Efficient Two-Step Parametrization of a Control-Oriented Zero-Dimensional Polymer Electrolyte Membrane Fuel Cell Model Based on Measured Stack Data

Processes

ZhangPeng Du¹  Stefan Jakubek¹  Christoph Steindl² 

[1] Institute of Mechanics and Mechatronics, Technische Universität Wien, Getreidemarkt 9, 1060 Vienna, Austria;Institute of Powertrains and Automotive Technology, Technische Universität Wien, Getreidemarkt 9, 1060 Vienna, Austria;

关键词: polymer electrolyte membrane fuel cell;    control-oriented model;    grey-box modeling;    analytical differentiability;    model reduction;    parameter sensitivity analysis;   

DOI  :  10.3390/pr9040713

来源: DOAJ

【 摘 要 】

This paper proposes a new efficient two-step method for parametrizing control-oriented zero-dimensional physical polymer electrolyte membrane fuel cell (PEMFC) models with measured stack data. Parametrizations of these models are computationally intensive due to the numerous unknown parameters and the typically nonlinear, stiff model properties. This work reduces an existing model to decrease its stiffness for accelerated numerical simulations. Subdividing the parametrization into two consecutive subproblems (thermodynamic and electrochemical ones) reduces the solution space significantly. A parameter sensitivity analysis further reduces each sub-solution space by excluding non-significant parameters. The method results in an efficient parametrization process. The two-step approach minimizes each sub-solution space’s dimension by two-thirds, respectively three-fourths, compared to the global one. An achieved $R^2$ value between simulation and measurement of 91% on average provides the required accuracy for control-oriented models.

【 授权许可】

Unknown