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Optimization of intake and exhaust system of a gasoline engine based on genetic algorithm
A genetic algorithm with a penalty function is used to optimize the intake and exhaust system of gasoline engine, whose middle range torque was deceased a lot due to the adding of a catalyst. First two GT-power models are built based on experimental results of the gasoline engine with/without catalyst. Then the intake pipe length and diameter and exhaust pipe length and diameter are chosen as the optimal variables. A genetic algorithm (GA) with two constrain conditions is used to search the optimal result, and a penalty function is added to solve the constrain conditions. This optimization process is done by a simulink model coupled with the GT-power models (SCG models). The final optimal result shows that the missing torque of the original engine can be well recovered. The GA model is a good optimization tool for the complex engine problem.
Optimization of intake and exhaust system of a gasoline engine based on genetic algorithm
A genetic algorithm with a penalty function is used to optimize the intake and exhaust system of gasoline engine, whose middle range torque was deceased a lot due to the adding of a catalyst. First two GT-power models are built based on experimental results of the gasoline engine with/without catalyst. Then the intake pipe length and diameter and exhaust pipe length and diameter are chosen as the optimal variables. A genetic algorithm (GA) with two constrain conditions is used to search the optimal result, and a penalty function is added to solve the constrain conditions. This optimization process is done by a simulink model coupled with the GT-power models (SCG models). The final optimal result shows that the missing torque of the original engine can be well recovered. The GA model is a good optimization tool for the complex engine problem.
Optimization of intake and exhaust system of a gasoline engine based on genetic algorithm
Yang Xiaolong, (Autor:in) / Huang Ming, (Autor:in) / Liu Biao, (Autor:in)
01.11.2009
234093 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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