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Fault Diagnosis for Functional Safety in Electrified and Automated Vehicles

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Fault Diagnosis for Functional Safety in Electrified and Automated Vehicles Fault Diagnosis for Functional Safety in Electrified and Automated Vehicles Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Tianpei Li, Graduate Program in Mechanical Engineering The Ohio State University 2020 Dissertation Committee: Prof. Giorgio Rizzoni, Advisor Prof. Manoj Srinivasan Prof. Ran Dai Prof. Qadeer Ahmed c Copyright by Tianpei Li 2020 Abstract Vehicle safety is one of the critical elements of modern automobile development. With increasing automation and complexity in safety-related electrical/electronic (E/E) systems, and given the functional safety standards adopted by the automo- tive industry, the evolution and introduction of electrified and automated vehicles had dramatically increased the need to guarantee unprecedented levels of safety and security in the automotive industry. The automotive industry has broadly and voluntarily adopted the functional safety standard ISO 26262 to address functional safety problems in the vehicle development process. A V-cycle software development process is a core element of this standard to ensure functional safety. This dissertation develops a model-based diagnostic method- ology that is inspired by the ISO-26262 V-cycle to meet automotive functional safety requirements. Specifically, in the first phase, system requirements for diagnosis are determined by Hazard Analysis and Risk Assessment (HARA) and Failure Modes and Effect Analysis (FMEA). Following the development of system requirements, the second phase of the process is dedicated to modeling the physical subsystem and its fault modes. The implementation of these models using advanced simulation tools (MATLAB/Simulink and CarSim in this dissertation) permits quantification of the fault effects on system safety and performance. The next phase is dedicated ii to understanding the diagnosability of the system (given a sensor set), or the selec- tion of a suitable sensor set to achieve the desired degree of diagnosability, using a graph-theoretic method known as structural analysis. By representing a system in directed-graph or incidence-matrix form, structural analysis allows the determina- tion of analytical redundancy in the system and of the detectability and isolability of individual faults. Further, it provides a logical computation sequence for solving for system unknowns, by identifying analytical redundant relations (ARRs) that can be used to design diagnostic algorithms. The design of residual generation based on ARRs is linked to state estimation and system identification methods, includ- ing state observers and parameter estimation. The later phases of the V-diagram address the development of Model-In-the-Loop, Software -In-the-Loop, Hardware-In- the-Loop, in-vehicle calibration and validation. For the purposes of this dissertation we limit our demonstration of the methods to Model-In-the-Loop validation for two of the case studies and Hardware-In-the-Loop validation for a third. In addition to developing a process-oriented methodology, this dissertation also addresses trade-offs in selecting different methods in terms of computational causality and robustness to noise and uncertainty in compliance with diagnostic requirements. Further, when dealing with state estimation and system identification in nonlinear systems, system observability can change with operating conditions. This disserta- tion also introduces a novel nonlinear system observability index to quantify system observability under different operating conditions. This index helps determine proper scenarios to apply state estimation and system identification approaches for fault di- agnosis. That is, the system observability and fault detectability may be enhanced in some operating conditions. iii The effectiveness of the methodology is demonstrated in three case studies: i) the diagnosis of electric traction drive resolver faults in all-wheel drive battery electric vehicles; ii) resolver fault diagnosis in a P-2 configuration hybrid-electric powertrain; and iii) fault diagnosis in the automated vehicle steering system. While ISO 26262 applies to E/E systems, mechanical and electromechanical systems are also susceptible to safety-related degradation and failure. Thus, in the third case study, we extend the scope of functional safety problems addressed by ISO 26262 to mechanical faults in vehicle steering system. That is, this dissertation addresses functional safety issues related to both E/E systems and mechanical systems in electrified and autonomous vehicles. iv Dedicated to my parents v Acknowledgments First, I would like to express my sincere gratitude to my advisor, Prof. Giorgio Rizzoni, for his continuous guidance and support in helping me develop interests in my research area. Without his expertise, patience and supervision, this dissertation would not be successful. I also thank him for providing me with the opportunity to join the Ohio State University Center for Automotive Research (OSU CAR) and to work with a group of intelligent people. The invaluable knowledge and experience I gained throughout my entire Ph.D career will be the key to my future success. I would also like to thank Prof Qadeer Ahmed, Prof. Manoj Srinivasan, Prof. Ran Dai, for serving as my dissertation committee. I especially would like to express my appreciation to Prof. Qadeer Ahmed, for the helpful guidance in the research projects on electric traction drive resolver diagnosis and chassis system diagnosis. I would like to thank Dr. Jeff Chrstos for his knowledge and experience in vehicle dynamics, CarSim and driving simulator. I specially thank Ruban Sekar for his help and support in performing experiments for my research. I also thank my workmates in the diagnostic/prognostic research group at CAR, including Ruochen Yang, Kaveh Khodadadi Sadabadi. It was a pleasant experience to exchange ideas with these talented people. I am also deeply grateful to my parents for their unconditional love and care. Without their support, I would never grow into maturity. I would like to thank Ziyi vi Li, for all her love and company over the past years. I also thank my friends at CAR, especially Tong Zhao, Ye Cheng, Yuxing Liu, Ke Pan, Zhaoxuan Zhu, for being so encouraging and supportive that helps me get rid of stresses and overcome all the hardships. Finally, I would like to thank Ford Motor Company for providing me with great research opportunities and projects. My gratitude goes to the people at Ford Motor Company, especially Mathew Boesch, Jason Meyer, Bader Badreddine, Dexin Wang, Devon Eyerman and Timothy Drotar. vii Vita 2014 . .B.S. Vehicle Engineering, Hefei Univer- sity of Technology, Hefei, China 2014-present . .Graduate Research Associate, Center for Automotive Research, Department of Mechanical and Aerospace Engineer- ing, The Ohio State University, Colum- bus, Ohio, USA. Publications Research Publications Li, T., Rizzoni, G., Ahmed, Q., Meyer, J., Boesch, M. and Badreddine, B. (in press) \Model-Based Electric Traction Drive Resolver Fault Diagnosis for Electrified Vehi- cles". International Journal of Powertrains Li, T., Ahmed, Q., Rizzoni, G., Meyer, J., Boesch, M. and Badreddine, B. \Motor Resolver Fault for AWD EV based on Structural Analysis". SAE Technical Paper, 2018, No. 2018-01-1354 Li, T., Ahmed, Q., Rizzoni, G., Meyer, J., Boesch, M. and Badreddine, B. \Mo- tor Resolver Fault Propagation Analysis for Electrified Powertrain". ASME 2017 Dynamic Systems and Control Conference Zhang, J., Amodio, A., Li, T., Aksun-Gven, B. and Rizzoni, G. \Fault Diagnosis and Fault Mitigation for Torque Safety of Drive-by-Wire Systems". IEEE Transactions on Vehicular Technology, 67(9), pp.8041-8054 Zhang, J., Li, T., Amodio, A., Aksun-Guvenc, B. and Rizzoni, G. \Fault diagno- sis and fault tolerant control for electrified vehicle torque security". 2016 IEEE Transportation Electrification Conference and Expo (ITEC), pp. 1-7. IEEE viii Fields of Study Major Field: Mechanical Engineering ix Table of Contents Page Abstract . ii Dedication . .v Acknowledgments . vi Vita......................................... viii List of Tables . xiv List of Figures . xvi List of Acronyms and Symbols . xxv 1. Introduction . .1 1.1 Motivation . .1 1.2 Contributions of this Dissertation . 10 1.3 Organization of this Dissertation . 11 2. Background . 14 2.1 Automotive Functional Safety . 14 2.2 Diagnostic Challenge for Automated Vehicles . 17 2.3 ISO/PAS 21448 Standard - Road Vehicles- Safety of the Intended Functionality (SOTIF) . 20 2.4 Objectives of This Dissertation . 21 2.5 Hazard Analysis and Risk Assessment (HARA) . 23 2.6 Functional Safety Concept and Technical Safety Concept . 25 2.7 Failure Modes and Effect Analysis (FMEA) . 26 x 2.8 Model-based Diagnosis Approaches . 30 2.8.1 Analytical Redundancy . 30 2.8.2 Structural Analysis . 31 2.8.3 Fault diagnosis with observers . 43 2.8.4 Fault diagnosis with parity equation . 47 2.8.5 Equivalence between observer-based diagnosis and parity equation- based diagnosis . 49 2.8.6 Fault diagnosis with parameter estimation . 52 2.9 Overview of Model-based Fault Diagnosis Methodology . 56 2.10 Conclusion . 57 3. Diagnosis of Electric Traction Drive Resolver Fault in All-wheel Drive Electric Vehicles . 59 3.1 PMSM Drive System Modeling . 62 3.2 FMEA of Electric Traction Drive Resolver . 64 3.2.1 Resolver-to-digital Conversion . 65 3.2.2 Failure modes of the resolver . 66 3.3 Resolver Fault Effects Analysis . 69 3.3.1 Effects of Amplitude Imbalance and Quadrature Imperfection in PMSM Drive System . 70 3.3.2 Effects of Amplitude Imbalance and Quadrature Imperfection on Electric Motor Control . 71 3.3.3 Effects of Reference Phase Shift in PMSM Drive System . 73 3.4 Simulation of Resolver Fault in PMSM Drive System . 74 3.4.1 Amplitude Imbalance in PMSM Drive System . 74 3.4.2 Reference Phase Shift in PMSM Drive System . 75 3.5 Structural Analysis for FDI . 77 3.6 Tire Slip Analysis . 83 3.6.1 Scenario 1: Tire Slip due to Intensive Acceleration . 85 3.6.2 Scenario 2: Tire Slip due to Extreme Road Conditions . 85 3.6.3 Scenario 3: Tire Slip due to Code Error . 86 3.7 GPS based Vehicle Speed and Wheel Speed Sensor Performance with Tire Slip .
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