This book presents a step-by-step guide to engine control system design, providing case studies and a thorough analysis of the modelling process, using model predictive control (MPC). Covering advanced processes alongside the theoretical foundation, it enables engineers to improve performance in both hybrid and non-hybrid vehicles.
This book presents a step-by-step guide to engine control system design, providing case studies and a thorough analysis of the modelling process, using model predictive control (MPC). Covering advanced processes alongside the theoretical foundation, it enables engineers to improve performance in both hybrid and non-hybrid vehicles.
Amir-Mohammad Shamekhi received his PhD in Automobile Control from K. N. Toosi University of Technology, Tehran, Iran, in 2021, and was chosen as the superior researcher of the Department of Mechanical Engineering. His works concern Control and Machine Learning, and their applications particularly in vehicles, about which he has published in several journal papers. Amir Hossein Shamekhi received his B.Sc. in Mechanical Engineering from Tehran University, Tehran, Iran, in 1993. Carrying on his studies, he obtained M.Sc. from K. N. Toosi University of Technology, Tehran, Iran, in 1997. Receiving his PhD in 2004, Dr. Shamekhi was the first PhD alumni of Mechanical Engineering in K. N. Toosi University of Technology, where he is currently Associate Professor in the faculty of Mechanical Engineering. His fields of study include internal combustion engines, mechatronics, and automotive transmission.
Inhaltsangabe
Chapter 1 Introduction Chapter 2 Control-Oriented Modeling Chapter 3 Mid-Level Controller Design: Calibration Chapter 4 Low-Level Controller Design: Fuel Injection Control Chapter 5 High-Level Controller Design: Torque Control Appendix A: A Short Review of Neural Networks Design Appendix B: A Short Review of Some Optimization Algorithms
