DocumentCode :
1862556
Title :
Research of an Adaptive Particle Swarm Optimization on Engine Optimization Problem
Author :
Dongmei Wu ; Hao Gao
Author_Institution :
Coll. of Autom., Nanjing Univ. of Posts & Telecommun., Nanjing, China
Volume :
1
fYear :
2013
fDate :
26-27 Aug. 2013
Firstpage :
42
Lastpage :
45
Abstract :
This paper proposes a new particle swarm optimization (PSO) algorithm with an adaptive weight. Benchmark tests of the algorithm is described. Compared with standard PSO, it shows better convergence as well as ability of escaping from local optima. Diesel engines must meet the increasing demands for higher efficiency, cleaner exhaust gases and better drivability. Model-Based control is one of effective solutions to satisfy these demands. In this paper, a model-Based control system Based on the proposed algorithm is designed for the objective of raising fuel efficiency and reducing environmental-burden. A set of simulation results have demonstrated potential of such advanced engine control logic.
Keywords :
benchmark testing; diesel engines; fuel economy; particle swarm optimisation; adaptive particle swarm optimization algorithm; adaptive weight; advanced engine control logic; benchmark tests; diesel engines; engine optimization problem; environmental-burden reduction; exhaust gases; fuel efficiency; model-based control system; Adaptation models; Algorithm design and analysis; Convergence; Engines; Optimization; Particle swarm optimization; Standards; Adaptive weight; PSO; engine optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2013 5th International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-0-7695-5011-4
Type :
conf
DOI :
10.1109/IHMSC.2013.17
Filename :
6643829
Link To Document :
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