摘要
设计了一种新的基于人工免疫网络优化的模糊神经混合动力汽车能量管理控制器.该控制器结合模糊控制和神经网络的优点,利用神经网络的自学习能力,自动生成模糊规则和隶属函数,并不断优化隶属函数的参数,直到达到设计要求.为了避免神经网络的学习过程陷入局部极值点,采用人工免疫网络优化神经网络的参数.仿真结果显示,经过参数优化的模糊神经能量管理控制器的性能比普通能量管理控制器好,能进一步降低HEV的油耗.
An artificial immune network algorithm was designed based fuzzy neural network HEV energy management controller, which used neural network＇s self-learning ability to create the fuzzy rules and membership function, and optimize the parameters of membership function. In order to prevent neural network learning from getting into local extreme point, artificial immune network algorithm was used to optimize neural network＇s parameters. Simulation results shows that optimized FNNC has better performance than that of normal energy management controller, which can reduce more fuel consumption.
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2006年第9期94-96,共3页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
国家高技术研究发展计划资助项目(2001AA501200
2003AA501200)
关键词
混合动力汽车
能量管理策略
模糊神经网络
人工免疫网络
hybrid electric vehicle （HEV）
energy management strategies
fuzzy neural network
artificial immune network
