Investigating the influence of Thomson effect on the performance of a thermoelectric generator in a waste heat recovery system

2019 ◽  
Vol 16 (12) ◽  
pp. 917-929 ◽  
Author(s):  
Mohammad Kalteh ◽  
Hossein Akhlaghi Garmejani
Author(s):  
Dongxu Ji ◽  
Alessandro Romagnoli

In order to design an effective thermoelectric generator (TEG) heat exchanger for waste heat recovery, an accurate model is required for system design and performance predicting. In this paper, 1-D model is developed in MATLAB, taking into consideration of the multi-physics phenomena within TEG. The proposed model is different from existing thermoelectric models which mainly focus on the thermoelectric couple or device level without providing any guidance for designing an optimal system. When optimizing some TEG parameters, the optimal value found in a device level model might not be suitable when put into a waste heat recovery system. Therefore, in order to develop an optimized TEG system with optimum output power performance, a more comprehensive thermoelectric model integrated with the other components is needed. The current model integrates the thermoelectric module with the heat exchangers. Through this study, we found that the heat exchanger and module design have an impact on the total TEG output power in waste heat recovery system and a systematic design approach is needed.


2020 ◽  
Vol 5 (3) ◽  
pp. 58-61

Energy crisis is major problem in this era. Thermoelectric generator is a promising solution for this problem. This research aims to recover waste heat energy from automobile by converting it into electrical energy using thermoelectric generator. Thermoelectric generator is applied at automobile exhaust system to produce electrical energy from heat energy directly with a phenomenon called see-beck effect. This work develops a heat exchanger model with thermoelectric generator for automobile waste heat recovery in which heat source and cold sink are actually modeled. Main emphasis is put on effective temperature difference across the TEGs to get better performance of the exhaust waste heat recovery system. This research shows that the model is able to produce up to 2.67 W energy using 3 Numbers of TEGs in this design.


Author(s):  
M. Akif Kunt ◽  
Haluk Gunes

Worldwide, motorcycle sales have increased significantly during the coronavirus disease 2019 pandemic process. Thermoelectric generators are technologies that can directly convert waste heat into electrical energy in internal combustion engines. In this study, a waste heat recovery system with a thermoelectric generator has been designed for the exhaust system of a motorcycle engine with a cylinder volume of 50 cc. The performance of the waste heat recovery system has been examined under throttle opening of three-fourth and at different speeds, and a thermal model of the system has been created by means of the GT SUITE model. According to the test results, the increase in engine speed caused different temperature differences on the surfaces of the TEG module due to the constant flow of the fan the maximum recovery power has been found as 2.05 W at an engine speed of 6000 r/min and the maximum system efficiency has been found as 2.41% at an engine speed of 4000 r/min. Following minimum temperature differences have been calculated between experimental and GT SUITE thermal model calculations: 14.05 K at an engine speed of 4000 r/min and at [Formula: see text] temperatures; 14.1 K at an engine speed of 6000 r/min and at [Formula: see text] temperatures; and 7.5 K at an engine speed of 5500 r/mi and at [Formula: see text] temperatures.


2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Gunabal S

Waste heat recovery systems are used to recover the waste heat in all possible ways. It saves the energy and reduces the man power and materials. Heat pipes have the ability to improve the effectiveness of waste heat recovery system. The present investigation focuses to recover the heat from Heating, Ventilation, and Air Condition system (HVAC) with two different working fluids refrigerant(R410a) and nano refrigerant (R410a+Al2O3). Design of experiment was employed, to fix the number of trials. Fresh air temperature, flow rate of air, filling ratio and volume of nano particles are considered as factors. The effectiveness is considered as response. The results were analyzed using Response Surface Methodology


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