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Estimation of CO2 reduction by parallel hard-type power hybridization for gasoline and diesel vehicles

Title
Estimation of CO2 reduction by parallel hard-type power hybridization for gasoline and diesel vehicles
Author
박성욱
Keywords
Vehicle dynamic based model; Fuzzy logic; Internal combustion engine vehicles (ICEVs); Hybrid electric vehicles (HEVs); Fuel efficiency; CO2 emission rate
Issue Date
2017-05
Publisher
ELSEVIER SCIENCE BV
Citation
SCIENCE OF THE TOTAL ENVIRONMENT, v. 595, page. 2-12
Abstract
The purpose of this study is to investigate possible improvements in ICEVs by implementing fuzzy logic-based parallel hard-type power hybrid systems. Two types of conventional ICEVs (gasoline and diesel) and two types of HEVs (gasoline-electric, diesel electric) were generated using vehicle and powertrain simulation tools and a Matlab-Simulink application programming interface. For gasoline and gasoline-electric HEV vehicles, the prediction accuracy for four types of LDV models was validated by conducting comparative analysis with the chassis dynamometer and OBD test data. The predicted results show strong correlation with the test data. The operating points of internal combustion engines and electric motors are well controlled in the high efficiency region and battery SOC was well controlled within +/- 1.6%. However, for diesel vehicles, we generated virtual diesel-electric HEV vehicle because there is no available vehicles with similar engine and vehicle specifications with ICE vehicle. Using a fuzzy logic-based parallel hybrid system in conventional ICEVs demonstrated that HEVs showed superior performance in terms of fuel consumption and CO2 emission in most driving modes. (C) 2017 Elsevier B.V. All rights reserved.
URI
https://www.sciencedirect.com/science/article/pii/S0048969717306927?via%3Dihubhttp://repository.hanyang.ac.kr/handle/20.500.11754/114145
ISSN
0048-9697; 1879-1026
DOI
10.1016/j.scitotenv.2017.03.171
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > MECHANICAL ENGINEERING(기계공학부) > Articles
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