Hybrid systems, optimal control and hybrid vehicles : theory, methods and applications / Thomas J. Böhme, Benjamin Frank.
Böhme, Thomas J., author.; Frank, Benjamin, author.
2017
TL221.15
Available Online

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Title Hybrid systems, optimal control and hybrid vehicles : theory, methods and applications / Thomas J. Böhme, Benjamin Frank.
Author Böhme, Thomas J., author.
ISBN 9783319513171 (electronic book)
3319513176 (electronic book)
9783319513157
331951315X
DOI https://doi.org/10.1007/978-3-319-51317-1
Published Cham, Switzerland : Springer, 2017.
Language English
Description 1 online resource.
Item Number 10.1007/978-3-319-51317-1 doi
Call Number TL221.15
Dewey Decimal Classification 629.22/93
Summary This book assembles new methods showing the automotive engineer for the first time how hybrid vehicle configurations can be modeled as systems with discrete and continuous controls. These hybrid systems describe naturally and compactly the networks of embedded systems which use elements such as integrators, hysteresis, state-machines and logical rules to describe the evolution of continuous and discrete dynamics and arise inevitably when modeling hybrid electric vehicles. They can throw light on systems which may otherwise be too complex or recondite. Hybrid Systems, Optimal Control and Hybrid Vehicles shows the reader how to formulate and solve control problems which satisfy multiple objectives which may be arbitrary and complex with contradictory influences on fuel consumption, emissions and drivability. The text introduces industrial engineers, postgraduates and researchers to the theory of hybrid optimal control problems. A series of novel algorithmic developments provides tools for solving engineering problems of growing complexity in the field of hybrid vehicles. Important topics of real relevance rarely found in text books and research publications?switching costs, sensitivity of discrete decisions and there impact on fuel savings, etc.?are discussed and supported with practical applications. These demonstrate the contribution of optimal hybrid control in predictive energy management, advanced powertrain calibration, and the optimization of vehicle configuration with respect to fuel economy, lowest emissions and smoothest drivability. Numerical issues such as computing resources, simplifications and stability are treated to enable readers to assess such complex systems. To help industrial engineers and managers with project decision-making, solutions for many important problems in hybrid vehicle control are provided in terms of requirements, benefits and risks. Advances in Industrial Control aims to report and encourage 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.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Digital File Characteristics text file PDF
Source of Description Online resource; title from PDF title page (SpringerLink, viewed February 10, 2017).
Added Author Frank, Benjamin, author.
Series Advances in industrial control.
Available in Other Form Print version: 9783319513157
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Series Editors' Foreword; Preface; Intended Readership; What are the Contributions of This Book; What is Not Covered in This Book; Structure of the Book; Acknowledgements; Contents; Abbreviations and Symbols; 1 Introduction; 1.1 Motivation, Challenges, and Objectives; 1.2 Vehicle Design Aspects; 1.2.1 Stages of Energy Conversion; 1.2.2 Real-World Driving Profile, Consumption, and Emissions; 1.3 Process Model, Control Strategy, and Optimization; 1.3.1 General Problem Statement; 1.3.2 Energy Management; 1.3.3 Numerical Solutions; 1.4 Bibliographical Notes; References.

Part I Theory and Formulations2 Introduction to Nonlinear Programming; 2.1 Introduction; 2.2 Unconstrained Nonlinear Optimization; 2.2.1 Necessary and Sufficient Conditions for Optimality; 2.2.2 Newton
Raphson Method; 2.2.3 Globalization of the Newton
Raphson Method; 2.2.4 Quasi-Newton Method; 2.3 Constrained Nonlinear Optimization; 2.3.1 Necessary and Sufficient Conditions for Optimality; 2.3.2 Projected Hessian; 2.3.3 Sequential Quadratic Programming; 2.4 Sensitivity Analysis; 2.4.1 Sensitivity Analysis of the Objective Function and Constraints; 2.4.2 Linear Perturbations.

2.4.3 Approximation of the Perturbed Solution2.4.4 Approximation of the Confidence Region; 2.5 Multi-Objective Optimization; 2.5.1 Elitist Multi-Objective Evolutionary Algorithm; 2.5.2 Remarks for MOGAs; 2.6 Bibliographical Notes; References; 3 Hybrid Systems and Hybrid Optimal Control; 3.1 Introduction; 3.2 System Definition; 3.2.1 Continuous Systems; 3.2.2 Hybrid Systems; 3.2.3 Controlled Hybrid Systems and Switched Systems; 3.2.4 Existence and Uniqueness of Admissible States and Controls; 3.2.5 Control and State Constraints, Admissible Sets, and Admissible Function Spaces.

3.2.6 Reformulation of Switched Systems3.3 Optimal Control Problem Formulations; 3.3.1 Functionals; 3.3.2 Boundary Conditions; 3.3.3 Continuous Optimal Control Problem; 3.3.4 Hybrid Optimal Control Problem; 3.3.5 Switched Optimal Control Problem; 3.3.6 Binary Switched Optimal Control Problem; 3.3.7 Transformations of Optimal Control Problems; 3.4 Bibliographical Notes; References; 4 The Minimum Principle and Hamilton
Jacobi
Bellman Equation; 4.1 Introduction; 4.1.1 The Calculus of Variations; 4.1.2 Deriving First-Order Necessary Conditions for an Extremum of an Optimal Control Problem.

4.2 Minimum Principle4.2.1 Necessary Conditions for Optimal Control Problems with Control Restraints; 4.2.2 Necessary Conditions for Optimal Control Problems with State Constraints; 4.2.3 Necessary Conditions for Optimal Control Problems with Affine Controls; 4.3 Hamilton
Jacobi
Bellman Equation; 4.4 Hybrid Minimum Principle; 4.4.1 Necessary Conditions for Switched Optimal Control Problems Without State Jumps; 4.4.2 Necessary Conditions for Switched Optimal Control Problems with State Jumps; 4.4.3 Revisited: Necessary Conditions for a State Constrained Optimal Control Problem; 4.5 Existence.

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