Feed-Forward Air-Fuel Ratio Control during Transient Operation of an Alternative Fueled Engine

With the increasing government regulations for higher vehicle fuel economy and lower tailpipe emissions, today’s automotive engineers are pushed to develop advanced vehicles. Further, due to the high prices of oil, the consumer market is demanding for more fuel efficient vehicles. To adapt to the increasing demands, automotive manufacturers have been investing in the research of advanced vehicle technologies. The work described in this thesis details the development of a methodology to improve the feed-forward air-fuel ratio control during transient operation of an alternative fueled engine. Due to transport delays between the induction of the air-fuel mixture into the cylinder and the reading of the combustion exhaust gases from the oxygen sensor, conventional feedback control cannot be accurately used in transient operation. Since the engine used in this thesis is port-fuel injected, the fuel injection is made a discrete amount of time before the intake valve opening. This gives the fuel time to vaporize in the intake runner before being inducted. Therefore, in order to achieve stoichiometric combustion, the amount of inducted air will have to be determined a discrete amount of time into the future.This work outlines the development of a control algorithm that improves the transient air-fuel ratio control by predicting the intake manifold air pressure forward in time. Using model-based calibration techniques and engine dynamometer data, an intake manifold model was created. Coupling this model with a Forward Euler approximation, a predictive intake manifold pressure algorithm was developed. Adaptive models were implemented into the control algorithm to account for day-to-day variations in engine operation as well as calibration errors in the intake manifold model. The algorithm was verified in software validation with a mean value engine model and hardware validation in the engine dynamometer test cell. With the implementation of the predictive control algorithm, there was a vast improvement in air-fuel ratio control performance over the engine’s previous control strategy. Oxygen sensor results showed a significant reduction in deviations from stoichiometric combustion, allowing the three-way catalyst to operate in its most efficient range. The research detailed in this thesis shows the effectiveness of using a model-based approach to air-fuel ratio control and the importance of adaptive algorithms for day-to-day changes in engine operation.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Mechanical Engineering

Grantor dc:publisher

The Ohio State University

Year dc:date

2013

Author dc:creator

• Garcia, Andrew Michael

Contributors dc:contributor

• Midlam-Mohler, Shawn

• Mechanical Engineering
• Automotive Engineering
• air-fuel ratio control
• tailpipe emissions reduction
• feed-forward air-fuel ratio control
• model-based calibration
• intake manifold modeling
• Forward Euler approximation

Statement dc:rights

• unrestricted
• This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.

Language dc:language

English

Repository record dc:identifier

http://rave.ohiolink.edu/etdc/view?acc_num=osu1366034780

OAI identifier oai:identifier

oai:etd.ohiolink.edu:osu1366034780