Abstract
This paper presents a method that estimates the vehicle sideslip angle and a tire-road friction coefficient by combining measurements of a magnetometer, a global positioning system (GPS), and an inertial measurement unit (IMU). The estimation algorithm is based on a cascade structure consisting of a sensor fusing framework based on Kalman filters. Several signal conditioning techniques are used to mitigate issues related to different signal characteristics, such as latency and disturbances. The estimated sideslip angle information and a brush tire model are fused in a Kalman filter framework to estimate the tire-road friction coefficient. The performance and practical feasibility of the proposed approach were evaluated through several tests.
Similar content being viewed by others
References
Ahn, C. (2011). Robust Estimation of Road Friction Coefficient for Vehicle Active Safety Systems. Ph. D. Dissertation. The University of Michigan. Ann Arbor, USA.
Ahn, C., Peng, H. and Tseng, H. E. (2012). Robust estimation of road friction coefficient using lateral and longitudinal vehicle dynamics. Vehicle System Dynamics 50, 6, 961–985.
Ahn, C., Peng, H. and Tseng, H. E. (2013). Robust estimation of road frictional coefficient. IEEE Trans. Control Systems Technology 21, 1, 1–13.
Andersson, M., Bruzelius, F., Casselgren, J., Gäfvert, M., Hjort, M., Hultén, J., Håbring, F., Klomp, M., Olsson, G., Sjö dahl, M., Svendenius, J., Woxneryd, S. and Wälivaara, B. (2007). Road Friction Estimation. Intelligent Vehicle Safety Systems. 2004:17750.
Best, M. C., Gordon, T. J. and Dixon, P. J. (2000). An extended adaptive Kalman filter for real-time state estimation of vehicle handling dynamics. Vehicle System Dynamics 34, 1, 57–75.
Bevly, D. M. (2004). Global positioning system (GPS): A low-cost velocity sensor for correcting inertial sensor errors on ground vehicles. J. Dynamic Systems, Measurement, and Control 126, 2, 255–264.
Bevly, D. M., Gerdes, J. C. and Wilson, C. (2002). The use of GPS based velocity measurements for measurement of sideslip and wheel slip. Vehicle System Dynamics 38, 2, 127–147.
Canudas De Wit, C. and Tsiotras, P. (1999). Dynamic tire friction models for vehicle traction control. IEEE Int. Conf. Decision and Control, Phoenix, Arizona, USA, 3746–3751.
Dugoff, H., Fancher, P. S. and Segel, L. (1969). Tire Performance Characteristics Affecting Vehicle Response to Steering and Braking Control Inputs. Highway Safety Research Institute. PB187-667.
Eichhorn, U. and Roth, J. (1992). Prediction and monitoring of tyre/road friction. FISITA, London, UK, 67-74.
Farrelly, J. and Wellstead, P. (1996). Estimation of vehicle lateral velocity. IEEE Int. Conf. Control Applications, Dearborn, MI, USA, 552–557.
Grip, H. a. F., Imsland, L., Johansen, T. A., Fossen, T. I., Kalkkuhl, J. C. and Suissa, A. (2008). Nonlinear vehicle side-slip estimation with friction adaptation. Automatica 44, 3, 611–622.
Gustafsson, F. (1997). Slip-based tire-road friction estimation. Automatica 33, 6, 1087–1099.
Gustafsson, F. (1998). Monitoring tire-road friction using the wheel slip. IEEE Control Systems Magazine 18, 4, 42–49.
Hahn, J.-O., Rajamani, R. and Alexander, L. (2002). GPSbased real-time identification of tire-road friction coefficient. IEEE Trans. Control Systems Technology 10, 3, 331–343.
Holzmann, F., Bellino, M., Siegwart, R. and Bubb, H. (2006). Predictive estimation of the road-tire friction coefficient. IEEE Int. Conf. Control Applications, Munich, Germany, 885–890.
Hsu, Y.-H. J. and Gerdes, J. C. (2006). A feel for the road: A method to estimate tire parameters using steering torque. Int. Symp. Advanced Vehicle Control, Taipei, Taiwan, 835–840.
Hsu, Y.-H. J., Laws, S., Gadda, C. D. and Gerdes, J. C. (2006). A method to estimate the friction coefficient and tire slip angle using steering torque. Int. Mechanical Engineering Congress and Exposition, Chicago, IL, USA, 515–524
Imsland, L., Johansen, T. A., Fossen, T. I., Fjær Grip, H., Kalkkuhl, J. C. and Suissa, A. (2006). Vehicle velocity estimation using nonlinear observers. Automatica 42, 12, 2091–2103.
Ito, M., Yoshioka, K. and Saji, T. (1994). Estimation of road surface conditions using wheel speed behavior. Int. Symp. Advanced Vehicle Control, Tsukuba, Japan, 533–538.
Larsen, T. D., Andersen, N. A., Ravn, O. and Poulsen, N. K. (1998). Incorporation of time delayed measurements in a discrete-time Kalman filter. Conf. Decision and Control, 4, 3972–3977.
Lee, C., Hedrick, K. and Yi, K. (2004). Real time slip based estimation of maximum tire road friction coefficient. IEEE/ASME Trans. Mechatronics 9, 2, 454–458.
Liu, C.-S. and Peng, H. (1996). Road friction coefficient estimation for vehicle path prediction. Vehicle System Dynamics 25, 1, 413–425.
Mahalanobis, P. C. (1936). On the generalized distance in statistics. Proc. National Institute of Sciences (Calcutta) 2, 1, 49–55.
Pacejka, H. B. (2005). Tyre and Vehicle Dynamics. Elsevier. Oxford, UK.
Piyabongkarn, D., Rajamani, R., Grogg, J. A. and Lew, J. Y. (2009). Development and experimental evaluation of a slip angle estimator for vehicle stability control. IEEE Trans. Control Systems Technology 17, 1, 78–88.
Ray, L. R. (1997). Nonlinear tire force estimation and road friction identification: simulation and experiments. Automatica 33, 10, 1819–1833.
Ryu, J. and Gerdes, J. C. (2004a). Estimation of vehicle roll and road bank angle. American Control Conf., Boston, MA,USA, 2110–2115.
Ryu, J. and Gerdes, J. C. (2004b). Integrating inertial sensors with global positioning system (GPS) for vehicle dynamics control. J. Dynamic Systems, Measurement, and Control 126, 2, 243–254.
Sato, Y., Kobay, A. D., Kageyama, I., Watanabe, K., Kuriyagawa, Y. and Kuriyagawa, Y. (2007). Study on recognition method for road friction condition. JSAE Trans. 38, 2, 51–56.
Stephant, J., Charara, A. and Meizel, D. (2004). Virtual sensor: Application to vehicle sideslip angle and transversal forces. IEEE Trans. Industrial Electronics 51, 2, 278–289.
Umeno, T., Ono, E., Asano, K., Ito, S., Tanaka, A., Yasui, Y. and Sawada, M. (2002). Estimation of tire-road friction using tire vibration model. SAE World Cong., Detroit, Michigan, USA.
Yamada, M., Ueda, K., Horiba, I., Tsugawa, S. and Yamamoto, S. (2005). Road surface condition detection technique based on image taken by camera attached to vehicle rearview mirror. Review of Automotive Engineering 26, 2, 163–168.
Yi, K., Hedrick, K. and Lee, S.-C. (1999). Estimation of tire-road friction using observer based identifiers. Vehicle System Dynamics 31, 4, 233–261.
Yoon, J.-H. and Peng, H. (2010). Vehicle sideslip angle estimation using two single-antenna GPS receivers. Dynamic Systems and Control Conf., Boston, MA, USA, 863–870.
Yoon, J.-H. and Peng, H. (2014). Robust vehicle sideslip angle estimation through a disturbance rejection filter that integrates a magnetometer with GPS. IEEE Trans. Intelligent Transportation Systems 15, 1, 191–204.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Yoon, JH., Eben Li, S. & Ahn, C. Estimation of vehicle sideslip angle and tire-road friction coefficient based on magnetometer with GPS. Int.J Automot. Technol. 17, 427–435 (2016). https://doi.org/10.1007/s12239-016-0044-7
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12239-016-0044-7