A Cross Iteration Estimator with Base Vector for Estimation of Electric Mining Haul Truck's Mass and Road Grade

Abstract

Vehicle mass and road grade are important to traction control and safety control of electric mining haul trucks (EMHTs), especially to autonomous EMHTs. This paper proposes a base-vector based cross iteration estimator (BVCIE) to simultaneously estimate the vehicle mass and the road grade for EMHTs. To develop the estimator, the dynamics model for EMHTs is first built and the unknown parameters are identified by the recursive least square. Then the estimator is proposed by selecting a base vector from the parameters to be estimated, and by using a cross iteration strategy to update older information. This estimator is based on the ideology that the total mass of EMHT is a constant in every travelling trip. The estimator is finally validated on different loads under different road conditions with 930E. The experimental results show that both the vehicle mass and the road grade can be estimated with good accuracy.