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Hadi Taghavifar

Hadi Taghavifar

Academic rank: Assistant Professor
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Education: PhD.
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Faculty: Technical Engineering
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Research

Title
Multi-objective optimisation of injector and diesel engine by genetic algorithm: Nu-SVR modelling
Type
JournalPaper
Keywords
diesel engine; diesel injector; Nu-SVR; MOGA; multi-objective genetic algorithm; Pareto front
Year
2020
Journal International Journal of Heavy Vehicle Systems
DOI
Researchers Hadi Taghavifar

Abstract

The current study deals with application of evolutionary multiobjective genetic algorithm (MOGA) in a 1.8 L Ford diesel engine to enhance the power, fuel consumption, and air-fuel uniformity. To do so, four design parameters of engine geometry and injector parameters are defined and three sub-objectives are considered to get either maximised or minimised. On the sub-objectives, constraints are imposed to introduce the feasible solutions. The best solution is obtained at RunID66 from 70 design points. The results showed that increasing bowl radius after a certain point is not useful for enhancement of the mixture homogeneity. In the second part of the study, support vector regression (SVR) technique is applied on the input and output data to make a model to predict the engine power.