سال انتشار: ۱۳۹۱

محل انتشار: بیستمین کنفرانس سالانه مهندسی مکانیک

تعداد صفحات: ۴

نویسنده(ها):

Majid Bakhshi – MSc Student, Department of Mechanical Engineering, Urmia University
Shahram Khalilarya – Associate Professor, Department of Mechanical Engineering, Urmia University

چکیده:

This paper studies the combination of artificial neural network (ANN) and genetic algorithm (GA) to optimize the diesel engine efficiency and torque and operating parameters. The objective of the optimization was to find settings of engine that be able to optimize and increase efficiency and torque at the same time. In this paper the multi-layer back propagation algorithm with Levenberg-Marquardt training algorithm was used topredict and model the network -using experimental data of a sample engine -, receiving as inputs the engine operating parameters, and producing as outputs the efficiency and torque. The ANN outputs were then used to evaluate the objective function of the optimization process which was performed with a GA approach. Obtained results showed sensible increases in outputs.