Feed-Forward Air-Fuel Ratio Control During Transient Operation of an Alternative Fueled Engine
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Feed-Forward Air-Fuel Ratio Control during Transient Operation of an Alternative Fueled Engine A Thesis Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University By Andrew Michael Garcia, B.S. Graduate Program in Mechanical Engineering The Ohio State University 2013 Master's Examination Committee: Dr. Shawn Midlam-Mohler, Advisor Dr. Giorgio Rizzoni c Copyright by Andrew Michael Garcia 2013 Abstract With the increasing government regulations for higher vehicle fuel economy and lower tailpipe emissions, today's automotive engineers are pushed to develop advanced vehicle architectures. 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 method- ology 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 command 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 tran- sient air-fuel ratio control by predicting the intake manifold air pressure forward in ii time. Using model-based calibration techniques and engine dynamometer data, an in- take manifold model was created. Coupling this model with a Forward Euler approx- imation, a predictive intake manifold pressure algorithm was developed. Adaptive models were implemented into the control algorithm to account for day-to-day vari- ations 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 con- trol 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. iii This thesis is dedicated to my parents for their endless love, patience, and support. iv Acknowledgments I would like to thank the Center for Automotive Research for providing access to an unparalleled faculty and facilities to support my research. I would especially like to thank my advisor, Dr. Shawn Midlam-Mohler for his guidance and support throughout my graduate experience. His never-ending enthusiasm and dedication toward teaching has been paramount to success in my research. I would also like to thank Dr. Giorgio Rizzoni for his invaluable advice and support for the EcoCAR 2 program. I would like to thank my fellow graduate students, whom are always willing to share their knowledge and assistance. I would also like to thank the entire EcoCAR 2 team, their efforts in the de- sign, build, and validation of our team's parallel-series plug-in hybrid electric vehicle (PHEV) has been nothing short of inspiring. I would especially like to thank my fellow team leaders Katherine Bovee, Jason Ward, Matthew Yard, Matthew Organis- cak, Eric Gallo, Amanda Hyde, and David Walters for their knowledge, enthusiasm, and support. Finally, I would like to thank the U.S. DOE Graduate Automotive Technology Education (GATE) Center of Excellence for providing the funds and resources for the research in this thesis. v Vita July 6, 1989 . Born - Cleveland, Ohio December, 2011 . B.S. Mechanical Engineering, The Ohio State University December, 2011 . Graduate Research Associate, Department of Mechanical and Aerospace Engineering, The Ohio State University Publications Research Publications K. Bovee, A. Hyde, M. Yard, T. Trippel, M. Organiscak, A. Garcia, E. Gallo, M. Hornak, A. Palmer, J. Hendricks, S. Midlam-Mohler and G. Rizzoni \Design of a Parallel-Series PHEV for the EcoCAR 2 Competition". SAE, 2012-01-1762. Fields of Study Major Field: Mechanical Engineering vi Table of Contents Page Abstract....................................... ii Dedication...................................... iv Acknowledgments..................................v Vita......................................... vi List of Tables.................................... ix List of Figures................................... xi Nomenclature.................................... xv 1. Introduction..................................1 1.1 Motivation...............................1 1.2 EcoCAR 2 Competition........................2 1.2.1 Ohio State University EcoCAR 2 Vehicle Architecture...3 1.3 Thesis Overview............................4 2. Literature Review...............................7 2.1 Introduction..............................7 2.2 Air Dynamics..............................7 2.2.1 Throttle Modeling.......................9 2.2.2 Volumetric Efficiency...................... 12 2.2.3 Intake Manifold Modeling................... 15 2.2.4 Air-Fuel Ratio Control..................... 22 2.3 Honda R18A3 Engine......................... 30 2.4 Tailpipe Emissions........................... 33 vii 3. Experimental Description.......................... 36 3.1 Engine Instrumentation........................ 36 3.2 Data Acquisition System........................ 37 3.3 GM LE5 Mean Value Engine Model................. 40 4. Control Algorithm Development....................... 42 4.1 Introduction.............................. 42 4.2 Control Algorithm Description.................... 42 4.3 Summary................................ 47 5. Intake Manifold Modeling.......................... 50 5.1 Introduction.............................. 50 5.2 Throttle Model............................. 50 5.3 Volumetric Efficiency Model...................... 57 5.4 Intake Manifold Pressure Model.................... 61 5.5 Summary................................ 64 6. Control Algorithm Validation........................ 66 6.1 Introduction.............................. 66 6.2 Software Validation........................... 66 6.3 Hardware Validation.......................... 76 6.3.1 Recalibrating Ve Map..................... 78 6.3.2 Implementation of Adaptive Control Strategies....... 83 6.3.3 AFR Results.......................... 101 6.4 Summary................................ 115 7. Conclusions and Future Work........................ 117 7.1 Conclusions............................... 117 7.2 Future Work.............................. 118 Bibliography.................................... 120 Appendices 122 A. Intake Manifold Model Subsystems..................... 122 viii B. Adaptive Volumetric Efficiency Table Subsysems............. 126 ix List of Tables Table Page 2.1 Sensor specifications [1].......................... 24 2.2 Engine specifications [15]......................... 31 3.1 Relevant instrumented sensors on engine................ 37 4.1 Constant engine parameters....................... 46 5.1 Model MAP Sensitivity Analysis.................... 64 6.1 MAP prediction performance...................... 77 6.2 Comparison among proposed 2-d lookup functions........... 80 6.3 Comparison between original and recalibrated Ve maps........ 83 6.4 Error improvement using PI control................... 91 6.5 Error improvement using Ve adaptive control.............. 100 6.6 Closed-loop AFR results, area deviation................ 104 6.7 Closed-loop AFR results, maximum % deviation............ 104 6.8 Comparison of closed-loop AFR results for area deviation with steady- state algorithm recalibration....................... 108 6.9 Comparison of closed-loop AFR results for maximum % deviation with steady-state algorithm recalibration................... 109 x 6.10 Open-loop AFR results, area deviation................. 112 6.11 Open-loop AFR results, maximum % deviation............ 112 6.12 Test operating points for open-loop AFR control performance comparison113 xi List of Figures Figure Page 1.1 Ohio State University EcoCAR 2 vehicle architecture.........4 2.1 Three-way catalyst conversion efficiency [12]..............8 2.2 Variation in flow rate past a throttle [9].................9 2.3 Isenthalpic flow model of a throttle [12]................. 11 2.4 Affects of different flow phenomena on volumetric efficiency [8].... 14 2.5 Volumetric efficiency map of a 1.8L 4cyl E85 engine.......... 16 2.6 Model classification for an intake manifold [8]............. 17 2.7 MAF and MAP reading from throttle transient at 1200 RPM..... 21 2.8 Injection and transport delays [1].................... 23 2.9 2006 Honda R18A3 engine [15]...................... 31 2.10 Valve lift profiles of different cam settings [15]............. 32 2.11 Intake manifold variable length runner [15]............... 33 2.12 Emissions concentrations