Optimization of Thermoelectric Modules’ Number and Distribution Pattern in an Automotive Exhaust Thermoelectric Generator

IEEE ACCESS(2019)

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摘要
Thermoelectric generators are efficient devices to recover energy from the automotive exhaust gas. In this paper, conversion efficiency of automotive thermoelectric generator (ATEG) and the maximum electrical power generated by the ATEG, defining as the power output of the ATEG excluding the energy loss caused to the engine improved by optimizing the number of thermoelectric modules (TEMs) and its distribution pattern in an ATEG. An advanced numerical model of ATEG considering the effect of the heat transfer among the adjacent TEM's rows is developed with Simulation-X software. In order to acquire the ATEG's optimal electrical performance, a 3-step optimization is applied. First, 17 independent factors (the number of TEMs in each row from 1 to 18) are assessed and the significant parameters are screened using Plackett-Burman design. Second, an experiment designed with a central composite design is performed to analyze the sensitivity of six selected factors and a surrogate model is built through response surface method. Then, conflicts in two objectives are settled with a multi-objective genetic algorithm. According to the optimization results of a given ATEG, the maximum electrical power generated by the ATEG is 139.47 W and the conversion efficiency is 2.51% under steady engine condition. Finally, the performances of the optimized design under different engine conditions are discussed. The results show that the maximum power generated by the ATEG and efficiency respectively increase by 49.8% and 106.5% after optimization when the exhaust inlet temperature is 805 K and the mass flow rate is 0.5 kg/s.
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关键词
Automotive thermoelectric generator,multi-objective genetic algorithm,response surface method,thermoelectric modules,3-step optimization
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