An Object-Oriented Program to Predict Tractor
and Machine System Performance
Saad A. Al-Hamed and Abdulrahman A. Al-Janobi
Agricultural Engineering Department, King Saud University
P.O. Box 2460, Riyadh 11451, Saudi Arabia
Abstract
An object-oriented program in Visual C++ that calculates implement draft requirement
and predicts the performance of tractor-implement system was developed to use in farm
machinery management and educational and research purposes. The simulation program
finds the optimum field speed that matches the pull provided by a tractor with an implement
draft requirement and presents the performance parameters of the tractor-implement system.
The program has been tested with databases containing information of a number of tractors
and implements and has proven to be very user-friendly and efficient to meet the
requirement.
Introduction
Computer models and simulation programs for predicting the performance of tractors
and implements help researchers to evaluate various farm machinery systems to determine
the relative merits of each system. Proper selection of tractor and implement for a particular
farm situation can be determined from the performance parameters obtained by these models
and simulation programs. As field machines contribute a major portion of the total cost of
crop production systems, proper selection and matching of farm machinery is essential to
reduce significantly the cost of ownership and farm machinery use.
The availability of data relating to draft requirement of tillage implements is an
important factor in selecting suitable tillage implemts for a particular farm situation. The
computer models and simulation programs help farm managers and consultants to predict
draft and power requirment of tillage implements on different soil types and conditions to
determine correctly the proper size of tractor required. Therefore, by using accurate draft
data, the operating costs of both tractors and implements can be minimized. Many studies
have been conducted to measure draft and power requirements of tillage implements
operating on various soil conditions. Mathematical models have also been developed by
researchers to predict draft and power requirements of tillage implements. Grisso et al.
(1994) reviewed work reported by different researchers in measuring draft and power
requirements of the most common tillage implements. But with computer models and
simulation programs, the time and cost in coducting the tillage experiments can be saved to a
great extent provided database concerning specification parameters of most common tractors
and implements are available.
The draft required to pull a tillage implement is basically a function of implement width,
operating depth, and the speed at which it is pulled. Draft also depends on soil conditions and
geometry of the tillage implement (Upadhyaya et al., 1984). The effect of speed on
implement draft depends on the soil type and the type of implement. It has been widely
reported that the draft forces on implements increase significantly with speed and the
relationship varies from linear to quadratic (Grisso et al., 1994). Depth has an obvious effect
on implement draft, although this relationship has been investigated only recently. Harrigan
and Rotz (1994) proposed a simple function for a range of soil conditions and machine
specific parameters to predict the draft of tillage and seeding implements under general
conditions, where draft per unit width or cross-sectional area of the tilled zone is a function of
soil type and the speed at which the implement is pulled. They presented reference tables for
soil and machine specific parameters. These tables and mathematical expressions were
adopted by the American Society of Agricultural Engineers to revise the ASAE Standards for
Agricultural Machinery Management Data as part of ASAE D497.4 to predict draft
requirements for tillage implements in several soil types (ASAE Standards, 2000).
Currently, many researchers in various fields are involved in developing object-oriented
programs, which are effective and simple to access, by users than programs developed in
traditional programming languages. Most of the operations in these programs are executed in
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response to an event linked to an object. As it is a landmark in the software field, it is also
necessitated to develop such programs to service the educational and research needs in
agricultural field. Al-Hamed and Al-Janobi (2001) presented a Visual C++ program to predict
the performance of two-wheel-drive (2WD) and four-wheel-drive/mechanical-front-wheeldrive (4WD/MFWD) tractors operating on agricultural soils for both bias-ply and radial tires.
The purpose of the present research is to illustrate a tractor and machine system performance
program developed in Visual C++ programming environment that involves predicting the
operating speed for a specific tillage operation by matching the characteristics of a load unit
and a power unit, such as an implement and a tractor respectively. Correct matching should
result in the optimum use of the tractor and the attached implement for a particular farm
situation. This is necessitated in farm situations where the availabilty of tractors and
implements are limited in number. In this situation a perfect match between the implements
and tractors cannot be made because of the improper values of the draft of the implements
and tractor pull. So it would be better to look for the best operating speed for the specific
tillage after selecting the required implement to use with the available tractor. It is rather
beneficial and cost effective than to select an implement for a specific tillage operation and to
determine the correct size of the tractor.
The objective of this research was to develop an interactive object-oriented program in
Visual C++ to predict tractor and machine system performance. Specifically, the program
has to 1) calculate the draft requirement for a given tillage implement and performance of a
selected tractor by accessing the corresponding databases containing the required information
and 2) perform tractor and machine system simulation to predict the operating speed suitable
for the tractor-implement combination and the performance parameters of the system.
Performance model equations
Performance of tractors and implements depends on many factors.
Important
performance factors related to the tractor are engine power, weight distribution on drive
wheels, tire type, number of tires, travel speed, hitch type, and soil surface.
For the
implement, important performance factors are implement width, tillage depth, soil texture,
and the speed at which it is pulled. In our previous work (Al-Hamed & Al-Janobi, 2001), the
traction prediction equations presented by Brixius (1987) were used in the development of
the computer model for predicting tractor performance. The present work involves prediction
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of draft requirements of a number of tillage implements in addition to the prediction of tractor
performance. For the draft calculations, equations and other required parameters are adopted
from ASAE Standards (2000).
The performance of agricultural machines is measured by the rate and quality at which
the operations are completed. Rate is an important measure and for most of the agricultural
field machines it is reported as area per hour. This performance measure is called field
capacity of the machine and it is the most commonly used measure of machine performance.
Field capacity depends upon the achievable field speed and the efficient use of time of the
field machines. Field speed may be limited by heavy yields, rough ground, and adequacy of
operator control. The time dependent parameter, field efficiency is affected by irregularly
shaped fields, heavy yields, and high capacity machines. Typical ranges of speeds and field
efficiencies for most of the field machines can be found in ASAE Standards (2000). With an
established field efficiency, the equation for effective field capacity of the machine given by
Hunt (1995) is as follows:
C
S W Ef
(1)
c
where:
C is effective field capacity in ha/h;
S is speed in km/h;
W is machine width in m;
Ef is field efficiency in decimal; and
c is a constant, 10.
For a tractor-implement system, it is necessary to know the implement draft requirement.
Draft is defined as the force required to pull an implement in the horizontal direction of
travel. For seeding implements and minor tillage tools operated at shallow depths, draft is
primarily a function of the implement width and the speed at which it is pulled. For tillage
tools operated at deeper depths, draft also depends upon soil texture, tillage depth, and
geometry of the tool. The mathematical expression for typical draft requirements of tillage
implements provided by ASAE Standards (2000) is as follows:
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

D  Fi A  B( S )  C ( S ) 2 W T
(2)
where:
D is implement draft in N;
F is a dimensionless soil texture adjustment parameter;
i is 1 for fine, 2 for medium and 3 for coarse textured soils;
A, B, C
are machine-specific parameters;
S is field speed in km/h;
W is machine width in m or number of rows or tools; and
T is tillage depth in cm for major tools, 1 (dimensionless) for minor tillage tools
and seeding implements.
Machine-specific parameters and soil texture adjustment parameters for most tillage and
seeding implements are presented in the ASAE Standards (2000). The Constant parameter, A
is a function of soil strength, whereas coefficients of speed parameters, B or C are related to
soil bulk density. Soil is categorized as fine, medium, and coarse textured soils. These
categories are described as corresponding to clay, loamy, and sandy soils. Ranges of typical
speeds for most of the field machines are also given in the ASAE Standards (2000).
Tractor and machine system performance program
An event-driven, object-oriented, user friendly, application program was needed for
predicting performance of tractor and machine system to use in farm machinery management
and educational and research purposes. Visual C++ environment containing several windows
that serve specific purposes in the development process was used to develop this program.
After the application development was completed, it was converted to a free-standing
executable version in order to run the program directly on the Windows desktop, without
starting up the Visual C++ environment.
The tractor and machine system performance program mainly consists of three sections,
menu, Edit/View database, and simulate as shown in Fig. 1. Each section has a number of
subsections based on the design criteria for the program development. The program starts
with an opening screen as shown in Fig. 2. The screen consists of a menu bar with options
About and Exit and two frames. A set of options under the title Edit/View Data to access five
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databases of tractor specifications, traction constants, bias-ply, radial, and front tire data and
an Edit/View button are enclosed in one frame, whereas the other frame encloses a simulate
button to predict the performance of the selected tractor-implement system. Also there are a
set of check circles besides the options in the Edit/View Data frame to select the desired
option. The operation of the opening screen relating to various parameters associated with a
tractor database was discussed in Al-Hamed and Al-Janobi (2001).
A tractor of a particular model can be selected from a tractor selection database, which
contains a number of tractors manufactured by different companies and the corresponding
model number. This database is linked to the tractor specification database and in effect
linked to the other databases. Corresponding to a selected tractor and model, the various
inputs from the different databases can be fed to the tractor and machine parameters
calculation part of the program. Tractor and machine parameters screen as shown in Fig. 3
displays specifications of a selected tractor and model, soil cone index, machine width, field
area, field efficiency, and machine draft requirement. This input data set could be displayed
to the user for any change if needed without affecting the databases.
The draft requirement for a selected implement is initially calculated corresponding to a
typical speed by clicking the draft calculator button in the Tractor and machine parameters
screen. The program control is transferred to the Draft calculator screen as shown in Fig. 4.
The screen consists of two database grids, one with soil texture and the other with implement
name and description. Both the database grids are enclosed in a frame and with the help of
vertical and horizontal scroll bars the contents of them are moved around the screen for
accessible to the user. The screen also contains a frame which encloses four edit control
objects, depth, width, number of rows, and number of tools, and another to input for expected
speed. Once the soil texture and implement are selected, two of the four edit control objects
in the frame are unlocked and made available to view and change as desired. The depth
object is primarily made available for all implements, whereas the other objects depend on
the type and geometry of the implement. Clicking of the Calculate Draft button calculates the
draft requirement for the selected implement and soil texture and the numerical value is fed to
the tractor and machine parameters screen.
The simulation part of the program to match a tractor and implement for optimum
performance and predict the system performance parameters is done by clicking the next
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button in the Tractor and machine parameters screen (Fig. 3). The flow diagram of the
simulation part of the program is shown in Fig. 5. The simulation begins with an assumed
maximum no load speed of 18 km/h. This speed is adopted after considering 30% slip on the
average maximum field speed range of 11-13 km/h of most of the common field machines
(ASAE Standards, 2000). The tractor simulation is performed as presented by Al-Hamed and
Al-Janobi (2001). The system simulation looks for three cases of implement draft
requirement as illustrated in Fig. 6. The three cases shown in the figure represent the
variation of draft against speed for a moldboard plow. The three cases are generated with a
comparison between the tractor pull and the implement draft requirement. They are
corresponding to low and high implement drafts relative to the tractor pull and implement
draft very close to the tractor pull. The first two cases are generated when there is a mismatch
between the selected tractor and implement. Low implement draft case is examined by the
simulation program at the maximum no load speed. If the implement draft requirement is less
than what the tractor can provide with its pull at maximum speed, the simulation program is
stopped after outputing the tractor and machine system performance parameters
corresponding to the maximum speed. The output also alerts that the given implement draft is
low. High implement draft case occurs at a low speed when the simulation program is
continued with reduced no load speed with no convergence. At this low speed, the implement
draft is greater than the high tractor pull as shown in Fig. 6. Here also the simulation program
is stopped after outputting the system performance parameters at the lowest possible field
speed and giving an alert for the high implement draft. The third case occurs at a range of
field speed upon decrementing from the maximum no load speed, where the implement draft
requirement is within the range of tractor pull. When the program is met with this case, the
control is transferred next to a testing condition to obtain an optimum field speed, where the
tractor pull and the implement draft requirement are very close to each other.
The testing condition is whether the absolute value of the difference between the tractor
pull and the implement draft requirement greater than a tolerance of 0.5 kN. For the first time
the implement draft requirement obtained from the draft calculator is used. This draft value is
corresponding to an assumed typical field speed of 7 km/h, which is approximately an
average field speed of most of the common field machines (ASAE Standards, 2000). It is
higher than the tractor pull corresponding to the maximum no load speed. So the test
condition becomes true and the maximum no load speed is decremented by 0.01 km/h. Then
the control is transferred to the simulation part of the program and tractor simulation is
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performed with the new reduced speed, keeping the implement draft requirement value the
same. This process is repeated until the testing condition becomes false. Then the implement
draft requirement is recalculated based on the actual speed found by tractor simulation. After
this the program enters in a loop and the execution is continued until the absolute value of the
difference between two consecutive values of implement draft requirement is less than or
equal to a tolerance of 0.5 kN. Then the field capacity and actual use of time of the machine
are determined for the typical field speed.
At the end, the program converges to a typical field speed, at which the implement draft
requirement and the tractor pull are close to each other with the latter more predominant for
the system to be operated effectively. This required field speed gives the optimum
performance for the tractor-implement system. Tractor and machine system performance
parameters such as tractive efficiency, dynamic weight on front and rear axles, motion
resistance ratio, net traction ratio, wheel slip, actual speed, drawbar pull, drawbar power,
dynamic traction ratio (DTR), machine draft, operating no-load speed, effective field
capacity, and actual operating hours are predicted for the selected tractor-implement system.
The screen with these parameters is shown in Fig. 7.
Testing of the program
The program was tested with selected tractors and implements from the databases
incorporated in the program and found as an excellent package for selection of tractor and
implement for particular farm situations and predicting performance parameters of tractorimplement system after a perfect match is made between them. It was also found that the
screens in the program were intuitive to users and highly flexible in specifying the results
from the simulation. Figures 3,4, and 7 illustrate the results of predicting performance
parameters of a tractor-implement system after a match was made between the tractor, MF
3090 and the implement, moldboard plow at a typical field speed of 6.7 km/h for medium
textured soil. Figures 8 and 9 show the results of predicting performance parameters of
tractor-implement system with alerts when there was a mismatch between them due to high
and low draft requirement of the implements. High draft case occurred when the tractor
operated in 2WD mode attempted to pull the same moldboard plow, whereas low draft case
occurred when a field cultivator of nine tools was used to match with the same tractor.
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Conclusion
An object-oriented program in Visual C++, to predict tractor and machine system
performance, was developed for use in farm machinery management and educational and
research purposes. For a given tractor and implement, the simulation program finds the
optimum field speed and predicts the tractor-implement system performance parameters. For
the users, this program, developed in visual programming environment, is highly flexible and
easy to learn and operate compared to programs developed in traditional languages. With the
event-driven visual components in the program, the user can edit or expand the databases of
tractors and implements and manipulate the required task in the desired way.
References
[1] Al-Hamed, S.A. and A.A. Al-Janobi (2001). A program for predicting tractor
performance in Visual C++. Computers and Electronics in Agriculture, 31:137-149.
[2] ASAE Standards (2000). ASAE D497.4 Agricultural machinery management data.
ASAE, St. Joseph, MI 49085.
[3] Brixius, W.W. (1987). Traction prediction equations for bias ply tires. ASAE Paper No.
87-1622. ASAE, St. Joseph, MI 49085.
[4] Grisso, R.D., M. Yasin and M.F. Kocher (1994). Tillage implement forces operating in
silty clay loam. ASAE Paper No. 94-1532. ASAE, St. Joseph, MI 49085.
[5] Harrigan, T. M. and C.A. Rotz (1994). Draft of major tillage and seeding equipment.
ASAE Paper No. 94-1533. ASAE, St. Joseph, MI 49085.
[6] Hunt, D. (1995). Farm power and machinery management, 9th Ed., Iowa State University
Press, Ames, p.5.
[7] Upadhyaya, S.K., T.H. Williams, L.J. Kemble and N.E. Collins (1984). Energy
requirement for chiseling in coastal plain soils. Transactions of the ASAE, 27(6): 16431649.
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