State of charge estimation for liquid metal battery based on an improved sliding mode observer
State of charge estimation for liquid metal battery based on an improved sliding mode observer
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基于改进滑模观测器的液态金属电池荷电状态估计
DOI：
10.1016/j.est.2021.103701
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发表时间：
2022-01
影响因子：
9.4
通讯作者：
Cheng Shijie
中科院分区：
文献类型：
--
作者：
Xu Cheng;Zhang E.;Yan Shuai;Jiang Kai;Wang Kangli;Wang Zhuo;Cheng Shijie
电化学储能技术正成为可再生能源集成的最有前途的解决方案之一。液态金属电池由于其低成本和长寿命而成为一种有前景的固定能量存储电池化学。然而，平坦的电压平台和低工作电压容易引入相对误差，导致电池荷电状态（SOC）估计的挑战。同时，液态金属电池的实际应用需要高效的SOC估计算法进行大规模并行计算。因此，在本文中，提出了一种改进的滑模观测器（ISMO）的液态金属电池SOC估计，以满足挑战。首先，基于组合等效电路模型，利用遗忘因子递归最小二乘算法在整个工作范围内辨识模型参数。其次，提出了一种直接微分法来处理开路电压和SOC之间的线性化问题。最后，提出了一种新的自适应律来加速算法的收敛，抑制可能出现的大抖动，提高算法的估计精度。与传统的基于模型的方法相比，该方法具有收敛速度快、精度高、鲁棒性强、计算量小等优点，具有良好的产业化前景。
Electrochemical energy storage is becoming one of the most promising solution for renewable energy integration. Liquid metal battery is a prospective battery chemistry for stationary energy storage due to its low cost and long lifespan. However, the flat voltage platform and low working voltage easily introduce relative errors, resulting in challenges in battery state of charge (SOC) estimation. Meanwhile, practical applications of liquid metal batteries require efficient SOC estimation algorithms for massively parallel computing. Thus, in this paper, an improved sliding mode observer (ISMO) is proposed for liquid metal battery SOC estimation to meet the challenges. Firstly, based on a combined equivalent circuit model, the forgetting factor recursive least square algorithm is utilized to identify model parameters in the whole working range. Secondly, a direct differentiation method is put forward to deal with the linearization between the open circuit voltage and the SOC. Finally, a novel adaptive law is proposed to accelerate the convergence, restrict the probable large chattering and improve the estimation accuracy of the algorithm. Compared to the conventional model-based methods, the proposed ISMO exhibits faster convergence, higher accuracy, stronger robustness and lower computational cost in simulations, which indicates an industrialization prospect.
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