汽车工程

汽车工程 ›› 2019, Vol. 41 ›› Issue (12): 1347-1355.doi: 10.19562/j.chinasae.qcgc.2019.012.001

• •    下一篇

基于模糊逻辑控制的燃料电池汽车能量管理控制策略研究*

王骞1, 李顶根2, 苗华春3   

  1. 1.广东电科院能源技术有限责任公司,广州 510030;
    2.华中科技大学能源与动力工程学院,武汉 430074;
    3.深圳市晓龙新能源科技有限公司,深圳 518000
  • 发布日期:2019-12-25
  • 通讯作者: 李顶根,副教授,博士研究生,E-mail:lidinggen@hust.edu.cn
  • 基金资助:
    *国家重点研发计划项目(2018YFB0104100)资助

Research on Energy Management Strategy of Fuel Cell Vehicle Based on Fuzzy Logic Control

Wang Qian1, Li Dinggen2, Miao Huachun3   

  1. 1.Guangdong Diankeyuan Energy Technology Co., Ltd., Guangzhou 510030;
    2.School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan 430074;
    3.Shenzhen Xiaolong New Energy Technology Co., Ltd., Shenzhen 518000
  • Published:2019-12-25

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摘要： 针对燃料电池汽车频繁过度放电导致其使用寿命缩短、需求模组功率过高急剧增加经济成本的问题,以燃料电池汽车结合动力电池模组的方式,提出了基于微小变量模糊逻辑控制的燃料电池补偿动力电池放电的能量管理控制策略模型。通过对ADVISOR进行二次开发优化,仿真验证了所制定的电电混动模型能量管理控制策略的合理性,保证了整车的动力性和经济性,又以汽车结束行驶时系统总的能量利用效率为优化目标对其进行了优化,结果表明基于微小变量模糊逻辑控制的电电混动新能源汽车动力性满足要求,经济性得以提高。

关键词: 燃料电池汽车, 微小变量模糊逻辑, 能量管理, 控制策略, 仿真优化

Abstract: For the problem of shortened service life of the fuel cell vehicle due to frequent over-discharge and the rapid increase of economic cost caused by high power demand module, a control strategy model of energy management for fuel cell compensated power battery discharge based on micro-variable fuzzy logic control is proposed by combining fuel cell vehicle with power battery module. Through the secondary development and optimization of ADVISOR, the simulation results verify the rationality of the energy management control strategy of the fuel cell-battery hybrid model, which ensures the power and economic performance of the vehicle. In addition, the total energy utilization efficiency of the system at the end of the driving cycle is optimized. The results show that the fuel cell-battery hybrid vehicle based on micro-variable fuzzy logic control meets the requirements of power and the economic performance is improved.

Key words: fuel cell vehicles, micro-variable fuzzy logic, energy management, control strategy, simulation optimization