A Two-Stage Multi-objective Predictive Control Approach for Low Temperature Combustion Engines
| Author | : Thivaharan Albin Rajasingham |
| Publisher | : |
| Total Pages | : 158 |
| Release | : 2013 |
| Genre | : Internal combustion engines |
| ISBN | : 9783185233081 |
A Two Stage Multi Objective Predictive Control Approach For Low Temperature Combustion Engines
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Nonlinear Model Predictive Control of Combustion Engines
| Author | : Thivaharan Albin Rajasingham |
| Publisher | : Springer Nature |
| Total Pages | : 330 |
| Release | : 2021-04-27 |
| Genre | : Technology & Engineering |
| ISBN | : 303068010X |
This book provides an overview of the nonlinear model predictive control (NMPC) concept for application to innovative combustion engines. Readers can use this book to become more expert in advanced combustion engine control and to develop and implement their own NMPC algorithms to solve challenging control tasks in the field. The significance of the advantages and relevancy for practice is demonstrated by real-world engine and vehicle application examples. The author provides an overview of fundamental engine control systems, and addresses emerging control problems, showing how they can be solved with NMPC. The implementation of NMPC involves various development steps, including: • reduced-order modeling of the process; • analysis of system dynamics; • formulation of the optimization problem; and • real-time feasible numerical solution of the optimization problem. Readers will see the entire process of these steps, from the fundamentals to several innovative applications. The application examples highlight the actual difficulties and advantages when implementing NMPC for engine control applications. Nonlinear Model Predictive Control of Combustion Engines targets engineers and researchers in academia and industry working in the field of engine control. The book is laid out in a structured and easy-to-read manner, supported by code examples in MATLAB®/Simulink®, thus expanding its readership to students and academics who would like to understand the fundamental concepts of NMPC. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
Dynamic Modeling and Predictive Control of a Multi-Mode Combustion Engine
| Author | : |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2023 |
| Genre | : |
| ISBN | : |
Abstract : Low temperature combustion (LTC) offers high thermal efficiency and low engine-out nitrogen oxides (NOx) and particulate matter (PM) emissions. Homogeneous charge compression ignition (HCCI), partially premixed charge compression ignition (PPCI) and reactivity-controlled compression ignition (RCCI) are the common LTC modes studied in this research. The primary barrier to implementing the LTC modes in on-road vehicles is their limited operating range due to high cyclic variability and excessive pressure rise rates. The feasible operating range of the LTC modes is only a subset of the speed-load range of the conventional spark ignition (SI) engine. Therefore, a multi-mode engine concept operating in one or more LTC modes and SI mode is a viable option to improve engine performance in terms of efficiency and emissions. The goal of this dissertation is to develop model-based closed loop control of an SI-RCCI-SI multi-mode engine. Control-oriented models and predictive controllers for HCCI, PPCI and RCCI modes are developed to simultaneously control combustion phasing and engine load for an optimal operation of a multi-mode engine. Cyclic variability in HCCI and RCCI modes are modeled using machine learning classification algorithms. Nonlinear model predictive controllers are developed for HCCI and RCCI modes to control combustion phasing and engine load while constraining cyclic variability below 3%. Furthermore, LTC engine operation faces challenges of excessive pressure rise rates that can damage the hardware. To this end, supervised machine learning classification algorithms are developed to model the heat release type which is used as a scheduling variable to develop data-driven model for an LTC engine. Model predictive controller is then developed to control combustion phasing and engine load while constraining maximum pressure rise rate below 8 bar/CAD. RCCI mode offers good control over the combustion event by modulating the start of injection timing of high reactivity fuel and adjusting the premixed ratio of the dual fuels. Therefore, this research focuses on SI-RCCI-SI multi-mode engine concept. The aim of this research is to achieve smooth SI-RCCI-SI mode switching operation at different engine loads and speed. A dynamic model for SI-RCCI-SI multi-mode engine is developed and validated for different transient conditions. The model includes the mode switching dynamics as well as actuator dynamics. A model-based predictive controller framework is developed for SI-RCCI-SI mode switching. The mode switching controller showed good performance during mode transitions and steady state engine operation. The controller is capable of tracking the desired combustion phasing and engine load during mode switching while maintaining $\lambda$ near stoichiometry in SI mode and constraining maximum pressure rise rate below 8 bar/CAD in RCCI mode.
Recent Advances in Model Predictive Control
| Author | : Timm Faulwasser |
| Publisher | : Springer Nature |
| Total Pages | : 250 |
| Release | : 2021-04-17 |
| Genre | : Science |
| ISBN | : 3030632814 |
This book focuses on distributed and economic Model Predictive Control (MPC) with applications in different fields. MPC is one of the most successful advanced control methodologies due to the simplicity of the basic idea (measure the current state, predict and optimize the future behavior of the plant to determine an input signal, and repeat this procedure ad infinitum) and its capability to deal with constrained nonlinear multi-input multi-output systems. While the basic idea is simple, the rigorous analysis of the MPC closed loop can be quite involved. Here, distributed means that either the computation is distributed to meet real-time requirements for (very) large-scale systems or that distributed agents act autonomously while being coupled via the constraints and/or the control objective. In the latter case, communication is necessary to maintain feasibility or to recover system-wide optimal performance. The term economic refers to general control tasks and, thus, goes beyond the typically predominant control objective of set-point stabilization. Here, recently developed concepts like (strict) dissipativity of optimal control problems or turnpike properties play a crucial role. The book collects research and survey articles on recent ideas and it provides perspectives on current trends in nonlinear model predictive control. Indeed, the book is the outcome of a series of six workshops funded by the German Research Foundation (DFG) involving early-stage career scientists from different countries and from leading European industry stakeholders.
New Directions on Model Predictive Control
| Author | : Jinfeng Liu |
| Publisher | : MDPI |
| Total Pages | : 231 |
| Release | : 2019-01-16 |
| Genre | : Engineering (General). Civil engineering (General) |
| ISBN | : 303897420X |
This book is a printed edition of the Special Issue "New Directions on Model Predictive Control" that was published in Mathematics
Two-stage Ignition as an Indicator of Low Temperature Combustion in a Late Injection Pre-mixed Compression Ignition Control Strategy
| Author | : Joshua Andrew Bittle |
| Publisher | : |
| Total Pages | : |
| Release | : 2011 |
| Genre | : |
| ISBN | : |
Internal combustion engines have dealt with increasingly restricted emissions requirements. After-treatment devices are successful in bringing emissions into compliance, but in-cylinder combustion control can reduce their burden by reducing engine out emissions. For example, oxides of nitrogen (NOx) are diesel combustion exhaust species that are notoriously difficult to remove by after-treatment. In-cylinder conditions can be controlled for low levels of NOx, but this produces high levels of soot potentially leading to increased particulate matter (PM). The simultaneous reduction of NOx and PM can be realized through a combustion process known as low temperature combustion (LTC). In this study, the typical definition of LTC as the defeat of the inverse relationship between soot and NOx is not applicable as a return to the soot-NOx tradeoff is observed with increasing exhaust gas recirculation (EGR). It is postulated that this effect is the result of an increase in the hot ignition equivalence ratio, moving the combustion event into a slightly higher soot formation region. This is important because a simple emissions based definition of LTC is no longer helpful. In this study, the manifestation of LTC in the calculated heat release profile is investigated. The conditions classified as LTC undergo a two-stage ignition process. Two-stage ignition is characterized by an initial cool-flame reaction followed by typical hot ignition. In traditional combustion conditions, the ignition is fast enough that a cool-flame is not observed. By controlling initial conditions (pressure, temperature, and composition), the creation and duration of the cool-flame event is predictable. Further, the effect that injection timing and the exhaust gas recirculation level have on the controlling factors of the cool-flame reaction is well correlated to the duration of the cool-flame event. These two results allow the postulation that the presence of a sufficiently long cool-flame reaction indicates a combustion event that can be classified as low temperature combustion. A potential method for identifying low temperature combustion events using only the rate of heat release profile is theorized. This study employed high levels of EGR and late injection timing to realize the LTC mode of ordinary petroleum diesel fuel. Under these conditions, and based on a 90 percent reduction in nitric oxide and no increase in smoke output relative to the chosen baseline condition, a two part criteria is developed that identifies the LTC classified conditions. The criteria are as follow: the combustion event of conventional petroleum diesel fuel must show a two-stage ignition process; the first stage (cool-flame reaction) must consume at least 2 percent of the normalized fuel energy before the hot ignition commences.
Model Predictive Control
| Author | : Ridong Zhang |
| Publisher | : Springer |
| Total Pages | : 143 |
| Release | : 2018-08-14 |
| Genre | : Technology & Engineering |
| ISBN | : 9811300836 |
This monograph introduces the authors’ work on model predictive control system design using extended state space and extended non-minimal state space approaches. It systematically describes model predictive control design for chemical processes, including the basic control algorithms, the extension to predictive functional control, constrained control, closed-loop system analysis, model predictive control optimization-based PID control, genetic algorithm optimization-based model predictive control, and industrial applications. Providing important insights, useful methods and practical algorithms that can be used in chemical process control and optimization, it offers a valuable resource for researchers, scientists and engineers in the field of process system engineering and control engineering.
Introduction to Modeling and Control of Internal Combustion Engine Systems
| Author | : Lino Guzzella |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 303 |
| Release | : 2013-03-14 |
| Genre | : Technology & Engineering |
| ISBN | : 3662080036 |
Internal combustion engines still have a potential for substantial improvements, particularly with regard to fuel efficiency and environmental compatibility. These goals can be achieved with help of control systems. Modeling and Control of Internal Combustion Engines (ICE) addresses these issues by offering an introduction to cost-effective model-based control system design for ICE. The primary emphasis is put on the ICE and its auxiliary devices. Mathematical models for these processes are developed in the text and selected feedforward and feedback control problems are discussed. The appendix contains a summary of the most important controller analysis and design methods, and a case study that analyzes a simplified idle-speed control problem. The book is written for students interested in the design of classical and novel ICE control systems.
