A simulation framework for prediction of thermoelectric generator system performance
Artikel i vetenskaplig tidskrift, 2016
This paper presents a novel framework for characterization and simulation of thermoelectric generator systems that allows accurate and efficient prediction of electric and thermal performance at steady state conditions. The simulation framework relies on regression analysis of single thermoelectric modules including voltage, current, temperatures and heat flow. A physical description of the main phenomena is included in models and enables accurate prediction of module performance over large ranges in temperature and current. Moreover it allows a system of modules electrically connected to be analyzed and used together with fluid dynamics simulations. When used in conjunction with CFD analysis it allows efficient modeling of electrical and thermal performance by simultaneous solution of the coupled equations for energy transport and thermoelectric power generation. This efficiency comes from the fact the modeling does not require full resolution as first principle simulations does. Therefore it solves the scale separation problem and allows multiphysics simulation with just a minor increase in computational power. Experimental validation on a system consisting of electrically connected modules shows excellent prediction of heat flow as well as current and voltage. Validation confirms the simulation framework allows extrapolation outside the measured operating range used when developing the models. Even under highly non-ideal conditions with reversed current, i.e. when modules operate as Peltier coolers rather than generators, very reliable predictions are obtained. Results show the simulation framework captures the main physics and allows efficient and reliable predictions. The models allow physial separation of heat conduction, Peltier, Joule and Seebeck effects and the different phenomena are studied and discussed in detail for various thermal loads and electrical configurations.