摘要
采用汽车运行状态特征参数的最优子集建立了一个基于模糊神经网络的汽车运行状态识别模型。对北京、上海、广州、武汉的主干道和快速路运行工况进行了识别,计算结果为:除对北京市主干道运行工况的识别准确度为82.67%外,对其余运行工况的识别准确度都为100%;对北京市主干道和快速路汽车实际运行车速的识别准确度为89.08%。
By using the best subset of the vehicle driving fication model was created herein, which was based on the fuzzy-neural network. Identifying vehicle driving cycle on the urban way and highway of the Beijing, Shanghai, Guangzhou and Wuhan,the re- suits are: except the accuracy of Beijing urban way is as 82.67 %, the accuracy of other vehicle driving cycles is as 100 % ; and the accuracy of Beiiing urban way and highway on-road driving situation is as 89. 08%.
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2013年第11期1521-1524,1530,共5页
China Mechanical Engineering
基金
"十二五"国家科技支撑计划资助项目(2011BAG04B00)
北京市自然科学基金资助项目(4122062)
北京理工大学电动车辆国家工程实验室开放基金资助项目(2012-NELEV-03)
北京交通大学基本科研业务费资助项目(M12JB00070)
关键词
运行状态识别
运行状态特征参数
模糊神经网络
driving situation identification
driving pattern parameter
fuzzy-neural network