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This research project compares laboratory-measured fuel economy of a medium-duty diesel powered hydraulic hybrid vehicle drivetrain to both a conventional diesel drivetrain and a conventional gasoline drivetrain in a typical commercial parcel delivery application. Vehicles in this study included a model year 2012 Freightliner P10HH hybrid compared to a 2012 conventional gasoline P100 and a 2012 conventional diesel parcel delivery van of similar specifications. Drive cycle analysis of 484 days of hybrid parcel delivery van commercial operation from multiple vehicles was used to select three standard laboratory drive cycles as well as to create a custom representative cycle. These four cycles encompass and bracket the range of real world in-use data observed in Baltimore United Parcel Service operations.

This study compared fuel economy and emissions between heavy-duty hybrid electric vehicles (HEVs) and equivalent conventional diesel vehicles. In-use field data were collected from daily fleet operations carried out at a FedEx facility in California on six HEV and six conventional 2010 Freightliner M2-106 straight box trucks. Field data collection primarily focused on route assessment and vehicle fuel consumption over a six-month period. Chassis dynamometer testing was also carried out on one conventional vehicle and one HEV to determine differences in fuel consumption and emissions. Route data from the field study was analyzed to determine the selection of dynamometer test cycles. From this analysis, the New York Composite (NYComp), Hybrid Truck Users Forum Class 6 (HTUF 6), and California Air Resource Board (CARB) Heavy Heavy-Duty Diesel Truck (HHDDT) drive cycles were chosen.

When operated, the cabin climate control system is the largest auxiliary load on a vehicle. This load has significant impact on fuel economy for conventional and hybrid vehicles, and it drastically reduces the driving range of all-electric vehicles (EVs). Heating is even more detrimental to EV range than cooling because no engine waste heat is available. Reducing the thermal loads on the vehicle climate control system will extend driving range and increase the market penetration of EVs. Researchers at the National Renewable Energy Laboratory have evaluated strategies for vehicle climate control load reduction with special attention toward grid-connected electric vehicles. Outdoor vehicle thermal testing and computational modeling were used to assess potential strategies for improved thermal management and to evaluate the effectiveness of thermal load reduction technologies. A human physiology model was also used to evaluate the impact on occupant thermal comfort.

Four metrics related to vehicle duty cycle are derived from the energy equation of vehicle motion. Three key application areas are introduced. The first is the ability to quantify the sameness between vehicle duty cycles and the ability to asses a duty cycle's suitability for hybrid vehicle usage. The second area of application allows for the estimation of fuel consumption for a given vehicle over a target duty cycle. The third area of application allows us to predict how non-propulsion fuel use will affect energy use. The paper ends with real-world examples involving actual heavy-duty hybrids.

Plug-in hybrid electric vehicles (PHEVs) differ from hybrid vehicles (HEVs) with their ability to use off-board electricity generation to recharge their energy storage systems. In addition to possessing charge-sustaining HEV operation capability, PHEVs use the stored electrical energy during a charge-depleting operating period to displace a significant amount of petroleum consumption. The particular operating strategy employed during the charge-depleting mode will significantly influence the component attributes and the value of the PHEV technology. This paper summarizes three potential energy management strategies, and compares the implications of selecting one strategy over another in the context of the aggressiveness and distance of the duty cycle over which the vehicle will likely operate.

Today's hybrid electric vehicle (HEV) controls do not necessarily provide maximum fuel savings over all drive cycles. An approach that employs route-based control could improve HEV efficiency at potentially minimal additional cost. This paper evaluates a range of route-based control approaches and identifies look-ahead strategies (using input from “on-the-fly” route predictions) as an area meriting further analysis. A novel implementation approach is developed and discussed, and a comparison with simulation results using an optimized general control setting indicates that fuel savings of approximately 2% to 4% can be obtained with route-based control. Given the increasing prevalence of GPS systems in vehicles, this advance has the potential to provide considerable aggregate fuel savings if applied across the entire national fleet. For instance, a 3% across-the-board reduction in HEV fuel use would save nearly 6.5 million gallons of fuel annually in the United States.

Electrifying transportation can reduce or eliminate dependence on foreign fuels, emission of green house gases, and emission of pollutants. One challenge is finding a pathway for vehicles that gains wide market acceptance to achieve a meaningful benefit. This paper evaluates several approaches aimed at making plug-in electric vehicles (EV) and plug-in hybrid electric vehicles (PHEVs) cost-effective including opportunity charging, replacing the battery over the vehicle life, improving battery life, reducing battery cost, and providing electric power directly to the vehicle during a portion of its travel. Many combinations of PHEV electric range and battery power are included. For each case, the model accounts for battery cycle life and the national distribution of driving distances to size the battery optimally. Using the current estimates of battery life and cost, only the dynamically plugged-in pathway was cost-effective to the consumer.

Delphi and the National Renewable Energy Laboratory (NREL) collaborated to develop a simulation code to model the mechanical and electrical architectures of a series hybrid vehicle simultaneously. This co-simulation code is part of the larger ADVISOR® product created by NREL and diverse partners. Simulation of the macro power flow in a series hybrid vehicle requires both the mechanical drivetrain and the entire electrical architecture. It is desirable to solve the electrical network equations in an environment designed to comprehend such a network and solve the equations in terms of current and voltage. The electrical architecture for the series hybrid vehicle has been modeled in Saber™ to achieve these goals. This electrical architecture includes not only the high-voltage battery, generator, and traction motor, but also the normal low-voltage bus (14V) with loads common to all vehicles.

Hybrid vehicles may respond to fuel variables in unique ways; they could even require a unique driveability test. The Coordinating Research Council (CRC) conducted a program to determine the effect of ethanol content on driveability performance under cool ambient conditions. In addition to the 27 vehicles in the main fleet, four hybrid electric vehicles (HEVs) were tested using the same fuels and driveability procedure. These HEVs responded to fuel in a manner similar to conventional vehicles; however, the HEVs showed unique driving characteristics not well captured in the existing test.

One of the challenges of analyzing vehicular electrical systems is the co-dependence of the electrical system and the propulsion system. Even in traditional vehicles where the electrical power budget is very low, the electrical system analysis for macro power utilization over a drive cycle requires knowledge of the generator shaft rpm profile during the drive cycle. This co-dependence increases as the electrical power budget increases, and the integration of the two systems becomes complete when hybridization is chosen. Last year at this conference, the authors presented a paper entitled “Dual Voltage Electrical System Simulations.” That paper established validation for a suite of electrical component models and demonstrated the ability to predict system performance both on a macro power flow (entire drive cycle) level and a detailed transient-event level. The techniques were applicable to 12V, 42V, dual voltage, and/or elevated voltage systems.

The air-conditioning (A/C) system compressor load can significantly impact the fuel economy and tailpipe emissions of conventional and hybrid electric automobiles. With the increasing emphasis on fuel economy, it is clear that the A/C compressor load needs to be reduced. In order to accomplish this goal, more efficient climate control delivery systems and reduced peak soak temperatures will be necessary to reduce the impact of vehicle A/C systems on fuel economy and tailpipe emissions. Good analytical techniques are important in identifying promising concepts. The goal at the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) is to assess thermal comfort, fuel economy, and emissions by using an integrated modeling approach composed of CAD, computational fluid dynamics (CFD), thermal comfort, and vehicle simulation tools. This paper presents NREL's vehicle integrated modeling process.

As part of a U.S. Department of Energy supported study, the National Renewable Energy Laboratory has benchmarked a Toyota Prius hybrid electric vehicle from three aspects: system analysis, auxiliary loads, and battery pack thermal performance. This paper focuses on the testing of the battery back out of the vehicle. More recent in-vehicle dynamometer tests have confirmed these out-of-vehicle tests. Our purpose was to understand how the batteries were packaged and performed from a thermal perspective. The Prius NiMH battery pack was tested at various temperatures (0°C, 25°C, and 40°C) and under driving cycles (HWFET, FTP, and US06). The airflow through the pack was also analyzed. Overall, we found that the U.S. Prius battery pack thermal management system incorporates interesting features and performs well under tested conditions.

The impacts of fuel cell system power response capability on optimal hybrid and neat fuel cell vehicle configurations have been explored. Vehicle system optimization was performed with the goal of maximizing fuel economy over a drive cycle. Optimal hybrid vehicle design scenarios were derived for fuel cell systems with 10 to 90% power transient response times of 0, 2, 5, 10, 20, and 40 seconds. Optimal neat fuel cell vehicles where generated for responses times of 0, 2, 5, and 7 seconds. DIRECT, a derivative-free optimization algorithm, was used in conjunction with ADVISOR, a vehicle systems analysis tool, to systematically change both powertrain component sizes and the vehicle energy management strategy parameters to provide optimal vehicle system configurations for the range of response capabilities.

Proper electric and thermal management of an HEV battery pack, consisting of many modules of cells, is imperative. During operation, voltage and temperature differences in the modules/cells can lead to electrical imbalances from module to module and decrease pack performance by as much as 25%. An active battery management system (BMS) is a must to monitor, control, and balance the pack. The University of Toledo, with funding from the U.S. Department of Energy and in collaboration with DaimlerChrysler and the National Renewable Energy Laboratory has developed a modular battery management system for HEVs. This modular unit is a 2nd generation system, as compared to a previous 1st generation centralized system. This 2nd generation prototype can balance a battery pack based on cell-to-cell measurements and active equalization. The system was designed to work with several battery types, including lithium ion, NiMH, or lead acid.

A compact, lightweight compression-ignition engine designed for high fuel economy and low emissions was developed by ISUZU for the GM PNGV vehicle. This engine was the key component in the selected parallel hybrid vehicle powertrain for the 80 mpg fuel economy target. The base hardware was derived from a 1.7 Liter, 4-cylinder engine, and a three-cylinder version was created for the PNGV application. To achieve the required high efficiency, the engine used lightweight components thus minimizing weight and friction. To reduce exhaust emissions, electromechanical actuators were used for EGR, intake throttle, and turbocharger. Through careful application of these devices and combustion development, stringent engine out exhaust emission targets were also met.

Currently, several cost-per-mile calculators exist that can provide estimates of acquisition and operating costs for consumers and fleets. However, these calculators are limited in their ability to determine the difference in cost per mile for consumer versus fleet ownership, to calculate the costs beyond one ownership period, to show the sensitivity of the cost per mile to the annual vehicle miles traveled (VMT), and to estimate future increases in operating and ownership costs. Oftentimes, these tools apply a constant percentage increase over the time period of vehicle operation, or in some cases, no increase in direct costs at all over time. A more accurate cost-per-mile calculator has been developed that allows the user to analyze these costs for both consumers and fleets. Operating costs included in the calculation tool include fuel, maintenance, tires, and repairs; ownership costs include insurance, registration, taxes and fees, depreciation, financing, and tax credits.

Hybrid electric vehicles, plug-in hybrid electric vehicles, and battery electric vehicles offer the potential to reduce both oil imports and greenhouse gases, as well as to offer a financial benefit to the driver. However, assessing these potential benefits is complicated by several factors, including the driving habits of the operator. We focus on driver aggression, i.e., the level of acceleration and velocity characteristic of travel, to (1) assess its variation within large, real-world drive datasets, (2) quantify its effect on both vehicle efficiency and economics for multiple vehicle types, (3) compare these results to those of standard drive cycles commonly used in the industry, and (4) create a representative drive cycle for future analyses where standard drive cycles are lacking.

Chassis dynamometer testing of two 60 foot articulated transit busses, one conventional and one hybrid, was conducted at the National Renewable Energy Laboratory's, ReFUEL facility. Both test vehicles were 2004 New Flyer busses powered by Caterpillar C9 8.8L engines, with the hybrid vehicle incorporating a GM-Allison advanced hybrid electric drivetrain. Both vehicles also incorporated an oxidizing diesel particulate filter. The fuel economy and emissions benefits of the hybrid vehicle were evaluated over four driving cycles; Central Business District (CBD), Orange County (OCTA), Manhattan (MAN) and a custom test cycle developed from in-use data of the King County Metro (KCM) fleet operation. The hybrid vehicle demonstrated the highest improvement in fuel economy (mpg basis) over the low speed, heavy stop-and-go driving conditions of the Manhattan test cycle (74.6%) followed by the OCTA (50.6%), CBD (48.3%) and KCM (30.3%).

Software development tools can be used in conjunction with test automation tools to validate controller software. Test automation tools must have an open architecture to interface with all the different software and hardware components, within a control validation project. Therefore software development tools like Matlab/Simulink will be able to exchange data via real time interface software with test automation tools. The test automation tool must be flexible to pass data back and forth from/to Microsoft standard software programs like Excel.

This research project compares the in-use and laboratory-derived fuel economy of a medium-duty hybrid electric drivetrain with “engine off at idle” capability to a conventional drivetrain in a typical commercial package delivery application. Vehicles in this study included eleven model year 2010 Freightliner P100H hybrids that were placed in service at a United Parcel Service (UPS) facility in Minneapolis, Minn., during the first half of 2010. These hybrid vehicles were evaluated for 18 months against eleven model year 2010 Freightliner P100D diesels that were placed in service at the same facility a couple months after the hybrids. Both vehicle study groups use the same model year 2009 Cummins ISB 200 HP engine. The vehicles of interest were chosen by comparing the average daily mileage of the hybrid group to that of a similar size and usage diesel group.