Search Results

Tractor weight transfer is the most common farm-related cause of fatalities nowadays. As in India it is getting mandatory for all safety devices across all HP ranges. Considering any changes in the weight from an attachment such as Rops, PTO device, tow hook and draw bar etc. can shift the center of gravity towards the weight. center of gravity is higher on a tractor because the tractor needs to be higher in order to complete operations over crops and rough terrain. Terrains, attachments, weights, and speeds can change the tractor’s resistance to turning over. This center of gravity placement disperses the weight so that 30 percent of the tractor’s weight is on the front axle and 70 percent is on the rear axle for two-wheel drive propelled tractors and it must remain within the tractor’s stability baseline for the tractor to remain in an upright position.

This study introduces a method to examine the flow path of the lubricant inside a transmission housing of a tractor. A typical gearbox has several loads bearing elements which are in relative sliding motion to each other which causes heat to be released. The major sources of friction as well as heat are the meshing teeth between gears (sun/planet, planet/ring & power/range drive gear), thrust washers, thrust bearings and needle roller bearings. The churning of oil performs the vital function of both lubricating these sliding interfaces and cooling these sources of heat, thereby preventing failure of the gearbox. In this paper, we have applied VOF multiphase flow model and sliding meshing to simulate the fluid flow during splashed lubrication within a mating gear box. Lubrication oil dynamics and oil surface interaction with the air is modeled using VOF multiphase approach.

Connected vehicles technology is experiencing a boom across the globe. Vehicle manufacturers have started using telematics devices which leverage mobile connectivity to pool the data. Though the primary purpose of the telematics devices is location tracking, the additional vehicle information gathered through the devices can bring in much more insights about the vehicles and its working condition. Cloud computing is one of the major enabled for connected vehicles and its data-driven solutions. On the other hand, machine learning and data analytics enable a rich customer experience understanding different inferences from the available data. From a fleet owner perspective, the revenue and the maintenance costs are directly related to the usage conditions of the vehicle. Usage information like load condition could help in efficient vehicle planning, drive mode selection and proactive maintenance [1].