汽车工程 ›› 2021, Vol. 43 ›› Issue (5): 675-682.doi: 10.19562/j.chinasae.qcgc.2021.05.005

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基于交通信息的复合电源系统控制策略优化

胡杰1,2,3(),王明1,2,3,刘迪1,2,3,颜伏伍1,2,3,曹恺4   

  1. 1.武汉理工大学,现代汽车零部件技术湖北省重点实验室,武汉 430070
    2.武汉理工大学,汽车零部件技术湖北省协同创新中心,武汉 430070
    3.新能源与智能网联车湖北工程技术研究中心,武汉 430070
    4.东风汽车公司技术中心,武汉 430058
  • 收稿日期:2020-08-17 修回日期:2020-12-08 出版日期:2021-05-25 发布日期:2021-05-18
  • 通讯作者: 胡杰 E-mail:auto_hj@163.com
  • 基金资助:
    国家自然科学基金(51775393);柳州市科技计划项目(2018B0301b003)

Optimization of Control Strategy for Hybrid Power System Based on Traffic Information

Jie Hu1,2,3(),Ming Wang1,2,3,Di Liu1,2,3,Fuwu Yan1,2,3,Kai Cao4   

  1. 1.Wuhan University of Technology,Hubei Key Laboratory of Modern Auto Parts Technology,Wuhan 430070
    2.Wuhan University of Technology,Auto Parts Technology Hubei Collaborative Innovation Center,Wuhan 430070
    3.Hubei Technology Research Center of New Energy and Intelligent Connected Vehicle Engineering,Wuhan 430070
    4.Dongfeng Motor Corporation Technology Center,Wuhan 430058
  • Received:2020-08-17 Revised:2020-12-08 Online:2021-05-25 Published:2021-05-18
  • Contact: Jie Hu E-mail:auto_hj@163.com

摘要:

为考虑未来行驶车速和道路坡度对整车需求功率的影响,本文中基于交通信息融合对现有复合电源能量管理策略进行优化。首先采用MATLAB/Simulink搭建复合电源仿真模型,而基于交通拥堵情况和行驶车速类型提出了未来短时间车速变化趋势判定方法;接着结合道路坡度和车速变化趋势,设计了可基于交通信息自动修正超级电容输出功率的模糊控制器。最后,在能获取交通信息的前提下,采用该模糊控制器,对基于自适应小波变换-模糊控制的能量管理策略进行优化。结果表明,基于交通信息优化后的控制策略可进一步发挥复合电源的优势,使复合电源的能量消耗减少约2.3%,电池循环寿命提高约2.96%。

关键词: 复合电源, 能量管理策略, 交通信息, 车速变化趋势

Abstract:

With consideration of the influence of future driving speed and road slope on vehicle power demand, an optimization on the existing energy management strategy of hybrid power source is conducted in this paper based on traffic information fusion. Firstly, the hybrid power simulation model is constructed with MATLAB/Simulink, and based on the traffic congestion situation and driving speed type, a judgment method for the short?term speed changing trend in future is proposed. Then, according to the road slope and speed changing trend, a fuzzy controller, which can automatically correct the output power of ultra?capacitor based on traffic information, is designed. Finally, on the premise of acquiring traffic information and by using the fuzzy controller, an optimization on the energy management strategy based on adaptive wavelet transform?fuzzy control is performed. The results show that the control strategy optimized based on traffic information can further give play to the superiorities of hybrid power source, with its energy consumption reducing by about 2.3% and the battery cycle life extending by about 2.96%.

Key words: hybrid power source, energy management strategy, traffic information, speed changing trend