A comprehensive review of digital twin—part 1: modeling and twinning enabling technologies
As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented
attention because of its promise to further optimize process design, quality control, health …
attention because of its promise to further optimize process design, quality control, health …
A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems
With the rapid development of new energy electric vehicles and smart grids, the demand for
batteries is increasing. The battery management system (BMS) plays a crucial role in the …
batteries is increasing. The battery management system (BMS) plays a crucial role in the …
A review on state of health estimations and remaining useful life prognostics of lithium-ion batteries
Lithium-ion batteries have been generally used in industrial applications. In order to ensure
the safety of the power system and reduce the operation cost, it is particularly important to …
the safety of the power system and reduce the operation cost, it is particularly important to …
State estimation for advanced battery management: Key challenges and future trends
Batteries are presently pervasive in portable electronics, electrified vehicles, and renewable
energy storage. These indispensable engineering applications are all safety-critical and …
energy storage. These indispensable engineering applications are all safety-critical and …
A state-of-charge estimation method of the power lithium-ion battery in complex conditions based on adaptive square root extended Kalman filter
The control strategy of electric vehicles mainly depends on the power battery state-of-charge
estimation. One of the most important issues is the power lithium-ion battery state-of-charge …
estimation. One of the most important issues is the power lithium-ion battery state-of-charge …
Towards a smarter battery management system: A critical review on battery state of health monitoring methods
To ensure the driving safety and avoid potential failures for electric vehicles, evaluating the
health state of the battery properly is of significant importance. This study aims to serve as a …
health state of the battery properly is of significant importance. This study aims to serve as a …
Deep convolutional neural networks with ensemble learning and transfer learning for capacity estimation of lithium-ion batteries
It is often difficult for a machine learning model trained based on a small size of
charge/discharge cycling data to produce satisfactory accuracy in the capacity estimation of …
charge/discharge cycling data to produce satisfactory accuracy in the capacity estimation of …
State-of-charge estimation of Li-ion batteries using deep neural networks: A machine learning approach
Abstract Accurate State of Charge (SOC) estimation is crucial to ensure the safe and reliable
operation of Li-ion batteries, which are increasingly being used in Electric Vehicles (EV) …
operation of Li-ion batteries, which are increasingly being used in Electric Vehicles (EV) …
A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations
Due to increasing concerns about global warming, greenhouse gas emissions, and the
depletion of fossil fuels, the electric vehicles (EVs) receive massive popularity due to their …
depletion of fossil fuels, the electric vehicles (EVs) receive massive popularity due to their …
A novel Gaussian process regression model for state-of-health estimation of lithium-ion battery using charging curve
The state-of-health (SOH) estimation is always a crucial issue for lithium-ion batteries. In
order to provide an accurate and reliable SOH estimation, a novel Gaussian process …
order to provide an accurate and reliable SOH estimation, a novel Gaussian process …