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In order to optimize tractor design and optimize efficiency during tillage operation, it is essential to verify the impact through field tests on factors affecting the tractor load. The objectives of this study were to investigate the effect of tillage depth on power transmission efficiency of 42 kW power agricultural tractor during moldboard plowing. A load measurement system and a tillage depth measurement system were configured for field tests. To analyze the effect of tillage depth on power transmission efficiency and fuel consumption, the data measured in the three-repeated field test were classified according to tillage depth. As the tillage depth increased from 11 cm at the top of the hardpan to 23 cm at the deepest, the required power of the engine increased by approximately 13% from 35.48 kW to 40.11 kW, and the power transmission efficiency also increased significantly from 66% to 95%. Among them, the power transmission efficiency of the rear axle was significantly increased from 38% to 59%, which was the most affected. As the tillage depth increased, the overall power requirement is greatly increased due to the resulting workload, but the fuel consumption and the specific fuel consumption are reduced because the engine speed of the tractor is reduced. As the tillage depth increased from 11 cm to 23 cm, the fuel consumption rate was rather reduced by 13.5% as the engine rotational speed decreased 11.3% due to the increase work load of tractor. In addition, the specific fuel consumption decreased from 302.44 g/kWh to 236.93 g/kWh, showing a fuel consumption saving of up to 21.7% during moldboard plow. In addition, as the tillage depth increased, the ratio of the value excluding the mechanical and hydraulic power requirements has significantly decreased from 34% to 5% as the power transmission efficiency increases. This study considers the soil properties according to the soil depth, as well as the power transmission efficiency and fuel consumption rate. The research results can provide useful information for research on power transmission efficiency and selection of an appropriate power source of agricultural tractor according to tillage depth during moldboard plowing and are expected to be used in various ways as basic studies of digital farming research in agricultural machinery.
Yeon-Soo Kim; Wan-Soo Kim; Abu Ayub Siddique; Seung-Yun Baek; Seung-Min Baek; Su-Hwan Cheon; Sang-Dae Lee; Kyeong-Hwan Lee; Dong-Hyuck Hong; Seong-Un Park; Yong-Joo Kim. Power Transmission Efficiency Analysis of 42 kW Power Agricultural Tractor According to Tillage Depth During Moldboard Plowing. Agronomy 2020, 10, 1263 .
AMA StyleYeon-Soo Kim, Wan-Soo Kim, Abu Ayub Siddique, Seung-Yun Baek, Seung-Min Baek, Su-Hwan Cheon, Sang-Dae Lee, Kyeong-Hwan Lee, Dong-Hyuck Hong, Seong-Un Park, Yong-Joo Kim. Power Transmission Efficiency Analysis of 42 kW Power Agricultural Tractor According to Tillage Depth During Moldboard Plowing. Agronomy. 2020; 10 (9):1263.
Chicago/Turabian StyleYeon-Soo Kim; Wan-Soo Kim; Abu Ayub Siddique; Seung-Yun Baek; Seung-Min Baek; Su-Hwan Cheon; Sang-Dae Lee; Kyeong-Hwan Lee; Dong-Hyuck Hong; Seong-Un Park; Yong-Joo Kim. 2020. "Power Transmission Efficiency Analysis of 42 kW Power Agricultural Tractor According to Tillage Depth During Moldboard Plowing." Agronomy 10, no. 9: 1263.
In general, the tractor axle torque is used as an indicator for making various decisions when engineers perform transmission fatigue life analysis, optimal design, and accelerated life testing. Since the existing axle torque measurement method requires an expensive torque sensor, an alternative method is required. Therefore, the aim of this study is to develop a prediction model for the tractor axle torque during tillage operation that can replace expensive axle torque sensors. A prediction model was proposed through regression analysis using key variables affecting the tractor axle torque. The engine torque, engine speed, tillage depth, slip ratio, and travel speed were selected as explanatory variables. In order to collect explanatory and dependent variable data, a load measurement system was developed, and a field experiment was performed on moldboard plow tillage using a tractor with a load measurement system. A total of eight axle torque prediction regression models were proposed using the measured calibration dataset. The adjusted coefficient of determination (R2) of the proposed regression model showed a range of 0.271 to 0.925. Among them, the prediction model E showed an adjusted R2 of 0.925. All of the prediction models were verified using a validation set. All of the axle torque prediction models showed an mean absolute percentage error (MAPE) of less than 2.8%. In particular, Model E, adopting engine torque, engine speed, and travel speed as variables, and Model H, adopting engine torque, tillage depth and travel speed as variables, showed MAPEs of 1.19 and 1.30%, respectively. Therefore, it was found that the proposed prediction models are applicable to actual axle torque prediction.
Wan-Soo Kim; Yong-Joo Kim; Seung-Yun Baek; Yeon-Soo Kim; Seong-Un Park. Development of a Prediction Model for Tractor Axle Torque during Tillage Operation. Applied Sciences 2020, 10, 4195 .
AMA StyleWan-Soo Kim, Yong-Joo Kim, Seung-Yun Baek, Yeon-Soo Kim, Seong-Un Park. Development of a Prediction Model for Tractor Axle Torque during Tillage Operation. Applied Sciences. 2020; 10 (12):4195.
Chicago/Turabian StyleWan-Soo Kim; Yong-Joo Kim; Seung-Yun Baek; Yeon-Soo Kim; Seong-Un Park. 2020. "Development of a Prediction Model for Tractor Axle Torque during Tillage Operation." Applied Sciences 10, no. 12: 4195.
The objectives of this study were to develop a real-time tillage depth measurement system for agricultural tractor performance analysis and then to validate these configured systems through soil non-penetration tests and field experiment during plow tillage. The real-time tillage depth measurement system was developed by using a sensor fusion method, consisting of a linear potentiometer, inclinometer, and optical distance sensor to measure the vertical penetration depth of the attached implement. In addition, a draft force measurement system was developed using six-component load cells, and an accuracy of 98.9% was verified through a static load test. As a result of the soil non-penetration tests, it was confirmed that sensor fusion type A, consisting of a linear potentiometer and inclinometer, was 6.34–11.76% more accurate than sensor fusion type B, consisting of an optical distance sensor and inclinometer. Therefore, sensor fusion type A was used during field testing as it was found to be more suitable for use in severe working environments. To verify the accuracy of the real-time tillage depth measurement system, a linear regression analysis was performed between the measured draft and the predicted values calculated using the American Society of Agricultural and Biological Engineers (ASABE) standards-based equation. Experimental data such as traveling speed and draft force showed that it was significantly affected by tillage depth, and the coefficient of determination value at M3–Low was 0.847, which is relatively higher than M3–High. In addition, the regression analysis of the integrated data showed an R-square value of 0.715, which is an improvement compared to the accuracy of the ASABE standard prediction formula. In conclusion, the effect of tillage depth on draft force of agricultural tractors during plow tillage was analyzed by the simultaneous operation of the proposed real-time tillage depth measurement system and draft force measurement system. In addition, system accuracy is higher than the predicted accuracy of ± 40% based on the ASABE standard equation, which is considered to be useful for various agricultural machinery research fields. In future studies, real-time tillage depth measurement systems can be used in tractor power train design and to ensure component reliability, in accordance with agricultural working conditions, by predicting draft force and axle loads depending on the tillage depth during tillage operations.
Yeon-Soo Kim; Taek-Jin Kim; Yong-Joo Kim; Sang-Dae Lee; Seong-Un Park; Wan-Soo Kim. Development of a Real-Time Tillage Depth Measurement System for Agricultural Tractors: Application to the Effect Analysis of Tillage Depth on Draft Force during Plow Tillage. Sensors 2020, 20, 912 .
AMA StyleYeon-Soo Kim, Taek-Jin Kim, Yong-Joo Kim, Sang-Dae Lee, Seong-Un Park, Wan-Soo Kim. Development of a Real-Time Tillage Depth Measurement System for Agricultural Tractors: Application to the Effect Analysis of Tillage Depth on Draft Force during Plow Tillage. Sensors. 2020; 20 (3):912.
Chicago/Turabian StyleYeon-Soo Kim; Taek-Jin Kim; Yong-Joo Kim; Sang-Dae Lee; Seong-Un Park; Wan-Soo Kim. 2020. "Development of a Real-Time Tillage Depth Measurement System for Agricultural Tractors: Application to the Effect Analysis of Tillage Depth on Draft Force during Plow Tillage." Sensors 20, no. 3: 912.