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A range of axle suspensions, comprising hydro-pneumatic struts and diverse linkage configurations, have evolved in recent years for large size mining trucks to achieve improved ride and higher operating speeds. This paper presents a comprehensive analysis of different independent front suspension linkages that have been implemented in various off-road vehicles, including a composite linkage (CL), a candle (CA), a trailing arm (TA), and a double Wishbone (DW) suspension applied to a 190 tons mining truck. Four different suspension linkages are modeled in MapleSim platform to evaluate their kinematic properties. The relative kinematic properties of the suspensions are evaluated in terms of variations in the kingpin inclination, caster, camber, toe-in and horizontal wheel center displacements considering the motion of a hydro-pneumatic strut. The results revealed the CL and DW suspensions yield superior kinematic response characteristics compared to the CA and TA suspensions.

Intelligent autonomous articulated vehicles (IAAVs), the most important transportations of intelligent mining system, are the future direction of mining industry. Though it could realize the unmanned drive, without supports of hydraulic steering process analyses and vehicle dynamic researches, there are no references for the IAAVs to adjust the steering angle in certain driving error. It still has to check the signal from the angle sensor repeatedly to track the planned path in the working process, which lead to the low control accuracy. In this paper, the theories of hydraulic steering process and vehicle model will be developed for the vehicle intelligent control with the analyses of road and tire characteristics based on the principle of least resistance.

With high maneuverability and heavy-duty load capacity, articulated steer vehicles (ASV) are widely used in construction, forestry and mining sectors. However, the steering process of ASV is much different from wheeled steer vehicles and tractor-trailer vehicles. Unsuitable steering control in path following could easily give rise to the “snaking” behaviour, which greatly reduces the safety and stability of ASV. In order to achieve precise control for ASV, a novel path tracking control method is proposed by virtual terrain field (VTF) method. A virtual U-shaped terrain field is assumed to exist along the reference path. The virtual terrain altitude depends on the lateral error, heading error, preview distance and road curvature. If the vehicle deviates from the reference line, it will be pulled back to the lowest position under the influence of additional lateral tire forces which are caused by the virtual banked road.