Mining Truck Research Articles

Research analysis on the airflow-particle migration and dust disaster impact scope by the moving mining truck in the open-pit mine

For the purpose of evaluating the dust disaster impact scenario in the open-pit mine, a full-scale physical model of the 730E Komatsu heavy mining truck has been constructed and simulated in the ANSYS Fluent software with the refined wheel tire cannelure structure. The results show that the wind velocity poses a stationary-fluctuation-recovery sector along the longitudinal. A clockwise ellipse separation vortex shapes at the chamber hopper and two symmetrical trailing vortexes arise behind the mining truck. The dust exhibits a saddle shape distribution in the lateral section and shows a gradual sedimentation in the longitudinal, while the percentage of ultrafine dust increases from 26.5% to 46.3%. The minimum safety distance 45 m is feasible to avoid the dust disaster impact from mining truck. The dust disaster impact area presents a linear decrease along the longitudinal direction. It displays an initial increase and later decrease as the vertical height rises. The dust disaster impact scope delineation derived from the moving mining truck has a vital scientific practical significance for ensuring the personnel health security and defining the dust precise prevention priority, which contributes to improving the occupational health level in the open-pit mine.

Optimization Design of Double Wishbone Front Suspension Parameters for Large Mining Dump Truck and Analysis of Ride Comfort

With the advancement of technology, mining trucks are gradually becoming larger, imposing higher performance requirements on the front suspension. There is a need to transform the original integral non-independent front axle of mining dump trucks with a payload exceeding 300 tons into an independent front suspension with a double-wishbone suspension. The changing of the front suspension is bound to have an impact on the overall vehicle’s handling stability and ride comfort. Therefore, the following research is conducted to investigate and analyze these effects. Firstly, the paper proposes a method for optimizing the parameters of the double-wishbone front suspension. The double-wishbone front suspension is modeled, and a comparison with a kinematic model is conducted to validate the accuracy of the model. Secondly, unreasonable hardpoint parameters are optimized. Thirdly, a dynamic model of the entire vehicle is established based on the optimized parameters, and an analysis of handling stability and ride comfort for the entire vehicle is performed. Finally, simulation results are compared and analyzed against experimental data. The results indicate that the optimized positioning parameters not only effectively enhance the suspension performance of the mining dump truck but also meet the requirements for handling stability and smoothness. The overall smoothness of the vehicle is significantly improved after the modification. This study not only holds significant engineering value in reducing vibrations in dump trucks and enhancing driver comfort, but also provides theoretical support for subsequent research and development in the industry.

Bayesian network approach for reliability analysis of mining trucks

Having a safe and efficient system for mineral transportation is a top priority for all mining operations. Trucks are the most widely used material transportation systems that are applied in both surface and underground mines. Any truck failure disrupts the mineral transportation process and consequently decreases the overall output. Therefore, the reliability analysis of such equipment plays a critical role in increasing the efficiency and productivity of a mining operation. This paper proposes a novel method for analyzing the reliability of a fleet of mining trucks based on the Bayesian Network modeling. Considering the reliability block diagram, the fault tree of trucks was developed according to the logical relationship between the units. Then, a dynamic Bayesian network was constructed according to the conditional probability analysis. Moreover, the relative contributions of each truck’s component to the occurrence of the fleet failure were studied by using critical analysis. The results of this paper show that the successful operation of the fleet of trucks is most sensitive to truck no. 5, which has the highest reliability level in all time intervals. The reliability of the fleet of trucks reaches 0.881 at 20 h, and the fuel injection system of the truck’s engine is the main leading cause of the trucks failure. A proper preventive maintenance strategy should be paid more attention to improve the reliability and availability of the engine system.

Energy and exergy assessment of heavy-duty mining trucks. Discussion of saving opportunities

Heavy-duty mining trucks are essential for open-pit mining and are significant energy consumers, stressing the need for the mining industry to improve the fuel economy of mining trucks. However, there is a limited discussion on this topic in the specialized literature, mainly focusing on light-duty vehicles. This article discusses the energy and exergy balances of heavy-duty mining trucks operating in an open pit mine in Colombia. Results show saving opportunities by either using batteries or producing hydrogen with the power from regenerative brakes, reducing heat losses in the engine, recovering heat losses with combustion gases using thermoelectric generators, and replacing mechanical pumps with electrical pumps. The assessment shows that reducing engine heat losses by coating the cylinder, cylinder head, and piston crown can reduce fuel consumption between 1.8 % and 9.1 %. Moreover, the production of hydrogen, while economically feasible, needs to assess the implementation of electrolyzers in mining trucks. Other measures are not economically viable. Using batteries, which requires adding 12 t of weight to the truck, reduces truck productivity. Finally, using thermoelectric generators and replacing mechanical pumps shows marginal opportunities to reduce fuel consumption.

FusionPlanner: A multi-task motion planner for mining trucks via multi-sensor fusion

In recent years, significant achievements have been made in motion planning for intelligent vehicles. However, as a typical unstructured environment, open-pit mining attracts limited attention due to its complex operational conditions and adverse environmental factors. A comprehensive paradigm for unmanned transportation in open-pit mines is proposed in this research. Firstly, we propose a multi-task motion planning algorithm, called FusionPlanner, for autonomous mining trucks by the multi-sensor fusion method to adapt both lateral and longitudinal control tasks for unmanned transportation. Then, we develop a novel benchmark called MiningNav, which offers three validation approaches to evaluate the trustworthiness and robustness of well-trained algorithms in transportation roads of open-pit mines. Finally, we introduce the Parallel Mining Simulator (PMS), a new high-fidelity simulator specifically designed for open-pit mining scenarios. PMS enables the users to manage and control open-pit mine transportation from both the single-truck control and multi-truck scheduling perspectives. The performance of FusionPlanner is tested by MiningNav in PMS, and the empirical results demonstrate a significant reduction in the number of collisions and takeovers of our planner. We anticipate our unmanned transportation paradigm will bring mining trucks one step closer to trustworthiness and robustness in continuous round-the-clock unmanned transportation.

Investigation of regenerative braking for the electric mining truck based on fuzzy control

Investigation of regenerative braking for the electric mining truck based on fuzzy control

Field Measurement of Dust Concentration on Open-pit Coal Mine Truck Transportation Roads and Numerical Simulation of Dust Patterns

Dust generated by open-pit coal truck transportation is one of the main sources of pollution, adversely affecting road visibility and the surrounding air quality during transportation operations. To investigate the distribution patterns of transport dust on coal quality roads in open-pit coal mines, we conducted on-site measurements of transport dust pollution in a coal mine in Xinjiang, China. We also used numerical simulation software to simulate the distribution patterns of dust under different truck speeds. The results indicate that dust pollution on the coal quality road surfaces within the open-pit coal mine exceeds national standards. The concentration of dust behind the trucks at different speeds can be categorized into the following zones: vortex zone, rapid descent zone, and stable zone. The peak dust concentration occurs around 1.5 meters behind the rear of the trucks. Furthermore, the dust concentration behind the trucks follows an exponential decay pattern with increasing height and longitudinal distance.

Increasing technological sovereignty in dump trucks production facing economic sanctions

The article reflects the results of R&D on the design of a Jupiter mining truck with a lifting capacity of 240 tons. Increasing the unit load capacity is a fundamental factor of economic efficiency, as it ensures a reduction in costs, despite the high cost. This is precisely the path taken by foreign companies engaged in open-pit mining. At the same time, the pressure of sanctions from unfriendly countries limits the import of quarry equipment in all its segments. An analysis of the state of the Russian market for mining dump trucks and the state of the domestic automotive industry for the production of heavy mining dump trucks is provided.

Определение пожарной опасности большегрузных карьерных транспортных средств

Purpose. Heavy wheel-load mining trucks present a fire hazard. A key distinction from other vehicles, aside from their large size, is the presence of significant volumes (over 3 000 liters) of flammable lubricants and other operating fluids, as well as inaccessible areas in the event of a fire. Based on statistical data on fire locations and combustible materials, this article identifies the main sources of fire hazards in heavy wheel-load mining trucks, using a haul truck as an example. Methods. The study employed the following theoretical methods: analysis, modeling, and deduction. Findings. The analysis of statistical data on fire locations and combustible materials in heavy wheel-load mining trucks revealed that such equipment generates a significant amount of thermal energy and contains large amounts of flammable materials. The study identified the main fire-prone mechanisms and components, which are crucial for further evaluating the effectiveness of automatic fire suppression systems used in this type of trucks. Research application field. The results of this study provide basis for approaches to ensuring fire safety of heavy wheel-load mining trucks. Conclusions. The study identified potential sources of ignition in heavy wheel-load mining trucks. Further research on comprehensive protection measures for heavy wheel-load mining trucks will lead to new integrated design solutions to protect mining equipment from fire, prevent direct and indirect material damage, and reduce the risk of injury or death.

Scheduling optimization of underground mine trackless transportation based on improved estimation of distribution algorithm

The trend in underground mine development is trackless transportation, and the scheduling optimization of underground mine trackless transportation is a current research hotspot. This paper proposes a truck scheduling optimization method for underground mine trackless transportation based on an improved estimation of distribution algorithm to address the truck scheduling problem in the underground mine trackless transportation process. The transportation process of transport trucks in underground mines is analyzed. The dispatching model of transport trucks in underground mines is constructed based on the requirements of reducing transportation costs and increasing transportation efficiencies, taking into account the truck meeting situation in the ramp section and minimizing the total shift transportation distance and the total waiting time of transport trucks as the objective functions. The improved estimation of distribution algorithm is used to solve the truck scheduling model, resulting in the optimal ore blending and scheduling schemes. The comparative analysis employs a genetic algorithm, particle swarm optimization algorithm, and immune algorithm. The results demonstrate that, compared to other algorithms, the improved estimation of distribution algorithm proposed in this paper has superior performance in terms of convergence speed and the search for the optimal solution. The total number of transportation tasks associated with the optimal ore allocation scheme is at least 82, and the waiting time associated with the optimal scheduling scheme is reduced to 7.5 min. The operation time chart of transport trucks calculated by the optimal dispatching scheme can clearly depict the location of each transport truck at any time during a shift's working time, which has significant guiding significance for the actual truck transportation in the mine.

Performance Analysis of Permanent Magnet Synchronous Motor for Mining Applications – A Review

The features of Permanent Magnet Synchronous Motor (PMSM) makes it suitable for mining applications such as copper mining, mining floating machine, mining scraper conveyor, mine integrated machine, mining vacuum circuit breaker, mineral extraction in mines, coal mine belt conveyor system, mining truck and many more. This study focuses on performance analysis of permanent magnet synchronous motor for mining applications and performance analysis is the confirmation and analysis of parameters, various losses and efficiency at various loads. A comparative analysis of wound rotor synchronous motor, induction motor and permanent magnet synchronous motor confirmed the suitability of PMSM for various mining applications. Advanced technology of artificial intelligence integrated with permanent magnet synchronous motor also enhances the effectiveness and precision of the system.

Fault Diagnosis of Mine Truck Hub Drive System Based on LMD Multi-Component Sample Entropy Fusion and LS-SVM

As the main transportation equipment in ore mining, the wheel drive system of mining trucks plays a crucial role in the transportation capacity of mining trucks. The internal components of the hub drive system are mainly composed of bearings, gears, etc. The vibration signals caused during operation are nonlinear and nonstationary complex signals, and there may be more than one factor that causes faults, which causes certain difficulties for the fault diagnosis of the hub drive system. A fault diagnosis method based on local mean decomposition (LMD) multi-component sample entropy fusion and LS-SVM is proposed to address this issue. Firstly, the LMD method is used to decompose the vibration signals in different states to obtain a finite number of PF components. Then, based on the typical correlation analysis method, the distribution characteristics and correlation coefficients of vibration signals in the frequency domain under different states are calculated, and effective PF multi-component sample entropy features are constructed. Finally, the LS-SVM multi-fault classifier is used to train and test the extracted multi-component sample entropy features to verify the effectiveness of the method. The experimental results show that, even in small-sample data, the LMD multi-component sample entropy fusion and LS-SVM method can accurately extract fault features of vibration signals and complete classification, achieving fault diagnosis of wheel drive systems.

Comparative analysis of a mining truck motor with permanent magnets in a rotor and a synchronous homopolar motor without magnets in a drive

The relevance. Increasing need for using mining trucks with a diesel-electric (hybrid) drive for development of minerals. Improving operational and cost characteristics of the electric drive of mining trucks helps to reduce costs in the development of minerals. The main aim. To compare theoretically the performance of synchronous traction motors of various designs (a conventional design with permanent magnets inside a rotor and a homopolar design without permanent magnets with an excitation winding on a stator), optimized by the same method, in the drive of a mining truck. To optimize the motor design to reduce power loss and required inverter power, as well as to limit torque ripple and reduce the risk of permanent magnet demagnetization. Objects. Design of twelve-pole nine-phase synchronous AC motors with a rated power of 370 kW of various designs: a homopolar motor without permanent magnets with an excitation winding on the stator and a motor of a traditional design with permanent magnets in the rotor. Methods. Derivative-free optimization method; equivalent circuit method; mathematical modeling; two-dimensional finite element method. Results. Based on the analysis, the advantages and disadvantages of the considered motors were revealed. The advantage of the motor with permanent magnets in the rotor is reduction in active part length by 30 %. The advantage of the homopolar motor with an excitation winding on the stator are 4.6 times lower cost of active materials. In addition, the homopolar motor has a more reliable design, without the risk of overheating, demagnetization or deterioration of the properties of permanent magnets over time

The Development of Ackerman Steering System For 1/10<sup>th</sup> Scale Autonomous Mining Shuttle Design

The usage of Autonomous mining vehicles at mining sites leads to remarkable improvement in the mining industry with efficient truck hauling, safety, and driving assistance. The steering mechanism is one major component of mining shuttle anatomy design. A significant share of failure in safety measures of the mining shuttle is due to steering imbalance. Steering stability is one of the key components of any mining truck design specifically in the recent emerging technology of intelligent transportation systems such as autonomous truck haul. The earlier steering mechanisms for the heavy truck such as the Davis steering mechanism and other steering mechanisms available in both sliding and turning pairs will be present in the front wheel axle which has less stability of tires in a curved path. To overcome the problem, this paper proposes the design of an enhanced Ackermann steering system to meet the stability, control, and other steering capability of mining trucks by turning the front wheels at different angles. This paper also discusses the methodology to implement the designed principles using 1/10th scale of an original vehicle prototype built using STM 32 microcontroller by 3D printing, whose movement is controlled with Remote Control (RC). Hence the designed prototype model prototype with its innovative gear system provides mobility to the mining shuttle without loss in energy due to friction leading to fuel efficient, safe, stable intelligent transport system with green technology.

Stochastic Models and Processing Probabilistic Data for Solving the Problem of Improving the Electric Freight Transport Reliability

Improving the productivity and reliability of mining infrastructure is an important task contributing to the mining performance enhancement of any enterprise. Open-pit dump trucks that move rock masses from the mining site to unloading points are an important part of the infrastructure of coal mines, and they are the main transport unit used in the technological cycle during open-pit mining. The failure of any of the mining truck systems causes unscheduled downtime and leads to significant economic losses, which are associated with the need to immediately restore the working state and lost profits due to decreased site productivity and a disruption of the production cycle. Therefore, minimizing the number and duration of unscheduled repairs is a necessity. The most time-consuming operations are the replacement of the diesel engine, traction generator, and traction motors, which requires additional disassembly of the dump truck equipment; therefore, special reliability requirements are imposed on these units. In this article, a mathematical model intended for processing the statistical data was developed to determine the reliability indicators of the brush collector assembly and the residual life of brushes of electric motors, which, unlike existing models, allow the determination of the refined life of the brushes based on the limiting height of their wear. A method to predict the residual life of an electric brush of a DC electric motor is presented, containing a list of controlled reliability indicators that are part of the mathematical model. Using the proposed mathematical model, the reliability of the brush-collector assembly, the minimum height of the brush during operation, and the average rate of its wear were studied and calculated.

Productivity estimation of battery trolley mining truck fleets

ABSTRACT The mining sector is facing an immediate challenge to reduce its carbon emissions. The movement of material with mining truck fleets is a critical factor in reducing emissions. As the industry gradually replaces diesel trucks with more environmentally friendly transportation systems, it is important to analyse new solutions. This paper presents a new type of mining truck fleet called the Battery Trolley system, which is a combination of advanced technologies, including a battery-electric drivetrain, autonomy, trolley assist, and energy recovery systems. Depending on the site-specific differences and technology adoptions, decision-makers have three Battery Trolley system configurations to choose from: dynamic charging, stationary charging, and dual trolley Battery Trolley systems, each of which has its own advantages and disadvantages. One of the challenges of using Battery Trolley systems is their capacity and productivity. This study uses open-accessible project parameters and databases, with engineering assumptions, to create a mining scenario for both the dynamic charging and stationary charging perspectives. The study provides an equation to evaluate the Battery Trolley system’s mining productivity. Results show an incremental analysis of the Battery Trolley productivity as the trolley power increases from 8 MW to 32 MW in various Battery Trolley configurations. The study compares the Battery Trolley productivity for several open-pit mining applications, including copper, iron, and overburden waste. The results indicate that: (i) trolley power limitations significantly affect the capacity of Battery Trolley systems; (ii) a stationary charging option can achieve higher capacity and productivity than dynamic charging; (iii) Battery Trolley productivity varies in different applications under the given simulation assumptions.

Research on the Comprehensive Evaluation Method of Driving Behavior of Mining Truck Drivers in an Open-Pit Mine

Trucking is an important production link in most open-pit mines, and its transportation cost accounts for more than 50% of the total production cost of open-pit mines. The quality of the driver’s driving behavior plays a crucial role in the fine control of the production cost of transportation. Different from the previous evaluation studies of drivers’ driving behavior in open-pit mines, which mainly took safety driving behavior index as a factor variable, this paper puts forward a comprehensive evaluation method of driving behavior of mining truck drivers, which takes both safety driving and transportation cost as factor variables. Taking the mining truck as the research object, firstly, a scientific and reasonable data collection scheme is established, and the data information characterizing the transport state of the mining truck is obtained through data collection and analysis. Secondly, the RKNN algorithm of time series prediction and the wavelet analysis method are used to achieve noise reduction and missing processing of the original data so as to obtain accurate sample data. Then, taking the principal component analysis method as the entry point, through constructing the principal component analysis theory model, the key index system representing safe driving behavior and transportation cost is established to realize the comprehensive evaluation of the driving behavior of mining truck drivers, and the evaluation system of “standard driving”, “prudent driving” and “aggressive driving” of mining truck drivers is formulated. The results show that after noise reduction, the accuracy of mining car operation data can be improved by 7~12%, and the transportation cost can be reduced by about 5% after the driver’s operation behavior is standardized.

Lithium titanate battery system enables hybrid electric heavy-duty vehicles

Electrification plays an important role in the transformation of the global vehicle industry. Targeting the rapidly growing heavy-duty off-highway vehicles, we developed a battery system for hybrid-electric heavy-duty trucks based on lithium titanium oxide (LTO) batteries. With LTO as the anode and nickel manganese cobalt (NCM) as the cathode, comprehensive measurements of the battery cells and modules indicate that LTO batteries are uniquely suitable for applications requiring high-rate fast charging and discharging. An LTO battery system was constructed and implemented to realize the first advanced lithium-ion battery-based hybrid-electric heavy-duty vehicle, a hybrid-electric mining truck with vehicle mass 34 ton and maximum load 60 ton. Field operation tests of the hybrid-electric vehicle suggest that the performance of the LTO battery system meet the design expectations. After analyzing operation parameters of the hybrid-electric heavy-duty vehicle, we found 54.9 % fuel savings compared to conventional diesel-powered truck of the same mass and load.

Decoupled Real-Time Trajectory Planning for Multiple Autonomous Mining Trucks in Unloading Areas

Decoupled Real-Time Trajectory Planning for Multiple Autonomous Mining Trucks in Unloading Areas

Comparative life cycle assessment of battery-electric and diesel underground mining trucks

The mining sector is currently confronted with an energy market and evolving regulatory landscape that exerts pressure on the industry to consistently enhance its strategies and decision-making in support of sustainable practices. Traditionally, the ore is transported using heavy-duty trucks powered by diesel engines which have been identified as a primary contributor to environmental degradation. An emerging and technologically advanced solution of considerable interest is the implementation of battery-electric trucks, which still generates some uncertainty about its actual impact on the environment. The primary hypothesis under investigation is that battery-electric vehicles have significantly lower environmental impacts than conventional combustion vehicles. Thorough research is needed to bridge this knowledge gap and robustly understand the environmental effects of these technologies in the mining context. This study uses Life Cycle Assessment to evaluate the potential environmental impacts of battery-electric trucks compared to diesel trucks in a theoretical underground mine. The study analyses the environmental impacts around three main stages: the raw material supply for the manufacture of the vehicles, the energy supply (electricity or diesel fuel), and other indirect impacts associated with the operation of both types of trucks. The characterization methodology used is the ReCiPe2016 Midpoint (Hierarchical) using open-access software OpenLCA v1.10.3 for the impact assessment. The functional unit selected is one ton of material transported over 1 km. Our results for the baseline Chilean scenario indicate that diesel trucks have a considerably greater environmental impact in two of the five categories studied: global warming potential and stratospheric ozone depletion. The energy supply is the ‘hotspot’ for the electric truck life cycle, while the diesel truck life cycle has the operation and the energy supply as the main environmental impact sources due to the upstream and direct emissions associated with diesel supply and combustion, respectively. However, when considering particulate matter formation and water consumption, electric trucks exhibit higher impacts due to the technologies employed for generating the electricity used to charge their batteries. Furthermore, the environmental profile of the electric truck improves considerably when renewable sources of electricity substantially substitute coal in the electricity mix, as projected in the Chilean policy context. The main novelty of this study is that it is the first initiative comparing a battery-electric truck with a diesel truck considering an approach to the underground operation reality for the mining sector.