Volume 8: Advances in Energy Innovation and Development

Connected HEVs Energy Management Strategy Research Under the Traffic Information Preview Yang Shichun, Feng Song, Xie Hehui, Liu Jian, Chen Fei, Hua Yang



The traditional energy management system of hybrid electric vehicle did not take into account the future driving information. To realize the further energy optimization, the Bi-level energy management strategy in connected environment is studied in this paper. The upper controller is to predict the optimal velocity. Firstly, the target velocity range is first calculated based on the signal phase and timing (SPAT) information. Then the optimization function is designed to obtain the optimal acceleration. The lower controller is designed to follow the optimal acceleration and to save energy by optimizing the power split between the engine and motor under the condition of meeting the physical constraints. The rule-based and fuzzy logic controller based on genetic algorithm are adopted in this paper. Simulation results indicate that optimizing vehicle velocity trajectory in connected environment can effectively reduce fuel consumption and pollutant emission. Meanwhile, compared with Rule-based strategy, the fuzzy logic controller based on genetic algorithm contributes to realize the superior fuel economy performance and lower emissions.

Keywords Hybrid electrical vehicle, Energy management strategy, Intelligent traffic system, Connected environment

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