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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: 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: Katherine Marie Bovee
Publisher:
ISBN:
Category :
Languages : en
Pages : 158
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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: Joseph M. Morbitzer
Publisher:
ISBN:
Category : Hybrid electric vehicles
Languages : en
Pages : 0
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Book Description
Over the last decade, hybrid-electric vehicles have progressed from a futuristic icon to a firm production reality for a growing number of automobile manufacturers. While the motivation for this trend may vary, hybrid-electric vehicles today symbolize a recognition of the necessity to evolve advanced automotive technologies in order to sustain a culture of freedom of mobility. The Challenge X program communicates this message towards academia and future automotive engineers with strong support from both government and industry. The work of this thesis was aimed toward The Ohio State University's objectives as a participant in the Challenge X competition. As an initial task, the Ohio State team defined a set of vehicle technical specifications to steer and motivate the vehicle design and control strategy development. After an extensive decision-making process, a specific architecture emerged with the potential to meet the vehicle technical specifications. The chosen configuration is a charge-sustaining, power-split, hybrid-electric vehicle design. A downsized Diesel engine and integrated starter/alternator drive the front wheels through an automatic transaxle. A larger, tractive electric machine and single-speed gearbox exist on the rear drivetrain. Both electric machines and their respective inverters connect electrically to a single high-voltage battery pack. The validation procedure for both the vehicle architecture and a control strategy involves use of a computer vehicle simulator. A quasi-static vehicle model acts as a basis for a simulator to validate the design and control strategy with respect to energy management. A dynamic vehicle model establishes a foundation for eventual creation of a second simulator for drivability validation. Both simulators operate in a forward-moving fashion and contain three primary sections: (i) the driver, (ii) the hybrid-electric powertrain, and (iii) the vehicle. Both models are also highly nonlinear, but the main differentiating property is the relatively large system order of the dynamic model as compared to the quasi-static model. The high-level supervisory control strategy strives to accomplish certain objectives. The initial task involves appropriately selecting the vehicle mode from those predefined as being advantageous to the particular architecture. The control strategy then calculates the driver power request and commands the powertrain actuators so as to meet that request. In certain and applicable vehicle modes, the torque split also aims to minimize fuel consumption. High-voltage battery pack state-of-charge management is both indirectly and inherently incorporated into the fuel consumption minimization approach. As a future task, drivability assurance may involve a final adjustment of control strategy commands so as to respect certain levels of several identified drivability metrics during the vehicle response. Rapid prototyping with a rolling chassis apparatus provided a method of investigation into the pragmaticality of solely utilizing the tractive electric machine and high-voltage battery pack for vehicle propulsion. Initial experimentation validates functionality of the electric machine and inverter and also indicates potential for the power electronics system to act alone in acceptably accelerating the vehicle inertia from a rest. More revealing analysis of the vehicle architecture and control strategy occurred via software-in-the-loop techniques using a simulator based upon the quasi-static vehicle model. Simulation results verify expected fuel economy gains from conversion to a downsized Diesel engine, engine disablement at a vehicle rest, and regenerative braking. However, the simulator also demonstrates a reduced fuel economy from extended operation of the vehicle in a pure electric mode. Moreover, the simulator indicates a concern with the ability of the tractive electric machine and proposed high-voltage battery pack to sufficiently and solely power the vehicle in a pure electric mode. Further findings of the simulated vehicle in full hybrid-electric vehicle operation clearly reveal the control strategy's preference in exclusively relying upon the Diesel engine for most normal operation. Reasons for this behavior primarily result from the relatively high efficiency of the Diesel engine and ensuing lack of opportunity to improve overall system efficiency through engine load shifting. Still, the downsized engine necessitates some presence of power electronics for supplementation during large power requests. Therefore, for this particular vehicle architecture, the control strategy may be better suited to simply maintain sufficient charge of the high-voltage battery pack for supplemental power delivery as opposed to aggressive and frequent use of the electric machines. Reflection of these simulation results along with some certain intangible issues motivates several suggestions concerning a few particular potential vehicle architecture modifications for consideration and contemplation by the Ohio State Challenge X team.
Author: John Paul Arata (III.)
Publisher:
ISBN:
Category : Computer simulation
Languages : en
Pages :
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Book Description
Power-split hybrid-electric vehicles (HEVs) provide two power paths between the internal combustion (IC) engine and the driven wheels through gearing and electric machines (EMs) composing an electrically variable transmission (EVT). EVTs allow IC engine control such that rotational speed is independent of vehicle speed at all times. By breaking the rigid mechanical connection between the IC engine and the driven wheels, EVTs allow the IC engine to operate in the most efficient region of its characteristic brake specific fuel consumption (BSFC) map. If the most efficient IC engine operating point produces more power than is requested by the driver, the excess IC engine power can be stored in the energy storage system (ESS) and used later. Conversely, if the most efficient IC engine operating point does not meet the power request of the driver, the ESS delivers the difference to the wheels through the EMs. Therefore with an intelligent supervisory control strategy, power-split architectures can advantageously combine traditional series and parallel power paths.
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: 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: 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:
Publisher:
ISBN:
Category :
Languages : en
Pages : 458
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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 J. Böhme
Publisher: Springer
ISBN: 3319513176
Category : Technology & Engineering
Languages : en
Pages : 549
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Book Description
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.
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.
