基于RBF神经网络的农用车油耗值标定方法  

Fuel Consumption Calibration Method Based on RBF Neural Networks

作　　者：许崇霞[1] 冯德军[1] 

机构地区：[1]日照职业技术学院,山东日照276826

出　　处：《农机化研究》2013年第6期206-209,共4页Journal of Agricultural Mechanization Research

基　　金：日照职业技术学院基金项目(10Y72)

摘　　要：油耗直接影响着农用车的经济性,真实油耗数据的准确检测对农用车产品管理的科学化以及建设资源节约型社会具有积极的意义。为此,针对行车电脑往往不能准确显示油耗值的缺点,提出油耗值的RBF神经网络标定方法。实验表明,该方法能取得较好的标定效果,简单实用,为农用车油耗值的实时监测提供了一种有效的手段。Fuel Consumption direct impacts fuel economy of agricultural vehicles.Accurate detection of actual fuel consumption data could improve the scientific of vehicles product management with a positive meaning of building a resource-saving society.According to the shortcomings of trip computer couldn＇t afford the real fuel consumption values,this paper presented a calibration method based on RBF neural network.Experiment results show that the calibration method is effective,simple and practical,and provides an effective method for the agricultural vehicle fuel consumption value of real-time monitoring.

关 键 词：农用车 油耗 RBF神经网络 标定模型 

分 类 号：S229[农业科学—农业机械化工程] TP183[农业科学—农业工程]