# Dynamic Modeling and Output Characteristics Analysis of the Hub-Drive Reduction System
## 1 Introduction  
With the development of the global economy, the demand for mineral resources is increasing and mining technology for mineral resources has become an indispensable part of it. In practical engineering applications, large mining dump trucks, as one of the most popular mining machines, greatly promote the development and utilization of mining resources and occupy an important position in mining machinery. Its core component production, R&D, and intelligent technology have also attracted the attention of enterprises and researchers around the world, as have customizable aspects like lane widths that are related to design-related factors including saturation flow rate, lateral safety distance, traffic crash rate, and driver comfort [1, 2, 3, 4, 5]. Generally, the driving form of a mining dump truck can be categorized according to its rated loading capacity, and mining dump trucks with a load capacity of more than 100 t are generally used in large mine construction. An electric transmission is mainly used to drive a whole vehicle, as this transmission mode is more reliable and convenient than mechanical transmission. Compared with low-load mechanical transmission mining dump trucks, electric transmission trucks use a combination of a generator and an in-wheel motor to achieve transmission, which replaces the hydraulic gearbox and helical differential in the traditional mechanical transmission mechanism, making the overall structure simplerand more economical and prolonging the service life and operation performance of mining dump trucks [6; 7; 8; 9]. Some researchers have carried out research on mining dump trucks [10], which had certain first-mover advantages that were embodied in structural design, dynamic optimization, numerical modeling, and life prediction. Some people have studied the suspension stiffness and vehicle vibration of articulated mining dump trucks, analyzed the sensitivity of relevant influencing factors, and optimized design schemes. In addition, there have been many studies on the numerical modeling and analysis of mining dump trucks [11; 12; 13]. Using the pavement load spectrum and the stress of the machine parts, combined with finite element analysis to study the fatigue life mechanism, the dynamic performance of a vehicle and the fatigue life of its parts were analyzed and studied [14; 15]. [PERSON] et al. simulated and checked the strength of a dump truck frame by combining multi-body dynamics simulation, the analysis software ADAMS 2017, and the finite element analysis software NASTRAN 2017 to simulate and check the strength of the dump truck frame through a load spectrum under the actual working conditions of the mining dump truck. The elastic deformation characteristics of the frame were introduced into the dynamic analysis model, and the accuracy of the simulation calculation was verified with actual test data [16]. Moreover, based on the finite element numerical simulation method and the fatigue life research mechanism, some researchers have carried out stiffness verification and fatigue life predictions for the frames of mining dump trucks, and they have studied and analyzed the cracking causes, dynamic response, and structural stiffness of mining dump truck frames. In view of the strength and service life of mining dump truck frames, based on finite element analysis, dynamic response testing, vehicle bench testing, fatigue life prediction, etc., a relatively complete research framework for the failure analysis of mining dump truck frames has been proposed [17; 18; 19; 20; 21]. [PERSON] et al. conducted a fatigue life prediction study on the frame of a 220 t mining dump truck in a domestic heavy industry enterprise, which was mainly realized through the joint simulation of a multi-body dynamics model and a finite element model. The output load spectrum of the dynamic model was used as the input of the finite element model, and it was combined with a bench experiment to verify the accuracy of the simulation calculation [22]. [PERSON] et al.