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The operation of air conditioning (A/C) systems is a significant contributor to the total amount of fuel used by light-and heavy-duty vehicles. Therefore, continued improvement of the efficiency of these mobile A/C systems is important. Numerical simulation has been used to reduce the system development time and to improve the electronic controls, but numerical models that include highly detailed physics run slower than desired for carrying out vehicle-focused drive cycle-based system optimization. Therefore, faster models are needed even if some accuracy is sacrificed. In this study, a validated model with highly detailed physics, the “Fully-Detailed” model, and two models with different levels of simplification, the “Quasi-Transient” and the “Mapped-Component” models, are compared. The Quasi-Transient model applies some simplifications compared to the Fully-Detailed model to allow faster model execution speeds.

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.

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.

In an effort to better understand the operational requirements of port drayage vehicles and their potential for adoption of advanced technologies, National Renewable Energy Laboratory (NREL) researchers collected over 36,000 miles of in-use duty cycle data from 30 Class 8 drayage trucks operating at the Port of Long Beach and Port of Los Angeles in Southern California. These data include 1-Hz global positioning system location and SAE J1939 high-speed controller area network information. Researchers processed the data through NREL’s Drive-Cycle Rapid Investigation, Visualization, and Evaluation tool to examine vehicle kinematic and dynamic patterns across the spectrum of operations. Using the k-medoids clustering method, a repeatable and quantitative process for multi-mode drive cycle segmentation, the analysis led to the creation of multiple drive cycles representing four distinct modes of operation that can be used independently or in combination.

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.

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.

Several configurations of truck tractor sleeper cabs were tested and modeled to investigate the potential to reduce heating and cooling loads. Two trucks were tested outdoors and a third was used as a control. Data from the testing were used to validate a computational fluid dynamics (CFD) model and this model was used to predict reductions in cooling loads during daytime rest periods. The test configurations included the application of standard-equipped sleeper privacy curtain and window shades, an optional insulated or arctic sleeper curtain, and insulated window coverings. The standard curtain reduced sleeper area heating load by 21% in one test truck, while the arctic curtain decreased it by 26%. Insulated window coverings reduced the heating load by 16% in the other test truck and lowered daytime solar temperature gain by 8°C. The lowered temperature resulted in a predicted 34% reduction in cooling load from the model.

Accurate evaluation of vehicles' transient total power requirement helps achieving further improvements in vehicle fuel efficiency. When operated, the air-conditioning (A/C) system is the largest auxiliary load on a vehicle, therefore accurate evaluation of the load it places on the vehicle's engine and/or energy storage system is especially important. Vehicle simulation models, such as "Autonomie," have been used by OEMs to evaluate vehicles' energy performance. However, the load from the A/C system on the engine or on the energy storage system has not always been modeled in sufficient detail. A transient A/C simulation tool incorporated into vehicle simulation models would also provide a tool for developing more efficient A/C systems through a thorough consideration of the transient A/C system performance. The dynamic system simulation software MATLAB/Simulink® is frequently used by vehicle controls engineers to develop new and more efficient vehicle energy system controls.

The NASA-wide CEV Smart Buyer Team (SBT) was assembled in January 2006 and was tasked with the development of a NASA in-house design for the CEV Crew Module (CM), Service Module (SM), and Launch Abort System (LAS). This effort drew upon over 250 engineers from all of the 10 NASA Centers. In 6 weeks, this in-house design was developed. The Thermal Systems Team was responsible for the definition of the active and passive design architecture. The SBT effort for Thermal Systems can be best characterized as a design architecting activity. Proof-of-concepts were assessed through system-level trade studies and analyses using simplified modeling. This nimble design approach permitted definition of a point design and assessing its design robustness in a timely fashion. This paper will describe the architecting process and present trade studies and proposed thermal designs

An EVA simulation with a medical contingency scenario was conducted in 2006 with the NASA Haughton-Mars and EVA Physiology System and Performance Projects, to develop medical contingency management and evacuation techniques for planetary surface exploration. A rescue/evacuation system to allow two rescuer astronauts to evacuate one incapacitated astronaut was evaluated. The rescue system was utilized effectively to extract an injured astronaut up a slope of15-25° and into a surface mobility rover for transport to a simulated habitat for advanced medical care. Further research is recommended to evaluate the effects of reduced gravity and to develop synergies with other surface systems for carrying out the contingency procedures.

This project investigates methods to capture an astronaut's exhaled carbon dioxide (CO2) before it becomes diluted with the high volumetric oxygen flow present within a space suit. Typical expired breath contains CO2 partial pressures (pCO2) in the range of 20-35 mm Hg (.0226-.046 atm). This research investigates methods to capture the concentrated CO2 gas stream prior to its dilution with the low pCO2 ventilation flow. Specifically this research is looking at potential designs for a collection cup for use inside the space suit helmet. The collection cup concept is not the same as a breathing mask typical of that worn by firefighters and pilots. It is well known that most members of the astronaut corps view a mask as a serious deficiency in any space suit helmet design. Instead, the collection cup is a non-contact device that will be designed using a detailed Computational Fluid Dynamic (CFD) analysis of the ventilation flow environment within the helmet.

The subjective aspects of comfort in three different cooling garments, the MACS-Delphi, Russian Orlan, and LCVG were evaluated. Six subjects (4 males and 2 females) were tested in separate sessions in each garment and in one of two environmental chamber conditions: 24°C and 35°C. Subjects followed a staged exercise/rest protocol with different levels of physical exertion at different stages. Thermal comfort and heat perception were assessed by ratings on visual analog scales. Ratings of physical comfort of the garment and also garment flexibility in positions simulating movements during planetary exploration were also obtained. The findings indicated that both overall thermal comfort and head thermal comfort were rated highest in the MACS-Delphi at 24°C. The Orlan was rated lowest on physical comfort and less flexible in different body positions.

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.

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.

Thermal control systems for space application plant growth chambers offer unique challenges. The ability to control temperature and humidity independently gives greater flexibility for optimizing plant growth. Desired temperature and relative humidity range vary widely from 15°C to 35°C and 65% to 85% respectively. On top of all of these variables, the thermal control system must also be conservative in power and mass. These requirements to develop and test a robust thermal control system for space applications led to the design and development of the Environmental System Test Stand (ESTS) at NASA Johnson Space Center (JSC). The ESTS was designed to be a size constrained, environmental control system test stand with the flexibility to allow for a variety of thermal and lighting technologies. To give greater understanding to the environmental control system, the development of the ESTS included both mathematical models and the physical test stand.

The purification of waste water is a critical element of any long-duration space mission. The Vapor Phase Catalytic Ammonia Removal (VPCAR) system offers the promise of a technology requiring low quantities of expendable material that is suitable for exploration missions. NASA has funded an effort to produce an engineering development unit specifically targeted for integration into the NASA Johnson Space Center's Integrated Human Exploration Mission Simulation Facility (INTEGRITY) formally known in part as the Bioregenerative Planetary Life Support Test Complex (Bio-Plex) and the Advanced Water Recovery System Development Facility. The system includes a Wiped-Film Rotating-Disk (WFRD) evaporator redesigned with micro-gravity operation enhancements, which evaporates wastewater and produces water vapor with only volatile components as contaminants. Volatile contaminants, including organics and ammonia, are oxidized in a catalytic reactor while they are in the vapor phase.

This is Part 3 of a development program to evaluate candidate nonablative aeroshell designs. The primary goal of this C/C aeroshell development task was to demonstrate the feasibility and performance of a lightweight C/C non-ablative aeroshell design that integrates advanced C/C materials and structural configurations. The thermal performance was evaluated by Arc Jet testing at NASA Ames of representative structural models. In this phase of the program, new carbon-carbon materials and structural core designs were evaluated, as well as an alternative aerogel material. The test models were composed of a quasi-isotropic Carbon/Carbon(C/C) front face sheet (F/S), eggcrate or honeycomb core, C/C back F/S, Carbon and resorcinol-formaldehyde aerogel insulation. Part One of this work [1] demonstrated the feasibility through arc-jet testing and Part Two [2] included analytical modeling of the test geometry to validate the design.

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.

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.

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.