[HTML][HTML] Artificial intelligence and machine learning in energy systems: A bibliographic perspective

A Entezari, A Aslani, R Zahedi, Y Noorollahi - Energy Strategy Reviews, 2023 - Elsevier
Economic development and the comfort-loving nature of human beings in recent years have
resulted in increased energy demand. Since energy resources are scarce and should be …

A comprehensive review on the state of charge estimation for lithium‐ion battery based on neural network

Z Cui, L Wang, Q Li, K Wang - International Journal of Energy …, 2022 - Wiley Online Library
Implementing carbon neutrality and emission peak policies requires a high‐level electric
vehicle field. Lithium‐ion batteries have been considered an essential component of electric …

Machine learning: an advanced platform for materials development and state prediction in lithium‐ion batteries

C Lv, X Zhou, L Zhong, C Yan, M Srinivasan… - Advanced …, 2022 - Wiley Online Library
Lithium‐ion batteries (LIBs) are vital energy‐storage devices in modern society. However,
the performance and cost are still not satisfactory in terms of energy density, power density …

Error metrics and performance fitness indicators for artificial intelligence and machine learning in engineering and sciences

MZ Naser, AH Alavi - Architecture, Structures and Construction, 2023 - Springer
Artificial intelligence (AI) and Machine learning (ML) train machines to achieve a high level
of cognition and perform human-like analysis. Both AI and ML seemingly fit into our daily …

Advanced battery management strategies for a sustainable energy future: Multilayer design concepts and research trends

H Dai, B Jiang, X Hu, X Lin, X Wei, M Pecht - Renewable and Sustainable …, 2021 - Elsevier
Lithium-ion batteries are promising energy storage devices for electric vehicles and
renewable energy systems. However, due to complex electrochemical processes, potential …

[HTML][HTML] A review of machine learning state-of-charge and state-of-health estimation algorithms for lithium-ion batteries

Z Ren, C Du - Energy Reports, 2023 - Elsevier
Vehicle electrification has been proven to be an efficient way to reduce carbon dioxide
emissions and solve the energy crisis. Lithium-ion batteries (LiBs) are considered the …

Modeling, state of charge estimation, and charging of lithium‐ion battery in electric vehicle: a review

M Adaikkappan… - International Journal of …, 2022 - Wiley Online Library
Extension of driving range and battery run time optimization are necessary key points in the
modeling of Electric Vehicle (EV). In this view, Battery Management System (BMS) plays a …

Machine learning on sustainable energy: A review and outlook on renewable energy systems, catalysis, smart grid and energy storage

D Rangel-Martinez, KDP Nigam… - … Research and Design, 2021 - Elsevier
This study presents a broad view of the current state of the art of ML applications in the
manufacturing sectors that have a considerable impact on sustainability and the …

Tackling climate change with machine learning

D Rolnick, PL Donti, LH Kaack, K Kochanski… - ACM Computing …, 2022 - dl.acm.org
Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …

State estimation for advanced battery management: Key challenges and future trends

X Hu, F Feng, K Liu, L Zhang, J **e, B Liu - Renewable and Sustainable …, 2019 - Elsevier
Batteries are presently pervasive in portable electronics, electrified vehicles, and renewable
energy storage. These indispensable engineering applications are all safety-critical and …