An Active Equalization Technique Based on Flyback Converter Topology

2014 ◽  
Vol 721 ◽  
pp. 612-617
Author(s):  
Hong Wei Liu ◽  
Hong He ◽  
Yu Gui ◽  
Xiao Wei Hao
Keyword(s):  
Lithium Ion Battery ◽  
Lithium Ion ◽  
Active Cell ◽  
Battery Pack ◽  
Flyback Converter ◽  
Operational Principle ◽  
Converter Topology ◽  
Equalization Technique ◽  
Working Status ◽  
Cell Balancing

This paper presents an active cell balancing technique for lithium-ion battery stacks using a flyback dc/dc converter topology. The combination of batteries can be controlled according to the batteries voltages to implement the battery-balancing function. The operational principle of the proposed system is described in detail, then the paper develops different strategies adapting to different working status of battery pack and a series of bench experiments is conducted to examine the effectiveness of the equalization system.

Active cell balancing of lithium‐ion battery pack based on average state of charge

2020 ◽  
Vol 44 (4) ◽  
pp. 2535-2548 ◽  
Author(s):  
Zhiyong Zhang ◽  
Liuzhu Zhang ◽  
Lin Hu ◽  
Caixia Huang
Keyword(s):  
Lithium Ion Battery ◽  
Lithium Ion ◽  
State Of Charge ◽  
Active Cell ◽  
Battery Pack ◽  
Cell Balancing ◽  
Average State

scholarly journals Lithium-Ion Battery Cell-Balancing Algorithm for Battery Management System Based on Real-Time Outlier Detection

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Changhao Piao ◽  
Zhaoguang Wang ◽  
Ju Cao ◽  
Wei Zhang ◽  
Sheng Lu
Keyword(s):  
Lithium Ion Battery ◽  
Outlier Detection ◽  
Management System ◽  
Lithium Ion ◽  
Battery Pack ◽  
Battery Management System ◽  
Battery Management ◽  
Battery Cell ◽  
Online Clustering ◽  
Cell Balancing

A novel cell-balancing algorithm which was used for cell balancing of battery management system (BMS) was proposed in this paper. Cell balancing algorithm is a key technology for lithium-ion battery pack in the electric vehicle field. The distance-based outlier detection algorithm adopted two characteristic parameters (voltage and state of charge) to calculate each cell’s abnormal value and then identified the unbalanced cells. The abnormal and normal type of battery cells were acquired by online clustering strategy and bleeding circuits (R= 33 ohm) were used to balance the abnormal cells. The simulation results showed that with the proposed balancing algorithm, the usable capacity of the battery pack increased by 0.614 Ah (9.5%) compared to that without balancing.

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