Faulty Characteristics and Identification of Increased Connecting and Internal Resistance in Parallel-Connected Lithium-Ion Battery Pack for Electric Vehicles

2020 ◽  
Vol 69 (10) ◽  
pp. 10797-10808
Author(s):  
Mina Ma ◽  
Qiangling Duan ◽  
Chunpeng Zhao ◽  
Qingsong Wang ◽  
Jinhua Sun
Keyword(s):  
Lithium Ion Battery ◽  
Electric Vehicles ◽  
Lithium Ion ◽  
Internal Resistance ◽  
Battery Pack

Lithium-Ion Battery Packs Formation With Improved Electrochemical Performance for Electric Vehicles: Experimental and Clustering Analysis

2019 ◽  
Vol 16 (2) ◽  
Author(s):  
Liu Yun ◽  
Jayne Sandoval ◽  
Jian Zhang ◽  
Liang Gao ◽  
Akhil Garg ◽  
...  
Keyword(s):  
Electrochemical Performance ◽  
Lithium Ion Batteries ◽  
Lithium Ion Battery ◽  
Electric Vehicles ◽  
Clustering Analysis ◽  
Lithium Ion ◽  
Internal Resistance ◽  
Battery Pack ◽  
Self Organizing Map ◽  
Battery Packs

With the increase of production of electrical vehicles (EVs) and battery packs, lithium ion batteries inconsistency problem has drawn much attention. Lithium ion battery imbalance phenomenon exists during three different stages of life cycle. First stage is premanufacturing of battery pack i.e., during the design, the cells of similar performance need to be clustered to improve the performance of pack. Second is during the use of battery pack in EVs, batteries equalization is necessary. In the third stage, clustering of spent lithium ion batteries for reuse is also an important problem because of the great recycling challenge of lithium batteries. In this work, several clustering and equalization methods are compared and summarized for different stages. The methods are divided into the traditional methods and intelligent methods. The work also proposes experimental combined clustering analysis for new lithium-ion battery packs formation with improved electrochemical performance for electric vehicles. Experiments were conducted by dismantling of pack and measurement of capacity, voltage, and internal resistance data. Clustering analysis based on self-organizing map (SOM) neural networks is then applied on the measured data to form clusters of battery packs. The validation results conclude that the battery packs formed from the clustering analysis have higher electrochemical performance than randomly selected ones. In addition, a comprehensive discussion was carried out.

Model based insulation fault diagnosis for lithium-ion battery pack in electric vehicles

Measurement ◽  
2019 ◽  
Vol 131 ◽  
pp. 443-451 ◽  
Author(s):  
Yujie Wang ◽  
Jiaqiang Tian ◽  
Zonghai Chen ◽  
Xingtao Liu
Keyword(s):  
Fault Diagnosis ◽  
Lithium Ion Battery ◽  
Electric Vehicles ◽  
Lithium Ion ◽  
Battery Pack ◽  
Model Based

Metallurgical and mechanical methods for recycling of lithium-ion battery pack for electric vehicles

2018 ◽  
Vol 136 ◽  
pp. 198-208 ◽  
Author(s):  
Liu Yun ◽  
Duy Linh ◽  
Li Shui ◽  
Xiongbin Peng ◽  
Akhil Garg ◽  
...  
Keyword(s):  
Lithium Ion Battery ◽  
Electric Vehicles ◽  
Lithium Ion ◽  
Battery Pack ◽  
Mechanical Methods

Temperature Distribution Optimization of an Air-Cooling Lithium-Ion Battery Pack in Electric Vehicles Based on the Response Surface Method

2019 ◽  
Vol 16 (4) ◽  
Author(s):  
Xiangping Liao ◽  
Chong Ma ◽  
Xiongbin Peng ◽  
Akhil Garg ◽  
Nengsheng Bao
Keyword(s):  
Temperature Distribution ◽  
Lithium Ion Battery ◽  
Electric Vehicles ◽  
Cooling System ◽  
Lithium Ion ◽  
Battery Pack ◽  
Maximum Temperature ◽  
Air Cooling ◽  
Optimized Design ◽  
Original Design

Electric vehicles have become a trend in recent years, and the lithium-ion battery pack provides them with high power and energy. The battery thermal system with air cooling was always used to prevent the high temperature of the battery pack to avoid cycle life reduction and safety issues of lithium-ion batteries. This work employed an easily applied optimization method to design a more efficient battery pack with lower temperature and more uniform temperature distribution. The proposed method consisted of four steps: the air-cooling system design, computational fluid dynamics code setups, selection of surrogate models, and optimization of the battery pack. The investigated battery pack contained eight prismatic cells, and the cells were discharged under normal driving conditions. It was shown that the optimized design performs a lower maximum temperature of 2.7 K reduction and a smaller temperature standard deviation of 0.3 K reduction than the original design. This methodology can also be implemented in industries where the battery pack contains more battery cells.

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