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

Abstract

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,more » 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.« less

Authors:

Rios-Torres, Jackeline  ^[1];

• Search DOE PAGES for author "Rios-Torres, Jackeline"
• Search DOE PAGES for ORCID "0000-0001-6750-9408"

Liu, Jun  ^[2];

• Search DOE PAGES for author "Liu, Jun"
• Search DOE PAGES for ORCID "0000-0002-6336-4931"

Khattak, Asad ^[3]

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+ Show Author Affiliations

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

Publication Date:

Thu Jun 14 00:00:00 EDT 2018

Research Org.:

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:

USDOE

OSTI Identifier:

1457179

Grant/Contract Number:  

AC05-00OR22725

Resource Type:

Accepted Manuscript

Journal Name:

International Journal of Sustainable Transportation

Additional Journal Information:

Journal Volume: 13; Journal Issue: 2; Journal ID: ISSN 1556-8318

Publisher:

Taylor & Francis

Country of Publication:

United States

Language:

English

Subject:

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