Dynamic Reconfiguration of Thermoelectric Generators for Vehicle Radiators Energy Harvesting Under Location-Dependent Temperature Variations

Kim, Jaemin; Baek, Donkyu; Ding, Caiwen; Lin, Senshang; Shin, Donghwa; Lin, Xue; Wang, Yanzhi; Cho, Young Hoo; Park, Sang Hyun; Chang, Naehyuck

doi:10.1109/tvlsi.2018.2812705

Cited by 14 publications

(7 citation statements)

References 14 publications

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“…One distinct approach to produce electrical energy is to use TEG, which works based on the temperature difference on its both sides [30]. TEG is a semiconductor device that converts temperature difference into electrical potential difference through the Seebeck effect [31]. As this temperature difference increases, the overall output voltage deliverable at the TEG's output will be higher.…”

Section: Description Of Heh Systemmentioning

confidence: 99%

Thermally reused solar energy harvesting using current mirror cells

et al. 2023

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This paper implements a simultaneous solar and thermal energy harvesting system, as a hybrid energy harvesting (HEH) system, to convert ambient light into electrical energy through photovoltaic (PV) cells and heat absorbed in the body of PV cells. Indeed, a solar panel equipped with serially connected thermoelectric generators not only converts the incoming light into electricity but also takes advantage of heat emanating from the light. In a conventional HEH system, the diode block is used to provide the path for the input source with the highest value. In this scheme, at each time, only one source can be handled to generate its output, while other sources are blocked. To handle this challenge of combining resources in HEH systems, this paper proposes a method for collecting all incoming energies and conveying its summation to the load via the current mirror cells in an approach similar to the maximum power point tracking. This technique is implemented using off‐the‐shelf components. The measurement results show that the proposed method is a realistic approach for supplying electrical energy to wireless sensor nodes and low‐power electronics.

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Section: Description Of Heh Systemmentioning

confidence: 99%

Thermally reused solar energy harvesting using current mirror cells

et al. 2023

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“…Due to the low power density received from this part, several TEGs can be connected in series and parallel in an array, producing a usable voltage and a higher energy density. 40 The name ZT is used, as a figure of merit, to express the competence in determining the efficiency of thermocouples and TEGs. In this article, we have used TEG with the part number SP1848-27145.…”

Section: Structure Of Thermal Energy Harvestingmentioning

confidence: 99%

“…This element with the Seebeck effect generates electrical energy from thermal energy. Due to the low power density received from this part, several TEGs can be connected in series and parallel in an array, producing a usable voltage and a higher energy density 40 . The name ZT is used, as a figure of merit, to express the competence in determining the efficiency of thermocouples and TEGs.…”

Section: System Descriptionmentioning

confidence: 99%

Modeling and implementation of a novel active voltage balancing circuit using deep recurrent neural network with dropout regularization

Noohi

Faraji

Sadrossadat

et al. 2022

Circuit Theory & Apps

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Recurrent neural networks (RNN) emerged as powerful tools to model and analyze the nonlinear behavior of electronic circuits accurately and quickly.Efforts to improve the accuracy of RNN will lead to the design of better-quality products, which is essential in various fields such as the design of energy harvesting (EH) systems. EH techniques can provide the electrical energy needed for low-power electronics without the need for a battery or with minimal dependency. Due to the importance of the active voltage balancing circuit in EH systems, we have proposed a new macromodeling method called dropout local-feedback deep recurrent neural network (Dropout-LFDRNN) to model and analyze this circuit along with two other nonlinear circuits asexamples. This technique is an advance over the LFDRNN macromodeling method, and based on the obtained results from the measurements, we were able to build a fast macromodel for the active balancing circuit, which outperforms conventional deep recurrent neural network modeling method in terms of accuracy without sacrificing speed. It is worth mentioning that this proposed technique in this paper can be considered a viable approach for modeling and analysis of nonlinear electronic components and circuits. In addition to the advantage of generating a more accurate model, the model based on the Dropout-LFDRNN approach is much faster than the existing transistor-level models.

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“…In addition to wind, hydro, solar, and hydrogen [7,8], thermoelectric generation (TEG) also possesses remarkable application potential and value [9] because of its prominent advantages of simple structure, sturdiness, being noiseless, long service life, etc. TEG has been applied in some industrial production, such as in automobile engines [10], geothermal energy exploitation [11], natural gas boilers [12], solar thermoelectric cooling systems [13], combined heat and power generation [14], wearable devices [15], energy-autonomous sensors [16], etc. However, the low energy conversion efficiency of TEG systems given unpredictable and ineluctable heterogeneous temperature distribution (HgTD) is the main obstacle that limits its larger scale and wider range of application [17].…”

Section: Introductionmentioning

confidence: 99%

“…However, there are not many current studies on the TEG system reconfiguration. In [10], a dynamic reconfiguration algorithm is proposed for a TEG array installed on vehicle radiators, one which can change interconnections (series or parallel) of TEG modules. Nevertheless, it assumes that the temperature difference between the TEG modules connected in parallel in the same row is similar, which is not always guaranteed in largescale TEG systems.…”

Section: Introductionmentioning

confidence: 99%

Dynamic reconfiguration for TEG systems under heterogeneous temperature distribution via adaptive coordinated seeker

Chen

Yang

Guo

et al. 2022

Prot Control Mod Power Syst

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A thermoelectric generation (TEG) system has the weakness of relatively low thermoelectric conversion efficiency caused by heterogeneous temperature distribution (HgTD). Dynamic reconfiguration is an effective technique to improve its overall energy efficiency under HgTD. Nevertheless, numerous combinations of electrical switches make dynamic reconfiguration a complex combinatorial optimization problem. This paper aims to design a novel adaptive coordinated seeker (ACS) based on an optimal configuration strategy for large-scale TEG systems with series–parallel connected modules under HgTDs. To properly balance global exploration and local exploitation, ACS is based on ‘divide-and-conquer’ parallel computing, which synthetically coordinates the local searching capability of tabu search (TS) and the global searching capability of a pelican optimization algorithm (POA) during iterations. In addition, an equivalent re-optimization strategy for a reconfiguration solution obtained by meta-heuristic algorithms (MhAs) is proposed to reduce redundant switching actions caused by the randomness of MhAs. Two case studies are carried out to assess the feasibility and superiority of ACS in comparison with the artificial bee colony algorithm, ant colony optimization, genetic algorithm, particle swarm optimization, simulated annealing algorithm, TS, and POA. Simulation results indicate that ACS can realize fast and stable dynamic reconfiguration of a TEG system under HgTDs. In addition, RTLAB platform-based hardware-in-the-loop experiments are carried out to further validate the hardware implementation feasibility.

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Dynamic Reconfiguration of Thermoelectric Generators for Vehicle Radiators Energy Harvesting Under Location-Dependent Temperature Variations

Cited by 14 publications

References 14 publications

Thermally reused solar energy harvesting using current mirror cells

Thermally reused solar energy harvesting using current mirror cells

Modeling and implementation of a novel active voltage balancing circuit using deep recurrent neural network with dropout regularization

Dynamic reconfiguration for TEG systems under heterogeneous temperature distribution via adaptive coordinated seeker

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