A Predictive Model of SOFC Thermal Management Based on LS-SVM

摘要

The thermal management is crucial to the safety and lifespan of Solid Oxide Fuel Cell (SOFC) generation system. For the model-predictive control design, a model of SOFC thermal management system is proposed on the least squares support vector machine (LS-SVM). The model is composed of some thermal modules including SOFC stack, combustor, heat-exchanger and thermal equilibrium apparatus. It predicts the temperature distribution in SOFC generation system by computing the electrochemical reaction in the stack, the gas flow and the heat exchange through the modules. Checked by the experimental data, the model can be used for system temperature fast prediction with high precision and strong generalization ability, which meets the requirement of the research on the online predictive control design of SOFC generation system.