Modeling and Experimentation of New Thermoelectric Cooler–Thermoelectric Generator Module

Teffah, Khaled; Zhang, Youtong; Mou, Xiao-long

doi:10.3390/en11030576

Cited by 55 publications

(41 citation statements)

References 30 publications

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“…The principle for energy conversion is based on a thermoelectric effect that includes three different thermal-to-electric phenomena: the Seebeck effect, the Peltier effect, and the Thomson effect [3]. The Seebeck effect results in an induced voltage in response to the temperature difference applied across the two ends of a thermocouple, where the induced voltage is directly proportional to the temperature difference [4,5]. The Peltier effect is the reverse of the Seebeck effect, and it results in cooling or heating at the two junctions of a thermocouple when an electric current passes through it [6].…”

Section: Introductionmentioning

confidence: 99%

“…Experimental studies are often expensive and time-consuming when used to optimize all of the variables. Therefore, analytical and numerical models have been developed using simplified one-dimensional models [24,25] as well as complex three-dimensional models [5,26,27].Thermoelectric generators are now being utilized for a variety of applications, such as power sources for wireless sensor nodes in satellites, space probes, and unmanned remote facilities [28,29]. TEGs are being developed for use in automobiles for generating electricity from exhaust gases in order to improve overall engine efficiency [30].…”

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confidence: 99%

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confidence: 99%

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Combinatory Finite Element and Artificial Neural Network Model for Predicting Performance of Thermoelectric Generator

2018

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Thermoelectric generators (TEGs) are rapidly becoming the mainstream technology for converting thermal energy into electrical energy. The rise in the continuous deployment of TEGs is related to advancements in materials, figure of merit, and methods for module manufacturing. However, rapid optimization techniques for TEGs have not kept pace with these advancements, which presents a challenge regarding tailoring the device architecture for varying operating conditions. Here, we address this challenge by providing artificial neural network (ANN) models that can predict TEG performance on demand. Out of the several ANN models considered for TEGs, the most efficient one consists of two hidden layers with six neurons in each layer. The model predicted TEG power with an accuracy of ±0.1 W, and TEG efficiency with an accuracy of ±0.2%. The trained ANN model required only 26.4 ms per data point for predicting TEG performance against the 6.0 minutes needed for the traditional numerical simulations.Energies 2018, 11, 2216 2 of 17 in the Thomson heat, which is proportional to the electric current and absorbed or released based on the direction of the current [4].Continuous efforts have been made toward developing high performance n-type and p-type thermoelectric (TE) materials [1,[7][8][9]. The performance of TE materials is measured in terms of a dimensionless metric called the figure of merit, which is denoted as ZT. It combines three key material properties: thermal conductivity (κ), electrical resistivity (ρ), and the Seebeck coefficient (S), along with the absolute temperature (T), and it is given as ZT = S 2 κρ T [10,11]. The magnitude of ZT for most of the commercial thermoelectric materials is close to unity; however, recent studies have reported higher values for some of the state-of-the-art TE materials, such as a quantum-dot superlattice with ZT~3.5 at 575 K [12], a superlattice structure with ZT~2.4 at 300 K and ZT~2.9 at 400 K [13], and lead antimony silver telluride with ZT~2.2 at 800 K [14]. The thermoelectric modules built using nanostructured materials have been reported to exhibit thermal-to-electrical energy conversion efficiency up to 10% at a temperature difference of 500 K [15].The performance of TEG modules depends not only on the ZT of the TE material, but also on the geometric dimensions of the thermocouples and operating conditions such as the temperature difference and electrical load [16,17]. Several researchers in the past have attempted to optimize p-n leg geometry comprising of length, a cross-sectional area, and the number of thermocouples [18][19][20][21]. A few studies have attempted to provide optimal shape factor parameters such as the area ratio for p-n legs (Ap/An), the aspect ratio (leg length/leg area), and the slenderness ratio ((Ap/Lp)/(An/Ln), where Ap and An denote base area and Lp and Ln denote length of p-and n-type legs) [22,23]. However, these parameter changes depend upon the TE material used for fabricating TEG legs, the materials used in assembling the TEG modules, and oper...

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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Combinatory Finite Element and Artificial Neural Network Model for Predicting Performance of Thermoelectric Generator

2018

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“…Typical applications of Peltier devices include cooling in electronics, touristic and domestic refrigeration, laboratories, medicine and automobile uses [8]. The increasing interest in TE cooling and heating translates into the development of new applications [9], possible to obtain in accordance with the development of new production technologies and higher efficiency of modules [10], as well as system operation optimization [11].…”

Section: Introductionmentioning

confidence: 99%

A PV-Powered TE Cooling System with Heat Recovery: Energy Balance and Environmental Impact Indicators

Żelazna

Gołębiowska

2020

Energies

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Over the past decades, clean and renewable energy has become a subject of great interest to both science and industry in response to the pollution caused by conventional energy sources. Its useful form should always meet the requirements of high performance and low environmental impact, while remaining within the scope of the expected functionality. The purpose of study presented in this paper was to determine the operational characteristics for a recently developed photovoltaic (PV)-powered thermoelectric (TE) cooling system with heat recovery. The characteristics of operation of the tested system were determined within the use of a specially developed measurement system. The conducted experimental research allowed describing the conditions of power supply for TE module using PV system, calculate the coefficient of performance (COP) for the whole TE cooling system with heat recovery and calculate the environmental impact indicators based on the material and energy balance used for life cycle assessment (LCA).

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“…23456 In contrast, TE applications as coolants that utilize DC electric current sources are also intensively studied. Several related papers such as on [8,9] and that combines TE as a coolant and a power plant at the same time [10]. The working principle can be seen in Fig.…”

Section: Introductionmentioning

confidence: 99%

Temperature Control of Soft Drinks on Vehicle with Portable Storage Thermoelectric Cooler

Basri¹,

Mustofa

Patabang³

et al. 2018

EPI-IJE

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This study aims to design a control system with fuzzy logic on a system of cooling the storage of soft drinks with thermoelectric coolers. This storage can be carried in a vehicle using a DC electric power from a photovoltaic solar cell mounted on the roof of the car. Under certain conditions the energy source of cigarette lighter in a car can replace the solar cells. The test results show that a temperature of 15oC can be reached within 30 minutes with fuzzy control, while without fuzzy control the time needed in 63 minutes, 30 minutes longer.

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Modeling and Experimentation of New Thermoelectric Cooler–Thermoelectric Generator Module

Cited by 55 publications

References 30 publications

Combinatory Finite Element and Artificial Neural Network Model for Predicting Performance of Thermoelectric Generator

Combinatory Finite Element and Artificial Neural Network Model for Predicting Performance of Thermoelectric Generator

A PV-Powered TE Cooling System with Heat Recovery: Energy Balance and Environmental Impact Indicators

Temperature Control of Soft Drinks on Vehicle with Portable Storage Thermoelectric Cooler

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