Thermoelectric energy harvesting for internet of things devices using machine learning: A review

T Kucova, M Prauzek, J Konecny… - CAAI Transactions …, 2023 - Wiley Online Library
Initiatives to minimise battery use, address sustainability, and reduce regular maintenance
have driven the challenge to use alternative power sources to supply energy to devices …

Latest Advancements in Solar Photovoltaic‐Thermoelectric Conversion Technologies: Thermal Energy Storage Using Phase Change Materials, Machine Learning …

H Alghamdi, C Maduabuchi, K Okoli… - … Journal of Energy …, 2024 - Wiley Online Library
In recent times, the significance of renewable energy generation has increased and
photovoltaic‐thermoelectric (PV‐TE) technologies have emerged as a promising solution …

Thermo-mechanical optimization of thermoelectric generators using deep learning artificial intelligence algorithms fed with verified finite element simulation data

C Maduabuchi - Applied Energy, 2022 - Elsevier
The rising levels of global warming in the environment owing to emissions from fossil-fuel-
based engines has increased the search for efficient clean energy systems. Thermoelectric …

Deep neural networks for quick and precise geometry optimization of segmented thermoelectric generators

C Maduabuchi, C Eneh, AA Alrobaian, M Alkhedher - Energy, 2023 - Elsevier
To solve the problems of the current optimization methods for solar segmented
thermoelectric generator performance based on numerical methods, this paper applied …

Machine learning model for transient exergy performance of a phase change material integrated-concentrated solar thermoelectric generator

H Alghamdi, C Maduabuchi, DS Mbachu… - Applied Thermal …, 2023 - Elsevier
Despite the merits of incorporating phase change materials in concentrating solar
thermoelectric generating systems, the following research gaps still need to be filled to make …

[HTML][HTML] Segmented thermoelectric generator modelling and optimization using artificial neural networks by iterative training

Y Zhu, DW Newbrook, P Dai, J Liu, CHK de Groot… - Energy and AI, 2023 - Elsevier
Renewable energy technologies are central to emissions reduction and essential to achieve
net-zero emission. Segmented thermoelectric generators (STEG) facilitate more efficient …

Predicting the optimal performance of a concentrated solar segmented variable leg thermoelectric generator using neural networks

C Maduabuchi, H Fagehi, I Alatawi, M Alkhedher - Energies, 2022 - mdpi.com
The production of high-performing thermoelectrics is limited by the high computational
energy and time required by the current finite element method solvers that are used to …

Multiobjective Optimization and Machine Learning Algorithms for Forecasting the 3E Performance of a Concentrated Photovoltaic‐Thermoelectric System

H Alghamdi, C Maduabuchi, A Yusuf… - … Journal of Energy …, 2023 - Wiley Online Library
Previous theoretical research efforts which were validated by experimental findings
demonstrated the thermo‐economic benefits of the hybrid concentrated photovoltaic …

Sensors energy optimization for renewable energy-based WBANS on sporadic elder movements

AS Rajawat, SB Goyal, P Bedi, C Verma, CO Safirescu… - Sensors, 2022 - mdpi.com
The world is advancing to a new era where a new concept is emerging that deals with
“wirelessness”. As we know, renewable energy is the future, and this research studied the …

Machine learning and numerical simulations for electrical, thermodynamic, and mechanical assessment of modified solar thermoelectric generators

M Alobaid, C Maduabuchi, A Albaker, A Almalaq… - Applied Thermal …, 2023 - Elsevier
The frustum leg thermoelectric generator (FLTEG) was recently proposed as a high-
performing power generator. However, there is no basis for proposing this device since its …