An online estimation algorithm to predict external forces acting on a front-end loader. (October 2021)

• Record Type: Journal Article
• Authors: Madau, Riccardo; Colombara, Daniele; Alexander, Addison; Vacca, Andrea; Mazza, Luigi
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 235:Number 9(2021)
• Page Start: 1678
• Page End: 1697
• Publication Date: 2021-10
• Subjects: Bucket force estimation -- digging forces -- payload estimation -- wheel loader -- resistance forces; Mechanical engineering -- Periodicals; Automatic control -- Periodicals; Systems engineering -- Periodicals; 621.3
• DOI: 10.1177/09596518211005583
• Languages: English
• ISSNs: 0959-6518

Abstract

One of the most significant goals of earthmoving equipment is to maximize productivity during loading cycles. A real-time knowledge of the forces exchanged between the machine implement and the surrounding, that is, while digging, can be used in different ways to increase productivity. It can be used to determine the amount of material moved by the machine; or to find the optimal bucket trajectory; moreover, as input to traction control systems. This article presents an online force estimation algorithm able to predict vertical and horizontal forces exchanged between the front-loader and the surrounding environment, as well as the reaction forces through the implement itself. Taking the case of a 14-ton wheel loader as reference, this article illustrates the development of a simulation model for the analysis of the machine digging system, along with the instrumentation and testing of the proposed estimation algorithm. The model is divided into two sections describing, respectively, system kinematic and system dynamics. The kinematic model of the front-loader is compared against measurements, and results show an average error lower than 1%. The dynamic model predicts both hydraulic and dynamic features of the machine implement, achieving an accuracy on the payload mass within 2%–3%, even during dynamic conditions. The estimated pushing force reflects the expected behavior when tested for various pushing efforts and in different ground conditions. Eventually, the algorithm was tested on a complete loading cycle and the results show good consistency considering the measured front-loader trajectory and vehicle speed. The proposed model overcomes some drawbacks of the currently used technologies. For example, it allows for an online estimation of the bucket forces for any position of the implement. Although the results discussed in this article pertain to a specific reference machine, the proposed method can be extended to most wheel loaders equipped with standard digging equipment.