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Keywords: lithium-ion battery
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Journal Articles

Experimental Investigation on the Combustion Characteristics of Electrolyte Jets Containing Flame Retardant Tris (2-Chloroethyl) Phosphate

Zhou Jie, Peng Hui-Sheng, Zheng Dong
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research Papers
J. Energy Resour. Technol. September 2024, 146(9): 092301.
Paper No: JERT-24-1221
https://doi.org/10.1115/1.4065597
Published Online: June 7, 2024
...Zhou Jie; Peng Hui-Sheng; Zheng Dong It is critical to well understand the combustion characteristics of the electrolytes inside lithium-ion batteries for safety concerns, particularly the electrolyte jet flames after thermal runaway. An electrolyte jet fire setup is developed in this study...
View Article titled, Experimental Investigation on the Combustion Characteristics of Electrolyte Jets Containing Flame Retardant Tris (2-Chloroethyl) Phosphate
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Topics: Combustion, Electrolytes, Flame retardants, Flames, Jets, Temperature, Delays, Ignition delay
Journal Articles

Lithium-Ion Batteries’ Energy Efficiency Prediction Using Physics-Based and State-of-the-Art Artificial Neural Network-Based Models

Arash Nazari, Soheil Kavian, Ashkan Nazari
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research Papers
J. Energy Resour. Technol. October 2020, 142(10): 102001.
Paper No: JERT-20-1259
https://doi.org/10.1115/1.4047313
Published Online: June 12, 2020
...Arash Nazari; Soheil Kavian; Ashkan Nazari The new generation of lithium-ion batteries (LIBs) possesses considerable energy density that arise the safety concern much more than before. One of the main issues associated with LIB safety is the heat generation and thermal runaway in LIBs...
View Article titled, <span class="search-highlight">Lithium</span>-<span class="search-highlight">Ion</span> <span class="search-highlight">Batteries</span>’ Energy Efficiency Prediction Using Physics-Based and State-of-the-Art Artificial Neural Network-Based Models
Open the PDF for <span class="search-highlight">Lithium</span>-<span class="search-highlight">Ion</span> <span class="search-highlight">Batteries</span>’ Energy Efficiency Prediction Using Physics-Based and State-of-the-Art Artificial Neural Network-Based Models in another window
Topics: Energy efficiency, Heat, Lithium-ion batteries, Artificial neural networks, Graphite, Electrodes, Physics