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Chongfeng Wei

Researcher at University of Leeds

Publications -  49
Citations -  1570

Chongfeng Wei is an academic researcher from University of Leeds. The author has contributed to research in topics: Computer science & Engineering. The author has an hindex of 13, co-authored 36 publications receiving 957 citations. Previous affiliations of Chongfeng Wei include Hong Kong Polytechnic University & University of Waterloo.

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A comprehensive review on vibration energy harvesting: Modelling and realization

Abstract: This paper presents a state-of-the-art review on a hot topic in the literature, i.e., vibration based energy harvesting techniques, including theory, modelling methods and the realizations of the piezoelectric, electromagnetic and electrostatic approaches. To minimize the requirement of external power source and maintenance for electric devices such as wireless sensor networks, the energy harvesting technique based on vibrations has been a dynamic field of studying interest over past years. One important limitation of existing energy harvesting techniques is that the power output performance is seriously subject to the resonant frequencies of ambient vibrations, which are often random and broadband. To solve this problem, researchers have concentrated on developing efficient energy harvesters by adopting new materials and optimising the harvesting devices. Particularly, among these approaches, different types of energy harvesters have been designed with consideration of nonlinear characteristics so that the frequency bandwidth for effective energy harvesting of energy harvesters can be broadened. This paper reviews three main and important vibration-to-electricity conversion mechanisms, their design theory or methods and potential applications in the literature. As one of important factors to estimate the power output performance, the energy conversion efficiency of different conversion mechanisms is also summarised. Finally, the challenging issues based on the existing methods and future requirement of energy harvesting are discussed.
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MME-EKF-Based Path-Tracking Control of Autonomous Vehicles Considering Input Saturation

TL;DR: The RBFNN and composite nonlinear feedback (CNF) based ISMC is developed to achieve the yaw stabilization and enhance the transient tracking performance considering the input saturation of the front steering angle and the overall stability is proved with Lyapunov function.
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Differential Steering Based Yaw Stabilization Using ISMC for Independently Actuated Electric Vehicles

TL;DR: An improved disturbance observer based ISMC strategy is designed to cope with the unknown mismatched disturbances, and the composite nonlinear feedback technique is employed to design the nominal part of the controller to restrain overshoots and remove steady-state errors considering the tire force saturations.
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Lane keeping of autonomous vehicles based on differential steering with adaptive multivariable super-twisting control

TL;DR: Results of CarSim-Simulink simulations with the proposed control strategy compared with a tradition sliding mode controller based on a high-fidelity and full-car model have verified the effectiveness and robustness of the proposed controller in the lane keeping control via DDAS with the guaranteed high performance.
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A novel approach to energy harvesting from vehicle suspension system: Half-vehicle model

TL;DR: In this paper, a mathematical model of half vehicle model was developed and different parameters such as magnitude, frequency, vehicle velocity and the relative velocity between the sprung mass and front and rear unsprung masses were included for harmonic based road type.