In this paper a thorough comparison is made between steady state kinetic models for methanol synthesis from Graaf et al. 1988, Vanden Bussche and Froment 1996, Seidel et al. 2018, Ma et al. 2009 and Villa et al. 1985. A new experimental dataset using an industrial Cu/ZnO/Al₂O₃ catalyst is presented and used together with the dataset of Seidel et al. 2018 for refitting the kinetic models. The models are refitted using the statistical cross-validation (CV) method to test for predictive capabilities and model variance. A new kinetic model is proposed with the aim to reduce parameter identifiability problems. The model is derived based on physical observations from literature. This physically consistent model has ten parameters, however more experiments are needed, because the current dataset is not discriminating enough for regression of adsorption isotherms. The proposed model is further reduced to only six parameters. This model is predicting the dataset equally well or better than current higher parameter models. It is shown that the model is a good predicting model for experiments outside the training set. The model is valid for pressures from 20 to 70 bara and temperatures from 450 to 530 K with a high probability of predicting well outside these boundaries.

本文对Graaf等人合成甲醇的稳态动力学模型进行了全面比较。1988年，Vanden Bussche和Froment 1996年，Seidel等。2018，Ma等。2009和Villa等。1985年。使用工业Cu / ZnO / Al ₂ O _3的新实验数据集介绍了催化剂并与Seidel等人的数据集一起使用。2018年用于改装动力学模型。使用统计交叉验证（CV）方法对模型进行重新拟合，以测试预测能力和模型差异。为了减少参数可识别性问题，提出了一种新的动力学模型。该模型是基于文献的物理观察得出的。该物理上一致的模型有十个参数，但是需要进行更多的实验，因为当前数据集不能充分区分吸附等温线的回归。所提出的模型被进一步简化为仅六个参数。与当前较高参数的模型相比，该模型对数据集的预测同样好或更好。结果表明，该模型是训练集以外实验的良好预测模型。