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DEVELOPMENT OF EQUIVALENT FUEL CONSUMPTION MINIMIZATION STRATEGY FOR HYBRID ELECTRIC VEHICLES

Authors
Park, J.Park, Jahng Hyon
Issue Date
Aug-2012
Publisher
한국자동차공학회
Keywords
Hybrid electric vehicle; Supervisory control; Equivalent factor; Parameter optimization; Genetic algorithm
Citation
International Journal of Automotive Technology, v.13, no.5, pp 835 - 843
Pages
9
Indexed
SCIE
SCOPUS
KCI
Journal Title
International Journal of Automotive Technology
Volume
13
Number
5
Start Page
835
End Page
843
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/164987
DOI
10.1007/s12239-012-0084-6
ISSN
1229-9138
1976-3832
Abstract
Power distribution between an internal combustion engine and electric motors is one of main features of hybrid electric vehicles that improves their fuel economy. An equivalent fuel consumption minimization strategy can instantaneously identify the optimal power distribution by converting the battery power into the equivalent fuel power and minimizing the overall fuel consumption. To guarantee the effectiveness of the strategy, it is essential to find the proper value of the conversion factor used to obtain the equivalent fuel power. However, finding the proper value is not a straightforward process because it is necessary to consider the overall power conversion efficiencies and battery charge sustaining strategy for the target driving cycle in advance. In this study, a model-based parameter optimization method is introduced to find the optimal conversion factor. A hybrid electric vehicle simulation model capable of estimating fuel consumption was developed, and the optimal conversion factor was discovered using a genetic algorithm that evaluates its population members using the simulation model. A series of simulations and vehicle tests was conducted to verify the effectiveness of the optimized strategy, and the results show a distinct improvement in fuel economy.
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