web of Conferences 233 (2021): 01020. http://dx.doi.org/10.1051/e3sconf/202123301020.

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Lithium-ion batteries have attracted widespread attention as new energy storage materials, and electrode materials, especially cathode materials, are the main factors affecting the electrochemical performance of lithium-ion batteries, and they also determine the cost of preparing lithium-ion batteries. In recent years, there have been a lot of researches on the selection and modification of cathode materials based on lithium-ion batteries to continuously optimize the electrochemical performance of lithium-ion batteries. This article introduces the research progress of cathode materials for lithium ion batteries, including three types of cathode materials (layer oxide, spinel oxide, polyanionic compound) and three modification methods (doping modification, surface coating modification, nano modification method), and prospects for the future development of lithium ion battery cathode materials.

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Zhang, Kai, Jianxiang Yin, and Yunze He. "Acoustic Emission Detection and Analysis Method for Health Status of Lithium Ion Batteries." Sensors 21, no. 3 (January 21, 2021): 712. http://dx.doi.org/10.3390/s21030712.

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The health detection of lithium ion batteries plays an important role in improving the safety and reliability of lithium ion batteries. When lithium ion batteries are in operation, the generation of bubbles, the expansion of electrodes, and the formation of electrode cracks will produce stress waves, which can be collected and analyzed by acoustic emission technology. By building an acoustic emission measurement platform of lithium ion batteries and setting up a cycle experiment of lithium ion batteries, the stress wave signals of lithium ion batteries were analyzed, and two kinds of stress wave signals which could characterize the health of lithium ion batteries were obtained: a continuous acoustic emission signal and a pulse type acoustic emission signal. The experimental results showed that during the discharge process, the amplitude of the continuous acoustic emission signal decreased with the increase of the cycle times of batteries, which could be used to characterize performance degradation; there were more pulse type acoustic emission signals in the first cycle of batteries, less in the small number of cycles, and slowly increased in the large number of cycles, which was in line with the bathtub curve and could be used for aging monitoring. The research on the health of lithium ion batteries by acoustic emission technology provides a new idea and method for detecting the health lithium ion batteries.

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Camargos, Murilo, and Plamen Angelov. "State of Health and Lifetime Prediction of Lithium-ion Batteries Using Self-learning Incremental Models." PHM Society European Conference 7, no. 1 (June 29, 2022): 78–86. http://dx.doi.org/10.36001/phme.2022.v7i1.3323.

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Lithium-ion batteries are key energy storage elements in the context of environmental-aware energy systems representing a crucial technology to achieve the goal of zero carbon emission. Therefore, its conditions must be monitored to guarantee the safe and reliable operation of the systems that use these components. Furthermore, lithium-ion batteries’ prognostics and health management policies must cope with the nonlinear and time-varying nature of the complex electrochemical dynamics of battery degradation. This paper proposes an incremental-learning-based algorithm to estimate the State of Health (SoH) and the Remaining Useful Life (RUL) of lithium-ion batteries based on measurement data streams. For this purpose, a two-layer framework is proposed based on incremental modeling of the SoH. In the first layer, a set of representative features are extracted from voltage and current data of partial charging and discharging cycles; these features are then used to train the proposed model in a recursive procedure to estimate the battery’s SoH. The second layer uses the capacity data for incremental learning of an Autoregressive (AR) model for the SoH, which will be used to propagate the battery’s degradation through time to make the RUL prediction. The proposed method was applied to two datasets for experimental evaluation, one from CALCE and another from NASA. The proposed framework was able to estimate the SoH of 8 different lithium-ion cells with an average percentage error below 1.5% for all scenarios, while the lifetime model predicted the cell’s RUL with a maximum average error of 25%.

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Puttaswamy, Rangaswamy, Suresh Gurukar Shivappa, Mahadevan Kittappa Malavalli, and Yanjerappa Arthoba Nayaka. "Triclinic LiVPO4F/C Cathode For Aqueous Rechargeable Lithium-Ion Batteries." Advanced Materials Letters 10, no. 3 (December 31, 2018): 193–200. http://dx.doi.org/10.5185/amlett.2019.2141.

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Petrov, S. V., S. G. Bondarenko, and Sato Koichi. "Plasmo-chemical process of obtaining nanosilicon for lithium-ion batteries." Paton Welding Journal 2022, no. 10 (October 28, 2022): 49–56. http://dx.doi.org/10.37434/tpwj2022.10.08.

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Zhang, Chaolong, Yigang He, Lifeng Yuan, Sheng Xiang, and Jinping Wang. "Prognostics of Lithium-Ion Batteries Based on Wavelet Denoising and DE-RVM." Computational Intelligence and Neuroscience 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/918305.

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Lithium-ion batteries are widely used in many electronic systems. Therefore, it is significantly important to estimate the lithium-ion battery’s remaining useful life (RUL), yet very difficult. One important reason is that the measured battery capacity data are often subject to the different levels of noise pollution. In this paper, a novel battery capacity prognostics approach is presented to estimate the RUL of lithium-ion batteries. Wavelet denoising is performed with different thresholds in order to weaken the strong noise and remove the weak noise. Relevance vector machine (RVM) improved by differential evolution (DE) algorithm is utilized to estimate the battery RUL based on the denoised data. An experiment including battery 5 capacity prognostics case and battery 18 capacity prognostics case is conducted and validated that the proposed approach can predict the trend of battery capacity trajectory closely and estimate the battery RUL accurately.

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Yang, Qingyun, Yanjin Liu, Hong Ou, Xueyi Li, Xiaoming Lin, Akif Zeb, and Lei Hu. "Fe-Based metal–organic frameworks as functional materials for battery applications." Inorganic Chemistry Frontiers 9, no. 5 (2022): 827–44. http://dx.doi.org/10.1039/d1qi01396c.

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This review presents a comprehensive discussion on the development and application of pristine Fe-MOFs in lithium-ion batteries, sodium-ion batteries, potassium-ion batteries, metal–air batteries and lithium–sulfur batteries.

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Shah, Raj, Vikram Mittal, Eliana Matsil, and Andreas Rosenkranz. "Magnesium-ion batteries for electric vehicles: Current trends and future perspectives." Advances in Mechanical Engineering 13, no. 3 (March 2021): 168781402110033. http://dx.doi.org/10.1177/16878140211003398.

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Lithium-ion batteries have enabled electric vehicles to achieve a foothold in the automobile market. Due to an increasing environmental consciousness, electric vehicles are expected to take a larger portion of the market, with the ultimate goal of supplanting traditional vehicles. However, the involved costs, sustainability, and technical limitations of lithium-ion batteries do create substantial obstacles to this goal. Therefore, this article aims at presenting magnesium-ion batteries as a potential replacement for lithium-ion batteries. Though still under development, magnesium-ion batteries show promise in achieving similar volumetric and specific capacities to lithium-ion batteries. Additionally, magnesium is substantially more abundant than lithium, allowing for the batteries to be cheaper and more sustainable. Numerous technical challenges related to cathode and electrolyte selection are yet to be solved for magnesium-ion batteries. This paper discusses the current state-of-the-art of magnesium-ion batteries with a particular emphasis on the material selection. Although, current research indicates that sulfur-based cathodes coupled with a (HMDS)2Mg-based electrolyte shows substantial promise, other options could allow for a better performing battery. This paper addresses the challenges (materials and costs) and benefits associated with developing these batteries. When overcoming these challenges, magnesium-ion batteries are posed to be a groundbreaking technology potentially revolutionizing the vehicle industry.

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Xie, Xing-Chen, Ke-Jing Huang, and Xu Wu. "Metal–organic framework derived hollow materials for electrochemical energy storage." Journal of Materials Chemistry A 6, no. 16 (2018): 6754–71. http://dx.doi.org/10.1039/c8ta00612a.

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The recent progress and major challenges/opportunities of MOF-derived hollow materials for energy storage are summarized in this review, particularly for lithium-ion batteries, sodium-ion batteries, lithium–Se batteries, lithium–sulfur batteries and supercapacitor applications.

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Chang, Choong-koo. "Factors Affecting Capacity Design of Lithium-Ion Stationary Batteries." Batteries 5, no. 3 (August 28, 2019): 58. http://dx.doi.org/10.3390/batteries5030058.

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Lead-acid batteries are currently the most popular for direct current (DC) power in power plants. They are also the most widely used electric energy storage device but too much space is needed to increase energy storage. Lithium-ion batteries have a higher energy density, allowing them to store more energy than other types of batteries. The purpose of this paper is to elaborate on the factors affecting the capacity design of lithium-ion stationary batteries. Factors that need to be considered in calculating the capacity of stationary lithium-ion batteries are investigated and reviewed, and based on the results, a method of calculating capacity of stationary lithium-ion batteries for industrial use is proposed. In addition, the capacity and area required for replacing the lead-acid batteries for nuclear power plants with lithium-ion batteries are reviewed as part of this case study.

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Guo, Yi, and Yuhang Chen. "Study on SOC Estimation of Li-ion Battery Based on the Comparison of UKF Algorithm and AUKF Algorithm." Journal of Physics: Conference Series 2418, no. 1 (February 1, 2023): 012097. http://dx.doi.org/10.1088/1742-6596/2418/1/012097.

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Abstract In this study, a state of charge (SOC) estimate technique for lithium-ion batteries is presented using an adaptive traceless Kalman filter (AUKF). First, the battery’s second-order RC equivalent circuit model is created, and its parameters are identified. Next, in contrast to the traceless Kalman filter (UKF) algorithm, which ignores the time-varying characteristics of the system noise when estimating the lithium-ion battery’s state of charge, the AUKF-based SOC estimation method is formed from the perspective of adaptive noise adjustment (SOC). The results of testing the AUKF algorithm in real-world settings demonstrate that it has great estimate accuracy and stability and that its estimation outcomes outperform those of the UKF method.

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Gao, Yun, Wujun Ji, and Xiaoqiang Chen. "Numerical Study on Thermal Management of Air-Cooling Model for Diamond, Triangular and Rectangular Lithium-Ion Batteries of Electric Vehicles." Processes 10, no. 6 (June 1, 2022): 1104. http://dx.doi.org/10.3390/pr10061104.

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To improve the safety of electric vehicles, this paper analyzes the way of cooling lithium-ion batteries of electric vehicles and proposes an air-cooling scheme. First, a heat-generation model for the lithium-ion battery is prepared for numerical simulation and a finned air-cooling model is designed, which combines cold air with fins to lower the temperature of lithium-ion batteries. Through feasibility analysis, it is proved that the heat-generation model can reflect the actual heat generation of lithium-ion batteries. The cooling effect of the finned air-cooling model is also evaluated. The temperature can be 23.6 °C lower than the maximum compared with lithium-ion batteries without cooling. The cooling effect is desirable for diamond, triangle and rectangular lithium-ion battery packs, among which the rectangular battery pack achieves the most desirable effect. To conclude, to ensure the safe operation of lithium-ion batteries in electric vehicles, air cooling can be used to control their temperature, with the cooling effect in the rectangular lithium-ion battery pack being the most desirable.

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Zhao, Guang Jin, Wen Long Wu, and Yang Guo. "The Possibility of Using Oxide Cathode Materials of Spent Lithium-Ion Power Batteries for Carbon Dioxide Capture from Fossil Fuel Plant." Advanced Materials Research 779-780 (September 2013): 52–55. http://dx.doi.org/10.4028/www.scientific.net/amr.779-780.52.

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Following during development of electric vehicles and other modern-life appliances, numerous lithium-ion batteries are fabricated and used every year, and their consumption is constantly expanding. However, the battery life of the lithium-ion batteries is about 3 to 5 years, and there are some hazardous and noxious substances in spent lithium-ion batteries. Therefore, it is necessary to recycling these spent batteries with some resourceful and environment friendly technology. In this work, we propose a novel technology of resourceful disposing and utilizing oxide cathode materials from spent power lithium-ion batteries, which is using the recovered compounds from spent lithium-ion batteries to capture carbon dioxide from fossil fuel plant. The detailed technical routes of laboratory scale test and bench scale test are also given in the work.

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Nowak, Sascha, and Martin Winter. "Elemental analysis of lithium ion batteries." Journal of Analytical Atomic Spectrometry 32, no. 10 (2017): 1833–47. http://dx.doi.org/10.1039/c7ja00073a.

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Being successfully introduced into the market only 25 years ago, lithium ion batteries are already state-of-the-art power sources for portable electronic devices and the most promising candidate for energy storage in large-size batteries. Therefore, elemental analysis of lithium ion batteries (lithium ion batteries), their components and decomposition products is a fast growing topic in the literature.

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W, He. "Recycling Potential for Waste Electric Vehicle Lithium - ion Batteries in China." Open Access Journal of Waste Management & Xenobiotics 2, no. 4 (2019): 1–4. http://dx.doi.org/10.23880/oajwx-16000129.

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The number of waste EV LIBs (electric vehicle lithium - ion batteries) has been increasing in China. Reasonable disposal of waste EV LIBs has becoming a new research hotspot. In this paper, the current status of the generation of waste EV LIBs of China is analyzed, and the treatment strategy and recycling market potential of waste EV LIBs are introduced. And some recommendat ions were given for the existing problems in the waste EV LIBs recycling market.

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Yazvinskaya, Nataliya N., Mikhail S. Lipkin, Nikolay E. Galushkin, and Dmitriy N. Galushkin. "Peukert Generalized Equations Applicability with Due Consideration of Internal Resistance of Automotive-Grade Lithium-Ion Batteries for Their Capacity Evaluation." Energies 15, no. 8 (April 13, 2022): 2825. http://dx.doi.org/10.3390/en15082825.

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In this paper, the applicability of the Peukert equation and its generalizations were investigated for capacity evaluation of automotive-grade lithium-ion batteries. It is proved that the classical Peukert equation is applicable within the range of the discharge currents from 0.2Cn to 2Cn (Cn is the nominal battery capacity). As a rule, the operating currents of many automotive-grade lithium-ion batteries are exactly within this range of the discharge currents. That is why, successfully, the classical Peukert equation is used in many analytical models developed for these batteries. The generalized Peukert equation C = Cm/(1 + (i/i0)n) is applicable within the discharge currents range from zero to approximately 10Cn. All kinds of operating discharge currents (including both very small ones and powerful short-term bursts) fall into this discharge currents range. The modified Peukert equation C = Cm(1 − i/i1)/((1 − i/i1) + (i/i0)n) is applicable at any discharge currents. This equation takes into account the battery’s internal resistance and has the smallest error of experimental data approximation. That is why the discussed modified Peukert equation is most preferable for use in analytical models of automotive-grade lithium-ion batteries. The paper shows that all the parameters of the generalized Peukert equations have a clear electrochemical meaning in contrast to the classical Peukert equation, where all the parameters are just empirical constants.

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Pires, Rodrigo A., Samuel A. Carvalho, Braz J. Cardoso Filho, Igor A. Pires, Rudolf Huebner, and Thales A. C. Maia. "The Assessment of Electric Vehicle Storage Lifetime Using Battery Thermal Management System." Batteries 9, no. 1 (December 24, 2022): 10. http://dx.doi.org/10.3390/batteries9010010.

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Degradation and heat generation are among the major concerns when treating Lithium-ion batteries’ health and performance parameters. Due to the high correlation between the battery’s degradation, autonomy and heat generation to the cell’s operational temperature, the Battery Thermal Management System plays a key role in maximizing the battery’s health. Given the fact that the ideal temperature for degradation minimization usually does not match the ideal temperature for heat generation minimization, the BTMS must manage these phenomena in order to maximize the battery’s lifespan. This work presents a new definition of the discharge operation point of a lithium-ion battery based on degradation, autonomy and heat generation. Two cells of different electrodes formulation were modeled and evaluated in a case study. The results demonstrated a 50% improvement on total useful battery cycles in best-case scenarios.

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Lu, Jun Min, and Xiao Kan Wang. "Study on the Lithium-Ion Batteries Performance of Electric Vehicles." Advanced Materials Research 986-987 (July 2014): 1869–72. http://dx.doi.org/10.4028/www.scientific.net/amr.986-987.1869.

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By comprehensive analyzing the lead-acid batteries development situation of electric vehicle at first, and making a comprehensive comparison for the performances and features of the lead-acid batteries, nickel hydrogen batteries and lithium-ion batteries, then studying the charge and discharge performance of the lithium batteries which provides technical support and references for the application and popularization of lithium-ion batteries in electric vehicles.

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Wang, Jie, Ping Nie, Bing Ding, Shengyang Dong, Xiaodong Hao, Hui Dou, and Xiaogang Zhang. "Biomass derived carbon for energy storage devices." Journal of Materials Chemistry A 5, no. 6 (2017): 2411–28. http://dx.doi.org/10.1039/c6ta08742f.

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Biomass-derived carbon materials have received extensive attention as electrode materials for energy storage devices, including electrochemical capacitors, lithium–sulfur batteries, lithium-ion batteries, and sodium-ion batteries.

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Chen, Wenshuai, Haipeng Yu, Sang-Young Lee, Tong Wei, Jian Li, and Zhuangjun Fan. "Nanocellulose: a promising nanomaterial for advanced electrochemical energy storage." Chemical Society Reviews 47, no. 8 (2018): 2837–72. http://dx.doi.org/10.1039/c7cs00790f.

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Nanocellulose from various kinds of sources and nanocellulose-derived materials have been developed for electrochemical energy storage, including supercapacitors, lithium-ion batteries, lithium–sulfur batteries, and sodium-ion batteries.

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P, Nayana. "HIGH PERFORMANCE NANOWIRE ARRAY BATTERY WITH PRELOADED LITHIUM ION." Journal of Electrical Engineering and Automation 01, no. 01 (September 8, 2019): 21–29. http://dx.doi.org/10.36548/jeea.2019.1.003.

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Electricity playing a major role in the most of the application has become a one of the essential requirement in the existing world. The increased requirement of the electricity has led to the necessity of the rechargeable and the storage batteries and the lithium ion batteries have proved to be an effective in energy storage and the energy conversion for many portable and the implantable devices. Despite the capacities of the lithium ion batteries, the greater pressure on the life time of the battery paves way or the alternative, resulting in the emergence of the nanowires battery arrays. The paper proffers a GaN nanowire arrays integrated with the lithium ion batteries to have high performance Nano wire array –lithium ion battery that inhibits the potentials of the lithium ion battery and the GaN nanowires arrays providing an extended lifetime for the batteries.

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Bi, Jikai, Jae-Cheon Lee, and Hao Liu. "Performance Comparison of Long Short-Term Memory and a Temporal Convolutional Network for State of Health Estimation of a Lithium-Ion Battery using Its Charging Characteristics." Energies 15, no. 7 (March 26, 2022): 2448. http://dx.doi.org/10.3390/en15072448.

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The market for eco-friendly batteries is increasing owing to population growth, environmental pollution, and energy crises. The widespread application of lithium-ion batteries necessitates their state of health (SOH) estimation, which is a popular and difficult area of research. In general, the capacity of a battery is selected as a direct health factor to characterize the degradation state of the battery’s SOH. However, it is difficult to directly measure the actual capacity of a battery. Therefore, this study extracted three features from the current, voltage, and internal resistance of a lithium-ion battery during its charging–discharging process to estimate its SOH. A battery-accelerated aging test system was designed to obtain time series battery degradation data. A performance comparison of lithium-ion battery SOH fitting results was conducted for two different deep learning architectures, a long short-term memory (LSTM) network and temporal convolution network (TCN), which are time series deep learning networks based on a recurrent neural network (RNN) and convolutional neural network (CNN), respectively. The results showed that the proposed method has high prediction accuracy, while the performance of the TCN was 3% better than that of the LSTM regarding the average maximum relative error in SOH estimation of a lithium-ion battery.

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Diao, Weiping, Chetan Kulkarni, and Michael Pecht. "Development of an Informative Lithium-Ion Battery Datasheet." Energies 14, no. 17 (September 1, 2021): 5434. http://dx.doi.org/10.3390/en14175434.

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Lithium-ion battery datasheets, also known as specification sheets, are documents that battery manufacturers provide to define the battery’s function, operational limit, performance, reliability, safety, cautions, prohibitions, and warranty. Product manufacturers and customers rely on the datasheets for battery selection and battery management. However, battery datasheets often have ambiguous and, in many cases, misleading terminology and data. This paper reviews and evaluates the datasheets of 25 different lithium-ion battery types from eleven major battery manufacturers. Issues that customers may face are discussed, and recommendations for developing an informative and valuable datasheet that will help customers procure suitable batteries are presented.

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Zhang, Yixing, Shunli Wang, and Wenhua Xu. "An improved smoothing factor-extended kalman filtering method for accurate online state-of-charge estimation of Lithium-ion battery." Journal of Physics: Conference Series 2232, no. 1 (May 1, 2022): 012011. http://dx.doi.org/10.1088/1742-6596/2232/1/012011.

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Abstract The state of charge of battery is an important index of battery management system. The Lithium-ion batteries are widely used in various industries, so they are full of uncertainty, which makes them difficult to estimate the state of charge of Lithium-ion batteries. To solve the problem of low accuracy and large variability in real-time estimation of Lithium-ion batteries, taking Lithium-ion batteries as the research object, the Thevenin model is used to simulate the working characteristics. On the basis of the extended Kalman filtering algorithm, through the influence of the covariance matrix and noise, a smoothing factor is introduced to increase the Kalman gain and improve flexibility. Experiments have proved that the smoothing factor-extended Kalman algorithm improves the flexibility of the algorithm, and at the same time reduces the non-linear error caused by the rapid charging and discharging changes of Lithium-ion batteries. In the Hybrid Pulse Power Characterization test, the maximum estimation error is 0.14%, and the average estimation error is 0.1%. It provides a new method for estimating the state of charge of Lithium-ion batteries.

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Zou, Gang, Zhen Yan, Chengying Zhang, and Lei Song. "Transfer learning with CNN-LSTM model for capacity prediction of lithium-ion batteries under small sample." Journal of Physics: Conference Series 2258, no. 1 (April 1, 2022): 012042. http://dx.doi.org/10.1088/1742-6596/2258/1/012042.

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Abstract Nowadays, the application of lithium-ion batteries in various industries including our daily life is increasing, so the evaluation of the safety and reliability of lithium-ion batteries is essential. Assessing the performance of lithium-ion batteries accurately and in real-time has become a more critical research direction. However, in most application scenarios, the problem of small sample is often hidden in performance evaluation tasks of lithium-ion batteries. A model-based transfer learning framework to solve this problem is presented in this paper. Firstly, a CNN-LSTM fusion model is proposed by combining the solid spatial feature extraction capability of convolutional neural network (CNN) and the solid temporal dimensional feature extraction capability of long short-term memory network (LSTM); further, a model-based transfer learning approach is introduced to accomplish the performance evaluation task by pre-training and re-training. The experiments are conducted on NASA’s public dataset of lithium-ion batteries, and multiple sets of comparison experiments are set up. The results show that the method can better solve the small sample problem encountered in the lithium-ion batteries performance evaluation task.

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Reddy, Mogalahalli V., Alain Mauger, Christian M. Julien, Andrea Paolella, and Karim Zaghib. "Brief History of Early Lithium-Battery Development." Materials 13, no. 8 (April 17, 2020): 1884. http://dx.doi.org/10.3390/ma13081884.

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Lithium batteries are electrochemical devices that are widely used as power sources. This history of their development focuses on the original development of lithium-ion batteries. In particular, we highlight the contributions of Professor Michel Armand related to the electrodes and electrolytes for lithium-ion batteries.

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Chen, Yuxin. "Enhance the Market Competitiveness of Electric Vehicles by Improving the Design of Lithium-ion Batteries." Highlights in Science, Engineering and Technology 32 (February 12, 2023): 245–51. http://dx.doi.org/10.54097/hset.v32i.5173.

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Electric vehicles (EVs) are increasingly popular because they are energy efficient and capable of providing a good driving experience. However, the performance and market competitiveness of electric vehicles has been limited by a series of shortcomings, which are mainly caused by the limitations of the power source, lithium-ion batteries. To address these problems from the origin, this research analysed the causes of these problems and proposed some possible solutions based on the characteristics and working principles of lithium-ion batteries. The limitations of electric vehicles such as safety issues, low range, high cost, and limited life span are all proved to be related to the EV batteries. Lithium-ion batteries used by electric vehicles have the risk of fire and explosion when broken, overcharged, or exposed to high temperatures. The capacity and life span of them can easily be affected by different factors, which leads to the dissatisfaction of customers with the range and EV batteries’ life span. Furthermore, the production of lithium-ion batteries is very costly. Different ways to improve the performance of lithium-ion batteries are collected and evaluated. Finally, it is concluded that Li-S batteries and lithium titanate batteries are likely to become the solutions to what limited the development of electric vehicles. Since Li-S batteries and lithium titanate batteries still have some disadvantages, researchers should manage to tackle them in the future before they can be widely applied. This paper provides directions for the future development of EV batteries to improve the market competitiveness of electric vehicles.

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Jafari, Sadiqa, and Yung-Cheol Byun. "XGBoost-Based Remaining Useful Life Estimation Model with Extended Kalman Particle Filter for Lithium-Ion Batteries." Sensors 22, no. 23 (December 6, 2022): 9522. http://dx.doi.org/10.3390/s22239522.

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The instability and variable lifetime are the benefits of high efficiency and low-cost issues in lithium-ion batteries.An accurate equipment’s remaining useful life prediction is essential for successful requirement-based maintenance to improve dependability and lower total maintenance costs. However, it is challenging to assess a battery’s working capacity, and specific prediction methods are unable to represent the uncertainty. A scientific evaluation and prediction of a lithium-ion battery’s state of health (SOH), mainly its remaining useful life (RUL), is crucial to ensuring the battery’s safety and dependability over its entire life cycle and preventing as many catastrophic accidents as feasible. Many strategies have been developed to determine the prediction of the RUL and SOH of lithium-ion batteries, including particle filters (PFs). This paper develops a novel PF-based technique for lithium-ion battery RUL estimation, combining a Kalman filter (KF) with a PF to analyze battery operating data. The PF method is used as the core, and extreme gradient boosting (XGBoost) is used as the observation RUL battery prediction. Due to the powerful nonlinear fitting capabilities, XGBoost is used to map the connection between the retrieved features and the RUL. The life cycle testing aims to gather precise and trustworthy data for RUL prediction. RUL prediction results demonstrate the improved accuracy of our suggested strategy compared to that of other methods. The experiment findings show that the suggested technique can increase the accuracy of RUL prediction when applied to a lithium-ion battery’s cycle life data set. The results demonstrate the benefit of the presented method in achieving a more accurate remaining useful life prediction.

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Ouyang, Quan, Rui Ma, Zhaoxiang Wu, Guotuan Xu, and Zhisheng Wang. "Adaptive Square-Root Unscented Kalman Filter-Based State-of-Charge Estimation for Lithium-Ion Batteries with Model Parameter Online Identification." Energies 13, no. 18 (September 22, 2020): 4968. http://dx.doi.org/10.3390/en13184968.

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The state-of-charge (SOC) is a fundamental indicator representing the remaining capacity of lithium-ion batteries, which plays an important role in the battery’s optimized operation. In this paper, the model-based SOC estimation strategy is studied for batteries. However, the battery’s model parameters need to be extracted through cumbersome prior experiments. To remedy such deficiency, a recursive least squares (RLS) algorithm is utilized for model parameter online identification, and an adaptive square-root unscented Kalman filter (SRUKF) is designed to estimate the battery’s SOC. As demonstrated in extensive experimental results, the designed adaptive SRUKF combined with RLS-based model identification is a promising SOC estimation approach. Compared with other commonly used Kalman filter-based methods, the proposed algorithm has higher precision in the SOC estimation.

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Schmidgruber, Nils, Dominik Mayer, and Jürgen Fleischer. "Hochproduktive, hydraulische Batteriezellfertigung/Highly productive, hydraulic batterycell manufacturing - Plan for the highly productive manufacturing of lithium-ion batteries using a hydraulic press." wt Werkstattstechnik online 112, no. 09 (2022): 586–90. http://dx.doi.org/10.37544/1436-4980-2022-09-58.

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In diesem Beitrag wird ein neuartiges Konzept zur Herstellung von Lithium-Ionen-Batterien vorgestellt, das den Ablauf einer Pressenstraße auf die Batteriezellfertigung adaptiert. Es werden Optimierungspotenziale in den Teilprozessen analysiert und in Konzeptform ausgenutzt. Das Konzept wird anhand von Vorversuchen bewertet. This paper presents a novel plan for the production of lithium-ion batteries that adapts the sequence of a press line to battery cell production. Opportunities for improving the sub-processes are analysed and exploited in forming a plan. The plan is evaluated on the basis of preliminary tests.

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Long, Bing, Xiangnan Li, Xiaoyu Gao, and Zhen Liu. "Prognostics Comparison of Lithium-Ion Battery Based on the Shallow and Deep Neural Networks Model." Energies 12, no. 17 (August 25, 2019): 3271. http://dx.doi.org/10.3390/en12173271.

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Prognostics of the remaining useful life (RUL) of lithium-ion batteries is a crucial role in the battery management systems (BMS). An artificial neural network (ANN) does not require much knowledge from the lithium-ion battery systems, thus it is a prospective data-driven prognostic method of lithium-ion batteries. Though the ANN has been applied in prognostics of lithium-ion batteries in some references, no one has compared the prognostics of the lithium-ion batteries based on different ANN. The ANN generally can be classified to two categories: the shallow ANN, such as the back propagation (BP) ANN and the nonlinear autoregressive (NAR) ANN, and the deep ANN, such as the long short-term memory (LSTM) NN. An improved LSTM NN is proposed in order to achieve higher prediction accuracy and make the construction of the model simpler. According to the lithium-ion data from the NASA Ames, the prognostics comparison of lithium-ion battery based on the BP ANN, the NAR ANN, and the LSTM ANN was studied in detail. The experimental results show: (1) The improved LSTM ANN has the best prognostic accuracy and is more suitable for the prediction of the RUL of lithium-ion batteries compared to the BP ANN and the NAR ANN; (2) the NAR ANN has better prognostic accuracy compared to the BP ANN.

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Guo, Dongxu, Geng Yang, Guangjin Zhao, Mengchao Yi, Xuning Feng, Xuebing Han, Languang Lu, and Minggao Ouyang. "Determination of the Differential Capacity of Lithium-Ion Batteries by the Deconvolution of Electrochemical Impedance Spectra." Energies 13, no. 4 (February 18, 2020): 915. http://dx.doi.org/10.3390/en13040915.

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Electrochemical impedance spectroscopy (EIS) is a powerful tool for investigating electrochemical systems, such as lithium-ion batteries or fuel cells, given its high frequency resolution. The distribution of relaxation times (DRT) method offers a model-free approach for a deeper understanding of EIS data. However, in lithium-ion batteries, the differential capacity caused by diffusion processes is non-negligible and cannot be decomposed by the DRT method, which limits the applicability of the DRT method to lithium-ion batteries. In this study, a joint estimation method with Tikhonov regularization is proposed to estimate the differential capacity and the DRT simultaneously. Moreover, the equivalence of the differential capacity and the incremental capacity is proven. Different types of commercial lithium-ion batteries are tested to validate the joint estimation method and to verify the equivalence. The differential capacity is shown to be a promising approach to the evaluation of the state-of-health (SOH) of lithium-ion batteries based on its equivalence with the incremental capacity.

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Liu, Guanchen, and Lijun Zhang. "Research on the Thermal Characteristics of an 18650 Lithium-Ion Battery Based on an Electrochemical–Thermal Flow Coupling Model." World Electric Vehicle Journal 12, no. 4 (November 24, 2021): 250. http://dx.doi.org/10.3390/wevj12040250.

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Aiming at the complex experimental conditions of multi-physical field coupling in the analysis of thermal characteristics of lithium-ion batteries, a three-dimensional electrochemical-thermal flow coupling model for lithium-ion batteries was established using COMSOL Multiphysics software. Through the analysis of simulation results, the thermal characteristics of lithium-ion batteries for electric vehicles were explored from the aspects of heat generation and dissipation. It was found that increasing the charge–discharge rate and the electrode thickness will increase the temperature rise rate of lithium-ion batteries, and the temperature rise rate of lithium-ion batteries is the highest during their first time charging and discharging. Increasing the airflow velocity and reducing the size of the inlet flow area can improve the cooling effect on the cell. Under a single inlet, the cooling effect of the airflow field entering from the negative electrode is better than that from the positive electrode.

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Madani, Seyed Saeed, Erik Schaltz, and Søren Knudsen Kær. "Applying Different Configurations for the Thermal Management of a Lithium Titanate Oxide Battery Pack." Electrochem 2, no. 1 (January 23, 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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Chen, Libao, Ming Zhang, and Weifeng Wei. "Graphene-Based Composites as Cathode Materials for Lithium Ion Batteries." Journal of Nanomaterials 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/940389.

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Owing to the superior mechanical, thermal, and electrical properties, graphene was a perfect candidate to improve the performance of lithium ion batteries. Herein, we review the recent advances in graphene-based composites and their application as cathode materials for lithium ion batteries. We focus on the synthesis methods of graphene-based composites and the superior electrochemical performance of graphene-based composites as cathode materials for lithium ion batteries.

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Zhou, Fang, Yong Zhong, and Pei Zhang. "Research on Thermal Management System for the Vehicle Application of Lithium-Ion Power Batteries." Advanced Materials Research 347-353 (October 2011): 984–88. http://dx.doi.org/10.4028/www.scientific.net/amr.347-353.984.

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Thermal management technique is one of the key techniques for the vehicle application of lithium-ion power batteries. Based on the analysis of thermal characteristics of the lithium-ion power batteries, the establishment of thermal model and numerical simulation for the lithium-ion power batteries were discussed. Finally, a procedure for designing battery thermal management system (BTMS) was proposed, and the key techniques during designing a BTMS were studied, including selection of heat transfer medium, design of cooling/heating structure and so on. This research provides a technique support for designing a good and effective BTMS, as well as improving the working performance and security of the lithium-ion power batteries and the electric vehicles.

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Tao, Yibin, Jinhua Xue, Min Xia, Jin Tao, Qichao Zhang, Xiao Li, Qiangqiang Liao, Cheng Li, and Haibo Tang. "Economic Feasibility of Echelon Utilization Battery in Photovoltaic Energy Storage." E3S Web of Conferences 194 (2020): 02001. http://dx.doi.org/10.1051/e3sconf/202019402001.

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Taking the power load of an industrial park in Shanghai as an example in this paper, particle swarm optimization and cost-benefit model are employed to analyse the economy of new lithium-ion batteries, echelon lithium-ion batteries and lead-carbon batteries in photovoltaic energy storage systems in the whole life cycle. The research results showed that the economic order from large to small among different batteries in the photovoltaic energy storage system was new lithium-ion battery, echelon utilization lithium-ion battery and lead-carbon battery. The declines in energy storage cost and discount rate and the rise in peak electricity price can greatly improve the net present value of a photovoltaic-energy storage system (PV-BES) system.

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Su, Chun, Hongjing Chen, and Zejun Wen. "Prediction of remaining useful life for lithium-ion battery with multiple health indicators." Eksploatacja i Niezawodnosc - Maintenance and Reliability 23, no. 1 (January 2, 2021): 176–83. http://dx.doi.org/10.17531/ein.2021.1.18.

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Lithium-ion (Li-ion) battery has become a primary energy form for a variety of engineering equipments. To ensure the equipments’ reliability, it is crucial to accurately predict Liion battery’s remaining capacity as well as its remaining useful life (RUL). In this study, we propose a novel method for Li-ion battery’s online RUL prediction, which is based on multiple health indicators (HIs) and can be derived from the battery’s historical operation data. Firstly, four types of indirect HIs are built according to the battery’s operation current, voltage and temperature data respectively. On this basis, a generalized regression neural network (GRNN) is presented to estimate the battery’s remaining capacity, and the nonlinear autoregressive approach (NAR) is applied to predict the battery’s RUL based on the estimated capacity value. Furthermore, to reduce the interference, twice wavelet denoising are performed with different thresholds. A case study is conducted with a NASA battery dataset to demonstrate the effectiveness of the method. The result shows that the proposed method can obtain Li-ion batteries’ RUL effectively.

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Poyner, Mark A., Indumini Jayasekara, and Dale Teeters. "Fabrication of a Novel Nanostructured SnO2/LiCoO2 Lithium-Ion Cell." MRS Advances 1, no. 45 (2016): 3075–81. http://dx.doi.org/10.1557/adv.2016.537.

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ABSTRACTIncorporating nanotechnology processes and techniques to Li ion batteries has helped to improve the cycling capabilities and overall performance of several lithium ion battery chemistries. Nanostructuring a lithium ion battery’s anode and cathode, allows for extremely high surface area electrodes to be produced and utilized in many of these battery systems. Using a nanoporous Anodized Aluminum Oxide (AAO) membrane with nanopores of 200nm in diameter as a template, high surface area nanostructured electrode materials can be synthesized and utilized in a lithium ion cell. Through the use of RF magnetron sputter coating, these nanoporous AAO templates can be sputter coated with a thin film of active anode or cathode materials. The anode and cathode material in this research are SnO2 and LiCoO2, respectively. Nanostructured SnO2 has been investigated as an alternative high capacity anode to replace the more commonly used carbon based anodes of current lithium ion batteries. A novel nanostructured SnO2/LiCoO2 cell can be fabricated in a liquid electrolyte. The galvanostatic cell cycling performance will be discussed. Nanostructuring both electrode materials as well as the electrolyte can lead to a novel all-solid-state Li ion battery. Nanostructured SnO2 anode and LiCoO2 electrodes have been generated along with a polyethylene-oxide (PEO) based electrolyte nanoconfined in an AAO membrane, to generate a functioning nanostructured all-solid-state cell. The cell was investigated using AC impedance spectroscopy and galvanostatic cell cycling. The cycling results of both SnO2/LiCoO2 cell systems will be discussed.

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Journal articles on the topic 'Litium ion batteries'

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