Fuel consumption for various driving styles in conventional and hybrid electric vehicles [electronic resource] : Integrating driving cycle predictions with fuel consumption optimization.
Driving Cycle; Equivalent Consumption Minimization Strategy (Ecms); Fuel Consumption; Hybrid Electric Vehicle (Hev); Optimal Energy Management.
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Full Text (via OSTI) |
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| Format: | Government Document Electronic eBook |
| Language: | English |
| Published: |
Washington, D.C. : Oak Ridge, Tenn. :
United States. Department of Energy. ; distributed by the Office of Scientific and Technical Information, U.S. Department of Energy,
2018.
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| Subjects: |
MARC
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| 245 | 0 | 0 | |a Fuel consumption for various driving styles in conventional and hybrid electric vehicles |h [electronic resource] : |b Integrating driving cycle predictions with fuel consumption optimization. |
| 260 | |a Washington, D.C. : |b United States. Department of Energy. ; |a Oak Ridge, Tenn. : |b distributed by the Office of Scientific and Technical Information, U.S. Department of Energy, |c 2018. | ||
| 300 | |a TBD- : |b digital, PDF file. | ||
| 336 | |a text |b txt |2 rdacontent. | ||
| 337 | |a computer |b c |2 rdamedia. | ||
| 338 | |a online resource |b cr |2 rdacarrier. | ||
| 500 | |a Published through SciTech Connect. | ||
| 500 | |a 06/14/2018. | ||
| 500 | |a International Journal of Sustainable Transportation ISSN 1556-8318 AM. | ||
| 500 | |a Jackeline Rios-Torres; Jun Liu; Asad Khattak. | ||
| 520 | 3 | |a Here, improving fuel economy and lowering emissions are key societal goals. Standard driving cycles, pre-designed by the US Environmental Protection Agency (EPA), have long been used to estimate vehicle fuel economy in laboratory-controlled conditions. They have also been used to test and tune different energy management strategies for hybrid electric vehicles (HEVs). This paper aims to estimate fuel consumption for a conventional vehicle and a HEV using personalized driving cycles extracted from real-world data to study the effects of different driving styles and vehicle types on fuel consumption when compared to the estimates based on standard driving cycles. To do this, we extracted driving cycles for conventional vehicles and HEVs from a large-scale U.S. survey that contains real-world GPS-based driving records. Next, the driving cycles were assigned to one of three categories: volatile, normal, or calm. Then, the driving cycles were used along with a driver-vehicle simulation that captures driver decisions (vehicle speed during a trip), powertrain, and vehicle dynamics to estimate fuel consumption for conventional vehicles and HEVs with power-split powertrain. To further optimize fuel consumption for HEVs, the Equivalent Consumption Minimization Strategy (ECMS) is applied. The results show that depending on the driving style and the driving scenario, conventional vehicle fuel consumption can vary widely compared with standard EPA driving cycles. Specifically, conventional vehicle fuel consumption was 13% lower in calm urban driving, but almost 34% higher for volatile highway driving compared with standard EPA driving cycles. Interestingly, when a driving cycle is predicted based on the application of case-based reasoning and used to tune the power distribution in a hybrid electric vehicle, its fuel consumption can be reduced by up to 12% in urban driving. Implications and limitations of the findings are discussed. | |
| 520 | 0 | |a Driving Cycle; Equivalent Consumption Minimization Strategy (Ecms); Fuel Consumption; Hybrid Electric Vehicle (Hev); Optimal Energy Management. | |
| 536 | |b AC05-00OR22725. | ||
| 650 | 7 | |a Energy Conservation, Consumption, And Utilization. |2 edbsc. | |
| 650 | 7 | |a Energy Planning, Policy, And Economy. |2 edbsc. | |
| 710 | 2 | |a Oak Ridge National Laboratory. |4 res. | |
| 710 | 1 | |a United States. |b Department of Energy. |4 spn. | |
| 710 | 1 | |a United States. |b Department of Energy. |b Office of Scientific and Technical Information. |4 dst. | |
| 856 | 4 | 0 | |u http://www.osti.gov/scitech/biblio/1457179 |z Full Text (via OSTI) |
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