Author
Listed:
- Xiaofan Ji
(National Institute of Clean-and-Low-Carbon Energy of CHN Energy, Beijing 102209, China)
- Fengxiang Xie
(CHN Energy Gonghe New Energy Development Co., Ltd., Hainan Tibetan Autonomous Prefecture 813000, China)
- Yuantang Qi
(CHN Energy Gonghe New Energy Development Co., Ltd., Hainan Tibetan Autonomous Prefecture 813000, China)
- Yongdong Ji
(CHN Energy Gonghe New Energy Development Co., Ltd., Hainan Tibetan Autonomous Prefecture 813000, China)
- Decun Niu
(School of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266061, China)
- Qizhong Yan
(School of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266061, China)
Abstract
In modular multilevel converter battery energy storage systems (MMC-BESS), state-of-charge (SOC) balancing is essential for ensuring safe and reliable operation. Existing methods based on linear controllers or conventional model-predictive control (MPC) often suffer from slow balancing speed, difficult parameter tuning, and high computational burden. To address these challenges, this paper proposes a fast SOC balancing strategy based on nonlinear MPC. A nonlinear state-space model is first developed and then linearized to enable discrete single-step prediction of arm- and phase-level SOC values. A two-stage control scheme is introduced to coordinate inter-arm and inter-phase SOC balancing, significantly reducing the number of state variables involved in the MPC formulation. The proposed method eliminates the need for circulating current reference calculation and control parameter tuning. Simulation results demonstrate that the proposed method takes approximately 17.5 s and 39 s for inter-arm and inter-phase SOC balancing, respectively, while traditional three-level SOC balancing takes approximately 42 s and 88 s.
Suggested Citation
Xiaofan Ji & Fengxiang Xie & Yuantang Qi & Yongdong Ji & Decun Niu & Qizhong Yan, 2025.
"A Fast SOC Balancing Method for MMC-BESS Based on Nonlinear Model-Predictive Control,"
Energies, MDPI, vol. 18(10), pages 1-19, May.
Handle:
RePEc:gam:jeners:v:18:y:2025:i:10:p:2502-:d:1654423
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