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Mass Estimation of Load Trucks Based on CAN Bus Parameters with Dual Working Conditions
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Yongtao Li1, 2, Yunli Tian2, Yisheng Ning1, 2, Weiguang Zheng1, 2, Huijun Yin2, Enyong Xu3
Automotive Engineering | 2025, 47(5) : 982 - 991
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Automotive Engineering | 2025, 47(5): 982-991
• Papers •
Mass Estimation of Load Trucks Based on CAN Bus Parameters with Dual Working Conditions
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Yongtao Li1, 2, Yunli Tian2, Yisheng Ning1, 2, Weiguang Zheng1, 2, Huijun Yin2, Enyong Xu3
Affiliations
  • 1 School of Mechanical and Automotive Engineering，Guangxi University of Science and Technology，Liuzhou 545616
  • 2 Guangxi Key Laboratory of Automobile Components and Vehicle Technology，Liuzhou 545616
  • 3 Dongfeng Liuzhou Motor Company，Liuzhou 545616
Published: 2025-05-25 doi: 10.19562/j.chinasae.qcgc.2025.05.018
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The total vehicle mass is an important parameter for both power and safety control of the vehicle, especially for heavyduty 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.

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 . DOI: 10.19562/j.chinasae.qcgc.2025.05.018
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Article Info
doi: 10.19562/j.chinasae.qcgc.2025.05.018
  • Receive Date：2024-06-02
  • Online Date：2025-07-08
  • Published：2025-05-25
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  • Received：2024-06-02
  • Revised：2024-11-14
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Affiliations
    1 School of Mechanical and Automotive Engineering，Guangxi University of Science and Technology，Liuzhou 545616
    2 Guangxi Key Laboratory of Automobile Components and Vehicle Technology，Liuzhou 545616
    3 Dongfeng Liuzhou Motor Company，Liuzhou 545616
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https://castjournals.cast.org.cn/joweb/qcygc/EN/10.19562/j.chinasae.qcgc.2025.05.018
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