News Release

An active equalization strategy for series-connected lithium-ion battery packs based on a dual threshold trigger mechanism

Peer-Reviewed Publication

Beijing Institute of Technology Press Co., Ltd

The DTTM-based AES framework using dual-threshold trigger mechanism.

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An active equalization strategy for series-connected lithium-ion battery packs based on a dual threshold trigger mechanism

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Credit: GREEN ENERGY AND INTELLIGENT TRANSPORTATION

To address the issue of cell imbalance within battery packs, researchers have proposed an active equalization control strategy, incorporating a dual threshold triggering mechanism and an energy transfer path optimization feature. Both simulation and experimentation on an equalization test platform have demonstrated that the equalization strategy significantly reduces cell inconsistencies and heightens the battery pack's equalization efficiency.

A paper describing the equalization control strategy of lithium battery pack with dual threshold triggering mechanism and path optimization function was published in the journal Green Energy and Intelligent Transportation on June 18th, 2024.

Lithium-ion batteries are prevalent in electric vehicles due to their high energy density, durability, and low self-discharge. To fulfill voltage demands of electric vehicles, multiple single cells are usually connected in series to form a battery pack. However, inconsistencies in production, assembly, and manufacturing processes often lead to discrepancies among battery cells. These inconsistencies worsen over time, shortening battery pack lifespan. Thus, a reasonable and effective equalization strategy is crucial to minimize cell inconsistencies and enhance pack performance.

Researchers proposed an active equalization strategy for series lithium-ion battery packs, utilizing a dual threshold trigger mechanism (DTTM). Initially, by integrating the linearization capabilities of the Extended Kalman Filter with the observation prowess of the Particle Filter, the Extended Kalman Particle Filter (EKPF) algorithm is employed to increase the accuracy of SOC estimation, which subsequently triggers the equalization control strategy. Additionally, a modified dual-layer inductor equalization circuit is introduced to achieve energy transfer between non-adjacent cells, while an improved particle swarm optimization (IPSO) algorithm is used to acquire the optimal energy transfer path within the battery pack, further improving the equalization efficiency.

The researchers carefully designed the equalization topology circuit and control method, and verified the high efficiency of the proposed equalization strategy through simulation and experiment platform testing. The results show that the proposed equalization strategy can effectively control the battery pack, thereby reducing the inherent inconsistencies between cells.

In future efforts, the researchers will consider reducing the computational cost of the proposed equalization strategy and implementing it in real electric vehicles.

 

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Reference

Author: Hui Pang a, Wenzhi Nan a, Xiaofei Liu a, Fengbin Wang a, Kaiqiang Chen a, Yupeng Chen b

Affiliations:

aSchool of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, China

bTakushoku University, Japan

Title of original paper: An active equalization strategy for series-connected lithium-ion battery packs based on a dual threshold trigger mechanism

Article link: https://doi.org/10.1016/j.geits.2024.100206

Journal: Green Energy and Intelligent Transportation

https://www.sciencedirect.com/science/article/pii/S2773153724000586

DOI: 10.1016/j.geits.2024.100206

 


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