NDLI: Predictive control for air fuel ratio based on adaptive expand particle swarm optimization

Content Provider	IEEE Xplore Digital Library
Author	Zhi-xiang Hou Yi-hu Wu
Copyright Year	2008
Description	Author affiliation: Changsha Univ. of Sci. & Technol., Changsha (Zhi-xiang Hou; Yi-hu Wu)
Abstract	Because the oxygen sensor is installed into the vent-pipe of gasoline engine, the air fuel ratio signal of gasoline engine exists transmission delay, which affects the control accuracy of air fuel ratio if using directive air fuel ratio sensor signal. To overcome air fuel ratio transmission delay affection, a new air fuel ratio predictive control method was provided using adaptive expanded particle optimization in this paper. Particle is refreshed using individual and local extremum in the basic PSO algorithm. To improve the global convergence, particle is refreshed by multi-particle strategy; at the same time, parameter $c_{0}$ is adaptive adjusted for fast the convergence of PSO algorithm. Applying adaptive expand PSO algorithm optimize the control serial of air fuel ratio in the finite time field, and control system stability proof is presented. The simulation was accomplished using experiment data of HQ495 gasoline engine, and the results show that the predictive control method has better performance and the air fuel ratio error is below 1% if slower throttle change, and the air fuel ratio error is below 2% if faster throttle change during transient condition, which will help to improve the emission of gasoline engine.
Starting Page	705
Ending Page	709
File Size	243105
Page Count	5
File Format	PDF
ISBN	9781424421138
DOI	10.1109/WCICA.2008.4593008
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuels Predictive control Engines Artificial neural networks Particle swarm optimization Atmospheric modeling Petroleum stability air fuel ratio predictive control neural networks particle swarm optimization
Content Type	Text
Resource Type	Article

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