双源型纯电动汽车能量管理优化策略研究
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长沙理工大学

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“湖南省电动交通与智能配网工程技术研究中心”开放基金项目(2015TP2001);湖南省自然科学(2017JJ2265)


Research on energy management strategy improvement of dual source pure electric vehicle
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Changsha University of science and technology

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    摘要:

    驾驶意图是复合型能源汽车能量分配的重要影响因素,同时考虑到需求功率的低频部分冲击性小,可由蓄电池优先承担,高频部分冲击性大可由超级电容优先承担,提出了融合驾驶意图识别的混合电动汽车功率分配控制方法。通过驾驶员意图识别动态调整滤波器时间常数,从而调整能量分配,使得在传统控制策略中只考虑“车”因素基础上,增加考虑“人”的因素。在US06-HWY、HWFET、UDDS、NYCC类比高速工况、城市快速路、郊区路况、拥堵路况的四种类型工况下仿真,并测算了该策略下整车单位里程损耗均值为32.61wh/km。与传统模糊控制对比,所提出的策略蓄电池的输出电流更加平滑,功率波动降低了23.70%,温升降低了19.96%。仿真结果表明,所提策略能更充分利用储能系统的动力特性,有效延长蓄电池寿命。

    Abstract:

    driving intention is an important factor affecting the energy distribution of hybrid energy vehicles. Considering that the low-frequency part of the power demand has small impact, which can be borne by the battery first, and the high-frequency part of the impact can be borne by the super capacitor, a power distribution control method based on driving intention recognition for hybrid electric vehicles is proposed. By identifying the driver"s intention, the time constant of the dynamic adjustment filter is adjusted to adjust the energy distribution, so that the "human" factor is added to the traditional control strategy based on only considering the "car" factor. The simulation results show that the average vehicle mileage loss under us06-hwy, hwfet, UDDS, Nycc is 32.61wh/km under four types of driving conditions, such as high-speed, urban expressway, suburban road and congested road. Compared with the traditional fuzzy control, the output current of the battery is more smooth, the power fluctuation is reduced by 23.70%, and the temperature rise is reduced by 19.96%. The simulation results show that the proposed strategy can make full use of the dynamic characteristics of the energy storage system and effectively extend the battery life.

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  • 收稿日期:2021-03-11
  • 最后修改日期:2021-05-05
  • 录用日期:2021-06-18
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