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Processes
Special Issues
Advances in Waste Heat Recovery Using Thermoelectric Generators
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Advances in Waste Heat Recovery Using Thermoelectric Generators

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: closed (24 May 2024) | Viewed by 9168

Special Issue Editors

Dr. Minghui Ge

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Guest Editor
School of Energy and Environmental Engineering, Hebei University of Technology, Tianjin 300401, China
Interests: thermoelectric generator; waste heat recovery; condensation
Dr. Xun Liu

E-Mail Website
Guest Editor
Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan 43007, China
Interests: thermoelectric; thermal management; new energy vehicle
Special Issues, Collections and Topics in MDPI journals
Dr. Ding Luo

E-Mail Website
Guest Editor
College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443000, China
Interests: thermoelectricity; thermoelectric generator; thermoelectric system; thermoelectric refrigeration
Special Issues, Collections and Topics in MDPI journals
Dr. Yulong Zhao

E-Mail Website
Guest Editor
School of Energy and Environmental Engineering, Hebei University of Technology, Tianjin 300401, China
Interests: thermoelectricity; spray cooling; SOFC
Dr. Yanzhe Li

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, Tandon School of Engineering, New York University, New York, NY 11201, USA
Interests: thermoelectric power generation; porous media heat transfer enhancement; core flow heat transfer enhancement
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Waste heat recovery is a necessary means to achieve efficient use of energy and plays an important role in solving the energy crisis and environmental pollution problems. As a solid-state energy conversion device, thermoelectric generators are capable of directly converting thermal energy into electrical energy. Due to its simple structure, stability, and long life, it has shown great promise in aerospace, automotive, LNG, solar energy, body temperature, biomass, industrial waste heat, etc. However, due to the low efficiency of thermoelectric conversion, thermoelectric generators have not yet been used on a large scale.

To achieve the challenge of high thermoelectric performance, research and technology development are needed at multiple levels of materials, devices, and systems. This Special Issue will focus on high-efficiency thermoelectric conversion but is not limited to the following topics:

  • Thermoelectric theory
  • Thermoelectric materials
  • Thermoelectric generator
  • Thermoelectric system
  • Thermoelectric cooler
  • Advanced algorithms
  • Optimization methods
  • Testing technology
  • Application cases

Dr. Minghui Ge
Dr. Xun Liu
Dr. Ding Luo
Dr. Yulong Zhao
Dr. Yanzhe Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • thermoelectric
  • waste heat recovery
  • refrigeration
  • performance optimization
  • application

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

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Research

13 pages, 2406 KiB  
Article
Optimization Design of an Intermediate Fluid Thermoelectric Generator for Exhaust Waste Heat Recovery
by Wei Zhang, Wenjie Li, Shuqian Li, Liyao Xie, Minghui Ge and Yulong Zhao
Processes 2023, 11(6), 1853; https://doi.org/10.3390/pr11061853 - 20 Jun 2023
Cited by 2 | Viewed by 1405
Abstract
The intermediate fluid thermoelectric generator (IFTEG) represents a novel approach to power generation, predicated upon the principles of gravity heat pipe technology. Its key advantages include high-power output and a compact module area. The generator’s performance, however, is influenced by the variable exhaust [...] Read more.
The intermediate fluid thermoelectric generator (IFTEG) represents a novel approach to power generation, predicated upon the principles of gravity heat pipe technology. Its key advantages include high-power output and a compact module area. The generator’s performance, however, is influenced by the variable exhaust parameters typical of automobile operation, which presents a significant challenge in the design process. The present study establishes a mathematical model to optimize the design of the IFTEG. Our findings suggest that the optimal module area sees substantial growth with an increase in both the exhaust heat exchanger area and the exhaust flow rate. Interestingly, the optimal module area appears to demonstrate a low sensitivity to changes in exhaust temperature. To address the challenge of determining the optimal module area, this study introduces the concept of peak power deviation. This method posits that any deviation from the optimal module area results in an equivalent power deviation. For instance, with an exhaust heat exchanger area of 1.6 m2, the minimum peak power deviation is 27.5%, corresponding to a design module area of 0.124 m2. As such, the actual output power’s deviation from the maximum achievable output power will not exceed 27.5% for any given set of exhaust parameters. This study extends its findings to delineate the relationship between the optimal design module area and the exhaust heat exchanger area. These insights could serve as a useful guide for the design of future power generators. Full article
(This article belongs to the Special Issue Advances in Waste Heat Recovery Using Thermoelectric Generators)
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15 pages, 5818 KiB  
Article
Experimental Study on the Working Efficiency and Exergy Efficiency of the Vehicle-Mounted Thermoelectric Generator for Cold Chain Logistics Transportation Vehicle
by Yunchi Fu and Yanzhe Li
Processes 2023, 11(6), 1782; https://doi.org/10.3390/pr11061782 - 11 Jun 2023
Cited by 1 | Viewed by 1628
Abstract
This paper investigates a vehicle-mounted thermoelectric generator system working efficiency and exergy efficiency in a cold chain logistics transport vehicle (CLVTEG). The study examines the impact of factors such as load resistance, temperature difference, and copper foam on the performance of CLVTEG. Results [...] Read more.
This paper investigates a vehicle-mounted thermoelectric generator system working efficiency and exergy efficiency in a cold chain logistics transport vehicle (CLVTEG). The study examines the impact of factors such as load resistance, temperature difference, and copper foam on the performance of CLVTEG. Results demonstrate that adding copper foam significantly improves the output power of CLVTEG, with 40 PPI copper foam showing a 1.8 times increase compared to no copper foam. Additionally, copper foam enhances working and exergy efficiency, with 10 PPI copper foam achieving the best overall efficiency. The study also explores the effect of temperature difference on CLVTEGs efficiency, observing an initial increase followed by a decrease. Overall, this research underscores the importance of considering work and exergy efficiency when evaluating thermoelectric generators. Adding copper foam in the CLVTEG central area enhances heat transfer, resulting in improved efficiency. These findings offer valuable insights for optimizing the design and operation of thermoelectric generators in cold chain logistics transport vehicles. Full article
(This article belongs to the Special Issue Advances in Waste Heat Recovery Using Thermoelectric Generators)
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12 pages, 4814 KiB  
Article
Thermoelectric Generator Design and Characterization for Industrial Pipe Waste Heat Recovery
by Di Xiao, Peng Sun, Jianlin Wu, Yin Zhang, Jiehua Wu, Guoqiang Liu, Haoyang Hu, Jun Hu, Xiaojian Tan, Shi He and Jun Jiang
Processes 2023, 11(6), 1714; https://doi.org/10.3390/pr11061714 - 3 Jun 2023
Cited by 4 | Viewed by 3979
Abstract
Thermoelectric technology is an effective strategy to convert low–grade waste heat to electrical energy directly. Thermoelectric generators (TEGs) have been extensively studied in various waste heat scenarios, such as vehicle exhaust, metal casting processes and more. However, industrial pipelines also possess high levels [...] Read more.
Thermoelectric technology is an effective strategy to convert low–grade waste heat to electrical energy directly. Thermoelectric generators (TEGs) have been extensively studied in various waste heat scenarios, such as vehicle exhaust, metal casting processes and more. However, industrial pipelines also possess high levels of heat and wide distribution, yet there is limited research on TEGs for use in these pipes. The challenge in designing a TEG lies in the heat collector, which is complicated by the distinct structural differences between pipe and plate–shaped TEMs. Ultimately, we propose an arch bridge–shaped heat collector for the pipe to recover wasted thermal energy. The effects of some key factors, such as topology of TEMs, heat source temperature, cooling water temperature and velocity, on the generating performance are studied. The TEG achieved a temperature difference of 65.98 °C across the two ends of the TEM, resulting in an output power of 17.89 W at an open–circuit voltage of 133.35 V. This provides evidence that the designed heat collector is a feasible solution for recovering waste heat from pipes using TEG technology. This work provides reliable experimental data and efficient design for the application of TEGs in industrial pipes. Full article
(This article belongs to the Special Issue Advances in Waste Heat Recovery Using Thermoelectric Generators)
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15 pages, 6835 KiB  
Article
GA−BP Prediction Model for Automobile Exhaust Waste Heat Recovery Using Thermoelectric Generator
by Fei Li, Peng Sun, Jianlin Wu, Yin Zhang, Jiehua Wu, Guoqiang Liu, Haoyang Hu, Jun Hu, Xiaojian Tan, Shi He and Jun Jiang
Processes 2023, 11(5), 1498; https://doi.org/10.3390/pr11051498 - 15 May 2023
Viewed by 1401
Abstract
Thermoelectric generator (TEG) has important applications in automotive exhaust waste heat recovery. The Back propagation neural network (BP) can predict the electrical generating performance of TEG efficiently and accurately due to its advantage of being good at handing nonlinear data. However, BP algorithm [...] Read more.
Thermoelectric generator (TEG) has important applications in automotive exhaust waste heat recovery. The Back propagation neural network (BP) can predict the electrical generating performance of TEG efficiently and accurately due to its advantage of being good at handing nonlinear data. However, BP algorithm is easy to fall into local optimum, and its training data usually have deviation since the data are obtained through the simulation software. Both of the problems will reduce the prediction accuracy. In order to further improve the prediction accuracy of BP algorithm, we use the genetic algorithm (GA) to optimize BP neural network by selection, crossover, and mutation operation. Meanwhile, we create a TEG for the heat waste recovery of automotive exhaust and test 84 groups of experimental data set to train the GA−BP prediction model to avoid the deviation caused by the simulation software. The results show that the prediction accuracy of the GA−BP model is better than that of the BP model. For the predicted values of output power and output voltage, the mean absolute percentage error (MAPE) increased to 2.83% and 2.28%, respectively, and the mean square error (MSE) is much smaller than the value before optimization, and the correlation coefficient (R2) of the network model is greater than 0.99. Full article
(This article belongs to the Special Issue Advances in Waste Heat Recovery Using Thermoelectric Generators)
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