MODELING AND SIMULATION OF COMBUSTION IN SI ENGINES VIA NEURAL NETWORKS AND INVESTIGATION OF CALIBRATION AND DATA ACQUISITION IN THE GT-POWER SOFTWARE

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SHAMEKHI AMIR MOHAMMAD; SHAMEKHI AMIR HOSEIN

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Journal: Modares Mechanical Engineering Year:2015 | Volume:14 | Issue:13 Page(s): 233-244

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Title

MODELING AND SIMULATION OF COMBUSTION IN SI ENGINES VIA NEURAL NETWORKS AND INVESTIGATION OF CALIBRATION AND DATA ACQUISITION IN THE GT-POWER SOFTWARE

Author(s)

SHAMEKHI AMIR MOHAMMAD | SHAMEKHI AMIR HOSEIN | Issue Writer Certificate

Keywords

SPARK IGNITION ENGINESQ2

CONTROL-ORIENTED MODELINGQ2

GT-POWER SOFTWAREQ2

ARTIFICIAL NEURAL NETWORKSQ3

Abstract

A prerequisite in the majority of control processes is modeling. The model used to design a controller must be both accurate and real-time. Utilizing prevalent approaches of modeling, namely modeling based on (numerically) solving the equations governing the fluid in the combustion chamber, is too time - consuming and not suitable for control purpose. This paper aims to model combustion in an SI engine by means of neural networks and present an accurate and fast-response model for combustion. Obviously, any training procedure of neural networks involves empirical data acquisition. On the other hand, engine testing is highly expensive, and testing data tables available (in industry) is not sufficient to train neural networks. In this paper, first with the aid of CFD software, a one-dimensional model of an engine is constructed, and then calibrated using the factual experimental data at hand. Afterwards, acquiring data required is performed via the validated CFD model. As a matter of fact, because of the lack of access to necessary experimental coefficients, calibration is an extremely complicated and time-consuming process. An attempt is made to accomplish and spell out the calibration of the engine model in the GT-POWER SOFTWARE, in a scientific practice. After a brief survey on the methods employed in designing the neural networks, modeling of the combustion chamber will be stated. Eventually, the response of the constructed NN model will be compared to the results gained from the GT Power software, and the great accuracy of the NN model will be shown.

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APA: Copy

SHAMEKHI, AMIR MOHAMMAD, & SHAMEKHI, AMIR HOSEIN. (2015). MODELING AND SIMULATION OF COMBUSTION IN SI ENGINES VIA NEURAL NETWORKS AND INVESTIGATION OF CALIBRATION AND DATA ACQUISITION IN THE GT-POWER SOFTWARE. MODARES MECHANICAL ENGINEERING, 14(13), 233-244. SID. https://sid.ir/paper/179723/en

Vancouver: Copy

SHAMEKHI AMIR MOHAMMAD, SHAMEKHI AMIR HOSEIN. MODELING AND SIMULATION OF COMBUSTION IN SI ENGINES VIA NEURAL NETWORKS AND INVESTIGATION OF CALIBRATION AND DATA ACQUISITION IN THE GT-POWER SOFTWARE. MODARES MECHANICAL ENGINEERING[Internet]. 2015;14(13):233-244. Available from: https://sid.ir/paper/179723/en

IEEE: Copy

AMIR MOHAMMAD SHAMEKHI, and AMIR HOSEIN SHAMEKHI, “MODELING AND SIMULATION OF COMBUSTION IN SI ENGINES VIA NEURAL NETWORKS AND INVESTIGATION OF CALIBRATION AND DATA ACQUISITION IN THE GT-POWER SOFTWARE,” MODARES MECHANICAL ENGINEERING, vol. 14, no. 13, pp. 233–244, 2015, [Online]. Available: https://sid.ir/paper/179723/en

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