4.7 Article

Adaptive energy management in automated hybrid electric vehicles with flexible torque request

期刊

ENERGY
卷 214, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2020.118873

关键词

Hybrid electric vehicles; Energy management strategy; Equivalent consumption minimization strategy (ECMS); Vehicle electrification; Vehicle automation

资金

  1. National Natural Science Foundation of China [51905419, 51875054]
  2. Chongqing Natural Science Foundation for Distinguished Young Scholars [cstc2019jcyjjq0010]
  3. Natural Science Basic Research Program in Shaanxi Province of China [2019JQ503]

向作者/读者索取更多资源

An adaptive energy management strategy based on the equivalent consumption minimization strategy (ECMS) framework is developed to optimize gearshift commands and torque distribution for automated parallel hybrid electric vehicles. The methodology utilizes flexible torque requests to simultaneously consider drivability and fuel economy, resulting in improved powertrain optimization and promising fuel efficiency.
Rapidly-evolving technologies for vehicle electrification and automation offer increased opportunities to enhance the performance and efficiency of energy management strategies for automated hybrid electric vehicles (A-HEVs). In this context, an adaptive energy management approach based on an equivalent consumption minimization strategy (ECMS) framework is developed to optimize gearshift commands and torque distribution for an automated parallel HEV. This methodology utilizes the emerging idea of flexible torque request by considering drivability and fuel economy simultaneously. The gearshift map is extracted from optimal results with ECMS, as treated in the dynamic programming (DP)-based strategy, to avoid frequent gearshift events thereby considering both drivability and fuel economy. An adaptive energy management strategy with flexible torque request is then reformulated by a modified ECMS, seeking better performance for the powertrain optimization. As a result, utilizing the flexible torque request, the torque distribution and gearshift commands are jointly optimized in the same framework. A sensitivity study for different parameters is explored, and adaptation laws of the main parameters are also devised for the proposed approach. Finally, simulations are performed in two driving cases to demonstrate the effectiveness of the proposed method. Results confirm that the proposed methodology produces a promising fuel efficiency, relative to the one with fixed torque request, while ensuring good drivability and traffic efficiency. (C) 2020 Elsevier Ltd. All rights reserved.

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