| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1732102 | Energy | 2015 | 8 Pages |
•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.
