Transient Control of Gasoline Engines

311 Pages·2015·15.13 MB·English

by  Tielong Shen

Transient Control
of Gasoline
Engines
© 2016 by Taylor & Francis Group, LLC
T&F Cat #K19029 — K19029 C000 — page i — 9/19/2015 — 19:52
© 2016 by Taylor & Francis Group, LLC
Transient Control
of Gasoline
Engines
Tielong Shen • Jiangyan Zhang
Xiaohong Jiao • Mingxin Kang
Junichi Kako • Akira Ohata

© 2016 by Taylor & Francis Group, LLC
T&F Cat #K19029 — K19029 C000 — page iii — 9/19/2015 — 19:52
CRC Press
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© 2016 by Taylor & Francis Group, LLC
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© 2016 by Taylor & Francis Group, LLC
Contents
List of Figures xi
List of Tables xvii
Preface xix
Authors xxiii
1 Introduction 1
1.1 Control-Oriented Engine Model . . . . . . . . . . . . . . . . 3
1.2 Control Issues of Gasoline Engine . . . . . . . . . . . . . . . 4
1.3 Experimental Setup . . . . . . . . . . . . . . . . . . . . . . . 7
2 Mathematical Model of Gasoline Engines 13
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.2 Physics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.3 Modeling of Components . . . . . . . . . . . . . . . . . . . . 17
2.3.1 Air Intake Path . . . . . . . . . . . . . . . . . . . . . . 17
2.3.2 Fuel Path . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.4 In-Cylinder Dynamical Model . . . . . . . . . . . . . . . . . 21
2.5 Mean-Value Model . . . . . . . . . . . . . . . . . . . . . . . . 28
2.6 Numerical Simulation Model . . . . . . . . . . . . . . . . . . 31
2.7 Model Calibration Method . . . . . . . . . . . . . . . . . . . 32
2.8 A Lemma: Air Mass Flow Passing through a Nozzle . . . . . 34
3 Speed Control 39
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
3.2 Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
3.3 Idle Speed Control Scheme . . . . . . . . . . . . . . . . . . . 43
3.4 Uncertainty and Robustness . . . . . . . . . . . . . . . . . . 50
3.5 Starting Speed Control . . . . . . . . . . . . . . . . . . . . . 56
3.6 Experimental Case Study . . . . . . . . . . . . . . . . . . . . 66
3.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
4 Air–Fuel Ratio Control 73
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
4.2 Air Charge Prediction-Based Feedforward Control . . . . . . 77
vii
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viii Contents
4.3 Wall-Wetting Model-Based Feedforward Control . . . . . . . 81
4.4 Lyapunov-Based Adaptive Control . . . . . . . . . . . . . . . 85
4.5 Experimental Validation for Control Strategies . . . . . . . . 92
4.5.1 Case Studies for Air Charge Estimation . . . . . . . . 92
4.5.2 Case Studies for Wall-Wetting Compensation . . . . . 95
4.5.3 Case Studies for Adaptive Regulation . . . . . . . . . 99
4.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
5 Receding Horizon Optimal Control 113
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
5.2 Design Framework and Optimization Algorithm . . . . . . . 115
5.3 Torque Transient Control . . . . . . . . . . . . . . . . . . . . 120
5.3.1 Control-Oriented Model . . . . . . . . . . . . . . . . . 121
5.3.2 Torque Tracking Control Scheme Design . . . . . . . . 122
5.4 Speed Transient Control . . . . . . . . . . . . . . . . . . . . 126
5.4.1 Tracking Error Dynamics . . . . . . . . . . . . . . . . 126
5.4.2 Speed Tracking Control Scheme Design . . . . . . . . 128
5.5 Parameter Tuning . . . . . . . . . . . . . . . . . . . . . . . . 129
5.6 Adaptive Compensation of Disturbance . . . . . . . . . . . . 134
5.7 Experimental Case Studies . . . . . . . . . . . . . . . . . . . 136
5.7.1 Torque Transient Control . . . . . . . . . . . . . . . . 136
5.7.2 Speed Transient Control . . . . . . . . . . . . . . . . . 140
5.7.3 Parameter Tuning and Adaptive Compensation . . . . 145
5.8 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
6 Balancing Control 151
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
6.2 Exhaust Gas Mixing Model . . . . . . . . . . . . . . . . . . . 151
6.3 Individual Cylinder A/F . . . . . . . . . . . . . . . . . . . . 154
6.3.1 Individual Cylinder Fuel–Gas Ratio Modeling . . . . . 154
6.3.2 Model Validation . . . . . . . . . . . . . . . . . . . . . 156
6.4 A/F Balancing Control . . . . . . . . . . . . . . . . . . . . . 158
6.4.1 Self-Tuning Regulator . . . . . . . . . . . . . . . . . . 160
6.4.2 Generalized Predictive Control . . . . . . . . . . . . . 163
6.5 Linear Time-Varying Model and Offset Learning . . . . . . . 165
6.5.1 Periodic Time-Varying Fuel Path Model . . . . . . . . 166
6.5.2 State Observer . . . . . . . . . . . . . . . . . . . . . . 170
6.5.3 Observer-Based Offset Learning Control . . . . . . . . 173
6.5.4 Experimental Validation Study . . . . . . . . . . . . . 174
6.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
7 Residual Gas and Stochastic Control 181
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
7.2 Residual Gas Measurement . . . . . . . . . . . . . . . . . . . 183
7.3 Markovian Property of Residual Gas . . . . . . . . . . . . . . 186
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Contents ix
7.4 Stochastic Optimal Regulation . . . . . . . . . . . . . . . . . 193
7.5 Disturbance Rejection . . . . . . . . . . . . . . . . . . . . . . 197
7.6 Experimental Case Studies . . . . . . . . . . . . . . . . . . . 199
7.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
8 Benchmark Problems for Control and Modeling
of Automotive Gasoline Engine 211
8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 211
8.2 Benchmark Challenge of Engine Start Control Problem . . . 211
8.2.1 Provided Engine Simulator . . . . . . . . . . . . . . . 212
8.2.2 Benchmark Problem Description . . . . . . . . . . . . 216
8.2.3 Approaches of Challengers . . . . . . . . . . . . . . . . 221
8.2.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . 223
8.3 Benchmark Problem for Nonlinear Identification of
Automotive Engine . . . . . . . . . . . . . . . . . . . . . . . 224
8.3.1 Provided Engine Model . . . . . . . . . . . . . . . . . 224
8.3.2 Benchmark Problem . . . . . . . . . . . . . . . . . . . 232
8.3.3 Sample Results . . . . . . . . . . . . . . . . . . . . . . 234
8.3.4 Challengers’ Results . . . . . . . . . . . . . . . . . . . 235
8.3.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . 235
8.4 Benchmark Problem for Boundary Modeling and
Near-Boundary Control . . . . . . . . . . . . . . . . . . . . . 236
8.4.1 Provided Engine Model . . . . . . . . . . . . . . . . . 237
8.4.2 Benchmark Problem . . . . . . . . . . . . . . . . . . . 239
8.4.3 Plan to Share the Results of the Challengers . . . . . 245
8.4.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . 245
Appendix A: Lyapunov Stability and Adaptive Control 247
Appendix B: Time-Delay System and Stability 255
Appendix C: Optimal Control and Pontryagin Maximum
Principle 257
Appendix D: Stochastic Optimal Control 265
Bibliography 277
Index 289

© 2016 by Taylor & Francis Group, LLC
T&F Cat #K19029 — K19029 C000 — page ix — 9/19/2015 — 19:52
© 2016 by Taylor & Francis Group, LLC