The aim of this work is to deploy and experimentally validate a model-based strategy to estimate unmeasurable variables in a proton exchange membrane (PEM) fuel cell. First, a nonlinear PEM fuel cell dynamical model is implemented and calibrated using an optimisation approach that takes real measurement data as input. Then, an advanced observation approach is developed to retrieve non-measurable data from the fuel cell. Two states are estimated in this work: the fuel cell temperature and the internal liquid water fraction. To achieve this, a model-based high-order sliding mode observer (HOSM) with chattering-free capabilities is deployed. The fuel cell temperature is measured in real time to drive the estimation error to zero in a finite amount of time. Finally, the methodology is validated using experimental data stemming from a laboratory test station, comparing the the HOSM observer with and without chattering-free gain.

这项工作的目的是部署并实验验证基于模型的策略，以估计质子交换膜（PEM）燃料电池中不可测量的变量。首先，使用一种将实际测量数据作为输入的优化方法来实现和校准非线性PEM燃料电池动力学模型。然后，开发了一种先进的观察方法以从燃料电池中检索不可测量的数据。估计这项工作有两种状态：燃料电池温度和内部液态水分数。为此，部署了具有无抖动功能的基于模型的高阶滑模观察器（HOSM）。实时测量燃料电池温度，以在有限的时间内将估计误差驱动为零。最后，