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Author: Brian Su-Ming Fan
Publisher:
ISBN:
Category :
Languages : en
Pages : 146
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Book Description
A survey of the existing literature indicates that optimization on the power management logic of hybrid electric vehicle is mostly performed after the design of the powertrain architecture or the power source components are finalized. The goal of this research is to utilize Multidisciplinary Design Optimization (MDO) to automate and optimize the vehicle's powertrain component sizes, while simultaneously determining the optimal power management logic in developing the most cost-effective system solution. A generic, modular, and flexible vehicle model utilizing a backward-looking architecture is created using scalable powertrain components. The objective of the research work is to study the energy efficiency of the vehicle system, where the dynamics of the vehicle is not of concern; a backward-looking architecture could be used to compute the power consumption and the overall efficiency accurately while minimizing the required computing resource. An optimization software platform utilizing multidisciplinary design optimization approach is implemented containing the generic vehicle model and an optimizer of the user's choice. The software model is created in the MATLAB/Simulink environment, where the optimization code and the powertrain component properties are implemented using m-files, and the power consumption calculations of the vehicle system are performed in Simulink. Furthermore, a feature-based optimization technique is developed with the motivation of significantly reducing the simulation run-time. To demonstrate the capabilities of the developed approach and contributions of the research, two optimization case studies are undertaken: (i) series hybrid electric vehicles, and (ii) police vehicle anti-idling system. As the first case study, a plug-in battery-only series hybrid electric vehicle with similar power components as the Chevrolet Volt is created, where the battery size and the power management logic are simultaneously optimized. The objective function of the optimizer is defined from the financial cost perspective, where the objective is to minimize the initial cost of batteries, gasoline and electricity consumption over a period of five years, and the carbon tax as a penalty function for fuel emissions. The battery-only series hybrid electric vehicle is subsequently extended to include ultracapacitors, and the optimization process is expanded to the rest of the powertrain components and power management logic. A comparison between the optimization algorithms found that only genetic algorithm (GA) was capable of finding the optimal solution during a full simulation, while simulated annealing and pattern search were not able to converge to any solution after a 24-hour period.
Author: Brian Su-Ming Fan
Publisher:
ISBN:
Category :
Languages : en
Pages : 146
Get Book Here
Book Description
A survey of the existing literature indicates that optimization on the power management logic of hybrid electric vehicle is mostly performed after the design of the powertrain architecture or the power source components are finalized. The goal of this research is to utilize Multidisciplinary Design Optimization (MDO) to automate and optimize the vehicle's powertrain component sizes, while simultaneously determining the optimal power management logic in developing the most cost-effective system solution. A generic, modular, and flexible vehicle model utilizing a backward-looking architecture is created using scalable powertrain components. The objective of the research work is to study the energy efficiency of the vehicle system, where the dynamics of the vehicle is not of concern; a backward-looking architecture could be used to compute the power consumption and the overall efficiency accurately while minimizing the required computing resource. An optimization software platform utilizing multidisciplinary design optimization approach is implemented containing the generic vehicle model and an optimizer of the user's choice. The software model is created in the MATLAB/Simulink environment, where the optimization code and the powertrain component properties are implemented using m-files, and the power consumption calculations of the vehicle system are performed in Simulink. Furthermore, a feature-based optimization technique is developed with the motivation of significantly reducing the simulation run-time. To demonstrate the capabilities of the developed approach and contributions of the research, two optimization case studies are undertaken: (i) series hybrid electric vehicles, and (ii) police vehicle anti-idling system. As the first case study, a plug-in battery-only series hybrid electric vehicle with similar power components as the Chevrolet Volt is created, where the battery size and the power management logic are simultaneously optimized. The objective function of the optimizer is defined from the financial cost perspective, where the objective is to minimize the initial cost of batteries, gasoline and electricity consumption over a period of five years, and the carbon tax as a penalty function for fuel emissions. The battery-only series hybrid electric vehicle is subsequently extended to include ultracapacitors, and the optimization process is expanded to the rest of the powertrain components and power management logic. A comparison between the optimization algorithms found that only genetic algorithm (GA) was capable of finding the optimal solution during a full simulation, while simulated annealing and pattern search were not able to converge to any solution after a 24-hour period.
Author: Michael Nikowitz
Publisher: Springer
ISBN: 3319263056
Category : Technology & Engineering
Languages : en
Pages : 230
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Book Description
This contributed volume contains the results of the research program “Agreement for Hybrid and Electric Vehicles”, developed in the framework of the Energy Technology Network of the International Energy Agency. The topical focus lies on technology options for the system optimization of hybrid and electric vehicle components and drive train configurations which enhance the energy efficiency of the vehicle. The approach to the topic is genuinely interdisciplinary, covering insights from fields. The target audience primarily comprises researchers and industry experts in the field of automotive engineering, but the book may also be beneficial for graduate students.
Author: Emanuele Crisostomi
Publisher: CRC Press
ISBN: 1498745008
Category : Technology & Engineering
Languages : en
Pages : 261
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Book Description
This book explores the behavior of networks of electric and hybrid vehicles. The topics that are covered include: energy management issues for aggregates of plug-in vehicles; the design of sharing systems to support electro-mobility; context awareness in the operation of electric and hybrid vehicles, and the role that this plays in a Smart City context; and tools to test and design massively large-scale networks of such vehicles. The book also introduces new and interesting control problems that are becoming prevalent in the EV-PHEV's context, as well as identifying some open questions. A particular focus of the book is on the opportunities afforded by networked actuation possibilities in electric and hybrid vehicles, and the role that such actuation may play in air-quality and emissions management.
Author: Axel Schumacher
Publisher: Springer
ISBN: 3319679880
Category : Science
Languages : en
Pages : 2101
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Book Description
The volume includes papers from the WSCMO conference in Braunschweig 2017 presenting research of all aspects of the optimal design of structures as well as multidisciplinary design optimization where the involved disciplines deal with the analysis of solids, fluids or other field problems. Also presented are practical applications of optimization methods and the corresponding software development in all branches of technology.
Author: Shashi Kamal Shahi
Publisher:
ISBN:
Category : Hybrid electric vehicles
Languages : en
Pages : 294
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Book Description
Plug-in hybrid electric vehicles (PHEV), which share the characteristics of both a conventional HEV and an all-electric vehicle, rely on large storage batteries. Therefore, the characteristics and hybridization of the PHEV battery with the engine and electric motor play an important role in the design and potential adoption of PHEVs. In this research work, a multi-objective optimization approach is applied to compare the operational performance of Toyota Prius PHEV20 (PHEV for 20 miles of all electric range) based on fuel economy, operating cost, and green house gas emissions for 4480 combinations (20 batteries, 14 motors, and 16 engines). Powertrain System Analysis Toolkit software package automated with the Pareto Set Pursuing multi-objective optimization method is used for this purpose on two different drive cycles. It was found that 1) battery, motor, and engine work collectively in defining an optimal hybridization scheme; and 2) the optimal hybridization scheme varies with drive cycles.
Author: Jili Tao
Publisher: Elsevier
ISBN: 0443131902
Category : Science
Languages : en
Pages : 348
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Book Description
Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management presents the state-of-the-art in hybrid electric vehicle system modelling and management. With a focus on learning-based energy management strategies, the book provides detailed methods, mathematical models, and strategies designed to optimize the energy management of the energy supply module of a hybrid vehicle.The book first addresses the underlying problems in Hybrid Electric Vehicle (HEV) modeling, and then introduces several artificial intelligence-based energy management strategies of HEV systems, including those based on fuzzy control with driving pattern recognition, multi objective optimization, fuzzy Q-learning and Deep Deterministic Policy Gradient (DDPG) algorithms. To help readers apply these management strategies, the book also introduces State of Charge and State of Health prediction methods and real time driving pattern recognition. For each application, the detailed experimental process, program code, experimental results, and algorithm performance evaluation are provided.Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management is a valuable reference for anyone involved in the modelling and management of hybrid electric vehicles, and will be of interest to graduate students, researchers, and professionals working on HEVs in the fields of energy, electrical, and automotive engineering. Provides a guide to the modeling and simulation methods of hybrid electric vehicle energy systems, including fuel cell systems Describes the fundamental concepts and theory behind CNN, MPC, fuzzy control, multi objective optimization, fuzzy Q-learning and DDPG Explains how to use energy management methods such as parameter estimation, Q-learning, and pattern recognition, including battery State of Health and State of Charge prediction, and vehicle operating conditions
Author: Chitra A.
Publisher: John Wiley & Sons
ISBN: 1119682010
Category : Computers
Languages : en
Pages : 288
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Book Description
Electric vehicles/hybrid electric vehicles (EV/HEV) commercialization is still a challenge in industries in terms of performance and cost. The performance along with cost reduction are two tradeoffs which need to be researched to arrive at an optimal solution. This book focuses on the convergence of various technologies involved in EV/HEV. The book brings together the research that is being carried out in the field of EV/HEV whose leading role is by optimization techniques with artificial intelligence (AI). Other featured research includes green drive schemes which involve the possible renewable energy sources integration to develop eco-friendly green vehicles, as well as Internet of Things (IoT)-based techniques for EV/HEVs. Electric vehicle research involves multi-disciplinary expertise from electrical, electronics, mechanical engineering and computer science. Consequently, this book serves as a point of convergence wherein all these domains are addressed and merged and will serve as a potential resource for industrialists and researchers working in the domain of electric vehicles.
Author: Petros Frantzeskakis
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Simona Onori
Publisher: Springer
ISBN: 1447167813
Category : Technology & Engineering
Languages : en
Pages : 121
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Book Description
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.
Author: Iqbal Husain
Publisher: CRC Press
ISBN: 0203009398
Category : Technology & Engineering
Languages : en
Pages : 293
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Book Description
With advances driven by pressure from governments, environmental activists, and its associated industries, the subject of electric and hybrid vehicles is becoming increasingly important. Trends clearly suggest that we must educate the engineers of today and tomorrow in the technical details of these vehicles. While there are many books that provide narrative descriptions of electric and hybrid vehicle components, none cover the technical aspects from a mathematically derived, design point of view, and none serve well as a textbook. Electric and Hybrid Vehicles: Design Fundamentals presents a comprehensive, systems-level perspective of these vehicles that strikes an outstanding balance between technical details, design equations, numerical examples, and case studies. Starting with some historic background, the author describes the system components, the laws of physics governing vehicle motion, the mathematical relationships within and between the components, energy sources, and designing components to meet the complete vehicle specifications. As this text illustrates, the electric vehicle is an excellent example of electro-mechanical and electro-chemical systems, one that is technically challenging as well as highly motivating to engineering students. The material presented is designed to be covered comfortably in a one-semester course. Its multidisciplinary nature and systems approach makes Electric and Hybrid Vehicles ideal for teaching electrical, mechanical, and chemical engineers all in one course.
