汽车工程

汽车工程

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基于工况预测的复合电源功率分配策略研究

王峰,罗玉涛   

  1. 华南理工大学机械与汽车工程学院，广州，510641
  • 出版日期:2019-03-05 发布日期:2019-03-05
  • 基金资助:
     

Research of Power Splitting Strategy of Hybrid Energy Storage System Based on Driving Cycle Prediction

    

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  • Online:2019-03-05 Published:2019-03-05
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摘要： 电池+超级电容组成的复合电源可以兼顾储能系统的能量需求和功率需求，并可以延长电池使用寿命。本文提出了一种基于工况预测的复合电源自适应神经模糊功率分配策略，采用马尔科夫链模型对汽车未来的运行工况进行预测，得到的车速预测结果，作为自适应神经模糊控制器的其中一个输入，经自适应神经模糊控制器处理后得到功率分配值。实验结果表明，自适应神经模糊的复合电源功率分配策略对电池寿命有明显的提升，综合使用成本比纯电池包低。

关键词: 复合电源, 工况预测, 自适应神经模糊, 功率分配

Abstract: The hybrid energy storage system composed of battery pack and supercapacitor can meet the energy and power requirements of the energy storage system and extend the battery life. In this paper, an adaptive neural fuzzy inference system (ANFIS) power splitting strategy for hybrid energy storage system based on driving cycle prediction is proposed. The Markov chain model is used to predict the future driving cycle of vehicle. The predicted speed is used as one of the inputs of the ANFIS controller. The output power of the supercapacitor is obtained by ANFIS controller. The experimental results show that the hybrid energy storage system using the ANFIS based on driving cycle prediction can significantly improve the battery life, and the cost is lower than that of the pure battery pack.

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