Application of Genetic Algorithm for the Calibration of the Kinetic Scheme of a Diesel Oxidation Catalyst Model

The concerns for global warming have pushed very harsh regulations on conventional propulsion systems based on the use of fossil fuels. New technologies are being promoted, but their current technological status needs further research and development to become a competitive substitute for the ever-present internal combustion engine. Transition technologies like hybrid-electric platforms are the preferred solution, but their dependence on the internal combustion engine demands continued developing and improving this technology. Advanced combustion modes like dual-mode dual-fuel combustion are attractive solutions with room for improvement. This work evaluates the specifics of the hydrocarbon composition emitted during the operation of a medium-duty dual-mode dual-fuel engine, analyzing the specific requirements of a diesel oxidation catalyst for this application. Also, the modeling approach of this after-treatment component is revised for this type of application, proposing a new approach and evaluating numerically the performance of a conventional diesel oxidation catalyst. The results show that the new modeling approach brings better accuracy when modeling the transient operation of the engine.

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Application of Genetic Algorithm for the Calibration of the Kinetic Scheme of a Diesel Oxidation Catalyst Model

Cited by 2 publications

References 16 publications

Performance evaluation of neural networks in modeling exhaust gas aftertreatment reactors

Performance evaluation of neural networks in modeling exhaust gas aftertreatment reactors

Engine-out hydrocarbon speciation and DOC reaction modeling for dual-fuel combustion concept

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