This content is not included in your SAE MOBILUS subscription, or you are not logged in.
Travelling Resistance Estimation and Sandy Road Identification for SUVs
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 3, 2018 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
The mechanical properties of sandy road are quite different from those of hard surface road. For vehicle control systems such as EMS (engine management system), TCU (transmission control unit) and ABS (antilock brake system), the strategies and parameters set for solid surface road are not optimal for driving on sandy road. It is an effective way to improve the mobility of all-terrain vehicles by identifying sandy road online and shifting the control strategies and parameters of control systems to sandy sets. In this paper, a sandy road identification algorithm for SUVs is proposed. Firstly, the vehicle signals, such as engine torque and speed, gear position, wheel and vehicle speed, are acquired from EMS, TCU and ESP (electronic stability program) through CAN (controller area network) bus respectively. Based on the information and longitudinal force equilibrium equation, the travelling resistance of vehicle is estimated. The hydraulic torque converter is divided into several parts to calculate the acceleration resistance instead of using the rotational inertia coefficient. Then, the sandy road identification algorithm is proposed mainly based on the travelling resistance. Finally, real vehicle tests are carried out on different road conditions. After cone index penetrometer and soil hygrometer are used to measure the sandy test fields, performances of the travelling resistance estimation method and sandy road identification algorithm are validated. The results show that the identification algorithm designed in the paper can identify the sandy terrain effectively.
CitationWu, W., Zhang, J., Zhao, J., and Zhu, B., "Travelling Resistance Estimation and Sandy Road Identification for SUVs," SAE Technical Paper 2018-01-0578, 2018, https://doi.org/10.4271/2018-01-0578.
Data Sets - Support Documents
|[Unnamed Dataset 1]|
|[Unnamed Dataset 2]|
|[Unnamed Dataset 3]|
|[Unnamed Dataset 4]|
- Gao, Y., Spiteri, C., Minh-Tri, P., and Al-Milli, S., “A Survey on Recent Object Detection Techniques Useful for Monocular Vision-Based Planetary Terrain Classification,” Robotics and Autonomous Systems 62(2):151-167, 2014, doi:10.1016/j.robot.2013.11.003.
- Brooks, C.A. and Iagnemma, K., “Self-Supervised Terrain Classification for Planetary Surface Exploration Rovers,” Journal of Field Robotics 29(3):445-468, 2012, doi:10.1002/rob.21408.
- Leitner, J., Harding, S., Förster, A., and Schmidhuber, J., “Mars Terrain Image Classification Using Cartesian Genetic Programming,” Presented at 11th I-SAIRAS, Italy, 4-6 Sept 2012.
- Halatci, I., Brooks, C.A., and Iagnemma, K., “Terrain Classification and Classifier Fusion for Planetary Exploration Rovers,” Presented at Aerospace Conference 2007 IEEE, USA, 2007.
- Mathur, P. and Pandian, K.S., “Terrain Classification for Traversability Analysis for Autonomous Robot Navigation in Unknown Natural Terrain,” IJEST 4(1):38-49, 2012.
- Bekker, M.G., “Introduction to Terrain-Vehicle Systems,” (Ann Arbor, The University of Michigan Press, 1969), 447-455.
- Wong, J.Y., “Theory of Ground Vehicles, Third Edition,” (Ottawa, John Wiley & Sons, Inc., 2011), ISBN:0-471-35461-9.
- Taheri, S., Sandu, C., Taheri, S., Pinto, E. et al., “A Technical Survey on Terramechanics Models for Tire-Terrain Interaction Used in Modeling and Simulation of Wheeled Vehicles,” Journal of Terramechanics 57:1-22, 2015, doi:10.1016/j.jterra.2014.08.003.
- Brun, K., Meyenberg, C., and Thoro, J., “Hydrodynamic Torque Converters for Oil & Gas Compression and Pumping Applications: Basic Principles, Performance Characteristics and Applications,” Presented in Asia Turbomachinery & Pump Symposium, USA, 2016.
- Howell, J., Sherwin, C., Passmore, M.A., and Le Good, G.M., “The Aerodynamic Drag of a Compact SUV as Measured On-Road and in the Wind Tunnel,” SAE Technical Paper 020529, 2002, doi:10.4271/2002-01-0529.
- Rula, A.A., and Nuttall, J.C.J., “An Analysis of Ground Mobility Models (ANAMOB),” (1971).
- The US Army Engineer School, “M-5-430-00-1/AFJPAM 32-8013, Vol. 1,” 1994.
- Elwaleed, A.K., Yahya, A., Zohadie, M., Ahmad, D. et al., “Effect of Inflation Pressure on Motion Resistance Ratio of a High-Lug Agricultural Tyre,” Journal of Terramechanics 43(2):69-84, 2006, doi:10.1016/j.jterra.2004.08.006.
- Taghavifar, H. and Mardani, A., “Investigating the Effect of Velocity, Inflation Pressure, and Vertical Load on Rolling Resistance of a Radial Ply Tire,” Journal of Terramechanics 50(2):99-106, 2013, doi:10.1016/j.jterra.2013.01.005.