Real-time control for a parallel hybrid electric vehicle based on Pontryagin's Minimum Principle

Liu, Teng; Zou, Yuan; Liu, Dexing; Sun, Fengchun

doi:10.1109/itec-ap.2014.6941257

Cited by 3 publications

(2 citation statements)

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“…According to the Hamiltonian function transformed by the Pontiac Gold Extreme Value (PMP) principle, 20,21 the above equation is converted into equation (8).…”

Section: Ecms Control Strategymentioning

confidence: 99%

Control strategy optimization of plug-in hybrid electric vehicle based on driving data mining

Wang

Pan

Sun

2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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SDP (Stochastic Dynamic Programming) control strategy can mine the travel data of drivers, so that the energy-saving potential of vehicles could be improved. However, there are two problems need to be solved in the current SDP: firstly, the analysis and construction method of driver’s typical driving cycle is not clear; secondly, the adaptability of SDP algorithm to a typical driving cycle is insufficient. To solve the above problems, a driving cycle construction method for off-line SDP solution is proposed, which is based on “analysis, dimension reduction and clustering” process. In addition, a coupled control strategy (ECMS-SDP) based on driving conditions identification is developed. Because it is difficult to predict the driving conditions in real time, the working part of the coupled control strategy is calculated by the method of improved random forest. The simulation results show that ECMS-SDP control strategy can save 8%–15% fuel on average compared with CD-CS control strategy, and can save 4%–7% fuel on average compared with ECMS control strategy. The results prove that the ECMS-SDP coupled control strategy can respond well to the changing driving environment, and the fuel economy of vehicles is enhanced.

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“…According to the Hamiltonian function transformed by the Pontiac Gold Extreme Value (PMP) principle, 20,21 the above equation is converted into equation (8).…”

Section: Ecms Control Strategymentioning

confidence: 99%

Control strategy optimization of plug-in hybrid electric vehicle based on driving data mining

Wang

Pan

Sun

2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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“…In the literature, several works have studied the optimal control for hybrid system. The work () treats the real time energy management strategy of hybrid system composed of FC/battery in order to minimize the fuel consumption while maintaining the battery SOC within reasonable bounds. The energy management problem is solved by using optimal control based on Pontryagin's Minimum Principle (PMP) combined with the proportional integral (PI) control.…”

Section: Proposed Optimal Controlmentioning

confidence: 99%

Combined passivity based control and optimal control for energy management of fuel cell/battery hybrid system

Benmouna

Becherif

2019

Asian J Control

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The energy management of hybrid electric vehicles is becoming an interesting topic for many researchers. Furthermore, the wise choice of the energy management strategy allows not only the best distribution of the power between the used sources, but also it allows reduction of consumption, increase in the lifetime of the sources, and improves the autonomy of the hybrid electric vehicle.The autonomy is guaranteed by the optimization of the embedded sources. In this study, the hybrid system consists of combining the fuel cell as the main source with the battery as the auxiliary source. The novelty of the proposed energy management strategy for the studied hybrid system is the combination between interconnection and damping assignment-passivity based control and the Hamiltonian Jacobi Bellman method. The stability proof is given and the efficiency of the proposed strategy is proved by the experimental work, where the obtained results show the good and adequate results to the proposed scenario.

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Real-time control for a parallel hybrid electric vehicle based on Pontryagin's Minimum Principle

Cited by 3 publications

References 20 publications

Control strategy optimization of plug-in hybrid electric vehicle based on driving data mining

Control strategy optimization of plug-in hybrid electric vehicle based on driving data mining

Combined passivity based control and optimal control for energy management of fuel cell/battery hybrid system

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