基于用户关联的车辆耐久性载荷谱编制

doi:10.13229/j.cnki.jdxbgxb.20220619

摘要/Abstract

摘要：

提出了一种新的车辆行驶工况划分方法，并将其应用到基于用户关联的车辆耐久性载荷谱编制当中。在车辆行驶工况的划分过程中选取了用以区分、量化和识别路面不平度、地形地貌、驾驶习惯等方面的7维随机向量。对这7个维度随机变量之间的相关性进行了研究，统计分析显示，7个随机变量中没有任何两个变量之间存在高度的相关性，因此，不宜对车辆行驶工况的划分方法作进一步简化。同时，由于相关维度的随机变量之间非独立，凸显了需要通过联合概率密度分布来描述车辆行驶工况的必要性。结果显示，由于所选择的各个维度全面描述和界定了车辆的行驶工况，形成了一个有机整体，在与整车不同载荷进行关联时，这一有机整体呈现出显著且有区别的整体相关性，可以基于此开展用户关联的车辆耐久性载荷谱编制。

关键词: 车辆工程, 行驶工况, 大数据分析, 用户关联, 车辆耐久性, 载荷谱

Abstract:

A new method to divide vehicle's driving conditions was presented and used in compiling vehicle durability load spectrum based on customer usage correlation. A seven dimension random vector was adopted to distinguish， quantify and identify road roughness， topographic feature and driving habit for division of vehicle's driving conditions. Correlation relations between the seven random variables were studied. The statistic results showed that any two variables among the seven random variables were not highly related， which indicated that further simplifying the method to divide vehicle's driving condition was not supported. Besides， the seven random variables were not independent， which highlighted the necessity to use the associated probability density distribution to describe vehicle's driving conditions. The results shown that the chosen dimensions thoroughly described and defined vehicle's driving conditions， which became an organic unity. When correlating to different loads of vehicle， the organic unity showed significant but distinctive overall correlation relationship， which could be used to compile vehicle durability load spectrum correlated to customer usage.

Key words: vehicle engineering, driving condition, big data analysis, customer usage correlation, vehicle durability, load spectrum

中图分类号:

U467

李旭东,王新宇,田程,张新峰,牛治慧,赵志强. 基于用户关联的车辆耐久性载荷谱编制[J]. 吉林大学学报(工学版), 2024, 54(1): 66-75.

Xu-dong LI,Xin-yu WANG,Cheng TIAN,Xin-feng ZHANG,Zhi-hui NIU,Zhi-qiang ZHAO. Compiling vehicle durability load spectrum based on customer usage correlation[J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(1): 66-75.

图/表 9

图1

表1

随机变量之间的相关系数"

	$X x 0$	$X x 1$	$X y$	$X z$	$X S p e e d$
$X x 0$	1	0.1283	0.4943	0.4004	-0.3982
$X x 1$	0.1283	1	0.2743	0.1926	-0.2290
$X y$	0.4943	0.2743	1	0.4669	-0.4028
$X z$	0.4004	0.1926	0.4669	1	0.0178
$X S p e e d$	-0.3982	-0.2290	-0.4028	0.0178	1

表1

表2

随机变量之间的偏相关系数"

	$X x 0'$	$X y'$	$X z'$	$X S p e e d'$
$X x 0'$	1	0.2186	-0.3036	-0.3248
$X y'$	0.2186	1	0.4153	0.3581
$X z'$	-0.3036	0.4153	1	0.3278
$X S p e e d'$	-0.3248	0.3581	0.3278	1

表2

图2

表3

图3

表4

假设检验结果汇总"

所分析的载荷	速度区间/（km·h^-1）	比较状态	$T$	$t n + m - 2 (α 2)$ 或 $u α / 2$
质心垂向加速度	40~60	空载vs满载	6.1373	1.9617
		空载vs半载	4.6003
		半载vs满载	2.0517
	80~100	空载vs满载	6.7046	1.96
		空载vs半载	5.4818
		半载vs满载	2.1199
前稳定杆剪应变	40~60	空载vs满载	3.9669	1.9617
前稳定杆剪应变	80~100	空载vs满载	2.6136	1.96
左前轮六分力垂向力分量	40~60	空载vs满载	0.9709	1.9617
		空载vs半载	0.5257
		半载vs满载	0.4981
	80~100	空载vs满载	1.2384	1.96
		空载vs半载	2.2909
		半载vs满载	1.0527

表4

图4

图5

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维度	前稳定杆应变	质心处垂向加速度	左前轮六分力所测得的力			左前转向拉杆横向力
维度	前稳定杆应变	质心处垂向加速度	纵向分量	侧向分量	垂向分量	左前转向拉杆横向力
车速	-0.4028	-0.0254	-0.4473	-0.435	-0.0207	-0.4857
坡度	0.0294	0.0467	-0.1679	-0.0178	0.0527	-0.1048
纵向加速	0.479	0.4563	0.5879	0.4914	0.4588	0.702
纵向减速	0.2706	0.2363	0.535	0.2967	0.2245	0.3488
侧向	0.8258	0.5676	0.4347	0.9122	0.5734	0.761
轴头垂向	0.5867	0.835	0.1889	0.394	0.914	0.4359