基于密度聚类的商用车编队策略

doi:10.13229/j.cnki.jdxbgxb.20220733

Abstract

Abstract:

The total fuel consumption will only decrease when the increased fuel consumption during formation is less than the reduced fuel consumption during platoon operation. In order to form a commercial vehicle platoon with fuel saving potential， this paper proposes a density clustering based commercial vehicle formation strategy. First， the commercial vehicle model in Trucksim was used to collect fuel consumption data， and an equivalent fuel consumption model was established through fitting and simplified in the distance domain； Second， utilizing the optimization problem of two vehicle formation to obtain formation standards with fuel saving potential； Then， in density clustering， the dispersed commercial vehicles are clustered into sub platoon clusters using this standard， and the optimal equivalent fuel consumption function is defined to determine the final platoon form. Finally， the effectiveness and superiority of the formation strategy proposed in this paper were verified through co-simulation.

Key words: commercial vehicles, energy consumption, platoon formation standard, density clustering

CLC Number:

TP393.08

Di LIU,Yao SUN,Yun-feng HU,Hong CHEN. Commercial vehicle formation strategy based on density clustering[J].Journal of Jilin University(Engineering and Technology Edition), 2024, 54(5): 1459-1468.

Figures/Tables 15

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Table 1

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Table 2

Results of vehicle cluster and platoon arrangement based on DBSCAN clustering"

初始车速	初始位置
$v 0,1$ =30 m/s， $v 0,2$ =28 m/s，	$s 0,1$ =696 m， $s 0,2$ =671 m，
$v 0,3$ =28 m/s， $v 0,4$ =28 m/s，	$s 0,3$ =640 m， $s 0,4$ =620 m，
$v 0,5$ =27 m/s， $v 0,6$ =27 m/s，	$s 0,5$ =571 m， $s 0,6$ =443 m，
$v 0,7$ =27 m/s， $v 0,8$ =26 m/s，	$s 0,7$ =383 m， $s 0,8$ =195 m，
$v 0,9$ =24 m/s， $v 0,10$ =20 m/s	$s 0,9$ =89 m， $s 0,10$ =68 m

Table 2

Table 3

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名称	数值	单位
车重	5000	kg
迎风面积	5.3	m²
轮胎半径	510	mm
风阻系数	0.4	-
滚阻系数	0.0041	-
最大刹车力矩	12.5	kN·m
发动机最大功率	225	kW

子车队序号	包含车辆序号	车辆数目
1	1，2，3，4，6	5
2	9	1
3	5，8	2
4	7	1
5	10	1

Commercial vehicle formation strategy based on density clustering

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