Tractor Research Articles

A Survey on the Sleep Quality in Agricultural Tractor Drivers in Different Climatic Conditions

Background and Objectives: Among the various agricultural activities, working and driving with farm tractors in different weather conditions lead to fatigue and burnout. The objective of this study was to evaluate the sleep quality of farm tractors drivers in different weather conditions.
 Methods: Amongst tractor drivers in Behbahan, Eqlid, and Kavar, 90 participants (Kavar: 27; Eqlid: 33; Behbahan: 30) were selected. The required data was gathered using the demographic characteristics questionnaire and standard questionnaire Pittsburgh Sleep Quality Index (PSQI). We used Kruskal-Wallis and Post-hoc pairwise comparison tests to analyze the data (α = 0.05).
 Results: The results showed that there were no significant differences in sleep quality and sleep quality parameters between different region tractors drivers (P > 0.05); but there were significant differences in mental sleep quality (P = 0.001), in terms of delays in falling asleep (P = 0.02), going to sleep duration (P = 0.04) and between Kavar and Behbehan tractor drivers, and also there are significant differences in going to sleep duration (P = 0.04) between Kavar and Eqlid tractor drivers.
 Conclusion: Working in critical cold weather (like nights in Eqlid) or critical hot weather (like noon in Behbahan) should be strongly forbidden by providing with a suitable working schedule especially while tractor drivers without driver’s cabin. Drivers’ cabins safeguards drivers against temperature, wind and dust, and, therefore increase their comfort and sleep quality.

The Effect of Power Sources in the Agricultural Tractor and the Developed Sprayer System on the Performance of the Electrical and Mechanical Sprayer System and some Performance Indicators of the Engine

An experiment was conducted to study the effect of the sprayer type according to the source of power and the size of the spray nozzle concerning the quality of the spray produced and fuel consumption.Two types of sprayers were used: a conventional boom sprayer (S1) and a modified (electrified) boom sprayer (S2), along with three sizes of the XR TeeJet 110 spray nozzle (N). The following technical performance indicators were examined: Density of coverage (drops/cm2) using ImageJ software, a 600dpi business card scanner, specifically the ScanShell 800N by CSSN, Inc, and water-sensitive paper (WSP), rate of spray nozzles discharge (ml/min), and fuel consumption (liters/hectare) using a calibrated cylinder, and the percentage of weed control by sampling treated and untreated weeds. The experiment was designed as a complete randomized block design in the order of the system (Nested design). Sprayer type had significant effect on spray coverage and nozzle discharge rate. The conventional boom sprayer resulted in a coverage of 169.5 drops/cm2, while the modified (electrified) boom sprayer achieved only 149.4 drops/cm2. The discharge rate was 707.5 ml/min when using the conventional boom sprayer, compared to 671.2 ml/min with lower pesticide consumption when using the modified (electrified) boom sprayer.The smaller-sized XR TeeJet 110.015 VP nozzle (N1) outperformed the other nozzle sizes in terms of coverage (178.7 drops/cm2), weed control percentage (84.56%), and lower pesticide consumption (lower nozzle discharge) of 490.4 ml/min.

The Effect of Diesel Fuel Additives on the Exhaust Gases of Agricultural Tractors During Plowing

The research aims to study the effect of the fuel type, plow types, and engine speeds on carbon monoxide (CO), hydrogen sulfide (H2S), and oxygen (O2) gases. The field experiments were conducted on an experimental farm in Al-Hamdaniya, Nineveh, Iraq. The investigation was factorial, using a Randomized Complete Block Design with Split –Split plot Design. The three types of fuel were placed in the main plot, the plow types in the secondary split plot, and the speed engine in the Split –Split action. The results showed significant differences between the fuel, plows, and engine speeds in most studied traits. There were no significant differences in the interaction between the plow types and the engine’s speed regarding CO emissions at the two levels. Still, the rate at 1000 rpm recorded the lowest emission value. At the two levels (the level of the exhaust nozzle - the status of the tractor driver’s seat), it amounted to 39.833-18.767 ppm, respectively. Moreover, the highest reading of H2S gas emissions was recorded with diesel without added fuel and the moldboard plow. Finally, the results showed no significant difference, as diesel fuel with super additives from Manol and an engine speed of 2000 rpm recorded the lowest emission rate for the emission rate of O2 gas, amounting to 20.550%.

Development and performance evaluation of lateral control simulation-based multi-body dynamics model for autonomous agricultural tractor

Development and performance evaluation of lateral control simulation-based multi-body dynamics model for autonomous agricultural tractor

Research on Battlefield Repair of Tractors Damaged by Fragment Warhead

This study established a typical tractor model and divided the vehicle model into five parts. At the same time, combined with the damage model of the fragment warhead, the probability of damage to various parts of the vehicle when the fragment warhead explodes at different positions was analyzed. Based on the constructed model, we randomly generate 1000 bomb landing points to obtain the number of bomb fragments hitting different parts of the vehicle. Then we analyze the vulnerable parts in each part of the vehicle, and provide corresponding repair methods and spare parts carrying capacity for the corresponding parts. It has certain reference significance for the battlefield support of vehicle.

Soil mobilization in function of sowing speed in maize

The sowing process can be affected by constructive differences related to the seeder, morphological and climatological conditions, and depending on the working speed used. The performance of the furrow opening components of the seeders is essential for obtaining good yields and productivity of maizecrops. This work aims to evaluate maize sowing with a Massey Ferguson tractor model MF 7370 with power of 125 kW pneumatic seeder-fertilizer as a function of its behavior at the different displacement speeds. The statistical design used was randomized blocks, with six displacement speeds, approximately (V1=2.0; V2=4.7; V3=6.5; V4=8.1; V5=10.3 and V6=12.3 km h-1), for the maize crop, with four replications, totaling 24 experimental plots. Soil mobilization parameters were evaluated: furrow width and depth, furrow mobilized area, and furrow opening angle. As agronomic traits were evaluated: the number of days for sowing emergence, initial and final sowing population, and grain yield. The mobilized area, angle, and depth of the furrowing fitted the quadratic regression model, while sulcus width had an increasing linear effect. Intermediate speeds V4 (8.1 km h-1) showed the highest values of the mobilized area and furrow depth and the lowest furrow angle value, whereas V3 (6.5 km h-1) presented the highest yield (8902 kg ha-1).

The Development of a Draft Force Prediction Model for Agricultural Tractors Based on the Discrete Element Method in Loam and Clay Loam

In the field of agricultural machinery, various empirical field tests are conducted to measure design loads for the optimal design and implementation of tractors. However, conducting field tests is costly and time-consuming, with many constraints on weather and field soil conditions, and research utilizing simulations has been proposed as an alternative to overcome these shortcomings. The objective of this study is to develop a DEM-based draft force prediction model that reflects differences in soil properties. For this, soil property measurements were conducted in two fields (Field A in Daejeon, Republic of Korea, and Field B in Chuncheon, Republic of Korea). The measured properties were used as parameters for DEM-based particle modeling. For the interparticle contact model, the EEPA contact model was used to reflect the compressibility and stickiness of cohesive soils. To generate an environment similar to real soil, particle mass and surface energy were calibrated based on bulk density and shear torque. The soil property measurements showed that Field B had a higher shear strength and lower cone index and moisture content compared to Field A. The actual measured draft force was 19.47% higher in Field B than in Field A. In this study, this demonstrates the uncertainty in predicting draft force by correlating only one soil property and suggests the need for a comprehensive consideration of soil properties. The simulation results of the tillage operation demonstrated the accuracy of the predicted shedding force compared to the actual field experiment and the existing theoretical calculation method (ASABE D497.4). Compared to the measured draft force in the actual field test, the predictions were 86.75% accurate in Field A and 74.51% accurate in Field B, which is 84% more accurate in Field A and 37.32% more accurate in Field B than the theoretical calculation method. This result shows that load prediction should reflect the soil properties of the working environment, and is expected to be used as an indicator of soil–tool interaction for digital twin modeling processes in the research field of bio-industrial machinery.

Path Tracking Control of a Tractor on a Sloping Road with Steering Compensation

Agricultural tractors are subject to lateral forces when traveling on slopes, making it difficult to accurately follow a set course. In this paper, a steering compensation method is first proposed based on the force analysis of a tractor traveling on slopes, which compensates the steering angle according to the friction force and gravity force imposed on the tractor. Further, when traveling on slopes, acceleration and a load applied to the tractor are usually time-varying. To address this problem, this paper proposes a steering compensator that can automatically adjust a compensation coefficient, as well as a design for a model predictive controller with the steering compensator for a tractor. Simulation results show that under different traveling speeds, turning radius, and slope angles, the steering compensator allows the tractor to travel more smoothly, i.e., the distance between the actual traveling route and the reference route fluctuates within a smaller range. Further, during straight-line traveling, the static error can be effectively reduced, i.e., the distance between the actual traveling route and the reference route is closer to zero. Overall, the steering compensator enables the tractor to track the reference route more accurately.

Features of Wear of Gears of Agricultural Machinery

Abstract The paper presents data on the resource and wear of the gears of agricultural tractor transmissions, on the basis of which the research problem and the novelty of the proposed methodology are formulated, based on the development and application of the stress state model of the gear, taking into account surface hardening. The methodology and calculation scheme for determining the power parameters of gearing are described in detail. In this case, the dependences and results of previous studies in the field of increasing the durability and reducing the wear of gears of transmission elements of vehicles of various functional purposes were used. To achieve this goal, the mathematical models of the stress state of gears are constructed without the presence of an external diffusion hardening coating and with a coating. Based on the simulation of the process of interaction of rubbing pairs of gears, the distribution of stresses in the contact zone over the surface layer of non-hardened and cemented to a depth of 1 mm gears, as well as the dependence of deflection on the thickness of the cemented layer and the deformation of the cemented layer during operation was established. Considering the research results given in literature, as well as those obtained on the basis of our own research, it should be noted that the analysis of gear stress state is an important direction in the study of the durability of gear units, the entire gearbox, and other gears of tractor transmissions and automotive technology at the present time. At the same time, the actual task is to establish the ratios of the allowable wear of gears and the limiting value of displacement of the centre distance, taking into account changes in the stress state scheme when using various types of coatings.

Comparative experimental study of microclimate conditions in farm tractor cabs

Comparative experimental study of microclimate conditions in farm tractor cabs

Development of a Real-Time Tractor Model for Gear Shift Performance Verification

Verification of the system is essential during the development of a tractor; however, there are cost and time limitations when verification is performed on an actual tractor. To solve this problem, we developed a tractor model for real-time simulation to verify the gear shift performance of the tractor and evaluate the control algorithm. This study examined and modeled a dual-clutch transmission (DCT)-type 105 kW class tractor. The proportional control valve, synchronizer, and clutch were modeled to accurately implement the shift behavior, and the developed individual model was verified based on actual individual product test data. The 45 s driving simulation was conducted to confirm whether real-time simulation of the entire developed tractor model was possible and whether it simulated the behavior of the target tractor well. The driving simulation results confirmed that the driving speed of the tractor model matched the engine speed, transmission gear ratio, and tractor specifications, and the gear shift performance of the tractor model according to the number of gears was confirmed. The simulated model thus satisfies the characteristics of the target tractor and can be used to verify the gear shift performance, indicating that the model can verify the performance of the control algorithm in real time.

Optimal Coverage Path Planning for Agricultural Vehicles with Curvature Constraints

Complete coverage path planning (CCPP) is vital in mobile robot applications. Optimizing CCPP is particularly significant in precision agriculture, where it enhances resource utilization, reduces soil compaction, and boosts crop yields. This work offers a comprehensive approach to CCPP for agricultural vehicles with curvature constraints. Our methodology comprises four key stages. First, it decomposes complex agricultural areas into simpler cells, each equipped with guidance tracks, forming a fixed track system. The subsequent route planning and smooth path planning stages compute a path that adheres to path constraints, optimally traverses the cells, and aligns with the track system. We use the generalized traveling salesman problem (GTSP) to determine the optimal traversing sequence. Additionally, we introduce an algorithm for calculating paths that are both smooth and curvature-constrained within individual cells, as well as paths that enable seamless transitions between cells, resulting in a smooth, curvature-constraint coverage path. Our modular approach allows method flexibility at each step. We evaluate our method on real agricultural fields, demonstrating its effectiveness in minimizing path length, ensuring efficient coverage, and adhering to curvature constraints. This work establishes a strong foundation for precise and efficient agricultural coverage path planning, with potential for further real-world applications and enhancements.

Robots addressing agricultural labour shortages and environmental issues

PurposeThe purpose of this paper is to provide details of recent developments in agricultural robots with an emphasis of those that address labour shortages and environmental issues.Design/methodology/approachFollowing an introduction which highlights some of the challenges facing the agricultural industry, this discusses recent robotic agricultural vehicle developments and the enabling technologies. It then provides examples of terrestrial and airborne robots employed in precision agricultural practices. Finally, brief conclusions are drawn.FindingsTraditional, labour-intensive and environmentally harmful agricultural practices are not sustainable in the long term, and if food supply is to meet future demand, radical changes will be required. Exploiting recent advances in artificial intelligence (AI), agricultural equipment manufacturers are developing robotic vehicles in response to labour shortages. Precision agricultural practices will mitigate many of the detrimental environmental impacts and can also reduce the reliance on manpower. Weeding robots which reduce or eliminate the use of herbicides have been commercialised by a growing number of companies and again exploit AI techniques. Drones equipped with imaging device are playing an increasingly important role by characterising agricultural and crop conditions, thereby allowing highly targeted agrochemical application.Originality/valueThis illustrates how the agricultural industry is adopting robotic technology in response to the need to increased productivity while mitigating the problems of shortages of labour and environmental degradation.

PREDICTION MODEL OF PITCH ANGLE OF GREENHOUSE ELECTRIC TRACTORS BASED ON TIME SERIES ANALYSIS

The pitch angle of greenhouse tractors changes when operating on rough soil pavement. As a result, the feedback signal lags behind the tractor motion attitude signal, thereby affecting the real-time control of tilling depth. In this study, a pitch angle prediction model of greenhouse electric tractor was proposed based on extended Kalman filter (EKF) and time series analysis to improve the dynamic response speed of tilling depth regulation by providing predictive information for advance control. EKF was used to track the tilling depth of greenhouse electric tractor in real time, and an auto-regressive moving average model (ARMA) was established for the obtained time series data. ARMA (2, 1) was designed as the pitch angle prediction model of greenhouse electric tractors by constructing a simulation model. Inertia measurement unit (IMU) of tractor was used to construct the extended Kalman estimation model of the pitch angle. Actual vehicle tests were carried out under different working conditions. Results show that the estimated values obtained under two operating conditions have a high correlation with the measured values, with correlation coefficients(R) of 0.9504 and 0.9734, root mean square error (RMSE) of 0.2355 and 0.2173, and maximum absolute error (MAE) of 0.1929 and 0.1703, respectively. And ,the MAE and the RMSE of the predicted and measured values of ARMA (2,1) model approximately have the same value under the two conditions, with with the R of 0.9665 and 0.9755, the RMSE of 0.2002 and 0.1812, and the MAE of 0.1578 and 0.1387, respectively. The effectiveness of ARMA (2, 1) as the pitch angle estimation and prediction model of greenhouse electric tractors is verified. This study provides theoretical reference for designing the control law of tilling depth stability in subsequent greenhouse operation. Keywords: Time series, prediction, pitch angle,electric tractor

Coverage Analysis of LoRa and NB-IoT Technologies on LPWAN-Based Agricultural Vehicle Tracking Application

This study focuses on the recently emerged Internet of Vehicles (IoV) concept to provide an integrated agricultural vehicle/machinery tracking system through two leading low power wide area network (LPWAN) technologies, namely LoRa and NB-IoT. The main aim is to investigate the theoretical coverage limits by considering the urban, suburban, and rural environments. Two vehicle tracking units (VTUs) have been designed for LoRa and NB-IoT connectivity technologies that can be used as reference hardware in coverage analysis. On this basis, the closed-form explicit analytical expressions of the maximum transmission range have been derived using the Hata path loss model. Besides, the computer simulation results have been validated via the maps from XIRIO online radio planning tool. In light of the obtained findings, several evaluations have been made to enhance the LPWAN-based agricultural vehicle tracking feasibility in smart farms.

Design and Experimental Assessment of a Vibration Control System Driven by Low Inertia Hydrostatic Magnetorheological Actuators for Heavy Equipment

Active suspension systems for automotive vehicles were developed in the past using hydrostatic, electric, magnetic and magnetorheological (MR) technologies to control road vibrations and vehicle dynamics and thus improve ride comfort and vehicle performance. However, no such systems were developed for heavy equipment, trucks and off-highway vehicles. For instance, agricultural tractors are still equipped with minimal suspension systems causing discomfort and health problems to drivers. The high suspension loads due to the massive weight of these vehicles are a challenge since high forces are needed to achieve efficient active suspension control. This paper presents an experimentally validated feasibility study of a hydrostatic, MR clutch-driven system of actuators. The scope of this paper is to evaluate the preliminary performance of the actuator for future vibration control. The hydraulic system allows the actuators to be remotely located from the wheels or cabin of the heavy vehicle and conveniently placed on the vehicle’s suspended frame. The design includes two MR clutches driven in an antagonistic configuration to push and pull on the end effector. Experiments on a laboratory prototype show that the low-inertia characteristics of the clutches allow a high blocked-output force bandwidth of 20 Hz with peak output forces exceeding 15 kN.

The Influence of Soil Physical Properties on the Load Factor for Agricultural Tractors in Different Paddy Fields

The load factor (LF) of a tractor represents the ratio of actual engine power and rated engine power, and is an important indicator directly used in calculating national air pollutant emissions. Currently, in the Republic of Korea, a fixed value of 0.48 is used for the LF regardless of the working conditions, making it difficult to establish a reliable national air pollutant inventory. Since tractors perform work under soil conditions, soil physical properties directly affect the tractor LF. Therefore, it is expected that more accurate LF estimation will be possible by utilizing soil physical properties. This study was conducted to assess the impact of soil physical properties on the LF. Experimental data were collected in ten different soil conditions. Correlation analysis revealed that the LF exhibited strong correlations with SMC, soil texture, and CI, in that order. The coefficient of determination for the regression model developed using soil variables ranged from 0.678 to 0.926. The developed regression models generally showed higher accuracy when utilizing multiple soil variables, as compared to using a single soil variable. Therefore, an effective estimation of the LF through non-experimental methods can be achieved by measuring various soil properties.

Analysis of current methods for improving the reliability of steering systems in agricultural transport when moving on deformable soils

This article is dedicated to the analysis of current methods aimed at improving the reliability of steering control in agricultural transport when operating on deformable soil. Objective of this paper is to analyze existing methods aimed at enhancing the reliability of steering control in agricultural transport on deformable terrain. Given the high relevance of the use of vehicles in agriculture on such ground conditions, there is a need to develop methods that can improve steering reliability and reduce the likelihood of accidents. The outcome of this article is a consideration of various approaches and methods that help address this issue; the paper aims to consolidate experience and knowledge in this field and offer recommendations for enhancing the steering control reliability of agricultural transport when operating on deformable soil. The methods examined in this paper include improving the quality of materials and components, developing optimal ball joint geometry, using automatic adjustment systems, applying new «Precision Agriculture» technology concepts, and implementing operational self-diagnostics with regular technical maintenance. Selection of stronger and more durable materials, the installation of automatic suspension adjustment systems, and regular technical maintenance will increase the reliability and lifespan of steering equipment on deformable soil. The use of new technologies, such as machine learning and artificial intelligence, will enhance the safety of agricultural machines. The author brings novelty to the study of enhancing steering control reliability in agricultural transport on deformable soil by focusing on the application of modern technologies and methods, such as the use of automatic adjustment systems and the implementation of new technologies. Moreover, the author emphasizes the need for regular technical maintenance and replacement of worn parts to maintain the efficiency and safety of the steering equipment's operation.

The Use of Machine Learning Algorithms to Determine the Characteristics of Turbocharging of the Diesel Engines

The results of the development of a method for determining the characteristics of gas turbine supercharging of the diesel engines without testing on specialized stands are presented. The parameters of the training model were studied under operating conditions of an agricultural tractor.

A GIS-based land suitability model for agricultural tractors in CALABARZON Region, Philippines

Agricultural machinery distribution programs are key components of the Philippine government to strengthen its economic productivity. However, concerns were reported that some of the distributed machines were under-utilized or unutilized in their respective farms. This study is focused on the development of a GIS-based model of determining suitable lowland rice areas for two-wheel and four-wheel tractors. A numerical rating system was designed that assigns a suitability score from three criteria, namely slope, road network proximity, and flood risk, based on established scales. Analytical Hierarchy Process was used as an approach to determine the relative influence in which results show that slope has the greatest weight (65%) followed by flood risk and road network proximity with 20% and 15%, respectively. The total suitability score (TSS) is then determined by getting the weighted average of the individual suitability scores. Land suitability mapping on the study area, the CALABARZON region, show that majority of the lowland rice areas are highly suitable for two-wheel and four-wheel tractors (81.39%) while some areas fall under marginal (15.03%) and moderate suitability (3.58%). Geotagged locations of the distributed agricultural tractors from 2015 to 2020 reveal that 78% of the distributed two-wheel tractors and 80% of four-wheel tractors in the region are situated in highly suitable areas. The GIS-based suitability model generated in this study can be utilized by the government to improve its machine distribution programs of two-wheel and four-wheel tractors in lowland rice farms.