Tractor Research Articles

Trends and Future Perspective of Electrification in Agricultural Tractor-Implement Applications

The worldwide growing demand for food is pushing the agricultural field towards new innovative solutions to increase the efficiency and productivity of cultivations. In this direction, agricultural mechanization plays a crucial role, and tractors are among the most important actors. Agricultural tractors are machines designed to push/pull special instruments usually referred to as implements, to which they may transfer power by means of a mechanical power take-off (PTO) or via hydraulic connections, thanks to the availability of pressurized oil. The tractor can be seen as a mobile power station: the more efficiently it provides power to external implements or to the ground in terms of tractive effort, the higher will be the efficiency and productivity of a certain task. However, the growing demand for greener and sustainable work machines is pushing towards new concepts of tractor powertrains with the goal of reducing, as much as possible, the amount of pollutants and GHG emissions per unit of work. In this paper, the authors will propose a review of the current trends towards electrification of agricultural tractors. Electrification can help in making vehicles more efficient and opening a new scenario for work optimization. Moreover, electrification is also involving the implements attached to the tractor and responsible for actually performing a wide variety of field tasks. However, tractor electrification requires proper attention due to the impact of high power electric systems on the vehicle configuration. For this reason, a proper level of hybridization should be considered. In this paper, a new classification method will be proposed, considering the electrification level in terms of power and as a function of the installed electric energy storage. This definition will be applied to classify the current state of the art of electric and hybrid agricultural tractors, investigating current trends in the scientific community and among industrial manufacturers with a look to the new upcoming technologies.

A Solution to Prevent and Minimize the Consequences of Accidents with Farm Tractors in the Context of Mountainous Regions with Low Population Density.

Farm tractors have become a key part of daily routine agriculture, converting complex and time-consuming tasks into tasks that are easier to perform and less dependent on human labor, contributing directly to increasing the economic value generated by this activity sector, either by increasing the productivity or by making certain agricultural crops viable, which otherwise would not be sustainable. However, despite all the advantages, accidents with this type of equipment are common, often with critical and sometimes fatal consequences. The evolution of safety requirements of these machines has occurred at a good level; however, a significant part of the agricultural tractors in use are older models that do not have such solutions. Even in the new models, which contain such solutions, these are not always correctly used, and it is even common that they are turned off or simply not used at all. It is therefore natural that accidents continue to occur, a situation that is aggravated by other factors. Lack of situational awareness of the operators, which can result from advanced age, inadequate training, reduced sensitivity/respect for safety rules, or working on irregular terrain like mountainous areas, contribute to high-risk contexts that end in the loss of human life. The consequences of such accidents are clearly aggravated by the time it takes to assist the victims-either because accidents are simply not identified/reported immediately, or by the time it takes to locate and provide help to the victims. This is a scenario that is more common in mountainous regions and regions with low population density. The current paper, using NB-IoT, a set of sensors, and a web application, presents a conceptual toolset conceived to prevent accidents and minimize consequences (human and material) that can be applied to old and new farm tractors. The development was carried out taking the characterization of the farmers and the land in the region in which the authors' research institution is located into account, which has the highest rate of fatal accidents with agricultural tractors in the country; it is a region of mountainous with a very low population density.

The Design and Simulation of Autonomous Agricultural Vehicle for Orchards

In recent years, agricultural producers have faced challenges due to the uncertainty of labor force access, growing demand for safe, accessible, and high-quality agricultural products, high competition with international producers, and the need to reduce their carbon footprint. To continue their competitive and profitable production, producers must invest in technology and increase efficiency. Autonomous agricultural vehicles are crucial for autonomous processes in orchards, increasing productivity, collecting data for decision-making, reducing operating costs, and carbon footprint. This study focuses on the design and simulation of an autonomous vehicle for orchards. The autonomous vehicle can map the orchards using data from odometry and light detection and ranging (LIDAR) sensors by utilizing Simultaneous Localization and Mapping (SLAM) algorithm, accurately determine its position using the Adaptive Monte Carlo Localization method, and avoid obstacles using the dynamic window approach algorithm. The autonomous vehicle is an original design for netted orchards where GPS cannot work properly and is fully autonomous, requiring no external GPS data. It is expected to provide higher efficiency by reducing environmental pollution, operating expenses, and labor force in practice. The success of the mapping and localization application depends on the update frequency of the position and the number of particles used for localization. A path-planning application was developed to reach the desired position from the autonomous agricultural vehicle's current position on the map. The Dijkstra Algorithm was used for path planning, with the Dynamic Window Approach allowing the robot to escape obstacle. The simulation studies achieved the lowest position error when the vehicle's position was updated at intervals of 2 cm, and a minimum of 500 and a maximum of 2000 particles were used. While the vehicle was moving on a straight obstacle row in the simulation environment, an average localization error of 2.1 cm was obtained. This error is convenient as it enables seamless navigation between tree rows without any collision.

General modeling and energy management optimization for the fuel cell electric tractor with mechanical shunt type

The fuel cell electric tractor has emerged as a new development direction in modern agriculture due to its energy-controllable and emission-reducing advantages. This paper focuses on improving the universality of basic research by studying the fuel cell electric tractor with mechanical shunt type (FCETMST). The bond graph model has the benefits of cross-physical system integration. To fill the gap in general modeling of electric tractors, an electromechanical hydraulic integrated machine model by utilizing the bond graph model, which includes energy system, drive system, lifting system and power take-off (PTO) system, is developed. The general power flow model of the electric tractor with mechanical shunt type is also derived. Lastly, the accuracy of the model is validated by analyzing the tractor’s traction characteristics. To further enhance energy efficiency, this paper proposes an energy management strategy (EMS) utilizing a multi-population genetic algorithm (MPGA) and compares it with a power following control strategy (PFCS) for a fuel cell/lithium battery composite energy system. The results base on the co-simulation by using AVL-Cruise and Matlab/Simulink to build a vehicle simulation model and EMS models, respectively, show that under ploughing and transportation conditions, compared with the traditional PFCS, using MPGA leads to reduce state of charge (SOC) fluctuations and the remaining SOC is 11.22 % and 6.1 % higher, respectively. The theoretical hydrogen fuel consumption is decreased by about 26.49 % and 36.21 %, respectively. This study can provide theoretical support for the modeling and energy management optimization of the electric tractor system.

Analysis of Injuries and Cause of Death in Fatal Accidents with Farm Tractors

Abstract Farm tractor accidents are a frequent cause of death for people in agricultural field of work. The aim of this study was to evaluate the characteristics of the fatal farm tractor accidents, as well as the most significant types of injuries and causes of death. Research is based on epidemiological criteria of subjects, traffic participation, cause of death, distribution of injury, outliving period and toxicological details. The study included 22 (4.2%) farm tractor related fatalities out of all 525 subjects who died from sustained injuries or complications of the injuries sustained in road traffic accidents. The highest number of deaths was reported in men in 95.5%. The highest percentage died of bleeding out (41%), while in 18% of cases, complications that occurred during the outliving period were the cause of death. Analyzing injuries through organ systems, it is observed that the highest number of farm tractor drivers had a chest injury (90%), and the most common chest injury was a rib fracture (82%). When determining the outliving period, the highest number of fatal farm tractor drivers died at the scene of accidents (68.2%). Of all of the subjects, 32% were under the influence of alcohol, while 23% had blood alcohol concentration level greater than 0.5 ‰. The high mortality of farm tractor drivers can be reduced by introducing a mandatory rollover protective structures system and the use of a seat belt in farm tractors with cabs, which would reduce the possibility of the driver falling out of the farm tractor seat and additional injuries due to rollover.

Local Navigation and Obstacle Avoidance for an Agricultural Tractor With Nonlinear Model Predictive Control

Local Navigation and Obstacle Avoidance for an Agricultural Tractor With Nonlinear Model Predictive Control

Ultra-low soot/ particulate emissions from a dimethyl ether-fueled agricultural tractor engine

This study eveluates using dimethyl ether (DME) fuelled engine for marching towards zero soot and particulate matter (PM) emissions in the agricultural sector. Comparative emissions and particulate characteristics were analysed for a customised DME-fuelled engine and an unmodified baseline diesel engine. The experimental investigations were performed on a multi-cylinder tractor engine using a dedicated DME fuel injection equipment (FIE) and an unmodified diesel FIE. Regulated emissions, namely carbon monoxide (CO), hydrocarbons (HC), and oxides of nitrogen (NOx), smoke opacity, and particulates were measured at three engine speeds (1200, 1600 and 2000 rpm) and five loads (1.29, 2.59, 3.88, 5.18, and 6.47 bar BMEP). The static fuel injection timing for both test fuels was maintained constant; however, the actual injection timing could be slightly different for both test fuels because of their different physicochemical properties. DME-fuelled engine exhibited relatively higher HC and CO emissions than diesel at low loads; however, both test fuels exhibited nearly identical emissions at higher loads. NOx emissions were lower for DME-fuelled engine than baseline diesel, and its smoke opacity was also negligible at all engine loads and speeds. The particulate number concentration for DME-fuelled engines was much lower than baseline diesel at all test conditions, except 1.29 bar BMEP. Particulate emissions from DME-fuelled engine were mainly in the form of nanoparticles and nucleation mode particles, with negligible numbers of accumulation mode particles. This experimental study demonstrated that DME-fuelling of the tractor engine reduced emissions and it can be used as a sustainable and greener fuel to develop cleaner engines for agriculture/ transport sectors.

Performance analysis and control of an agricultural tractor suspension system

Suspension systems play a vital role in providing comfortable and safe vehicle ride. This paper aims to improve the passenger ride comfort, vehicle stability, safety, road holding in an active quarter tractor model. the main objective is to obtain a stable, robust, and controlled system. It is necessary to use controller to increase the stability and performance of the system. the controller selection and design aimed to achieve good passenger ride comfort and health, stability, and passenger body acceleration and displacement response under uneven road excitations. PID and LQR controllers are developed, and compare their performances against the road disturbances. The performance of the designed controllers evaluated using simulation work in MATLAB. Simulation results show that the proposed LQR control scheme can successfully achieve the desired ride comfort and passenger safety compared to PID control scheme

Development of a Spatial Tier 2 Emission Inventory for Agricultural Tractors by Combining Two Large-Scale Datasets

Agricultural tractor emissions have a notable influence on total emissions and climate change. This is especially important when developing an agricultural machinery emission inventory since tractors are the most widely used agricultural machinery. However, as with other agricultural machinery, there is a significant lack of data concerning tractors. This study combined two large-scale datasets to develop a Tier 2 tractor emission inventory for the Republic of Croatia. The first dataset, which was collected via a large-scale survey with 8895 respondents, includes data on fuel consumption by machine and engine type. The second dataset, which is official data of the Ministry of the Interior, includes data on machinery age. Since there is no direct link between datasets, data on fuel consumption were calculated for each of 21 Croatian counties and were then linked to the corresponding municipalities’ tractor age and power rating of the vehicle fleet. The result was used to calculate tractor emissions by with a Tier 2 approach using the method listed in the 2019 EMEP/EEA emissions guidebook. The calculations were made for five exhaust emission components: carbon dioxide (CO2), carbon monoxide (CO), hydrocarbon (HC), nitrogen oxide (NOX) and particulate matter (PM). The continental counties had the highest emissions for all emission types, especially the Osječko-baranjska and Vukovarsko-srijemska counties. The Tier 2 emission inventory was compared to data calculated using the Tier 1 method on a county level. There were notable differences between the inventories for HC and PM emissions, which is mainly due to Tier 2 approach having different emission factors depending on vehicle age. The end result was compared to the already existing Tier 1 emission inventory on a county level.

PERFORMANCE EVALUATION OF SEED DRILL- FERTILIZER UNDER TWO DIFFERENT FARMING SYSTEMS AND TRACTOR PRACTICAL SPEEDS

This study was aim to investigate performance of seed drill - fertilizer (GIL-SAX multisem18) was evaluated under two different farming systems (till and no-till) and tractor speeds (5.28, 7.76 and 8.30 km.h-1). The characteristics were measured including draft force, wheel slip, seed delivery rate, and germination rate. The experiment was organized as a randomized complete block design (RCBD). The significant difference was examined using the least significant difference tests at a P≤0.05. The results showed a minimum draft force and wheel slip under the till system and tractor speed of 5.28 km.h-1 interaction. The lowest seed delivery rate was found when no-till was practiced with a speed of 5.28 km.h-1. Adopting the no-till system with the speed of 7.76 km.h-1 achieved the highest germination rate. The till system achieved the lowest fuel cost in economic analysis 8395 IQD. ha-1 at a speed of 8.30 km.h-1, while the no-till system achieved the lowest cost of seeds 65066 IQD. ha-1 and sowing operation cost 36079 IQD. ha-1 at speed 5.28 km.h-1. Irrigation and agronomy indicators should be addressed in the further work.

Estimates to determining the agricultural tractor fleet in Mexico

Objective: the objective of the study was to know the current state of the national fleet of agricultural machinery. Design/ Methodology/ Approach: an estimate of the tractor fleet was made by adding the number of tractors with one year of lag, plus the number of tractors from national sales, minus the number of tractors leaving the fleet due to the end of their useful life, the period from 2007 to 2027. Results: there is a downward trend in the tractor fleet in the period 2007 to 2027. If the downward trend continues, the tractor fleet will have decreased by 114 thousand units in 2027, compared to the 238 thousand existing in 2007. This means a drop of 52%, compared to the initial year, which would leave the fleet of tractors with 124 thousand units. Limitations/ Implications of the study: the main limitation is the non-existence of official data after 2007. Therefore, in order to know the current state of the national fleet of tractors in Mexico, estimates such as the one carried out in this investigation are required. Findings/ Conclusions: The estimate of the tractor industrial fleet in Mexico indicates that annually the number of tractors that are added is less than the number of obsolete tractors that leave the fleet, which indicates that the rate of mechanization will decrease in the future. To avoid such a trend, the Government is required to support investments in agricultural machinery.

SELECTION CRITERIA TO CHOOSE A RIGHT FARM TRACTOR FOR AN OIL PALM PLANTATION

Farm tractors are used in oil palm plantations to carry out various field operations. Selection of the right farm tractor will incur lower running cost, ensure faster return of investment, and field operations are carried out efficiently and effectively. The selection criteria for a tractor depends on horsepower (Hp), tractor transmission, clutch, power take off (PTO), specific fuel consumption (SFC), torque, brake, hydraulic, weight, drawbar pull and lifting capacity. In addition, the safety and ergonomic factors are also needed to be given equal importance when choosing a farm tractor for estate operations. Keywords: Hp, PTO, torque, SFC, clutch and transmission.

Five-phase induction motor drive-A comprehensive review

Modern Electrical Vehicles (EV) and Electric Traction rely heavily on electrical drives. Every day, electric vehicles are being improved and expanded to include commercial vehicles such as passenger vehicles, goods delivery vehicles, and agricultural vehicles. Today, researchers are concentrating on multi-phase electrical drives to improve EV technology. This article provides a comprehensive analysis of the Five-Phase Induction Motor (FPIM) drive. The proposed study investigates the FPIM drive in terms of mathematical modeling and design, the different topologies of a Five-Phase Voltage Source Inverter (FPVSI) (Two-Level, Multi-Level, Matrix), the methodologies utilised to generate the pulse for FPVSI (Carrier-Based Pulse Width Modulation (CBPWM), Space Vector Pulse Width Modulation (SVPWM)), and the control of FPIM. This study evaluates the many strategies available in the literature for controlling the FPIM in order to assist researchers and industrial Research and Development (R&D) engineers in selecting the most suitable tool for their applications.

A Neural-network-based Control System for a Dynamic Model of Tractor With Multiple Trailers System

A Neural-network-based Control System for a Dynamic Model of Tractor With Multiple Trailers System

World experience in the use of unmanned aerial vehicles in agriculture

The study of unmanned aerial vehicles in agriculture is limited by regulations. Each country has its own restrictions in the form of flight altitude, maximum takeoff weight, and the required package of documents. The article discusses the main regulatory restrictions for the use of drones in various countries of the world.

Object Detection for Agricultural Vehicles: Ensemble Method Based on Hierarchy of Classes.

Vision-based object detection is essential for safe and efficient field operation for autonomous agricultural vehicles. However, one of the challenges in transferring state-of-the-art object detectors to the agricultural domain is the limited availability of labeled datasets. This paper seeks to address this challenge by utilizing two object detection models based on YOLOv5, one pre-trained on a large-scale dataset for detecting general classes of objects and one trained to detect a smaller number of agriculture-specific classes. To combine the detections of the models at inference, we propose an ensemble module based on a hierarchical structure of classes. Results show that applying the proposed ensemble module increases mAP@.5 from 0.575 to 0.65 on the test dataset and reduces the misclassification of similar classes detected by different models. Furthermore, by translating detections from base classes to a higher level in the class hierarchy, we can increase the overall mAP@.5 to 0.701 at the cost of reducing class granularity.

Performance of Harvesting Residue Treatment Methods in South African Pine Plantations

Forest harvesting generates variable amounts of residue that pose a fire hazard and a hindrance to regeneration and must be managed accordingly. In South Africa, burning is the most common residue management method, but there is interest in introducing safer and more effective techniques, such as mulching. For that reason, a productivity study was conducted in the Eastern Cape province after a mechanised cut-to-length (harvester and forwarder) harvesting operation to gather information on the productivity, cost, and work quality of the three main alternatives: manual broadcasting, manual broadcasting followed by mulching with an adapted farm tractor and mulching with a purpose-built mulcher. The stem wood residues after harvesting ranged from 12 to 14 ODT/ha. The average time consumption was 16 worker h/ha for manual broadcasting, 3.6 worker h/ha for mulching with a farm tractor, and 0.9 worker h/ha for mulching using a purpose-built mulcher (one pass). Manual broadcasting was the cheapest option, at an average cost of 400 ZAR/ha. Mulching with a farm tractor and a purpose-built mulcher incurred an average cost of 3267 ZAR/ha and 4083 ZAR/ha, respectively. Manual broadcasting achieved a minimal reduction in residue size, with 50% of the slash (branches and stem wood) having a mean length greater than 40 cm. When mulching with a farm tractor was applied, 49% of the slash (branches and stem wood) length was reduced to about 30 cm. When a purpose-built mulcher was used, only 10% of the slash elements exceeded 40 cm in length.

基于能耗最优的改进动态窗口法的电动拖拉机避障方法

In order to solve the real-time obstacle avoidance problem in electric tractor operation, an improved dynamic window approach (DWA) based on optimal energy consumption is proposed for electric tractor obstacle avoidance. Firstly, energy consumption model of tractor is established based on the transmission system of electric tractor, then energy consumption evaluation sub-function is introduced to improve the evaluation function of original DWA algorithm, and finally, the trajectory is evaluated and the optimal solution of the trajectory is determined by using new evaluation function. Based on the kinematics model of YL254ET electric tractor in Yancheng Yueda, a model predictive controller is designed. The obstacle avoidance planning and tracking control of electric tractor are simulated jointly on Simulink and CarSim simulation platform. Finally, the obstacle avoidance planning test is carried out. The simulation and experimental results show that after the algorithm improvement, the energy consumption of electric tractors is reduced, the generated path is smoother, and the lateral error is smaller.

基于微分与积分自适应滑模的拖拉机电液悬挂力位综合控制

The accuracy of tractor plowing is an important link to ensure the quality of agricultural crops. The integrated control of draft-position in plowing is an effective plowing precision control technology which can be used to improve the tractor's plowing efficiency. The hydraulic system of the tractor hitch has the characteristics of large load and complex working environment. A differential and integral sliding mode adaptive controller (DISMAC) is designed for the tractor hitch hydraulic system with strong nonlinearity, uncertainty and time-varying parameters. Compared with the traditional PID controller, integral sliding mode adaptive controller(I-SMAC) and differential and integral sliding mode adaptive controller (DI-SMAC) in the electro-hydraulic hitch control system, the numerical simulation verifies the advantages of the differential and integral sliding mode adaptive controller. The real test platform of the agricultural tractor is built. The test results show that the DI-SMAC can realize the integrated control function of draft-position. In the position control mode, there is no static error, and the anti-interference ability is strong; Under the draft control mode, compared with the traditional PID controller, the range of traction error of differential and integral sliding mode controller is reduced by 32.9%, and the standard deviation is reduced by 38.6%; When the weight coefficient is changed, the traction force and tillage depth fluctuation are different with different weight coefficients. It is shown that the DI-SMAC is stable and effective, and the developed method is expected to provide technical support for the fine plowing operation of tractors.

Real-Time Localization and Colorful Three-Dimensional Mapping of Orchards Based on Multi-Sensor Fusion Using Extended Kalman Filter

To realize autonomous navigation and intelligent management in orchards, vehicles require real-time positioning and globally consistent mapping of surroundings with sufficient information. However, the unstructured and unstable characteristics of orchards present challenges for accurate and stable localization and mapping. This study proposes a framework fusing LiDAR, visual, and inertial data by using the extended Kalman filter (EKF) to achieve real-time localization and colorful LiDAR point-cloud mapping in orchards. First, the multi-sensor data were integrated into a loosely-coupled framework based on the EKF to improve the pose estimation, with the pose estimation from LiDAR and gyroscope acting as the predictions, while that from visual-inertial odometry acting as the observations. Then, the Loam_Livox algorithm was enhanced by incorporating color from the image into the LiDAR point cloud, enabling the real-time construction of a three-dimensional colorful map of the orchard. The method demonstrates a high accuracy for localization in different motion trajectories (average RMSE: 0.3436) and different scenarios (average RMSE: 0.1230) and clear and efficient construction of three-dimensional colorful mapping, taking only 75.01 ms in localization and mapping for a frame of LiDAR point cloud. This indicates the proposed method has a great potential for the autonomous navigation of agricultural vehicles.