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UM E-Theses Collection (澳門大學電子學位論文庫)

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Title

Design and experimental evaluation of predictive engine air-ratio control using relevance vector machine

English Abstract

Air-ratio relates closely to pollution reduction and fuel efficiency improvement among all of the engine control variables. Maintaining the air-ratio to be the stoichiometric value can ensure the maximum efficiency of the three-way catalytic converter so that minimizing the engine emission. The thesis presents a new model predictive control (MPC) algorithm for air-ratio regulation based on relevance vector machine (RMV). The control algorithm has been implemented on a real car to test. Experimental results show that the control performance of the relevance vector machine model predictive controller (RVMMPC) is superior to typical neural network MPC, decremental least-squares support vector machine MPC and conventional proportional-integral (PI) controller in production cars. Therefore, the RVMMPC is a potential scheme to replace PI controller in the automotive ECU for engine air-ratio control.

Issue date

2009

Author

Wong, Hang Cheong

Faculty

Faculty of Science and Technology

Degree

M.Sc.

Subject

Automobiles -- Motors -- Computer control systems

Automobiles -- Motors -- Control systems

Pedictive control

Electromechanical Engineering -- Department of Electromechanical Engineering

Supervisor

Wong, Pak Kin

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Location
1/F Zone C
Library URL
991005551799706306