Estimation of Parameter Probability Distributions for Lithium-Ion Battery String Models Using Bayesian Methods
Estimation of Parameter Probability Distributions for Lithium-Ion Battery String Models Using Bayesian Methods
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DOI：
10.1115/dscc2020-3218
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发表时间：
2020-10
期刊：
影响因子：
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通讯作者：
Luis D. Couto;Dong Zhang;A. Aitio;S. Moura;D. Howey
中科院分区：
文献类型：
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作者：
Luis D. Couto;Dong Zhang;A. Aitio;S. Moura;D. Howey
研究了串联电池锂离子电池组模型的参数估计问题。这些有价值的信息可用于故障诊断，以估计表现出异常行为的单元数量，例如，大电阻或小容量。特别是，我们使用贝叶斯方法来估计使用等效电路建模的两个单元布置的参数。虽然我们的建模框架已经在文献中得到了广泛的报道，但据作者所知，其结构可识别属性尚未报道。此外，文献中的大多数贡献都是通过假设高斯噪声的逐点估计来解决估计问题，例如使用最小二乘方法(最大似然估计)或卡尔曼滤波(最大后验估计)。相反，我们应用适合于非线性和非高斯估计问题的方法来估计参数的全后验概率分布。我们研究了模型结构、可用测量值和模型参数的先验知识如何影响为参数恢复的潜在后验概率分布。对于串联的两个单元，得到了双峰分布，其模式以每个单元的参数的实值为中心。因此，可以推导出电池组模型参数的界限。
This paper addresses the parameter estimation problem for lithium-ion battery pack models comprising cells in series. This valuable information can be exploited in fault diagnostics to estimate the number of cells that are exhibiting abnormal behaviour, e.g. large resistances or small capacities. In particular, we use a Bayesian approach to estimate the parameters of a two-cell arrangement modelled using equivalent circuits. Although our modeling framework has been extensively reported in the literature, its structural identifiability properties have not been reported yet to the best of the authors’ knowledge. Moreover, most contributions in the literature tackle the estimation problem through point-wise estimates assuming Gaussian noise using e.g. least-squares methods (maximum likelihood estimation) or Kalman filters (maximum a posteriori estimation). In contrast, we apply methods that are suitable for nonlinear and non-Gaussian estimation problems and estimate the full posterior probability distribution of the parameters. We study how the model structure, available measurements and prior knowledge of the model parameters impact the underlying posterior probability distribution that is recovered for the parameters. For two cells in series, a bimodal distribution is obtained whose modes are centered around the real values of the parameters for each cell. Therefore, bounds on the model parameters for a battery pack can be derived.