Regression Modeling of Fuel Cosumption Optimization of Rotary Blades of Power Tiller Under Sandy Clay Loam Condition

Abstract

Fuel consumption optimization is one of the selection criteria of tractor tillage implementation. However, studies that concern with various rotary blades of power tiller fuel consumption optimization model under sandy clay loam conditions has not so far been determined and documented. The objectives of this paper were to modify the fuel consumption mathematical model, optimize the objective function and to evaluate the efficiency of a “pick”, a “C”, an “I”, an “L” and a “J”-shaped rotary blades. Ultimately a modified fuel consumption mathematical model accounting for the integrated system parameters of various rotary blades was derived. The derived system parameters in this model include rotational velocity (N), rotor radius (R), depth of tillage (L_d), cutting width (Bw), velocity ratio (ã) and volume of soil tilled (V_st). Optimal solutions of these system parameters as well as the corresponding fuel consumption were obtained. To validate the model and test, sensitivity and correlation coefficient analysis were used. Results from the sensitivity analysis revealed that depth of tillage and cutting width were found to be highly significant parameters influencing fuel consumption requirement. Amongst the five rotary blades tested, however, depth of tillage of the “L” and the “J”-shaped were the most significant parameters to change fuel consumption requirement. The output of sensitivity analysis from the rate of depth of tillage showed a trend of reduction from 28.57% to 18.18 % for the “L” and 54.55% to 26.09 % for the “J”- shaped rotary blade. Consequently, fuel consumption rate reduced from 0.0843% to 0.0841% for the “L” and 0.272 % to 0.271 % for “J” -shaped. However, the cutting width of the “J” -shaped increased from 6.67 % to 7.69 %, while fuel consumption requirement rate increased from 0.017 % to 0.023 %. Similarly, correlation coefficient analysis revealed that depth of tillage and cutting width correlation coefficient (r) was predicted to be 0.7 and 0.5, respectively. Consequently, the p-value for depth of tillage was significant (p< 0.05), while for the cutting width was highly significant (p< 0.01).