What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Electrical engineering
Huei Peng mostly deals with Control theory, Automotive engineering, Control engineering, Simulation and Optimal control.
In the field of Control theory, his study on Adaptive control, Vehicle dynamics and Feed forward overlaps with subjects such as Mathematical model.
The Automotive engineering study combines topics in areas such as Powertrain, Hybrid system, Power control and Automotive industry.
His Control engineering research integrates issues from Electricity generation, Power management, Stochastic programming and Energy management.
The concepts of his Power management study are interwoven with issues in Truck and Hybrid vehicle.
His Optimal control study also includes fields such as
- Dynamic programming which intersects with area such as Schedule,
- Corporate Average Fuel Economy and Petrol engine most often made with reference to Supervisory control.
His most cited work include:
- Power management strategy for a parallel hybrid electric truck (1005 citations)
- A comparative study of equivalent circuit models for Li-ion batteries (953 citations)
- Automated vehicle control developments in the PATH program (608 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Automotive engineering, Control theory, Control engineering, Simulation and Vehicle dynamics.
Huei Peng has researched Automotive engineering in several fields, including Powertrain and Dynamic programming.
Huei Peng interconnects Electric vehicle, Optimal design, Energy management and Benchmark in the investigation of issues within Powertrain.
His works in Control theory, Optimal control, Feed forward, Control system and Adaptive control are all subjects of inquiry into Control theory.
He has included themes like Control, Cruise control, Hybrid vehicle, Power management and Automotive industry in his Control engineering study.
His Simulation study frequently draws connections between adjacent fields such as Active safety.
He most often published in these fields:
- Automotive engineering (32.32%)
- Control theory (27.40%)
- Control engineering (25.29%)
What were the highlights of his more recent work (between 2015-2021)?
- Automotive engineering (32.32%)
- Powertrain (11.48%)
- Control theory (27.40%)
In recent papers he was focusing on the following fields of study:
His main research concerns Automotive engineering, Powertrain, Control theory, Fuel efficiency and Vehicle dynamics.
He studies Clutch which is a part of Automotive engineering.
The various areas that he examines in his Control theory study include Tracking and Model predictive control.
His research in Vehicle dynamics intersects with topics in Frequency domain, Brake, Optimal control and Feed forward.
His Control theory study results in a more complete grasp of Control engineering.
His work in Control engineering addresses issues such as Collision avoidance, which are connected to fields such as Obstacle avoidance.
Between 2015 and 2021, his most popular works were:
- Accelerated Evaluation of Automated Vehicles Safety in Lane-Change Scenarios Based on Importance Sampling Techniques (132 citations)
- State-of-health monitoring of lithium-ion battery modules and packs via incremental capacity peak tracking (109 citations)
- State-of-health monitoring of lithium-ion battery modules and packs via incremental capacity peak tracking (109 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Electrical engineering
- Control theory
His primary areas of investigation include Powertrain, Automotive engineering, Simulation, Fuel efficiency and Control theory.
His work deals with themes such as Efficient energy use, Clutch, Optimal design, Markov chain and Driving cycle, which intersect with Powertrain.
In his study, which falls under the umbrella issue of Automotive engineering, Skid, Robot, Motion planning and Power is strongly linked to Propulsion.
His Simulation study also includes
- Mixture model, which have a strong connection to Control system,
- Data modeling, which have a strong connection to Crash,
- Importance sampling and related Active safety.
His Fuel efficiency research is multidisciplinary, incorporating elements of Routing, Optimal control, Global optimal, Vehicle dynamics and Rule-based system.
His Control theory study incorporates themes from Scheduling, Dynamic programming and Model predictive control.
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