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Author: Guilin Zhu
Publisher:
ISBN:
Category : Mechanical engineering
Languages : en
Pages : 94
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Book Description
The EcoCAR3 project is a four-year competition sponsored by General Motors and the U.S. Department of Energy challenging 16 universities teams to reengineer a 2016 Chevrolet Camaro to be a performance plug-in hybrid electric vehicle. A pre-transmission (P2) without clutch parallel architecture was chosen by Wayne State University EcoCAR3 team in Year 3. The parallel PHEV architecture was modeled by using MATLAB, Simulink and Stateflow for the MIL and SIL environment which was used to test different control strategies. To efficiently distribute the power between engine and electric motor and assess component and system statuses, a hybrid supervisory controller was developed to safely control the interactions between powertrain components. The thesis details the development of hybrid supervisory controller with emphasis on energy management strategy, a fault diagnosis strategy for safety critical system is also presented in the thesis. A rule-based control strategy is developed to efficiently control hybrid powertrain components in four different operating modes. An optimization based control strategy is then developed to find appropriate torque split between engine and electric motor to reduce the energy consumption in the charge sustaining mode, compared to rule-based control strategy, the optimization based controller effectively reduce the energy consumption on simulated drive cycles.
Author: Guilin Zhu
Publisher:
ISBN:
Category : Mechanical engineering
Languages : en
Pages : 94
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Book Description
The EcoCAR3 project is a four-year competition sponsored by General Motors and the U.S. Department of Energy challenging 16 universities teams to reengineer a 2016 Chevrolet Camaro to be a performance plug-in hybrid electric vehicle. A pre-transmission (P2) without clutch parallel architecture was chosen by Wayne State University EcoCAR3 team in Year 3. The parallel PHEV architecture was modeled by using MATLAB, Simulink and Stateflow for the MIL and SIL environment which was used to test different control strategies. To efficiently distribute the power between engine and electric motor and assess component and system statuses, a hybrid supervisory controller was developed to safely control the interactions between powertrain components. The thesis details the development of hybrid supervisory controller with emphasis on energy management strategy, a fault diagnosis strategy for safety critical system is also presented in the thesis. A rule-based control strategy is developed to efficiently control hybrid powertrain components in four different operating modes. An optimization based control strategy is then developed to find appropriate torque split between engine and electric motor to reduce the energy consumption in the charge sustaining mode, compared to rule-based control strategy, the optimization based controller effectively reduce the energy consumption on simulated drive cycles.
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: Bo Gu
Publisher:
ISBN:
Category : Hybrid electric vehicles
Languages : en
Pages : 286
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Book Description
Abstract: As crude oil price rises, the advantages of Hybrid Electric Vehicle (HEV) are more and more attractive to the automotive industry and customers. The work of this thesis is aimed toward the Ohio State University's objective as a participant in the Challenge X competition. During the first year of this three-year project, the vehicle architecture is carefully chosen. Vehicle modeling, simulation and control algorithm designs are partially completed. This thesis covers work completed in the second year -- further improving the supervisory control strategy and its application in a microcontroller system. In the first two chapters, HEV technologies and designs are reviewed. Advantages of HEV are outlined and how such advantages can be achieved is explained. The Challenge X architecture is then introduced. Current control algorithms for HEV are reviewed. In Chapter 3, a quasi-static model of HEV is introduced. In the quasi-static model, the dynamics of the powertrain are not considered. Instead, most of components of the powertrain are simplified as maps. Such approach provides acceptable approximation of vehicle for designing the supervisory control algorithms for energy management, and for further optimization. Novel energy management algorithms are introduced in Chapters 4 and 5. A 3-way Equivalent (fuel) Consumption Minimization Strategy (ECMS), a P1 State-of-Charge management algorithm and an adaptive version of ECMS based on driving pattern recognition are introduced. ECMS provides real-time near-optimal energy management decisions by minimizing the "equivalent" fuel consumption, which is a combination of the actual fuel consumption and electrical energy use. An equivalence factor converts electrical power consumption into fuel consumption, based on the average efficiency of the battery in discharge/recharge and the efficiencies of electric motors and other devices. A driving pattern recognition method is used to obtain better estimation of the equivalence factor. Eighteen standard driving cycles provided by the Environmental Protection Agency are analyzed. Twenty one different cycle-characterizing quantities, such as average, peak and rms velocity, are extracted. Using the ideas of Principal Component Analysis and of statistical clustering, 18 driving cycles are classified into four Representative Driving Patterns (RDP), such as urban and highway. While the vehicle is running, a time window of past driving conditions is analyzed periodically and recognized as one of the four RDPs. Periodically updating the control parameter according to the driving conditions yields more precise estimation of the equivalent fuel consumption cost, thus providing better fuel economy. Besides minimizing the instantaneous equivalent fuel consumption, the battery State of Charge (SOC) is also maintained by using a P1 controller to keep the SOC around a nominal value. Such control algorithm does not require the knowledge of future driving cycles and has a low additional computational burden. Results obtained in this research shows that the driving conditions can be successfully recognized and good performance can be achieved in various driving conditions while sustaining battery Soc within desired limits. chapter 6 focuses on how to convert the control algorithm applied in the simulator into real-time implementation in the microcontroller systems. A set of 6 dimensional maps is generated and stored for real-time application, according to the computation limitation of the microcontroller. Simulation results show that real-time solution based on look-up tables have similar results as those provided by instantaneous calculation. Therefore the microcontroller system version of supervisory control strategy is acceptable for implementation. The contributions of this thesis extend previous research conducted at the OSU center for Automotive Research, and include: the successful implementation of 3-way ECMS control strategy in the challenge x vehicle; the design of the new adaptive-EcMS; and the implementation of supervisory control strategy in the microcontroller systems. A PDF copy of this thesis with color figures is available from the center for Automotive Research, the Ohio State University. It is also available from gu.4Oosu.edu upon request.
Author: Amir Taghavipour
Publisher: Springer
ISBN: 3030003140
Category : Technology & Engineering
Languages : en
Pages : 202
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Book Description
Intelligent Control of Connected Plug-in Hybrid Electric Vehicles presents the development of real-time intelligent control systems for plug-in hybrid electric vehicles, which involves control-oriented modelling, controller design, and performance evaluation. The controllers outlined in the book take advantage of advances in vehicle communications technologies, such as global positioning systems, intelligent transportation systems, geographic information systems, and other on-board sensors, in order to provide look-ahead trip data. The book contains simple and efficient models and fast optimization algorithms for the devised controllers to address the challenge of real-time implementation in the design of complex control systems. Using the look-ahead trip information, the authors of the book propose intelligent optimal model-based control systems to minimize the total energy cost, for both grid-derived electricity and fuel. The multilayer intelligent control system proposed consists of trip planning, an ecological cruise controller, and a route-based energy management system. An algorithm that is designed to take advantage of previewed trip information to optimize battery depletion profiles is presented in the book. Different control strategies are compared and ways in which connecting vehicles via vehicle-to-vehicle communication can improve system performance are detailed. Intelligent Control of Connected Plug-in Hybrid Electric Vehicles is a useful source of information for postgraduate students and researchers in academic institutions participating in automotive research activities. Engineers and designers working in research and development for automotive companies will also find this book of interest. 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.
Author: Trevor Crain
Publisher:
ISBN:
Category : Hybrid electric vehicles
Languages : en
Pages : 79
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Book Description
This thesis presents the design process used to create and validate a hybrid vehicle supervisory control system for a plug-in hybrid electric vehicle in the EcoCAR 2 competition. The vehicle utilized a Parallel through the Road hybrid architecture with a B20 biodiesel engine-powered front axle and electric motor-driven rear axle. The primary goal of this work is to present a selection of the processes used by the controls team throughout the competition to define the control system requirements and platforms, model the components of the vehicle and validate each model, and estimate the effects of various control system strategies and parameters on overall vehicle performance. The advantages of using a version-controlled Simulink model for supervisory controller development are discussed along with an explanation of the software architecture and primary hybrid control modes. The models developed to simulate the primary drivetrain components are detailed in addition to their parameterization and validation testing methods. The final chapter presents an analysis on dynamometer test data used to quantify the effects of various controller parameters and strategies on the results of the Emissions and Energy Consumption (E&EC) event's dynamic drive testing. The electrical energy consumption of the vehicle during charge depleting mode testing is used to select a state of charge value for transitioning to charge sustaining mode. Various implementations of engine stop start are also analyzed, showing the potential for a 3.8% improvement in B20 fuel consumption over the course of the City/Highway E&EC drive cycle.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Objectives are to: (1) Investigate novel engine control strategies targeted at rapid engine/catalyst warming for the purpose of mitigating tailpipe emissions from plug-in hybrid electric vehicles (PHEV) exposed to multiple engine cold start events; and (2) Validate and optimize hybrid supervisory control techniques developed during previous and on-going research projects by integrating them into the vehicle level control system and complementing them with the modified engine control strategies in order to further reduce emissions during both cold start and engine re-starts. Approach used are: (1) Perform a literature search of engine control strategies used in conventional powertrains to reduce cold start emissions; (2) Develop an open source engine controller providing full access to engine control strategies in order to implement new engine/catalyst warm-up behaviors; (3) Modify engine cold start control algorithms and characterize impact on cold start behavior; and (4) Develop an experimental Engine-In-the-Loop test stand in order to validate control methodologies and verify transient thermal behavior and emissions of the real engine when combined with a virtual hybrid powertrain. Some major accomplishments are: (1) Commissioned a prototype engine controller on a GM Ecotec 2.4l direct injected gasoline engine on an engine test cell at the University of Tennessee. (2) Obtained from Bosch (with GM's approval) an open calibration engine controller for a GM Ecotec LNF 2.0l Gasoline Turbocharged Direct Injection engine. Bosch will support the bypass of cold start strategies if calibration access proves insufficient. The LNF engine and its open controller were commissioned on an engine test cell at ORNL. (3) Completed a literature search to identify key engine cold start control parameters and characterized their impact on the real engine using the Bosch engine controller to calibrate them. (4) Ported virtual hybrid vehicle model from offline simulation environment to real-time Hardware-In-the-Loop platform.
Author: Brian Neal Harries
Publisher:
ISBN:
Category : Vehicles
Languages : en
Pages : 320
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Book Description
"A Series PHEV was chosen as ERAU's entry into EcoCar2 through a multidisciplinary architecture selection process. The first controller implemented was a simplified bang-bang controller to operate at the global minimum BSFC. A power-tracking controller was then developed to minimize powertrain losses. The power-tracking controller substantially reduced the vehicles energy consumption on simulated EPA drive cycles."--Leaf 3.
Author: Lino Guzzella
Publisher: Springer Science & Business Media
ISBN: 3540746927
Category : Technology & Engineering
Languages : en
Pages : 345
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Book Description
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.
Author: Chris Mi
Publisher: John Wiley & Sons
ISBN: 111897056X
Category : Technology & Engineering
Languages : en
Pages : 611
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Book Description
The latest developments in the field of hybrid electric vehicles Hybrid Electric Vehicles provides an introduction to hybrid vehicles, which include purely electric, hybrid electric, hybrid hydraulic, fuel cell vehicles, plug-in hybrid electric, and off-road hybrid vehicular systems. It focuses on the power and propulsion systems for these vehicles, including issues related to power and energy management. Other topics covered include hybrid vs. pure electric, HEV system architecture (including plug-in & charging control and hydraulic), off-road and other industrial utility vehicles, safety and EMC, storage technologies, vehicular power and energy management, diagnostics and prognostics, and electromechanical vibration issues. Hybrid Electric Vehicles, Second Edition is a comprehensively updated new edition with four new chapters covering recent advances in hybrid vehicle technology. New areas covered include battery modelling, charger design, and wireless charging. Substantial details have also been included on the architecture of hybrid excavators in the chapter related to special hybrid vehicles. Also included is a chapter providing an overview of hybrid vehicle technology, which offers a perspective on the current debate on sustainability and the environmental impact of hybrid and electric vehicle technology. Completely updated with new chapters Covers recent developments, breakthroughs, and technologies, including new drive topologies Explains HEV fundamentals and applications Offers a holistic perspective on vehicle electrification Hybrid Electric Vehicles: Principles and Applications with Practical Perspectives, Second Edition is a great resource for researchers and practitioners in the automotive industry, as well as for graduate students in automotive engineering.
Author: Nikhil Ramaswamy
Publisher:
ISBN:
Category : Control thoery
Languages : en
Pages :
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Book Description
This thesis (1) reports a new Dynamic Programming (DP) approach, and (2) reports a Real Time Control strategy to optimize the energy management of a Hybrid Electric Vehicle(HEV). Increasing environmental concerns and rise in fuel prices in recent years has escalated interest in fuel efficient vehicles from government, consumers and car manufacturers. Due to this, Hybrid electric vehicles (HEV) have gained popularity in recent years. HEV's have two degrees of freedom for energy flow controls, and hence the performance of a HEV is strongly dependent on the control of the power split between thermal and electrical power sources. In this thesis backward-looking and forward-looking control strategies for two HEV architectures namely series and parallel HEV are developed. The new DP approach, in which the state variable is not discretized, is first introduced and a theoretical base is established. We then prove that the proposed DP produces globally optimal solution for a class of discrete systems. Then it is applied to optimize the fuel economy of HEV's. Simulations for the parallel and series HEV are then performed for multiple drive cycles and the improved fuel economy obtained by the new DP is compared to existing DP approaches. The results are then studied in detail and further improvements are suggested. A new Real Time Control Strategy (RTCS) based on the concept of preview control for online implementation is also developed in this thesis. It is then compared to an existing Equivalent Cost Minimization Strategy (ECMS) which does not require data to be known apriori. The improved fuel economy results of the RTCS for the series and parallel HEV are obtained for standard drive cycles and compared with the ECMS results.
