Estimation of Electric Mining Haul Trucks' Mass and Road Slope Using Dual Level Reinforcement Estimator
Estimation of Electric Mining Haul Trucks' Mass and Road Slope Using Dual Level Reinforcement Estimator
复制标题
使用双级加固估算器估算电动矿用运输卡车的质量和道路坡度
DOI：
10.1109/tvt.2019.2943574
复制
发表时间：
2019-11-01
影响因子：
6.8
通讯作者：
Murphey, Yi Lu
中科院分区：
文献类型：
--
作者：
Zhang, Ying;Zhang, Yingjie;Murphey, Yi Lu
本文提出了一种双级配筋估计方法来估计矿用电动运输卡车的总质量和道路坡度。为了设计估计器，建立了EMHT的纵向动力学模型，并采用具有双遗忘因子的递推最小二乘（RLS）辨识模型参数。该DLRE由初始水平估计和扩展水平估计组成。在初始估算中，对总质量和道路坡度进行了初步估算。在扩展估计中，为了防止估计的质量误差导致道路坡度产生较大误差，首先估计道路坡度，然后根据估计的道路坡度估计总质量。DLRE克服了传统的基于递归策略的估计器的缺点，即累积估计误差经常导致估计性能差甚至导致估计偏离。用930E的EMHT验证了DLRE的性能，实验结果表明，使用DLRE可以较准确地估计总质量和道路坡度。
This paper proposes a dual level reinforcement estimator (DLRE) to estimate the electric mining haul trucks' (EMHTs') total mass and road slope. To design the estimator, the longitudinal dynamics model of EMHT is built and the model's parameters are identified by a recursive least square (RLS) with double forgetting factors. This DLRE consists of an initial level estimation and an extended level estimation. In the initial estimation, the total mass and the road slope are preliminary estimated. In the extended estimation, to prevent the estimated mass error from leading to great errors in the road slope, the road slope is first estimated and then the total mass is estimated based on the estimated road slope. The DLRE overcomes the defects of the traditional recursive-strategy-based estimators whose cumulative estimation errors often lead to poor estimation performance or even lead to estimation divergence. The DLRE performance is validated with an EMHT of 930E, and the experimental results show that the total mass and the road slope are estimated with higher accuracy using the DLRE.