期刊 电动汽车城市行驶工况构建方法研究  

Research on Construction Method of Electric Vehicle Urban Driving Conditions

作  者:阙海霞 宋若旸 兰海潮 王露[1] 马宗钰 

Que Haixia;Song Ruoyang;Lan Haichao;Wang Lu;Ma Zongyu(Chang’an University,Shaanxi Xi'an 710054)

机构地区:[1]长安大学,陕西西安710054

出  处:《汽车实用技术》2020年第22期10-13,共4页Automobile Applied Technology

Research on Construction Method of Electric Vehicle Urban Driving Conditions

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.

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 

分 类 号:U469.72[机械工程—车辆工程]

 

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