Nonlinear Model Predictive Control Of Combustion Engines

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Nonlinear Model Predictive Control of Combustion Engines

Author : Thivaharan Albin Rajasingham
Publisher : Springer Nature
ISBN 13 : 303068010X
Total Pages : 330 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Nonlinear Model Predictive Control of Combustion Engines by : Thivaharan Albin Rajasingham

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.

Automotive Model Predictive Control

Author : Luigi Del Re
Publisher : Springer Science & Business Media
ISBN 13 : 1849960704
Total Pages : 291 pages
Book Rating : 4.8/5 (499 download)

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Book Synopsis Automotive Model Predictive Control by : Luigi Del Re

Download or read book Automotive Model Predictive Control written by Luigi Del Re and published by Springer Science & Business Media. This book was released on 2010-03-11 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automotive control has developed over the decades from an auxiliary te- nology to a key element without which the actual performances, emission, safety and consumption targets could not be met. Accordingly, automotive control has been increasing its authority and responsibility – at the price of complexity and di?cult tuning. The progressive evolution has been mainly ledby speci?capplicationsandshorttermtargets,withthe consequencethat automotive control is to a very large extent more heuristic than systematic. Product requirements are still increasing and new challenges are coming from potentially huge markets like India and China, and against this ba- ground there is wide consensus both in the industry and academia that the current state is not satisfactory. Model-based control could be an approach to improve performance while reducing development and tuning times and possibly costs. Model predictive control is a kind of model-based control design approach which has experienced a growing success since the middle of the 1980s for “slow” complex plants, in particular of the chemical and process industry. In the last decades, severaldevelopments haveallowedusing these methods also for “fast”systemsandthis hassupporteda growinginterestinitsusealsofor automotive applications, with several promising results reported. Still there is no consensus on whether model predictive control with its high requi- ments on model quality and on computational power is a sensible choice for automotive control.

Nonlinear Model Predictive Control

Author : Frank Allgöwer
Publisher : Birkhäuser
ISBN 13 : 3034884079
Total Pages : 463 pages
Book Rating : 4.0/5 (348 download)

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Book Synopsis Nonlinear Model Predictive Control by : Frank Allgöwer

Download or read book Nonlinear Model Predictive Control written by Frank Allgöwer and published by Birkhäuser. This book was released on 2012-12-06 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the past decade model predictive control (MPC), also referred to as receding horizon control or moving horizon control, has become the preferred control strategy for quite a number of industrial processes. There have been many significant advances in this area over the past years, one of the most important ones being its extension to nonlinear systems. This book gives an up-to-date assessment of the current state of the art in the new field of nonlinear model predictive control (NMPC). The main topic areas that appear to be of central importance for NMPC are covered, namely receding horizon control theory, modeling for NMPC, computational aspects of on-line optimization and application issues. The book consists of selected papers presented at the International Symposium on Nonlinear Model Predictive Control – Assessment and Future Directions, which took place from June 3 to 5, 1998, in Ascona, Switzerland. The book is geared towards researchers and practitioners in the area of control engineering and control theory. It is also suited for postgraduate students as the book contains several overview articles that give a tutorial introduction into the various aspects of nonlinear model predictive control, including systems theory, computations, modeling and applications.

Assessment and Future Directions of Nonlinear Model Predictive Control

Author : Rolf Findeisen
Publisher : Springer
ISBN 13 : 3540726993
Total Pages : 644 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Assessment and Future Directions of Nonlinear Model Predictive Control by : Rolf Findeisen

Download or read book Assessment and Future Directions of Nonlinear Model Predictive Control written by Rolf Findeisen and published by Springer. This book was released on 2007-09-08 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thepastthree decadeshaveseenrapiddevelopmentin the areaofmodelpred- tive control with respect to both theoretical and application aspects. Over these 30 years, model predictive control for linear systems has been widely applied, especially in the area of process control. However, today’s applications often require driving the process over a wide region and close to the boundaries of - erability, while satisfying constraints and achieving near-optimal performance. Consequently, the application of linear control methods does not always lead to satisfactory performance, and here nonlinear methods must be employed. This is one of the reasons why nonlinear model predictive control (NMPC) has - joyed signi?cant attention over the past years,with a number of recent advances on both the theoretical and application frontier. Additionally, the widespread availability and steadily increasing power of today’s computers, as well as the development of specially tailored numerical solution methods for NMPC, bring thepracticalapplicabilityofNMPCwithinreachevenforveryfastsystems.This has led to a series of new, exciting developments, along with new challenges in the area of NMPC.

Nonlinear Systems and Circuits in Internal Combustion Engines

Author : Ferdinando Taglialatela-Scafati
Publisher : Springer
ISBN 13 : 3319671405
Total Pages : 80 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Nonlinear Systems and Circuits in Internal Combustion Engines by : Ferdinando Taglialatela-Scafati

Download or read book Nonlinear Systems and Circuits in Internal Combustion Engines written by Ferdinando Taglialatela-Scafati and published by Springer. This book was released on 2017-10-31 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Automotive Model Predictive Control

Author : Luigi Del Re
Publisher : Springer
ISBN 13 : 1849960712
Total Pages : 290 pages
Book Rating : 4.8/5 (499 download)

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Book Synopsis Automotive Model Predictive Control by : Luigi Del Re

Download or read book Automotive Model Predictive Control written by Luigi Del Re and published by Springer. This book was released on 2010-03-11 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automotive control has developed over the decades from an auxiliary te- nology to a key element without which the actual performances, emission, safety and consumption targets could not be met. Accordingly, automotive control has been increasing its authority and responsibility – at the price of complexity and di?cult tuning. The progressive evolution has been mainly ledby speci?capplicationsandshorttermtargets,withthe consequencethat automotive control is to a very large extent more heuristic than systematic. Product requirements are still increasing and new challenges are coming from potentially huge markets like India and China, and against this ba- ground there is wide consensus both in the industry and academia that the current state is not satisfactory. Model-based control could be an approach to improve performance while reducing development and tuning times and possibly costs. Model predictive control is a kind of model-based control design approach which has experienced a growing success since the middle of the 1980s for “slow” complex plants, in particular of the chemical and process industry. In the last decades, severaldevelopments haveallowedusing these methods also for “fast”systemsandthis hassupporteda growinginterestinitsusealsofor automotive applications, with several promising results reported. Still there is no consensus on whether model predictive control with its high requi- ments on model quality and on computational power is a sensible choice for automotive control.

Model Predictive Control

Author : Eduardo F. Camacho
Publisher : Springer Science & Business Media
ISBN 13 : 0857293982
Total Pages : 405 pages
Book Rating : 4.8/5 (572 download)

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Book Synopsis Model Predictive Control by : Eduardo F. Camacho

Download or read book Model Predictive Control written by Eduardo F. Camacho and published by Springer Science & Business Media. This book was released on 2013-01-10 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of "Model Predictive Control" provides a thorough introduction to theoretical and practical aspects of the most commonly used MPC strategies. It bridges the gap between the powerful but often abstract techniques of control researchers and the more empirical approach of practitioners. The book demonstrates that a powerful technique does not always require complex control algorithms. Many new exercises and examples have also been added throughout. Solutions available for download from the authors' website save the tutor time and enable the student to follow results more closely even when the tutor isn't present.

Advances in Applied Nonlinear Optimal Control

Author : Gerasimos Rigatos
Publisher : Cambridge Scholars Publishing
ISBN 13 : 1527562468
Total Pages : 741 pages
Book Rating : 4.5/5 (275 download)

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Book Synopsis Advances in Applied Nonlinear Optimal Control by : Gerasimos Rigatos

Download or read book Advances in Applied Nonlinear Optimal Control written by Gerasimos Rigatos and published by Cambridge Scholars Publishing. This book was released on 2020-11-19 with total page 741 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume discusses advances in applied nonlinear optimal control, comprising both theoretical analysis of the developed control methods and case studies about their use in robotics, mechatronics, electric power generation, power electronics, micro-electronics, biological systems, biomedical systems, financial systems and industrial production processes. The advantages of the nonlinear optimal control approaches which are developed here are that, by applying approximate linearization of the controlled systems’ state-space description, one can avoid the elaborated state variables transformations (diffeomorphisms) which are required by global linearization-based control methods. The book also applies the control input directly to the power unit of the controlled systems and not on an equivalent linearized description, thus avoiding the inverse transformations met in global linearization-based control methods and the potential appearance of singularity problems. The method adopted here also retains the known advantages of optimal control, that is, the best trade-off between accurate tracking of reference setpoints and moderate variations of the control inputs. The book’s findings on nonlinear optimal control are a substantial contribution to the areas of nonlinear control and complex dynamical systems, and will find use in several research and engineering disciplines and in practical applications.

Introduction to Modeling and Control of Internal Combustion Engine Systems

Author : Lino Guzzella
Publisher : Springer Science & Business Media
ISBN 13 : 3662080036
Total Pages : 303 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Introduction to Modeling and Control of Internal Combustion Engine Systems by : Lino Guzzella

Download or read book Introduction to Modeling and Control of Internal Combustion Engine Systems written by Lino Guzzella and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Nonlinear Industrial Control Systems

Author : Michael J. Grimble
Publisher : Springer Nature
ISBN 13 : 1447174577
Total Pages : 778 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Nonlinear Industrial Control Systems by : Michael J. Grimble

Download or read book Nonlinear Industrial Control Systems written by Michael J. Grimble and published by Springer Nature. This book was released on 2020-05-19 with total page 778 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear Industrial Control Systems presents a range of mostly optimisation-based methods for severely nonlinear systems; it discusses feedforward and feedback control and tracking control systems design. The plant models and design algorithms are provided in a MATLAB® toolbox that enable both academic examples and industrial application studies to be repeated and evaluated, taking into account practical application and implementation problems. The text makes nonlinear control theory accessible to readers having only a background in linear systems, and concentrates on real applications of nonlinear control. It covers: different ways of modelling nonlinear systems including state space, polynomial-based, linear parameter varying, state-dependent and hybrid; design techniques for nonlinear optimal control including generalised-minimum-variance, model predictive control, quadratic-Gaussian, factorised and H∞ design methods; design philosophies that are suitable for aerospace, automotive, marine, process-control, energy systems, robotics, servo systems and manufacturing; steps in design procedures that are illustrated in design studies to define cost-functions and cope with problems such as disturbance rejection, uncertainties and integral wind-up; and baseline non-optimal control techniques such as nonlinear Smith predictors, feedback linearization, sliding mode control and nonlinear PID. Nonlinear Industrial Control Systems is valuable to engineers in industry dealing with actual nonlinear systems. It provides students with a comprehensive range of techniques and examples for solving real nonlinear control design problems.

Engine Modeling and Control

Author : Rolf Isermann
Publisher : Springer
ISBN 13 : 3642399347
Total Pages : 637 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Engine Modeling and Control by : Rolf Isermann

Download or read book Engine Modeling and Control written by Rolf Isermann and published by Springer. This book was released on 2014-07-01 with total page 637 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Handbook of Model Predictive Control

Author : Saša V. Raković
Publisher : Springer
ISBN 13 : 3319774891
Total Pages : 692 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Handbook of Model Predictive Control by : Saša V. Raković

Download or read book Handbook of Model Predictive Control written by Saša V. Raković and published by Springer. This book was released on 2018-09-01 with total page 692 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent developments in model-predictive control promise remarkable opportunities for designing multi-input, multi-output control systems and improving the control of single-input, single-output systems. This volume provides a definitive survey of the latest model-predictive control methods available to engineers and scientists today. The initial set of chapters present various methods for managing uncertainty in systems, including stochastic model-predictive control. With the advent of affordable and fast computation, control engineers now need to think about using “computationally intensive controls,” so the second part of this book addresses the solution of optimization problems in “real” time for model-predictive control. The theory and applications of control theory often influence each other, so the last section of Handbook of Model Predictive Control rounds out the book with representative applications to automobiles, healthcare, robotics, and finance. The chapters in this volume will be useful to working engineers, scientists, and mathematicians, as well as students and faculty interested in the progression of control theory. Future developments in MPC will no doubt build from concepts demonstrated in this book and anyone with an interest in MPC will find fruitful information and suggestions for additional reading.

Advanced Model Predictive Control

Author : Tao Zheng
Publisher : BoD – Books on Demand
ISBN 13 : 9533072989
Total Pages : 434 pages
Book Rating : 4.5/5 (33 download)

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Book Synopsis Advanced Model Predictive Control by : Tao Zheng

Download or read book Advanced Model Predictive Control written by Tao Zheng and published by BoD – Books on Demand. This book was released on 2011-07-05 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Predictive Control (MPC) refers to a class of control algorithms in which a dynamic process model is used to predict and optimize process performance. From lower request of modeling accuracy and robustness to complicated process plants, MPC has been widely accepted in many practical fields. As the guide for researchers and engineers all over the world concerned with the latest developments of MPC, the purpose of "Advanced Model Predictive Control" is to show the readers the recent achievements in this area. The first part of this exciting book will help you comprehend the frontiers in theoretical research of MPC, such as Fast MPC, Nonlinear MPC, Distributed MPC, Multi-Dimensional MPC and Fuzzy-Neural MPC. In the second part, several excellent applications of MPC in modern industry are proposed and efficient commercial software for MPC is introduced. Because of its special industrial origin, we believe that MPC will remain energetic in the future.

Nonlinear Predictive Control Using Wiener Models

Author : Maciej Ławryńczuk
Publisher : Springer Nature
ISBN 13 : 3030838153
Total Pages : 358 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Nonlinear Predictive Control Using Wiener Models by : Maciej Ławryńczuk

Download or read book Nonlinear Predictive Control Using Wiener Models written by Maciej Ławryńczuk and published by Springer Nature. This book was released on 2021-09-21 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents computationally efficient MPC solutions. The classical model predictive control (MPC) approach to control dynamical systems described by the Wiener model uses an inverse static block to cancel the influence of process nonlinearity. Unfortunately, the model's structure is limited, and it gives poor control quality in the case of an imperfect model and disturbances. An alternative is to use the computationally demanding MPC scheme with on-line nonlinear optimisation repeated at each sampling instant. A linear approximation of the Wiener model or the predicted trajectory is found on-line. As a result, quadratic optimisation tasks are obtained. Furthermore, parameterisation using Laguerre functions is possible to reduce the number of decision variables. Simulation results for ten benchmark processes show that the discussed MPC algorithms lead to excellent control quality. For a neutralisation reactor and a fuel cell, essential advantages of neural Wiener models are demonstrated.

Simulation Techniques for Applied Dynamics

Author : Martin Arnold
Publisher : Springer Science & Business Media
ISBN 13 : 3211895485
Total Pages : 382 pages
Book Rating : 4.2/5 (118 download)

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Book Synopsis Simulation Techniques for Applied Dynamics by : Martin Arnold

Download or read book Simulation Techniques for Applied Dynamics written by Martin Arnold and published by Springer Science & Business Media. This book was released on 2009-06-15 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: The coupling of models from different physical domains and the efficient and reliable simulation of multidisciplinary problems in engineering applications are important topics for various fields of engineering, in simulation technology and in the development and analysis of numerical solvers. The volume presents advanced modelling and simulation techniques for the dynamical analysis of coupled engineering systems consisting of mechanical, electrical, hydraulic and biological components as well as control devices often based on computer hardware and software. The book starts with some basics in multibody dynamics and in port-based modelling and focuses on the modelling and simulation of heterogeneous systems with special emphasis on robust and efficient numerical solution techniques and on a variety of applied problems including case studies of co-simulation in industrial applications, methods and problems of model based controller design and real-time application.

Nonlinear Estimation and Control of Automotive Drivetrains

Author : Hong Chen
Publisher : Springer Science & Business Media
ISBN 13 : 3642415725
Total Pages : 250 pages
Book Rating : 4.6/5 (424 download)

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Book Synopsis Nonlinear Estimation and Control of Automotive Drivetrains by : Hong Chen

Download or read book Nonlinear Estimation and Control of Automotive Drivetrains written by Hong Chen and published by Springer Science & Business Media. This book was released on 2013-12-30 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear Estimation and Control of Automotive Drivetrains discusses the control problems involved in automotive drivetrains, particularly in hydraulic Automatic Transmission (AT), Dual Clutch Transmission (DCT) and Automated Manual Transmission (AMT). Challenging estimation and control problems, such as driveline torque estimation and gear shift control, are addressed by applying the latest nonlinear control theories, including constructive nonlinear control (Backstepping, Input-to-State Stable) and Model Predictive Control (MPC). The estimation and control performance is improved while the calibration effort is reduced significantly. The book presents many detailed examples of design processes and thus enables the readers to understand how to successfully combine purely theoretical methodologies with actual applications in vehicles. The book is intended for researchers, PhD students, control engineers and automotive engineers. Hong Chen is a professor at the State Key Laboratory of Automotive Simulation and Control, and the Department of Control Science and Engineering at Jilin University. Bingzhao Gao is an associate professor at the State Key Laboratory of Automotive Simulation and Control at Jilin University.

Artificial Intelligence and Data Driven Optimization of Internal Combustion Engines

Author : Jihad Badra
Publisher : Elsevier
ISBN 13 : 032388458X
Total Pages : 262 pages
Book Rating : 4.3/5 (238 download)

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Book Synopsis Artificial Intelligence and Data Driven Optimization of Internal Combustion Engines by : Jihad Badra

Download or read book Artificial Intelligence and Data Driven Optimization of Internal Combustion Engines written by Jihad Badra and published by Elsevier. This book was released on 2022-01-05 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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