Fuel consumption for various driving styles in conventional and hybrid electric vehicles: Integrating driving cycle predictions with fuel consumption optimization

Rios-Torres, Jackeline; Liu, Jun; Khattak, Asad

doi:10.1080/15568318.2018.1445321

Fuel consumption for various driving styles in conventional and hybrid electric vehicles: Integrating driving cycle predictions with fuel consumption optimization

Journal Article · Thu Jun 14 00:00:00 EDT 2018 · International Journal of Sustainable Transportation

DOI:https://doi.org/10.1080/15568318.2018.1445321· OSTI ID:1457179

^[1]; ^[2]; Khattak, Asad ^[3]

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); The Univ. of Tennessee, Knoxville, TN (United States)
Virginia Dept. of Transportation, Richmond, VA (United States); The Univ. of Tennessee, Knoxville, TN (United States)
The Univ. of Tennessee, Knoxville, TN (United States)

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.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1457179

Journal Information:: International Journal of Sustainable Transportation, Journal Name: International Journal of Sustainable Transportation Journal Issue: 2 Vol. 13; ISSN 1556-8318

Publisher:: Taylor & FrancisCopyright Statement

Country of Publication:: United States

Language:: English

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Related Subjects

29 ENERGY PLANNING, POLICY, AND ECONOMY
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
Driving cycle
equivalent consumption minimization strategy (ECMS)
fuel consumption
hybrid electric vehicle (HEV)
optimal energy management

Fuel consumption for various driving styles in conventional and hybrid electric vehicles: Integrating driving cycle predictions with fuel consumption optimization

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