Predictive energy management strategy of fuel cell bus based on comprehensive energy consumption and compound braking proportion distribution

Mei Yan, Guotong Li, Hongwen He*, Hao Li

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

To improve the energy efficiency of fuel cell buses and reduce the adverse effects on vehicle braking impact caused by the distribution of motor braking and mechanical braking, a predictive energy management strategy (EMS) for fuel cell buses with comprehensive energy consumption and compound braking ratio is proposed to weigh braking ride comfort and energy consumption. Firstly, the driver pattern recognition based on K-means is designed to improve the speed prediction module of BiLSTM (Bi-directional Long Short-Term Memory) to improve the speed prediction accuracy; then, the optimal braking distribution ratio and energy distribution strategy of fuel cell bus are optimized by designing LQR (linear quadratic regulator) controller, and the results are compared with the EMS based on CDCS (Charge depletion charge sustaining) and the EMS based on DP (Dynamic programming). The results show that this strategy can effectively reduce the energy consumption and braking impact degree while reducing the predicted RMSE (Root mean square value) by 9.4%. Compared to the regular braking ratio, the braking impact degree of this strategy is reduced from 3.02m/s3 to 2.72m/s3. By comparing the two benchmark EMSs, the performance of this strategy is close to that of the DP-based EMS. The equivalent hydrogen consumption of 100 km decreased from 7.02kg to 6.36kg.

源语言英语
主期刊名2022 6th CAA International Conference on Vehicular Control and Intelligence, CVCI 2022
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9781665453745
DOI
出版状态已出版 - 2022
活动6th CAA International Conference on Vehicular Control and Intelligence, CVCI 2022 - Nanjing, 中国
期限: 28 10月 202230 10月 2022

出版系列

姓名2022 6th CAA International Conference on Vehicular Control and Intelligence, CVCI 2022

会议

会议6th CAA International Conference on Vehicular Control and Intelligence, CVCI 2022
国家/地区中国
Nanjing
时期28/10/2230/10/22

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