scholarly journals Simulation of Design Factors of a Clutch Pack for Power-Shift Transmission for an Agricultural Tractor

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7293
Author(s):  
Md. Abu Ayub Siddique ◽  
Wan-Soo Kim ◽  
Yeon-Soo Kim ◽  
Seung-Yun Baek ◽  
Seung-Min Baek ◽  
...  
Keyword(s):  
Simulation Model ◽  
Sensor Fusion ◽  
Precision Agriculture ◽  
Maximum Energy ◽  
Fusion Method ◽  
Power Shift ◽  
Clutch Engagement ◽  
Significant Difference ◽  
Design Factors ◽  
The Mathematical Model

The objective of this study is the simulation of the most affected design factors and variables of the clutch pack for the power-shift transmission (PST) of a tractor based measured data. The simulation model, the mathematical model of sliding velocity, a moment of inertia, and clutch engagement pressure of clutch pack were developed using the powertrain and configurations of the real PST tractor. In this study, the sensor fusion method was used to precisely measure the proportional valve pressure by test bench, which was applied to the simulation model. The clutch engagement times were found 1.20 s at all temperatures for determined factors. The engagement pressures have a significant difference at various temperatures (25 to 100 °C) of the hydraulic oils after the 1.20 s but the most affected factors were satisfied with the simulation conditions that ensure the clutch engagement on time. Finally, this sensor fusion method is believed to be helpful in realizing precision agriculture through minimization of power loss and maximum energy efficiency of tractors.

scholarly journals Simulation of Fuel Consumption Based on Engine Load Level of a 95 kW Partial Power-Shift Transmission Tractor

Agriculture ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 276
Author(s):  
Md. Abu Ayub Siddique ◽  
Seung-Min Baek ◽  
Seung-Yun Baek ◽  
Wan-Soo Kim ◽  
Yeon-Soo Kim ◽  
...  
Keyword(s):  
Simulation Model ◽  
Fuel Consumption ◽  
Input Parameter ◽  
Load Level ◽  
Regression Equations ◽  
Exponential Relationship ◽  
Engine Load ◽  
Power Shift ◽  
Significant Difference ◽  
Agricultural Tractor

This study is focused on the estimation of fuel consumption of the power-shift transmission (PST) tractor based on PTO (power take-off) dynamometer test. The simulation model of PST tractor was developed using the configurations and powertrain of the real PST tractor. The PTO dynamometer was installed to measure the engine load and fuel consumption at various engine load levels (40, 50, 60, 70, 80, and 90%), and verify the simulation model. The axle load was also predicted using tractor’s specifications as an input parameter of the simulation model. The simulation and measured results were analyzed and compared statistically. It was observed that the engine load, as well as fuel consumption, were directly proportional to the engine load levels. However, it was statistically proved that there was no significant difference between the simulation and measured engine torque and fuel consumption at each load level. The regression equations show that there was an exponential relationship between the fuel consumption and engine load levels. However, the specific fuel consumptions (SFC) for both simulation and measured were linear relationships and had no significant difference between them at each engine load level. The results were statistically proved that the simulation and measured SFCs were similar trends. The plow tillage operation could be performed at the gear stage of 7.65 km/h with higher working efficiency at low fuel consumption. The drawback of this study is to use a constant axle load instead of dynamic load. This study can provide useful information for both researchers and manufacturers related to the automated transmission of an agricultural tractor, especially PST tractor for digital farming solutions. Finally, it could contribute to the manufacturers developing a new agricultural tractor with higher fuel efficiency.

scholarly journals Reducing Topdressing N Fertilization with Variable Rates Does Not Reduce Maize Yield

2021 ◽  
Vol 13 (14) ◽  
pp. 8059
Author(s):  
Calogero Schillaci ◽  
Tommaso Tadiello ◽  
Marco Acutis ◽  
Alessia Perego
Keyword(s):  
Precision Agriculture ◽  
Stem Elongation ◽  
Maize Yield ◽  
Application Rate ◽  
N Fertilization ◽  
Economic Benefits ◽  
Growth Monitoring ◽  
Fixed Rate ◽  
Positioning Systems ◽  
Significant Difference

Proximal sensing represents a growing avenue for precision fertilization and crop growth monitoring. In the last decade, precision agriculture technology has become affordable in many countries; Global Positioning Systems for automatic guidance instruments and proximal sensors can be used to guide the distribution of nutrients such as nitrogen (N) fertilization using real-time applications. A two-year field experiment (2017–2018) was carried out to quantify maize yield in response to variable rate (VR) N distribution, which was determined with a proximal vigour sensor, as an alternative to a fixed rate (FR) in a cereal-livestock farm located in the Po valley (northern Italy). The amount of N distributed for the FR (140 kg N ha−1) was calculated according to the crop requirement and the regional regulation: ±30% of the FR rate was applied in the VR treatment according to the Vigour S-index calculated on-the-go from the CropSpec sensor. The two treatments of N fertilization did not result in a significant difference in yield in both years. The findings suggest that the application of VR is more economically profitable than the FR application rate, especially under the hypothesis of VR application at a farm scale. The outcome of the experiment suggests that VR is a viable and profitable technique that can be easily applied at the farm level by adopting proximal sensors to detect the actual crop N requirement prior to stem elongation. Besides the economic benefits, the VR approach can be regarded as a sustainable practice that meets the current European Common Agricultural Policy.

Validation of a Rapid Colorimetric Method with Field Soils

2017 ◽  
Vol 60 (4) ◽  
pp. 1271-1278 ◽  
Author(s):  
Sang Yoon Lee ◽  
Hyo Je Park ◽  
Cheol Woo Han ◽  
Seung Yun Lee ◽  
Gi Young Kweon
Keyword(s):  
South Korea ◽  
Precision Agriculture ◽  
Analytical Methods ◽  
Soil Phosphorus ◽  
Spectroscopic Method ◽  
Colorimetric Method ◽  
Laboratory Procedure ◽  
Laboratory Test Results ◽  
Significant Difference ◽  
Field Soils

Abstract. Regularly monitoring the variations in soil composition is an essential part of proper cultivation management. Some conventional soil characterization methods are often costly and require experienced labor. The spectroscopic method is a simpler procedure that minimizes experimental steps and is faster and more economical than conventional methods. Wide-ranging analytical methods have been developed to determine soil phosphorus concentrations in the field; however, no method has been commercialized. Analytical methods based on colorimetric Mehlich-3 and Lancaster soil tests, developed to reduce measurement time in laboratories in the U.S. and South Korea, have been efficient. However, due to laboratory procedures, the soil was pretreated and not verified with field soil. We tested the rapid colorimetric method, which is for on-site plant-available soil phosphorus tests in the field and allows reduced analysis time. The target accuracy of the field tests was >70% correlation with laboratory test results. This method consists of three steps: fast extraction, fast filtration, and fast color development. In a comparison of the rapid colorimetric method and the standard laboratory procedure, the R2 values were 0.78, 0.71, 0.72, and 0.74, respectively, for field soils collected in four regions of South Korea. However, the results showed significant differences in some areas. When the moisture content and electrical conductivity of soil from each region were included in the multiple regression analysis, the cross-validation results showed superior output with no significant difference (p > 0.05). Keywords: Colorimetry, Phosphorus, Precision agriculture, Sensor, Soil.

scholarly journals Engineering of Light Electric Commercial Vehicle

2020 ◽  
Vol 19 (1) ◽  
pp. 63-75
Author(s):  
R. Dorofeev ◽  
A. Tumasov ◽  
A. Sizov ◽  
A. Kocherov ◽  
A. Meshkov ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Electric Vehicle ◽  
Electric Motor ◽  
Field Tests ◽  
Angular Speed ◽  
Maximum Energy ◽  
Driving Cycle ◽  
Thermal Calculation ◽  
Technical Solutions ◽  
The Mathematical Model

The paper describes the process and results of the development of the light commercial electric vehicle. In order to ensure maximum energy efficiency of the developed vehicle the key parameters of the original electric motor. The article also presents the results of power electronic thermal calculation. For the mathematical model of the vehicle, the driving cycle parameters of the electric platform were determined in accordance with UNECE Regulations No 83, 84. The driving cycle was characterized by four successive urban and suburban cycles. The mathematical model also takes into account the time phases of the cycle, which include idling, vehicle idling, acceleration, constant speed movement, deceleration, etc. The model of the electric part of the vehicle was developed using MatLab-Simulink (SimPowerSystems library) in addition to the mechanical part of the electric car. The electric part included the asynchronous electric motor, the motor control system and the inverter. This model at the output allows to obtain such characteristics of the electric motor as currents, flows and voltages of the stator and rotor in a fixed and rotating coordinate systems, electromagnetic moment, angular speed of rotation of the motor shaft. The developed model allowed to calculate and evaluate the performance parameters of the electric vehicle. Technical solutions of the electric vehicle design were verified by conducting strength calculations. In conclusion, the results of field tests of a commercial electric vehicle are presented.

scholarly journals Inherent Reflectance Variability of Vegetation

Agriculture ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 246 ◽  
Author(s):  
Baabak Mamaghani ◽  
M. Grady Saunders ◽  
Carl Salvaggio
Keyword(s):  
Remote Sensing ◽  
Precision Agriculture ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Remote Sensing Data ◽  
Time Of Day ◽  
Unmanned Aircraft ◽  
P Value ◽  
Ground Sample ◽  
Significant Difference

With the inception of small unmanned aircraft systems (sUAS), remotely sensed images have been captured much closer to the ground, which has meant better resolution and smaller ground sample distances (GSDs). This has provided the precision agriculture community with the ability to analyze individual plants, and in certain cases, individual leaves on those plants. This has also allowed for a dramatic increase in data acquisition for agricultural analysis. Because satellite and manned aircraft remote sensing data collections had larger GSDs, self-shadowing was not seen as an issue for agricultural remote sensing. However, sUAS are able to image these shadows which can cause issues in data analysis. This paper investigates the inherent reflectance variability of vegetation by analyzing six Coneflower plants, as a surrogate for other cash crops, across different variables. These plants were measured under different forecasts (cloudy and sunny), at different times (08:00 a.m., 09:00 a.m., 10:00 a.m., 11:00 a.m. and 12:00 p.m.), and at different GSDs (2, 4 and 8 cm) using a field portable spectroradiometer (ASD Field Spec). In addition, a leafclip spectrometer was utilized to measure individual leaves on each plant in a controlled lab environment. These spectra were analyzed to determine if there was any significant difference in the health of the various plants measured. Finally, a MicaSense RedEdge-3 multispectral camera was utilized to capture images of the plants every hour to analyze the variability produced by a sensor designed for agricultural remote sensing. The RedEdge-3 was held stationary at 1.5 m above the plants while collecting all images, which produced a GSD of 0.1 cm/pixel. To produce 2, 4, and 8 cm GSD, the MicaSense RedEdge-3 would need to be at an altitude of 30.5 m, 61 m and 122 m respectively. This study did not take background effects into consideration for either the ASD or MicaSense. Results showed that GSD produced a statistically significant difference (p < 0.001) in Normalized Difference Vegetation Index (NDVI, a commonly used metric to determine vegetation health), R 2 values demonstrated a low correlation between time of day and NDVI, and a one-way ANOVA test showed no statistically significant difference in the NDVI computed from the leafclip probe (p-value of 0.018). Ultimately, it was determined that the best condition for measuring vegetation reflectance was on cloudy days near noon. Sunny days produced self-shadowing on the plants which increased the variability of the measured reflectance values (higher standard deviations in all five RedEdge-3 channels), and the shadowing of the plants decreased as time approached noon. This high reflectance variability in the coneflower plants made it difficult to accurately measure the NDVI.

scholarly journals Nurse Scheduling Using Genetic Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Komgrit Leksakul ◽  
Sukrit Phetsawat
Keyword(s):  
Genetic Algorithm ◽  
Simulation Model ◽  
Input Data ◽  
Level Of Service ◽  
Nurse Scheduling ◽  
Random Mutation ◽  
Scheduling Model ◽  
Hospital Staffing ◽  
Service Standards ◽  
The Mathematical Model

This study applied engineering techniques to develop a nurse scheduling model that, while maintaining the highest level of service, simultaneously minimized hospital-staffing costs and equitably distributed overtime pay. In the mathematical model, the objective function was the sum of the overtime payment to all nurses and the standard deviation of the total overtime payment that each nurse received. Input data distributions were analyzed in order to formulate a simulation model to determine the optimal demand for nurses that met the hospital’s service standards. To obtain the optimal nurse schedule with the number of nurses acquired from the simulation model, we proposed a genetic algorithm (GA) with two-point crossover and random mutation. After running the algorithm, we compared the expenses and number of nurses between the existing and our proposed nurse schedules. For January 2013, the nurse schedule obtained by GA could save 12% in staffing expenses per month and 13% in number of nurses when compare with the existing schedule, while more equitably distributing overtime pay between all nurses.

The Control and Model of Synchronous Generator on Ship

2012 ◽  
Vol 195-196 ◽  
pp. 1095-1101
Author(s):  
Le Luo ◽  
Lan Gao ◽  
Liang Chen ◽  
Liang Hu
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Simulation Model ◽  
Synchronous Generator ◽  
Excitation Control ◽  
Synchronous Generators ◽  
Simulation Test ◽  
Power Station ◽  
Model And Simulation ◽  
The Mathematical Model

This paper analyzes the characteristics of marine power station. The mathematical model and simulation model of synchronous generators AVR+PSS excitation control system was built. At last the simulation test of suddenly add load was did in MATLAB/simulink environment. The result shows that the excitation control system has well stability, rapidity and some robustness.

scholarly journals An evidential sensor fusion method in fault diagnosis

2016 ◽  
Vol 8 (3) ◽  
pp. 168781401664182 ◽  
Author(s):  
Wen Jiang ◽  
Boya Wei ◽  
Chunhe Xie ◽  
Deyun Zhou
Keyword(s):  
Fault Diagnosis ◽  
Sensor Fusion ◽  
Fusion Method
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