摘要
为描述西安市电动汽车行驶状况,选取三种方法构建工况:聚类法、V-A矩阵法、马尔科夫法。对试验获得的数据先进行降噪平滑处理,然后采用短行程法划分运动学片段,最后根据不同方法合成了C-SHT工况、C-VA工况、C-PKMMC工况。通过计算三种工况与原始数据的误差,发现C-PKMMC工况的误差最小,为4.94%,而其他俩个分别为7%和9.35%。可以得到马尔科夫法构建的工况既满足行驶工况合成的要求,同时也提高了行驶工况的精度。
In order to describe the driving situation of electric vehicles in Xi'an,three methods of constructing working conditions were selected:Clustering method,V-A matrix method,and Markov method.For the data obtained from the experiment,the noise reduction and smoothing process is first performed,and then the short-stroke method is used to divide it into kinematics fragments.Finally,the C-SHT working conditions,C-VA working conditions,and C-PKMMC working conditions are synthesized according to different methods.By calculating the error between the three working conditions and the original data,it is found that the error rate of the C-PKMMC working condition is the smallest,which is 4.94%,while the other two are 7%and 9.35%,respectively.The working conditions constructed by the Markov method meet the requirements of driving condition synthesis,and also improve the accuracy of driving conditions.
作者
阙海霞
宋若旸
兰海潮
王露
马宗钰
Que Haixia;Song Ruoyang;Lan Haichao;Wang Lu;Ma Zongyu(Chang’an University,Shaanxi Xi'an 710054)
出处
《汽车实用技术》
2020年第22期10-13,共4页
Automobile Applied Technology
关键词
聚类法
V-A矩阵法
马尔科夫方法
短行程法
相对误差
Clustering method
V-A matrix method
Markov method
Short-Stroke method
Relative error