期刊文献+

基于Parzen窗的手动变速器挡位识别方法研究 被引量:1

Research on Manual Transmission Gear Identification Method Based on Parzen Window
下载PDF
导出
摘要 针对手动挡车辆在运行过程中无挡位传感器的情况下挡位信号无法识别获取的问题,通过对多次整车转鼓试验进行分析,发现读取CAN总线里面的速比信息,然后基于直方图计算各速比范围信号出现的频率,并以此确定挡位数目和速比的大小范围,再利用Parzen窗函数的方法获取各挡位的实际速比,可以实现对挡位信号精准的识别。试验结果表明,采用Parzen窗的挡位识别方法能够识别出挡位信号。对比Parzen窗获取的挡位识别信息与挡位信号传感器直接获取的挡位信息,发现两者的相似度很高,这也验证了该方法的可行性和准确性。该方法提供了整车运行过程中一种挡位识别的新方式。 During operation a manual transmission vehicle could not obtain the gear position signal without installing the corresponding sensors. This paper analyzed the whole vehicle experiments on the drum tester, read the gear ratio information through CAN bus, then calculated the frequency of each speed ratio signal to determine the number of gear ratios and the range of speed ratio based on the histogram, and the actual speed ratio could be obtained by using the Parzen window function method, which ultimately achieved the accurate identification of the gear position signal. The gear position information acquired by using the Parzen window method agrees well with that obtained directly from the sensor. The comparison verifies the feasibility and accuracy of the method and the paper provides a new method for gear position identification.
出处 《汽车工程学报》 2016年第6期449-453,共5页 Chinese Journal of Automotive Engineering
基金 上汽科技基金(SAIC1517)
关键词 手动变速器 挡位识别 PARZEN窗 CRUISE manual transmission gear calibration Parzen window CRUISE
  • 相关文献

参考文献8

二级参考文献65

  • 1常群,王晓龙,林沂蒙,王熙照,Daniel S.Yeung.支持向量分类和多宽度高斯核[J].电子学报,2007,35(3):484-487. 被引量:10
  • 2尹传环,田盛丰,牟少敏.一种面向间隙核函数的快速算法[J].电子学报,2007,35(5):875-881. 被引量:1
  • 3杨伟斌,吴光强,秦大同.双离合器式自动变速器传动系统的建模及换挡特性[J].机械工程学报,2007,43(7):188-194. 被引量:59
  • 4王望予.汽车设计[M].4版.北京:机械工业出版社,2004:209-210.
  • 5Baram Y.Learning by kernel polarization[J].Neural Com-putation,2005,17(6):1264-1275.
  • 6Nguyen C H,Ho T B.Kernel matrix evaluation[C].Hy-derabad,India:Proc of the 20th International JointConference on Artificial Intelligence,2007:987-992.
  • 7WANG T,TIAN S,HUANG H,et al.Learning by localkernel polarization[J].Neurocomputing,2009,72(13-15):3077-3084.
  • 8Cortes C,Mohri M,Rostamizadeh A.Two-stage learningkernel algorithms[C].Haifa,Israel:Proc of the 27th Inter-national Conference on Machine Learning,2010:239-246.
  • 9Wang G,Yeung D Y,Lochovsky F H.A kernel path algo-rithm for support vector machines[C].Corvalis,USA:Proc of the 24th International Conference on MachineLearning,2007:951-958.
  • 10WU K P,WANG S D.Choosing the kernel parameters forsupport vector machines by inter-cluster distance in the featurespace[J].Pattern Recognition,2009,42(5):710-717.

共引文献132

同被引文献13

引证文献1

二级引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部