The Optimization of Intake Port using Genetic Algorithm and Artificial Neural Network for Gasoline Engines Tianjin Univ

Format:

Conference/Event

Author/Creator:

Sun, Sun, author.

Contributor:

Cui, Lei

Jia, Ming

Lu, Zhen

Wang, Tianyou

Conference Name:

SAE 2015 World Congress & Exhibition (2015-04-21 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2015

Summary:

AbstractThe flow performance of intake port significantly affects engine output power, fuel economy, and exhaust emissions in gasoline engines. Thus, optimal intake port geometry is desired in gasoline engines. To optimize the flow performance of intake port, a new optimization method combining genetic algorithm (GA) and artificial neural network (ANN) was proposed.First, an automatic system for generating the geometry of the tangential intake port was constructed to create various port geometries through inputting the 18 pre-defined structural parameters.Then, the effects of four critical structural parameters were investigated through numerical simulation. On the basis of the computational results, an ANN was used to model the flow performance of the intake port, and a genetic algorithm was simultaneously employed to optimize the flow performance by optimizing the four important structural parameters.Finally, the optimization results were verified through numerical simulation. The results show that, compared to the original design, the tumble ratio significantly increases (about 6.12%), while flow coefficient remains nearly unchanged in the new design of the intake portrait

Notes:

Vendor supplied data

Publisher Number:

2015-01-1353

Access Restriction:

Restricted for use by site license