Robust Feedback Linearization Approach For Fuel Optimal Oriented Control Of Turbocharged Spark Ignition Engines
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Intelligent and Efficient Transport Systems
Author: Truong Quang Dinh
language: en
Publisher: BoD – Books on Demand
Release Date: 2020-04-01
The aim of this book is to present a number of digital and technology solutions to real-world problems across transportation sectors and infrastructures. Nine chapters have been well prepared and organized with the core topics as follows: -A guideline to evaluate the energy efficiency of a vehicle -A guideline to design and evaluate an electric propulsion system -Potential opportunities for intelligent transportation systems and smart cities -The importance of system control and energy-power management in transportation systems and infrastructures -Bespoke modeling tools and real-time simulation platforms for transportation system development This book will be useful to a wide range of audiences: university staff and students, engineers, and business people working in relevant fields.
Turbocharged Engine Control for Fuel Efficiency and Torque Responsiveness
Fuel economy standards for cars and other vehicles are growing increasingly stringent, thus motivating automakers to find ways to improve fuel efficiency. One popular strategy is to turbocharge a downsized (smaller displacement) engine, which can be more fuel efficient than a naturally aspirated engine delivering the same power output. However, turbocharged engines can be sluggish to respond to torque requests, which drivers often find undesirable. Unfortunately, improving torque responsiveness results in reduced fuel efficiency, and vice versa. This dissertation explores two model-based control strategies to manage this tradeoff. The first strategy is a decentralized controller, in which the throttle and wastegate are controlled in separate loops. The throttle loop uses feedback linearization with supplemental PI control to obtain good torque tracking. The wastegate is opened or closed, based on a preview of the reference torque, to switch between fuel-optimal and torque-optimal modes. The second strategy is a multi-objective optimization scheme to obtain good fuel efficiency and fast torque response by controlling the throttle and wastegate simultaneously. Simulation results show promising performance from both strategies. Additionally, the models used in these control methods are described in detail. A high-fidelity engine simulator in Simscape is used for controller validation. This simulator is too complex for controller design, so a simpler 4-state model is constructed. This model works well in continuous time, but the optimization-based control method requires a discrete-time model. Unfortunately, discretizing the 4-state model results in chattering due to numerical stiffness. This numerical stiffness is analyzed, and a solution is proposed to represent the throttle pressure ratio as a static map. This results in a 3-state model that is easily discretized.
A STUDY OF MODEL-BASED CONTROL STRATEGY FOR A GASOLINE TURBOCHARGED DIRECT INJECTION SPARK IGNITED ENGINE
Abstract : To meet increasingly stringent fuel economy and emissions legislation, more advanced technologies have been added to spark-ignition (SI) engines, thus exponentially increase the complexity and calibration work of traditional map-based engine control. To achieve better engine performance without introducing significant calibration efforts and make the developed control system easily adapt to future engines upgrades and designs, this research proposes a model-based optimal control system for cycle-by-cycle Gasoline Turbocharged Direct Injection (GTDI) SI engine control, which aims to deliver the requested torque output and operate the engine to achieve the best achievable fuel economy and minimum emission under wide range of engine operating conditions. This research develops a model-based ignition timing prediction strategy for combustion phasing (crank angle of fifty percent of the fuel burned, CA50) control. A control-oriented combustion model is developed to predict burn duration from ignition timing to CA50. Using the predicted burn duration, the ignition timing needed for the upcoming cycle to track optimal target CA50 is calculated by a dynamic ignition timing prediction algorithm. A Recursive-Least-Square (RLS) with Variable Forgetting Factor (VFF) based adaptation algorithm is proposed to handle operating-point-dependent model errors caused by inherent errors resulting from modeling assumptions and limited calibration points, which helps to ensure the proper performance of model-based ignition timing prediction strategy throughout the entire engine lifetime. Using the adaptive combustion model, an Adaptive Extended Kalman Filter (AEKF) based CA50 observer is developed to provide filtered CA50 estimation from cyclic variations for the closed-loop combustion phasing control. An economic nonlinear model predictive controller (E-NMPC) based GTDI SI engine control system is developed to simultaneously achieve three objectives: tracking the requested net indicated mean effective pressure (IMEPn), minimizing the SFC, and reducing NOx emissions. The developed E-NMPC engine control system can achieve the above objectives by controlling throttle position, IVC timing, CA50, exhaust valve opening (EVO) timing, and wastegate position at the same time without violating engine operating constraints. A control-oriented engine model is developed and integrated into the E-NMPC to predict future engine behaviors. A high-fidelity 1-D GT-POWER engine model is developed and used as the plant model to tune and validate the developed control system. The performance of the entire model-based engine control system is examined through the software-in-the-loop (SIL) simulation using on-road vehicle test data.