Skip to main content

Advertisement

Log in

Amelioration of Energy Dissipation Through Robotic Evacuation Process of Solid Bulk Materials: Effectiveness of Wheel Slip Control System

  • Research Article-Mechanical Engineering
  • Published:
Arabian Journal for Science and Engineering Aims and scope Submit manuscript

Abstract

Robotic evacuation process is commonly performed for confined spaces such as reactors and process towers of chemical, petrochemical, oil, and gas industries. This study deals with an applied research for amelioration of energy dissipation through robotic evacuation process of hazardous bulk materials with possibility of explosion as well as combustion inside industrial confined spaces. As a source of energy dissipation in the process was longitudinal slip of mobile robot wheels, a wheel slip control system was developed for the robot. The system was designed based on control algorithm of proportional integral and control strategy of increasing torque and speed of wheels. Effectiveness of the system for different levels of robot forward speed (0.5, 0.33 and 0.17 m/s) and tire air pressure (55.16, 34.47 and 20.68 kPa) was practically assessed through robotic trials on various solid ball diameters (0.0508, 0.0254 and 0.0127 m). Results obtained from the trials elucidated that employment of the wheel slip control system led to noteworthy amelioration of energy dissipation from range of 132.81–774.62 to 85.73–492.80 J/m2. It discloses that energy dissipation reduced 19.57–57.50%. Magnitude of energy dissipation reduction related to positive effect of causative factors (robot forward speed, tire air pressure, and solid ball diameter) on the slip of robot wheels. Among the causative factors, solid ball diameter had the greatest effect on magnitude of energy dissipation reduction. Overall, outcome of this research is helpful for energy dissipation management through robotic evacuation process of solid bulk materials.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Abbreviations

CV:

Coefficient of variation (%)

CNU:

Coefficient of non-uniformity (%)

DCT:

Data collection time (s)

ED:

Energy dissipation (J/m2)

EDRi :

ith energy dissipation reduction (J/m2)

EDRmax :

Maximum energy dissipation reduction (J/m2)

EDRmin :

Minimum energy dissipation reduction (J/m2)

EPN:

Encoder pulse number for one wheel revolution

EPNfw :

Encoder pulse number of fifth wheel

EPNrw :

Encoder pulse number of robot wheel

GTFiw :

Gross traction force of ith wheel (N)

LSw :

Longitudinal slip of wheel (%)

LSiw :

Longitudinal slip of ith wheel (%)

M:

Mean of used data (J/m2)

N:

Number of data

PD:

Power dissipation (W)

RDfw :

Rolling diameter of fifth wheel (m)

RDrw :

Rolling diameter of robot wheel (m)

RFS:

Robot forward speed (m/s)

RW:

Robot width (m)

SD:

Standard deviation (J/m2)

References

  1. Shafaei, S.M.; Mousazadeh, H.: Development of a mobile robot for safe mechanical evacuation of hazardous bulk materials in industrial confined spaces. J. Field Robot. 39(3), 218–231 (2022)

    Google Scholar 

  2. Shafaei, S.M.; Mousazadeh, H.: A practical quantification of longitudinal slippage of robot platform wheels traversing on solid balls based uneven terrain. J. Terramech. 99(1), 17–28 (2022)

    Google Scholar 

  3. Bouguelia, M.; Gonzalez, R.; Iagnemma, K.; Byttner, S.: Unsupervised classification of slip events for planetary exploration rovers. J. Terramech. 73(1), 95–106 (2017)

    Google Scholar 

  4. Gonzalez, R.; Apostolopoulos, D.; Iagnemma, K.: Slippage and immobilization detection for planetary exploration rovers via machine learning and proprioceptive sensing. J. Field Robot. 35(2), 231–247 (2018)

    Google Scholar 

  5. Gonzalez, R.; Fiacchini, M.; Iagnemma, K.: Slippage prediction for off-road mobile robots via machine learning regression and proprioceptive sensing. Rob. Auton. Syst. 105(1), 85–93 (2018)

    Google Scholar 

  6. Gonzalez, R.; Apostolopoulos, D.; Iagnemma, K.: Improving rover mobility through traction control: simulating rovers on the Moon. Auton. Robots 43(8), 1977–1988 (2019)

    Google Scholar 

  7. Gonzalez, R.; Chandler, S.; Apostolopoulos, D.: Characterization of machine learning algorithms for slippage estimation in planetary exploration rovers. J. Terramech. 82(1), 23–34 (2019)

    Google Scholar 

  8. Guo, J.; Li, W.; Ding, L.; Guo, T.; Gao, H.; Huang, B.; Deng, Z.: High-slip wheel-terrain contact modelling for grouser-wheeled planetary rovers traversing on sandy terrains. Mech. Mach. Theory. 153(1), 104032 (2020)

    Google Scholar 

  9. Onafeko, O.: Analysis of the rolling resistance losses of wheels operating on deformable terrain. J. Agric. Eng. Res. 14(2), 176–182 (1969)

    Google Scholar 

  10. Yong, R.N.; Chen, C.K.; Sylvestre-Williams, R.: A study of the mechanics of cone indentation and its relation to soil-wheel interaction. J. Terramech. 9(1), 19–36 (1972)

    Google Scholar 

  11. Yong, R.N.: Analytical predictive requirements for physical performance of mobility. J. Terramech. 10(4), 47–60 (1973)

    Google Scholar 

  12. Yong, R.N.: Some further problems in the design of wheels and tracks. J. Terramech. 13(2), 63–73 (1976)

    Google Scholar 

  13. Yong, R.N.; Fattah, E.A.: Prediction of wheel-soil interaction and performance using the finite element method. J. Terramech. 13(4), 227–240 (1976)

    Google Scholar 

  14. Yong, R.N.; Fattah, E.A.; Boonsinsuk, P.: Analysis and prediction of tyre-soil interaction and performance using finite elements. J. Terramech. 15(1), 43–63 (1978)

    Google Scholar 

  15. Yong, R.N.; Boonsinsuk, P.; Fattah, E.A.: Tyre flexibility and mobility on soft soils. J. Terramech. 17(1), 43–58 (1980)

    Google Scholar 

  16. Yong, R.N.; Fattah, E.A.; Skiadas, N.: Vehicle Traction Mechanics, 1st edn. Elsevier, Netherlands (1984)

    Google Scholar 

  17. Yong, R.N.; Foda, M.A.: Tribology model for determination of shear stress distribution along the tyre-soil interface. J. Terramech. 27(2), 93–114 (1990)

    Google Scholar 

  18. Gao, H.; Xia, K.; Ding, L.; Deng, Z.; Liu, Z.; Liu, G.: Optimized control for longitudinal slip ratio with reduced energy consumption. Acta Astronaut. 115(1), 1–17 (2015)

    Google Scholar 

  19. Taghavifar, H.; Mardani, A.; Hosseinloo, A.H.: Experimental analysis of the dissipated energy through tire-obstacle collision dynamics. Energy 91(1), 573–578 (2015)

    Google Scholar 

  20. Farhadi, P.; Golmohammadi, A.; Malvajerdi, A.S.; Shahgholi, G.: Tire and soil effects on power loss: measurement and comparison with finite element model results. J. Terramech. 92(1), 13–22 (2020)

    Google Scholar 

  21. Shafaei, S.M.; Loghavi, M.; Kamgar, S.: Profound insight into tractor energy dissipation through inevitable interaction inside wheel-soil interface for the period of plowing works. Soil Till. Res. 211(1), 104998 (2021)

    Google Scholar 

  22. Shafaei, S.M.; Loghavi, M.; Kamgar, S.: Analytical description of power delivery efficiency of front wheel assist tractor in tillage works. J. Biosyst. Eng. 46(3), 236–253 (2021)

    Google Scholar 

  23. Shafaei, S.M., Mousazadeh, H.: Characterization of motion power loss of off-road wheeled robot in a slippery terrain. J. Field Robot. in Press (2022).

  24. Kim, C.H.; Kim, B.K.: Minimum-energy translational trajectory generation for differential-driven wheeled mobile robots. J. Intell. Robot. Syst. 49(4), 367–383 (2007)

    Google Scholar 

  25. Wei, H.; Wang, B.; Wang, Y.; Shao, Z.; Chan, K.C.C.: Staying-alive path planning with energy optimization for mobile robots. Expert Syst. Appl. 39(3), 3559–3571 (2012)

    Google Scholar 

  26. Plonski, P.A.; Tokekar, P.; Isler, V.: Energy-efficient path planning for solar-powered mobile robots. J. Field Robot. 30(4), 583–601 (2013)

    Google Scholar 

  27. Tokekar, P.; Karnad, N.; Isler, V.: Energy-optimal trajectory planning for car-like robots. Auton. Robots 37(3), 279–300 (2014)

    Google Scholar 

  28. Kim, H.; Kim, B.K.: Minimum-energy trajectory generation for cornering with a fixed heading for three-wheeled omni-directional mobile robots. J. Intell. Robot. Syst. 75(2), 205–221 (2014)

    Google Scholar 

  29. Kim, H.; Kim, B.K.: Online minimum-energy trajectory planning and control on a straight-line path for three-wheeled omnidirectional mobile robots. IEEE Trans. Ind. Electron. 61(9), 4771–4779 (2014)

    Google Scholar 

  30. Liu, S.; Sun, D.: Minimizing energy consumption of wheeled mobile robots via optimal motion planning. IEEE/ASME Trans. Mechatron. 19(2), 401–411 (2014)

    Google Scholar 

  31. Yacoub, M.I.; Necsulescu, D.S.; Sasiadek, J.Z.: Energy consumption optimization for mobile robots motion using predictive control. J. Intell. Robot. Syst. 83(3–4), 585–602 (2016)

    Google Scholar 

  32. Kang, H.; Liu, C.; Jia, Y.: Inverse dynamics and energy optimal trajectories for a wheeled mobile robot. Int. J. Mech. Sci. 134(1), 576–588 (2017)

    Google Scholar 

  33. Kim, H.; Kim, B.K.: Minimum-energy cornering trajectory planning with self-rotation for three-wheeled omni-directional mobile robots. Int. J. Control Autom. Syst. 15(4), 1857–1866 (2017)

    Google Scholar 

  34. Xie, L.; Henkel, C.; Stol, K.; Xu, W.: Power-minimization and energy-reduction autonomous navigation of an omnidirectional Mecanum robot via the dynamic window approach local trajectory planning. Int. J. Adv. Robot. Syst. 15(1), 1–12 (2018)

    Google Scholar 

  35. Serralheiro, W.; Maruyama, N.; Saggin, F.: Self-tuning time-energy optimization for the trajectory planning of a wheeled mobile robot. J. Intell. Robot. Syst. 95(3–4), 987–997 (2019)

    Google Scholar 

  36. Dogru, S.; Marques, L.: Power characterization of a skid-steered mobile field robot with an application to headland turn optimization. J. Intell. Robot. Syst. 93(3–4), 601–615 (2019)

    Google Scholar 

  37. Jaramillo-Morales, M.F.; Dogru, S.; Gomez-Mendoza, J.B.; Marques, L.: Energy estimation for differential drive mobile robots on straight and rotational trajectories. Int. J. Adv. Robot. Syst. 17(2), 1–12 (2020)

    Google Scholar 

  38. Stefek, A.; Pham, T.V.; Krivanek, V.; Pham, K.L.: Energy comparison of controllers used for a differential drive wheeled mobile robot. IEEE Access 8(1), 170915–170927 (2020)

    Google Scholar 

  39. Effati, M.; Fiset, J.; Skonieczny, K.: Considering slip-track for energy-efficient paths of skid-steer rovers. J. Intell. Robot. Syst. 100(1), 335–348 (2020)

    Google Scholar 

  40. Quann, M.; Ojeda, L.; Smith, W.; Rizzo, D.; Castanier, M.; Barton, K.: Off-road ground robot path energy cost prediction through probabilistic spatial mapping. J. Field Robot. 37(3), 421–439 (2020)

    Google Scholar 

  41. Kim, H.; Kim, B.K.: Energy-optimal transport trajectory planning and online trajectory modification for holonomic robots. Asian J. Control 23(5), 2185–2200 (2021)

    Google Scholar 

  42. Jaiem, L.; Crestani, D.; Lapierre, L.; Druon, S.: Energy consumption of control schemes for the pioneer 3DX mobile robot: models and evaluation. J. Intell. Robot. Syst. 102(1), 23 (2021)

    Google Scholar 

  43. Osborne, L.E.: A field comparison of the performance of two-and four-wheel drive and tracklaying tractors. J. Agric. Eng. Res. 16(1), 46–61 (1971)

    Google Scholar 

  44. Domier, K.W.; Friesen, O.H.; Townsend, J.S.: Traction characteristics of two-wheel drive, four-wheel drive and crawler tractors. Trans. ASAE 14(3), 520–522 (1971)

    Google Scholar 

  45. Taylor, J.H.; Burt, E.C.: Track and tire performance in agricultural soils. Trans. ASAE 18(1), 3–6 (1975)

    Google Scholar 

  46. Brixius, W.W.; Zoz, F.M.: Tires and tracks in agriculture. SAE Trans. 85(3), 2034–2044 (1976)

    Google Scholar 

  47. Culshaw, D.: Rubber tracks for traction. J. Terramech. 25(1), 69–80 (1988)

    Google Scholar 

  48. Esch, J.H.; Bashford, L.L.; Bargen, K.V.; Ekstrom, R.E.: Tractive performance comparisons between a rubber belt track and a four-wheel-drive tractor. Trans. ASAE 33(4), 1109–1115 (1990)

    Google Scholar 

  49. Dwyer, M.J.; Okello, J.A.; Scarlett, A.J.: A theoretical and experimental investigation of rubber tracks for agriculture. J. Terramech. 30(4), 285–298 (1993)

    Google Scholar 

  50. Okello, J.A.; Dwyer, M.J.; Cottrell, F.B.: The tractive performance of rubber tracks and a tractor driving wheel tyre as influenced by design parameters. J. Agric. Eng. Res. 59(1), 33–43 (1994)

    Google Scholar 

  51. Turner, R.J.: Comparison of two and four track machines to rubber tire tractors in prairie soil conditions. SAE Trans. 104(2), 194–206 (1995)

    Google Scholar 

  52. Bashford, L.L.; Kocher, M.F.: Belts vs tires, belts vs belts, tires vs tires. Appl. Eng. Agric. 15(3), 175–181 (1999)

    Google Scholar 

  53. Wakabayashi, S.; Sato, H.; Nishida, S.: Design and mobility evaluation of tracked lunar vehicle. J. Terramech. 46(3), 105–114 (2009)

    Google Scholar 

  54. Arvidsson, J.; Westlin, H.; Keller, T.; Gilbertsson, M.: Rubber track systems for conventional tractors - effects on soil compaction and traction. Soil Till. Res. 117(1), 103–109 (2011)

    Google Scholar 

  55. Molari, G.; Bellentani, L.; Guarnieri, A.; Walker, M.; Sedoni, E.: Performance of an agricultural tractor fitted with rubber tracks. Biosyst. Eng. 111(1), 57–63 (2012)

    Google Scholar 

  56. Sutoh, M.; Yusa, J.; Ito, T.; Nagatani, K.; Yoshida, K.: Traveling performance evaluation of planetary rovers on loose soil. J. Field Robot. 29(4), 648–662 (2012)

    Google Scholar 

  57. Rasool, S.; Raheman, H.: Improving the tractive performance of walking tractors using rubber tracks. Biosyst. Eng. 167(1), 51–62 (2018)

    Google Scholar 

  58. Iagnemma, K.; Dubowsky, S.: Traction control of wheeled robotic vehicles in rough terrain with application to planetary rovers. Int. J. Rob. Res. 23(10–11), 1029–1040 (2004)

    Google Scholar 

  59. Choi, H.D.; Woo, C.K.; Kim, S.; Kwak, Y.K.; Yoon, S.: Independent traction control for uneven terrain using stick-slip phenomenon: application to a stair climbing robot. Auton. Robots 23(1), 3–18 (2007)

    Google Scholar 

  60. Wei, S.; Uthaichana, K.; Zefran, M.; DeCarlo, R.: Hybrid model predictive control for the stabilization of wheeled mobile robots subject to wheel slippage. IEEE Trans. Control Syst. Technol. 21(6), 2181–2193 (2013)

    Google Scholar 

  61. Kim, J.; Lee, J.: Traction-energy balancing adaptive control with slip optimization for wheeled robots on rough terrain. Cogn. Syst. Res. 49(1), 142–156 (2018)

    Google Scholar 

  62. Toupet, O.; Biesiadecki, J.; Rankin, A.; Steffy, A.; Meirion-Griffith, G.; Levine, D.; Schadegg, M.; Maimone, M.: Terrain-adaptive wheel speed control on the Curiosity Mars rover: algorithm and flight results. J. Field Robot. 37(5), 699–728 (2020)

    Google Scholar 

  63. Hori, Y.; Toyoda, Y.; Tsuruoka, Y.: Traction control of electric vehicle: basic experimental results using the test EV “UOT electric march.” IEEE Trans. Ind. Appl. 34(5), 1131–1138 (1998)

    Google Scholar 

  64. Li, L.; Kodama, S.; Hori, Y.: Design of anti-slip controller for an electric vehicle with an adhesion status analyzer based on the Ev simulator. Asian J. Control 8(3), 261–267 (2006)

    MathSciNet  Google Scholar 

  65. Yin, D.; Oh, S.; Hori, Y.: A novel traction control for EV based on maximum transmissible torque estimation. IEEE Trans. Ind. Electron. 56(6), 2086–2094 (2009)

    Google Scholar 

  66. Magallan, G.A.; Angelo, H.D.; Garcia, G.O.: Maximization of the traction forces in a 2WD electric vehicle. IEEE Trans. Veh. Technol. 60(2), 369–380 (2011)

    Google Scholar 

  67. Wang, J.; Wang, Q.; Jin, L.; Song, C.: Independent wheel torque control of 4WD electric vehicle for differential drive assisted steering. Mechatronics 21(1), 63–76 (2011)

    Google Scholar 

  68. Deur, J.; Pavkovic, D.; Burgio, G.; Hrovat, D.: A model-based traction control strategy non-reliant on wheel slip information. Veh. Syst. Dyn. 49(8), 1245–1265 (2011)

    Google Scholar 

  69. Castro, R.D.; Araujo, R.E.; Freitas, D.: Wheel slip control of EVs based on sliding mode technique with conditional integrators. IEEE Trans. Ind. Electron. 60(8), 3256–3271 (2012)

    Google Scholar 

  70. Zhang, L.; Li, L.; Lin, C.; Wang, C.; Qi, B.; Song, J.: Coaxial-coupling traction control for a four-wheel-independent-drive electric vehicle on a complex road. J. Automot. Eng. 228(12), 1398–1414 (2014)

    Google Scholar 

  71. Ivanov, V.; Savitski, D.; Augsburg, K.; Barber, P.; Knauder, B.; Zehetner, J.: Wheel slip control for all-wheel drive electric vehicle with compensation of road disturbances. J. Terramech. 61(1), 1–10 (2015)

    Google Scholar 

  72. Li, J.; Song, Z.; Shuai, Z.; Xu, L.; Ouyang, M.: Wheel slip control using sliding-mode technique and maximum transmissible torque estimation. J. Dyn. Syst. Meas. Control 137(11), 111010 (2015)

    Google Scholar 

  73. Ko, S.; Ko, J.; Lee, S.; Cheon, J.; Kim, H.: A study on the road friction coefficient estimation and motor torque control for an in-wheel electric vehicle. J. Automot. Eng. 229(5), 611–623 (2015)

    Google Scholar 

  74. Xu, G.; Xu, K.; Zheng, C.; Zahid, T.: Optimal operation point detection based on force transmitting behavior for wheel slip prevention of electric vehicles. IEEE Trans. Intell. Transp. Syst. 17(2), 481–490 (2016)

    Google Scholar 

  75. Savitski, D.; Schleinin, D.; Ivanov, V.; Augsburg, K.; Jimenez, E.; He, R.; Sandu, C.; Barber, P.: Improvement of traction performance and off-road mobility for a vehicle with four individual electric motors: driving over icy road. J. Terramech. 69(1), 33–43 (2017)

    Google Scholar 

  76. Jia, F.; Liu, Z.; Zhou, H.; Chen, W.: A novel design of traction control based on a piecewise-linear parameter-varying technique for electric vehicles with in-wheel motors. IEEE Trans. Veh. Technol. 67(10), 9324–9336 (2018)

    Google Scholar 

  77. Hartani, K.; Khalfaoui, M.; Merah, A.; Aouadj, N.: A robust wheel slip control design with radius dynamics observer for EV. SAE Int. J. Veh. Dyn. Stab. NVH 2(2), 135–146 (2018)

    Google Scholar 

  78. Tavernini, D.; Metzler, M.; Gruber, P.; Sorniotti, A.: Explicit nonlinear model predictive control for electric vehicle traction control. IEEE Trans. Control Syst. Technol. 27(4), 1438–1451 (2019)

    Google Scholar 

  79. Ma, Y.; Zhao, J.; Zhao, H.; Lu, C.; Chen, H.: MPC-based slip ratio control for electric vehicle considering road roughness. IEEE Access 7(1), 52405–52413 (2019)

    Google Scholar 

  80. Liang, Z.; Zhao, J.; Dong, Z.; Wang, Y.; Ding, Z.: Torque vectoring and rear-wheel-steering control for vehicle’s uncertain slips on soft and slope terrain using sliding mode algorithm. IEEE Trans. Veh. Technol. 69(4), 3805–3815 (2020)

    Google Scholar 

  81. Guo, L.; Xu, H.; Zou, J.; Jie, H.; Zheng, G.: A state observation and torque compensation-based acceleration slip regulation control approach for a four-wheel independent drive electric vehicle under slope driving. J. Automot. Eng. 234(12), 2728–2743 (2020)

    Google Scholar 

  82. Chen, Q.; Kang, S.; Chen, H.; Liu, Y.; Bai, J.: Acceleration slip regulation of distributed driving electric vehicle based on road identification. IEEE Access 8(1), 144585–144591 (2020)

    Google Scholar 

  83. Tan, H.; Chin, Y.: Vehicle traction control: variable-structure control approach. J. Dyn. Syst. Meas. Control 113(2), 223–230 (1991)

    Google Scholar 

  84. Song, J.; Kim, B.; Shin, D.: Development of TCS slip control logic based on engine throttle control. KSME Int. J. 13(1), 74–81 (1999)

    Google Scholar 

  85. Austin, L.; Morrey, D.: Recent advances in antilock braking systems and traction control systems. J. Automot. Eng. 214(6), 625–638 (2000)

    Google Scholar 

  86. Kabganian, M.; Kazemi, R.: A new strategy for traction control in turning via engine modeling. IEEE Trans. Veh. Technol. 50(6), 1540–1548 (2001)

    Google Scholar 

  87. Hadri, A.E.; Cadiou, J.C.; M’Sirdi, K.N.; Delanne, Y.: Wheel-slip regulation based on sliding mode approach. SAE Int. J. Passeng. Cars Mech. Syst. 110(6), 608–616 (2001)

    Google Scholar 

  88. Kang, S.; Yoon, M.; Sunwoo, M.: Traction control using a throttle valve based on sliding mode control and load torque estimation. J. Automot. Eng. 219(5), 645–653 (2005)

    Google Scholar 

  89. Nakakuki, T.; Shen, T.; Tamura, K.: Adaptive control approach to uncertain longitudinal tire slip in traction control of vehicles. Asian J. Control 10(1), 67–73 (2008)

    MathSciNet  Google Scholar 

  90. Amodeo, M.; Ferrara, A.; Terzaghi, R.; Vecchio, C.: Wheel slip control via second-order sliding-mode generation. IEEE Trans. Intell. Transp. Syst. 11(1), 122–131 (2010)

    Google Scholar 

  91. Shi, J.; Li, X.; Lu, T.; Zhang, J.: Development of a new traction control system for vehicles with automatic transmissions. Int. J. Automot. Technol. 13(5), 743–750 (2012)

    Google Scholar 

  92. Kang, M.; Li, L.; Li, H.; Song, J.; Han, Z.: Coordinated vehicle traction control based on engine torque and brake pressure under complicated road conditions. Veh. Syst. Dyn. 50(9), 1473–1494 (2012)

    Google Scholar 

  93. Li, H.Z.; Li, L.; He, L.; Kang, M.X.; Song, J.; Yu, L.Y.; Wu, C.: PID plus fuzzy logic method for torque control in traction control system. Int. J. Automot. Technol. 13(3), 441–450 (2012)

    Google Scholar 

  94. Li, L.; Ran, X.; Wu, K.; Song, J.; Han, Z.: A novel fuzzy logic correctional algorithm for traction control systems on uneven low-friction road conditions. Veh. Syst. Dyn. 53(6), 711–733 (2015)

    Google Scholar 

  95. Ran, X.; Zhao, X.; Chen, J.; Yang, C.; Yang, C.: Novel coordinated algorithm for traction control system on split friction and slope road. Int. J. Automot. Technol. 17(5), 817–827 (2016)

    Google Scholar 

  96. Zhao, J.; Zhang, J.; Zhu, B.: Coordinative traction control of vehicles based on identification of the tyre-road friction coefficient. J. Automot. Eng. 230(12), 1585–1604 (2016)

    Google Scholar 

  97. Pinto, S.D.; Chatzikomis, C.; Sorniotti, A.; Mantriota, G.: Comparison of traction controllers for electric vehicles with on-board drivetrains. IEEE Trans. Veh. Technol. 66(8), 6715–6727 (2017)

    Google Scholar 

  98. Sakai, S.; Sado, H.; Hori, Y.: Motion control in an electric vehicle with four independently driven in-wheel motors. IEEE/ASME Trans. Mechatron. 4(1), 9–16 (1999)

    Google Scholar 

  99. Bang, M.S.; Lee, S.H.; Han, C.S.; Maciuca, D.B.; Hedrick, J.K.: Performance enhancement of a sliding mode wheel slip controller by the yaw moment control. J. Automot. Eng. 215(4), 455–468 (2001)

    Google Scholar 

  100. Ivanov, V.; Savitski, D.; Shyrokau, B.: A survey of traction control and antilock braking systems of full electric vehicles with individually controlled electric motors. IEEE Trans. Veh. Technol. 64(9), 3878–3896 (2015)

    Google Scholar 

  101. Canale, M.; Fagiano, L.; Ferrara, A.; Vecchio, C.: Vehicle yaw control via second-order sliding-mode technique. IEEE Trans. Ind. Electron. 55(11), 3908–3916 (2008)

    Google Scholar 

  102. Geng, C.; Mostefai, L.; Denai, M.; Hori, Y.: Direct yaw-moment control of an in-wheel-motored electric vehicle based on body slip angle fuzzy observer. IEEE Trans. Ind. Electron. 56(5), 1411–1419 (2009)

    Google Scholar 

  103. Cairano, S.D.; Tseng, H.E.; Bernardini, D.; Bemporad, A.: Vehicle yaw stability control by coordinated active front steering and differential braking in the tire sideslip angles domain. IEEE Trans. Control Syst. Technol. 21(4), 1236–1248 (2013)

    Google Scholar 

  104. Ding, S.; Liu, L.; Zheng, W.X.: Sliding mode direct yaw-moment control design for in-wheel electric vehicles. IEEE Trans. Ind. Electron. 64(8), 6752–6762 (2017)

    Google Scholar 

  105. Hu, J.; Wang, Y.; Fujimoto, H.; Hori, Y.: Robust yaw stability control for in-wheel motor electric vehicles. IEEE/ASME Trans. Mechatron. 22(3), 1360–1370 (2017)

    Google Scholar 

  106. Zhang, J.; Sun, W.; Feng, Z.: Vehicle yaw stability control via H gain scheduling. Mech. Syst. Signal Process. 106(1), 62–75 (2018)

    Google Scholar 

  107. Asiabar, A.N.; Kazemi, R.: A direct yaw moment controller for a four in-wheel motor drive electric vehicle using adaptive sliding mode control. J. Multi-body Dyn. 233(3), 549–567 (2019)

    Google Scholar 

  108. Lenzo, B.; Zanchetta, M.; Sorniotti, A.; Gruber, P.; Nijs, W.D.: Yaw rate and sideslip angle control through single input single output direct yaw moment control. IEEE Trans. Control Syst. Technol. 29(1), 124–139 (2021)

    Google Scholar 

  109. Ishigami, G.; Nagatani, K.; Yoshida, K.: Slope traversal controls for planetary exploration rover on sandy terrain. J. Field Robot. 26(3), 264–286 (2009)

    Google Scholar 

  110. Asnani, V.; Delap, D.; Creager, C.: The development of wheels for the Lunar Roving Vehicle. J. Terramech. 46(3), 199–210 (2009)

    Google Scholar 

  111. Nakashima, H.; Fujii, H.; Oida, A.; Momozu, M.; Kanamori, H.; Aoki, S.; Yokoyama, T.; Shimizu, H.; Miyasaka, J.; Ohdoi, K.: Discrete element method analysis of single wheel performance for a small lunar rover on sloped terrain. J. Terramech. 47(5), 307–321 (2010)

    Google Scholar 

  112. Li, W.; Ding, L.; Gao, H.; Deng, Z.; Li, N.: ROSTDyn: rover simulation based on terramechanics and dynamics. J. Terramech. 50(3), 199–210 (2013)

    Google Scholar 

  113. Heverly, M.; Matthews, J.; Lin, J.; Fuller, D.; Maimone, M.; Biesiadecki, J.; Leichty, J.: Traverse performance characterization for the Mars Science Laboratory rover. J. Field Robot. 30(6), 835–846 (2013)

    Google Scholar 

  114. Inotsume, H.; Sutoh, M.; Nagaoka, K.; Nagatani, K.; Yoshida, K.: Modeling, analysis, and control of an actively reconfigurable planetary rover for traversing slopes covered with loose soil. J. Field Robot. 30(6), 875–896 (2013)

    Google Scholar 

  115. Arvidson, R.E.; Iagnemma, K.D.; Maimone, M.; Fraeman, A.A.; Zhou, F.; Heverly, M.C.; Bellutta, P.; Rubin, D.; Stein, N.T.; Grotzinger, J.P.; Vasavada, A.R.: Mars science laboratory curiosity rover megaripple crossings up to sol 710 in gale crater. J. Field Robot. 34(3), 495–518 (2017)

    Google Scholar 

  116. Yamauchi, G.; Nagatani, K.; Hashimoto, T.; Fujino, K.: Slip-compensated odometry for tracked vehicle on loose and weak slope. Robomech J. 4(1), 27 (2017)

    Google Scholar 

  117. Skonieczny, K.; Shukla, D.K.; Faragalli, M.; Cole, M.; Iagnemma, K.D.: Data-driven mobility risk prediction for planetary rovers. J. Field Robot. 36(2), 475–491 (2019)

    Google Scholar 

  118. Guo, J.; Li, W.; Ding, L.; Gao, H.; Guo, T.; Huang, B.; Deng, Z.: Linear expressions of drawbar pull and driving torque for grouser-wheeled planetary rovers without terrain mechanical parameters. IEEE Robot. Autom. Lett. 6(4), 8197–8204 (2021)

    Google Scholar 

  119. Effati, M.; Skonieczny, K.: Optimal traction forces for four-wheel rovers on rough terrain. Can. J. Electr. Comput. Eng. 42(4), 215–224 (2019)

    Google Scholar 

  120. Reina, G.; Ojeda, L.; Milella, A.; Borenstein, J.: Wheel slippage and sinkage detection for planetary rovers. IEEE/ASME Trans. Mechatron. 11(2), 185–195 (2006)

    Google Scholar 

  121. Lemus, D.L.D.M.; Kohanbash, D.; Moreland, S.; Wettergreen, D.: Slope descent using plowing to minimize slip for planetary rovers. J. Field Robot. 31(5), 803–819 (2014)

    Google Scholar 

  122. Xu, H.; Liu, X.; Fu, H.; Putra, B.B.; He, L.: Visual contact angle estimation and traction control for mobile robot in rough-terrain. J. Intell. Robot. Syst. 74(3–4), 985–997 (2014)

    Google Scholar 

  123. Gonzalez, R.; Iagnemma, K.: Slippage estimation and compensation for planetary exploration rovers state of the art and future challenges. J. Field Robot. 35(4), 564–577 (2018)

    Google Scholar 

  124. Shafaei, S.M.; Loghavi, M.; Kamgar, S.: Development and implementation of a human machine interface-assisted digital instrumentation system for high precision measurement of tractor performance parameters. Eng. Agric. Environ. Food 12(1), 11–23 (2019)

    Google Scholar 

  125. Summers, J.D.; Self, K.P.; McLaughlin, G.L.; Hart, J.; Hughey, R.; Sharp, R.: Performance of I-3 traction implement tires on sod and soil. SAE Trans. 96(3), 616–621 (1987)

    Google Scholar 

  126. Kiss, P.: Rolling radii of a pneumatic tyre on deformable soil. Biosyst. Eng. 85(2), 153–161 (2003)

    Google Scholar 

  127. Yahya, A.; Zohadie, M.; Kheiralla, A.F.; Giew, S.K.; Boon, N.E.: Mapping system for tractor-implement performance. Comput. Electron. Agric. 69(1), 2–11 (2009)

    Google Scholar 

  128. Goli, H.; Minaee, S.; Jafari, A.; Keyhani, A.; Borghaee, A.; Hajiahmad, A.: An instrumented drive axle to measure tire tractive performance. J. Terramech. 49(6), 309–314 (2012)

    Google Scholar 

  129. Smieszek, M.; Dobrzanska, M.; Dobrzanski, P.: The impact of load on the wheel rolling radius and slip in a small mobile platform. Auton. Robots 43(8), 2095–2109 (2019)

    Google Scholar 

  130. Kutzbach, H.D.; Burger, A.; Bottinger, S.: Rolling radii and moment arm of the wheel load for pneumatic tyres. J. Terramech. 82(1), 13–21 (2019)

    Google Scholar 

  131. Persson, S.P.E.: Parameters for tractor wheel performance part II description and use. Trans. ASAE 10(3), 424–428 (1962)

    Google Scholar 

  132. Sina, N.; Nasiri, S.; Karkhaneh, V.: Effects of resistive loads and tire inflation pressure on tire power losses and CO2 emissions in real-world conditions. Appl. Energy 157(1), 974–983 (2015)

    Google Scholar 

  133. Shafaei, S.M.; Kamgar, S.: A comprehensive investigation on static and dynamic friction coefficients of wheat grain with the adoption of statistical analysis. J. Adv. Res. 8(4), 351–361 (2017)

    Google Scholar 

  134. Janulevicius, A.; Pupinis, G.; Kurkauskas, V.: How driving wheels of front-loaded tractor interact with the terrain depending on tire pressures. J. Terramech. 53(1), 83–92 (2014)

    Google Scholar 

  135. Janulevicius, A.; Damanauskas, V.: How to select air pressures in the tires of MFWD (mechanical front-wheel drive) tractor to minimize fuel consumption for the case of reasonable wheel slip. Energy 90(1), 691–700 (2015)

    Google Scholar 

  136. Moinfar, A.; Shahgholi, G.; Gilandeh, Y.A.; Gundoshmian, T.M.: The effect of the tractor driving system on its performance and fuel consumption. Energy 202(1), 117803 (2020)

    Google Scholar 

  137. Janulevicius, A.; Damanauskas, V.: Prediction of tractor drive tire slippage under different inflation pressures. J. Terramech. 101(1), 23–31 (2022)

    Google Scholar 

Download references

Acknowledgements

The authors would like to appreciate Zagros Sanat Arka Company for provision of technical and financial supports under grant number of 99-7957154 (2021-2022).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to H. Mousazadeh.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shafaei, S.M., Mousazadeh, H. Amelioration of Energy Dissipation Through Robotic Evacuation Process of Solid Bulk Materials: Effectiveness of Wheel Slip Control System. Arab J Sci Eng 48, 11237–11250 (2023). https://doi.org/10.1007/s13369-022-07371-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13369-022-07371-7

Keywords

Navigation