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A Novel Method for thermoelectric Generator Based on Neural Network

Computers, Materials & Continua 2022年第10期73卷 2115-2133页

作者： Mohammad Saraireh A.M.Maqableh Manar Jaradat Omar A.Saraereh Mechanical Engineering Department Faculty of EngineeringMutah UniversityKarak61710Jordan Electromechanical Engineering Department Luminus Technical University CollegeAmman11118Jordan Department of Computer Engineering Faculty of EngineeringThe Hashemite UniversityZarqa13133Jordan Department of Electrical Engineering Faculty of EngineeringThe Hashemite UniversityZarqa13133Jordan

The growing need for renewable energy and zero carbon dioxide emissions has fueled the development of thermoelectric generators with improved power generating *** with the endeavor to develop thermoelectric materials with greater figures of merit,the geometrical and structural optimization of thermoelectric generators is equally critical for maximum power output and *** energy strategies that are constantly updated are a viable option for addressing the global energy issue while also protecting the *** have been significant focuses on the development of thermoelectric modules for a range of solar,automotive,military,and aerospace applications in recent years due to various advantages including as low vibration,great reliability and durability,and the absence of moving *** order to enhance the system performance of the thermoelectric generator,an artificial neural network(ANN)based algorithm is ***,to achieve high efficiency and system stability,a buck converter is designed and *** and experimental findings demonstrate that the suggested method is viable and available,and that it is almost similar to the real value in the steady state with the least power losses,making it ideal for vehicle exhaust thermoelectric generator ***,the proposed hybrid algorithm has a high reference value for the development of a dependable and efficient car exhaust thermoelectric generating system.

关键词： thermoelectric system thermodynamics electromechanics rotational factors neural networks

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