scholarly journals Extreme Learning Machine Based Thermal Model for Lithium-ion Batteries of Electric Vehicles under External Short Circuit

Engineering ◽  
2020 ◽  
Author(s):  
Ruixin Yang ◽  
Rui Xiong ◽  
Weixiang Shen ◽  
Xinfan Lin
Keyword(s):  
Lithium Ion Batteries ◽  
Extreme Learning Machine ◽  
Electric Vehicles ◽  
Thermal Model ◽  
Short Circuit ◽  
Lithium Ion ◽  
Learning Machine

Remaining Useful Life Prediction of Lithium-ion Batteries Using Multiple Kernel Extreme Learning Machine

2020 ◽  
Vol 13 ◽  
Author(s):  
Renxiong Liu
Keyword(s):  
Lithium Ion Batteries ◽  
Extreme Learning Machine ◽  
Kernel Function ◽  
Lithium Ion ◽  
Remaining Useful Life ◽  
Prediction Methods ◽  
Multiple Kernel ◽  
Kernel Extreme Learning Machine ◽  
Useful Life ◽  
Learning Machine

Objective: Lithium-ion batteries are important components used in electric automobiles (EVs), fuel cell EVs and other hybrid EVs. Therefore, it is greatly important to discover its remaining useful life (RUL). Methods: In this paper, a battery RUL prediction approach using multiple kernel extreme learning machine (MKELM) is presented. The MKELM’s kernel keeps diversified by consisting multiple kernel functions including Gaussian kernel function, Polynomial kernel function and Sigmoid kernel function, and every kernel function’s weight and parameter are optimized through differential evolution (DE) algorithm. Results : Battery capacity data measured from NASA Ames Prognostics Center are used to demonstrate the prediction procedure of the proposed approach, and the MKELM is compared with other commonly used prediction methods in terms of absolute error, relative accuracy and mean square error. Conclusion: The prediction results prove that the MKELM approach can accurately predict the battery RUL. Furthermore, a compare experiment is executed to validate that the MKELM method is better than other prediction methods in terms of prediction accuracy.

scholarly journals Detection Technology for Battery Safety in Electric Vehicles: A Review

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4636
Author(s):  
JiYang Xu ◽  
Jian Ma ◽  
Xuan Zhao ◽  
Hao Chen ◽  
Bin Xu ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Electric Vehicles ◽  
Short Circuit ◽  
Lithium Ion ◽  
Thermal Runaway ◽  
Research Progress ◽  
Future Research ◽  
Safety Testing ◽  
Power Battery ◽  
Detection Technology

The safety of electric vehicles (EVs) has aroused widespread concern and attention. As the core component of an EV, the power battery directly affects the performance and safety. In order to improve the safety of power batteries, the internal failure mechanism and behavior characteristics of internal short circuit (ISC) and thermal runaway (TR) in extreme cases need to be tested and studied. The safety of lithium ion batteries (LIBs) has become a research hotspot for many scholars. With unreasonable misuse or abuse of lithium ion batteries, it is easy to cause internal short circuits, resulting in thermal runaway, which poses a great threat to the safety of the whole vehicle. This comprehensive review aims to describe the research progress of safety testing methods and technologies of lithium ion batteries under conditions of mechanical, electrical, and thermal abuse, and presents existing problems and future research directions.

scholarly journals Investigation of effects of design parameters on the internal short-circuit in cylindrical lithium-ion batteries

RSC Advances ◽  
2017 ◽  
Vol 7 (24) ◽  
pp. 14360-14371 ◽  
Author(s):  
Jun Xu ◽  
Yijing Wu ◽  
Sha Yin
Keyword(s):  
Lithium Ion Batteries ◽  
Electric Vehicles ◽  
Short Circuit ◽  
Lithium Ion ◽  
Design Parameters ◽  
Power Sources ◽  
Internal Short Circuit

Cylindrical lithium-ion batteries are now widely applied in electric vehicles as power sources, but they still have an inevitable risk of internal short-circuit accompanied by catastrophic consequences.

scholarly journals Development of a Thermal Model for Lithium-Ion Batteries for Plug-In Hybrid Electric Vehicles

2012 ◽  
Vol 5 (2) ◽  
pp. 300-306
Author(s):  
N. Omar ◽  
M. Al Sakka ◽  
M. Daowd ◽  
P. Van den Bossche ◽  
J. Van Mierlo ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Electric Vehicles ◽  
Thermal Model ◽  
Hybrid Electric Vehicles ◽  
Lithium Ion ◽  
Hybrid Electric
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