Statistical model for analysis of mass, power and traction characteristics of agricultural tractors

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.