Energy, exergy, environmental sustainability and economic analyses for automotive thermoelectric generator system with various configurations

Garud, Kunal Sandip; Seo, Jae-Hyeong; Bang, You-Ma; Pyo, Youngdug; Cho, Chongpyo; Lee, Moo‐Yeon; Lee, Dong-Yeon

doi:10.1016/j.energy.2021.122587

Cited by 25 publications

(4 citation statements)

References 51 publications

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“…The authors concluded that the maximum output voltage and power of 5.18 mV and 11.7 mW, respectively, were obtained from the device when operated under a hot junction temperature of 400 o C for an optimum length ratio of 0.5. Garud et al, [29] sought to investigate the energy, exergy, economic, and environmental sustainability performances of 3 thermoelectric device con gurations including singlestage, double-stage, and segmented device design. An experimental method was used to assess the performance of the single-stage thermoelectric generator design while a numerical model developed in ANSYS software was used to compare the performances of the different thermoelectric generator designs.…”

Section: Segmented Thermoelectric Generatormentioning

confidence: 99%

WITHDRAWN: A prediction model for a concentrating solar thermoelectric generator using artificial neural networks and extreme learning machines

Maduabuchi

Al‐Dahidi

Alnami

et al. 2022

Preprint

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The current numerical simulation tools used to optimize the performance of concentrating solar thermoelectric generators are extremely time consuming, and consequently require expensive computational energies. Furthermore, they are incapable of considering the effects of diverse real-life operating conditions on the performance of the system. Additionally, they sometimes neglect temperature dependency in the thermoelectric semiconductors and base their studies on just unicouple thermoelectric cells to avoid the further complexity of the numerical computation. These factors limit the flexibility of optimization studies that can be conducted on solar thermoelectrics; hence, limiting the insights that can be drawn to design high performing solar thermoelectric generators. This work is the first of its kind to introduce artificial neural networks and extreme learning machines as a substitute to these numerical methods to accelerate and ease the design process of solar thermoelectric generators. The data generation process is conducted using a 3-dimensional numerical model developed in ANSYS numerical solver and the optimized parameters include the high-temperature material content, semiconductor height and area, concentrated solar irradiance, cooling film coefficient, wind speed, and ambient temperature – on the system performance. A full-scale customized thermoelectric module comprising 127 thermocouples is designed and integrated in an optical concentrator for solar power generation while considering temperature dependency in all thermoelectric materials. Results depict that the geometry and operating condition optimization improved the system power and efficiency by 42.02% and 82.23%, respectively. Furthermore, the artificial neural network had the highest regression of 95.82% with the least mean squared error of 2.71 \(\times\) 10− 5 in learning the numerical-generated data set while performing 389 and 203 times faster than the numerical method in forecasting the system power and efficiency, respectively. Finally, methods of manufacturing the optimized thermoelectric module using 3-dimensional printing are discussed.

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Section: Segmented Thermoelectric Generatormentioning

confidence: 99%

WITHDRAWN: A prediction model for a concentrating solar thermoelectric generator using artificial neural networks and extreme learning machines

Maduabuchi

Al‐Dahidi

Alnami

et al. 2022

Preprint

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“…V is volume flow rate of oil. During the experimentation, obtained results deviate from the actual results owing to the errors in the prob position and calibration, measurement errors, accuracy of measuring devices and errors associated with ambient conditions [31]. The deviation between actual and obtained results is termed uncertainty in experimental parameters.…”

Section: Experimental Parameters and Uncertainty Analysismentioning

confidence: 99%

Heat Transfer Characteristics of an Electric Motor with Oil-Dripping Cooling under Overload Conditions

Kang,

Garud,

Park

et al. 2024

Symmetry

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The continuously increasing energy density of electric motors to match the performance of electric vehicles with internal-combustion-engine vehicles demands an advanced cooling strategy. Direct dripping/spray cooling is one of such potential cooling strategies to replace the conventional cooling method for achieving the desired thermal management of next-generation electric motors. In the present work, the heat transfer characteristics of an electric motor with oil-dripping cooling were experimentally investigated considering overload operating conditions. An experimental set-up comprising a 15 kW electric motor and an oil-dripping cooling system was developed. The experimental data were used to evaluate the maximum temperature, heat transfer coefficient and power consumption under the influence of a dripping hole diameter (2 mm, 3 mm, 4 mm), oil flow rate (8 LPM, 12 LPM, 16 LPM) and overload operating power (8.28 kW, 12.05 kW, 14.21 kW). The symmetrical oil distribution over the electric motor and the superior heat transfer from the electric motor to the oil was achieved when the oil-dripping cooling system was designed with the combination of a 4 mm dripping hole diameter and a 12 LPM oil flow rate. The combination of the 4 mm dripping hole diameter and 12 LPM oil flow rate showed the lowest maximum temperatures of 31.9 °C and 46.3 °C for electric motor under overload operating powers of 8.28 kW and 14.21 kW, respectively. In addition, the highest heat transfer coefficient of 7528.61 W/m2-K and lowest power consumption of 18.07 W were achieved for the oil-dripping cooling system with the combination of a 4 mm dripping hole diameter and 12 LPM oil flow rate. The best combination of the operating parameters is proposed for developing the oil-dripping cooling system that enables superior heat transfer characteristics and, thus, an enhanced thermal management of electric motors under overload conditions.

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“…Recentemente a abordagem M-FTE foi utilizada para avaliação das características de desempenho energético e exergético, sustentabilidade ambiental e aspecto econômico de geradores termoelétricos automotivos de um estágio, dois estágios e segmentados. (Garud et al 2022) Brazilian Journal of Development, Curitiba, v.9, n.10, p. 27762-27779, oct., 2023 Os resultados revelaram que o gerador termoelétrico de dois estágios de telureto de bismuto apresenta desempenhos energéticos e exergéticos superiores, maior sustentabilidade ambiental e menor economicidade. (Garud et al 2022) Um modelo M-FTE foi estabelecido na plataforma COMSOL para investigar a viabilidade do uso de geradores de vórtice longitudinal (LVGs) para melhorar a transferência de calor em sistemas TEG-a.…”

Section: )unclassified

“…(Garud et al 2022) Brazilian Journal of Development, Curitiba, v.9, n.10, p. 27762-27779, oct., 2023 Os resultados revelaram que o gerador termoelétrico de dois estágios de telureto de bismuto apresenta desempenhos energéticos e exergéticos superiores, maior sustentabilidade ambiental e menor economicidade. (Garud et al 2022) Um modelo M-FTE foi estabelecido na plataforma COMSOL para investigar a viabilidade do uso de geradores de vórtice longitudinal (LVGs) para melhorar a transferência de calor em sistemas TEG-a. Foram pesquisados os efeitos da altura LVG, ângulo de ataque LVG e temperatura do gás de entrada do lado quente.…”

Section: )unclassified

Simulação da performance de gerador termoelétrico para recuperação da energia dos gases de exaustão automotiva

Barbosa Júnior,

Dos Santos,

Barbosa

et al. 2023

Braz. J. Develop.

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Os estudos e desenvolvimento de novas aplicações de engenharia nas últimas décadas estão cada vez mais associados à utilização de técnicas numéricas e softwares computacionais capazes de estimar com grande precisão a solução de modelos matemáticos com grau de complexidade crescente em diversas áreas. Neste trabalho foi concebido um projeto piloto de um sistema de recuperação de calor do tipo gerador termoelétrico (TEG) útil para diversas aplicações de engenharia onde resíduos térmicos estão disponíveis como fonte de calor. Para o dimensionamento deste gerador termoelétrico, buscou-se avaliar a eficácia de uma geometria semelhante a tubos de gases de exaustão automotiva com aletas internas como elemento recuperador de calor com a montagem na superfície externa de um conjunto de módulos termoelétricos a base de telureto de bismuto. Foi simulado no ANSYS o desempenho em regime permanente de um gerador termoelétrico automotivo contendo 16 módulos termoelétricos, utilizando-se o modelo numérico multifísico fluido-térmico-elétrico, com temperaturas (425 K, 475 k, 575K) e vazão mássica (35 g/s, 45 g/s 55 g/s) dos gases de exaustão. A simulação apresentou desempenho pífio do TEG automotivo nas temperaturas dos gases de exaustão de 425 K e 475 K. A máxima potência elétrica estimada do TEG automotivo foi de 50,88 W para temperatura dos gases de exaustão de 575 K.

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Energy, exergy, environmental sustainability and economic analyses for automotive thermoelectric generator system with various configurations

Cited by 25 publications

References 51 publications

WITHDRAWN: A prediction model for a concentrating solar thermoelectric generator using artificial neural networks and extreme learning machines

WITHDRAWN: A prediction model for a concentrating solar thermoelectric generator using artificial neural networks and extreme learning machines

Heat Transfer Characteristics of an Electric Motor with Oil-Dripping Cooling under Overload Conditions

Simulação da performance de gerador termoelétrico para recuperação da energia dos gases de exaustão automotiva

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