A breakthrough in energy equalization for lithium-ion battery packs

In the global transition toward sustainable energy, lithium-ion batteries have emerged as the cornerstone of electric vehicles and renewable energy storage systems. However, a persistent challenge lies in the energy imbalance among individual cells within battery packs. Manufacturing inconsistencies, environmental conditions, and thermal variations cause some cells to overcharge while others undercharge, leading to reduced efficiency, shortened lifespan, and even safety hazards such as thermal runaway. 

To address this issue, battery management systems (BMS) rely on equalization circuits—technologies designed to redistribute energy among cells to maintain balance. Conventional single-layer equalization methods often struggle with long battery strings and complex operating conditions, resulting in inefficiency and excessive energy loss. This study introduces an innovative two-layer active balancing strategy that significantly enhances energy transfer efficiency and speed. 

The newly developed layered energy equalization structure integrates inductor and transformer circuits, enabling simultaneous energy balancing both within and between battery cell groups. A key advancement is the multi-weighted optimal matching algorithm, which models the circuit as a directed graph to identify the most efficient energy transfer paths, thereby minimizing losses. Additionally, a dynamic fuzzy controller adjusts the balancing current in real-time based on each cell’s State of Charge (SOC), optimizing both speed and efficiency. 

Experimental validation demonstrated remarkable improvements. The new strategy achieves 42.03% faster equalization compared to traditional maximum value methods, drastically reducing the time required to balance battery cells. Energy efficiency also sees a 6.08% increase, ensuring more power is utilized effectively rather than wasted as heat. Furthermore, in charging and discharging scenarios, the final average SOC was 0.90% to 9.97% higher than conventional approaches, highlighting superior performance in maintaining battery health. 

The implications of this breakthrough extend across multiple industries. In electric vehicles, faster and more efficient energy balancing translates to longer driving ranges and extended battery lifespan, ultimately lowering ownership costs. For renewable energy storage, the technology enhances reliability by ensuring optimal battery performance in solar and wind power systems. Large-scale applications in smart grids could also benefit, as improved energy storage efficiency supports grid stability and reduces operational losses. 

Looking ahead, this technology is adaptable to next-generation battery systems, including solid-state batteries, ensuring its relevance as energy storage evolves. Future research will focus on hardware implementation and refining SOC consistency to further enhance performance. 

This study marks a significant leap forward in battery equalization technology, combining advanced circuit design, intelligent control algorithms, and optimized energy pathways. By delivering higher efficiency, faster balancing, and improved reliability, this innovation holds immense potential for advancing sustainable energy solutions. As the technology progresses from simulation to real-world deployment, it promises to redefine how we store and utilize energy—powering a cleaner, more efficient future. 

Reference

Author: Jianfang Jiao ^a, Hongwei Wang ^a, Feng Gao ^a, Serdar Coskun ^b, Guang Wang ^a, Jiale Xie ^a, Fei Feng ^c

Title of original paper: Layered energy equalization structure for series battery pack based on multiple optimal matching

Article link: https://doi.org/10.1016/j.geits.2024.100182

Journal: Green Energy and Intelligent Transportation

https://www.sciencedirect.com/science/article/pii/S2773153724000343

DOI: 10.1016/j.geits.2024.100182

Affiliations:

^a Department of Automation, North China Electric Power University, Baoding 071003, China

^b Department of Mechanical Engineering, Tarsus University, Tarsus, Turkey

^c School of Automation, Chongqing University, Chongqing 400044, China