Search Results

Understanding in-use fleet operating behavior is of paramount importance when evaluating the potential of advanced/alternative vehicle technologies. Accurately characterizing real world vehicle operation assists in properly allocating advanced technologies, playing a role in determining initial payback period and return on investment. In addition, this information contributes to the design and deployment of future technologies as the result of increased awareness regarding tractive power requirements associated with typical operating behavior. In this presentation, the concept of vehicle duty cycles and their relation to advanced technologies will be presented and explored. Additionally, current research attempts to characterize school bus operation will be examined, and existing computational analysis and evaluation tools associated with these efforts discussed. Presenter Adam Duran, National Renewable Energy Laboratory

Spark-ignition engine fuel standards have been put in place to ensure acceptable hot and cold weather driveability (HWD and CWD). Vehicle manufacturers and fuel suppliers have developed systems that meet our driveability requirements so effectively that drivers overwhelmingly find that their vehicles reliably start up and operate smoothly and consistently throughout the year. For HWD, fuels that are too volatile perform more poorly than those that are less volatile. Vapor lock is the apparent cause of poor HWD, but there is conflicting evidence in the literature as to where in the fuel system it occurs. Most studies have found a correlation between degraded driveability and higher dry vapor pressure equivalent or lower TV/L = 20, and less consistently with a minimum T50. For CWD, fuels with inadequate volatility can cause difficulty in starting and rough operation during engine warmup.

This paper describes the need for dynamic (transient) simulation of automotive air conditioning systems, the reasons why such simulations are challenging, and the applicability of a general purpose off-the-shelf thermohydraulic analyzer to answer such challenges. An overview of modeling methods for the basic components are presented, along with relevant approximations and their effect on speed and accuracy of the results.

Current vehicle climate control systems are dramatically overpowered because they are designed to condition the cabin air mass in a specified period of time. A more effective and energy efficient objective is to directly achieve thermal comfort of the passengers. NREL is developing numerical and experimental tools to predict human thermal comfort in non-uniform transient thermal environments. These tools include a finite element model of human thermal physiology, a psychological model that predicts both local and global thermal comfort, and a high spatial resolution sweating thermal manikin for testing in actual vehicles.

How much fuel does vehicle air conditioning actually use? This study attempts to answer that question to determine the national and state-by-state fuel use impact seen by using air conditioning in light duty gasoline vehicles. The study used data from US cities, representative of averages over the past 30 years, whose temperature, incident radiation, and humidity varied through time of day and day of year. National surveys estimated when people drive their vehicles during the day and throughout the year. A simple thermal comfort model based on Fanger's heat balance equations determined the percentage of time that a driver would use the air conditioning based on the premise that if a person were dissatisfied with the thermal environment, they would turn on the air conditioning. Vehicle simulations for typical US cars and trucks determined the fuel economy reduction seen with AC use.

Natural gas, coal, and biomass can be converted to diesel fuel through Fischer-Tropsch (F-T) processes. Variations of the F-T process and/or product work-up can be used to tailor the fuel properties to meet end-users needs. Regardless of feedstock or process, F-T diesel fuels typically have a number of very desirable properties. This review describes typical F-T diesel fuel properties, discusses how these fuel properties impact pollutant emissions, and draws together data from known engine and chassis dynamometer studies of emissions. The comparison of fuel properties reveals that F-T diesel fuel is typically one of two types - a very high cetane number (>74), zero aromatic product or a moderate cetane (∼60), low aromatic (≤15%) product. The very high cetane fuels typically have less desirable low temperature properties while the moderate cetane fuels have cold flow properties more typical of conventional diesel fuels.

In the United States, intercity long-haul trucks idle approximately 1,800 hrs per year primarily for sleeper cab hotel loads, consuming 838 million gallons of diesel fuel [1]. The U.S. Department of Energy's National Renewable Energy Laboratory (NREL) is working on solutions to this challenge through the CoolCab project. The objective of the CoolCab project is to work closely with industry to design efficient thermal management systems for long-haul trucks that keep the cab comfortable with minimized engine idling. Truck engine idling is primarily done to heat or cool the cab/sleeper, keep the fuel warm in cold weather, and keep the engine warm for cold temperature startup. Reducing the thermal load on the cab/sleeper will decrease air conditioning system requirements, improve efficiency, and help reduce fuel use. To help assess and improve idle reduction solutions, the CoolCalc software tool was developed.

An ADvanced Automotive Manikin (ADAM) developed at the National Renewable Energy Laboratory (NREL) is used to evaluate NASA’s liquid cooling garments (LCGs) used in advanced spacesuits. The manikin has 120 separate heated/sweating zones and is controlled by a finite-element physiological model of the human thermo-regulatory system. Previous testing showed the thermal sensation and comfort followed expected trends as the LCG inlet fluid temperature was changed. The Phase II test data demonstrates the repeatability of ADAM by retesting the baseline LCG. Skin and core temperature predictions using ADAM in an LCG/arctic suit combination are compared to NASA physiological data to validate the manikin/model. An additional Orlan LCG configuration is assessed using the manikin and compared to the baseline LCG.

People who wear protective uniforms that inhibit evaporation of sweat can experience reduced productivity and even health risks when their bodies cannot cool themselves. This paper describes a new sweating manikin and a numerical model of the human thermoregulatory system that evaluates the thermal response of an individual to transient, non-uniform thermal environments. The physiological model of the human thermoregulatory system controls a thermal manikin, resulting in surface temperature distributions representative of the human body. For example, surface temperatures of the extremities are cooler than those of the torso and head. The manikin contains batteries, a water reservoir, and wireless communications and controls that enable it to operate as long as 2 hours without external connections. The manikin has 120 separately controlled heating and sweating zones that result in high resolution for surface temperature, heat flux, and sweating control.

The National Renewable Energy Laboratory (NREL) has developed a suite of thermal comfort tools to help develop smaller and more efficient climate control systems in automobiles. The tools consist of a thermal comfort manikin, physiological model, and psychological model that are linked together to assess comfort in a transient non-homogeneous environment. The manikin, which consists of 120 individually controlled zones, mimics the human body by heating, sweating, and breathing. The physiological model is a 40,000-node numerical simulation of the human body. The model receives heat loss data from the manikin and predicts the human physiological response and skin temperatures. Based on human subject test data, the psychological model takes the temperatures of the human and predicts thermal sensation and comfort.

Automotive ancillary loads have a significant impact on the fuel economy of both conventional and advanced vehicles. Improving the delivery methods for conditioned air is an effective way to increase thermal comfort at little energy cost, resulting in reduced air-conditioning needs and fuel use. Automotive seats are well suited for effective delivery of conditioned air due to their large contact area with and close proximity to the occupants. Normally a seat acts as a thermal insulator, increasing skin temperatures and reducing evaporative cooling of sweat. Ventilating a seat has low energy costs and eliminates this insulating effect while increasing evaporative cooling. The U.S. Department of Energy's National Renewable Energy Laboratory (NREL) has applied a combination of experimental testing and modeling to quantify improved thermal comfort and potential fuel savings by using a ventilated seat.

Accurate vehicle parameters are valuable for design, modeling, and reporting. Estimating vehicle parameters can be a very time-consuming process requiring tightly-controlled experimentation. This work describes a method to estimate vehicle parameters such as mass, coefficient of drag/frontal area, and rolling resistance using data logged during standard vehicle operation. The method uses a Monte Carlo method to generate parameter sets that are fed to a variant of the road load equation. The modeled road load is then compared to the measured load to evaluate the probability of the parameter set. Acceptance of a proposed parameter set is determined using the probability ratio to the current state, so that the chain history will give a distribution of parameter sets. Compared to a single value, a distribution of possible values provides information on the quality of estimates and the range of possible parameter values. The method is demonstrated by estimating dynamometer parameters.

Fleet managers need a tool to assist them in assessing their need to comply with EPAct and to provide them with the ability to obtain information that will allow them to make alternative fuel vehicle purchasing decisions. This paper will describe the Web-based tool that will inform a fleet manager, based on their geographic location, the type of fleet they own or operate, and the number and types of vehicles in their fleet, whether or not they need to meet the requirements of EPAct, and, if so, the percentage of new vehicle purchases needed to comply with the law. The tool provides detailed specifications on available OEM alternative fuel vehicles, including the purchase cost of the vehicles, fuel and fuel system characteristics, and incentives and rebates surrounding the purchase of each vehicle. The full set of federal, state, and local incentives is made available through the tool, as well as detailed access to refueling site and dealership locations.

This paper summarizes current work in the Environmental Science & Health Effects (ES&HE) Program being sponsored by DOE's Office of Heavy Vehicle Technologies (OHVT) through the National Renewable Energy Laboratory (NREL). The program is regulatory-driven, and focuses on ozone, airborne particles, visibility and regional haze, air toxics, and health effects of air pollutants. The goal of the ES&HE Program is to understand atmospheric impacts and potential health effects that may be caused by the use of petroleum-based and alternative transportation fuels. Each project in the program is designed to address policy-relevant objectives. Studies in the ES&HE Program have four areas of focus: improving technology for emissions measurements; vehicle emissions measurements, emission inventory development/improvement; and ambient impacts, including health effects.

Evaporative cooling of the fuel-air charge by fuel evaporation is an important feature of direct-injection spark-ignition engines that improves fuel knock resistance and reduces pumping losses at intermediate load, but in some cases, may increase fine particle emissions. We have reported on experimental approaches for measuring both total heat of vaporization and examination of the evaporative heat effect as a function of fraction evaporated for gasolines and ethanol blends. In this paper, we extend this work to include other low-molecular-weight alcohols and present results on species evolution during fuel evaporation by coupling a mass spectrometer to our differential scanning calorimetry/thermogravimetric analysis instrument. The alcohols examined were methanol, ethanol, 1-propanol, isopropanol, 2-butanol, and isobutanol at 10 volume percent, 20 volume percent, and 30 volume percent.

With support from the U.S. Department of Energy's Vehicle Technologies Office, the National Renewable Energy Laboratory developed BLAST-V-the Battery Lifetime Analysis and Simulation Tool for Vehicles. The addition of high-resolution spatial-temporal travel histories enables BLAST-V to investigate user-defined infrastructure rollouts of publically accessible charging infrastructure, as well as quantify impacts on vehicle and station owners in terms of improved vehicle utility and station throughput. This paper presents simulation outputs from BLAST-V that quantify the utility improvements of multiple distinct rollouts of publically available Level 2 electric vehicle supply equipment (EVSE) in the Seattle, Washington, metropolitan area. Publically available data on existing Level 2 EVSE are also used as an input to BLAST-V. The resulting vehicle utility is compared to a number of mock rollout scenarios.

The emergence of connected and automated vehicles and smart cities technologies create the opportunity for new mobility modes and routing decision tools, among many others. To achieve maximum mobility and minimum energy consumption, it is critical to understand the energy cost of decisions and optimize accordingly. The Route Energy prediction model (RouteE) enables accurate estimation of energy consumption for a variety of vehicle types over trips or sub-trips where detailed drive cycle data are unavailable. Applications include vehicle route selection, energy accounting and optimization in transportation simulation, and corridor energy analyses, among others. The software is a Python package that includes a variety of pre-trained models from the National Renewable Energy Laboratory (NREL). However, RouteE also enables users to train custom models using their own data sets, making it a robust and valuable tool for both fast calculations and rigorous, data-rich research efforts.

As demand for consumer electric vehicles (EVs) has drastically increased in recent years, manufacturers have been working to bring heavy-duty EVs to market to compete with Class 6-8 diesel-powered trucks. Many high-profile companies have committed to begin electrifying their fleet operations, but have yet to implement EVs at scale due to their limited range, long charging times, sparse charging infrastructure, and lack of data from in-use operation. Thus far, EVs have been disproportionately implemented by larger fleets with more resources. To aid fleet operators, it is imperative to develop tools to evaluate the electrification potential of heavy-duty fleets. However, commercially available tools, designed mostly for light-duty vehicles, are inadequate for making electrification recommendations tailored to a fleet of heavy-duty vehicles.

Current vehicle climate control systems are dramatically overpowered because they are designed to condition the cabin air mass in a specified period of time. A more effective and energy efficient objective is to directly achieve thermal comfort of the passengers. NREL is developing numerical and experimental tools to predict human thermal comfort in non-uniform transient thermal environments. These tools include a finite element model of human thermal physiology, a psychological model that predicts both local and global thermal comfort, and a high spatial resolution sweating thermal manikin for testing in actual vehicles.