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Automotive (24)

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Fuel economy (11) Energy conservation (6) Mathematical models (6) Research and development (6) Autonomous vehicles (5) Design processes (5) Electric vehicles (5) Energy consumption (5) Hybrid electric vehicles (5) Fuel cells (4) Simulation and modeling (4) Simulators (4) Automated Vehicles (3) Education and training (3) Neural networks (3) Optimization (3) Vehicle to vehicle (V2V) (3) Emissions (2) Environmental protection (2) Greenhouse gas emissions (2) Hardware-in-the-loop (2) Lithium-ion batteries (2) Powertrains (2) Sensors and actuators (2) Weather and climate (2) Air pollution (1) Architecture (1) Batteries (1) Buses (1) CAD, CAM and CAE (1) Carbon monoxide (1) Computer simulation (1) Constant-velocity joint (1) Control systems (1) Crashes (1) Downsizing (1) Driver behavior (1) Emissions measurement (1) Energy storage systems (1) Fatal injuries (1) Fleets (1) Fuel consumption (1) Global positioning systems (GPS) (1) Lidar (1) Life cycle analysis (1) Life support systems (1) Light trucks (1) Mobility (1) Natural gas (1) Nitrogen oxides (1) Performance tests (1) Product development (1) Productivity (1) Regulations (1) Road tests (1) Stall (1) Systems engineering (1) Technical review (1) Test procedures (1) Traffic management (1) Vehicle acceleration (1) Vehicle charging (1) Vehicle drivers (1) Vehicle performance (1) Vehicle to grid (V2G) (1) Windows and windshields (1)

Authors

Bradley, Thomas (24) Asher, Zachary (9) Geller, Benjamin (5) Motallebiaraghi, Farhang (5) Salisbury, Shawn (5) Meyer, Rick (4) Rabinowitz, Aaron (4) Bucher, Jake (3) Fanas Rojas, Johan (3) Asher, Zachary D. (2) Baker, David (2) Brown, Nicolas (2) Fong, Alvis (2) Fox, Matthew (2) Gaikwad, Tushar (2) Kadav, Parth (2) Rabinowitz, Aaron I. (2) A. Miller, Damon (1) Alvarado, Caleb (1) Asher, Zachary D (1)

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SAE (24)

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Colorado State University (17) Western Michigan University (8) Colorado State Univ. (5) Colorado State Univ (2) Argonne National Laboratory (1) Idaho National Lab. (1) Lockheed Martin (1) National Renewable Energy Laboratory (1) Tesla Motors (1) University of California Irvine (1) University of Michigan (1) Utah State Univ. (1) Vehicle Safety Research, LLC (1)

Events

WCX SAE World Congress Experience (9) SAE 2014 World Congress & Exhibition (4) SAE 2016 World Congress and Exhibition (2) WCX World Congress Experience (2) SAE 2012 International Powertrains, Fuels & Lubricants Meeting (1) SAE 2012 World Congress & Exhibition (1) SAE 2013 World Congress & Exhibition (1) SAE 2014 International Powertrain, Fuels & Lubricants Meeting (1) SAE WCX Digital Summit (1) Symposium on International Automotive Technology 2017 (1) WCX™ 17: SAE World Congress Experience (1)

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Select Vehicle Velocity Prediction Using Artificial Neural Network and Effect of Real World Signals on Prediction Window

Vehicle Velocity Prediction Using Artificial Neural Network and Effect of Real World Signals on Prediction Window

Technical Paper
2020-01-0729
DOI: https://doi.org/10.4271/2020-01-0729

Published 2020-04-14 by SAE International in United States

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Select Synchronous and Open, Real World, Vehicle, ADAS, and Infrastructure Data Streams for Automotive Machine Learning Algorithms Research

Synchronous and Open, Real World, Vehicle, ADAS, and Infrastructure Data Streams for Automotive Machine Learning Algorithms Research

Technical Paper
2020-01-0736
DOI: https://doi.org/10.4271/2020-01-0736

Published 2020-04-14 by SAE International in United States

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Select Quantifying Uncertainty in Vehicle Simulation Studies

Quantifying Uncertainty in Vehicle Simulation Studies

SAE International Journal of Passenger Cars - Mechanical Systems

Journal Article
2012-01-0506

Published 2012-04-16 by SAE International in United States

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Select Actual Versus Estimated Utility Factor of a Large Set of Privately Owned Chevrolet Volts

Actual Versus Estimated Utility Factor of a Large Set of Privately Owned Chevrolet Volts

SAE International Journal of Alternative Powertrains

Journal Article
2014-01-1803

Published 2014-04-01 by SAE International in United States

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Select Analyzing the Energy Consumption Variation during Chassis Dynamometer Testing of Conventional, Hybrid Electric, and Battery Electric Vehicles

Analyzing the Energy Consumption Variation during Chassis Dynamometer Testing of Conventional, Hybrid Electric, and Battery Electric Vehicles

SAE International Journal of Alternative Powertrains

Journal Article
2014-01-1805

Published 2014-04-01 by SAE International in United States

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Select Performance Evaluation of an Autonomous Vehicle Using Resilience Engineering

Performance Evaluation of an Autonomous Vehicle Using Resilience Engineering

Technical Paper
2022-01-0067
DOI: https://doi.org/10.4271/2022-01-0067

Published 2022-03-29 by SAE International in United States

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Select Quantifying Repeatability of Real-World On-Road Driving Using Dynamic Time Warping

Quantifying Repeatability of Real-World On-Road Driving Using Dynamic Time Warping

Technical Paper
2022-01-0269
DOI: https://doi.org/10.4271/2022-01-0269

Published 2022-03-29 by SAE International in United States

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Select Mobility Energy Productivity Evaluation of Prediction-Based Vehicle Powertrain Control Combined with Optimal Traffic Management

Mobility Energy Productivity Evaluation of Prediction-Based Vehicle Powertrain Control Combined with Optimal Traffic Management

Technical Paper
2022-01-0141
DOI: https://doi.org/10.4271/2022-01-0141

Published 2022-03-29 by SAE International in United States

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Select The Importance of HEV Fuel Economy and Two Research Gaps Preventing Real World Implementation of Optimal Energy Management

The Importance of HEV Fuel Economy and Two Research Gaps Preventing Real World Implementation of Optimal Energy Management

Technical Paper
2017-26-0106
DOI: https://doi.org/10.4271/2017-26-0106

Published 2017-01-10 by SAE International in United States

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Select Investigation of Vehicle Speed Prediction from Neural Network Fit of Real World Driving Data for Improved Engine On/Off Control of the EcoCAR3 Hybrid Camaro

Investigation of Vehicle Speed Prediction from Neural Network Fit of Real World Driving Data for Improved Engine On/Off Control of the EcoCAR3 Hybrid Camaro

Technical Paper
2017-01-1262
DOI: https://doi.org/10.4271/2017-01-1262

Published 2017-03-28 by SAE International in United States

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