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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Model-Based Framework to Optimize Charger Station Deployment for Battery Electric Vehicles

The development of battery electric vehicles (BEVs) is accelerating due to their environmental advantages over gasoline and diesel-powered vehicles, including a decrease in air pollution and an increase in energy efficiency. The deployment of charging infrastructure will need to increase to keep pace with demand, especially for large commercial vehicles for which few public chargers currently exist. In this paper, a new flexible framework is proposed for optimizing the placement of charging stations for BEVs, within which different physical models and optimization techniques may be used. Furthermore, a set of metrics is suggested to help enforce complex constraints and facilitate direct comparison between different optimization techniques. Unlike many existing charger placement techniques, the proposed method directly considers the historical driving patterns on a vehicle-by-vehicle basis, using transparent models to assess impacts of candidate charger placements, thus improving the explainability of the results. In the developed framework, modeled BEVs are first generated along the road network to mimic historical traffic data and are simulated traveling along a given route according to a simplified vehicle model. During the simulation, the charger placement problem is initially relaxed to allow vehicles to charge at any node along the road network, and vehicle states are tracked to assess areas of high charging demand. Charging stations are then placed based on the results of the relaxed simulation, and suggested placements are evaluated via road network simulation with fixed charger locations. This proposed framework is applied to a sample problem of placing charging stations along five major highway corridors for Class 8 over-the-road electric trucks. A novel mixed integer programming (MIP) formulation is proposed to optimize charger placements based upon the expected charging demand. Constraints were imposed on the final placement results to limit expected wait times at each station and ensure a minimum threshold of trucking routes are viable for BEVs. The results demonstrate the flexibility and potential effectiveness of the developed model-based framework for scalable charger station deployment.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Neural Network-Based Electric Vehicle Range Prediction for Smart Charging Optimization

Range prediction is a standard feature in most modern road vehicles, allowing drivers to make informed decisions about when to refuel. Most vehicles make range predictions through data- or model-driven means, monitoring the average fuel consumption rate or using a tuned vehicle model to predict fuel consumption. The uncertainty of future driving conditions makes the range prediction problem challenging, particularly for less pervasive battery electric vehicles (BEV). Most contemporary machine learning-based methods attempt to forecast the battery SOC discharge profile to predict vehicle range. In this work, we propose a novel approach using two recurrent neural networks (RNNs) to predict the remaining range of BEVs and the minimum charge required to safely complete a trip. Each RNN has two outputs that can be used for statistical analysis to account for uncertainties; the first loss function leads to mean and variance estimation (MVE), while the second results in bounded interval estimation (BIE). These outputs of the proposed RNNs are then used to predict the probability of a vehicle completing a given trip without charging, or if charging is needed, the remaining range and minimum charging required to finish the trip with high probability. Training data was generated using a low-order physics model to estimate vehicle energy consumption from historical drive cycle data collected from medium-duty last-mile delivery vehicles. Here, the proposed method demonstrated high accuracy in the presence of day-to-day route variability, with the root-mean-square error (RMSE) below 6% for both RNN models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Spatially Resolved Domicile Charging Demands for Light-, Medium-, and Heavy-Duty Electric Vehicles in Virginia

The use of plug-in electric vehicles (PEVs) and resulting grid impacts are likely to grow rapidly, and evaluation of optimal smart charge management and grid integration strategies is warranted now. Evaluating distribution grid impacts requires fine-grained models of PEV operations to estimate charging loads across diverse vehicles at high spatial resolution. We propose such a model and consider a high-electrification scenario in Richmond and Newport News, Virginia. Our framework considers four categories of vehicle that are amenable to early aggressive electrification: light-duty passenger vehicles (LDV), trucks and vans with a focus on delivery or other local operations, school buses, and transit buses. These vehicles have a relatively consistent domicile, reducing the need for public charging infrastructure rollout to electrify. We apply a recent LDV model and propose new models for each vocation of medium- and heavy-duty vehicle, leveraging telematics data. We demonstrate our framework in Virginia and find energy demands in the region may total 15 GWh day, with most consumed by LDV. However, considering power demand at high spatial resolution reveals a different trend: LDVs have relatively small peak loads at specific sites (peak site demand around 800 kW) compared to average and high demand medium- and heavy-duty vehicle charging sites (peak site demand around 6,000 kW at a transit bus depot, 1,500 kW at a local freight hub, and 1,000 kW at a school). Our framework yields insights on the relative impacts of each vocation and enables future work to tailor grid integration strategies to each vehicle category.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1962

NASA Scout ST-1 Flight-Test Results and Analyses, Launch Operations, and Test Vehicle Description

The first of a series of flight tests for the development of the four-stage, solid-propellant Scout vehicle was conducted at the NASA Wallops Station under the direction of the Langley Research Center. Vehicle designation for the test was NASA Scout ST-1. Performance characteristics of the vehicle and components were recorded during a high-altitude probe mission. Flight-simulation studies are presented and show that the accuracy of the guidance system during the flight was within control-system design specifications. The control system functioned normally during the flight with the exception of an overpowering of the reaction-control roll jets near burnout of the third-stage rocket motor. The resulting roll displacement of the vehicle is shown to have caused the monitor tracking radar which had been erroneously tracking a radar beacon in the vehicle on a side lobe to reorient to the major lobe of the receiving antenna. This tracking switch falsely indicated a violent turning maneuver on the monitor plot board and resulted in a hold-fire decision for the fourth-stage rocket motor. Although data for the final thrusting and coast phase of the flight were not obtained, the majority of the test objectives were achieved. In-flight thrust misalignment angles for the second- and third-stage rocket motors derived from control-system error data and for the first-stage motor determined from flight-simulation studies are presented. All rocket-motor thrust misalignment angles were well within the tolerances used for control-system design. Rocket-motor flight performance is presented, and velocity increments attained from the first three stages substantiated the predicted nominal performance. Operation of the rocket motors was satisfactory with the exception of high-level vibrations which were encountered during third-stage motor burning. Rolling moments which overpowered the reaction-control jets are also attributed to the burning characteristics of the third-stage motor. A discussion of the premature loss of the third-stage heat shield is given and shows that the heat-shield latching mechanism failed from pressure loads as the vehicle entered the transonic speed range. Although venting was provided to relieve the high negative pressures known to exist on the heat shield at these speeds, a field modification of the wiring tunnel had the same effect as opening the inside of the heat shield to ambient pressures. Consequently, the latching mechanism failed from pressure loads which were of about the same magnitude as the latching-mechanism yield loads. Skin temperatures were recorded at several locations on the vehicle and were generally in good agreement with theoretical values. Aerodynamic heating presented no problem during the flight since the maximum temperatures recorded during the flight were only about half the design values because of the high-launch-angle trajectory. Environmental vibrations recorded in the vicinity of the guidance package showed that no significant continuous amplitude levels above the general instrumentation noise level were present during first- and second-stage burning. Large vibration amplitudes were recorded during third-stage burning which coincided with the large roll disturbance experienced by the vehicle near burnout of the third-stage motor.

Scout Launch Vehicle↗
DOE OSTI2021

Future Cost Benefits Analysis for Electrified Vehicles from Advances Due to U.S. Department of Energy Targets

The U.S. Department of Energy’s Vehicle Technologies Office (DOE-VTO) supports research and development (R&D), as well as deployment of efficient and sustainable transportation technologies, that will improve energy efficiency and fuel economy and enable America to use less petroleum. To accelerate the creation and adoption of new technologies, DOE-VTO has developed specific targets for a wide range of powertrain technologies (e.g., engine, battery, electric machine, lightweighting, etc.). This paper quantifies the impact of VTO R&D on vehicle energy consumption and cost compared to expected historical improvements across vehicle classes, powertrains, component technologies and timeframes. We have implemented a large scale simulation process to develop and simulate tens of thousands of vehicles on U.S. standard driving cycles using Autonomie, a vehicle simulation tool developed by Argonne National Laboratory. Results demonstrate significant additional reductions in both cost and energy consumption due to the existence of VTO R&D targets compared to predicted historical trends. It is observed that, over time, the fuel consumption of different electrified vehicles is expected to decrease by 40–50% and a reduction of 45–55% for vehicle manufacturing costs owing to significant improvements through various VTO R&D targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Spatial and unobserved heterogeneity in consumer preferences for adoption of electric and hybrid vehicles: A Bayesian hierarchical modeling approach

The transition to low carbon vehicles known as alternative fuel vehicles (AFVs) is well underway. This transition has been motivated partly by consumer demand and partly by legislation such as the Zero Emission Vehicle mandate, which requires manufacturers to sell a certain percentage of their vehicles as AFVs. While the long-term adoption of AFVs (specifically, electric and hybrids) may take several years, there is a need to understand consumer preferences for AFV adoption and the pathways of AFV adoption from a national perspective. Therefore, this study sought to provide information about consumer preferences regarding AFV ownership while considering spatial and unobserved heterogeneity in consumer preferences, which can potentially impact societal transition to low carbon fueled vehicles. The 2017 National Household Travel Survey was used to calibrate Bayesian logit and hierarchical models. Here, the findings of these models reveal that higher gasoline prices contribute toward the adoption of battery electric vehicles. The results also reveal that the perceived disadvantages of AFVs for long commutes are the key barrier in wider adoption of AFVs. Interestingly, frequent use of the internet by consumers revealed a higher likelihood for purchase of hybrid vehicles. Furthermore, West Coast residents are observed to be a large portion of the early adopters and are more likely to purchase hybrids as compared to battery electric vehicles. The knowledge generated by this study has implications for making better informed decisions about AFV adoption and developing incentives to promote wider adoption of AFVs by overcoming their perceived disadvantages.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Regional Emissions Analysis of Light-Duty Battery Electric Vehicles

Light-duty battery electric vehicles (BEVs) can reduce both greenhouse gas (GHG) and criteria air pollutant (CAPs) emissions, when compared to gasoline vehicles. However, research has found that while today’s BEVs typically reduce GHGs, they can increase certain CAPs, though with significant regional variability based on the electric grid mix. In addition, the environmental performance of electric and gasoline vehicles is not static, as key factors driving emissions have undergone significant changes recently and are expected to continue to evolve. In this study, we perform a cradle-to-grave life cycle analysis using state-level generation mix and vehicle operation emission data. We generated state-level emission factors using a projection from 2020 to 2050 for three light-duty vehicle types. We found that BEVs currently provide GHG benefits in nearly every state, with the median state’s benefit being between approximately 50% to 60% lower than gasoline counterparts. However, gasoline vehicles currently have lower total NOx, urban NOx, total PM 2.5 , and urban PM 2.5 in 33%; 15%; 70%; and 10% of states, respectively. BEV emissions will decrease in 2050 due to a cleaner grid, but the relative benefits when compared to gasoline vehicles do not change significantly, as gasoline vehicles are also improving over this time.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2012

Aero-Assisted Pre-Stage for Ballistic and Aero-Assisted Launch Vehicles

A concept of an aero-assisted pre-stage is proposed, which enables launch of both ballistic and aero-assisted launch vehicles from conventional runways. The pre-stage can be implemented as a delta-wing with a suitable undercarriage, which is mated with the launch vehicle, so that their flight directions are coaligned. The ample wing area of the pre-stage combined with the thrust of the launch vehicle ensure prompt roll-out and take-off of the stack at airspeeds typical for a conventional jet airliner. The launch vehicle is separated from the pre-stage as soon as safe altitude is achieved, and the desired ascent trajectory is reached. Nominally, the pre-stage is non-powered. As an option, to save the propellant of the launch vehicle, the pre-stage may have its own short-burn propulsion system, whereas the propulsion system of the launch vehicle is activated at the separation point. A general non-dimensional analysis of performance of the pre-stage from roll-out to separation is carried out and applications to existing ballistic launch vehicle and hypothetical aero-assisted vehicles (spaceplanes) are considered.

access to space↗
NASA NTRSDate not supplied

Urban Aerial Mobility Networks using Amphibious Vertical Takeoff and Landing Vehicles

This study considers novel urban aerial mobility (UAM) networks that address some of the key operator and community acceptance challenges inherent in proposed UAM operations. This paper seeks to examine three possible approaches to improve operator and community acceptance – specifically targeting cost, safety, and noise. First, the conceptual design space will be examined for VTOL amphibious vehicle technologies, including the implications of onwater versus in-flight time/speed. Second, the implications of minimizing community overflights by flying over-water will be examined. Third, the implications of the partial use of onwater, or near-shore/littoral, vertiports on UAM network performance will be examined. This study considers an alternate design trade space for urban aerial mobility systems. A large number of cities in the United States are located near or surround large bodies of water. Many of these same cities are considered to be candidates for metropolitan aerial transportation systems so as to moderate the impact of urban ground-transportation congestion. This paper will expand discussion and study of notional amphibious VTOL vehicles. There is nothing particularly new with regards to helicopters with amphibious takeoff and landing capability. For example, light rotorcraft have been outfitted with pontoons since the 1950s. Larger utility helicopters – used for carrying offshore oil-rig crew – have been designed, with varying degrees of success, to emergency land in rough waters in case of onboard mechanical system failures. The unique difference for the proposed amphibious UAM vehicles, as compared to these earlier amphibious rotorcraft, is that water operation is the norm rather than the exception and that, further, the water-born operation (and design) of such vehicles can be optimized to yield significant economic and operational benefits over solely UAM land-based stations and operations. Various different amphibious UAM networks will be discussed. A first-order set of analyses – employing novel mission metrics – is presented in this paper that will examine the operational performance of these amphibious networks. In particular, amphibious operations might address critical safety and community acceptance issues. An examination of the aerodynamic and hydrodynamic characteristics of amphibious VTOL UAM vehicles will be presented in this paper. One possible conceptual design for an amphibious UAM vehicle is a hybrid synchropter/hydroplane vehicle. As interest in urban aerial mobility grows, it is worthwhile to consider whether or not amphibious vertical takeoff and landing vehicles can play an important role in providing such mobility.

Urban Aerial Mobility↗
NASA NTRSDate not supplied

Evaluating the Performance of Hybrid Vehicles between LEO, Cislunar Space, and Mars

Nuclear power and electric propulsion technologies can enable a broad range of existing and future space mission concepts. This paper evaluates how these two technology classes, when combined into systems with various performance levels (and paired with a chemical propulsion system) affect vehicle sizing and mission feasibility for round-trip, opposition-class, crewed missions to Mars. The technology trade-space evaluated in this paper encompasses: various nuclear power system mass-efficiency levels (or power-specific mass), a range of output power levels available to the electric propulsion system, two electric propulsion thruster technologies (Hall and Magnetoplasmadynamic) at various characteristic specific impulse levels, and a range of propellant tank mass sizing coefficient. Each combination of the technologies is evaluated for the 2039 and the 2042 Mars mission opportunities for a range of imposed total mission duration constraints. The results show that synergies between technology performance levels exist and that increasing the performance of some parameters might have undesired consequences for the trajectory and vehicle. It was found that increasing the mass-efficiency of the nuclear power system is broadly beneficial, resulting in lower vehicle masses and enabling shorter mission durations. However, increasing the specific impulse of a thruster or increasing the available power level do not always yield a net benefit to the vehicle or mission; since increasing the specific impulse or power level (holding power system mass-efficiency constant) tends to decrease the vehicle thrust-to-mass ratio. Furthermore, the results show that mission feasibility is highly dependent on the mission duration; the required technology performance level to enable a mission is relaxed as the mission duration increases. Given the optimally sized vehicles resulting from the trade-space for a crewed mission to Mars, this paper also evaluates the impact of aggregating the Mars mission vehicle in Low-Earth Orbit and transferring it to the Mars mission departure node (using the on-board power and propulsion systems). The trade-space for this portion of the analysis includes the option of in-space vehicle refueling at the Mars mission departure node. The results show that on-orbit refueling can relax the required technology performance levels to achieve lower launch masses and orbit-raising durations at the cost of increased architecture complexity and risk.

Nuclear Electric Propulsion↗
DOE OSTI2022

How to support EV adoption: Tradeoffs between charging infrastructure investments and vehicle subsidies in California

Supporting the adoption of zero-emission vehicle (ZEVs), including plug-in electric vehicles (EVs), has become a priority for governments due to their ability to reduce petroleum demand, improve air quality, and reduce carbon dioxide (CO2) emissions. Optimal strategies to accelerate EV adoption must weigh the relative value of alternative policy mechanisms to consumers, including public charging infrastructure and vehicle purchase subsidies. We use a historically validated light-duty vehicle consumer choice tool, the ADOPT model, to simulate personal light-duty vehicle adoption and related emissions in California. ADOPT is updated to incorporate a quantification of the tangible value of public charging infrastructure, allowing us to simulate the impact of investments in public charging infrastructure and vehicle purchase subsidies under different scenarios. We show that both policies result in increased EV adoption, with the most effective policy varying depending on vehicle technology assumptions. Under conservative technology improvement assumptions, infrastructure investments are most effective in promoting EV sales and reducing CO2 emissions, while under optimistic technology improvement assumptions a combination of infrastructure and subsidies best supports EV sales and CO2 emission reductions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Light-Duty Vehicle Choice Modeling and Benefits Analysis (van018)

The U.S. Department of Energy’s Vehicle Technologies and Hydrogen and Fuel Cell Technologies Offices (VTO and HFTO) support research and development of efficient and sustainable transportation technologies that will improve energy efficiency, minimize emissions, and enable America to use less petroleum. The analysis in this poster is based on technical progress goals established in VTO and HFTO in the years immediately prior to and including 2020, and it summarizes the estimated energy and emissions benefits corresponding with achievement of those goals. The goals span research activities on batteries, electric drive technologies (EDT), combustion, lightweight materials, fuel cells, and hydrogen storage. The Automotive Deployment Options Projection Tool (ADOPT) is used to estimate the benefits for light-duty vehicles. ADOPT is a vehicle choice and stock model that estimates vehicle technology improvement impacts on sales, energy, and emissions. It includes all the existing vehicle options for realism, estimates their sales using extensively validated consumer preferences, creates new market-driven vehicle options through time, and rolls up sales to estimate energy and emissions. ADOPT takes in technology progress assumptions and applies these to the modeled vehicles through time. The assumptions are represented by a No Program scenario that reflects the technology improvements assumed to occur without further contributions from VTO or HFTO, and a Program Success scenario under which VTO and HFTO program goals are realized. The benefits are calculated by comparing ADOPT's estimated national-level energy and emissions resulting from the Program Success relative to the No Program scenario. By 2050, the Program Success scenario results in 11% less annual petroleum consumption and 10% less annual carbon emissions than the No Program scenario.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Empirical Evidence for the Potential Climate Benefits of Decarbonizing Light Vehicle Transport in the U.S. with Bioenergy from Purpose-Grown Biomass with and without BECCS

Climate mitigation scenarios limiting global temperature increases to 1.5 °C rely on decarbonizing vehicle transport with bioenergy production plus carbon capture and storage (BECCS), but climate impacts for producing different bioenergy feedstocks have not been directly compared experimentally or for ethanol vs electric light-duty vehicles. A field experiment at two Midwest U.S. sites on contrasting soils revealed that feedstock yields of seven potential bioenergy cropping systems varied substantially within sites but little between. Bioenergy produced per hectare reflected yields: miscanthus > poplar > switchgrass > native grasses ≈ maize stover (residue) > restored prairie ≈ early successional. Greenhouse gas emission intensities for ethanol vehicles ranged from 20 to -179 g CO 2 e MJ –1 : maize stover $\gg$ miscanthus ≈ switchgrass ≈ native grasses ≈ poplar > early successional ≥ restored prairie; direct climate benefits ranged from ~80% (stover) to 290% (restored prairie) reductions in CO 2 e compared to petroleum and were similar for electric vehicles. With carbon capture and storage (CCS), reductions in emission intensities ranged from 204% (stover) to 416% (restored prairie) for ethanol vehicles and from 329 to 558% for electric vehicles, declining 27 and 15%, respectively, once soil carbon equilibrates within several decades of establishment. Extrapolation based on expected U.S. transportation energy use suggests that, once CCS potential is maximized with CO 2 pipeline infrastructure, negative emissions from bioenergy with CCS for light-duty electric vehicles could capture >900 Tg CO 2 e year –1 in the U.S. In the future, as other renewable electricity sources become more important, electricity production from biomass would offset less fossil fuel electricity, and the advantage of electric over ethanol vehicles would decrease proportionately.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Powertrain distribution based on total cost of ownership for privately owned vehicles and TNC in the Chicago metropolitan area

From a Total Cost of Ownership (TCO) standpoint, the lowest-cost powertrain option depends on driving conditions and number of miles driven over the lifetime of the vehicle. Studies looking at the value proposition of powertrain options traditionally assess the energy consumption based on standardized drive cycles. TCO is then calculated using average yearly Vehicle Miles Travelled (VMT). This approach which looks at TCO at the aggregate level, does not take into consideration the variations in driving patterns and the spread of VMT that exist in the vehicle population. In this study, we first determine the driving pattern of each vehicle in the Chicago metropolitan area. We then consider different powertrain options for each vehicle, calculate its associated TCO and provide a powertrain distribution based on lowest TCO. Vehicles under consideration are Privately Owned Vehicles (POV) and vehicles used by Transportation Network Companies (TNC).

Freyermuth, Vincent↗
DOE OSTI2025

Incorporating Elevation in Traffic-Vehicle CO-Simulation: Issues, Impacts, and Solutions

Traffic-vehicle co-simulation couples microscopic traffic simulation with full-body vehicle dynamics to assess system-level impacts on mobility, energy, and safety with greater realism. Incorporating elevation is critical for accurately modeling vehicle behavior and energy use, especially for gradient-sensitive vehicles such as electric and heavy-duty trucks. However, raw elevation data often contain noise, discontinuities, and inconsistencies. While such issues may be negligible in traditional traffic simulations, they significantly affect traffic-vehicle co-simulations where vehicle dynamics are sensitive to road grade variations. This paper investigates the impact of unprocessed elevation data on vehicle behavior and energy consumption using a 42-mile simulation along Interstate 81. We propose an elevation processing workflow that can mitigate the effects stem from elevation data issues, improving the realism and stability of traffic-vehicle co-simulation. Results show that the method effectively removes noise and abrupt elevation transitions while preserving roadway geometry.

Xu, Guanhao [ORNL] (ORCID:0000000214326357)↗
DOE OSTI2022

Vehicle Residual Value Analysis by Powertrain Type and Impacts on Total Cost of Ownership

Vehicle depreciation is a key factor in determining the total cost of vehicle ownership and consumer purchase behavior. This report examines how light-duty-vehicle residual values have evolved over time for conventional and advanced vehicle technologies, accounting for important factors such as market segment, size class, and country of assembly. Advancements in electric vehicle technology have led to plug-in vehicles exhibiting depreciation curves similar to those of conventional vehicles. This report compares two methods for determining depreciation trends (snapshot method and time-series method) in order to identify potential impacts on calculating vehicle total cost of ownership given differing data availability.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Estimating vehicle fuel economy from overhead camera imagery and application for traffic control

In this work, we explore the ability to estimate vehicle fuel consumption using imagery from overhead fisheye lens cameras deployed as traffic sensors. We utilize this information to simulate vision-based control of a traffic intersection, with a goal of improving fuel economy with minimal impact to mobility. We introduce the ORNL Overhead Vehicle Dataset (OOVD), consisting of a data set of paired, labeled vehicle images from a ground-based camera and an overhead fisheye lens traffic camera. The data set includes segmentation masks based on Gaussian mixture models for vehicle detection. We show the dataset utility through three applications: the estimate of fuel consumption based on segmentation bounding boxes, vehicle discrimination for those vehicles with largest bounding boxes, and a fine-grained classification on a limited number of vehicle makes and models using a pre-trained set of convolutional neural network models. We compare these results with estimates based on a large open-source data set based on web-scraped imagery. Finally, we show the utility of the approach using reinforcement learning in a traffic simulator using the open source Simulation of Urban Mobility (SUMO) package. Our results show the feasibility of the approach for controlling traffic lights for better fuel efficiency based solely on visual vehicle estimates from commercial, fisheye lens cameras.

Karnowski, Thomas↗
DOE OSTI2020

An Unobstructive Sensing Method for Indoor Air Quality Optimization and Metabolic Assessment within Vehicles

This work investigates the use of an intelligent and unobstructive sensing technique for maintaining vehicle cabin’s indoor air quality while simultaneously assessing the driver metabolic rate. CO 2 accumulation patterns are of great interest because CO 2 can have negative cognitive effects at higher concentrations and also since CO 2 accumulation rate can potentially be used to determine a person’s metabolic rate. The management of the vehicle’s ventilation system was controlled by periodically alternating the air recirculation mode within the cabin, which was actuated based on the CO 2 levels inside the vehicle’s cabin. The CO 2 accumulation periods were used to assess the driver’s metabolic rate, using a model that considered the vehicle’s air exchange rate. In the process of the method optimization, it was found that the vehicle’s air exchange rate (λ [h –1 ]) depends on the vehicle speeds, following the relationship: λ = 0.060 × (speed) – 0.88 when driving faster than 17 MPH. An accuracy level of 95% was found between the new method to assess the driver’s metabolic rate (1620 ± 140 kcal/day) and the reference method of indirect calorimetry (1550 ± 150 kcal/day) for a total of N = 16 metabolic assessments at various vehicle speeds. The new sensing method represents a novel approach for unobstructive assessment of driver metabolic rate while maintaining indoor air quality within the vehicle cabin.

passive sensing↗