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Connected HEVs Energy Management Strategy Research Under the Traffic Information Preview

  • Beihang University

科研成果: 期刊稿件会议文章同行评审

摘要

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 rulebased 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.

源语言英语
期刊Energy Proceedings
8
DOI
出版状态已出版 - 2020
活动Applied Energy Symposium: MIT A+B, AEAB 2020 - Cambridge, 美国
期限: 17 5月 202019 5月 2020

联合国可持续发展目标

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  1. 可持续发展目标 7 - 经济适用的清洁能源
    可持续发展目标 7 经济适用的清洁能源

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