@inproceedings{CleesKlaassenNikitinetal.2021,
  author    = {Clees, Tanja and Klaassen, Bernhard and Nikitin, Igor and Nikitina, Lialia and Pott, Sabine},
  title     = {Statistical and Principal Component Analysis in the Design of Alkaline Methanol Fuel Cells},
  booktitle = {Dini, Pyshkin et al. (Eds.): ADVCOMP 2021. Fifteenth International Conference on Advanced Engineering Computing and Applications in Sciences, October 3-7, 2021, Barcelona, Spain},
  isbn      = {978-1-61208-887-7},
  url       = {https://www.thinkmind.org/index.php?view=article\&articleid=advcomp_2021_1_10_20008},
  institution = {Fachbereich Ingenieurwissenschaften und Kommunikation},
  pages     = {1 -- 5},
  year      = {2021},
  abstract  = {In this paper, the electrochemical alkaline methanol oxidation process, which is relevant for the design of efficient fuel cells, is considered. An algorithm for reconstructing the reaction constants for this process from the experimentally measured polarization curve is presented. The approach combines statistical and principal component analysis and determination of the trust region for a linearized model. It is shown that this experiment does not allow one to determine accurately the reaction constants, but only some of their linear combinations. The possibilities of extending the method to additional experiments, including dynamic cyclic voltammetry and variations in the concentration of the main reagents, are discussed.},
  language  = {en}
}