Haul Trucks Research Articles

Emission Factors of a Euro VI Heavy-duty Diesel Refuse Collection Vehicle

Modern (Euro VI) heavy-duty vehicles have significantly lower pollutant emissions than older vehicles. However, there are still concerns regarding the emissions of refuse collection vehicles in cities, because in some cases they may use engines designed for long haulage trucks. For this reason, we tested a diesel Euro VI (step C) refuse collection heavy-duty vehicle, both in the laboratory on a chassis dynamometer and on the road, similar to the regulated in-service conformity cycle, but also with actual refuse collection cycles. Particle number (PN) and gaseous pollutants (NOx, CO, HC) were measured using a Portable Emissions Measurement System (PEMS). Additionally, in the laboratory we used laboratory grade gaseous, particle number, and FTIR (Fourier-transform infrared spectroscopy) systems to assess the PEMS. For short periods, where the exhaust gas temperature was low for the aftertreatment devices (cold start, some city conditions), the NOx emissions reached 2000 mg/km. Nevertheless, all pollutants were well below the applicable emissions limits expressed in mg/kWh for all cycles examined (in brackets the ratio to the laboratory limit): NOx < 400 mg/kWh (0.87), CO < 850 mg/kWh (0.21), HC < 12 mg/kWh (0.08), PN < 2.4×1010 p/kWh (0.04). To make sure that this will always be the case, future heavy-duty type approval emissions regulations should specifically consider the urban conditions for municipality vehicles, such as refuse trucks.

Development of an Underground Haulage System Evaluation Tool for Feasibility Studies

The mining industry faces many difficult challenges, for example, lower ore grades, smaller and deeper deposits, and longer transportation distances. In the past, there have been remarkable innovations in both equipment and the types of mining methods for which it is used, which have resulted in economies of scale. This has led to an increased use of bulk mining methods, like sublevel and block caving, which has increased productivity and reduced costs. Haulage alone plays a major role. Current haulage techniques are a significant cost driver, which account for between 15 and 30% of the overall capital investment (capex) in a mine and are an increasingly part of the operating costs (opex). The paper introduces a simulation tool of main haulage system in underground mining. Therefore, performances and the costs of the three most common underground main haulage systems, rail, truck, and conveyor, are calculated using a developed modeling tool. The tool was applied and validated in a case study carried out with the LKAB Kiruna Mine in northern Sweden.

Hub relay network design for daily driver routes

Hub-based relay networks for long haul trucking offer an opportunity to improve the work–life balance of drivers while simultaneously supporting faster delivery through near-continuous flow of containers from source to destination. In this paper, we develop a model for deciding hub location and sizing along with the routing of loads. Costs of hub construction and operation, transportation and penalties for multi-day driver trips are included. Both deterministic and two-stage stochastic programming models have been formulated in this paper. The goal is to determine the optimal hub and route decisions so that overall cost is minimised. A case study on the highway network for the Western United States demonstrates the computational tractability of the approach along with the importance of considering demand uncertainty.

Energy consumption in mine haulage due to road pavement performance

ABSTRACTMine haul road pavements are often designed with informal methods. This approach means the energy consumption in haulage is not quantified and so pavement operating costs are not able to be defined. The energy consumption of haul trucks operating on unbound and cementitiously modified haul road pavement basecourse and wearing courses were estimated with variable traffic, climate and maintenance inputs. Energy consumption estimates showed that significant benefits may arise through the use of superior gravels that contain a suitable fines content with low to medium plasticity in the pavement wearing course. Similarly, it was shown that the pavement structural class significantly impacts haul truck energy consumption. Structural class is determined by pavement design and may be improved by increasing the pavement depth or utilizing stiffer materials. Estimating the energy consumption of haul trucks as part of the pavement design process would allow optimization of capital and operating costs over the life of a haul road.

Improving the Environmental Performance of a Copper Mine Site in Indonesia by Implementing Potential Greenhouse Gas Emissions Reduction Activities

Indonesia has targeted 29 % Greenhouse gas (GHG) emissions reduction in 2030 and Industry is one of the big two contributors for GHG emissions. As an industry, mining is an energy-intensive industry, and reducing energy consumption is one of the strategies to improve mining environmental performance. The aim of this paper is to estimate the GHG emission reduction in a mining project through energy reduction initiatives. A copper mine in Indonesia with processing plant capacity of 120,000 t/d and operate 111 Caterpillar 793C Haul Truck was taken as a case study. This mine site has two sources of an electricity namely coal-fired power plant with 112 MW output and diesel power plant with 45 MW output. The analysis method for calculating CO2 emission is using IPCC method where fuel consumption and emission factor are two main variables for GHG emissions. Business as usual scenario (TIER 1) showed that the average of diesel fuel consumption for fleets operation generated 294,006 t CO2-eq/y. A coal-fired power plant with average coal consumption of 350 t/d/unit generated 1.15 Mt CO2-eq/y and diesel power plant consumed 4.35 ML/y produced 11,632 t CO2-eq/y. Two energy initiative programs were identified namely fuel conversion and used oil utilisation program. The initiative scenario focused on substituting, reducing and reusing of fossil fuels including coal, diesel fuel, and used oil. This scenario was estimated to contribute the carbon emission reduction (t CO2-eq) of 258,381 annually. The involvement of mining industry in carbon emission reduction is not only helping Indonesia in achieving its GHG emissions reduction target but also increases mine site environmental performance and company image.

In-pit crushing and conveying technology in open-pit mining operations: a literature review and research agenda

ABSTRACTIn-Pit Crushing and Conveying (IPCC) systems are receiving more attention today due to current characteristics of open-pit mining operations and what is expected to occur in the future. Today, it has become more necessary than ever to reduce the cost of truck haulage, which accounts for roughly half the operating costs of mining operation. Trucking costs can be significantly reduced by bringing the crushers inside the pits. The present paper aims to provide a comprehensive literature review of all aspects of technical, economic and sustainable development of in-pit crushing systems along with a statistical analysis of the systems since 1956 to the present. The paper also presents the scope of future research and examines defects and flaws in the design and planning tasks that limit the IPCC system’s applications. Transition time from a pure-truck system to an alternative IPCC system, necessity of integration of production plan and IPCC plan, ultimate pit limit for fully mobile systems, capacity optimization, IPCC’s plan for waste material and optimum conveyor exit scheme are introduced as the main open problems that are worthy of future study.

Prospects for the Use of Liquefied Natural Gas as a Motor Fuel for Haul Trucks

The state-of-the-art of efficiency and relevance of the use of liquefied natural gas as a motor fuel for truck operation is considered. A brief analysis of economic and environmental benefits of using liquefied natural gas as a motor fuel is conducted. It is noted that liquefied natural gas seems to be the most promising alternative to oil fuels for high-payload-capacity haul trucks. It is affirmed that for the first time in Russia, in Kuzbass, OOO “Siber-Energo” successfully implemented an integrated project for the production of liquefied natural gas and its consumption in relation to high-payload-capacity BelAZ haul trucks. The data on the assessment of the energy intensity of the process of rock mass hauling by high-payload-capacity BelAZ 75131 haul trucks equipped with on-board cryogenic fuel system are presented. The data show that the energy intensity of the process of rock mass hauling by dual-fuel (gas-diesel) haul trucks is much less than that of diesel-powered haul trucks. It is said that, according to the energy criterion for evaluating the operation, it is more efficient to use haul trucks running on gas-diesel mixture.

Procedure for Haul Truck On-Board LNG Fuel Systems Performance Evaluation

The state-of-the-art of the advantages of using liquefied natural gas as a motor fuel for haul trucks instead of oil motor fuel is considered. It is noted that the energy intensity of the process of rock mass hauling by dual-fuel (gas-diesel) haul trucks is less than that of haul trucks running on diesel only. It is argued that the most promising in relation to heavy-duty mining trucks, is the conversion of diesel engines to gas-diesel operation. The universal integrated procedure for evaluating currently used haul truck on-board cryogenic fuel systems performance is presented. The method of evaluating the “rate of replacement” of diesel fuel with liquefied natural gas, when operating haul trucks equipped with on-board cryogenic fuel systems, is described in detail. The possible sequence of per-cycle, per-ingle-shift and per-day monitoring of the rate of diesel fuel replacement with liquefied natural gas is presented. The method for evaluating the economic efficiency of the operation of high-payload-capacity haul trucks conversed to gas-diesel operation is given, which allows, among other things, determining the actual service life of on-board cryogenic fuel systems and their time to failure.

Analysing human effect on the reliability of mining equipment

In the mineral industries, the heavy equipment is widely used, and the operator performance is a significant factor for fulfilling intended functions of this equipment. This study aims to analyse and interpret the effect of the human factor on the reliability of the equipment used in the mining industry. In doing so, a combined approach based on the reliability analysis, statistical inference and a machine learning technique is proposed. A case study was conducted on haul trucks in a mining operation. The case study showed that the reliability drops of haul trucks vary in the range of 0.84% and 2.45% in a shift. It was also calculated that 16.9% of these reliability drops were associated with operator habits. A truck's condition at the beginning of a shift and the initial reliability contribute to 36.3% and 31.1% of the reliability drops, respectively. The findings can be used in scheduling training programs, short-term mine planning, and simulation of material handling systems.

Analysing human effect on the reliability of mining equipment

In the mineral industries, the heavy equipment is widely used, and the operator performance is a significant factor for fulfilling intended functions of this equipment. This study aims to analyse and interpret the effect of the human factor on the reliability of the equipment used in the mining industry. In doing so, a combined approach based on the reliability analysis, statistical inference and a machine learning technique is proposed. A case study was conducted on haul trucks in a mining operation. The case study showed that the reliability drops of haul trucks vary in the range of 0.84% and 2.45% in a shift. It was also calculated that 16.9% of these reliability drops were associated with operator habits. A truck's condition at the beginning of a shift and the initial reliability contribute to 36.3% and 31.1% of the reliability drops, respectively. The findings can be used in scheduling training programs, short-term mine planning, and simulation of material handling systems.

Determining the optimal orientation of ultimate pits for mines using fully mobile in-pit crushing and conveying systems

Ultimate pit limit determination provides the outline of the optimal pit for use in the mine design process. Ultimate pit limit determination for truck and shovel haulage systems can be completed with proven mathematical optimality. For fully mobile in-pit crushing and conveying systems, a new ultimate pit limit determination method must be developed that includes the additional constraints of a straight wall for the pit exit conveyor and regularly flat pit floors. One of the major steps in the new method is determining the orientation of the straight wall. A proposed method of achieving this using the mathematical concepts of convex hulls and bounding boxes is presented, with an explanation as to how it could be implemented in an ultimate pit limit determination algorithm. This method allows the determination of ultimate pit limits for fully mobile in-pit crushing and conveying with a straight wall oriented to provide the most value to the project.

Fractal Dimension and Power Spectrum of Electroencephalography Signals of Sleep Inertia State

Human brain functions and behaviors during the transition state between sleep and wakefulness are not similar to these at alert wakefulness state. The transition state, which is called sleep inertia, has many unpleasant and dangerous effects on many situations that require full attention and fast response, such as driving. Within 30 minutes after waking up from sleep, the driver’s performance might be impaired due to the sleep inertia effects. Groups of drivers that may drive within a short period after waking up are: workers who travel early in the morning; secondary drivers of long distance bus who sleep in the bus before taking over the job from the primary drivers; night travelers; and long haul truck drivers who stop at the rest area to sleep for a while and continue driving. Previous research used subjective self-report measurement, eye tracker, and a driving simulator to analyze the driver’s performance during sleep inertia state. The physiological measures of the drivers, such as their brain signals have also been studied. However, the brain signals which are recorded in Electroencephalography (EEG) are typically analyzed in perspective of the power spectrum. This study proposes a hybrid of EEG features, which are fractal dimension and power spectrum, supported by behavioral data which is the driver’s reaction time. This study finds the features that significantly differentiate between normal and sleep inertia drivers based on the classification accuracy and p-value of the statistical ANOVA. This study compares the results with other features (power spectrum, variance, sample entropy), and between EEG channel. This study record the EEG from the Fz, T7, Cz, Pz, and O1 channels. This study uses subjective and behavioral measurements to support the results. The results show that the hybrid of fractal dimension estimated by Katz’s algorithm at the O1 channel and delta power from the Fz channel, and alpha power from the O1 channel, have better classifications than the power spectrum alone. Furthermore, the reaction time recorded from the LED reaction time task shows a significant difference between drivers with sleep inertia and normal (alert) drivers.

Study on theory and methods of payload online estimation for cable shovels

Cable shovels are one of the most widely used machines in open-pit mining industry. Precise estimation of payload can effectively avoid overload and underload for each dump, significantly improve the working performance of cable shovels and reduce the maintenance costs of haul trucks. In this research, an algorithm based on static analysis for payload online estimation was established, which took hoist force, crowd force and geometrical parameters of the working device as input variables for the situation when both hoist and crowd motors were hovering during the digging process. More specifically, the torque balance function was applied for payload calculation on the basis of the kinematic model built for evaluating the length of different force arms when the dipper handle stayed in different positions. In order to verify the efficiency of the payload online estimation algorithm, six different working positions and four different fullness states of the dipper were chosen for testing. And a testing system consisting of a 1/35 scale model of cable shovel, software of LabVIEW, hardware of cRIO and multi-types of sensors was designed and set up. Testing results show that the relative error between the theoretically calculated value and the real weight of payload is averagely less than 6% when the dipper was 40% fully filled and averagely less than 3% when the fullness reached 100%, which has proved the efficiency of the payload online estimation theory and methods established in this research.

Optimal Speed and Gear Shift Control of Long-haulage Trucks

Abstract Long haulage trucks consume large amounts of fuel, and fuel savings are desired both from economical and environmental aspects. When the upcoming road topology is known, the speed and gear shifts can be optimized in order to minimize the fuel consumption by e.g. minimizing the braking of the truck. Three different optimal control approaches are evaluated and compared for the speed and gear shift optimization problem. The results are based on simulations, but two of the three evaluated solvers are also implemented on-board a truck using rapid prototyping to investigate the feasibility of such systems. The results indicate that optimal control of the speed reduces the fuel consumption more than finding the optimal gear shift trajectory. The overall optimization problem contains one discrete and one continuous state, which makes the selection of optimization method complex. A sequential optimization scheme where the optimal speed profile is found using linear programming and the optimal gear profile is found using dynamic programming shows similar results as using dynamic programming for the overall problem simultaneously. One drawback with this solution is robustness and several tuning parameters. The driveability of the solutions are found good at the performed on-board tests.

Development of Technical Requirements for On-Board Cryogenic Fuel Systems of Belaz Dump Trucks

The state-of-the-art of the issue of the efficiency and relevance of the use of liquefied natural gas (LNG) as a motor fuel in the operation of dump trucks is considered. An analysis of the benefits of using LNG as a motor fuel is given. It is noted that, LNG seems to be the most promising alternative to oil types of motor fuel in the segment of open-pit truck haulage. It is affirmed that in Russia, in Kuzbass, the group of companies successfully implemented for the first time an integrated project for the production of LNG and its consumption in relation to BelAZ dump trucks. Data on the relevance and the need to develop technical requirements for on-board cryogenic fuel systems of mine dump trucks are given. Data on the developed groups of technical requirements for on-board cryogenic fuel systems of BelAZ dump trucks are given. It is said that the developed technical requirements made it possible to solve a number of tasks related to the development of circuit and design solutions for equipping BelAZ dump trucks with cryogenic systems. It is argued that the developed technical requirements will contribute to the further development of domestic projects for the production and consumption of liquefied natural gas.

Ultimate pit limit determination for fully mobile in-pit crushing and conveying systems

Fully-mobile in-pit crushing and conveying systems have different pit shape requirements to traditional truck haulage systems due to linear bench and flat floor constraints imposed by conveyor systems. As the shape of a pit is largely based on the ultimate pit limit, it is desirable to have the additional shape requirements of fully mobile in-pit crushing and conveying systems included in the ultimate pit limit determination process. This paper discusses and highlights why there are different requirements for these systems, and what they are. A method of including these extra requirements during ultimate pit limit determination is presented. A case study has been included to show the method working, with scheduling of the pits to further highlight the viability of fully mobile in-pit crushing and conveying. This case study shows that through the reduced mining costs, a fully mobile in-pit crushing and conveying pit can return a higher net present value than the traditional truck and shovel pit for the same deposit. The development of this method provides the opportunity for the metalliferous industry to accurately determine ultimate pit limits for mines considering the use of fully mobile in-pit crushing and conveying systems.

Designing waste rock barriers by advanced numerical modelling

Design of waste rock barriers forming safety berms for haul trucks requires knowledge of complex interactions which cannot readily be tested by physical means. An advanced numerical model based on non-smooth multi-domain mechanics is presented together with model calibration using limited full-scale experimental data. Waste rock is represented by spherical particles with rolling resistance, and an ultra-class haul truck is represented by a rigid multibody system interconnected with mechanical joints. The model components are first calibrated and then the calibrated model is used for simulating various collision scenarios with different approach conditions and safety berm geometries. Numerical predictions indicate that the width of the berm is most critical for efficiently stopping a runaway truck. The model can also predict if a certain berm geometry is capable of stopping a runaway truck. Results are summarised in a series of diagrams intended for use as design guidelines by practitioners and engineers.

Potential of on-board energy recovery systems to reduce haulage costs over the life of a deep surface mine

ABSTRACTThe installation of energy recovery systems (ERSs) on-board diesel-electric mine haul trucks to capture energy when braking and re-inject stored energy on acceleration and ramp ascent, is proposed to reduce haul costs in surface mining. ERSs would add to equipment cost and reduce truck payload, reducing productivity and effectively increasing other haul-related costs. However, stored energy could reduce fuel consumption and could be used to reduce cycle time thereby improving productivity when conditions are favourable. This paper investigates how the installation of fixed size electro-mechanical flywheel (EMFW) or lithium iron phosphate (LiFePO4) based ERSs could affect the overall cost of truck haulage over the 20-year life of a metalliferous surface mine reaching 600 m deep. The simulation study suggests LiFePO4 technology can be expected to provide significantly greater haul cost reductions than the EMFW technology by reducing haul costs by 1.4–6.2% depending on the energy re-injection strategy employed.

Energy Saving Control Strategy for the High-Frequency Start-up Process for Electric Mining Haul Trucks

Electric mining haul trucks (EMHTs) used for “short distance” mining transportation undergo a high-frequency of start-ups which can be highly energy consuming. This paper proposes an energy saving control (ESC) strategy for the high-frequency start-up process of EMHTs. To design the ESC strategy, a system model is established based on the characteristics of the power transfer mechanism of the EMHT drive system. With this model, the ESC strategy is designed using optimal control theory. The Hamilton function is reconstructed and the Pontryagin minimum principle is used to formulate the ESC strategy by taking the energy consumption and the response time into account. Based on this strategy, an ESC-strategy-based control algorithm for EMHT is designed by selecting the switching time according to the system boundary condition. To verify the ESC strategy performance, the simulation model of dc drive 154t EMTH is built with MATLAB. Compared with the constant power control and the driver's manual control, the ESC strategy enjoys better dynamic performances and a lower energy consumption in the start-up process.

Big data analytics to identify illegal construction waste dumping: A Hong Kong study

Illegal dumping, referring to the intentional and criminal abandonment of waste in unauthorized areas, has long plagued governments and environmental agencies worldwide. Despite the tremendous resources spent to combat it, the surreptitious nature of illegal dumping indicates the extreme difficulty in its identification. In 2006, the Construction Waste Disposal Charging Scheme (CWDCS) was implemented, regulating that all construction waste must be disposed of at government waste facilities if not otherwise properly reused or recycled. While the CWDCS has significantly improved construction waste management in Hong Kong, it has also triggered illegal dumping problems. Inspired by the success of big data in combating urban crime, this paper aims to identify illegal dumping cases by mining a publicly available data set containing more than 9 million waste disposal records from 2011 to 2017. Using behavioral indicators and up-to-date big data analytics, possible drivers for illegal dumping (e.g., long queuing times) were identified. The analytical results also produced a list of 546 waste hauling trucks suspected of involvement in illegal dumping. This paper contributes to the understanding of illegal dumping behavior and joins the global research community in exploring the value of big data, particularly for combating urban crime. It also presents a three-step big data-enabled urban crime identification methodology comprising ‘Behavior characterization’, ‘Big data analytical model development’, and ‘Model training, calibration, and evaluation’.