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About this book

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.

Table of Contents

Frontmatter

2017 | OriginalPaper | Chapter

Chapter 1. Introduction

Thomas J. Böhme, Benjamin Frank

Theory and Formulations

Frontmatter

2017 | OriginalPaper | Chapter

Chapter 2. Introduction to Nonlinear Programming

Thomas J. Böhme, Benjamin Frank

2017 | OriginalPaper | Chapter

Chapter 3. Hybrid Systems and Hybrid Optimal Control

Thomas J. Böhme, Benjamin Frank

2017 | OriginalPaper | Chapter

Chapter 4. The Minimum Principle and Hamilton–Jacobi–Bellman Equation

Thomas J. Böhme, Benjamin Frank

Methods for Optimal Control

Frontmatter

2017 | OriginalPaper | Chapter

Chapter 5. Discretization and Integration Schemes for Hybrid Optimal Control Problems

Thomas J. Böhme, Benjamin Frank

2017 | OriginalPaper | Chapter

Chapter 6. Dynamic Programming

Thomas J. Böhme, Benjamin Frank

2017 | OriginalPaper | Chapter

Chapter 7. Indirect Methods for Optimal Control

Thomas J. Böhme, Benjamin Frank

2017 | OriginalPaper | Chapter

Chapter 8. Direct Methods for Optimal Control

Thomas J. Böhme, Benjamin Frank

Numerical Implementations

Frontmatter

2017 | OriginalPaper | Chapter

Chapter 9. Practical Implementation Aspects of Large-Scale Optimal Control Solvers

Thomas J. Böhme, Benjamin Frank

Modeling of Hybrid Vehicles for Control

Frontmatter

2017 | OriginalPaper | Chapter

Chapter 10. Modeling Hybrid Vehicles as Switched Systems

Thomas J. Böhme, Benjamin Frank

Applications

Frontmatter

2017 | OriginalPaper | Chapter

Chapter 11. Advanced Vehicle Calibration

Thomas J. Böhme, Benjamin Frank

2017 | OriginalPaper | Chapter

Chapter 12. Predictive Real-Time Energy Management

Thomas J. Böhme, Benjamin Frank

2017 | OriginalPaper | Chapter

Chapter 13. Optimal Design of Hybrid Powertrain Configurations

Thomas J. Böhme, Benjamin Frank

Appendix

Frontmatter

2017 | OriginalPaper | Chapter

Chapter 14. Graph Theoretical Fundamentals for Sparse Matrices

Thomas J. Böhme, Benjamin Frank

Backmatter

Additional information

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