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An energy-saving control strategy for wheel loaders is proposed in this paper to address the issue of high energy consumption during their operation. The strategy is based on the intelligent identification of working stages, allowing for staged power matching and resulting in reduced energy consumption. Each work stage of the loader is identified by matching it to the main pump pressure waveform and actuator pilot pressure waveform. Using a sliding time window method, pressure waveforms from each working stage are subjected to feature extraction. A bidirectional long short-term memory neural network (BILSTM) algorithm is then used to establish an intelligent recognition model. Based on work stage identification, an energy-saving control strategy based on power matching is proposed for the shoveling stage of the loader, and the Grey Wolf optimization (GWO)-PID algorithm is utilized for control parameter tuning. Finally, the effectiveness of the energy-saving control strategy based on work stage identification is verified through experiments. The research results indicate that the BILSTM recognition model outperforms other models with a recognition accuracy of 96.1%. The optimal time window width is 0.6 s, and the proposed energy-saving control strategy achieves a fuel-saving rate of 6.81%. This method provides feasibility for reducing energy consumption in construction machinery and achieving energy-saving and carbon-reduction goals. [ABSTRACT FROM AUTHOR]

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The traditional loader drive system is based on the hydraulic torque converter as the key component, and its gear is shifted through the coordination of the clutch and gearbox, which greatly increases power loss and operator fatigue. To address the above problem, a variable-structure hydrostatic drive system is proposed. This system adopts a closed-loop design and adjusts the displacement of the pump and dual motors to follow the throttle opening of the vehicle, achieving automatic gear shifting and smooth speed regulation. It can also automatically change the system structure according to the vehicle's speed, meeting the vehicle's demand for rapid switching output of high torque and high speed. At the same time, in the displacement matching control process, an adaptive sliding mode control scheme based on radial basis function neural network compensation is proposed. This scheme designs an adaptive hyperparameter update strategy according to the characteristics of the system to effectively compensate for changes in uncertain factors. Experimental results show that, compared to traditional drive systems, this system has the characteristics of simple operation, smooth speed regulation, and high fuel economy. [ABSTRACT FROM AUTHOR]

To improve the control performance and energy efficiency of the hydrostatic transmission (HST) system of wheel loaders, this study proposes a novel variable structure dual-motor hydrostatic transmission system, accompanied by a multivariable control strategy based on fuzzy sliding mode control. By constructing a simulation model of the transmission system, the performance of the novel transmission system is verified, and the control effects of common control strategies are compared. The simulation results show that the proposed control strategy and system have good matching and can adapt to disturbances actively. Field experiment results show that the proposed solution can achieve smooth automatic shifting of wheel loaders, while effectively adjusting system pressure, flow, and power. Compared with the traditional hydrodynamic torque converter loader transmission system, its transmission efficiency is effectively increased by 30%, and the efficiency is increased by 8% compared with the traditional hydrostatic transmission system This achievement is of great significance for improving the working efficiency of wheel loaders and reducing energy consumption. The future research focus is to further improve the multivariable control strategy, achieve intelligent operation, and improve the efficiency and reliability of the transmission system. [ABSTRACT FROM AUTHOR]

Abstract Fast and accurate measurement of the volume of earthmoving materials is of great significance for the real-time evaluation of loader operation efficiency and the realization of autonomous operation. Existing methods for volume measurement, such as total station-based methods, cannot measure the volume in real time, while the bucket-based method also has the disadvantage of poor universality. In this study, a fast estimation method for a loader’s shovel load volume by 3D reconstruction of material piles is proposed. First, a dense stereo matching method (QORB–MAPM) was proposed by integrating the improved quadtree ORB algorithm (QORB) and the maximum a posteriori probability model (MAPM), which achieves fast matching of feature points and dense 3D reconstruction of material piles. Second, the 3D point cloud model of the material piles before and after shoveling was registered and segmented to obtain the 3D point cloud model of the shoveling area, and the Alpha-shape algorithm of Delaunay triangulation was used to estimate the volume of the 3D point cloud model. Finally, a shovel loading volume measurement experiment was conducted under loose-soil working conditions. The results show that the shovel loading volume estimation method (QORB–MAPM VE) proposed in this study has higher estimation accuracy and less calculation time in volume estimation and bucket fill factor estimation, and it has significant theoretical research and engineering application value.

Fast and accurate measurement of the volume of earthmoving materials is of great significance for the real-time evaluation of loader operation efficiency and the realization of autonomous operation. Existing methods for volume measurement, such as total station-based methods, cannot measure the volume in real time, while the bucket-based method also has the disadvantage of poor universality. In this study, a fast estimation method for a loader's shovel load volume by 3D reconstruction of material piles is proposed. First, a dense stereo matching method (QORB–MAPM) was proposed by integrating the improved quadtree ORB algorithm (QORB) and the maximum a posteriori probability model (MAPM), which achieves fast matching of feature points and dense 3D reconstruction of material piles. Second, the 3D point cloud model of the material piles before and after shoveling was registered and segmented to obtain the 3D point cloud model of the shoveling area, and the Alpha-shape algorithm of Delaunay triangulation was used to estimate the volume of the 3D point cloud model. Finally, a shovel loading volume measurement experiment was conducted under loose-soil working conditions. The results show that the shovel loading volume estimation method (QORB–MAPM VE) proposed in this study has higher estimation accuracy and less calculation time in volume estimation and bucket fill factor estimation, and it has significant theoretical research and engineering application value. [ABSTRACT FROM AUTHOR]

The traditional loader drive system is based on the hydraulic torque converter as the key component, and its gear is shifted through the coordination of the clutch and gearbox, which greatly increases power loss and operator fatigue. To address the above problem, a variable-structure hydrostatic drive system is proposed. This system adopts a closed-loop design and adjusts the displacement of the pump and dual motors to follow the throttle opening of the vehicle, achieving automatic gear shifting and smooth speed regulation. It can also automatically change the system structure according to the vehicle’s speed, meeting the vehicle’s demand for rapid switching output of high torque and high speed. At the same time, in the displacement matching control process, an adaptive sliding mode control scheme based on radial basis function neural network compensation is proposed. This scheme designs an adaptive hyperparameter update strategy according to the characteristics of the system to effectively compensate for changes in uncertain factors. Experimental results show that, compared to traditional drive systems, this system has the characteristics of simple operation, smooth speed regulation, and high fuel economy.

In view of the contact fatigue problem of the wheel side reducer gear of the drive axle of the loader during its service, the fatigue life was evaluated. Finite element models of the sun wheel and the planet wheel were established in Hypermesh. Statics and transient dynamics were solved in Ansys Workbench according to the fatigue loading spectrum. The fatigue life was calculated in Ncode environment based on statics and transient dynamics. The fatigue life calculated based on finite element was compared with the bench test results. The results show that the contact stress calculated by transient dynamics is greater than that calculated by static. The fatigue life based on transient dynamics is 47 417 h, which is closer to the experimental results, and the relative errors are 9.32% and 15.14%. The analysis results provide reference and basis for the optimization and fatigue life evaluation of the drive axle gear system of loader.

Copyright of Ordnance Industry Automation is the property of Editorial Board for Ordnance Industry Automation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The research is aimed at how the tractor drivers respond to whole-body vibrations (WBV) during real-field loader operation. Seat-to-head transmissibility (STHT) behavior of tractor drivers is characterized to examine the impact of WBV. Tractor with a mounted loader was driven by nine (9) male tractor drivers during the experiment. The vibration levels were tested along three translational axes at the seat pan and the head. This study developed an Internet of Things (IoT) module for online data transmission to increase the efficiency of experimentation by eliminating potential causes of experimenter error. The data were examined using weighted root mean square acceleration (Aw), daily exposure A (8), signal-to-noise (S/N) ratios, power spectral density (PSD), and STHT. The vertical (z) axis dominated vibration exposure levels at the seat pan and head. A(8) response was measured to be greater than the exposure action value limit of 0.5 m/s2 as specified by Directive 2002/44/EU. PSDs at the head and seat pan showed low-frequency dominating frequencies. In the 4–7 Hz and 8–12 Hz frequency bands, respectively, STHT showed primary and secondary resonance. Tractor designers and manufacturers could use the research's findings to reduce high vibration amplitudes and important resonance frequencies to enhance the tractor ride.

To improve the control performance and energy efficiency of the hydrostatic transmission (HST) system of wheel loaders, this study proposes a novel variable structure dual-motor hydrostatic transmission system, accompanied by a multivariable control strategy based on fuzzy sliding mode control. By constructing a simulation model of the transmission system, the performance of the novel transmission system is verified, and the control effects of common control strategies are compared. The simulation results show that the proposed control strategy and system have good matching and can adapt to disturbances actively. Field experiment results show that the proposed solution can achieve smooth automatic shifting of wheel loaders, while effectively adjusting system pressure, flow, and power. Compared with the traditional hydrodynamic torque converter loader transmission system, its transmission efficiency is effectively increased by 30%, and the efficiency is increased by 8% compared with the traditional hydrostatic transmission system This achievement is of great significance for improving the working efficiency of wheel loaders and reducing energy consumption. The future research focus is to further improve the multivariable control strategy, achieve intelligent operation, and improve the efficiency and reliability of the transmission system.

Achieving precise load detection for Intelligent Loaders is an important task, which directly affects the operation energy efficiency and the fatigue life analysis for the loader's working mechanism. The operation of the mechanism is regarded as a 3-DOF (degree of freedom) planar motion process coordinated with the vehicle body. Affected by complex dynamic coupling in motion, the existing dynamic models of the mechanism have the problem of insufficient accuracy, which is not conducive to the precise calculation of load. Taking the reverse six-linkage loader as the research object, an accurate dynamic model of the mechanism is established considering its cooperative motion with the vehicle body. Firstly, the kinematic description of the mechanism is given by the Rodriguez method. Then, to overcome the coupling effect caused by the cooperative motion, the sufficient inertia forces of the mechanism are established in joint space using the Lagrange method. Furthermore, to overcome the coupling effect caused by the complex structure, the Newton–Euler method is used to establish the force mapping relations between the joint space and the drive space by multi-body modeling. Finally, the dynamic model of the mechanism in drive space is obtained, and the specific mapping relations between the bucket force, the vehicle driving force, and the drive parameters are given. Compared with existing dynamic models in simulation, the analysis shows that the average and maximum absolute errors of the vehicle driving force calculated by the established model do not exceed 20% of the existing model errors, and the corresponding errors of the bucket force do not exceed 10% of the existing model errors, which proves that the motions of vehicle body and front-end mechanism, as well as the force of the tilt hydraulic cylinder, play important roles in improving the model accuracy. The established model is superior to existing models and is more suitable for cooperative motion with the vehicle body. [ABSTRACT FROM AUTHOR]

To give full play to the advantages of pure electric drive, and aimed at the transmission system of electric loader, the low efficiency hydraulic torque converter and reverse direction clutch of traditional models are cancelled. By analyzing the shift law of the pure electric drive system, the electro-hydraulic shift control system is used to control the wet clutch, and based on the feedback of pressure and speed, combined with the driving motor active working in the speed and torque mode, the matching of torque and speed in the process of clutch engagement and disengagement is realized. For a 50-type pure electric drive loader, a shift control strategy of pure electric drive loader based on composite control of drive motor and clutch pressure is proposed. The result of vehicle test shows that the proposed control strategy can give full play to the advantages of pure electric drive. The shift time is reduced by about 50%, the sliding friction work is greatly reduced, and the maximum shift impact is 14.08 m/s 3, which is within the recommended limit value of 17.64 m/s 3 for Chinese vehicles.

The article considers the problem of ensuring the operability of articulated units of load haul dumpers. The hinge units were found to have an insufficiently reliable design and lack technical state controllability. It was identified that the pivot skew assembly units used in load haul dumpers based on articulated truck frames are the least reliable design elements. Tests and experiments have proven that the worn-out hinge units tend to dismantle from the vehicles when exposed to vibration causing the pin to come out from the coupling. This results in critical vehicle failures caused by the loss of the unit assembly integrity since the unit ensures vehicle safety. Certain technical design solutions aimed at improving the operability and controllability of the hinge assembly. This article reviews a concept method based on the Maintenance 4.0 approach for managing operability and reliability of load haul dumpers. [ABSTRACT FROM AUTHOR]

The bucket fill factor is a core evaluation indicator for the optimization of the loader's autonomous shoveling operation. Accurately predicting the bucket fill factor of the loader after different excavation trajectories is fundamental for optimizing the loader's efficiency and energy cost. Therefore, this paper proposes a method for predicting the bucket fill factor of the loader based on the three-dimensional information of the material surface. Firstly, the co-simulation model of loader shoveling material is established based on the multi-body dynamics software RecurDyn and the discrete element method software (DEMS) EDEM, and the co-simulation is conducted under different excavation trajectories. Then, the three-dimensional material surface information before shovel excavation is obtained from DEMS, and the surface function of the material contour is fitted based on the corresponding shovel excavation trajectory information. Meanwhile, the volume of the material excavated by the loader is obtained by the numerical integration method, and it is divided by the rated bucket volume to obtain the estimated bucket fill factor. Finally, the actual volume of the material after the shovel excavation is divided by the rated bucket volume to obtain the accurate bucket fill factor. Based on this, the prediction model of the bucket fill factor is built. The experimental results show that the proposed method is feasible, with a maximum error of 4.3%, a root mean square error of 0.025 and an average absolute error of 0.021. The research work lays the foundation for predicting the bucket fill factor of construction machinery such as loaders and excavators under real working conditions, which is conducive to promoting the development of autonomous, unmanned, and intelligent construction machinery. [ABSTRACT FROM AUTHOR]

The study of the performance of dynamic hydraulic throttling under the condition of stable fluid is of great significance. The effect of a step change in pressure differences on the throttling performance of a hydraulic valve is studied. This paper studies the dynamic and static performance of a hydraulic-valve-outlet throttling-speed regulation system, builds a more accurate mathematical model, considers the linear factors of the flow of hydraulic-valve throttling, analyzes the influence of the step-load change in pressure difference on the stability of the hydraulic-valve movement speed, and constructs a nonlinear mathematical model of the speed-regulation system of the outlet throttling. A pressure sensor is used to measure the change in pressure overshoot, and the effect of a pressure-difference step change on the throttling performance of the hydraulic valve is studied under steady-fluid conditions. The theory is analyzed and verified by experiment, and the parameters of hydraulic components are modified using the dynamic-change rule of the hydraulic valve's two-chamber pressure. [ABSTRACT FROM AUTHOR]

Copyright of China Mechanical Engineering is the property of Editorial Board of China Mechanical Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)