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Robust battery fuel gauge algorithm development, part 3: State of charge tracking

机译:强大的电池燃料表算法开发,第3部分:充电状态跟踪

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In this paper, we present a novel SOC tracking algorithm for Li-ion batteries. The proposed approach employs a voltage drop model that avoid the need for modeling the hysteresis effect in the battery. Our proposed model results in a novel reduced order (single state) filtering for SOC tracking where no additional variables need to be tracked regardless of the level of complexity of the battery equivalent model. We identify the presence of correlated noise that has been so far ignored in the literature and use this for improved SOC tracking. The proposed approach performs within 1% or better SOC tracking accuracy based on both simulated as well as HIL evaluations.
机译:本文介绍了一种用于锂离子电池的新型SOC跟踪算法。 该方法采用电压降模型,避免了对电池中的滞后效果建模的需要。 我们所提出的模型导致新颖的减少顺序(单个状态)过滤,用于SOC跟踪,无论电池等效模型的复杂程度如何,都不需要跟踪额外的变量。 我们确定了在文献中忽略了相关噪声的存在,并用于改进的SOC跟踪。 基于模拟和HIL评估,所提出的方法在1%或更好的SOC跟踪精度下执行。

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