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Development of a novel engine power model to estimate heavy-duty truck fuel consumption

Journal Article · · Transportmetrica. A, Transport Science
 [1];  [2];  [2];  [3]
  1. Intelligent Transportation system department, SenseTime, Shanghai, People’s Republic of China; PATH, University of California, Berkeley, CA, USA
  2. PATH, University of California, Berkeley, CA, USA
  3. University of California, Berkeley, CA, USA
+ Show Author Affiliations

Not provided.

Research Organization:
University of California, San Diego, CA (United States)
Sponsoring Organization:
USDOE
OSTI ID:
2424763
Journal Information:
Transportmetrica. A, Transport Science, Journal Name: Transportmetrica. A, Transport Science Journal Issue: 3 Vol. 18; ISSN 2324-9935
Publisher:
Taylor & Francis
Country of Publication:
United States
Language:
English

References (14)

Long short-term memory neural network for traffic speed prediction using remote microwave sensor data journal May 2015
Influences on Energy Savings of Heavy Trucks Using Cooperative Adaptive Cruise Control conference April 2018
Instantaneous vehicle fuel consumption estimation using smartphones and recurrent neural networks journal April 2019
Fuel consumption model for heavy duty diesel trucks: Model development and testing journal August 2017
Heavy-Duty Diesel Vehicle Fuel Consumption Modeling Based on Road Load and Power Train Parameters conference November 2005
A new modelling approach for road traffic emissions: VERSIT+ journal August 2007
A car-following model considering asymmetric driving behavior based on long short-term memory neural networks journal October 2018
Modal Emissions Model for Heavy-Duty Diesel Vehicles
  • Barth, Matthew; Scora, George; Younglove, Theodore
  • Transportation Research Record: Journal of the Transportation Research Board, Vol. 1880, Issue 1 https://doi.org/10.3141/1880-02
journal January 2004
Virginia Tech Comprehensive Power-Based Fuel Consumption Model: Model development and testing journal October 2011
Vehicle Dynamics Model for Predicting Maximum Truck Acceleration Levels journal October 2001
Virginia Tech Comprehensive Power-Based Fuel Consumption Model: Modeling Diesel and Hybrid Buses
  • Edwardes, William; Rakha, Hesham
  • Transportation Research Record: Journal of the Transportation Research Board, Vol. 2428, Issue 1 https://doi.org/10.3141/2428-01
journal January 2014
Recurrent neural networks and robust time series prediction journal March 1994
Estimation of the Energy Consumption of Battery Electric Buses for Public Transport Networks Using Real-World Data and Deep Learning journal May 2020
Learning long-term dependencies with gradient descent is difficult journal March 1994

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Related Subjects

Transportation