What is he best known for?
The fields of study he is best known for:
- Control theory
- Electrical engineering
- Artificial intelligence
Yujie Wang focuses on Battery, Control theory, Electronic engineering, State of charge and Robustness.
His work on Lithium-ion battery and State of health as part of general Battery study is frequently connected to Degradation and Monte Carlo method, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His work deals with themes such as Control engineering, Battery terminal and Voltage, which intersect with Control theory.
His Electronic engineering research integrates issues from Resource, Current noise, Estimation and Model switching.
His State of charge study incorporates themes from Filter and Extended Kalman filter.
The various areas that Yujie Wang examines in his Robustness study include Algorithm, Available energy, Dynamic demand and Energy storage.
His most cited work include:
- A method for state-of-charge estimation of LiFePO4 batteries at dynamic currents and temperatures using particle filter (140 citations)
- A method for joint estimation of state-of-charge and available energy of LiFePO 4 batteries (131 citations)
- A novel Gaussian process regression model for state-of-health estimation of lithium-ion battery using charging curve (117 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Battery, Control theory, Voltage, Automotive engineering and Lithium-ion battery.
His Battery research includes elements of Electric vehicle, Computer data storage and Equivalent circuit.
His Control theory research incorporates elements of State of charge and Lithium iron phosphate.
His study in State of charge is interdisciplinary in nature, drawing from both Electronic engineering and Extended Kalman filter.
Yujie Wang combines subjects such as Control engineering and Noise with his study of Voltage.
He has included themes like Driving cycle, Energy management and Energy storage in his Automotive engineering study.
He most often published in these fields:
- Battery (66.67%)
- Control theory (41.67%)
- Voltage (35.00%)
What were the highlights of his more recent work (between 2020-2021)?
- Battery (66.67%)
- Thermoelectric effect (3.33%)
- Materials science (10.00%)
In recent papers he was focusing on the following fields of study:
Yujie Wang mainly investigates Battery, Thermoelectric effect, Materials science, Control theory and Energy management.
Battery is often connected to Voltage in his work.
A majority of his Thermoelectric effect research is a blend of other scientific areas, such as Impulse, Model parameter, Particle model, Polarization and Concentration polarization.
Stress factor and Work are fields of study that intersect with his Materials science study.
His Energy management research includes themes of Multi-objective optimization, Random forest, Support vector machine and Computer data storage.
Between 2020 and 2021, his most popular works were:
- An improved single particle model for lithium-ion batteries based on main stress factor compensation (2 citations)
- Capacity attenuation mechanism modeling and health assessment of lithium-ion batteries (1 citations)
- Sizing Optimization and Energy Management Strategy for Hybrid Energy Storage System Using Multi-objective Optimization and Random Forests (0 citations)
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