Methodology for Finding Maximum Performance and Improvement Possibility of Rule-Based Control for Parallel Type-2 Hybrid Electric Vehicles

Haeseong Jeoung, Kiwook Lee and Namwook Kim
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Haeseong Jeoung: Machine Dynamics Laboratory, Department of Mechanical Engineering, Hanyang University, Gyeonggi-do, Ansan 15588, Korea
Kiwook Lee: Machine Dynamics Laboratory, Department of Mechanical Engineering, Hanyang University, Gyeonggi-do, Ansan 15588, Korea
Namwook Kim: Machine Dynamics Laboratory, Department of Mechanical Engineering, Hanyang University, Gyeonggi-do, Ansan 15588, Korea

Energies, 2019, vol. 12, issue 10, 1-17

Abstract: 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.

Keywords: optimization; P2 HEV; rule-based control; large-scale simulation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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