Non-linear Model-based Predictive Control of a Low-temperature Gasoline Combustion Engine - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Non-linear Model-based Predictive Control of a Low-temperature Gasoline Combustion Engine write by Kai Hoffmann. This book was released on 2010. Non-linear Model-based Predictive Control of a Low-temperature Gasoline Combustion Engine available in PDF, EPUB and Kindle.
Nonlinear Model Predictive Control of Combustion Engines
Nonlinear Model Predictive Control of Combustion Engines - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Nonlinear Model Predictive Control of Combustion Engines write by Thivaharan Albin Rajasingham. This book was released on 2021-04-27. Nonlinear Model Predictive Control of Combustion Engines available in PDF, EPUB and Kindle. 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
Dynamic Modeling and Predictive Control of a Multi-Mode Combustion Engine - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Dynamic Modeling and Predictive Control of a Multi-Mode Combustion Engine write by . This book was released on 2023. Dynamic Modeling and Predictive Control of a Multi-Mode Combustion Engine available in PDF, EPUB and Kindle. 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.
Nonlinear Systems and Circuits in Internal Combustion Engines
Nonlinear Systems and Circuits in Internal Combustion Engines - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Nonlinear Systems and Circuits in Internal Combustion Engines write by Ferdinando Taglialatela-Scafati. This book was released on 2017-10-31. Nonlinear Systems and Circuits in Internal Combustion Engines available in PDF, EPUB and Kindle. This brief provides an overview on the most relevant nonlinear phenomena in internal combustion engines with a particular emphasis on the use of nonlinear circuits in their modelling and control. The brief contains advanced methodologies —based on neural networks and soft-computing approaches among others— for the compensation of engine nonlinearities by using the combustion pressure signal and proposes several techniques for the reconstruction of this signal on the basis of different engine parameters, including engine-block vibration and crankshaft rotational speed. Another topic of the book is the diagnosis of the nonlinearities of injection systems and their balancing, which is a mandatory task for the new generation of gasoline direct injection engines. The authors come from both industrial and academic backgrounds, so the brief represents an important tool both for researchers and practitioners in the automotive industry.
Novel Approaches to Nonlinear Model Predictive Control with Application to High Temperature Fuel Cells
Novel Approaches to Nonlinear Model Predictive Control with Application to High Temperature Fuel Cells - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Novel Approaches to Nonlinear Model Predictive Control with Application to High Temperature Fuel Cells write by Matthew Kuure-Kinsey. This book was released on 2008. Novel Approaches to Nonlinear Model Predictive Control with Application to High Temperature Fuel Cells available in PDF, EPUB and Kindle.
