scholarly journals Contribution of Road Grade to the Energy Use of Modern Automobiles Across Large Datasets of Real-World Drive Cycles

2014 ◽  
Author(s):  
Eric Wood ◽  
Evan Burton ◽  
Adam Duran ◽  
Jeffrey Gonder
Keyword(s):  
Real World ◽  
Energy Use ◽  
Large Datasets ◽  
Road Grade

Measurement and Evaluation of Real-World Speed and Acceleration Activity Envelopes for Light-Duty Vehicles

2015 ◽  
Vol 2503 (1) ◽  
pp. 128-136 ◽  
Author(s):  
Bin Liu ◽  
H. Christopher Frey
Keyword(s):  
Real World ◽  
Test Procedure ◽  
Accurate Estimation ◽  
Vehicle Type ◽  
Light Duty ◽  
Road Grade ◽  
Light Duty Vehicle ◽  
Curb Weight ◽  
Vehicle Activity ◽  
Light Duty Vehicles

Accurate estimation of vehicle activity is critically important for the accurate estimation of emissions. To provide a benchmark for estimation of vehicle speed trajectories such as those from traffic simulation models, this paper demonstrates a method for quantifying light-duty vehicle activity envelopes based on real-world activity data for 100 light-duty vehicles, including conventional passenger cars, passenger trucks, and hybrid electric vehicles. The vehicle activity envelope was quanti-fied in the 95% frequency range of acceleration for each of 15 speed bins with intervals of 5 mph and a speed bin for greater than 75 mph. Potential factors affecting the activity envelope were evaluated; these factors included vehicle type, transmission type, road grade, engine displacement, engine horsepower, curb weight, and ratio of horsepower to curb weight. The activity envelope was wider for speeds ranging from 5 to 20 mph and narrowed as speed increased. The latter was consistent with a constraint on maximum achievable engine power demand. The envelope was weakly sensitive to factors such as type of vehicle, type of transmission, road grade, and engine horsepower. The effect of road grade on cycle average emissions rates was evaluated for selected real-word cycles. The measured activity envelope was compared with those of dynamometer driving cycles, such as the federal test procedure, highway fuel economy test, SC03, and US06 cycles. The effect of intervehicle variability on the activity envelope was minor; this factor implied that the envelope could be quantified based on a smaller vehicle sample than used for this study.

scholarly journals Research into Navigation, Collaborative Interaction, and Gigapixel Displays

2011 ◽  
Vol 2 (2) ◽  
pp. 1
Author(s):  
Roy A Ruddle ◽  
David J Duke
Keyword(s):  
Virtual Reality ◽  
Cancer Diagnosis ◽  
Real World ◽  
Research Group ◽  
Large Datasets ◽  
Graph Exploration ◽  
Communication Breakdown ◽  
Collaborative Interaction ◽  
Visualization Techniques

Research by the Visualization & Virtual Reality Research Group (School of Computing, University of Leeds, UK) includes themes that focus on navigation, collaborative interaction, and gigapixel displays. The group also carries out research into visualization techniques and systems, including new systems technologies for visualization, and tools for investigating features within large datasets. This article summarizes that research and describes current projects that are taking place: Virtual trails to aid real-world navigation, Mobile geophysics, Communication breakdown in collaborative VR, Cancer diagnosis with a VR Microscope, Visual analytic interfaces for optimization, and Overlays for graph exploration.

scholarly journals Querying Log Data with Metric Temporal Logic

2018 ◽  
Vol 62 ◽  
pp. 829-877 ◽  
Author(s):  
Sebastian Brandt ◽  
Elem Güzel Kalaycı ◽  
Vladislav Ryzhikov ◽  
Guohui Xiao ◽  
Michael Zakharyaschev
Keyword(s):  
Temporal Logic ◽  
Real World ◽  
Large Datasets ◽  
Weather Data ◽  
Data Complexity ◽  
Log Data ◽  
Metric Temporal Logic ◽  
Temporal Concepts ◽  
Horn Fragment ◽  
Typical User

We propose a novel framework for ontology-based access to temporal log data using a datalog extension datalogMTL of the Horn fragment of the metric temporal logic MTL. We show that datalogMTL is EXPSPACE-complete even with punctual intervals, in which case full MTL is known to be undecidable. We also prove that nonrecursive datalogMTL is PSPACE-complete for combined complexity and in AC0 for data complexity. We demonstrate by two real-world use cases that nonrecursive datalogMTL programs can express complex temporal concepts from typical user queries and thereby facilitate access to temporal log data. Our experiments with Siemens turbine data and MesoWest weather data show that datalogMTL ontology-mediated queries are efficient and scale on large datasets.

scholarly journals Variability in Measured Real-World Operational Energy Use and Emission Rates of a Plug-In Hybrid Electric Vehicle

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1140 ◽  
Author(s):  
H. Christopher Frey ◽  
Xiaohui Zheng ◽  
Jiangchuan Hu
Keyword(s):  
Real World ◽  
Hybrid Electric Vehicle ◽  
Energy Use ◽  
Average Energy ◽  
Specific Power ◽  
Emission Measurement ◽  
Emission Rates ◽  
Wide Range ◽  
Hybrid Electric ◽  
Cold Starts

Compared to comparably sized conventional light duty gasoline vehicles (CLDGVs), plug-in hybrid electric vehicles (PHEVs) may offer benefits of improved energy economy, reduced emissions, and the flexibility to use electricity as an energy source. PHEVs operate in either charge depleting (CD) or charge sustaining (CS) mode; the engine has the ability to turn on and off; and the engine can have multiple cold starts. A method is demonstrated for quantifying the real-world activity, energy use, and emissions of PHEVs, taking into account these operational characteristics and differences in electricity generation resource mix. A 2013 Toyota Prius plug-in was measured using a portable emission measurement system. Vehicle specific power (VSP) based modal average energy use and emission rates are inferred to assess trends in energy use and emissions with respect to engine load and for comparisons of engine on versus engine off, and cold start versus hot stabilized running. The results show that, compared to CLDGVs, the PHEV operating in CD mode has improved energy efficiency and lower CO2, CO, HC, NOx, and PM2.5 emission rates for a wide range of power generation fuel mixes. However, PHEV energy use and emission rates are highly variable, with periods of relatively high on-road emission rates related to cold starts.

COMBINING DATA ANALYTICS WITH XBRL: THE VIEWDRIVE CASE

2021 ◽  
Author(s):  
Amanuel Fekade Tadesse ◽  
Nishani Vincent
Keyword(s):  
Active Learning ◽  
Real World ◽  
Data Analytics ◽  
Large Datasets ◽  
Securities And Exchange Commission ◽  
Financial Report ◽  
Business Reporting ◽  
Accounting Curriculum ◽  
Combining Data ◽  
Real World Datasets

This advisory case is designed to develop data analytics skills using multiple large real-world datasets based on eXtensible Business Reporting Language (XBRL). This case can also be used to introduce students to XBRL concepts such as extension taxonomies. Students are asked to recommend an XBRL preparation software for a hypothetical company (ViewDrive) that is adopting XBRL to satisfy the financial report filing requirements imposed by the Securities and Exchange Commission (SEC). Students perform data cleansing (extract, transform, load) procedures to prepare large datasets for data analytics. Students are encouraged to think critically, specify assumptions before performing data analytics (using analytic software such as Tableau), and generate visualizations that support their written recommendations. The case is easy to implement, promotes active learning, and has received favorable student and instructor feedback. This case can be used to introduce technology and data analytics topics into the accounting curriculum to help satisfy AACSB’s objectives.

Sign in / Sign up

Export Citation Format

Share Document