State Estimation for 4WD In-Wheel Motor Electric Vehicle

Abstract:

This article proposed a Double Extended Kalman Filters (Double EKFs) observer to estimate states of 4WD in-wheel motor electric vehicle. One EKF observer was used to estimate vehicle longitudinal velocity. The other EKF observer was employed to estimate vehicle sideslip angle. The structure has two benefits: Firstly, two EKFs reduce the order of the wholly state observer, so that calculation load could be lower. Secondly, the two EKFs could be adjusted easier and more independently. The paper investigates the feasibility of this observer in two vehicle test conditions. The test results indicate the effectiveness of the Double EKFs State estimation.

• Periodical: Applied Mechanics and Materials (Volume 610)
• Pages: 147-155
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.610.147
• Online since: August 2014
• Authors: Bo Lin Gao*, Hui Chen, Shu Gang Xie, Jin Feng Gong
• Keywords: 4WD EV, Double Extended Kalman Filter, Magic Formula Tire Model, State Estimation

References

[1] A. T. VAN ZANTEN, et al. Control aspects of the Bosch-VDC, AVEC' 96.

[2] A. T. VAN ZANTEN. Bosch ESP System: 5 Year of Experience, SAE Paper, 2000-01-1633.

[3] MATTHEW C BEST, TIMOTHY J GORDON. Real time state estimation of vehicle handling dynamics using an adaptive Kalman filter, [C] \5th International Symposium on Advanced Vehicle Control, Nagoya, 1998: 183-188.

DOI: 10.1076/0042-3114(200008)34:1;1-k;ft057

[4] PAUL J. T. VENHOVENSI, KARL NAAB. Vehicle dynamics estimation using Kalman filters [J] Vehicle System Dynamics, 1999, 32(1): 171.

DOI: 10.1076/vesd.32.2.171.2088

[5] ALEXSANDER HAC, MELINDA D. SIMPSON. Estimation of vehicle sideslip angle and yaw rate [C]. Detroit: SAE, 2000-01-0696.

[6] IRIS UNGER, ROLF ISERMANN. Fault tolerant sensors for vehicle dynamics control [C] American Control Conference, Minnesota. Detroit: American Control Committee, 2006: 3948-3953.

DOI: 10.1109/acc.2006.1657335

[7] KALMAN, R.E. 1960, a new approach to linear filtering and prediction problems. Transactions of the ASME-Journal of Basic Engineering, Series D. 82, 35-45.

DOI: 10.1115/1.3662552

[8] GUO KONGHUI, FU HAO, DING HAITAO. Estimation of CG sideslip angle based on extended Kalman filter [J]. Automobile Technology, 1000-3703 (2009) 04-0001-03.

[9] HU DAN. Research on the vehicle state and road tire friction coefficient estimation based on dual extended Kalman filter [D] \Jinlin University, 2009: 15-16.

[10] WENZEL T. A. , BURNHAM K. J. , BLUNDELL M. V., et al. Dual extended Kalman filter for vehicle state and parameter estimation [J] . Vehicle System Dynamics, 2006, 44 (2): 153-171.

DOI: 10.1080/00423110500385949

[11] BEST M C. Combined state and parameter estimation of vehicle handling dynamics [C] \Proc of AVEC, (2000).

[12] YOICHI HORI. Future Vehicle driven by Electricity and Control Research on 4 Wheel Motored "UOT March II,. AMC2002 Proc (7th International Workshop on Advanced Motion Control Proceedings). pp.1-14, (2002).

DOI: 10.1109/amc.2002.1026883

[13] BOLIN GAO, HUI CHEN. State Estimation for Active Safety Control of 4WD In-Wheel Motor Electric Vehicle. [C]. First International Symposium on Future Active Safety Technology toward zero-traffic-accident September 5-9, (2011).

[14] H.B. PACEJKA, AND E. BAKKER, The Magic Formula Tyre Model, Proc. 1st International Colloquium on Tyre Models for Vehicle Dynamics Analysis, Delft, Netherlands, Oct 21-22 (1991).

DOI: 10.1080/00423119208969994