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State of charge estimation based on sliding mode observer for vanadium redox flow battery

机译:基于滑模观测器的钒氧化还原液流电池充电状态估计

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State of charge (SOC) of the batteries is a key indicator for battery monitoring and control. Long-time operation of vanadium redox flow batteries (VRBs) may cause ion diffusions across the membrane and the depletion of active materials, which will lead to capacity fading and internal resistance increasing. A selection of proper SOC method considering capacity fading factor is critical. In previous studies, capacity fading factor is not considered when SOC observer has been designed. In addition, the traditional method - extended kalman filter - is not appropriate to estimate SOC when the battery capacity is decaying. In this paper, an adaptive method, sliding mode observer (SMO), capable of dynamic estimation is proposed based on a model considering capacity fading. The simulation result shows that a capacity loss of 13.9% is estimated based on the diffusion model. The mean error between the observed and the modelled capacities is 0.14 Ah.
机译:电池的充电状态(SOC)是电池监视和控制的关键指标。钒氧化还原液流电池(VRB)的长时间运行可能会导致离子在整个膜上扩散以及活性物质耗尽,这将导致容量衰减和内部电阻增加。考虑到容量衰减因子,选择合适的SOC方法至关重要。在以前的研究中,设计SOC观察器时未考虑容量衰减因子。此外,当电池容量下降时,传统方法-扩展卡尔曼滤波器-不适合估算SOC。本文基于考虑容量衰减的模型,提出了一种能够动态估计的自适应方法滑模观测器(SMO)。仿真结果表明,基于扩散模型,容量损失估计为13.9%。观测到的容量与建模容量之间的平均误差为0.14 Ah。

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