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Analysis of Pressure Variation in Wheel Using Statistical Methods
Technical Paper
2019-28-2450
ISSN: 0148-7191, e-ISSN: 2688-3627
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Event:
NuGen Summit
Language:
English
Abstract
Tire is one of the significant components of the vehicle, and so its characteristics for proper functioning of vehicle. Tire characteristics relies on number of factors including pressure in tire, construction of the tire and thread pattern. Of these, the factor of our interest is tire pressure. Maintaining proper tire pressure becomes necessity, as it causes several undesired effects which in turn affect the motorcycle performance. Hence, pressure variations should be detected as one of the safety measures.
Wheel speed based detection of tire pressure is not observed before in motorcycles. In this approach only, software algorithm is needed to complete the system to measure pressure, no extra hardware is required.
The paper presents a method to analyze variation in tire pressure by using the wheel speed sensor. The idea is to detect pressure variations in the wheel with respect to nominal pressure using data obtained from wheel speed sensor. The data is captured by varying pressure in two tires and measuring the wheel speed based on Design of Experiments (DoE). The method compares the wheel speed of front and rear wheel of the two-wheeler. At first, the errors in the data is chopped down by using band pass filter and then data is smoothened by using Moving Average method. The relative variation is then analyzed by using various statistical techniques and then correlated to the pressure.
Authors
Citation
Marwadi, R., Mandhana, A., and Basavarajappa, R., "Analysis of Pressure Variation in Wheel Using Statistical Methods," SAE Technical Paper 2019-28-2450, 2019, https://doi.org/10.4271/2019-28-2450.Data Sets - Support Documents
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References
- Bansal, A., Jain, A., Srivastava, P., Tiwary, A. et al. , “Significance of Tire Pressure Monitoring System in Motorcycle,” SAE Technical Paper 2016-01-1634, 2016, doi:10.4271/2016-01-1634.
- Velupillai, S. and Guvenc, L. , “Tire Pressure Monitoring [Applications of Control],” Control Systems Magazine, IEEE 27(8):22-25, Dec. 2007, doi:10.1109/MCS.2007.909477.
- Zhang a, J., Zhang b, Z.-H., Chen, T., Kong, X.-M. et al. , “A Tire Pressure Monitoring System Based on MEMS Sensor,” Key Engineering Materials 483:370-373, 2011.
- Persson, N. and Gustafsson, F. , “Indirect Tire Pressure Monitoring Using Sensor Fusion,” SAE Technical Paper 2002-01-1250, 2001, doi:10.4271/2002-01-1250.
- Barad, M. , “Design of Experiments (DOE)-A Valuable Multi-Purpose Methodology,” Applied Mathematics 5:2120-2129, 2014.
- Praekhaow, P. , “Determination of Trading Points using the Moving Average Methods,” in International Conference for a Sustainable Greater Mekong Subregion, Bangkok, Thailand, 26-27 August 2010.
- Ilie G. and. Ciocoiu C.N., “Application of Fishbone Diagram to Determine the Risk of an Event with Multiple Causes Management Research and Practice,” 2(1):1-20, 2010.