The mining trucks with heavy loads are widely used in open‐pit mines, which are usually under working conditions where the recoverable potential energy accounts for more than 1/3 of the traction energy. Therefore, it is important to study the existing energy recovery technologies suitable for mining trucks. This work presents a comparative study on the economy of a mining truck by integrating four different energy storage systems (ESS): battery, supercapacitor, hydraulic accumulator, and air tank combining with the existing internal combustion engine to form a hybrid mining truck. First, recent applications and features of the four ESSs in vehicles are discussed. Next, the configurations of four types of partial hybrid mining trucks are presented. In addition, this project compares different configurations by the total benefit over 10 years of operation. The compressed‐air ESS with full capacity obtained the best benefit under medium and heavy load scenarios, which is more applicable to the actual situations. Therefore, it will be beneficial to turn the conventional electric‐driving mining truck into a compressed‐air hybrid.

This paper presents a novel model-based method for estimating the attitude of underground articulated vehicles (UAV). We selected the Load–Haul–Dump (LHD) vehicle as our application object, as it is a typical UAV. First, we established the involved models of the LHD vehicle, including a kinematic model, the linear and angular constraints of a center articulation model, and a dynamic four degrees-of-freedom (DOF) yaw model. Second, we designed a Kalman filter (KF) to integrate the kinematic and constraint models with the data from an inertial measurement unit (IMU), overcoming gyroscope drift and disturbances in external acceleration. In addition, we designed another KF to estimate the yaw based on the dynamic yaw model. The accuracy of the estimations was further enhanced by data fusion. Then, the proposed method was validated by a simulation and a field test under different dynamic conditions. The errors in the estimation of roll, pitch, and yaw were 3.8%, 2.4%, and 4.2%, respectively, in the field test. The estimated longitudinal acceleration was used to obtain the velocity of the LHD vehicle; the error was found to be 1.2%. A comparison of these results to those of other methods showed that the proposed method has high precision. The proposed model-based method will greatly benefit the location, navigation, and control of UAVs without any artificial infrastructure in a global positioning system (GPS)-free environment.

Owing to the harsh environment of underground mines, autonomous underground articulated vehicles (UAVs) with precise control and positioning system are particularly important. However, the ambiguity of steering characteristics hinders the development of UAVs. This study presents a model-based method to uncover the steering characteristics of a UAV. Firstly, a hybrid model of UAV was established, which included a dynamic model of articulated frames and a model of the hydraulic power steering system. Secondly, a field test of a typical UAV, a load-haul-dump (LHD) with 4 m³ capacity, was carried out. In order to verify the correctness of the established model and the accuracy of the involved parameters, the field test results were used to verify the dynamic model in time and frequency domains. Then, the steering characteristics of the UAV were uncovered based on the verified hybrid model, and the results showed that the increased load would increase ‘oversteering’ under the same articulation angle and that the error of trajectory exceeded 0.3 m. In addition, the deviations of trajectories between the two frames were revealed during the transient steering process, and the maximum deviation reached 0.21 m when the velocity was 2 m/s and the articulation angle was 15°. The comprehensive results indicate that the steering characteristics of UAVs cannot be ignored in regard to precise autonomous control and positioning.

Tire wear cost accounts for a large proportion of the total cost of heavy mining dump trucks (HMDTs), and the shimmy of the steering system aggravates the tire wear severely. This study proposes a model-based approach to avoid the shimmy of the steering system for such trucks without replacement or destruction of steering structure. First, a five degrees-of-freedom (DOF) shimmy dynamic model of the steering system is established considering the tire lateral dynamics and the nonlinearity of the hydro-pneumatic suspension (HPS). Second, the unstable parameter range of the dynamic model is obtained based on the Lyapunov’s first approximation theorem and Hopf bifurcation theory. The stability analysis results show that the steering system of heavy mining dump trucks is a self-excited vibration system because of the Hopf bifurcation in the unstable parameter range, and this unstable parameter range is greatly affected by the load and the initial pneumatic volume of hydro-pneumatic suspension. In addition, the accuracy of the dynamic is verified by a field test. Therefore, how the load and initial pneumatic volume affect the shimming is analyzed numerically. In other words, how to match the load and initial pneumatic volume is uncovered to avoid the shimmy. For instance, it shows that the shimmy at full load can be avoided at the speed of 30 km/h by charging the initial pneumatic volume of hydro-pneumatic suspension to 14.5 l.

The energy storage system of electric-drive heavy mining trucks takes on a critical significance in the characteristics including excellent load capacity, economy, and high efficiency. However, the existing battery-based system does not apply to harsh cold environments, which is the common working condition for the above trucks. A type of cycle hydro-pneumatic energy storage system for the trucks was proposed in this study. The dynamic model of the system, including the dynamic and thermodynamic models of hydraulic and pneumatic parts, was built to analyze the performance of the system. Subsequently, the thermodynamic characteristics were clarified during the energy storage and released through the real test condition-based simulation. The power and energy performances of the system were studied in practice based on the above characteristics. The analysis of the results showed that the system reduced 22.03% driving power at the optimal braking energy recovery rate, the energy density was nearly 12.6 MJ/m³, the maximum input power was higher than 230 kW, and the cycle efficiency was about 40.6%. The results of this study will be conducive to the application of the hydro-pneumatic energy storage system for the electric-drive mining trucks and reducing the resulting carbon emission.

As an important component of the automatic hydraulic quick coupling device (AHQCD) on rescue vehicles, the hydraulic quick couplings (HQCs) are used to rapidly dock hydraulic lines and transport fluid while changing and operating hydraulic working tools. However, during tool operation at rescue sites, pressure pulsations at multiple frequencies in the hydraulic lines can coincide with the natural frequencies of the HQCs, potentially causing resonance that severely affects the stability of fluid conveying and damages the connection of hydraulic lines accidentally. To investigate the natural frequencies of the HQCs with upstream and downstream lines, the characteristics of fluid–structure interaction were considered between the poppets and the fluid in this study, and an equivalent stiffness model of the fluid domain was derived based on the fluid compressibility. A dynamic model, along with 6-DOF equations for the system, was established, and the natural frequencies and mode vectors were determined by free vibration analysis. In addition, the effects of working pressure, air content, and stiffness of the springs on the natural frequency of the HQC system were analyzed. The results show the natural frequency increases with a higher working pressure and lower air content, while the effect of spring stiffness on natural frequencies varies with different modes. Furthermore, the proposed model is validated by experimental pressure signals, showing good agreement, with an average error of 2.7% for the first-order natural frequency. This paper presents a theoretical method for improving the stability of fluid transport when operating various hydraulic tools under complex rescue conditions.