Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
Abstract : This report presents an analysis on energy consumption of a Gen II Chevrolet Volt PHEV and its energy savings potential in Real World Driving scenarios with the help of vehicle connectivity. The research on the energy consumption analysis and optimization using connectivity will focus on four main areas of contribution which includes 1.) vehicle testing on a pre-defined drive cycle and alternative routing near the Michigan Tech campus and APS research center that is a continuation of previous students' works, 2) the energy savings potential of vehicle platooning and various vehicle platoon configurations, 3) the updating of a PHEV implementation of a charge depleting-charge sustaining energy blending optimization algorithm and 4) the development of an IC Engine start-stop prediction algorithm for HEV and PHEV's using connectivity data. The first part of the report discusses the development of a Real World Drive Cycle called Reverse MTU Drive Cycle which is the successor of MTU Drive Cycle, a drive cycle previously developed local to the Michigan Technological University. The energy consumption of the PHEV on the R-MTUDC is analyzed and the baseline characteristics of the drive cycle is setup. A set of baseline drive cycle characteristics was developed and tests on the drive cycle proved that the energy consumption on the real-world drive route is consistent with variability less than 3%. The next part of the report investigates the energy savings potential of the cars when they are traveling in a platoon rather than independently. Various tests have been conducted to investigate energy savings under different platoon scenarios, like variable gap settings, variable speeds, inclusion of a vehicle with aero-modifier and effect of moving collinearly in a platoon. A platoon wide savings as high as 8.3% was achieved in the study. After that, the report discusses the on-road implementation of a Route Based Blended Mode Optimizer, in PHEVs, which comes up with an optimal control matrix using Dynamic Programming and Cost-To-Go matrix, to make use of the Hold mode capability of the Volts, to operate the cars in Charge Sustaining mode at sections of Drive Cycles where it is most efficient to be operated. Upto, 5% savings in energy was obtained using the optimizer. Some of the runs didn't provide the desired results and this is also investigated. Finally, the report presents the development of two kinds of Engine Start-Stop Optimizers, which utilizes vehicle connectivity and vehicle energy consumption model to come up with an optimal control map of regions on the predicted driving route where the engine should be turned On and Off for minimizing energy consumption in HEVs and PHEVs. The first optimizer uses vehicle and route characteristics to predict engine starts and stops and then optimizes these signals based on decisions made from energy calculations. The second optimizer uses Dynamic Programming to create a matrix of engine On and Off signals based on the route characteristics. These controllers are shown to provide energy savings as high as 8% on some routes.
Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
Plug-in hybrid electric vehicles (PHEVs) are being developed for mass production by the automotive industry. PHEVs have been touted for their potential to reduce the US transportation sector's dependence on petroleum and cut greenhouse gas (GHG) emissions by (1) using off-peak excess electric generation capacity and (2) increasing vehicles energy efficiency. A well-to-wheels (WTW) analysis - which examines energy use and emissions from primary energy source through vehicle operation - can help researchers better understand the impact of the upstream mix of electricity generation technologies for PHEV recharging, as well as the powertrain technology and fuel sources for PHEVs. For the WTW analysis, Argonne National Laboratory researchers used the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model developed by Argonne to compare the WTW energy use and GHG emissions associated with various transportation technologies to those associated with PHEVs. Argonne researchers estimated the fuel economy and electricity use of PHEVs and alternative fuel/vehicle systems by using the Powertrain System Analysis Toolkit (PSAT) model. They examined two PHEV designs: the power-split configuration and the series configuration. The first is a parallel hybrid configuration in which the engine and the electric motor are connected to a single mechanical transmission that incorporates a power-split device that allows for parallel power paths - mechanical and electrical - from the engine to the wheels, allowing the engine and the electric motor to share the power during acceleration. In the second configuration, the engine powers a generator, which charges a battery that is used by the electric motor to propel the vehicle; thus, the engine never directly powers the vehicle's transmission. The power-split configuration was adopted for PHEVs with a 10- and 20-mile electric range because they require frequent use of the engine for acceleration and to provide energy when the battery is depleted, while the series configuration was adopted for PHEVs with a 30- and 40-mile electric range because they rely mostly on electrical power for propulsion. Argonne researchers calculated the equivalent on-road (real-world) fuel economy on the basis of U.S. Environmental Protection Agency miles per gallon (mpg)-based formulas. The reduction in fuel economy attributable to the on-road adjustment formula was capped at 30% for advanced vehicle systems (e.g., PHEVs, fuel cell vehicles [FCVs], hybrid electric vehicles [HEVs], and battery-powered electric vehicles [BEVs]). Simulations for calendar year 2020 with model year 2015 mid-size vehicles were chosen for this analysis to address the implications of PHEVs within a reasonable timeframe after their likely introduction over the next few years. For the WTW analysis, Argonne assumed a PHEV market penetration of 10% by 2020 in order to examine the impact of significant PHEV loading on the utility power sector. Technological improvement with medium uncertainty for each vehicle was also assumed for the analysis. Argonne employed detailed dispatch models to simulate the electric power systems in four major regions of the US: the New England Independent System Operator, the New York Independent System Operator, the State of Illinois, and the Western Electric Coordinating Council. Argonne also evaluated the US average generation mix and renewable generation of electricity for PHEV and BEV recharging scenarios to show the effects of these generation mixes on PHEV WTW results. Argonne's GREET model was designed to examine the WTW energy use and GHG emissions for PHEVs and BEVs, as well as FCVs, regular HEVs, and conventional gasoline internal combustion engine vehicles (ICEVs). WTW results are reported for charge-depleting (CD) operation of PHEVs under different recharging scenarios. The combined WTW results of CD and charge-sustaining (CS) PHEV operations (using the utility factor method) were also examined and reported. According to the utility factor method, the share of vehicle miles traveled during CD operation is 25% for PHEV10 and 51% for PHEV40. Argonne's WTW analysis of PHEVs revealed that the following factors significantly impact the energy use and GHG emissions results for PHEVs and BEVs compared with baseline gasoline vehicle technologies: (1) the regional electricity generation mix for battery recharging and (2) the adjustment of fuel economy and electricity consumption to reflect real-world driving conditions. Although the analysis predicted the marginal electricity generation mixes for major regions in the United States, these mixes should be evaluated as possible scenarios for recharging PHEVs because significant uncertainties are associated with the assumed market penetration for these vehicles. Thus, the reported WTW results for PHEVs should be directly correlated with the underlying generation mix, rather than with the region linked to that mix.
Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
Abstract : This thesis details the development of a methodology to blend charge-depleting (CD) and charge-sustaining (CS) modes in a multi-mode plug-in hybrid electric vehicle (PHEV) to minimize energy consumption when the planned drive route cannot be completely executed in all-electric mode. This methodology enables efficient utilization of onboard energy resources by using increased awareness of driving conditions facilitated by Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), Vehicle-to-Everything (V2X) connectivity, and onboard perception technologies of Connected and Automated Vehicles (CAVs). With such application demanding a real-time update of optimal mode scheme to dynamic traffic conditions, the emphasis of this study is to develop a quick and computationally inexpensive blended mode optimizer by reduced-order modeling of Chevrolet Volt. On-road validation of the developed optimizer on a fleet of 4 instrumented vehicles revealed energy savings in the range of 2 to 12% and an initial optimization time less than 7 seconds for a 24-mile drive cycle.
Author: Emanuele Crisostomi Publisher: CRC Press ISBN: 1498745008 Category : Technology & Engineering Languages : en Pages : 261
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: Publisher: ISBN: Category : Languages : en Pages :
Book Description
Researchers at Argonne National Laboratory expanded the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model and incorporated the fuel economy and electricity use of alternative fuel/vehicle systems simulated by the Powertrain System Analysis Toolkit (PSAT) to conduct a well-to-wheels (WTW) analysis of energy use and greenhouse gas (GHG) emissions of plug-in hybrid electric vehicles (PHEVs). The WTW results were separately calculated for the blended charge-depleting (CD) and charge-sustaining (CS) modes of PHEV operation and then combined by using a weighting factor that represented the CD vehicle-miles-traveled (VMT) share. As indicated by PSAT simulations of the CD operation, grid electricity accounted for a share of the vehicle's total energy use, ranging from 6% for a PHEV 10 to 24% for a PHEV 40, based on CD VMT shares of 23% and 63%, respectively. In addition to the PHEV's fuel economy and type of on-board fuel, the marginal electricity generation mix used to charge the vehicle impacted the WTW results, especially GHG emissions. Three North American Electric Reliability Corporation regions (4, 6, and 13) were selected for this analysis, because they encompassed large metropolitan areas (Illinois, New York, and California, respectively) and provided a significant variation of marginal generation mixes. The WTW results were also reported for the U.S. generation mix and renewable electricity to examine cases of average and clean mixes, respectively. For an all-electric range (AER) between 10 mi and 40 mi, PHEVs that employed petroleum fuels (gasoline and diesel), a blend of 85% ethanol and 15% gasoline (E85), and hydrogen were shown to offer a 40-60%, 70-90%, and more than 90% reduction in petroleum energy use and a 30-60%, 40-80%, and 10-100% reduction in GHG emissions, respectively, relative to an internal combustion engine vehicle that used gasoline. The spread of WTW GHG emissions among the different fuel production technologies and grid generation mixes was wider than the spread of petroleum energy use, mainly due to the diverse fuel production technologies and feedstock sources for the fuels considered in this analysis. The PHEVs offered reductions in petroleum energy use as compared with regular hybrid electric vehicles (HEVs). More petroleum energy savings were realized as the AER increased, except when the marginal grid mix was dominated by oil-fired power generation. Similarly, more GHG emissions reductions were realized at higher AERs, except when the marginal grid generation mix was dominated by oil or coal. Electricity from renewable sources realized the largest reductions in petroleum energy use and GHG emissions for all PHEVs as the AER increased. The PHEVs that employ biomass-based fuels (e.g., biomass-E85 and -hydrogen) may not realize GHG emissions benefits over regular HEVs if the marginal generation mix is dominated by fossil sources. Uncertainties are associated with the adopted PHEV fuel consumption and marginal generation mix simulation results, which impact the WTW results and require further research. More disaggregate marginal generation data within control areas (where the actual dispatching occurs) and an improved dispatch modeling are needed to accurately assess the impact of PHEV electrification. The market penetration of the PHEVs, their total electric load, and their role as complements rather than replacements of regular HEVs are also uncertain. The effects of the number of daily charges, the time of charging, and the charging capacity have not been evaluated in this study. A more robust analysis of the VMT share of the CD operation is also needed.
Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
Abstract : A recent study at Michigan Technological University as part of the NEXTCAR DOE APRA-E Project was conducted to determine the potential energy savings of a plug-in hybrid electric vehicle (PHEV) equipped with various Connected and Automated Vehicle (CAV) Technologies. One aspect of this study focused on the development of an Eco Approach and Departure (Eco AnD) Application that would further reduce the energy consumed around a signalized intersection. Many modern intersections are equipped with traffic signals that can broadcast Basic Safety (BSM), MAP, and Signal Phase and Timing (SPaT) message sets that contain intersection ID, location, current phase, and cyclic timing information. This data can then be used as inputs to an optimization algorithm that will predict the most energy efficient maneuver for a vehicle as it approaches and departs from an intersection. This Eco AnD Application has been developed to allow a test vehicle to interface with the traffic signals, run the optimization routine, and then relay the information back to the driver in the form of a velocity profile. Benefits of an Eco Approach and Departure Application have been evaluated on six different intersections on the Michigan Technological University Drive Cycle (MTUDC). A driver, given information about the cyclic timing and offsets of each intersection, drove through each intersection numerous times collecting data that would be used to show energy consumption of the vehicle. The energy consumption using the human driver was then compared to the maneuvers generated by the Eco AnD Application. Energy reduction benefits could then be determined on an intersection-by-intersection basis, for a subset of the MTUDC, and for the entire MTUDC. Thus far, the Eco AnD Application has been used to experimentally demonstrate 2-4% energy savings on the MTUDC.
Author: Mohammad Alzorgan Publisher: ISBN: Category : Hybrid electric vehicles Languages : en Pages : 71
Book Description
The environmental impact of the fossil fuels has increased tremendously in the last decade. This impact is one of the most contributing factors of global warming. This research aims to reduce the amount of fuel consumed by vehicles through optimizing the control scheme for the future route information. Taking advantage of more degrees of freedom available within PHEV, HEV, and FCHEV energy management allows more margin to maximize efficiency in the propulsion systems. The application focuses on reducing the energy consumption in vehicles by acquiring information about the road grade. Road elevations are obtained by use of Geographic Information System (GIS) maps to optimize the controller. The optimization is then reflected on the powertrain of the vehicle. The approach uses a Model Predictive Control (MPC) algorithm that allows the energy management strategy to leverage road grade to prepare the vehicle for minimizing energy consumption during an uphill and potential energy harvesting during a downhill. The control algorithm will predict future energy/power requirements of the vehicle and optimize the performance by instructing the power split between the internal combustion engine (ICE) and the electric-drive system. Allowing for more efficient operation and higher performance of the PHEV, and HEV. Implementation of different strategies, such as MPC and Dynamic Programming (DP), is considered for optimizing energy management systems. These strategies are utilized to have a low processing time. This approach allows the optimization to be integrated with ADAS applications, using current technology for implementable real time applications. The Thesis presents multiple control strategies designed, implemented, and tested using real-world road elevation data from three different routes. Initial simulation based results show significant energy savings. The savings range between 11.84% and 25.5% for both Rule Based (RB) and DP strategies on the real world tested routes. Future work will take advantage of vehicle connectivity and ADAS systems to utilize Vehicle to Vehicle (V2V), Vehicle to Infrastructure (V2I), traffic information, and sensor fusion to further optimize the PHEV and HEV toward more energy efficient operation.
Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
Primary Factors that Impact the Fuel Consumption of Plug-In Hybrid Electric Vehicles RICHARD 'BARNEY' CARLSON, MATTHEW G. SHIRK Idaho National Laboratory 2525 N. Fremont Ave., Idaho Falls, ID 83415, USA [email protected] Abstract Plug-in Hybrid Electric Vehicles (PHEV) have proven to significantly reduce petroleum consumption as compared to conventional internal combustion engine vehicles (ICE) by utilizing electrical energy for propulsion. Through extensive testing of PHEV's, analysis has shown that the fuel consumption of PHEV's is more significantly affected than conventional vehicles by either the driver's input or by the environmental inputs around the vehicle. Six primary factors have been identified that significantly affect the fuel consumption of PHEV's. In this paper, these primary factors are analyzed from on-road driving and charging data from over 200 PHEV's throughout North America that include Hymotion Prius conversions and Hybrids Plus Escape conversions. The Idaho National Laboratory (INL) tests plug-in hybrid electric (PHEV) vehicles as part of its conduct of DOE's Advanced Vehicle Testing Activity (AVTA). In collaboration with its 75 testing partners located in 23 states and Canada, INL has collected data on 191 PHEVs, comprised of 12 different PHEV models (by battery manufacturer). With more than 1 million PHEV test miles accumulated to date, the PHEVs are fleet, track, and dynamometer tested. Six Primary Factors The six primary factors that significantly impact PHEV fuel consumption are listed below. Some of the factors are unique to plug-in vehicles while others are common for all types of vehicles. 1. Usable Electrical Energy is dictated by battery capacity, rate of depletion as well as when the vehicle was last plugged-in. With less electrical energy available the powertrain must use more petroleum to generate the required power output. 2. Driver Aggressiveness impacts the fuel consumption of nearly all vehicles but this impact is greater for high efficiency powertrains. 3. Accessory Utilization like air conditioner systems or defroster systems can use a significant amount of additional energy that is not contributing to the propulsion of the vehicle. 4. Route Type such as city, highway or mountainous driving can affect the fuel consumption since it can involve stop and go driving or ascending a step grade. 5. Cold Start / Key On includes control strategies to improve cold start emissions as well as control routines to quickly supply cabin heat. These control strategies are necessary for consumer acceptance even though fuel consumption is negatively impacted. 6. Ambient Temperature can reduce the efficiency of many powertrain components by significantly increasing fluid viscosity. For vehicles that utilize battery energy storage systems, the temperature of the battery system can greatly affect the power output capability therefore reducing its system effectiveness. The analysis of the six primary factors that impact fuel economy of PHEV's helped to identify areas of potential further development as well as may assist in informing drivers of these effects in an effort to modify driving behavior to reduce petroleum consumption.
Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
The Plug-in Hybrid Electric Vehicle (PHEV) Fuel Use Reporting Methods and Results report provides real world test results from PHEV operations and testing in 20 United States and Canada. Examples are given that demonstrate the significant variations operational parameters can have on PHEV petroleum use. In addition to other influences, PHEV mpg results are significantly impacted by driver aggressiveness, cold temperatures, and whether or not the vehicle operator has charged the PHEV battery pack. The U.S. Department of Energy's (DOE's) Advanced Vehicle Testing Activity (AVTA) has been testing plug-in hybrid electric vehicles (PHEVs) for several years. The AVTA http://avt.inl.gov/), which is part of DOE's Vehicle Technology Program, also tests other advanced technology vehicles, with 12 million miles of total test vehicle and data collection experience. The Idaho National Laboratory is responsible for conducting the light-duty vehicle testing of PHEVs. Electric Transportation Engineering Corporation also supports the AVTA by conducting PHEV and other types of testing. To date, 12 different PHEV models have been tested, with more than 600,000 miles of PHEV operations data collected.
Author: Yiming He Publisher: ISBN: Category : Languages : en Pages :
Book Description
Abstract: The U.S. federal government is seeking useful applications of Vehicle-Infrastructure Integration (VII) to encourage a greener and more efficient transportation system; Plug-in Hybrid Electric Vehicles (PHEVs) are considered as one of the most promising automotive technologies for such an application. In this study, the author demonstrates a strategy to improve PHEV energy efficiency via the use of VII. This dissertation, which is composed of three published peer-reviewed journal articles, demonstrates the efficacies of the PHEV-VII system as regards to both the energy use and environmental impact under different scenarios. The first article demonstrates the capabilities of and benefits achievable for a power-split drivetrain PHEV with a VII-based energy optimization strategy. With the consideration of several real-time implementation issues, the results show improvements in fuel consumption with the PHEV-VII system under various driving cycles. In the second article, a forward PHEV model with an energy management system and a cycle optimization algorithm is evaluated for energy efficiency. Prediction cycles are optimized using a cycle optimization strategy, which resulted in 56-86% fuel efficiency improvements for conventional vehicles. When combined with the PHEV power management system, about 115% energy efficiency improvements were achieved. The third article focuses on energy and emission impacts of the PHEV-VII system. At a network level, a benefit-cost analysis is conducted, which indicated that the benefits outweighed costs for PHEV and Hybrid Electric Vehicle (HEV) integrated with a VII system at the fleet penetration rate of 20% and 30%, respectively.
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Author: Emanuele Crisostomi
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Author: Mohammad Alzorgan
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Author: Yiming He