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Dive into the research topics where Zhao Kegang is active.

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Featured researches published by Zhao Kegang.


international conference on information science and engineering | 2010

Sensorless speed control of the switched reluctance motor using extended Kalman filter

Li Yu-zhou; Zhao Kegang

It is important to use non position sensor controlling strategy to improve the performance of switched reluctance drive system. A novel method that estimates the speed and rotor of switched reluctance motor using extended Kalman filter is introduced. By the algorithm and method, the non position sensor controlling strategy of switched reluctance motor is realized. The simulated results show that the method has better forecast, emendation, as well as precise track of position and speed of switched reluctance motor. In addition, the method can solve the problem of system parameter variation and system interfere, and measure the effect of observed interfere.


International Journal of Vehicle Design | 2005

Study on a new split type of HEV powertrains

Huang Xiangdong; Zhao Kegang; Luo Yutao; Liu Wenbin

To remedy the imperfection of the existing power-split type of multi-energy powertrain based on a planetary mechanism for HEV (Hybrid Electric Vehicle), and to increase the power transmittability, efficiency and variable speed range of the CVT (Continuously variable transmission) used with it, a new power-split type of HEV powertrain is here put forward and studied. The working principle of this type of mechatronic assembly is analysed in detail and general and key points for its design and realisation are also discussed. Its technical features and applied perspective are thus revealed.


international conference on measuring technology and mechatronics automation | 2011

Adaptive Back-stepping Control of Permanent Magnetic Synchronous Motor Based on Slide Mode Observer

Li Yu-zhou; Zhao Kegang

Permanent-magnet synchronous-motor is a multi-variable, non-linear, strong coupling system that is highly sensitive to the outer interfere and inter perturbation. To improve the system robustness, the adaptive back-stepping control of permanent magnet synchronous motor based on slide mode observer is put forward. Based on the mathematic model of permanent magnet synchronous motor and the theory of slide mode observer, the real-time online estimation of the position angle and speed of rotor is realized, and furthermore the estimation of the position of rotor is revised, so the close loop controlling of motor is conducted. In addition in order to suppress the effect of uncertain factors to the performance of system such as parameter perturbation and load perturbation, the adaptive back-stepping control strategy is used to adaptively adjust states in according to the change of parameters for ensuring the stability and performance of system. The simulation results show the strategy with good dynamic characteristic and robustness.


First International Conference on Transportation Engineering | 2007

REAL-TIME OPTIMIZATION SUPERVISORY CONTROL OF HEV POWERTRAIN

Zhao Kegang; Luo Yutao; Guangdong Key

Considering a charge-sustaining PHEV (Parallel Hybrid Electric Vehicle) as an object, the corresponding mechanical and battery constraint functions are established. For real-time controlling, the global criterion is replaced with a real-time one , and a general scheme of real-time power assigning and speed ratio optimizing are given.Based on the math models related to HEVs powertrain, a MATLAB/Simulink simulation platform was built up to calculate ideal tables of power distribution among powertrain elements and the corresponding gear shifts which will be stored into the HEVs onboard supervisory controller. Validity and real time responsibility of the instantaneous optimization control strategy are proved by simulations with typical driving cycles, revealing worthy of the strategy.


international conference on computer science and information technology | 2010

Expert system for bus styling evaluation based on neural network and feature extraction

Li Xiaofu; Zhao Kegang; Yang Yong

This paper firstly examines the traditional vehicle styling evaluation methods and issues, and then presents a new approach which uses ANN (artificial neural network) to build an expert system for bus styling evaluation. It describes the key technical issues of quasi-three-dimensional bus styling evaluation expert system from data collection, graphical pre-processing, graphics feature extraction, knowledge base construction to neural network model design and training. On this basis, authors have developed a bus styling evaluation expert system software, and satisfactory results are obtained in actual bus styling retrofit project.


Archive | 2004

Series-parallel type power assembly of mixed power electric vehicle

Huang Xiangdong; Zhao Kegang; Yuan Zhongrong


Archive | 2017

Hybrid power system and control method thereof

Zhao Kegang; Huang Xiangdong; Yang Yong; Li Gang; Liang Zhihao


Proceedings of the Csee | 2005

VARIABLE CURRENT DISCHARGE CHARACTERISTICS AND SOC ESTIMATION OF EV/HEV BATTERY

Zhao Kegang


SAE 2010 World Congress & Exhibition | 2010

Investigation of Vehicle Handling and Ride Comfort Oriented Cooperative Optimization

Yang Rongshan; Xiangdong Huang; Zhao Kegang


Journal of Mechanical Engineering | 2016

Optimal Control for Gear Shift of a Pure Electric Vehicle's 2-speed Transmission with Single Friction Clutch

Ye Jie; Huang Xiangdong; Zhao Kegang; Liu Yanwei; Huang Xiexin

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Huang Xiangdong

South China University of Technology

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Zhou Sijia

South China University of Technology

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Luo Yutao

South China University of Technology

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Li Gang

South China University of Technology

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Li Yu-zhou

Guangdong University of Technology

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Hu Hongfei

South China University of Technology

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Li Xiaofu

South China University of Technology

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Liu Wenbin

South China University of Technology

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Tan Xiamei

South China University of Technology

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