Optimizing the electric range of plug-in vehicles via fuel economy simulations of real-world driving in California. (August 2019)
- Record Type:
- Journal Article
- Title:
- Optimizing the electric range of plug-in vehicles via fuel economy simulations of real-world driving in California. (August 2019)
- Main Title:
- Optimizing the electric range of plug-in vehicles via fuel economy simulations of real-world driving in California
- Authors:
- Laberteaux, Kenneth P.
Hamza, Karim
Willard, John - Abstract:
- Highlights: Framework for modeling well to wheels real-world plug-in vehicles CO2 using big data. Simulations conducted using open-source code and public data sets. Considered sensitivity to fuel mix in electric grid as well as charging behavior. Examined several electric range designs for three plug-in powertrain architectures. Too long electric range can be detrimental to equivalent CO2 emissions. Abstract: This paper presents a modeling and simulation study of the greenhouse gas (GHG) emissions of plug-in vehicles subject to real-world driving conditions. The simulations utilize open-source software tools for estimation of second-by-second energy and/or fuel consumption in more than 65 thousand real-world recorded trips in the California household travel survey (CHTS) data set. Statistical distributions of the equivalent well-to-wheels (W2W) GHG emissions corresponding to CHTS trips are generated for three baseline public-domain plug-in vehicle models of: (i) parallel-drive plug-in hybrid, (ii) serial-drive plug-in hybrid, and (iii) pure electric vehicle. In addition to the baseline models, several derived vehicle models are created by upsizing of the battery and powertrain via an iterative procedure to attain the new all-electric range (AER). The emissions model also considers days when a pure electric vehicle cannot meet the travel demand by assuming that the driving on those days is done on a conventional vehicle. For each of the considered powertrain architectures,Highlights: Framework for modeling well to wheels real-world plug-in vehicles CO2 using big data. Simulations conducted using open-source code and public data sets. Considered sensitivity to fuel mix in electric grid as well as charging behavior. Examined several electric range designs for three plug-in powertrain architectures. Too long electric range can be detrimental to equivalent CO2 emissions. Abstract: This paper presents a modeling and simulation study of the greenhouse gas (GHG) emissions of plug-in vehicles subject to real-world driving conditions. The simulations utilize open-source software tools for estimation of second-by-second energy and/or fuel consumption in more than 65 thousand real-world recorded trips in the California household travel survey (CHTS) data set. Statistical distributions of the equivalent well-to-wheels (W2W) GHG emissions corresponding to CHTS trips are generated for three baseline public-domain plug-in vehicle models of: (i) parallel-drive plug-in hybrid, (ii) serial-drive plug-in hybrid, and (iii) pure electric vehicle. In addition to the baseline models, several derived vehicle models are created by upsizing of the battery and powertrain via an iterative procedure to attain the new all-electric range (AER). The emissions model also considers days when a pure electric vehicle cannot meet the travel demand by assuming that the driving on those days is done on a conventional vehicle. For each of the considered powertrain architectures, optimizing the AER for minimum GHG emissions becomes a trade-off between reducing the gasoline driven miles and maintaining reasonably sized (lightweight) powertrain components. As such, the equivalent GHG emissions of a vehicle are shown to have diminishing returns in terms of AER, and the optimum AER depends on both the carbon content in the electric grid, as well as the charging behavior. Within considered modeling assumptions and several vehicle usage conditions, the optimum AER is estimated to be between 30 and 60 miles for PHEVs, and between 120 and 200 miles for BEVs. … (more)
- Is Part Of:
- Transportation research. Volume 73(2019)
- Journal:
- Transportation research
- Issue:
- Volume 73(2019)
- Issue Display:
- Volume 73, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 73
- Issue:
- 2019
- Issue Sort Value:
- 2019-0073-2019-0000
- Page Start:
- 15
- Page End:
- 33
- Publication Date:
- 2019-08
- Subjects:
- Plug-in vehicles -- Electric vehicle range -- Greenhouse gas reduction -- California household travel survey
Transportation -- Research -- Periodicals
Transportation -- Environmental aspects -- Periodicals
354.76 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13619209 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.trd.2019.05.013 ↗
- Languages:
- English
- ISSNs:
- 1361-9209
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9026.274630
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 11361.xml