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The air-conditioning (A/C) compressor load significantly impacts the fuel economy of conventional vehicles and the fuel use/range of plug-in hybrid electric vehicles (PHEV). A National Renewable Energy Laboratory (NREL) vehicle performance analysis shows the operation of the air conditioner reduces the charge depletion range of a 40-mile range PHEV from 18% to 30% in a worst case hot environment. Designing for air conditioning electrical loads impacts PHEV and electric vehicle (EV) energy storage system size and cost. While automobile manufacturers have climate control procedures to assess A/C performance, and the U.S. EPA has the SCO3 drive cycle to measure indirect A/C emissions, there is no automotive industry consensus on a vehicle level A/C fuel use test procedure. With increasing attention on A/C fuel use due to increased regulatory activities and the development of PHEVs and EVs, a test procedure is needed to accurately assess the impact of climate control loads.

To help guide heavy vehicle engine, fuel, and exhaust after-treatment technology development, the U.S. Department of Energy and the Lovelace Respiratory Research Institute are conducting research not addressed elsewhere on aspects of the toxicity of particulate engine emissions. Advances in these technologies that reduce diesel particulate mass emissions may result in changes in particle composition, and there is concern that the number of ultrafine (<0.1 micron) particles may increase. All present epidemiological and laboratory data on the toxicity of diesel emissions were derived from emissions of older-technology engines. New, short-term toxicity data are needed to make health-based choices among diesel technologies and to compare the toxicity of diesel emissions to those of other engine technologies.

Hydrogen fuel cell vehicles (FCVs) appear to be a promising solution for the future of clean and efficient personal transportation. Issues of how to generate the hydrogen and then store it on-board to provide satisfactory driving range must still be resolved before they can compete with conventional vehicles. Alternatively, FCVs could obtain hydrogen from on-board reforming of gasoline or other fuels such as methanol or ethanol. On-board reformers convert fuel into a hydrogen-rich fuel stream through catalytic reactions in several stages. The high temperatures associated with fuel processing present an engineering challenge to warm up the reformer quickly and efficiently in a vehicle environment. Without a special warmup phase or vehicle hybridization, the reformer and fuel cell system must provide all power to move the vehicle, including ¼ power in 30 s, and ½ power in 3 min to satisfy the Federal Test Procedure (FTP) cycle demands.

Piston cooling nozzles/jets play several crucial roles in the power cylinder of an internal combustion engine. Primarily, they help with the thermal management of the piston and provide lubrication to the cylinder liner and the piston’s wrist pin. In order to evaluate the oil jet characteristics from various piston cooling nozzle (PCN) designs, a quantitative and objective process was developed. The PCN characterization began with a computational fluid dynamics (CFD) turbulent model to analyze the mean oil velocity and flow distribution at the nozzle exit/tip. Subsequently, the PCN was tested on a rig for a given oil temperature and pressure. A high-speed camera captured images at 2500 frames per second to observe the evolution of the oil stream as a function of distance from the nozzle exit. An algorithm comprised of standard digital image processing techniques was created to calculate the oil jet width and density.

Accumulation of lubricant and fuel derived ash in the diesel particulate filter (DPF) during vehicle operation results in a significant increase of pressure drop across the after-treatment system leading to loss of fuel economy and reduced soot storage capacity over time. Under certain operating conditions, the accumulated ash and/or soot cake layer can collapse resulting in ash deposits upstream from the typical ash plug section, henceforth termed mid-channel ash deposits. In addition, ash particles can bond (either physically or chemically) with neighboring particles resulting in formation of bridges across the channels that effectively block access to the remainder of the channel for the incoming exhaust gas stream. This phenomenon creates serious long-term durability issues for the DPF, which often must be replaced. Mid-channel deposits and ash bridges are extremely difficult to remove from the channels as they often sinter to the substrate.

In this study, a 15-L heavy-duty diesel engine and an emission control system consisting of diesel oxidation catalysts, NOx adsorber catalysts, and diesel particle filters were evaluated over the course of a 2000 hour aging study. The work is a follow-on to a previously documented development effort to establish system regeneration and sulfur management strategies. The study is one of five projects being conducted as part of the U.S. Department of Energy's Advanced Petroleum Based Fuels - Diesel Emission Control (APBF-DEC) activity. The primary objective of the study was to determine if the significant NOx and PM reduction efficiency (>90%) demonstrated in the development work could be maintained over time with a 15-ppm sulfur diesel fuel. The study showed that high NOx reduction efficiency can be restored after 2000 hours of operation and 23 desulfation cycles.

On-road fuel economy is known to vary significantly between individual trips in real-world driving conditions. This work introduces a methodology for rapidly simulating a specific vehicle’s fuel economy over the wide range of real-world conditions experienced across the country. On-road test data collected using a highly instrumented vehicle is used to refine and validate this modeling approach. Model accuracy relative to on-road data collection is relevant to the estimation of “off-cycle credits” that compensate for real-world fuel economy benefits that are not observed during certification testing on a chassis dynamometer.

Fuel usage negatively impacts the environment and is a significant portion of operational costs of moving freight globally. Reducing fuel consumption is key to lessening environmental impacts and maximizing freight efficiency, thereby increasing the profit margin of logistic operators. In this paper, fuel economy improvements of a cab-over style 49T heavy duty Foton truck powered by a Cummins 12-liter engine are studied and systematically applied for the China market. Most fuel efficiency improvements are found within the vehicle design when compared to opportunities available at the engine level. Vehicle design (improved aerodynamics), component selection/matching (low rolling resistance tires), and powertrain electronic features integration (shift schedule/electronic trim) offer the largest opportunities for lowering fuel consumption.

Electric vehicles (EVs) need highly optimized thermal management systems to improve range. Climate control can reduce vehicle efficiency and range by more than 50%. Due to the relative shortage of waste heat, heating the passenger cabin in EVs is difficult. Cabin cooling can take a high portion of the energy available in the battery. Compared to internal combustion engine-driven vehicles, different heating methods and more efficient cooling methods are needed, which can make EV thermal management systems more complex. More complex systems typically allow various alternative modes of operation that can be selected based on driving and ambient conditions. A good system simulation tool can greatly reduce the time and expense for developing these complex systems. A simulation model should also be able to efficiently co-simulate with vehicle simulation programs, and should be applicable for evaluating various control algorithms.

This paper presents multiple methods for predicting heavy/medium-duty vehicle fuel consumption based on driving cycle information. A polynomial model, a black box artificial neural net model, a polynomial neural network model, and a multivariate adaptive regression splines (MARS) model were developed and verified using data collected from chassis testing performed on a parcel delivery diesel truck operating over the Heavy Heavy-Duty Diesel Truck (HHDDT), City Suburban Heavy Vehicle Cycle (CSHVC), New York Composite Cycle (NYCC), and hydraulic hybrid vehicle (HHV) drive cycles. Each model was trained using one of four drive cycles as a training cycle and the other three as testing cycles. By comparing the training and testing results, a representative training cycle was chosen and used to further tune each method.

The National Renewable Energy Laboratory’s (NREL’s) CoolSim MATLAB/Simulink modeling framework was used to explore control strategies for an electric vehicle combined loop system. Three system variants of increased complexity and efficiency were explored: a glycol-based positive temperature coefficient heater (PTC), PTC with power electronics and electric motor (PEEM) waste heat recovery, and PTC with PEEM waste heat recovery plus heat pump versions. Additionally, the benefit of electric motor preheating was considered. A two-level control strategy was developed where the mode selection and component control were treated separately. Only the parameters typically available by vehicle sensors were used to control the system. The control approach included a mode selection algorithm and controllers for the compressor speed, cabin blower flow rate, coolant flow rate, and the front-end heat exchanger coolant bypass rate.

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.

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.

The National Renewable Energy Laboratory’s (NREL’s) CoolSim MATLAB/Simulink modeling framework was expanded by including a newly developed coolant loop solution method aimed at reducing the simulation effort for complex thermal management systems. The new approach does not require the user to identify specific coolant loops and their flow. The user only needs to connect the fluid network elements in a manner consistent with the desired schematic. Using the new solution method, a model of NREL's advanced combined coolant loop system for electric vehicles was created that reflected the test system architecture. This system was built using components provided by MAHLE Inc. and included both air conditioning and heat pump modes. Validation with test bench data and verification with the previous solution method were performed for 10 operating points spanning a range of ambient temperatures between -2°C and 43°C.

Annual fuel use for sleeper cab truck rest period idling is estimated at 667 million gallons in the United States, or 6.8% of long-haul truck fuel use. Truck idling during a rest period represents zero freight efficiency and is largely done to supply accessory power for climate conditioning of the cab. The National Renewable Energy Laboratory’s CoolCab project aims to reduce heating, ventilating, and air conditioning (HVAC) loads and resulting fuel use from rest period idling by working closely with industry to design efficient long-haul truck thermal management systems while maintaining occupant comfort. Enhancing the thermal performance of cab/sleepers will enable smaller, lighter, and more cost-effective idle reduction solutions. In addition, if the fuel savings provide a one- to three-year payback period, fleet owners will be economically motivated to incorporate them.

This research focuses on the technical issues that are critical to the adoption of high-energy-producing lithium Ion batteries. In addition to high energy density / high power density, this publication considers performance requirements that are necessary to assure lithium ion technology as the battery format of choice for electrified vehicles. Presentation of prime topics includes: • Long calendar life (greater than 10 years) • Sufficient cycle life • Reliable operation under hot and cold temperatures • Safe performance under extreme conditions • End-of-life recycling To achieve aggressive fuel economy standards, carmakers are developing technologies to reduce fuel consumption, including hybridization and electrification. Cost and affordability factors will be determined by these relevant technical issues which will provide for the successful implementation of lithium ion batteries for application in future generations of electrified vehicles.

In 2011, the United States imported almost half of its petroleum. Lightweighting vehicles reduces that dependency directly by decreasing the engine, braking and rolling resistance losses, and indirectly by enabling a smaller, more efficiently operating engine to provide the same performance. The Future Automotive Systems Technology Simulator (FASTSim) tool was used to quantify these impacts. FASTSim is the U.S. Department of Energy's (DOE's) high-level vehicle powertrain model developed at the National Renewable Energy Laboratory. It steps through a time versus speed drive cycle to estimate the powertrain forces required to meet the cycle. It simulates the major vehicle powertrain components and their losses. It includes a cost model based on component sizing and fuel prices. FASTSim simulated different levels of lightweighting for four different powertrains.

Modeling and simulation are crucial in the development of advanced energy efficient control strategies. Utilizing real-world driving data as the underlying basis for control design and simulation lends veracity to projected real-world energy savings. Standardized drive cycles are limited in their utility for evaluating advanced driving strategies that utilize connectivity and on-vehicle sensing, primarily because they are typically intended for evaluating emissions and fuel economy under controlled conditions. Real-world driving data, because of its scale, is a useful representation of various road types, driving styles, and driving environments. The scale of real-world data also presents challenges in effectively using it in simulations. A fast and efficient simulation methodology is necessary to handle the large number of simulations performed for design analysis and impact evaluation of control strategies.

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%).

A critical element to the success of new propulsion technologies that enable reductions in fuel use is the integration of component thermal management technologies within a viable vehicle package. Vehicle operation requires vehicle thermal management systems capable of balancing the needs of multiple vehicle systems that may require heat for operation, require cooling to reject heat, or require operation within specified temperature ranges. As vehicle propulsion transitions away from a single form of vehicle propulsion based solely on conventional internal combustion engines (ICEs) toward a wider array of choices including more electrically dominant systems such as plug-in hybrid electric vehicles (PHEVs), new challenges arise associated with vehicle thermal management. As the number of components that require active thermal management increase, so do the costs in terms of dollars, weight, and size.