The article presents the results of developing a software solution in the MS Excel environment for assessing the integrated safety of tractor cabins which will help determine the safest model by comparative analysis. The methodology for assessing the safety of agricultural tractor cabins takes into account the working conditions and makes it possible to determine the overall safety level of various tractor models.

The purpose of the study is to clarify the approach to substantiating the normative values of diagnostic parameters of tractors. The analysis of known developments and regulatory and technical documentation on the topic since 1960 has been carried out. Results. It is shown that the optimization of the normative values of the diagnostic parameters of parts, interfaces, assemblies, machine assemblies, their service life, etc. is still very relevant for the engineering service of the agroindustrial complex. However, there are still few practical operational recommendations for this, although the main approach to substantiating the standards of technical operation of machines has been known since 1925. — technical and economic to minimize direct and indirect total unit costs and technical service costs. With this approach, the achievements of agricultural and motor transport scientists are known, and they are most widely performed by Prof. Mikhlin V. M. Alone, his justifi cation of the values of permissible diagnostic parameters of agricultural tractors is abstract, time-consuming and not widely implemented. Only gradual parametric diagnostic parameters were taken into account, and real mechanical failures were ignored. The infl uence of the permissible values of diagnostic parameters on the reliability and resource of control objects is excessively overestimated. Conclusions. The paper proposes to optimize the values of the parameters that control the technical service from the condition of achieving accounting costs for the technical service of a particular object to the cost of a similar new or renovated object.

This study proposes a new control algorithm based on the optimization of the conservation of traction power and efficient use of energy, which is adaptable to changing the tillage conditions. The proposed control algorithm is called the Tillage and Energy Control System (TECS). In this study, a cultivator was taken as a tillage tool. The optimized control speed is assigned to the vehicle by observing the slip rate that may occur in the wheel during the plunging and traction of the cultivator, which is the most important parameter of TECS. The traction optimizer obtained the optimal traction models a function of the traction ratios related to maximum traction and energy efficiency using experimental data on the traction-terrain interaction at different soil conditions. The optimal traction models were used to determine the desired value of traction by observing changes such as traction and slippage in real agrobot robots a control input in the traction controller. The traditional PID controller and Fuzzy Inference System model are used for optimal traction control. The proposed traction controller has been developed by compensating for the change in soil spectrum, the impact of stones during tillage, and the noises in the controller. Finally, TECS was experimentally verified by controlling a four-wheel skid steer robot prototype.

BACKGROUND: One of the challenges of modern agricultural industry is the integration of digital and robotic technologies, pursuing the reduction of the human factor in the production chain. Transition from manned agricultural transport and technological machines to autonomous ground mobile facilities (AGMF) is of particular interest. An agricultural tractor is a universal pull-push mobile system of the agricultural industry (ACI), so it can be used as an optimal platform for the design of the AGMF chassis. At the design stage of unmanned ground mobile systems, it is necessary to develop such a technical solution that allows the AGMF to function effectively without loss of mobility. The developed drawbar load has a significant impact on the mobility of the agricultural tractor on the ground. Therefore, in order to obtain an optimal technical solution, it is necessary to define the interrelation between the key characteristics of tractors, helping to select the primary parameters of the AGMF chassis. AIM: Definition of interrelation between technical and design parameters of wheeled and tracked agricultural tractors as mathematical dependencies in order to select primary parameters of the AGMF. METHODS: Building of the statistical model was based on compiling a sample of the existing models of agricultural tractors and determining the type of mathematical regularities between technical parameters as regression equations. RESULTS: Regression equations defining the interrelation between tractor engine power, gross weight, specific engine power and specific ground pressure were obtained, and primary technical parameters of AGMF were selected. CONCLUSION: The practical value of the study lies in the possibility of using the obtained parameters in the selection of primary parameters in the design, ensuring the competitiveness of the machine in a certain traction-power segment and compliance with agro-technological requirements.

Drones play a fundamental role in changes in the management of agricultural practices. With its great ability to efficiently monitor vast areas of land, it detects infestations early, allowing farmers to act quickly to mitigate crop damage. Furthermore, the use of drones enables the precise application of pesticides in affected areas, avoiding the rapid use of pesticides as well as the environmental impact. With the help of advanced data analysis, farmers achieve real planning control through strategic decisions. In short, drones are revolutionizing the management of agricultural practices, thus providing an efficient, sustainable and cost-effective approach to crop protection. The objective of this work is to compare the technical and economic efficiency of drones sprayed with agricultural tractors in soybean cultivation. The justification for this study is to provide a significant increase in this type of equipment in agriculture, as it avoids accumulation in the lines, in addition to a significant reduction in time and resources, reducing the environmental impact.

Agricultural tractors account for a substantial portion of greenhouse gas emissions in the farming sector, necessitating the development of sustainable machinery solutions. This study systematically reviews the latest advancements in electrification and smartification technologies for modern tractors, with a particular focus on algorithmic control strategies and their applications. Architecturally, the study provides a comparative analysis of four key configurations, pure electric, series hybrid, parallel hybrid, and series-parallel hybrid, detailing their respective advantages and challenges in energy efficiency and operational performance. From an algorithmic perspective, three primary methodologies—rule-based control strategies, optimization algorithms, and reinforcement learning—are examined for their applicability in energy management and control systems. The research further explores the integration of intelligent systems in unmanned farming scenarios, addressing critical challenges such as adaptive path planning in unstructured environments and multi-machine collaborative operations. A case study on battery-electric tractors demonstrates practical advancements in battery technology and energy management systems. Lifecycle cost analysis confirms the long-term economic viability of electrification, while outlining a forward-looking technological roadmap for sustainable and intelligent agricultural machinery.

The results of research of the possibility of improving the performance of diesel engine D-243 (type 4Ch 11/12,5) designed for agricultural tractor at its operation on cooled fuel are presented. The research was carried out on a computer model. Two variants of the external velocity response of the diesel engine are calculated: at a typical fuel temperature in the injector atomizer equal to 380 K; and when the fuel is cooled to 303 K (30 °C). The crankshaft speed of the diesel engine varied from 1000 to 2200 min –1 . The effective power and the operating torque of the diesel engine when operating on cooled fuel were higher by 16.9–17.8%. This result is mainly due to the growth of hourly fuel consumption by 16.4–16.8%. Specific fuel consumption differs within ±1.9 g/(kWh), and at cooling with favorable result in the most demanded speed range: 1800÷2200 min –1 . The main thermodynamic parameter, the internal efficiency, changes by ±1.1% relative to the first variant, which indicates that the quality of the diesel working process is preserved. Smokiness on cooled fuel is higher and has an absolute difference of 1–10%. Emission of nitrogen oxides increases by 0.9–1.4 g/(kWh). Greenhouse gas emissions, on the contrary, decrease by 0–6 g/(kWh). Due to the forced cooling of the fuel supplied it is possible to significantly improve the traction and power properties of the D-243 diesel engine when working on the external speed characteristic in the period of spring-summer operation. Environmental indicators do not change significantly. One should expect an increase in the lubricity of modern low-sulfur diesel fuel when it is cooled and an increase in the reliability of the fuel system during the specified period of the tractor's operation. At the same time, the changes in the fuel system operation are the same as in case of natural fuel cooling in the fall-winter period of operation in the conditions of continental climate of Western Siberia and other regions. Regulating parameters of the fuel system remain unchanged.

<div>In recent years, the powertrains of agricultural tractors have been transitioning toward hybrid electric configurations, paving the way for a greener future agricultural machinery. However, stability challenges arise in hybrid electric tractors due to the relative small capacity to perform power-intensive tasks, such as plowing and harvesting. These operations demand significant power, which are supplied by the electric power take-off system. The substantial disturbances introduced by the electric power take-off system during these tasks render conventional small-signal analysis methods inadequate for ensuring system stability. In this article, we first develop a large-signal model of the onboard power electronic systems, which includes components such as the diesel engine–generator set, batteries, in-wheel motors, and electric power take-off system. By employing mixed potential theory, we conduct a thorough analysis of this model and derive a stability criterion for the onboard power electronic systems under large disturbance conditions. Using this criterion, we estimate the stability boundaries of the onboard power electronic systems and evaluate the influence of various circuit parameters on its performance under large load fluctuations. Finally, case studies are presented to validate the proposed stability criterion and to demonstrate the impact of key circuit parameters on system stability.</div>

Accurate estimates of operational speed are crucial for modeling skidding productivity and planning efficient timber extraction. This study provides an event-level characterization of operational speeds in timber skidding operations in Romania, comparing cable skidders and farm tractors. Unlike most previous studies, which are based on limited datasets, this research uses a large, diverse dataset obtained through GNSS tracking over 98 field days at 14 sites, supplemented by synchronized video recordings. A total of 1.74 million seconds of data were collected, with 1.20 million seconds retained for analysis after data quality filtering. Descriptive statistics and Mann–Whitney U tests revealed significant differences in speed. For cable skidders, median speeds ranged from 1.6 km/h during maneuvering at the pre-skidding site to 5.0 km/h during unloaded driving to the pre-skidding site. For farm tractors, median speeds ranged from 2.2 km/h during maneuvering on the forest road to 6.0 km/h when driving unloaded to the pre-skidding site. The highest speeds were observed during unloaded driving, while the lowest occurred during maneuvering. Surprisingly, farm tractors outperformed cable skidders in some operational events due to more favorable terrain. The findings document GNSS-derived speed as a sufficiently reliable proxy for machine performance assessment and provide robust data for predictive modeling, operational planning, and equipment selection in forestry.

With the rapid development of automated wheeled vehicle technology, complex vehicle functions require extensive safety testing for verification. Compared with real-vehicle testing, scenario-based virtual testing, which constructs virtual environments to simulate real scenarios and efficiently evaluates vehicle safety and risk decision-making capabilities, has become a core means for the safety evaluation of automated wheeled vehicles. This paper outlines the research progress of scenario-based virtual testing for automated wheeled vehicles (including highway autonomous vehicles and off-highway autonomous vehicles); classifies three key technologies in highway scenarios, hazard evaluation, hazardous scenario generation and generalization, and acceleration evaluation; and reveals the challenges faced when existing methods are migrated to agricultural vehicles, engineering vehicles, etc., such as low scenario adaptability, multi-dimensional coupling of risk targets, and weak data foundation. This study finds that current technologies have formed a symmetric framework in highway scenarios, but there are significant adaptability problems when migrating to off-highway scenarios due to scenario asymmetry. To this end, this paper proposes ideas for realizing off-highway scenario testing by adopting methods such as dynamic safety distance reconstruction, multi-physics simulation, and digital twin-driven approaches, providing theoretical support for building a unified safety assessment platform for automated wheeled vehicles.

The operational stability of agricultural tractors is directly influenced by the mass distribution between axles, particularly when using mounted implements with variable loads. This study aimed to evaluate how different masses of a mounted sprayer (550 kg, 850 kg, and 1150 kg) and tire inflation pressures (151.7–193.1 kPa) affect the load distribution between axles, tire contact area, center of gravity (CG) displacement, and tractor lead ratio. A 3 × 4 factorial design was adopted with a statistical analysis of key parameters across 12 experimental combinations. The results demonstrated that increasing implement mass significantly shifted the load toward the rear axle, reducing the front axle load by up to 46% and displacing the CG rearward by more than 11 cm, thereby compromising stability. Tire pressure, as well as the interaction between mass and pressure, also exhibited statistically significant influence on load distribution and CG positioning while modulating the tire contact area. The lead ratio increased linearly with mass, exceeding the recommended 5% threshold when the sprayer was at full capacity. These findings indicate that while the implement mass exerts a dominant effect, tire pressure management represents a statistically relevant factor for stability, requiring integrated management that considers the interaction between ballasting and tire inflation to mitigate operational risks.

Abstract Studies investigating the effects of ambient noise on animals’ tolerance to predators and risk assessment typically rely solely on sound playbacks, neglecting multimodal perception by omitting visual or other contextual cues. To address this limitation, we tested whether the faster escape responses from an approaching potential predator observed in isolated noise playback studies—commonly attributed to heightened vigilance—actually result from the absence of typical contextual cues, such as the visible noise source (the “cross-modal sensory dissonance” hypothesis). If true, pairing noise with its typical cues should reduce or eliminate the difference in flight initiation distances (FIDs) between noise-exposed and non-noise-exposed individuals. We simultaneously exposed male barn swallows Hirundo rustica to both acoustic noise and its visual source—an agricultural tractor. Subsequently, we compared these results with those from our previous research, which utilized only tractor noise playbacks. Birds initiated flight at significantly greater distances when the noisy tractor was nearby. This effect was significantly greater than in the experiment that used only isolated noise playback. We conclude that the longer FIDs observed in barn swallows during noise-playback experiments reflect increased vigilance, rather than merely a response to the “dissonance” of hearing noise without seeing its source.

Abstract The article presents the results of a theoretical study on optimizing the life cycle costs of complex technical objects, using agricultural tractors as an example. A mathematical model has been developed to differentiate tractor reliability indicators under specific conditions of use. The developed model supports the cost optimization of tractors and similar high-complexity mechanical systems. An example of applying the mathematical model is provided, along with recommendations for an agricultural enterprise to enhance the profitability of tractor operations. Calculations have shown that the optimal indicator of the mean time between failures for complexity group 3 tractors of traction class 5-7 is the optimum value of the objective function within the 480-740 engine hours range. At the same time, the monitoring data of operational indicators indicate that the actual operating time for K744P2 tractors is 215 engine hours, and for Buhler Versatile 2375 tractors, it is 865 engine hours. Thus, the use of Buhler Versatile 2375 tractors from the point of view of cost optimization is 12.7% more economically advantageous than the use of K744P2 tractors in these conditions. However, the use of Buhler Versatile 2375 tractors also does not correspond to the optimum of the objective function, and further optimization by another 13.8% is possible here.

Applications of unmanned aerial vehicles (UAVS) in agriculture: A review

Maximizing agricultural tractor energy efficiency is crucial for sustainable farming. Tractors are one of the most popular machines in use in agriculture, and much of their use is dedicated to drawbar operations. Under these conditions, only up to 70 % of engine power is transferred to the soil, and this may even drop to 50 % on soils with poor mechanical properties. Recently, tyres which meet very high flexion standards have hit the market and to date, no study has performed a thorough full-vehicle traction analysis of vehicles equipped with such standards. This paper investigated the influence of tyres on vehicle performance and efficiency. Moreover, a cost analysis of the new tyre technology was carried out to assess the duration of use necessary for farmers to recoup the financial investment this new tyre technology requires. The analysis comprised steady-state drawbar tests on two soil types using a tractor rated at 230 kW and equipped with wheel force transducers. Key performance indicators were calculated from the collected data. Results showed superior traction on softer soil, where the mean vehicle traction ratio was 6.4 % higher than on firmer soil, highlighting tyre set performance differences. However, traction efficiency was 17.5 % greater on firmer soil. Very high flexion tyres resulted in improved indicators in both soils and despite the greater cost of tyres using the new standard, farmers may obtain economic benefits even within a year if such tyres are mostly used in field operations and on soft soils. • Reducing fuel use in field operations increases focus on traction efficiency. • Tyre technology greatly impacts tractor and transmission efficiency. • Traction efficiency is measured using Wheel Force Transducers on the tractor. • Very-High Flexion tyres develop higher drawbar force under certain slip conditions. • Very-High Flexion tyres had a lower cost per hectare than standard tyre sets.

Improved adaptive iterative learning trajectory tracking control with adaptive high-order internal model for autonomous farming vehicle

This study describes a novel adaptive free-will arbitrary time sliding mode controller (AFWATSMC) designed to improve the performance of a three-phase rectifier in an autonomous oil palm grabber vehicle (Robot Autonomous Mechanical Buffalo Grabber (MBG)). The graber, initially powered by a diesel engine with an uncontrolled rectifier, was upgraded to support intelligent systems that require stable DC voltage management. To address the limitations of conventional rectifiers, the suggested AFWATSMC integrates adaptive factors to improve the performance of the original free-will arbitrary time algorithm. The key innovation of this work lies in combining the adaptive sliding-mode control structure with the free-will arbitrary convergence time algorithm, permitting user-defined system settling time nevertheless of dynamic uncertainties (system parameters and initial conditions), a capability not demonstrated in prior rectifier control strategies to the best of the current knowledge. An optimized control laws using genetic algorithm (GA) and particle swarm optimization (PSO) is suggested to tune the parameters using MATLAB Simulink and coding. A smooth waveform with reduced ripple factor was achieved for the DC output of the alternator with a total improvement of 75.47%; the AC output alternator current exhibited an enhanced sinusoidal shape, a reduction of the total harmonic distortion (THD) with a 46.69% improvement, and an achievement of unity power factor of 0.20% improvement was obtained compared to another adaptive SMC.

Skidding is one of the most important methods for wood extraction globally, necessitating updated models to assess its performance based on the technical characteristics of the fleet in use. Based on a nation-wide, all-season dataset, this paper aimed to develop time and fuel consumption models for currently used cable skidders and farm tractors fitted for skidding in Romania. Although some statistical assumptions were not met, our models characterized the performance well in terms of time and fuel consumption, allowing for a differentiation in performance between skidders and farm tractors. For skidders, cycle time was explained to a degree of 58% (R2 = 0.58) by payload volume, number of pieces, and extraction distance, highlighting the importance of these variables when assessing cycle time performance of machines equipped with a double-drum winch. In contrast, for farm tractors, cycle time was explained solely by extraction distance (R2 = 0.87), which indicates a lower variability induced by payload size and number of pieces for machines equipped with a single-drum winch. Similar models were developed for fuel consumption, showing the significance of payload volume and extraction distance for skidders (R2 = 0.54) and extraction distance alone (R2 = 0.75) for farm tractors. Beyond an extraction distance of 50 m, the productivity of farm tractors decreased sharply, reaching half of that of skidders at an extraction distance of 1500 m, indicating a better time and fuel consumption performance of skidders, particularly in the case of excessively long extraction distances. Further studies should focus on finding effective methods and developing automated systems able to track the performance of operations and keep the pace with improvements in machine performance.

During headland manoeuvres of agricultural tractors, self-propelled machines, and autonomous agricultural vehicles, it is crucial not only to achieve the required working width but also to minimise the number of turns, path length, and time to reach the next field pass. The shortest trajectories can be obtained using Dubins curves or Reeds–Shepp paths. However, traversing such paths at constant velocity is only theoretically feasible. At the junctions between path segments, either the vehicle must stop or the steering angle must change at an infinite rate. These points exhibit abrupt changes in acceleration components, resulting in infinite jerk. This study presents the use of transition curves for executing U-turns and Ω-turns during headland manoeuvres. Implementing curves with gradually varying curvature ensures smooth transitions between trajectory segments, reducing sudden direction changes and improving motion dynamics. The curvature and tangent angle are defined using trigonometric functions. For the designed trajectory, kinematic parameters, including wheel steering angles, were determined for two models of agricultural tractors. The results provide a solid foundation for future research on refining transition curve models and integrating the proposed solutions with agricultural vehicle control systems.

The integration of advanced technologies in agriculture, known as Agriculture 4.0, aims to optimize practices, enhance productivity, and improve sustainability. Despite significant advancements in precision agriculture, ploughing operations have seen limited technological growth, even though they are among the most power-demanding and widely used soil preparation methods. Traditional on-field ploughing tests are irreversible, time-consuming, and costly, highlighting the need for a comprehensive virtual model of ploughing operations within a simulated environment. This study presents the development of a high-fidelity analytical model for ploughing, implemented in a real-time multibody simulation platform, both in software and Human-In-The-Loop (Hu-IL) configurations. The simulation environment incorporates a tractor model rigidly connected to the plough model, receiving contact forces from the field model. The model outputs vehicle dynamics information and ploughing operation data, allowing for operator inputs or simulated inputs. The model is used to perform a sensitivity analysis on ploughing parameters, including tractor speed, soil hardness, ploughing depth, and the number of furrows, to evaluate their impact on energy consumption and operational efficiency. In literature each component (tractor, plough, soil, etc.) is generally analyzed separately form the other; this paper aims to combine all the key factors that contribute to overall fuel consumption instead, considering the non-linearities of each subsystem.