Machine learning for a sustainable energy future
Transitioning from fossil fuels to renewable energy sources is a critical global challenge; it
demands advances—at the materials, devices and systems levels—for the efficient …
demands advances—at the materials, devices and systems levels—for the efficient …
A review on battery modelling techniques
The growing demand for electrical energy and the impact of global warming leads to a
paradigm shift in the power sector. This has led to the increased usage of renewable energy …
paradigm shift in the power sector. This has led to the increased usage of renewable energy …
Degradation of lithium-ion batteries in an electric transport complex
NI Shchurov, SI Dedov, BV Malozyomov, AA Shtang… - Energies, 2021 - mdpi.com
The article provides an overview and comparative analysis of various types of batteries,
including the most modern type—lithium-ion batteries. Currently, lithium-ion batteries (LIB) …
including the most modern type—lithium-ion batteries. Currently, lithium-ion batteries (LIB) …
[HTML][HTML] Data-driven state of health modelling—A review of state of the art and reflections on applications for maritime battery systems
Battery systems are becoming an increasingly attractive alternative for powering ocean
going ships, and the number of fully electric or hybrid ships relying on battery power for …
going ships, and the number of fully electric or hybrid ships relying on battery power for …
Epic: An electric power testbed for research and training in cyber physical systems security
Testbeds that realistically mimic the operation of critical infrastructure are of significant value
to researchers. One such testbed, named Electrical Power and Intelligent Control (EPIC), is …
to researchers. One such testbed, named Electrical Power and Intelligent Control (EPIC), is …
Prediction of vanadium redox flow battery storage system power loss under different operating conditions: Machine learning based approach
N Ra, A Bhattacharjee - International Journal of Energy …, 2022 - Wiley Online Library
Prediction of battery storage system loss is necessary to further improve the performance
reliability and efficiency of the battery storage system. The prediction of the overall system …
reliability and efficiency of the battery storage system. The prediction of the overall system …
Revealing inhomogeneities in electrode lithiation using a real-time discrete electro-chemical model
Transmission line-or mixed conducting network models are a widely used model category
for the characterization of porous electrodes in the frequency domain. Their benefits in time …
for the characterization of porous electrodes in the frequency domain. Their benefits in time …
Lifetime prediction of lithium-ion capacitors based on accelerated aging tests
Lithium-ion Capacitors (LiCs) that have intermediate properties between lithium-ion
batteries and supercapacitors are still considered as a new technology whose aging is not …
batteries and supercapacitors are still considered as a new technology whose aging is not …
Machine‐Learning‐Based Accurate Prediction of Vanadium Redox Flow Battery Temperature Rise Under Different Charge–Discharge Conditions
D Anirudh Narayan, A Johar, D Kalra… - Energy …, 2024 - Wiley Online Library
Accurate prediction of battery temperature rise is very essential for designing efficient
thermal management scheme. In this paper, machine learning (ML)‐based prediction of …
thermal management scheme. In this paper, machine learning (ML)‐based prediction of …
Modeling of charging profiles for stationary battery systems using curve fitting approach
K Chaudhari, NK Kandasamy… - IECON 2017-43rd …, 2017 - ieeexplore.ieee.org
Stationary Battery Systems (SBS) are becoming a critical component in power distribution
network across the world. Penetration of renewable energy sources which are intermittent in …
network across the world. Penetration of renewable energy sources which are intermittent in …