Modelling and optimal energy management for battery energy storage systems in renewable energy systems: A review
Abstract Incorporating Battery Energy Storage Systems (BESS) into renewable energy
systems offers clear potential benefits, but management approaches that optimally operate …
systems offers clear potential benefits, but management approaches that optimally operate …
Applications of energy storage systems in enhancing energy management and access in microgrids: A review
As the world's population continues to grow and the demand for energy increases, there is
an urgent need for sustainable and efficient energy systems. Renewable energy sources …
an urgent need for sustainable and efficient energy systems. Renewable energy sources …
[HTML][HTML] Online capacity estimation of lithium-ion batteries with deep long short-term memory networks
There is an increasing demand for modern diagnostic systems for batteries under real-world
operation, specifically for the estimation of their state of health, for example, via their …
operation, specifically for the estimation of their state of health, for example, via their …
[HTML][HTML] One-shot battery degradation trajectory prediction with deep learning
The degradation of batteries is complex and dependent on several internal mechanisms.
Variations arising from manufacturing uncertainties and real-world operating conditions …
Variations arising from manufacturing uncertainties and real-world operating conditions …
[HTML][HTML] Data-driven systematic parameter identification of an electrochemical model for lithium-ion batteries with artificial intelligence
Electrochemical models are more and more widely applied in battery diagnostics,
prognostics and fast charging control, considering their high fidelity, high extrapolability and …
prognostics and fast charging control, considering their high fidelity, high extrapolability and …
Early prediction of battery lifetime via a machine learning based framework
Accurately predicting the lifetime of lithium-ion batteries in early cycles is crucial for ensuring
the safety and reliability, and accelerating the battery development cycle. However, most of …
the safety and reliability, and accelerating the battery development cycle. However, most of …
Deep reinforcement learning-based energy management of hybrid battery systems in electric vehicles
In this paper, we propose an energy management strategy based on deep reinforcement
learning for a hybrid battery system in electric vehicles consisting of a high-energy and a …
learning for a hybrid battery system in electric vehicles consisting of a high-energy and a …
Physics-informed neural networks for electrode-level state estimation in lithium-ion batteries
An accurate estimation of the internal states of lithium-ion batteries is critical to improving the
reliability and durability of battery systems. Data-driven methods have exhibited enormous …
reliability and durability of battery systems. Data-driven methods have exhibited enormous …
Toward more realistic microgrid optimization: Experiment and high-efficient model of Li-ion battery degradation under dynamic conditions
Accurate and high-efficient battery life prediction is critical for microgrid optimization and
control problems. Extracted from EV (electric vehicle)-PV (photovoltaics)-battery-based …
control problems. Extracted from EV (electric vehicle)-PV (photovoltaics)-battery-based …
Optimal dispatch approach for second-life batteries considering degradation with online SoH estimation
In light of upcoming electric vehicle (EV) battery retirement issues, second-life batteries
(SLBs) have received increasing attention for their ability to extend the life-span of existing …
(SLBs) have received increasing attention for their ability to extend the life-span of existing …