Vehicle mass estimation is the key technology to improve vehicle stability. However, the existing mass estimation accuracy is easily affected by the change of road gradient, and there are few studies on the mass estimation method of the light truck. Aiming at this problem, this paper uses sensors to measure road gradient and rear suspension deformation and proposes a sensor-based vehicle mass estimation algorithm. First, factors that affect the mass estimation are analyzed, road gradient error correction method and mass estimation error correction method are established. Besides, the suspension deformation is decoupled from the road gradient. Second, the mass estimation algorithm model was established in Matlab/Simulink platform and compared with the mass estimation iterative algorithm. Finally, the road test was carried out under various conditions, the results show that the proposed mass estimation algorithm is robust, and the accuracy of the mass estimation will not be affected by the sudden change of road gradient.

中文翻译：

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基于车载传感器的卡车质量估计方法

车辆质量估计是提高车辆稳定性的关键技术。然而，现有的质量估计精度容易受到道路坡度变化的影响，对轻型卡车质量估计方法的研究较少。针对这一问题，本文利用传感器测量道路坡度和后悬架变形，提出一种基于传感器的车辆质量估计算法。首先分析了影响质量估计的因素，建立了道路坡度误差修正方法和质量估计误差修正方法。此外，悬架变形与道路坡度解耦。其次，在Matlab/Simulink平台上建立了质量估计算法模型，并与质量估计迭代算法进行了比较。最后，