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A Smart Measuring System for Vehicle Dynamics Testing
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 14, 2020 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
A fast measurement of the car handling performance is highly desirable to easily compare and assess different car setup, e.g. tires size and supplier, suspension settings, etc. Instead of the expensive professional equipment normally used by car manufacturers for vehicle testing, the authors propose a low-cost solution that is nevertheless accurate enough for comparative evaluations. The paper presents a novel measuring system for vehicle dynamics analysis, which is based uniquely on the sensors embedded in a smartphone and therefore completely independent on the signals available through vehicle CAN bus. Data from tri-axial accelerometer, gyroscope, GPS and camera are jointly used to compute the typical quantities analyzed in vehicle dynamics applications. In addition to signals such as yaw rate, lateral and longitudinal acceleration, vehicle speed and trajectory, normally available when working with Inertial Measurement Units (IMU) equipped with GPS, in the presented application the steering wheel angle is also measured, without additional sensors. The latter signal, besides being important for identifying the maneuver imposed by the driver, enables the usage of Kalman filters based on dynamic vehicle models (e.g. the single-track model) for the estimation of body sideslip angle. The system was tested during experimental campaigns on test tracks and the comparison between data from a professional measuring equipment and the Smart Measuring System showed a very good match. In the paper, hardware installation of smartphone and related accessories is discussed together with the main tasks of the algorithm implemented in the application, i.e. identification of smartphone orientation, steering wheel angle measurement, Kalman filter sideslip angle estimators (based on kinematic and single-track models). Furthermore, the time histories of the vehicle dynamics quantities during a lap on a handling test track are shown and compared with reference signals from the professional equipment. The proposed system proved to be a promising cost- and time-effective solution for vehicle dynamics testing.
CitationGalvagno, E., Mauro, S., Pastorelli, S., Servetti, A. et al., "A Smart Measuring System for Vehicle Dynamics Testing," SAE Technical Paper 2020-01-1066, 2020, https://doi.org/10.4271/2020-01-1066.
Data Sets - Support Documents
|[Unnamed Dataset 1]|
- Velardocchia, M. and Vigliani, A. , “Control Systems Integration for Enhanced Vehicle Dynamics,” Open Mechanical Engineering Journal 7(1):58-69, 2013.
- Morgando, A., Velardocchia, M., Vigliani, A., Van Leeuwen, B.G., and Ondrak, V. , “An Alternative Approach to automotive ESC Based on Measured Wheel Forces,” Vehicle System Dynamics 49(12):1855-1871, 2011.
- Segers, J. , “Analysis Techniques for Racecar Data Acquisition,” SAE Technical Paper 2008-03-25, 2008, doi:https://doi.org/10.4271/2008-03-25.
- Andria, G. et al. , “Development of an Automotive Data Acquisition Platform for Analysis of Driving Behavior,” Measurement 93:278-287, 2016.
- https://www.kistler.com/en/product/type-cs350a/, available on 18/11/2019
- https://www.navtechgps.com/oxts_xnav200/, available on 18/11/2019
- Arndt, D. , “Method and Device for Determining the Float Angle of a Motor Vehicle,” U.S. Patent No. 7,058,486, June 6, 2006.
- Leung, T. and King, et al. , “A Review of Ground Vehicle Dynamic State Estimations Utilising GPS/INS,” Vehicle System Dynamics 49(1-2):29-58, 2011.
- Wang, H., Tota, A., Aksun-Guvenc, B., and Guvenc, L. , “Real Time Implementation of Socially Acceptable Collision Avoidance of a Low Speed Autonomous Shuttle Using the Elastic Band Method,” Mechatronics 50:341-355, 2018.
- Tota, A., Velardocchia, M., and Güvenç, L. , “Path Tracking Control for Autonomous Driving Applications,” in International Conference on Robotics in Alpe-Adria Danube Region, Springer, Cham, 2017.
- Sharifzadeh, M. et al. , “Real Time Tyre Forces Estimation for Advanced Vehicle Control,” International Journal of Mechanics and Control 18:77-84, 2017.
- Chindamo, D., Lenzo, B., and Gadola, M. , “On the Vehicle Sideslip Angle Estimation: A Literature Review of Methods, Models, and Innovations,” Applied Sciences 8(3):355, 2018.
- Selmanaj, D. et al. , “Robust Vehicle Sideslip Estimation Based on Kinematic Considerations,” IFAC-PapersOnLine 50(1):14855-14860, 2017.
- Selmanaj, D. et al. , “Vehicle Sideslip Estimation: A Kinematic Based Approach,” Control Engineering Practice 67:1-12, 2017.
- Lu, Q. et al. , “Enhancing Vehicle Cornering Limit through Sideslip and Yaw Rate Control,” Mechanical Systems and Signal Processing 75:455-472, 2016.
- Cheli, F. et al. , “A Methodology for Vehicle Sideslip Angle Identification: Comparison with Experimental Data,” Vehicle System Dynamics 45(6):549-563, 2007.
- Dakhlallah, J., Glaser, S., and Mammar, S. , “Vehicle Side Slip Angle Estimation with Stiffness Adaptation,” International Journal of Vehicle Autonomous Systems 8(1):56-79, 2010.
- Piyabongkarn, D. et al. , “Development and Experimental Evaluation of a Slip Angle Estimator for Vehicle Stability Control,” IEEE Transactions on Control Systems Technology 17(1):78-88, 2008.
- Li, X., Song, X., and Chan, C. , “Reliable Vehicle Sideslip Angle Fusion Estimation Using Low-Cost Sensors,” Measurement 51:241-258, 2014.
- Leung, K.T. et al. , “Road Vehicle State Estimation Using Low-Cost GPS/INS,” Mechanical Systems and Signal Processing 25(6):1988-2004, 2011.
- Svensson, J. , “Design of a Portable Steering Wheel Angle Measurement System,” 2015.
- Hoeller, R. et al., “Combined Steering Angle and Torque Sensor,” U.S. Patent No. 7,726,208, Jun 1, 2010.
- Chowdhury, M. et al., “Non-Contact Angle/Torque Sensor for Steering Apparatus of Vehicle,” U.S. Patent No. 10,234,263, Mar 19, 2019.