Performance of Novel Thermoelectric Cooling Module (original) (raw)
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COOLING PERFORMANCE OF THERMOELECTRIC COOLER MODULES: EXPERIMENTAL AND NUMERICAL METHODS
A novel pulse-driving method in which the pulse frequency modulation is was developed by optimising the input power owing to the duty cycle of rectangular wave to enhance the cooling efficiency and thermal stability of the thermoelectric module. The aim of this driving method is to have better control of the thermoelectric cooler module temperature and to improve its coefficient of performance. In this method, the average current and the peak of pulse drive are in the 50% duty cycle with the same magnitude and the performance of Peltier module driving with average dc is compared with the pulse driving. The measurement results show that the coefficient of performance of the thermoelectric module with the pulse-frequency modulation driving method increased up to 102% as compared to the constant dc driving method. An artificial neural network has been successfully used to analyse these experimentally collected data and predict the performance of the module. When the developed artificial neural network model was tested using untrained data, the average correlation of the model was 99% and the overall prediction error was 1.38%. An accurate and simple analytical equation based on the predicted and experimental results was determined using the MATLAB ® Curve Fitting Toolbox. The average correlation of the analytical model was 0.99 and the root-mean-square error was 0.074.
Analytical Investigation of Thermoelectric Performance for Cooling Application
This paper presents the method used to predict the internal parameters of thermoelectric module (TEM) and the several factors that affect the temperature reduction of air in Thermoelectric (TE) cooling system. A TE cooling system consists of three TEMs attached on the top of an air duct with the dimensions 9.3 cm × 9.3 cm × 55 cm. Ambient air flows through the duct and its outlet temperature is estimated by using the log mean temperature difference (LMTD) method for different weather conditions. At the considered conditions, results showed that 6 A is the optimum operating current, and the maximum temperature reduction can reach to 2.41 °C. The performance of TE cooling system strongly depends on the ambient condition and for the considered 40 hours weather conditions, the maximum temperature reduction happened at around 3 pm. It was also found that the increase of inlet air velocity causes the temperature reduction to decrease exponentially. As a result, this study identified the correlate effects of the ambient weather, the operating current and the air velocity on the TE cooling system. As one does not have control on the ambient weather, selecting the optimum operating current level and inlet air velocity of the system is important to fully utilize the cooling effect of the system.
Prediction of the performance of thermoelectric cooling material (figure of merit, ZT) was carried out by simulated results obtained from the finite element method (FEM) as a training dataset with an artificial neural network. A total of 87 input vectors for the ZT obtained from the four thermoelectric cooling (TEC) modules modeled using the FEM analysis were available in the training set to a back-propagation artificial neural network. An average correlation and maximum prediction error were found to be 100% and 0.01%, respectively, for the ZT after training. The standard deviation of the values was 0.05%. A set of test data, different from the training dataset was used to investigate the network performance. The average correlation and maximum prediction error were found to be 99.92% and 0.07%, respectively, for the tested TEC module. A thermoelectric module produced based on the numerical results was shown to be a promising device for use in cooling systems.
Journal of Electronic Materials, 2015
This work examines the validity of formulating the effective thermoelectric material properties as a way to predict thermoelectric module performance. The three maximum parameters (temperature difference, current, and cooling power) of a thermoelectric cooler were formulated on the basis of the hot junction temperature. Then, the effective material properties (Seebeck coefficient, electrical resistance, and thermal conductivity) were defined in terms of the three maximum parameters that were taken from either a commercial thermoelectric cooler module or the measurements. It is demonstrated that the simple standard equation with the effective material properties predicts well the performance curves of the four selected commercial products. Normalized parameters over the maximum parameters were also formulated to present the characteristics of the
ARTICLE INFO Cooling of electronics component is one of the major challenges faced by thermal engineers. In recent years, a significant increase in microprocessor power dissipation coupled with CPU size has resulted in an increase in heat fluxes. Microprocessor heat fluxes have also increased for many commercial applications. Therefore, thermal management is becoming one of most challenging issues and an important subject in regard to cooling system performance. For a number of applications, direct air-cooling systems like by applying blower, fan or water cooling are having moving parts and not reliable for continuous operation for long time and will have to be replaced or enhanced by other high performance compact cooling techniques. Liquid–vapor phase change, impinging jets spray, the use of thermoelectric modules and heat pipes are attractive cooling solutions for removing high heat fluxes because of their high heat transfer coefficients. In the present work we perform the initial experimental investigation and basic mathematical modeling to determine the thermal performance of thermoelectric module integrated with heat pipe for electronics cooling at different operating variables and parameters. Currently the experiments are in progress, so we put our initial experimental setup and discussions. The detail results after experiments will help us to analyze the temperature distribution and heat transfer limitation characteristic in thermoelectric module and its role in future of electronics cooling.
Compact design of thermoelectric cooler and its performance analysis
1ST INTERNATIONAL CONFERENCE ON MANUFACTURING, MATERIAL SCIENCE AND ENGINEERING (ICMMSE-2019), 2019
Thermoelectric cooling is one of the easiest and cheapest ways of recovering waste heat and convert it to obtain required cooling effect. A 127 couple thermoelectric cooler (TEC) is taken and its performance is analyzed. Also focus has been made to get an optimal and compact design with a better cooling capacity. Simulation is carried out in COMSOL Multiphysics 5.0 by varying parameters such as size and cross section of thermoelectric leg, number of couples in the module, thickness of copper conductor and the most important parameter the semiconductor material. Choosing Bismuth Telluride as semiconducting material, the cooling capacity is found to be 21.04 W when the TEC legs are made in circular cross section with 0.2 cm leg length and 41.87 W when leg length is 0.1 cm with copper plate thickness of 0.05cm which is almost double. With Bismuth antimony as a semiconductor material cooling effect is measured to be 538.38W for the same configuration which makes any designer to incline towards choosing this material. Non-linear circular cross section leg TEC, Bismuth Antimony as semiconducting material is giving a better cooling capacity than a non-linear square cross section leg TEC, Bismuth Telluride as material. For a given cooling capacity the size of TEC can be minimized since the results of 126 couple TEC is showing just 0.1 % lesser value as that of 127 couple TEC.
Theoretical study of thermoelectric cooling system performance
Journal of Engineering Research
This work provides a theoretical investigation to study the effect of different operational parameters on the performance of TE cooling system including the system COP and the rate of heat transfer. The parameters investigated are, the applied input power, inlet working fluid velocity, the arrangement of utilized TECs modules and fluid type. The geometry is created with ANSYS multi-physics software as a two-dimensional base case, it is consisted from two attached horizontal ducts of length (520 mm) and (560 mm), the interface surface between the two ducts contains three thermoelectric modules (4 mm height by 40 mm wide and 40 mm length). The distance between two consecutive thermoelectric modules (150 mm), the inlet and outlet duct diameter (15 mm) and the height of each duct (10 cm), the inlet voltage to thermoelectric modules ranges from 8.0 V to 12 V and the water inlet velocity to the two ducts from 0.001 to 0.01 m/s. Theoretical results showed that the overall COP of TE cooling system is increased with the applied input power up to 8.0 W then it decreases with input power up to 18 W after that it takes nearly a constant value, a noticeable enhancement in the COP is found when the three TECs are in use (Case 10) and the COP of TE cooling system using pure water and nanofluid with 0.05% of nanoparticles as coolants takes the maximum value.
Optimization of Thermoelectric Cooling System for Application in CPU Cooler
Energy Procedia, 2017
A multi-objective optimization based on thermoelectric heat exchanger module (TEHEM) is presented for application in CPU cooler. The thermoelectric heat exchanger module coupling multi-parameters is used as a novel method to solve the heat dissipation. Assuming that thermal-power consumption and physical properties of thermoelectric material are known, the optimal operating conditions covering with working current and hot-side thermal resistance are derived analytically from previous module. By combining the surface temperature of CPU and input power with a weight factor as the multi-objective function, the optimization is again implemented. Simultaneously, the multi-objective optimization is compared with the surface temperature of CPU and input power as the single-objective function. Finally, the optimal conditions are investigated to get a balance between the surface temperature and the input power. The simulation results show the optimal variables for single objective function are not suitable multi objective function sometimes. It is indispensable to consider the relative importance of objective values when it comes to practical demand. In addition, the optimal operating conditions depend on intensities of these operating parameters.
Improving the coefficient of performance of thermoelectric cooling systems: a review
International Journal of Energy Research, 2004
This paper reviews research carried out to improve the coefficient of performance of thermoelectric cooling systems during the past decade. This includes development of new materials for thermoelectric modules, optimisation of module design and fabrication, system analysis and heat exchange efficiency. Several conclusions are drawn.