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Fast charging is attractive to battery electric vehicle (BEV) drivers for its ability to enable long-distance travel and to quickly recharge depleted batteries on short notice. However, such aggressive charging and the sustained vehicle operation that results could lead to excessive battery temperatures and degradation. Properly assessing the consequences of fast charging requires accounting for disparate cycling, heating, and aging of individual cells in large BEV packs when subjected to realistic travel patterns, usage of fast chargers, and climates over long durations (i.e., years). The U.S. Department of Energy's Vehicle Technologies Office has supported the National Renewable Energy Laboratory's development of BLAST-V-the Battery Lifetime Analysis and Simulation Tool for Vehicles-to create a tool capable of accounting for all of these factors. We present on the findings of applying this tool to realistic fast charge scenarios.

The combined anticipated trends of vehicle sharing (ride-hailing), automated control, and powertrain electrification are poised to disrupt the current paradigm of predominately owner-driven gasoline vehicles with low levels of utilization. Shared, automated, electric vehicle (SAEV) fleets offer the potential for lower cost and emissions and have garnered significant interest among the research community. While promising, unmanaged operation of these fleets may lead to unintended negative consequences. One potentially unintended consequence is a high quantity of SAEVs charging during peak demand hours on the electric grid, potentially increasing the required generation capacity. This research explores the flexibility associated with charging loads demanded by SAEV fleets in response to servicing personal mobility travel demands. Travel demand is synthesized in four major United States metropolitan areas: Detroit, MI; Austin, TX; Washington, DC; and Miami, FL.

The key hurdles to achieving wide consumer acceptance of battery electric vehicles (BEVs) are weather-dependent drive range, higher cost, and limited battery life. These translate into a strong need to reduce a significant energy drain and resulting drive range loss due to auxiliary electrical loads the predominant of which is the cabin thermal management load. Studies have shown that thermal sub-system loads can reduce the drive range by as much as 45% under ambient temperatures below −10 °C. Often, cabin heating relies purely on positive temperature coefficient (PTC) resistive heating, contributing to a significant range loss. Reducing this range loss may improve consumer acceptance of BEVs. The authors present a unified thermal management system (UTEMPRA) that satisfies diverse thermal and design needs of the auxiliary loads in BEVs.

Increased market penetration of electric drive vehicles (EDVs) requires overcoming a number of hurdles, including limited vehicle range and the elevated cost in comparison to conventional vehicles. Climate control loads have a significant impact on range, cutting it by over 50% in both cooling and heating conditions. To minimize the impact of climate control on EDV range, the National Renewable Energy Laboratory has partnered with Hyundai America and key industry partners to quantify the performance of thermal load reduction technologies on a Hyundai Sonata plug-in hybrid electric vehicle. Technologies that impact vehicle cabin heating in cold weather conditions and cabin cooling in warm weather conditions were evaluated. Tests included thermal transient and steady-state periods for all technologies, including the development of a new test methodology to evaluate the performance of occupant thermal conditioning.

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 air-conditioning system can significantly impact the fuel economy and tailpipe emissions of automobiles. If the peak soak temperature of the passenger compartment can be reduced, the air-conditioner compressor can potentially be downsized while maintaining human thermal comfort. Solar reflective film is one way to reduce the peak soak temperature by reducing the solar heat gain into the passenger compartment. A 3M non-metallic solar reflective film (SRF) was tested in two minivans and two sport utility vehicles (SUV). The peak soak temperature was reduced resulting in a quicker cooldown. Using these data, a reduction in air-conditioner size was estimated and the fuel economy and tailpipe emissions were predicted.

The National Renewable Energy Laboratory (NREL) has conducted a series of chassis dynamometer and road tests on the 2000 model-year Honda Insight. This paper will focus on results from the testing, how the results have been applied to NREL's Advanced Vehicle Simulator (ADVISOR), and how test results compare to the model predictions and published data. The chassis dynamometer testing included the FTP-75 emissions certification test procedure, highway fuel economy test, US06 aggressive driving cycle conducted at 0°C, 20°C, and 40°C, and the SC03 test performed at 35°C with the air conditioning on and with the air conditioning off. Data collection included bag and continuously sampled emissions (for the chassis tests), engine and vehicle operating parameters, battery cell temperatures and voltages, motor and auxiliary currents, and cabin temperatures.

An experimental investigation was conducted to evaluate tensile and fatigue behaviors of two thermoplastics, a neat impact polypropylene and a mineral and elastomer reinforced polyolefin. Tensile tests were performed at various strain rates at room, −40°C, and 85°C temperatures with specimens cut parallel and perpendicular to the mold flow direction. Tensile properties were determined from these tests and mathematical relations were developed to represent tensile properties as a function of strain rate and temperature. For fatigue behavior, the effects considered include mold flow direction, mean stress, and temperature. Tension-compression as well as tension-tension load-controlled fatigue tests were performed at room temperature, −40°C and 85°C. The effect of mean stress was modeled using the Walker mean stress model and a simple model with a mean stress sensitivity factor.

A hot and cold water mixing process with a steam condenser and a chilled water heat exchanger is set up for an engine EGR fouling test. The test rig has water recycled in the loop of a pump, heat exchangers, a three-way mixing valve, and a test EGR unit. The target unit temperature is controlled by a heating, cooling and mixing process with individual valves regulating the flow-rate of saturated steam, chilled water and mixing ratio. The challenges in control design are the dead-time, interaction, nonlinearity and multivariable characteristics of heat exchangers, plus the flow recycle in the system. A systems method is applied to extract a simple linear model for control design. The method avoids the nonlinearity and interaction among different temperatures at inlet, outlet and flow-rate. The test data proves the effectiveness of systems analysis and modeling methodology. As a result, the first-order linear model facilitates the controller design.

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.

This paper presents a technological comparison of weldability and mechanical properties between a dual phase steel (DP) and an advanced high strength low alloy steel (AHSLA) used for automotive structural parts in order to demonstrate some unclear characteristics of each. Samples were spot welded and had their hardness and microstructure analyzed, also a shear test was applied on the weld button area. The edge stretchability was analyzed using hole expansion tests and tensile tests to determine the tensile and yield strength, anisotropic coefficients and total elongation. Data were used to estimate crash energy absorption. The results showed an AHSLA steel with higher than typical ductility. Finally, while DP showed improved stretchability, it was also concluded that such AHSLA could perform better bendability, drawability, flangeability and weldability.

A methodology that enables two-dimensional strain field measurement in the vicinity of ductile rupture is described. Fully martensitic steel coupons were strained to fracture using a miniature tensile stage with custom data and image acquisition systems. Rupture initiated near the center of each coupon and progressed slowly toward the gage section edges. A state-of-the-art digital image correlation technique was used to compute the true strain field before rupture initiation and ahead of the resulting propagating macroscopic crack before final fracture occurred. True strains of the order of 95% were measured ahead of the crack at later stages of deformation.

Vehicle occupants, unlike building occupants, are exposed to continuously varying, non-uniform solar heat load. Automotive manufacturers use photovoltaic cells based solar sensor to measure intensity and direction of the direct-beam solar radiation. Use of the time of the day and the position - latitude and longitude - of a vehicle is also common to calculate direction of the direct-beam solar radiation. Two angles - azimuth and elevation - are used to completely define the direction of solar radiation with respect to the vehicle coordinate system. Although the use of solar sensor is common in today’s vehicles, the solar heat load on the occupants, because of their exposure to the direct-beam solar radiation remains the area of in-car subjective evaluation and tuning. Since the solar rays travel in parallel paths, application of the ray tracing method to determine solar insolation of the vehicle occupants is possible.

Annual fuel use for long-haul truck rest period idling is estimated at 667 million gallons in the United States. The U.S. Department of Energy's 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 climate control systems while maintaining occupant comfort. Enhancing the thermal performance of cab/sleepers will enable smaller, lighter, and more cost-effective idle reduction solutions. In order for candidate idle reduction technologies to be implemented at the original equipment manufacturer and fleet level, their effectiveness must be quantified. To address this need, a number of promising candidate technologies were evaluated through experimentation and modeling to determine their effectiveness in reducing rest period HVAC loads.

Finite element dummy models have been more and more widely applied in virtual development of occupant protection systems across the automotive industry due to their predictive capabilities. H350 dyna dummy model [1] is a finite element representation of the Hybrid III male dummy [2], which is designed to represent the average of the United States adult male population. Lower extremity injuries continue to occur in front crash accidents despite increasing improvement of vehicle crashworthiness and occupant restraint system. It is therefore desirable to predict lower tibia injury numbers in front occupant simulations. Though lower tibia loading/index predictions are not studied as much as the FMVSS 208 regulated injury numbers, the tibia indices are injury criteria that need to be assessed during IIHS and Euro NCAP frontal offset occupant simulations. However during front crash simulations, it is very difficult to achieve good correlations or predictions of lower tibia loadings.

It is widely understood that cold ambient temperatures increase vehicle fuel consumption due to heat transfer losses, increased friction (increased viscosity lubricants), and enrichment strategies (accelerated catalyst heating). However, relatively little effort has been dedicated to thoroughly quantifying these impacts across a large set of real world drive cycle data and ambient conditions. This work leverages experimental dynamometer vehicle data collected under various drive cycles and ambient conditions to develop a simplified modeling framework for quantifying thermal effects on vehicle energy consumption. These models are applied over a wide array of real-world usage profiles and typical meteorological data to develop estimates of in-use fuel economy. The paper concludes with a discussion of how this integrated testing/modeling approach may be applied to quantify real-world, off-cycle fuel economy benefits of various technologies.

Mixing controlled compression ignition, i.e., diesel engines are efficient and are likely to continue to be the primary means for movement of goods for many years. Low-net-carbon biofuels have the potential to significantly reduce the carbon footprint of diesel combustion and could have advantageous properties for combustion, such as high cetane number and reduced engine-out particle and NOx emissions. We developed a list of over 400 potential biomass-derived diesel blendstocks and populated a database with the properties and characteristics of these materials. Fuel properties were determined by measurement, model prediction, or literature review. Screening criteria were developed to determine if a blendstock met the basic requirements for handling in the diesel distribution system and use as a blend with conventional diesel. Criteria included cetane number ≥40, flashpoint ≥52°C, and boiling point or T90 ≤338°C.

A new apparatus for testing modern safety belt systems was developed. The apparatus design, dynamic behavior and test procedure are described. A number of tests have been conducted using this apparatus. These tests allowed identification of key performance parameters of pretensioners and load limiting retractors which are relevant to occupant protection in a crash environment. Good test repeatability was observed, which allowed comparison of different safety belt designs. The apparatus may be used for better specification and verification of safety belt properties on a subsystem level as well as for the validation of CAE models of safety belts used in simulations of occupant response to crash events.

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.

Both hydrogen and plug-in electric vehicles offer significant social and environmental benefits to enhance energy security and reduce criteria and greenhouse gas emissions from the transportation sector. However, the rollout of electric vehicle supply equipment (EVSE) and hydrogen retail stations (HRS) requires substantial investments with high risks due to many uncertainties. We compare retail infrastructure costs on a common basis - cost per mile, assuming fueling service to 10% of all light-duty vehicles in a typical 1.5 million person city in 2025. Our analysis considers three HRS sizes, four distinct types of EVSE and two distinct EVSE scenarios. EVSE station costs, including equipment and installation, are assumed to be 15% less than today's costs. We find that levelized retail capital costs per mile are essentially indistinguishable given the uncertainty and variability around input assumptions.