期刊
ENERGIES
卷 12, 期 10, 页码 -出版社
MDPI
DOI: 10.3390/en12101924
关键词
optimization; P2 HEV; rule-based control; large-scale simulation
资金
- Korea Institute of Energy Technology Evaluation and Planning (KETEP)
- Ministry of Trade, Industry and Energy (MOTIE) of the Republic of Korea [20172010104970]
- Technology Innovation Program [20002762]
- Ministry of Trade, Industry and Energy (MOTIE, Korea)
- Korea Evaluation Institute of Industrial Technology (KEIT) [20172010104970] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Hybrid electric vehicles (HEVs) require supervisory controllers to distribute the propulsion power from sources like an engine and motors. Control concepts based on optimal control theories such as dynamic programming (DP) and Pontryagin's minimum principle (PMP) have been studied to maximize fuel efficiencies. These concepts are, however, not practical for real-world applications because they guarantee optimality only if future driving information is given prior to the actual driving. Instead, heuristic rule-based control concepts are widely used in real-world applications. Those concepts are not only simple enough to be designed based on existing vehicle control concepts, but also allow developers to easily intervene in the control to enhance other vital aspects of real-world vehicle performances, such as safety and drivability. In this study, a rule-based control for parallel type-2 HEVs is developed based on representative control concepts of real-world HEVs, and optimal control parameters are determined by optimization processes. The performance of the optimized rule-based control is evaluated by comparing it with the optimal results obtained by PMP, and it shows that the rule-based concepts can achieve high fuel efficiencies, which are close, typically within 4%, to the maximum values obtained by PMP.
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