Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1282456 | International Journal of Hydrogen Energy | 2011 | 11 Pages |
Abstract
⺠This paper presents new steady-state and dynamic models for solid oxide fuel cells using core vector regression (CVR). ⺠Two CVRs are trained for each operating mode of solid oxide fuel cell, considering important operating parameters. ⺠In comparison with existing black-box models, the proposed model has little training time and small amount of memory. ⺠The proposed model has less error and better correlation coefficient in comparison with existing black-box models. ⺠Because of less support vectors the proposed CVR-based model is faster than existing models for time-consuming studies.
Related Topics
Physical Sciences and Engineering
Chemistry
Electrochemistry
Authors
M. Mohammadi, M. Raoofat, H. Marzooghi, G.B. Gharehpetian,