Investigation of active cell balancing performance for series connected lithium‐ion cells in electric vehicle applications

• Published in: IET power electronics 2023-11, Vol.16 (15), p.2492-2503
• Main Authors: Krishnamoorthy, Umapathi, Satheesh Kumar, Gobichettipalyam Shanmugam, Barua, Sourav, Fayek, Hady Habib
• Format: Article
• Language: English
• Subjects: buck converter; cell balancing; cell voltage; lithium‐ion battery; reconfigurable battery system; state of charge
• ISSN: 1755-4535; 1755-4543
• DOI: 10.1049/pel2.12575

Lithium‐ion batteries have a very wide application range. They can power up small electronic devices such as smart watches to larger electric vehicles. Due to its varied range of applications, they come in different packaging and in such battery packs, even when individual cell voltage exceeds by a few milli‐volts above 4.2 V, it may result in thermal runaway and explode the cell. During discharge cycle, cell imbalances hinder the use of battery to its full capacity. This in turn decreases the battery lifetime. The individual battery cells should be equalized on a regular basis to keep the imbalances to a minimum and to have a good battery life. The process of balancing the individual cell charges by measuring the cell state of charge (SoC) and its voltage in a battery pack is known as cell balancing. This paper details an active cell balancing technique that uses a buck converter for balancing a series connected battery pack of lithium‐ion cells. A buck converter along with a pair of MOSFET switches for each cell, one turned on for charging the cell and the other one turned on while discharging the cell is used in this experiment. An algorithmic model suitable for reconfigurable battery systems that measures the individual cell voltages and is developed for balancing a pack of series connected Li‐ion battery cells. The developed model is simulated using MATLAB for verifying its performance. A state of charge of 25% is maintained across the cells and when SoC value drops below this even a difference of 0.02% is sensed by the algorithm to initiate balancing function. This balancing is found to take 275 ms to balance three 3.7 V batteries and thus the model is found to respond faster. The results show that this method can self‐adaptively attain satisfactory performance within a limited equalizing period.