Optimal Control of Hybrid Vehicles
Optimal Control of Hybrid Vehicles

Author: Bram de Jager

Publisher: Springer Science & Business Media

Published: 2013-04-05

Total Pages: 159

ISBN-13: 1447150767

DOWNLOAD EBOOK

Optimal Control of Hybrid Vehicles provides a description of power train control for hybrid vehicles. The background, environmental motivation and control challenges associated with hybrid vehicles are introduced. The text includes mathematical models for all relevant components in the hybrid power train. The power split problem in hybrid power trains is formally described and several numerical solutions detailed, including dynamic programming and a novel solution for state-constrained optimal control problems based on the maximum principle. Real-time-implementable strategies that can approximate the optimal solution closely are dealt with in depth. Several approaches are discussed and compared, including a state-of-the-art strategy which is adaptive for vehicle conditions like velocity and mass. Three case studies are included in the book: • a control strategy for a micro-hybrid power train; • experimental results obtained with a real-time strategy implemented in a hybrid electric truck; and • an analysis of the optimal component sizes for a hybrid power train. Optimal Control of Hybrid Vehicles will appeal to academic researchers and graduate students interested in hybrid vehicle control or in the applications of optimal control. Practitioners working in the design of control systems for the automotive industry will also find the ideas propounded in this book of interest.

Hybrid Systems, Optimal Control and Hybrid Vehicles
Hybrid Systems, Optimal Control and Hybrid Vehicles

Author: Thomas J. Böhme

Publisher: Springer

Published: 2017-02-01

Total Pages: 549

ISBN-13: 3319513176

DOWNLOAD EBOOK

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.

Hybrid Electric Vehicles
Hybrid Electric Vehicles

Author: Simona Onori

Publisher: Springer

Published: 2015-12-16

Total Pages: 121

ISBN-13: 1447167813

DOWNLOAD EBOOK

This SpringerBrief deals with the control and optimization problem in hybrid electric vehicles. Given that there are two (or more) energy sources (i.e., battery and fuel) in hybrid vehicles, it shows the reader how to implement an energy-management strategy that decides how much of the vehicle’s power is provided by each source instant by instant. Hybrid Electric Vehicles: •introduces methods for modeling energy flow in hybrid electric vehicles; •presents a standard mathematical formulation of the optimal control problem; •discusses different optimization and control strategies for energy management, integrating the most recent research results; and •carries out an overall comparison of the different control strategies presented. Chapter by chapter, a case study is thoroughly developed, providing illustrative numerical examples that show the basic principles applied to real-world situations. The brief is intended as a straightforward tool for learning quickly about state-of-the-art energy-management strategies. It is particularly well-suited to the needs of graduate students and engineers already familiar with the basics of hybrid vehicles but who wish to learn more about their control strategies.

Vehicle Propulsion Systems
Vehicle Propulsion Systems

Author: Lino Guzzella

Publisher: Springer Science & Business Media

Published: 2007-09-21

Total Pages: 345

ISBN-13: 3540746927

DOWNLOAD EBOOK

The authors of this text have written a comprehensive introduction to the modeling and optimization problems encountered when designing new propulsion systems for passenger cars. It is intended for persons interested in the analysis and optimization of vehicle propulsion systems. Its focus is on the control-oriented mathematical description of the physical processes and on the model-based optimization of the system structure and of the supervisory control algorithms.

Modeling and Control of Hybrid Propulsion System for Ground Vehicles
Modeling and Control of Hybrid Propulsion System for Ground Vehicles

Author: Yuan Zou

Publisher: Springer

Published: 2018-07-02

Total Pages: 331

ISBN-13: 3662536730

DOWNLOAD EBOOK

This book focuses on the systematic design of architectures, parameters and control of typical hybrid propulsion systems for wheeled and tracked vehicles based on a combination of theoretical research and engineering practice. Adopting a mechatronic system dynamics perspective, principles and methods from the fields of optimal control and system optimization are applied in order to analyze the hybrid propulsion configuration and controller design. Case investigations for typical hybrid propulsion systems of wheeled and tracked ground vehicles are also provided.

Vehicle Power Management
Vehicle Power Management

Author: Xi Zhang

Publisher: Springer Science & Business Media

Published: 2011-08-12

Total Pages: 353

ISBN-13: 0857297368

DOWNLOAD EBOOK

Vehicle Power Management addresses the challenge of improving vehicle fuel economy and reducing emissions without sacrificing vehicle performance, reliability and durability. It opens with the definition, objectives, and current research issues of vehicle power management, before moving on to a detailed introduction to the modeling of vehicle devices and components involved in the vehicle power management system, which has been proven to be the most cost-effective and efficient method for initial-phase vehicle research and design. Specific vehicle power management algorithms and strategies, including the analytical approach, optimal control, intelligent system approaches and wavelet technology, are derived and analyzed for realistic applications. Vehicle Power Management also gives a detailed description of several key technologies in the design phases of hybrid electric vehicles containing battery management systems, component optimization, hardware-in-the-loop and software-in-the-loop. Vehicle Power Management provides graduate and upper level undergraduate students, engineers, and researchers in both academia and the automotive industry, with a clear understanding of the concepts, methodologies, and prospects of vehicle power management.

Modelling, Dynamics and Control of Electrified Vehicles
Modelling, Dynamics and Control of Electrified Vehicles

Author: Haiping Du

Publisher: Woodhead Publishing Limited

Published: 2017-10

Total Pages: 520

ISBN-13: 9780128127865

DOWNLOAD EBOOK

Modelling, Dynamics and Control of Electrified Vehicles provides a systematic overview of EV-related key components, including batteries, electric motors, ultracapacitors and system-level approaches, such as energy management systems, multi-source energy optimization, transmission design and control, braking system control and vehicle dynamics control. In addition, the book covers selected advanced topics, including Smart Grid and connected vehicles. This book shows how EV work, how to design them, how to save energy with them, and how to maintain their safety. The book aims to be an all-in-one reference for readers who are interested in EVs, or those trying to understand its state-of-the-art technologies and future trends. Offers a comprehensive knowledge of the multidisciplinary research related to EVs and a system-level understanding of technologies Provides the state-of-the-art technologies and future trends Covers the fundamentals of EVs and their methodologies Written by successful researchers that show the deep understanding of EVs

Optimization and Optimal Control in Automotive Systems
Optimization and Optimal Control in Automotive Systems

Author: Harald Waschl

Publisher: Springer

Published: 2014-03-20

Total Pages: 334

ISBN-13: 331905371X

DOWNLOAD EBOOK

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.

Introduction to Hybrid Vehicle System Modeling and Control
Introduction to Hybrid Vehicle System Modeling and Control

Author: Wei Liu

Publisher: John Wiley & Sons

Published: 2013-02-08

Total Pages: 428

ISBN-13: 1118407393

DOWNLOAD EBOOK

This is an engineering reference book on hybrid vehicle system analysis and design, an outgrowth of the author's substantial work in research, development and production at the National Research Council Canada, Azure Dynamics and now General Motors. It is an irreplaceable tool for helping engineers develop algorithms and gain a thorough understanding of hybrid vehicle systems. This book covers all the major aspects of hybrid vehicle modeling, control, simulation, performance analysis and preliminary design. It not only systemically provides the basic knowledge of hybrid vehicle system configuration and main components, but also details their characteristics and mathematic models. Provides valuable technical expertise necessary for building hybrid vehicle system and analyzing performance via drivability, fuel economy and emissions Built from the author's industry experience at major vehicle companies including General Motors and Azure Dynamics Inc. Offers algorithm implementations and figures/examples extracted from actual practice systems Suitable for a training course on hybrid vehicle system development with supplemental materials An essential resource enabling hybrid development and design engineers to understand the hybrid vehicle systems necessary for control algorithm design and developments.

Proceedings of ELM 2018
Proceedings of ELM 2018

Author: Jiuwen Cao

Publisher: Springer

Published: 2019-06-29

Total Pages: 356

ISBN-13: 3030233073

DOWNLOAD EBOOK

This book contains some selected papers from the International Conference on Extreme Learning Machine 2018, which was held in Singapore, November 21–23, 2018. This conference provided a forum for academics, researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique and brain learning. Extreme Learning Machines (ELM) aims to enable pervasive learning and pervasive intelligence. As advocated by ELM theories, it is exciting to see the convergence of machine learning and biological learning from the long-term point of view. ELM may be one of the fundamental “learning particles” filling the gaps between machine learning and biological learning (of which activation functions are even unknown). ELM represents a suite of (machine and biological) learning techniques in which hidden neurons need not be tuned: inherited from their ancestors or randomly generated. ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series, etc.) as long as they are nonlinear piecewise continuous, independent of training data and application environments. Increasingly, evidence from neuroscience suggests that similar principles apply in biological learning systems. ELM theories and algorithms argue that “random hidden neurons” capture an essential aspect of biological learning mechanisms as well as the intuitive sense that the efficiency of biological learning need not rely on computing power of neurons. ELM theories thus hint at possible reasons why the brain is more intelligent and effective than current computers. The main theme of ELM2018 is Hierarchical ELM, AI for IoT, Synergy of Machine Learning and Biological Learning. This book covers theories, algorithms and applications of ELM. It gives readers a glance at the most recent advances of ELM.