Battery and energy management system for vanadium redox flow battery: A critical review and recommendations
As one of the most promising large-scale energy storage technologies, vanadium redox flow
battery (VRFB) has been installed globally and integrated with microgrids (MGs), renewable …
battery (VRFB) has been installed globally and integrated with microgrids (MGs), renewable …
[HTML][HTML] Review of “grey box” lifetime modeling for lithium-ion battery: Combining physics and data-driven methods
Lithium-ion batteries are a popular choice for a wide range of energy storage system
applications. The current motivation to improve the robustness of lithium-ion battery …
applications. The current motivation to improve the robustness of lithium-ion battery …
Modelling and estimation of vanadium redox flow batteries: A review
Redox flow batteries are one of the most promising technologies for large-scale energy
storage, especially in applications based on renewable energies. In this context …
storage, especially in applications based on renewable energies. In this context …
Thermodynamically consistent machine-learned internal state variable approach for data-driven modeling of path-dependent materials
Abstract Characterization and modeling of path-dependent behaviors of complex materials
by phenomenological models remains challenging due to difficulties in formulating …
by phenomenological models remains challenging due to difficulties in formulating …
[HTML][HTML] A novel U-Net based data-driven vanadium redox flow battery modelling approach
This research proposes a highly accurate data-driven vanadium redox flow battery (VRB)
modelling approach for power engineering applications. The proposed approach addresses …
modelling approach for power engineering applications. The proposed approach addresses …
A novel vanadium redox flow battery modelling method using honey badger optimization assisted CNN-BiLSTM
This research proposes a highly accurate data-driven vanadium redox flow battery (VRB)
modelling approach for power engineering applications. The proposed approach addresses …
modelling approach for power engineering applications. The proposed approach addresses …
A feature-encoded physics-informed parameter identification neural network for musculoskeletal systems
Identification of muscle-tendon force generation properties and muscle activities from
physiological measurements, eg, motion data and raw surface electromyography (sEMG) …
physiological measurements, eg, motion data and raw surface electromyography (sEMG) …
[HTML][HTML] Innovations in stack design and optimization strategies for redox flow batteries in large-scale energy storage
Redox flow batteries are promising electrochemical systems for energy storage owing to
their inherent safety, long cycle life, and the distinct scalability of power and capacity. This …
their inherent safety, long cycle life, and the distinct scalability of power and capacity. This …
PINN surrogate of Li-ion battery models for parameter inference, Part I: Implementation and multi-fidelity hierarchies for the single-particle model
To plan and optimize energy storage demands that account for Li-ion battery aging
dynamics, techniques need to be developed to diagnose battery internal states accurately …
dynamics, techniques need to be developed to diagnose battery internal states accurately …
Optimizing of working conditions of vanadium redox flow battery based on artificial neural network and genetic algorithms
The integration of electrode compression in a vanadium redox flow battery (VRFB) with
optimized operating conditions is essential for achieving the maximum net discharge power …
optimized operating conditions is essential for achieving the maximum net discharge power …