한국산업융합학회 논문집 (Journal of the Korean Society of Industry Convergence)

  • 제22권1호
  • /
  • Pages.1-9
  • /
  • 2019
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  • 1226-833X(pISSN)
  • /
  • 2765-5415(eISSN)
한국산업융합학회 (The Korean Society of Industry Convergence)
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Mathematical Model and Design Optimization of Reduction Gear for Electric Agricultural Vehicle

  • Pratama, Pandu Sandi (Life and Industry Convergence Research Institute Pusan National University) ;
  • Byun, Jae-Young (Department of Bio-industrial Machinery Engineering Pusan National University) ;
  • Lee, Eun-Suk (Department of Bio-industrial Machinery Engineering Pusan National University) ;
  • Keefe, Dimas Harris Sean (Department of Bio-industrial Machinery Engineering Pusan National University) ;
  • Yang, Ji-Ung (Department of Bio-industrial Machinery Engineering Pusan National University) ;
  • Chung, Song-Won (Department of Bio-industrial Machinery Engineering Pusan National University) ;
  • Choi, Won-Sik (Department of Bio-industrial Machinery Engineering Pusan National University)
  • 투고 : 2018.09.27
  • 심사 : 2019.01.03
  • 발행 : 2019.01.31
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초록

In electric agricultural machine the gearbox is used to increase torque and lower the output speed of the motor shaft. The gearbox consists of several shafts, helical gears and spur gears works in series. Optimization plays an important role in gear design as reducing the weight or volume of a gear set will increase its service life and improve the bearing capacity. In this paper the basic design parameters for gear like shaft diameter and face width are considered as the input variables. The bending stress and material volume is considered as the objective function. ANSYS was used to investigate the bending stress when the variable was changed. Artificial Neural Network (ANN) was used to obtain the mathematical model of the system based on the bending stress behaviour. The ANN was used since the output system is nonlinear. The Genetic Algorithm (GA)　technique of optimization is used to obtain the optimized values of shaft diameter and face width on the pinion based on the ANN mathematical model and the results are compared as that obtained using the traditional method. The ANN and GA were performed using MATLAB. The simulation results were shown that the proposed algorithm was successfully calculated the value of shaft diameter and face width to obtain the minimal bending stress and material volume of the gearbox.

키워드

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Fig. 1 Proposed electric vehicle.

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Fig. 2 Electrical configuration of electric agricultural vehicle.

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Fig. 3 Failed gear.

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Fig. 4 Front side and rear view of reduction gear.

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Fig. 5 Modification of shaft 3.

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Fig. 6 Simulation analysis procedure.

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Fig. 8 Von-Misses Stress of pinion 4.

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Fig. 7 Von-Misses Stress.

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Fig. 9 Training regression of ANN.

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Fig. 10 Surface obtained from RSM.

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Fig. 11 Surface obtained from Artificial Neural Network model.

Table 1. Finite element method simulation result

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Table 2. Comparison result of RSM and ANN-GA

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참고문헌

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  3. P. S. Pratama, A. V. Gulakari, Y. D. Setiawan, D. H. Kim, H. K. Kim, and S. B. Kim, "Trajectory tracking and fault detection algorithm for automatic guided vehicle based on multiple positioning modules," International Journal of Control, Automation and Systems, vol. 14, no. 2, pp. 400-410, (2016). https://doi.org/10.1007/s12555-014-0294-y
  4. P. S. Pratama, S. K. Jeong, S. S. Park, and S. B. Kim, "Moving Object Tracking and Avoidance Algorithm for Differential Driving AGV Based on Laser Measurement Technolog," International Journal of Science and Engineering, vol. 4, no. 1, pp. 11-15, (2013).
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