ABSTRACT
Optimal engine torque management, a fundamental objective, depends predominantly on engine speed tracking performance. It ensures to attain desired speed profile in the presence of uncertainties, disturbances and malfunctions. On the other hand, certain requirements such as emissions control, fuel efficiency and drivability are degraded in case of poor speed tracking. Furthermore, constraints on engine speed tracking performance are even more stringent for hybrid power-train architecture as crankshaft speed and engine torque are the basic variables for coordinated control. Speed tracking is also considered essential for gear shift control of the automatic transmission. In this research work, a framework for fault-tolerant speed tracking of the gasoline engine is proposed using the First Principle-based Engine Model (FPEM). A high-fidelity direct relationship between fuel injection input and engine speed is derived by the transformation of FPEM. Fault is induced in the fuel injection subsystem to generate the torque imbalance. Using the proposed framework, a second-order sliding mode-based control technique is applied to track desired speed profile by mitigating the faults in the fuel injection subsystem. Reference data acquired from the engine test rig is used to demonstrate the offline validity and fault tolerance capabilities of the proposed framework in MATLAB/Simulink.
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Raheel Anjum
Raheel Anjum received PhD degree in Control Systems from Capital University of Science and Technology (CUST), Islamabad in 2019. He completed MS in Control Systems from UET, Taxila and BE in Mechanical Engineering from the National University of Sciences and Technology, Islamabad in 2001. His research interest includes Engine Modeling and Control, Fault-Tolerant Control and Consensus Control of Multi-agent Systems.
Ahmed Yar
Ahmed Yar received BS degree in Electrical Engineering from the University of Engineering and Technology, Lahore, Pakistan. He did MS in Systems Engineering and PhD in Control systems in 2017 from Control Systems from Capital University of Science and Technology, Islamabad, Pakistan. His research interests are Internal Combustion Engines, Vehicle Power-train and Embedded Systems.
Ghulam Murtaza
Ghulam Murtaza is a graduate of the College of Electrical and Mechanical Engineering, National University of Science and Technology, Islamabad, Pakistan. He has Masters and PhD in Control System Engineering from the Capital University of Science and Technology, Islamabad, Pakistan. His research interests include the application of Sliding Mode-based algorithms for the development of Fault-Tolerant Control Systems and Robotics.
Qadeer Ahmed
Qadeer Ahmed is the Research Associate Professor with the Departments of Mechanical and Aerospace Engineering and Electrical and Computer Engineering and a core faculty affiliate of the Center for Automotive Research, The Ohio State University, Columbus, OH, USA. He received a PhD degree in Control Systems from Mohammad Ali Jinnah University, Islamabad, Pakistan, in 2011. His research includes controls, optimisation, and diagnostics of automotive systems with a focus on their efficiency, safety, and security. He has authored more than 100+ international peer-reviewed publications and received the OSU's Lumley Research Award in 2018, SAE's Buckendale Award in 2019, and SAE's Forest R. McFarland Award in 2022.
Aamer I. Bhatti
Aamer Iqbal Bhatti received the MS degree in control systems from Imperial College London, UK, in 1994, and the PhD degree in control engineering from Leicester University, UK, in 1998. Since 2007, he has been a Professor with the Department of Electrical Engineering, Capital University of Science and Technology, Islamabad, Pakistan. He is currently the pioneering Head of the Control and Signal Processing Research Group, CASPR Dynamics, Islamabad. His research interests include automotive parameter estimation, automotive engine control and diagnostics, air vehicle guidance and control, radar system design, fuel cell control and diagnostics and nonlinear sliding mode controller/observer theory.