scholarly journals Multiphase mixed-integer nonlinear optimal control of hybrid electric vehicles

Automatica ◽  
2021 ◽  
Vol 123 ◽  
pp. 109325 ◽  
Author(s):  
Nicolò Robuschi ◽  
Clemens Zeile ◽  
Sebastian Sager ◽  
Francesco Braghin
Keyword(s):  
Optimal Control ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Nonlinear Optimal Control ◽  
Mixed Integer ◽  
Hybrid Electric

Optimal Control of Series Plug-In Hybrid Electric Vehicles Considering the Cabin Heat Demand

2016 ◽  
Vol 24 (3) ◽  
pp. 1126-1133 ◽  
Author(s):  
Jorg Gissing ◽  
Philipp Themann ◽  
Sidney Baltzer ◽  
Thomas Lichius ◽  
Lutz Eckstein
Keyword(s):  
Optimal Control ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Heat Demand ◽  
Hybrid Electric

scholarly journals A Real Time Energy Management Strategy for Plug-in Hybrid Electric Vehicles based on Optimal Control Theory

2014 ◽  
Vol 45 ◽  
pp. 949-958 ◽  
Author(s):  
Laura Tribioli ◽  
Michele Barbieri ◽  
Roberto Capata ◽  
Enrico Sciubba ◽  
Elio Jannelli ◽  
...  
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Real Time ◽  
Energy Management ◽  
Electric Vehicles ◽  
Optimal Control Theory ◽  
Management Strategy ◽  
Hybrid Electric Vehicles ◽  
Energy Management Strategy ◽  
Hybrid Electric

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

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1924 ◽  
Author(s):  
Haeseong Jeoung ◽  
Kiwook Lee ◽  
Namwook Kim
Keyword(s):  
Optimal Control ◽  
Electric Vehicles ◽  
Real World ◽  
Hybrid Electric Vehicles ◽  
Minimum Principle ◽  
Rule Based ◽  
Real World Applications ◽  
Hybrid Electric ◽  
Parallel Type

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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