A novel particle swarm and genetic algorithm hybrid method for improved heuristic optimization of diesel engine performance

dc.contributor.advisor Song-Charng Kong
dc.contributor.author Bertram, Aaron
dc.contributor.department Mechanical Engineering
dc.date 2018-07-22T00:11:22.000
dc.date.accessioned 2020-06-30T02:53:55Z
dc.date.available 2020-06-30T02:53:55Z
dc.date.copyright Wed Jan 01 00:00:00 UTC 2014
dc.date.embargo 2015-07-30
dc.date.issued 2014-01-01
dc.description.abstract <p>This study explores a novel application of the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) heuristic methods in a hybrid construction on a 4 cylinder medium-duty diesel engine at part-load conditions. The application of the hybrid PSO-GA approach is compared with a basic PSO in the optimization of the control parameters of a diesel engine utilizing high EGR capability, modestly high fuel pressure capability, and a two-injection fuel strategy.</p> <p>The results indicate that the application of the GA to the basic PSO method improved the search breadth and convergence rate when compared to the basic PSO method alone. The novel approach of applying the GA to the fuel schedule is found to be worthy of further investigation. Applying the GA to specific parameters as way to improve optimizations on was effective in reducing the iterations and time taken to achieve satisfactory objective values. The hybrid method showed up to a 49% improvement in objective value over the basic PSO with less operational time in testing.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/etd/14036/
dc.identifier.articleid 5043
dc.identifier.contextkey 6199769
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath etd/14036
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/28223
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/etd/14036/Bertram_iastate_0097M_14454.pdf|||Fri Jan 14 20:12:34 UTC 2022
dc.subject.disciplines Mechanical Engineering
dc.subject.keywords Exhaust Emissions
dc.subject.keywords Heuristics
dc.subject.keywords Internal Combustion
dc.subject.keywords Optimization
dc.title A novel particle swarm and genetic algorithm hybrid method for improved heuristic optimization of diesel engine performance
dc.type article
dc.type.genre thesis
dspace.entity.type Publication
relation.isOrgUnitOfPublication 6d38ab0f-8cc2-4ad3-90b1-67a60c5a6f59
thesis.degree.level thesis
thesis.degree.name Master of Science
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