基于CAN总线参数的双工况载重车质量估计

doi:10.19562/j.chinasae.qcgc.2025.05.018

Abstract

Abstract:

The total vehicle mass is an important parameter for both power and safety control of the vehicle， especially for heavy-duty trucks. Based on the theory of vehicle longitudinal dynamics， a method for estimating the total vehicle mass according to the vehicle operating conditions is proposed in this paper. Firstly， under acceleration conditions， engine torque and longitudinal acceleration are obtained through CAN bus， using the Kalman filter algorithm （KF） to estimate the total vehicle mass. Then the estimated mass is used to identify the unknown parameters. At constant speed， the mass is estimated based on the identified unknown parameters and a simplified vehicle longitudinal dynamics model. The effectiveness of the method is verified through joint simulation suing the estimator constructed by TruckSim/Simulink. By the vehicle road test， the results show that the method is able to estimate the total vehicle mass more accurately under different operating conditions.

Key words: total vehicle mass, parameter identification, TruckSim /Simulink, CAN bus

Yongtao Li,Yunli Tian,Yisheng Ning,Weiguang Zheng,Huijun Yin,Enyong Xu. Mass Estimation of Load Trucks Based on CAN Bus Parameters with Dual Working Conditions[J].Automotive Engineering, 2025, 47(5): 982-991.

Figures/Tables 19

References 22

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参数	符号	单位	数值
外型尺寸	L×W×H	mm	10100×2550×4000
整车质量	M₁	kg	7 880
额定载质量	M₂	kg	9 990
发动机功率	P	kW	180
最大转矩		N·m	950
主减速器传动比	i₀		4.364
迎风面积	A	m²	9.875
车轮半径	r	m	0.505

名称	KF	EKF	RLS
估计均值/kg	15 640	14 365	14 144
相对误差/%	3.78	-4.67	-6.14
均方根误差/kg	490.782	792.258	706.311

名称	KF	EKF	RLS
估计均值/kg	17 311	18 817	16 836
相对误差/%	-3.35	5.06	-6.03
均方根误差/kg	465.525	931.868	987.948

名称	KF	EKF	RLS
估计均值/kg	12 574	11 943	13 052
相对误差/%	2.56	-2.58	6.46
均方根误差/kg	517.648	677.911	673.080

名称	KF	RLS
估计均值/kg	16 026	17 275
相对误差/%	-10.52	-3.54
均方根误差/kg	1 159.886	660.684

Mass Estimation of Load Trucks Based on CAN Bus Parameters with Dual Working Conditions

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