Download or read book Adaptive Model Predictive Control of Diesel Engine Selective Catalytic Reduction Scr Systems written by and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Distributed Parameter Control of Selective Catalytic Reduction SCR for Diesel powered Vehicles written by Hallas Pakravesh and published by . This book was released on 2013 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main scope of this work is to design a distributed parameter control for SCR, which is modelled by using coupled hyperbolic and parabolic partial differential equations (PDEs). This is a boundary control problem where the control objectives are to reduce the amount of NO[subscript x] emissions and ammonia slip as far as possible. Two strategies are used to control SCR. The first strategy includes using the direct transcription (DT) as the open-loop control technique. The second strategy includes the design of a closed-loop control technique that uses a new numerical method developed in this work, which combines the method of characteristics and spectral decomposition, and the characteristic-based nonlinear model predictive control (CBNMPC) as the control algorithm. The results show that the designed advanced controllers are able to achieve very high control performance in terms of NO[subscript x] and ammonia slip reduction.

Download or read book Implementing Improved Model Predictive Control of Selective Catalytic Reduction written by Jonathan Sowman and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Implementing Improved Model Predictive Control of Selective Catalytic Reduction written by Jonathan A. Sowman and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Issues in Robotics and Automation 2013 Edition written by and published by ScholarlyEditions. This book was released on 2013-05-01 with total page 1196 pages. Available in PDF, EPUB and Kindle. Book excerpt: Issues in Robotics and Automation / 2013 Edition is a ScholarlyEditions™ book that delivers timely, authoritative, and comprehensive information about Computing Information and Control. The editors have built Issues in Robotics and Automation: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Computing Information and Control in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Robotics and Automation: 2013 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Download or read book Fundamentals of Medium Heavy Duty Diesel Engines written by Gus Wright and published by Jones & Bartlett Learning. This book was released on 2021-09-30 with total page 1895 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Fundamentals of Medium/Heavy Duty Diesel Engines, Second Edition offers comprehensive coverage of every ASE task with clarity and precision in a concise format that ensures student comprehension and encourages critical thinking. This edition describes safe and effective diagnostic, repair, and maintenance procedures for today's medium and heavy vehicle diesel engines"--

Download or read book Control of Diesel Engine Urea Selective Catalytic Reduction Systems written by Ming-Feng Hsieh and published by . This book was released on 2010 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: A systematic nonlinear control methodology for urea-SCR systems applicable for light-to-heavy-duty Diesel engine platforms in a variety of on-road, off-road, and marine applications is developed and experimentally validated in this dissertation. Urea selective catalytic reduction (urea-SCR) systems have been proved of being able to reduce more than 90% of Diesel engine-out NOx emissions and have been favored by the automotive industry in recent years. Urea-SCR systems utilize ammonia, converted from 32.5% aqueous urea solution (AdBlue) injected at upstream of the SCR catalyst, as the reductant for NOx reductions. Because ammonia is considered a hazardous material, urea injection should be systematically controlled to avoid undesired tailpipe ammonia slip while achieving a sufficient level of SCR NOx reduction. The novelty of the control methodology is to regulate the ammonia storage distribution along the axial direction of a SCR catalyst to a staircase profile and thus to simultaneously realize high NOx reduction efficiency and low ammonia emissions. To achieve this control objective, several relevant subjects are studied, including: 1) aftertreatment system control-oriented modeling, 2) online NOx sensor ammonia cross-sensitivity correction, 3) SCR catalyst ammonia coverage ratio estimation, as well as 4) adaptive urea dosing controller design. A unique SCR system which consists of a urea injector and two SCR catalysts connected in-series with several NOx and NH3 sensors is used for the study of the proposed urea-SCR control methodology. Such a SCR system is integrated with a state-of-the-art Diesel engine and aftertreatment system (DOC-DPF). The US06 test cycle experimental results show the proposed control methodology, in comparison to a conventional control strategy, is capable of improving the SCR NOx reduction by 63% and reducing the tailpipe ammonia slip amount by 74%. The contributions of this research to the art include: 1) A novel, efficient, and generalizable urea-SCR dosing control methodology; 2) Diesel engine-DOC-DPF NO/NO2 ratio control-oriented models and observer-based estimations; 3) SCR catalyst ammonia coverage ratio estimation methods; 4) An online correction approach for NOx sensor ammonia cross-sensitivity elimination; and 5) An improved SCR control-oriented model.

Download or read book Nonlinear Model Predictive Control of Combustion Engines written by Thivaharan Albin Rajasingham and published by Springer Nature. This book was released on 2021-04-27 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Robust Gain Scheduled Estimation and Control of Electrified Vehicles via LPV Technique written by Hui Zhang and published by Springer Nature. This book was released on 2023-06-10 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents techniques such as the robust control and nonlinearity approximation using linear-parameter-varying (LPV) techniques. Meanwhile, the control of independently driven electric vehicles and autonomous vehicles is introduced. It covers a comprehensive literature review, robust state estimation with uncertain measurements, sideslip angle estimation with finite-frequency optimization, fault detection of vehicle steering systems, output-feedback control of in-wheel motor-driven electric vehicles, robust path following control with network-induced issues, and lateral motion control with the consideration of actuator saturation. This book is a good reference for researchers and engineers working on control of electric vehicles.

Download or read book Spark Ignition Engine Modeling and Control System Design written by Amir-Mohammad Shamekhi and published by CRC Press. This book was released on 2023-02-22 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a step-by-step guide to the engine control system design, providing case studies and a thorough analysis of the modeling process using machine learning, and model predictive control (MPC). Covering advanced processes alongside the theoretical foundation, MPC enables engineers to improve performance in both hybrid and non-hybrid vehicles. Control system improvement is one of the major priorities for engineers seeking to enhance an engine. Often possible on a low budget, substantial improvements can be made by applying cutting-edge methods, such as artificial intelligence when modeling engine control system designs and using MPC. This book presents approaches to control system improvement at mid, low, and high levels of control. Beginning with the model-in-the-loop hierarchical control design of ported fuel injection SI engines, this book focuses on optimal control of both transient and steady state and also discusses hardware-in-the-loop. The chapter on low-level control discusses adaptive MPC and adaptive variable functioning, as well as designing a fuel injection feed-forward controller. At mid-level control, engine calibration maps are discussed, with consideration of constraints such as limits on pollutant emissions. Finally, the high-level control methodology is discussed in detail in relation to transient torque control of SI engines. This comprehensive yet clear guide to control system improvement is an essential read for any engineer working in automotive engineering and engine control system design.

Download or read book New Directions on Model Predictive Control written by Jinfeng Liu and published by MDPI. This book was released on 2019-01-16 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "New Directions on Model Predictive Control" that was published in Mathematics

Download or read book Applications of Model Predictive Control to Vehicle Dynamics for Active Safety and Stability written by Craig Earl Beal and published by Stanford University. This book was released on 2011 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Each year in the United States, thousands of lives are lost as a result of loss of control crashes. Production driver assistance systems such as electronic stability control (ESC) have been shown to be highly effective in preventing many of these automotive crashes, yet these systems rely on a sensor suite that yields limited information about the road conditions and vehicle motion. Furthermore, ESC systems rely on gains and thresholds that are tuned to yield good performance without feeling overly restrictive to the driver. This dissertation presents an alternative approach to providing stabilization assistance to the driver which leverages additional information about the vehicle and road that may be obtained with advanced estimation techniques. This new approach is based on well-known and robust vehicle models and utilizes phase plane analysis techniques to describe the limits of stable vehicle handling, alleviating the need for hand tuning of gains and thresholds. The resulting state space within the computed handling boundaries is referred to as a safe handling envelope. In addition to the boundaries being straightforward to calculate, this approach has the benefit of offering a way for the designer of the system to directly adjust the controller to accomodate the preferences of different drivers. A model predictive control structure capable of keeping the vehicle within the safe handling boundaries is the final component of the envelope control system. This dissertation presents the design of a controller that is capable of smoothly and progressively augmenting the driver steering input to enforce the boundaries of the envelope. The model predictive control formulation provides a method for making trade-offs between enforcing the boundaries of the envelope, minimizing disruptive interventions, and tracking the driver's intended trajectory. Experiments with a steer-by-wire test vehicle demonstrate that the model predictive envelope control system is capable of operating in conjunction with a human driver to prevent loss of control of the vehicle while yielding a predictable vehicle trajectory. These experiments considered both the ideal case of state information from a GPS/INS system and an a priori friction estimate as well as a real-world implementation estimating the vehicle states and friction coefficient from steering effort and inertial sensors. Results from the experiments demonstrated a controller that is tolerant of vehicle and tire parameterization errors and works well over a wide range of conditions. When real time sensing of the states and friction properties is enabled, the results show that coupling of the controller and estimator is possible and the model predictive control structure provides a mechanism for minimizing undesirable coupled dynamics through tuning of intuitive controller parameters. The model predictive control structure presented in this dissertation may also be considered as a general framework for vehicle control in conjunction with a human driver. The structure utilized for envelope control may also be used to restrict other vehicle states for safety and stability. Results are presented in this dissertation to show that a model predictive controller can coordinate a secondary actuator to alter the planar states and reduce the energy transferred into the roll modes of the vehicle. The systematic approach to vehicle stabilization presented in this dissertation has the potential to improve the design methodology for future systems and form the basis for the inclusion of more advanced functions as sensing and computing capabilities improve. The envelope control system presented here offers the opportunity to advance the state of the art in stabilization assistance and provides a way to help drivers of all skill levels maintain control of their vehicle.

Download or read book Modeling and Control of a Hydrocarbon Selective Catalytic Reduction System for Diesel Exhaust written by Oliver Rivera and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Diesel vehicles are continually being regulated each year by tighter restrictions on exhaust emissions. Nitrogen Oxides (NOx) form one of the more difficult emissions to control. Urea based selective catalytic reduction (SCR) of NOx emissions is an evolving technology that has seen widespread implementation on over the road vehicles. However, this technology requires an on-board reductant to function properly. Hydrocarbon based SCR (HC-SCR) technology eliminates the need for an additional on-board liquid by using diesel fuel as the reductant. A review of aftertreatment systems including HC-SCR is provided in this work. This review is followed by an experimental investigation of an HC-SCR aftertreatment system fitted to a marine diesel engine. A model of the HC-SCR outlet NOx concentration is developed and validated for several operating conditions. A sensitivity analysis of the model parameters is performed, demonstrating the most influential model parameters. A controller is successfully implemented in simulation and in the laboratory environment.

Download or read book A Model based Method for Optimising Emissions of Diesel Engines Through Non linear Model Predictive Control written by Xiaoming Wang and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Modelling and Observation of Exhaust Gas Concentrations for Diesel Engine Control written by Dr.-Ing. David Blanco-Rodriguez and published by Springer. This book was released on 2014-05-19 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a complete new methodology for the on-board measurements and modeling of gas concentrations in turbocharged diesel engines. It provides the readers with a comprehensive review of the state-of-art in NOx and lambda estimation and describes new important achievements accomplished by the author. These include: the online characterization of lambda and NOx sensors; the development of control-oriented models of lambda and NOx emissions; the design of computationally efficient updating algorithms; and, finally, the application and evaluation of the methods on-board. Because of its technically oriented approach and innovative findings on both control-oriented algorithms and virtual sensing and observation, this book offers a practice-oriented guide for students, researchers and professionals working in the field of control and information engineering.

Download or read book Advanced Hybrid Powertrains for Commercial Vehicles written by Haoran Hu and published by SAE International. This book was released on 2021-04-14 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Powertrains for commercial vehicles have evolved since the late nineteenth-century invention of the ICE. In the revised second edition of Advanced Hybrid Powertrains for Commercial Vehicles, the authors explore commercial powertrains through history from the ICE through the introduction of the hybrid powertrain in commercial vehicles. Readers are given an understanding of the ICE as well as the classification of commercial vehicle hybrid powertrains, the variety of energy storage systems, fuel-cell hybrid powertrain systems, and commercial vehicle electrification. The authors review the legislation of vehicle emissions and the regulation necessary to promote the production of fuel-efficient vehicles.

Download or read book Adaptive Learning and Robust Model Predictive Control for Uncertain Dynamic Systems written by Kunwu Zhang and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent decades have witnessed the phenomenal success of model predictive control (MPC) in a wide spectrum of domains, such as process industries, intelligent transportation, automotive applications, power systems, cyber security, and robotics. For constrained dynamic systems subject to uncertainties, robust MPC is attractive due to its capability of effectively dealing with various types of uncertainties while ensuring optimal performance concerning prescribed performance indices. But most robust MPC schemes require prior knowledge on the uncertainty, which may not be satisfied in practical applications. Therefore, it is desired to design robust MPC algorithms that proactively update the uncertainty description based on the history of inputs and measurements, motivating the development of adaptive MPC. This dissertation investigates four problems in robust and adaptive MPC from theoretical and application points of view. New algorithms are developed to address these issues efficiently with theoretical guarantees of closed-loop performance. Chapter 1 provides an overview of robust MPC, adaptive MPC, and self-triggered MPC, where the recent advances in these fields are reviewed. Chapter 2 presents notations and preliminary results that are used in this dissertation. Chapter 3 investigates adaptive MPC for a class of constrained linear systems with unknown model parameters. Based on the recursive least-squares (RLS) technique, we design an online set-membership system identification scheme to estimate unknown parameters. Then a novel integration of the proposed estimator and homothetic tube MPC is developed to improve closed-loop performance and reduce conservatism. In Chapter 4, a self-triggered adaptive MPC method is proposed for constrained discrete-time nonlinear systems subject to parametric uncertainties and additive disturbances. Based on the zonotope-based reachable set computation, a set-membership parameter estimator is developed to refine a set-valued description of the time-varying parametric uncertainty under the self-triggered scheduling. We leverage this estimation scheme to design a novel self-triggered adaptive MPC approach for uncertain nonlinear systems. The resultant adaptive MPC method can reduce the average sampling frequency further while preserving comparable closed-loop performance compared with the periodic adaptive MPC method. Chapter 5 proposes a robust nonlinear MPC scheme for the visual servoing of quadrotors subject to external disturbances. By using the virtual camera approach, an image-based visual servoing (IBVS) system model is established with decoupled image kinematics and quadrotor dynamics. A robust MPC scheme is developed to maintain the visual target stay within the field of view of the camera, where the tightened state constraints are constructed based on the Lipschitz condition to tackle external disturbances. In Chapter 6, an adaptive MPC scheme is proposed for the trajectory tracking of perturbed autonomous ground vehicles (AGVs) subject to input constraints. We develop an RLS-based set-membership based parameter to improve the prediction accuracy. In the proposed adaptive MPC scheme, a robustness constraint is designed to handle parametric and additive uncertainties. The proposed constraint has the offline computed shape and online updated shrinkage rate, leading to further reduced conservatism and slightly increased computational complexity compared with the robust MPC methods. Chapter 7 shows some conclusion remarks and future research directions.