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A Soft ECU Approach to Develop a Powertrain Control Strategy

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A Soft ECU Approach to Develop a Powertrain Control Strategy A Soft ECU Approach to Develop a Powertrain Control Strategy 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 Spiegel, B.S. Graduate Program in Mechanical Engineering The Ohio State University 2015 Thesis Committee: Professor Shawn Midlam-Mohler, Advisor Professor Marcello Canova Copyright by Andrew Spiegel 2015 ABSTRACT Automotive control systems are becoming increasingly complex as consumers and government regulations demand vehicles with better fuel economy, reduced emissions, improved safety, and increased functionality while maintaining performance. The short development time frames of embedded control software in automotive Electronic Control Units (ECUs) has put additional attention on methods for rapid control development. Model-based control design is used widely in the automotive industry for the development of embedded control systems for attributes such as reducing development times, lowering cost, and preventing revisions while ensuring quality of complex control systems [1]. The Ohio State University’s Center for Automotive Research (CAR) is working on a research project to develop a novel powertrain control strategy using model-based design techniques. To develop the new control strategy, the Ohio State University (OSU) needed a simplified version of a target vehicle’s state-of-the-art powertrain control strategy. Because OSU is under time constraints to develop and demonstrate the control strategy, a soft ECU model representing the target vehicle’s powertrain control strategy was developed. The soft ECU model will help speed the development process of the novel powertrain control strategy by serving as a benchmark and starting point for control design. This thesis describes the approach of developing, verifying, and utilizing a soft ECU model ii in the development process of the novel powertrain control strategy. The soft ECU model was developed in Simulink using model-based control techniques. The soft ECU model, a driver model, and a vehicle plant model were combined to create a complete vehicle model. The complete vehicle model was verified through Model-In-the-Loop simulations. The accuracy of the components in the complete vehicle model were compared with their respective isolated system accuracies. The complete vehicle model’s components show good accuracy to their corresponding drive cycle data collected from the target vehicle. The soft ECU model is an accurate benchmark of the target vehicle’s powertrain control strategy. Further modifications can be made to the soft ECU model and driver model to improve the overall accuracy of the complete vehicle model. The soft ECU model will be used as a starting point for the design of the new powertrain control strategy. iii Dedicated to my family and friends. iv ACKNOWLEDGEMENTS I would first like to thank my advisor, Dr. Shawn Midlam-Mohler, for his guidance and support throughout both undergraduate and graduate school. I would also like to thank Dr. Marcello Canova for his inclusion on this research project. I would also like to thank the following people who have helped me in my time at the Center for Automotive Research: Stephanie Stockar, Cristian Rostiti, Vincenzo Colandrea, Salvatore Riccardo, Luigi Angelino, and Luca D’Avico. Finally, I would like to thank my family and friends for their endless support. v VITA March 12, 1991 .................................................Born – Bucyrus, Ohio 2009...................................................................Bucyrus High School 2013...................................................................B.S. Mechanical Engineering, The Ohio State University August 2013 to Present ....................................Graduate Research Associate, Department of Mechanical Engineering, The Ohio State University FIELDS OF STUDY Major Field: Mechanical Engineering vi TABLE OF CONTENTS ABSTRACT ........................................................................................................................ ii ACKNOWLEDGEMENTS ................................................................................................ v VITA .................................................................................................................................. vi TABLE OF CONTENTS .................................................................................................. vii CHAPTER 1: INTRODUCTION ....................................................................................... 1 1.1 Motivation............................................................................................................... 1 1.2 Scope....................................................................................................................... 2 1.3 Thesis Outline ......................................................................................................... 3 CHAPTER 2: LITERATURE REVIEW ............................................................................ 4 2.1 Introduction............................................................................................................. 4 2.2 Automotive ECUs ................................................................................................... 4 2.3 Model-Based Control Design ................................................................................. 6 2.3.1 V-Model ............................................................................................................. 7 2.3.2 Development Phases .......................................................................................... 8 2.3.2.1 Conceptualization Phase ............................................................................. 8 2.3.2.2 System Development Phase ........................................................................ 9 2.3.2.3 Verification and Validation....................................................................... 10 2.4 Soft ECU Models .................................................................................................. 13 2.5 Artificial Neural Networks ................................................................................... 14 2.6 Model-In-The-Loop Techniques .......................................................................... 16 vii CHAPTER 3: CONCLUSIONS AND FUTURE WORK ................................................ 18 3.1 Conclusions .......................................................................................................... 18 3.2 Future Work .......................................................................................................... 19 BIBLIOGRAPHY ............................................................................................................. 21 APPENDIX: LIST OF SYMBOLS AND ABBREVIATIONS ....................................... 23 viii LIST OF FIGURES Figure 1: Engine Control System [4] .................................................................................. 5 Figure 2: Transmission Control System [4] ........................................................................ 6 Figure 3: V-Model for Model-Based Software Development [5] ...................................... 8 Figure 4: Model-Based Control Development Approach [6] ........................................... 10 Figure 5: Verification and Validation Processes [6] ......................................................... 11 Figure 6: Model of an Artificial Neuron [9] ..................................................................... 15 Figure 7: Artificial Neural Network [9] ............................................................................ 15 ix CHAPTER 1: INTRODUCTION 1.1 Motivation Automotive control systems continue to become more complex as consumers and government regulations demand that vehicles achieve better fuel economy, reduced emissions, improved safety, and increased functionality while maintaining performance. In addition, car manufacturers must meet consumer demands within relatively short timeframes. These challenges have driven engineers to look for methods to rapidly develop complex control software for automotive embedded systems. One of the major industry responses for fast development of embedded software in automotive Electronic Control Units (ECUs) is model-based control design. Model-based control design features a variety of standardized techniques that enable efficient development of control systems in a cost-effective way [2]. Model-based design is used widely throughout the automotive industry to reduce development times, lower cost, and prevent revisions while ensuring quality of complex control systems [1]. 1 1.2 Scope Members from the Ohio State University’s Center for Automotive Research (CAR) are working on a research project to develop a novel powertrain control strategy using model-based design techniques. The control strategy’s main purpose is to optimize vehicle powertrains for fuel economy and drivability. During the project definition stage of control development, the Ohio State University (OSU) needed a simplified version of a target vehicle’s powertrain control strategy. The purpose of the simplified control strategy is to simulate the behavior of the complete vehicle powertrain when coupled with a driver model and exercised over desired velocity profiles to establish benchmarks of fuel economy, drivability, and performance metrics. A soft ECU model representing the vehicle’s powertrain control strategy was therefore
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