ICT2014 Abstracts

Thermoelectric generators (TEGs) are currently a topic of interest in the energy recovery for vehicles. In applying TEGs to the outside surface of the exhaust tailpipe, a small amount of electrical power will be generated because of the temperature difference between the hot exhaust gases and the automobile coolant. The amount of power is anticipated to be a few hundred watts based on the expected temperature difference and the properties of the thermoelectric materials for the TEGs. It is well know that, for thermoelectric exhaust energy recovery, the temperature uniformity of the heat exchangers has a strong influence on the electric power generation. In current research, the temperature uniformity of a heat exchanger was improved by optimizing the fin distribution to maximize the electric power generated for a given vehicle and TEG. A computational fluid dynamics (CFD) model of the heat exchanger was constructed to assess the influence of fin distributions on the temperature uniformity and the pressure drop in the exhaust system. For the fin distributions, three factors are considered: length of the fins, length of the gap between fins and thickness of fins. Based on the three factors, a design of experiments (DOE) study using the optimal Latin hypercube method was conducted to analyze the sensitivity of the design variables and build a database to set up the surrogate model using Kriging response surface method. A multi-island genetic algorithm was used to optimize the fin distribution based on the surrogate model. In order to validate the accuracy of the CFD model, a generic heat exchanger module was manufactured and a related test-bed was constructed, then the temperature distribution on the surface of the exchanger was measured to compare with the results obtained by CFD.