A program for predicting tractor performance in Visual C++

Computers and Electronics in Agriculture 31 (2001) 137 149 www.elsevier.com/locate/compag A program for predicting tractor performance in Visual C++ S.A. Al-Hamed *, A.A. Al-Janobi Agricultural Engineering Department, King Saud Uni ersity, P.O. Box 2460, Riyadh, 11451, Saudi Arabia Received 6 May 2000; received in revised form 26 September 2000; accepted 2 October 2000 Abstract A tractor performance program that predicts the performance of two-wheel-drive (2WD) and four-wheel-drive/mechanical-front-wheel-drive (4WD/MFWD) tractors on agricultural soils for both bias-ply and radial tires was developed to meet the user requirements for both educational and research programs. The program was written in Visual C++ programming language as a new method of predicting 2WD and 4WD/MFWD tractor performance. The program provides an intuitive user interface by linking databases such as tractor specifications, tire data (front, bias-ply, and radial), and traction equation coefficients to predict the performance of a selected tractor and model. The program has been proven to be user friendly and efficient. 2001 Elsevier Science B.V. All rights reserved. Keywords: Tractor performance; Traction equation coefficients; Simulation; Visual programming 1. Introduction Computer models and simulation programs for predicting tractor performance help researchers to determine the relative importance of many factors affecting field performance of tractors without conducting expensive, as well as time consuming, field tests. They also help researchers and manufacturers to improve the tractor performance by comparing and analyzing various parameters that influence tractor performance. The rapid progress in developing new software and the trend in * Corresponding author. Fax: +9661-4678502. E-mail address: alhamed@ksu.edu.sa (S.A. Al-Hamed). 0168-1699/01/$ - see front matter 2001 Elsevier Science B.V. All rights reserved. PII: S0168-1699(00)00177-0

138 S.A. Al-Hamed, A.A. Al-Janobi / Computers and Electronics in Agriculture 31 (2001) 137 149 enhancing the existing application software and programming languages always tend to facilitate the interaction between users and computers. As a result, many computer modeling and simulation programs have been developed. Considerable research has been conducted in developing computer based models and simulation programs to service the educational and research needs in the farm machinery area of agricultural engineering. Zoz (1970) presented a graphical method for predicting tractor field performance. The method was useful for predicting drawbar pull, drawbar power, travel speed, and travel reduction of 2WD tractors under various soil conditions. Wismer and Luth (1972) outlined a set of empirical equations for the tractive performance of tires on agricultural (cohesive-frictional) soils. These equations described tractive characteristics of both towed and driven tires and these were used later by many researchers to develop tractive performance models for tractors. Clark (1985) proposed generalized forms of the Wismer and Luth model for a wider range of actual field conditions. Brixius (1987) presented equations to predict the tractive performance of bias-ply tires operating on agricultural soils as revisions of equations introduced by Wismer and Luth (1972). The new equations improved the prediction of tractive performance and extended the range of applications. These equations can be applied to wheeled vehicles ranging from lawn and garden tractors to earthmovers as long as the set of variables are within the applicable limits. The set of variables includes width-to-diameter ratio, deflection ratio, weight divided by width and diameter, and cone index. The applicable limits include all conditions typically encountered by agricultural tractor tires, except radial tires. Wheel torque, motion resistance, net traction and tractive efficiency were predicted as a function of soil strength, wheel load, slip, tire size, and tire deflection for both dual and single wheels. The equations can be used for radial tires by adjusting the equations coefficients as recommended by Brixius (1987). Zoz (1987) developed Lotus templates for predicting 2WD and 4WD/MFWD tractor performance for bias-ply tires on agricultural soils using the traction equations by Brixius (1987) and on concrete using the equations presented by Zoz and Brixius (1979). Evans et al. (1989) developed a traction prediction and ballast selection model based on the traction equations proposed by Brixius (1987) using the equation solving software TK Solver. The traction model developed for a specific small front wheel assist tractor operating on grass surface was demonstrated by adjusting the coefficients of traction equations. Grisso et al. (1992) demonstrated the flexibility of templates introduced by Zoz (1987) as an educational tool by comparing bias-ply versus radial tires, dual versus single tires, and the influence of travel speed, tire size, ballast distribution, and soil condition for 2WD and 4WD/MFWD tractors. An alternative calculation mode can be used to determine the required ballast weight to obtain a desired performance. This mode with an optimizing ballast scheme was used to predict the optimum wheel slip and maximum tractive efficiency for each comparison. Al- Hamed et al. (1994) revised the Lotus compatible templates from the Zoz (1987) spreadsheets. These revised templates were capable of predicting 2WD and 4WD/ MFWD tractor performance on agricultural soils for both bias-ply and radial

S.A. Al-Hamed, A.A. Al-Janobi / Computers and Electronics in Agriculture 31 (2001) 137 149 139 tractor tires. Comparison between the predicted and experimental results of a given number of tractors for the performance variables (wheel slip, drawbar pull, and tractive efficiency) showed that the templates performance was fair and acceptable. Computer models and simulation programs for predicting tractor performance were developed by many researchers using various programming tools. With the fast development in computer software and hardware, it is necessary to take advantage of the recently introduced programming tools such as Visual Basic and Visual C++ to develop software for the needs of educational and research programs in farm machinery. The availability of visual languages made programming easier for programmers and the programs written in visual programming environment are easily accessible to the users of them. Visual programming provides a set of screens, object buttons, scroll bars, and menus. The objects can be positioned on a form, and their behaviors are described through the use of a scripting language associated with each one. Visual programming is used for applications development, systems design, and simulations. They let users put more effort into solving their particular problem rather than learning about a programming language. As it seems to be an excellent tool for developing flexible and user friendly software for various applications, it is considered as a new approach to develop a program for predicting tractor performance. The objective of this research was to develop a tractor performance program in Visual C++ as a new method to predict performance of 2WD and 4WD/MFWD tractors for both bias-ply and radial tires. Specifically, the program has to predict the performance parameters for a given tractor by accessing databases concerning tractor specification, tire information, and traction equation coefficients. 2. Tractor performance model equations The traction prediction equations of Brixius (1987) have been used in the development of the computer program for predicting tractor performance. In this research, the following traction equations are considered and it will be shown that the program developed in Visual C++ programming language becomes rather easy for the user to predict the performance of a selected tractor and model Gross Traction, GT= T r (1) where T, torque applied to the wheel, and r, rolling radius of the tire. Part of the GT is required to overcome the motion resistance (MR) and the remainder is the net traction (NT). Therefore, Gross Traction, GT=MR+NT From the experimental data, the gross traction ratio is expressed as: GT W =A 1(1 e A 2B n )(1 e A 3s )+A 4 (2) (1a)

140 S.A. Al-Hamed, A.A. Al-Janobi / Computers and Electronics in Agriculture 31 (2001) 137 149 where A 1, A 2, A 3, and A 4, traction coefficients based on tire type (Table 1), W, dynamic wheel load, s, wheel slip and B n, mobility number. The mobility number (B n ), combining the wheel numeric (C n =CIbd/W), the deflection ratio ( /h), and the section width-to-diameter ratio (b/d) is expressed as: B n = CIbd 1+A 5 /h (3) W 1+A 6 b/d where A 5 and A 6, traction equation coefficients based on tire type (Table 1). The motion resistance ratio is defined as: MR W =A 7 +A B 4 + 0.5 s (4) n B n where A 7, traction equation coefficient based on tire type (Table 1). The motion resistance ratio of an unpowered wheel can be predicted with Eq. (4) by setting the slip dependent term (0.5 s/ B n ) equal to zero. Net tractive ratio is defined as: NT W =A 1(1 e A 2B n )(1 e A3s ) A 7 0.5 s. (5) B n B n The net traction is a force in direction of travel developed by the traction device and transferred to the vehicle. The net traction includes the force produced at the drawbar and the motion resistance of any unpowered wheels. Thus P=NT MR UP (6) where P, drawbar pull, and MR UP, motion resistance of unpowered wheels. Dynamic wheel load can be calculated in terms of static load, drawbar pull and dynamic weight transfer. Wheel slip (s) is expressed as: Table 1 Traction equation coefficients for bias-ply and radial tires Traction coefficient Bias-ply a Radial Recommended range a Mean value A 1 0.88 0.88 0.88 A 2 0.1 0.1 0.1 A 3 7.5 8.50 10.50 9.5 A 4 0.04 0.03 0.035 0.032 A 5 5 5 5 A 6 3 3 3 1 0.9 0.9 A 7 a From Brixius (1987).

S.A. Al-Hamed, A.A. Al-Janobi / Computers and Electronics in Agriculture 31 (2001) 137 149 141 Fig. 1. Flow diagram of tractor performance program. 367.1 AXP s= 1 V t W A 4 ln 1 100 (7) A 3 A 1 (1 e A 2 B n ) whereaxp, axle power, andv t, wheel speed at no-load. The tractive efficiency (TE) of a driving wheel is defined as: TE= NT (1 s). (8) GT The equations for bias-ply tires have been approved by the Power and Machinery Division ASAE Standards Committee (ASAE Standards, 2000). 3. Tractor performance prediction program A flexible, object oriented, user friendly, application program was needed for predicting performance of 2WD and 4WD/MFWD tractors on agricultural soils for both bias-ply and radial tires. Thus, a program written in Visual C++ programming language was developed specifically for this purpose.

142 S.A. Al-Hamed, A.A. Al-Janobi / Computers and Electronics in Agriculture 31 (2001) 137 149 The tractor performance program mainly consists of three sections, menu, Edit/View, 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 with options About and Exit, a panel with Edit/View button to access five databases of tractor specifications, traction constants, bias-ply, radial, and front tires data, and a simulate button to predict the performance of the selected tractor of a particular model. The tractor specification screen is shown in Fig. 3. The tractor specification database contains information such as makes and models of a number of agricultural tractors. The other parameters included are tractor power, tractor type (2WD, 4WD/MFWD), tire type and size, number of tires, static weight on front and rear axles, wheel base, draft height and angle, distance behind rear axle, and wheel speed at no-load. The soil parameter, cone index value is also included in this database. The user can edit, remove, or add a tractor and its specifications. The traction constants database screen is shown in Fig. 4 and it contains the coefficients for bias-ply and radial tires. The coefficients for radial tires used in the model were the mean values recommended by Brixius (1987). The user can change the values of the coefficients in the database. The tire databases for bias-ply, radial and front tires include parameters such as tire size, section width, overall diameter, static loaded radius, rated capacity, ply rating for bias-ply or symbol marking for radial, and tread code. A screen from one of these databases is shown in Fig. 5. A tractor selection database, as shown in Fig. 6, contains a number of tractors manufactured by different companies and the corresponding model numbers. This database is linked to the tractor specification database and in effect linked to the other Fig. 2. Opening screen of tractor performance program.

S.A. Al-Hamed, A.A. Al-Janobi / Computers and Electronics in Agriculture 31 (2001) 137 149 143 Fig. 3. Tractor and soil specification database screen. databases. Corresponding to a selected tractor and model, the various inputs from the different databases can be fed to the simulation part of the performance program. The input data set could be displayed to the user for any change if needed without affecting the databases. The performance of 2WD and 4WD/MFWD tractors was predicted by clicking the simulate button (see Fig. 2) on the opening screen. The flow diagram of the simulation part of the program is shown in Fig. 7. Prediction of performance parameters was done for a selected tractor and model. Tire data, soil cone index, and no load speed could be viewed and changed if needed prior to commencing simulation. At the beginning of simulation, initial values of tractive efficiency, current and previous, and static weights on front and rear wheels of the tractor were assigned. The simulation screens (tractor performance screens), shown in Figs. 8 and 9 are intuitive to users and highly flexible in specifying the type of output from the simulation. Tractor performance parameters such as tractive efficiencies, dynamic weights on front and rear axles, motion resistance ratio, net traction ratio, wheel slip, actual speed, drawbar pull, drawbar power, and dynamic traction ratio were predicted for the selected tractor and model. The screen with these parameters is shown in Fig.

144 S.A. Al-Hamed, A.A. Al-Janobi / Computers and Electronics in Agriculture 31 (2001) 137 149 9. The simulation continued until a convergence occurred in which the difference of two successive values of tractive efficiency was less than a tolerance of 0.001%. 4. Validation of the model The traction prediction equations of Brixius (1987) were used in the development of the computer model for predicting tractor performance. Al-Hamed et al. (1994) templates, a revision of Zoz (1987) templates were the basis for developing the simulation program written in Visual C++ programming language. Thus, to validate the model, predicted performance variables were compared with the results of Al-Hamed et al. (1994) spreadsheets for bias-ply and radial tires. The same numerical values up to two decimal digits of precision were obtained for the performance variables. The tractor performance program developed in visual programming environment was also illustrated by selecting an example Steiger ST 225 tractor from the tractor specification database. The results of the various stages of predicting tractor performance parameters are shown in Figs. 2 6 and 8, and 9. 5. Conclusion A computer based model and simulation program for predicting 2WD and 4WD/MFWD tractors performance on agricultural soil was developed in a Visual C++ programming environment for use in educational and research needs. The Fig. 4. Traction constants database screen.

S.A. Al-Hamed, A.A. Al-Janobi / Computers and Electronics in Agriculture 31 (2001) 137 149 145 Fig. 5. Tire specification database screens: (a) bias-ply tire; (b) radial tire; (c) front tire.

146 S.A. Al-Hamed, A.A. Al-Janobi / Computers and Electronics in Agriculture 31 (2001) 137 149 Fig. 5. (Continued) Fig. 6. Tractor selection database screen.

S.A. Al-Hamed, A.A. Al-Janobi / Computers and Electronics in Agriculture 31 (2001) 137 149 147 Fig. 7. Flow diagram for simulation of tractor performance.

148 S.A. Al-Hamed, A.A. Al-Janobi / Computers and Electronics in Agriculture 31 (2001) 137 149 Fig. 8. Input parameters screen to the simulation program. Fig. 9. Tractor performance results screen.

S.A. Al-Hamed, A.A. Al-Janobi / Computers and Electronics in Agriculture 31 (2001) 137 149 149 menus and object driven windows were vital in making the program relatively easy to learn and operate compared to the programs developed using any software tool available prior to the visual programming tools. The intuitive user interface to the model is a visual object-oriented window, which allows the selection of the tractor, making changes to soil tractor tire factors, and initiates the simulation. The user can also access other windows to edit or expand available databases. These features provided by the facilities of visual programming make the program highly flexible and interactive to the users in both research and education in farm machinery area. References Al-Hamed, S.A., Grisso, R.D., Zoz, F.M., Von Bargen, K., 1994. Tractor performance spreadsheet for radial tires. Comput. Electron. Agric. 10, 45 62. ASAE Standards, 2000. ASAE D497.4 Agricultural machinery management data. ASAE, St. Joseph, MI. Brixius, W.W., 1987. Traction prediction equations for bias ply tires. ASAE Paper 87-1622, 8 pp. Clark, R.L., 1985. Tractive modeling with the modified Wismer-Luth model. ASAE Paper 85-1049. Evans, M.D., Clark, R.L,. Manor, G., 1989. A traction prediction and ballast selection model. ASAE Paper 89-1054, 14 pp. Grisso, R.D., Al-Hamed, S.A., Taylor, R.K., Zoz, F.M., 1992. Demonstrating tractor performance trends using Lotus templates. Appl. Eng. Agric. 8 (6), 733 738. Wismer, R.D., Luth, H.J., 1972. Off-road traction prediction for wheeled vehicles. ASAE Paper 72-619, 16 pp. Zoz, F.M., 1970. Predicting tractor field performance. ASAE Paper 70-118, 12 pp. Zoz, F.M., 1987. Predicting tractor field performance (updated). ASAE Paper 87-1623, 12 pp. Zoz, F.M., Brixius, W.W., 1979. Traction. prediction for agricultural tires on concrete. ASAE Paper 79-1046, 5 pp.