کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1732102 | 1521461 | 2015 | 8 صفحه PDF | دانلود رایگان |
• Drawbar pull energy was assessed by tire parameters in soil bin facility.
• Adaptive neuro-fuzzy inference system was applied for the modeling of problem.
• Trimf with 3,3,3 denoted mean square error and R2 of 0.00236 and 0.995, respectively.
Determination of the required energy for drawbar pull of agricultural tractors plays a significant role in the characterization of the quality of tractors during different operations. Assessment of the effect of some tire parameters on drawbar pull energy was performed utilizing a single-wheel tester in a soil bin facility. To this aim, the potential of a global searching soft computing approach (i.e. adaptive neuro-fuzzy inference system) with various membership functions was evaluated. The tire parameters of velocity at three levels of 0.8, 1 and 1.2 m/s, wheel load at three levels of 2, 3 and 4 kN and slippage at three levels of 8, 12 and 15% were applied to single-wheel tester while four installed load cells were responsible for the measurement of drawbar pull. It was concluded that drawbar pull energy is a direct function of wheel load, velocity and slippage. Hence, the greatest value of 1.056 kJ corresponded to the wheel load of kN, slippage of 15% and velocity of 1.2 m/s. The outperforming model yielded mean square error and coefficient of determination values of 0.00236 and 0.995, respectively.
Journal: Energy - Volume 85, 1 June 2015, Pages 586–593