## 1 Introduction  
The large-tonnage EWL is a widely used piece of mining machinery. The large-tonnage EWL is capable of shoveling, transporting, and unloading materials [1]. They are primarily used for handling loose materials, including soil, sand, gravel, and limestone. In recent years, due to operational demands, mining machinery has required higher efficiency levels and loading capacities. Because of advantages in size, bucket capacity, and tonnage, the large-tonnage EVLs have become increasingly popular. The shovel force is a crucial factor influencing the shoveling section of the device [2]. When shoveling materials, the shove force will experience a sharp increase and exhibit abrupt changes. When the shovel force exceeds the ground traction of the EWL, the tires of the EWL will slip, resulting in an additional power loss. Currently, there are three main methods used to improve the accuracy of bucket-force prediction: theoretical calculation, empirical formula, and discrete-element-based methods. This paper adopts a discrete-element-based approach. Compared to theoretical calculation, the discrete-element-based method makes it easier to obtain test data. In contrast to the empirical formula, which tends to have larger prediction errors for large-tonnage EVLs, the discrete-element-based method exhibits smaller prediction errors in the estimation of shovel force for large-tonnage EVLs. During the new-product design period of large-tonnage EVLs, when some data are lacking, it has been observed that using the empirical-formula-based methods to match motor power based on shovel force could result in significant errors. This could have a substantial impact on the EWL's design. To avoid the risk of design failure due to excessively high or low power-matching results, especially when the bucket of EWL configurations is similar, a method based on discrete elements has been proposed. This method selects the most typical operational and material conditions for EVLs, providing a method for accurate prediction of shovel force. The operational efficiency of EVLs is directly affected by shovel force. The forward design of buckets and engine matching has been guided by the research on shovel force. Therefore, many scholars have conducted extensive research on the loading section. [PERSON] [3] selected four factors, with a significant impact given to shovel force. She used orthogonal simulation analysis and range analysis to study the effects of these factors on the force at the peak of the shovel force. The factors were found to have the following order of significance: particle size, bucket width, insertion speed, and particle shape. [PERSON] [4], focusing on conditions associated with the loading of gravel, conducted comparative studies by installing different numbers of bucket teeth. The research found that the number of bucket teeth had an impact of no higher than 10% on shovel force, no higher than 7% on the full bucket rate, and no higher than 3.5% on insertion depth. [PERSON] [5] has proposed an improved conformal mapping (ICM) method for analyzing the air-gap magnetic field in surface-mounted permanent magnet synchronous motors (SPMSMs). In comparison to the traditional conformal mapping (TCM) method, ICM demonstrates higher calculation speed and accuracy by reducing the amount of mapping time. The article validates the accuracy and efficiency of the ICM method through an experimental prototype of an eccentric-shaped-pole permanent magnet motor. [PERSON] [6] introduces a multidisciplinary design optimization framework for underwater gliders. The article establishes a universal disciplinary framework and enhances efficiency through approximate models. The proposed approach combines concurrent subspace optimization, a penalty function method, and a multipopulational genetic algorithm. Validated through a sea trial of an improved Petrel-L glider, the method rapidly determines optimal design parameters. [PERSON] [7] proposes a low-thrust reconfiguration strategy for formation flying using Jordan normal form.