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Estimation of vehicle sideslip angle via pseudo-multisensor information fusion method

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Języki publikacji
EN
Abstrakty
EN
This paper presents a novel sideslip angle estimator based on the pseudo-multi-sensor fusion method. The kinematics-based and dynamics-based sideslip angle estimators are designed for sideslip angle estimation. Also, considering the influence of ill-conditioned matrix and model uncertainty, a novel sideslip angle estimator is proposed based on the wheel speed coupling relationship using a modified recursive least squares algorithm. In order to integrate the advantages of above three sideslip angle estimators, drawing lessons from the multisensory information fusion technology, a novel thinking of sideslip angle estimator design is presented through information fusion of pseudo-multi-sensors. Simulations and experiments were carried out, and effectiveness of the proposed estimation method was verified.
Rocznik
Strony
499--516
Opis fizyczny
Bibliogr. 36 poz., rys., tab., wykr., wzory
Twórcy
autor
  • Jiangsu University, School of Automotive and Traffic Engineering, Zhenjiang 212013, China
autor
  • Jiangsu University, School of Automotive and Traffic Engineering, Zhenjiang 212013, China
  • Jiangsu University, Automotive Engineering Research Institute, Zhenjiang 212013, China
autor
  • Jiangsu University, School of Automotive and Traffic Engineering, Zhenjiang 212013, China
  • Jiangsu University, Automotive Engineering Research Institute, Zhenjiang 212013, China
autor
  • Jiangsu University, School of Automotive and Traffic Engineering, Zhenjiang 212013, China
  • Jiangsu University, Automotive Engineering Research Institute, Zhenjiang 212013, China
Bibliografia
  • [1] Wang, R.R„ Hu, C., Wang, Z.J., Yan, F.J., Chen, N. (2015). Integrated optimal dynamics control of 4WD4WS electric ground vehicle with tire-road frictional coefficient estimation. Mech. Syst. Signal Process, 60-61, 727-741.
  • [2] Wang, R.R., Zhang, H., Wang, J.M. (2014). Linear parameter-varying controller design for four wheel independently-actuated electric ground vehicles with active steering systems. IEEE Trans. Control. Syst. Technol., 22(4), 1281-1296.
  • [3] Jo, C.H., Ko, J., Yeo, H., Kim, H. (2012). Cooperative regenerative braking control algorithm for an automatic-transmission-based hybrid electric vehicle during a downshift. Proc IMechE Part D: J. Automobile Engineering, (226), 457-467.
  • [4] Chen, T., Xu, X., Chen, L., Jiang, H.B., Cai, Y.F. (2018). Estimation of longitudinal force, lateral vehicle speed and yaw rate for four-wheel independent driven electric vehicles. Mech. Syst. Signal Process, 101, 377-388.
  • [5] Jin, X.J., Yin, G.D., Chen, N. (2015). Gain-scheduled robust control for lateral stability of four-wheel-independent-drive electric vehicles via linear parameter-varying technique. Mechatronics, 30, 286-296.
  • [6] Wang, R.R., Zhang, H., Wang, J.M., Yan, F.J., Chen, N. (2015). Robust lateral motion control of four-wheel independently actuated electric vehicles with tire force saturation consideration. Journal of The Franklin Institute, 352, 645-668.
  • [7] Nam, K., Fujimoto, H., Hori, Y. (2012). Lateral stability control of in-wheel-motor-driven electric vehicles based on sideslip angle estimation using lateral tire force sensors. IEEE Trans. Veh. Technol., 61(5), 1972-1985.
  • [8] Wang, R.R., Jing, H., Hu, C., Yan, F.J., Chen, N. (2016). Robust H∞ path following control for autonomous ground vehicles with delay and date dropout. IEEE Trans. Intell. Transp. Syst., 17(7), 2042-2049.
  • [9] Hu, C., Wang, R.R., Yan, F.J., Chen, N. (2016). Output constraint control on path following of four-wheel independently actuated autonomous ground vehicles. IEEE Trans. Veh. Technol., 65(6), 4033-4043.
  • [10] Wang, R.R., Hu, C., Yan, F.J., Chadli, M. (2016). Composite nonlinear feedback control for path following of four-wheel independently actuated autonomous ground vehicles. IEEE Trans. Intell. Transp. Syst., 17(7), 2063-2074.
  • [11] Doumiati, M., Victorino, A.C., Charara, A., Lechner, D. (2011). Onboard real-time estimation of vehicle lateral tire-road forces and sideslip angle. IEEE/ASME Trans. Mechatronics, 16(4), 601-614.
  • [12] Jin, X.J., Yin, G.D. (2015). Estimation of lateral tire-road forces and sideslip angle for electric vehicles using interacting multiple model filter approach. Journal of The Franklin Institute, 352, 686-707.
  • [13] Chen, B.C., Hsieh, F.C. (2008). Sideslip angle estimation using extended Kalman filter. Vehicle Syst. Dyn., 46(1), 353-364.
  • [14] Li, L., Song, J., Li, H.Z., Zhang, X.L. (2011). A variable structure adaptive extended Kalman filter for vehicle slip angle estimation. Int. J. Veh. Des., 56(1-4), 161-185.
  • [15] Boada, B.L., Boada, M.J.L., Diaz, V. (2016). Vehicle side slip angle measurement based on sensor data fusion using an integrated ANFIS and an Unscented Kalman Filter algorithm. Mech. Syst. Signal Process., 72, 832-845.
  • [16] Li, L., Jia, G., Ran, X., Song, J., Wu, K.H. (2014). Avariable structure extended Kalman filter for vehicle side slip angle estimation on a low friction road. Veh. Syst. Dyn., 52(2), 280-308.
  • [17] Liu, Y.H., Li, T., Yang, Y.Y., Ji, X.W., Wu, J. (2017). Estimation of tire-road friction coefficient based on combined APF-IEKF and iteration algorithm. Mech. Syst. Signal Process., 88, 25-35.
  • [18] Liu, W., He, H.W., Sun, F.C. (2016). Vehicle state estimation based on minimum model error criterion combining with extended Kalman filter. Journal of The Franklin Institute, 353, 834-856.
  • [19] Leung, K.T., Whildborne, J.F., Purdy, D., Dunoyer, A. (2011). A review of ground vehicle dynamic state estimations utilising GPS/INS. Vehicle Syst. Dyn., 49(1-2), 29-58.
  • [20] Baffet, G., Charara, A., Lechner, D. (2009). Estimation of vehicle sideslip, tire force and wheel cornering stiffness. Control Eng. Pract., 17(11), 1255-1264.
  • [21] Solmaz, S., Baslamish, S. (2012). A nonlinear sideslip observer design methodology for automotive vehicles based on a rational tire model. Int. J. Adv. Manuf. Technol., 60, 765-775.
  • [22] Ma, B., Liu, Y.H., Gao, Y.F., Yang, Y.Y., Ji, X.W., Bo, Y. (2016). Estimation of vehicle sideslip angle based on steering torque. Int. J. Adv. Manuf. Technol., DOI 10.1007/s00170-016-9426-2.
  • [23] Pi, D.W., Chen, N., Wang, J.X., Zhang, B.J. (2011). Design and evaluation of sideslip angle observer for vehicle stability control. Int. J. Automotive Technology, 12(3), 391-399.
  • [24] Li, B., Du, H., Li, W., Zhang, Y. (2015). Side-slip angle estimation based lateral dynamics control for omni-directional vehicles with optimal steering angle and traction/brake torque distribution. Mechatronics, 30, 348-362.
  • [25] Bevly, D.M., Ryu, J.H., Gerdes, J.C. (2006). Integrating INS sensors with GPS measurements for continuous estimation of vehicle sideslip, roll, and tire cornering stiffness. IEEE Trans. Intell. Transport. Syst., 7(4), 483-493.
  • [26] Li, X., Chan, C.Y., Wang, Y. (2016). A reliable fusion methodology for simultaneous estimation of vehicle sideslip and yaw angles. IEEE Trans. Veh. Technol., 65(6), 4440-4458.
  • [27] Madhusudhanan, A.K., Corno, M., Holweg, E. (2016). Vehicle sideslip estimator using load sensing bearings. Control Eng. Pract., 54, 46-57.
  • [28] Leung, K.T., Whildborne, J.F., Purdy, D., Barber P. (2011). Road vehicle state estimation using low-cost GPS/INS. Mech. Syst. Signal Process., 25(6), 1988-2004.
  • [29] Nam, K., Oh, S., Fujimoto, H. Hori, Y. (2013). Estimation of sideslip angle and roll angles of electric vehicles using lateral tire force sensors through RLS and Kalman filter approaches. IEEE Trans. Ind. Electron., 60(3), 988-1000.
  • [30] Yoon, J.H., Peng, H. A cost-effective sideslip estimation method using velocity measurements from two GPS receivers. IEEE Trans. Veh. Technol., 63(6), 2589-2599.
  • [31] Tuononen, A.J. (2009). Vehicle lateral state estimation based on measured tyre forces. Sensors, 9, 8761-8775.
  • [32] Li, X., Song, X, Chan CY. (2014). Reliable vehicle sideslip angle fusion estimation using low-cost sensors. Measurement, 51, 241-258.
  • [33] Yoon, J.H., Li, S.E., Ahn C. (2016). Estimation of vehicle sideslip angle and tire-road friction coefficient based on magnetometer with GPS. Int. J. Automotive Technology, 17(3), 427-435.
  • [34] Yoon, J.H., Peng, H. (2014). Robust vehicle sideslip angle estimation through a disturbance rejection filter that integrates a magnetometer with GPS. IEEE Trans. Intell. Transp. Syst., 15(1), 191-204.
  • [35] Zhang, B.J., Du, H.P., Lam, J., Zhang, N., Li, W.H. (2016). A novel observer design for simultaneous estimation of vehicle steering angle and sideslip angle. IEEE Trans. Ind. Electron., 63(7), 4357-4365.
  • [36] Zhang, H., Huang, X.Y., Wang, J.M., Karimi, H.R. (2015). Robust energy-to-peak sideslip angle estimation with applications to ground vehicles. Mechatronics, 30, 338-347.
Uwagi
EN
1. This work was supported by the National Natural Science Foundation of China (grant numbers U1664258 and U1564201), Six Major Talent Project of Jiangsu Province (grant number 2014-JXQC-004), 333 Project of Jiangsu Province (grant number BRA2016445), Key R&D Plan of Jiangsu Province (grant number BE 2017129), and Natural Science Foundation of Jiangsu Province (grant number BK 20160525).
PL
2. Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e5ffdb7a-5c88-4889-a7d8-e321bf0fda35
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