What is he best known for?
The fields of study he is best known for:
- Electrical engineering
- Artificial intelligence
- Machine learning
Energy management, Battery, Automotive engineering, Electric vehicle and State of charge are his primary areas of study.
His Energy management research integrates issues from Model predictive control, Smart grid, Renewable energy and Energy storage.
His research in Battery tackles topics such as Simulation which are related to areas like Electricity.
His Automotive engineering research is multidisciplinary, incorporating perspectives in Powertrain, Power management, Efficient energy use and Hybrid electric bus.
His study in State of charge is interdisciplinary in nature, drawing from both State of health and Control theory.
Xiaosong Hu interconnects Dynamic programming, Electronic engineering, Lithium-ion battery and Reinforcement learning in the investigation of issues within Control theory.
His most cited work include:
- A comparative study of equivalent circuit models for Li-ion batteries (953 citations)
- A comparative study of equivalent circuit models for Li-ion batteries (953 citations)
- Adaptive unscented Kalman filtering for state of charge estimation of a lithium-ion battery for electric vehicles (362 citations)
What are the main themes of his work throughout his whole career to date?
Xiaosong Hu mainly investigates Battery, Energy management, Automotive engineering, Control theory and State of charge.
The various areas that Xiaosong Hu examines in his Battery study include Reliability engineering and Voltage.
The Energy management study combines topics in areas such as Power, Dynamic programming, Efficient energy use and Model predictive control.
His Automotive engineering research is multidisciplinary, incorporating elements of Powertrain, Electric vehicle, Power management and Energy storage.
His studies deal with areas such as Control engineering, Hybrid electric bus and Optimal control as well as Powertrain.
His study focuses on the intersection of State of charge and fields such as Electronic engineering with connections in the field of Electrical impedance.
He most often published in these fields:
- Battery (42.49%)
- Energy management (37.31%)
- Automotive engineering (32.12%)
What were the highlights of his more recent work (between 2019-2021)?
- Battery (42.49%)
- Automotive engineering (32.12%)
- Energy management (37.31%)
In recent papers he was focusing on the following fields of study:
Xiaosong Hu focuses on Battery, Automotive engineering, Energy management, State of charge and Reliability engineering.
His Battery research includes themes of Kriging and Lithium.
His work carried out in the field of Automotive engineering brings together such families of science as Electric vehicle, Particle swarm optimization and Energy storage.
His research in Energy management intersects with topics in Power, Model predictive control, Dynamic programming and Powertrain, Torque.
His biological study spans a wide range of topics, including Kalman filter, Thermal conductivity, Robustness and Voltage.
His Robustness research includes elements of Control engineering, Multi-agent system and Fuel cells.
Between 2019 and 2021, his most popular works were:
- Cost-Optimal Energy Management of Hybrid Electric Vehicles Using Fuel Cell/Battery Health-Aware Predictive Control (72 citations)
- Battery Lifetime Prognostics (67 citations)
- Gaussian Process Regression With Automatic Relevance Determination Kernel for Calendar Aging Prediction of Lithium-Ion Batteries (64 citations)
In his most recent research, the most cited papers focused on:
- Electrical engineering
- Artificial intelligence
- Control theory
His primary areas of study are Battery, State of charge, Reliability engineering, Lithium-ion battery and Automotive engineering.
Battery is a subfield of Power that Xiaosong Hu tackles.
His State of charge study incorporates themes from Battery pack, Thermal, Filter and Kriging.
He combines subjects such as Battery degradation, Anode, Smart grid and Energy storage with his study of Reliability engineering.
Fuel cells is closely connected to Energy management in his research, which is encompassed under the umbrella topic of Automotive engineering.
Xiaosong Hu has included themes like Control theory and Voltage in his State of health study.
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