Geometric optimization of segmented thermoelectric generators for waste heat recovery systems using genetic algorithm

Lin, Yousheng; He, Qing; Wang, Wenhao; Chen, Jie-Chao; Huang, Si-Min

doi:10.1016/j.energy.2021.121220

Cited by 20 publications

(8 citation statements)

References 32 publications

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“…For further analysis, we compared our proposed WGAN-ResNet with a support vector machine (SVM), 53 k -nearest neighbor (KNN), 54 naïve Bayes model 55 and ensemble learning. 56 The hyper-parameters of SVM were optimized by a genetic algorithm (GA) 57 and particle swarm optimization (PSO). 58,59 SVM, KNN, the naïve Bayes model and ensemble learning can be considered to be shallow learning.…”

Section: Resultsmentioning

confidence: 99%

Pesticide detection combining the Wasserstein generative adversarial network and the residual neural network based on terahertz spectroscopy

Yang

Qin

et al. 2022

RSC Adv.

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Section: Resultsmentioning

confidence: 99%

Pesticide detection combining the Wasserstein generative adversarial network and the residual neural network based on terahertz spectroscopy

Yang

Qin

et al. 2022

RSC Adv.

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“…The optimized segmented irregularly variable cross-section TEG generated 51.71% and 7.57% more power than a conventional and only variable cross-section counterpart. Ge et al [195] compiled the geometry of two segmented TEGs operating under parallel-flow and counter-flow arrangements. They adopted the genetic algorithm (GA) and FEM to obtain the optimal solution.…”

Section: Segmented Leg Geometrymentioning

confidence: 99%

A Review of Thermoelectric Generators in Automobile Waste Heat Recovery Systems for Improving Energy Utilization

Bhakta,

Kundu

2024

Energies

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With the progress of modern times, automobile technology has become integral to human society. At the same time, the need for energy has also grown. In parallel, the total amount of waste energy that is liberated from different parts of the automobile has also increased. In this ever-increasing energy demand pool, future energy shortages and environmental pollution are the primary concerns. A thermoelectric generator (TEG) is a promising technology that utilizes waste heat and converts it into useful electrical power, which can reduce fuel consumption to a significant extent. This paper comprehensively reviews automobile thermoelectric generators and their technological advancements. The review begins by classifying different waste heat technologies and discussing the superiority of TEGs over the other existing technologies. Then, we demonstrate the basic concept of and advancements in new high-performance TEG materials. Following that, improvements and associated challenges with various aspects, such as the heat exchanger design, including metal foam, extended body, intermediate fluid and heat pipe, leg geometry design, segmentation, and multi-staging, are discussed extensively. Finally, the present study highlights research guidelines for TEG design, research gaps, and future directions for innovative works in automobile TEG technologies.

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“…For dynamically cooled systems, TENG systems may benefit from coolant flowing parallel to the heat source. Ge et al [240] found that parallel hot/cold flow resulted in a larger temperature gradient for the TEGs near the inlet, producing a larger overall power output than for a counter-flow system. The equalization of hot/cold fluids is especially pronounced for hot exhaust gas, which cools rapidly due to its low heat capacity, [241] so small, highefficiency TENGs placed where the exhaust gas is hottest are most efficient for maximizing power density.…”

Section: Harnessing Waste Heatmentioning

confidence: 99%

Recent Advances in the Nanomaterials, Design, Fabrication Approaches of Thermoelectric Nanogenerators for Various Applications

Kim

Kumar

Annamalai

et al. 2022

Adv Materials Inter

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power-dense, owing to their tuneable nanostructures. Hence, smaller TENGs are better suited for small form-factor applications like wearable electronics, internet of things (IoT) devices, and self-powered sensors. However, the higher complexity and cost of TENGs than TEGs inhibit their widespread adoption. This review appraises the latest advances in TENG materials, design, and fabrication in optimizing the performance of TENGs, making TENGs more viable for real-world applications. More precisely, this work examines how nanostructure engineering, nanomaterial compositing, and post-synthesis treatment approaches have enhanced the TE properties of common and promising TE materials, including tellurides, selenides, metal oxides, metal alloys, silicon, carbon nanomaterials, and organic compounds. Given that the TE material is a key component in TENGs, this review highlights how to optimize other vital parameters, including the TENG configuration, contact interface, form factor, heat sink use, and folded shape for specific applications. Lastly, critical attributes of TENGs used in wearable electronics, sensors, implantable electronics, solar energy conversion, and waste heat recovery are analyzed.

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Geometric optimization of segmented thermoelectric generators for waste heat recovery systems using genetic algorithm

Cited by 20 publications

References 32 publications

Pesticide detection combining the Wasserstein generative adversarial network and the residual neural network based on terahertz spectroscopy

Pesticide detection combining the Wasserstein generative adversarial network and the residual neural network based on terahertz spectroscopy

A Review of Thermoelectric Generators in Automobile Waste Heat Recovery Systems for Improving Energy Utilization

Recent Advances in the Nanomaterials, Design, Fabrication Approaches of Thermoelectric Nanogenerators for Various Applications

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