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Author: Nicholas J. Killingsworth Publisher: ISBN: Category : Languages : en Pages : 139
Book Description
The lack of a direct combustion trigger makes control of combustion timing during transients especially challenging. To aid in HCCI engine control during transients, we have developed a model that can be used to derive a controller for a thermally-managed, gasoline and natural gas fueled HCCI engine. The model uses an ignition threshold derived from detailed chemical kinetic simulations of HCCI engine combustion to provide an estimate for the combustion timing. The ignition threshold is a function of both temperature and pressure. An estimate of the residual gas fraction from the previous cycle can also be obtained, which is essential information due to the strong temperature sensitivity of HCCI ignition. This model allows the synthesis of nonlinear control laws, which can be utilized for control of an HCCI engine during transients.
Author: Nicholas J. Killingsworth Publisher: ISBN: Category : Languages : en Pages : 139
Book Description
The lack of a direct combustion trigger makes control of combustion timing during transients especially challenging. To aid in HCCI engine control during transients, we have developed a model that can be used to derive a controller for a thermally-managed, gasoline and natural gas fueled HCCI engine. The model uses an ignition threshold derived from detailed chemical kinetic simulations of HCCI engine combustion to provide an estimate for the combustion timing. The ignition threshold is a function of both temperature and pressure. An estimate of the residual gas fraction from the previous cycle can also be obtained, which is essential information due to the strong temperature sensitivity of HCCI ignition. This model allows the synthesis of nonlinear control laws, which can be utilized for control of an HCCI engine during transients.
Author: Rolf D. Reitz Publisher: ISBN: Category : Languages : en Pages :
Book Description
The goal of this project was to develop methods to optimize and control Homogeneous-Charge Compression Ignition (HCCI) engines, with emphasis on diesel-fueled engines. HCCI offers the potential of nearly eliminating IC engine NOx and particulate emissions at reduced cost over Compression Ignition Direct Injection engines (CIDI) by controlling pollutant emissions in-cylinder. The project was initiated in January, 2002, and the present report is the final report for work conducted on the project through December 31, 2004. Periodic progress has also been reported at bi-annual working group meetings held at USCAR, Detroit, MI, and at the Sandia National Laboratories. Copies of these presentation materials are available on CD-ROM, as distributed by the Sandia National Labs. In addition, progress has been documented in DOE Advanced Combustion Engine R & D Annual Progress Reports for FY 2002, 2003 and 2004. These reports are included as the Appendices in this Final report.
Author: Hsien-Hsin Liao Publisher: Stanford University ISBN: Category : Languages : en Pages : 201
Book Description
There has been an enormous global research effort to alleviate the current and projected environmental consequences incurred by internal combustion (IC) engines, the dominant propulsion systems in ground vehicles. Two technologies have the potential to improve the efficiency and emissions of IC engines in the near future: variable valve actuation (VVA) and homogeneous charge compression ignition (HCCI). IC engines equipped with VVA systems are proven to show better performance by adjusting the valve lift and timing appropriately. An electro-hydraulic valve system (EHVS) is a type of VVA system that possesses full flexibility, i.e., the ability to change the valve lift and timing independently and continuously, making it an ideal rapid prototyping tool in a research environment. Unfortunately, an EHVS typically shows a significant response time delay that limits the achievable closed-loop bandwidth and, as a result, shows poor tracking performance. In this thesis, a control framework that includes system identification, feedback control design, and repetitive control design is presented. The combined control law shows excellent performance with a root-mean-square tracking error below 40 [Mu]m over a maximum valve lift of 4 mm. A stability analysis is also provided to show that the mean tracking error converges to zero asymptotically with the combined control law. HCCI, the other technology presented in this thesis, is a combustion strategy initiated by compressing a homogeneous air-fuel mixture to auto-ignition, therefore, ignition occurs at multiple points inside the cylinder without noticeable flame propagation. The result is rapid combustion with low peak in-cylinder temperature, which gives HCCI improved efficiency and reduces NOx formation. To initiate HCCI with a typical compression ratio, the sensible energy of the mixture needs to be high compared to a spark ignited (SI) strategy. One approach to achieve this, called recompression HCCI, is by closing the exhaust valve early to trap a portion of the exhaust gas in the cylinder. Unlike a SI or Diesel strategy, HCCI lacks an explicit combustion trigger, as autoignition is governed by chemical kinetics. Therefore, the thermo-chemical conditions of the air-fuel mixture need to be carefully controlled for HCCI to occur at the desired timing. Compounding this challenge in recompression HCCI is the re-utilization of the exhaust gas which creates cycle-to-cycle coupling. Furthermore, the coupling characteristics can change drastically around different operating points, making combustion timing control difficult across a wide range of conditions. In this thesis, a graphical analysis examines the in-cylinder temperature dynamics of recompression HCCI and reveals three qualitative types of temperature dynamics. With this insight, a switching linear model is formulated by combining three linear models: one for each of the three types of temperature dynamics. A switching controller that is composed of three local linear feedback controllers can then be designed based on the switching model. This switching model/control formulation is tested on an experimental HCCI testbed and shows good performance in controlling the combustion timing across a wide range. A semi-definite program is formulated to find a Lyapunov function for the switching model/control framework and shows that it is stable. As HCCI is dictated by the in-cylinder thermo-chemical conditions, there are further concerns about the robustness of HCCI, i.e., the boundedness of the thermo-chemical conditions with uncertainty existing in the ambient conditions and in the engine's own characteristics due to aging. To assess HCCI's robustness, this thesis presents a linear parameter varying (LPV) model that captures the dynamics of recompression HCCI and possesses an elegant model structure that is more amenable to analysis. Based on this model, a recursive algorithm using convex optimization is formulated to generate analytical statements about the boundedness of the in-cylinder thermo-chemical conditions. The bounds generated by the algorithm are also shown to relate well to the data from the experimental testbed.
Author: Yu Shi Publisher: Springer Science & Business Media ISBN: 0857296191 Category : Technology & Engineering Languages : en Pages : 323
Book Description
Computational Optimization of Internal Combustion Engines presents the state of the art of computational models and optimization methods for internal combustion engine development using multi-dimensional computational fluid dynamics (CFD) tools and genetic algorithms. Strategies to reduce computational cost and mesh dependency are discussed, as well as regression analysis methods. Several case studies are presented in a section devoted to applications, including assessments of: spark-ignition engines, dual-fuel engines, heavy duty and light duty diesel engines. Through regression analysis, optimization results are used to explain complex interactions between engine design parameters, such as nozzle design, injection timing, swirl, exhaust gas recirculation, bore size, and piston bowl shape. Computational Optimization of Internal Combustion Engines demonstrates that the current multi-dimensional CFD tools are mature enough for practical development of internal combustion engines. It is written for researchers and designers in mechanical engineering and the automotive industry.
Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
The nine CRC fuels for advanced combustion engines (FACE fuels) have been evaluated in a simple, premixed HCCI engine under varying conditions of fuel rate, air-fuel ratio, and intake temperature. Engine performance was found to vary mainly as a function of combustion phasing as affected by fuel cetane and engine control variables. The data was modeled using statistical techniques involving eigenvector representation of the fuel properties and engine control variables, to define engine response and allow optimization across the fuels for best fuel efficiency. In general, the independent manipulation of intake temperature and air-fuel ratio provided some opportunity for improving combustion efficiency of a specific fuel beyond the direct effect of targeting the optimum combustion phasing of the engine (near 5 CAD ATDC). High cetane fuels suffer performance loss due to easier ignition, resulting in lower intake temperatures, which increase HC and CO emissions and result in the need for more advanced combustion phasing. The FACE fuels also varied in T90 temperature and % aromatics, independent of cetane number. T90 temperature was found to have an effect on engine performance when combined with high centane, but % aromatics did not, when evaluated independently of cetane and T90.
Author: Jihad Badra Publisher: Elsevier ISBN: 032388458X Category : Technology & Engineering Languages : en Pages : 262
Book Description
Artificial Intelligence and Data Driven Optimization of Internal Combustion Engines summarizes recent developments in Artificial Intelligence (AI)/Machine Learning (ML) and data driven optimization and calibration techniques for internal combustion engines. The book covers AI/ML and data driven methods to optimize fuel formulations and engine combustion systems, predict cycle to cycle variations, and optimize after-treatment systems and experimental engine calibration. It contains all the details of the latest optimization techniques along with their application to ICE, making it ideal for automotive engineers, mechanical engineers, OEMs and R&D centers involved in engine design. Provides AI/ML and data driven optimization techniques in combination with Computational Fluid Dynamics (CFD) to optimize engine combustion systems Features a comprehensive overview of how AI/ML techniques are used in conjunction with simulations and experiments Discusses data driven optimization techniques for fuel formulations and vehicle control calibration
Author: Rolf Isermann Publisher: Springer ISBN: 3642399347 Category : Technology & Engineering Languages : en Pages : 646
Book Description
The increasing demands for internal combustion engines with regard to fuel consumption, emissions and driveability lead to more actuators, sensors and complex control functions. A systematic implementation of the electronic control systems requires mathematical models from basic design through simulation to calibration. The book treats physically-based as well as models based experimentally on test benches for gasoline (spark ignition) and diesel (compression ignition) engines and uses them for the design of the different control functions. The main topics are: - Development steps for engine control - Stationary and dynamic experimental modeling - Physical models of intake, combustion, mechanical system, turbocharger, exhaust, cooling, lubrication, drive train - Engine control structures, hardware, software, actuators, sensors, fuel supply, injection system, camshaft - Engine control methods, static and dynamic feedforward and feedback control, calibration and optimization, HiL, RCP, control software development - Control of gasoline engines, control of air/fuel, ignition, knock, idle, coolant, adaptive control functions - Control of diesel engines, combustion models, air flow and exhaust recirculation control, combustion-pressure-based control (HCCI), optimization of feedforward and feedback control, smoke limitation and emission control This book is an introduction to electronic engine management with many practical examples, measurements and research results. It is aimed at advanced students of electrical, mechanical, mechatronic and control engineering and at practicing engineers in the field of combustion engine and automotive engineering.
Author: Thivaharan Albin Rajasingham Publisher: Springer Nature ISBN: 303068010X Category : Technology & Engineering Languages : en Pages : 330
Book Description
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.
Author: Harald Waschl Publisher: Springer ISBN: 331905371X Category : Technology & Engineering Languages : en Pages : 334
Book Description
This book demonstrates the use of the optimization techniques that are becoming essential to meet the increasing stringency and variety of requirements for automotive systems. It shows the reader how to move away from earlier approaches, based on some degree of heuristics, to the use of more and more common systematic methods. Even systematic methods can be developed and applied in a large number of forms so the text collects contributions from across the theory, methods and real-world automotive applications of optimization. Greater fuel economy, significant reductions in permissible emissions, new drivability requirements and the generally increasing complexity of automotive systems are among the criteria that the contributing authors set themselves to meet. In many cases multiple and often conflicting requirements give rise to multi-objective constrained optimization problems which are also considered. Some of these problems fall into the domain of the traditional multi-disciplinary optimization applied to system, sub-system or component design parameters and is performed based on system models; others require applications of optimization directly to experimental systems to determine either optimal calibration or the optimal control trajectory/control law. Optimization and Optimal Control in Automotive Systems reflects the state-of-the-art in and promotes a comprehensive approach to optimization in automotive systems by addressing its different facets, by discussing basic methods and showing practical approaches and specific applications of optimization to design and control problems for automotive systems. The book will be of interest both to academic researchers, either studying optimization or who have links with the automotive industry and to industrially-based engineers and automotive designers.
Author: Nicholas J. Killingsworth
Author: Nicholas J. Killingsworth
Author: Rolf D. Reitz
Author: Hsien-Hsin Liao
Author: Yu Shi
Author: 
Author: Jihad Badra
Author: Rolf Isermann
Author: Thivaharan Albin Rajasingham
Author: Harald Waschl
Author: Kushal Narayanaswamy