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Real‐time implementation of optimal control considering gear shifting and engine starting for parallel hybrid electric vehicle based on dynamic programming
Author(s) -
Fu Jiangtao,
Song Shuzhong,
Fu Zhumu,
Ma Jianwei
Publication year - 2017
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.2375
Subject(s) - dynamic programming , fuel efficiency , computer science , driving cycle , curse of dimensionality , optimal control , control (management) , automotive engineering , battery (electricity) , electric vehicle , a priori and a posteriori , mathematical optimization , engineering , algorithm , power (physics) , mathematics , philosophy , physics , epistemology , quantum mechanics , machine learning , artificial intelligence
Summary To achieve best fuel economy control for a parallel hybrid electric vehicle, optimized control based on dynamic programming (DP) is proposed. The main effort in this paper includes the following. First, the global optimal control mathematic model of the best fuel economy is constructed and its corresponding recursive equation is established. Second, 2 additional augmented cost functions are proposed to prevent frequent gear shifting and frequent engine stopping and starting. Third, an algorithm of restricting the exploring region is proposed to overcome the curse of dimensionality of the numerical DP, which can greatly reduce the computational complexity. Both this DP method and a simple threshold control in corporation of a standby optimization are applied to a vehicle manufactured by the Changan company on the Federal Test Program driving cycle. The results show that the proposed method is effective in reducing fuel consumption by 15%. Although the proposed DP method is implemented on a priori known driving cycle, it can provide a criterion to design and evaluate a control strategy to achieve better fuel consumption.