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Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
Plug-in hybrid electric vehicle (PHEV) technologies have the potential for considerable petroleum consumption reductions, possibly at the expense of increased tailpipe emissions due to multiple 'cold' start events and improper use of the engine for PHEV specific operation. PHEVs operate predominantly as electric vehicles (EVs) with intermittent assist from the engine during high power demands. As a consequence, the engine can be subjected to multiple cold start events. These cold start events may have a significant impact on the tailpipe emissions due to degraded catalyst performance and starting the engine under less than ideal conditions. On current hybrid electric vehicles (HEVs), the first cold start of the engine dictates whether or not the vehicle will pass federal emissions tests. PHEV operation compounds this problem due to infrequent, multiple engine cold starts. The research is broken down into two (2) distinct phases, involving both analytical and experimental areas. Phase I of the research, addressed in this document, focuses on the design of a vehicle supervisory control system for a pre-transmission parallel PHEV powertrain architecture. A suitable control system architecture is created and implemented into a standard vehicle modeling tool (in this case, the Powertrain Systems Analysis Toolkit). Energy management strategies are evaluated and implemented in a virtual environment for preliminary assessment of petroleum displacement benefits and rudimentary drivability issues. Engine cold start events are aggressively addressed in the development of this control system, which leads to enhanced pre-warming and energy-based engine warming algorithms that provide substantial reductions in tailpipe emissions over the baseline supervisory control strategy. The flexibility of the PHEV powertrain offers the potential for decreased emissions during any engine starting event through powertrain 'torque shaping' algorithms. The analytical work presented here is experimentally validated during Phase 2, the subject of a follow on paper.
Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
Plug-in hybrid electric vehicle (PHEV) technologies have the potential for considerable petroleum consumption reductions, possibly at the expense of increased tailpipe emissions due to multiple 'cold' start events and improper use of the engine for PHEV specific operation. PHEVs operate predominantly as electric vehicles (EVs) with intermittent assist from the engine during high power demands. As a consequence, the engine can be subjected to multiple cold start events. These cold start events may have a significant impact on the tailpipe emissions due to degraded catalyst performance and starting the engine under less than ideal conditions. On current hybrid electric vehicles (HEVs), the first cold start of the engine dictates whether or not the vehicle will pass federal emissions tests. PHEV operation compounds this problem due to infrequent, multiple engine cold starts. The research is broken down into two (2) distinct phases, involving both analytical and experimental areas. Phase I of the research, addressed in this document, focuses on the design of a vehicle supervisory control system for a pre-transmission parallel PHEV powertrain architecture. A suitable control system architecture is created and implemented into a standard vehicle modeling tool (in this case, the Powertrain Systems Analysis Toolkit). Energy management strategies are evaluated and implemented in a virtual environment for preliminary assessment of petroleum displacement benefits and rudimentary drivability issues. Engine cold start events are aggressively addressed in the development of this control system, which leads to enhanced pre-warming and energy-based engine warming algorithms that provide substantial reductions in tailpipe emissions over the baseline supervisory control strategy. The flexibility of the PHEV powertrain offers the potential for decreased emissions during any engine starting event through powertrain 'torque shaping' algorithms. The analytical work presented here is experimentally validated during Phase 2, the subject of a follow on paper.
Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
Plug-in hybrid electric vehicle (PHEV) technologies have the potential for considerable petroleum consumption reductions, possibly at the expense of increased tailpipe emissions due to multiple 'cold' start events and improper use of the engine for PHEV specific operation. PHEVs operate predominantly as electric vehicles (EVs) with intermittent assist from the engine during high power demands. As a consequence, the engine can be subjected to multiple cold start events. These cold start events may have a significant impact on the tailpipe emissions due to degraded catalyst performance and starting the engine under less than ideal conditions. On current hybrid electric vehicles (HEVs), the first cold start of the engine dictates whether or not the vehicle will pass federal emissions tests. PHEV operation compounds this problem due to infrequent, multiple engine cold starts. A continuation of previous analytical work, this research, experimentally verifies a vehicle supervisory control system for a pre-transmission parallel PHEV powertrain architecture. Energy management strategies are evaluated and implemented in a virtual environment for preliminary assessment of petroleum displacement benefits and rudimentary drivability issues. This baseline vehicle supervisory control strategy, developed as a result of this assessment, is implemented and tested on actual hardware in a controlled laboratory environment over a baseline test cycle. Engine cold start events are aggressively addressed in the development of this control system, which leads to enhanced pre-warming and energy-based engine warming algorithms that provide substantial reductions in tailpipe emissions over the baseline supervisory control strategy. The flexibility of the PHEV powertrain allows for decreased emissions during any engine starting event through powertrain 'torque shaping' algorithms. The results of the research show that PHEVs do have the potential for substantial reductions in fuel consumption. Tailpipe emissions from a PHEV test platform have been reduced to acceptable levels through the development and refinement of vehicle supervisory control methods only. Impacts on fuel consumption were minimal for the emissions reduction techniques implemented.
Author: Ali Emadi Publisher: CRC Press ISBN: 1466597704 Category : Technology & Engineering Languages : en Pages : 616
Book Description
Electrification is an evolving paradigm shift in the transportation industry toward more efficient, higher performance, safer, smarter, and more reliable vehicles. There is in fact a clear trend to move from internal combustion engines (ICEs) to more integrated electrified powertrains. Providing a detailed overview of this growing area, Advanced Electric Drive Vehicles begins with an introduction to the automotive industry, an explanation of the need for electrification, and a presentation of the fundamentals of conventional vehicles and ICEs. It then proceeds to address the major components of electrified vehicles—i.e., power electronic converters, electric machines, electric motor controllers, and energy storage systems. This comprehensive work: Covers more electric vehicles (MEVs), hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), range-extended electric vehicles (REEVs), and all-electric vehicles (EVs) including battery electric vehicles (BEVs) and fuel cell vehicles (FCVs) Describes the electrification technologies applied to nonpropulsion loads, such as power steering and air-conditioning systems Discusses hybrid battery/ultra-capacitor energy storage systems, as well as 48-V electrification and belt-driven starter generator systems Considers vehicle-to-grid (V2G) interface and electrical infrastructure issues, energy management, and optimization in advanced electric drive vehicles Contains numerous illustrations, practical examples, case studies, and challenging questions and problems throughout to ensure a solid understanding of key concepts and applications Advanced Electric Drive Vehicles makes an ideal textbook for senior-level undergraduate or graduate engineering courses and a user-friendly reference for researchers, engineers, managers, and other professionals interested in transportation electrification.
Author: Amir Taghavipour Publisher: Springer ISBN: 3030003140 Category : Technology & Engineering Languages : en Pages : 202
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: Publisher: ISBN: Category : Languages : en Pages : 458
Book Description
Plug-in hybrid electric vehicle (PHEV) technologies have the potential for considerable petroleum consumption reductions, at the expense of increased tailpipe emissions due to multiple "cold" start events and improper use of the engine for PHEV specific operation. PHEVs operate predominantly as electric vehicles (EVs) with intermittent assist from the engine during high power demands. As a consequence, the engine can be subjected to multiple cold start events. These cold start events have a significant impact on the tailpipe emissions due to degraded catalyst performance and starting the engine under less than ideal conditions. On current hybrid electric vehicles (HEVs), the first cold start of the engine dictates whether or not the vehicle will pass federal emissions tests. PHEV operation compounds this problem due to infrequent, multiple engine cold starts. The dissertation research focuses on the design of a vehicle supervisory control system for a pre-transmission parallel PHEV powertrain architecture. Energy management strategies are evaluated and implemented in a virtual environment for preliminary assessment of petroleum displacement benefits and rudimentary drivability issues. This baseline vehicle supervisory control strategy, developed as a result of this assessment, is implemented and tested on actual hardware in a controlled laboratory environment over a baseline test cycle. Engine cold start events are aggressively addressed in the development of this control system, which lead to enhanced pre-warming and energy-based engine warming algorithms that provide substantial reductions in tailpipe emissions over the baseline supervisory control strategy. The flexibility of the PHEV powertrain allows for decreased emissions during any engine starting event through powertrain "torque shaping" algorithms that eliminate high engine torque transients during these periods. The results of the dissertation research show that PHEVs do have the potential for substantial reductions in fuel consumption, while remaining environmentally friendly. Tailpipe emissions from a representative PHEV test platform have been reduced to acceptable levels through the development and refinement of vehicle supervisory control methods only. Impacts on fuel consumption are minimal for the emissions reduction techniques that are implemented, while in some cases, substantial fuel consumption reductions are observed.
Author: Thomas Francis Gorgia III Publisher: ISBN: Category : Automobiles Languages : en Pages : 158
Book Description
Criteria emission reduction techniques are being more sought out in the automotive industry due to current government regulation for light duty vehicles. Parallel-series plug- in hybrid electric vehicles can have multiple strategies to balance emissions and fuel consumption. Common controls strategies in industry target fuel economy by using a large electric vehicle range, known as charge depletion, followed by maintaining a state of charge after a specific vehicle threshold, or charge sustaining. A charge preserve strategy works by running an engine at an optimal loading condition, the engine will burn the fuel more complete reducing criteria emissions. Charge preserve will charge the vehicle more rapidly by loading the engine to achieve optimal loading conditions and yield a quicker recharge. The charge preserve strategy had the best results when compared to the corporate average fuel economy 2025 standards that regulate solely criteria emissions. The nitrogen oxides emissions of a Max Depletion strategy were higher than the standard by 200%. The Charge preserve strategy decreased Nitrogen oxides by 41%. Greenhouse gas emission from a Charge Preserve strategy, however can see an increase up to 15% and a 2% decrease in fuel economy was observed.
Author: Brian Neal Harries Publisher: ISBN: Category : Vehicles Languages : en Pages : 320
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: Katherine Marie Bovee Publisher: ISBN: Category : Languages : en Pages : 158
Book Description
Abstract: Increasingly stringent government regulations and the rising price of oil are causing automotive manufactures to develop vehicles capable of obtaining higher fuel economies and lower emissions. To achieve these goals, automotive manufactures have been developing hybrid electric vehicles (HEV) and plug-in hybrid electric vehicles (PHEV) that use both electricity and petroleum based fuels as their power sources. The additional power the vehicle receives from the high voltage batteries and the electric machines allow automotive manufacturers to downsize the engine inside of the vehicle. Vehicles with smaller engines are able to obtain a higher overall fuel economy because the smaller engine is able to operate at its more efficient high load operating points more frequently.
Author: Xiangrui Zeng Publisher: ISBN: Category : Languages : en Pages :
Book Description
One of the main goals of hybrid electric vehicle technology is to improve the energy efficiency. In industry and most of academic research, the powertrain control is designed and evaluated under standard driving cycles. However, the situations that a vehicle may encounter in the real world could be quite different from the standard cycles. Studies show that the human drivers have a great influence on the vehicle energy consumptions and emissions. The actual operating conditions that a vehicle faces are not only dependent on the roads and traffic, but also dependent on the drivers. A standard driving cycle can only represent the typical and averaged driving style under the typical driving scenarios, therefore the control strategies designed based on a standard driving cycle may not perform well for all different driving styles. This motivates the idea to design optimally-personalized hybrid electric vehicle control methods that can be adaptive to individual human driving styles and their driving routes. Human-subject experiments are conducted on a driving simulator to study the driving behaviors. A stochastic driver pedal model that can learn individual driver’s driving style is developed first. Then a theoretic investigation on worst-case relative cost optimal control problems, which is closely related to vehicle powertrain optimal control under real-world uncertain driving scenarios, is presented. A two-level control structure for plug-in hybrid electric vehicles is proposed, where the parameters in the lower-level controller can be on-line adjusted via optimization using historical driving data. The methods to optimize these parameters are designed for fixed-route driving first, and then extended to multi-routes driving using the idea similar to the worst-case relative cost optimal control. The performances of the two proposed methods are shown through simulations using human driving data and stochastic driver model data respectively. The energy consumption results in both situations are close to the posteriori optimal result and outperform other existing methods, which show the effectiveness of applying optimally-personalized energy management strategy on hybrid electric vehicles. Finally, a route-based global energy-optimal speed planning method is also proposed. This off-line method provides a useful tool to evaluate the potential of other speed planning methods, for either eco-driving guidance applications or future automated vehicle controls. The contributions of this dissertation include 1) a novel stochastic driver pedal behavior model which can learn independent drivers’ driving styles is created, 2) a new worst-case relative cost optimal control method is proposed, 3) a real-time implementable stochastic optimal energy management strategy for hybrid electric vehicles running on fixed routes is designed using the statistics of history driving data, 4) the fix-route strategy is extended to the multi-route situation, and 5) an off-line global energy-optimal speed planning solution for road vehicles on a given route is presented.
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Author: Ali Emadi
Author: Amir Taghavipour
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Author: Richard T. Rooney
Author: Thomas Francis Gorgia III
Author: Brian Neal Harries
Author: Katherine Marie Bovee
Author: Xiangrui Zeng