This paper describes a pattern recognition approach aiming to estimate fuel cell duration time from electrochemical impedance spectroscopy measurements. It consists in first extracting features from both real and imaginary parts of the impedance spectrum. A parametric model is considered in the case of the real part, whereas regression model with latent variables is used in the latter case. Then, a linear regression model using different subsets of extracted features is used fo r the estimation of fuel cell time duration. The performances of the proposed approach are evaluated on experimental data set to show its feasibility. This could lead to interesting perspectives for predictive maintenance policy of fuel cell.

本文提出利用模式识别方法从电化学阻抗谱测量结果中估计燃料电池寿命的方法，通过从实部和虚部提取特征，使用参数模型和具有潜在变量的回归模型，以及不同子集的特征进行线性回归模型来实现燃料电池时间持续估计，并在实验数据集上进行了有效性验证。这可能会为燃料电池的预测性维护政策提供有趣的前景。

基于潜在过程的回归模型监督学习。应用于燃料电池寿命估计