Online remaining useful lifetime prediction of proton exchange membrane fuel cells using a novel robust methodology
Online remaining useful lifetime prediction of proton exchange membrane fuel cells using a novel robust methodology
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DOI：
10.1016/j.jpowsour.2018.06.098
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发表时间：
2018-09
影响因子：
9.2
通讯作者：
Daming Zhou;A. Al‐Durra;Ke Zhang;A. Ravey;Fei Gao
中科院分区：
文献类型：
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作者：
Daming Zhou;A. Al‐Durra;Ke Zhang;A. Ravey;Fei Gao
本文提出了一种新颖的鲁棒预测方法，其中包含质子交换膜燃料电池（PEMFC）性能退化预测及其剩余使用寿命（RUL）估计的三个阶段。在第一个去趋势阶段，使用物理老化模型（PAM）来消除原始燃料电池退化数据中的非平稳趋势。在第二个滤波阶段，自回归和移动平均（ARMA）模型的阶数由自相关函数（ACF）、部分ACF和Akaike信息准则确定。然后，通过识别的 ARMA 模型过滤平稳时间序列中的线性分量。在第三个预测阶段，剩余的非线性模式用于训练时延神经网络（TDNN），以提供最终的预测结果。由于所提出的预测方法使用适当的方法来分析和预处理原始退化数据（即PAM保持平稳趋势，然后识别的ARMA过滤线性分量），因此平稳时间序列的剩余非线性模式可以保证TDNN良好的收敛性能。为了通过实验证明所提出方法的鲁棒性和预测准确性，使用两种类型的 PEMFC 堆栈进行退化测试。
This paper proposes a novel robust prognostic approach that contains three phases for degradation prediction of proton exchange membrane fuel cell (PEMFC) performance and its remaining useful lifetime (RUL) estimation. In the first detrending phase, a physical aging model (PAM) is used to remove the non-stationary trend in the original fuel cell degradation data. In the second filtering phase, the order of autoregressive and moving average (ARMA) model is determined by autocorrelation function (ACF), partial ACF and Akaike information criterion. The linear component in the stationary time series is then filtered by the identified ARMA model. In the third prediction phase, the remaining nonlinear pattern is used to train the time delay neural network (TDNN), in order to provide the final prediction result. Since the proposed prognostic approach uses appropriate methods to analyze and preprocess the original degradation data (i.e., the PAM maintains stationary trend, and then the identified ARMA filters linear component), the remaining nonlinear pattern of stationary time series can thus guarantee a good convergence performance of TDNN. In order to experimentally demonstrate the robustness and prediction accuracy of the proposed approach, degradation tests are performed using two types of PEMFC stack.