Energy management of a parallel hybrid electric vehicle based on Lyapunov algorithm

Aiming at the time-consuming problem of basic dynamic programming (DP) algorithm and the fact that adaptive energy control management strategy (A-ECMS) cannot provide the optimal fuel consumption, this paper proposes highly integrated model of the vehicle coupling with a detailed engine model which...

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Published ineTransportation (Amsterdam) Vol. 13; p. 100184
Main Authors Li, Yangyang, Deng, Xintao, Liu, Biao, Ma, Jugang, Yang, Fuyuan, Ouyang, Minggao
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.08.2022
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ISSN2590-1168
2590-1168
DOI10.1016/j.etran.2022.100184

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Summary:Aiming at the time-consuming problem of basic dynamic programming (DP) algorithm and the fact that adaptive energy control management strategy (A-ECMS) cannot provide the optimal fuel consumption, this paper proposes highly integrated model of the vehicle coupling with a detailed engine model which is validated by the NEDC tested value. Then, an online energy management algorithm is proposed based on Lyapunov optimization analysis considering the system stability. The results show that (1) the cumulative fuel consumption obtained from the integrated model is 832.01g while the tested fuel consumption is 845.82g. The relative error between the simulated and tested fuel consumption is 1.63%. On this basis, the integrated model can be considered to predict the fuel economy of the vehicle with extraordinarily high accuracy. (2) Comparing the Lyapunov algorithm with DP and A-ECMS algorithms on a series parallel hybrid electric vehicle, the average fuel consumption of the proposed online energy management algorithm based on Lyapunov optimization is reduced by 13% compared with A-ECMS algorithm, which lays the foundation for the development of a unified algorithm platform. •An integrated model of the vehicle coupling with a detailed engine model is built.•Energy management of a PHEV based on Lyapunov algorithm is presented.•Fuel consumption of A-ECMS algorithm based on Lyapunov optimization is reduced by 13%.
ISSN:2590-1168
2590-1168
DOI:10.1016/j.etran.2022.100184