Fault-type identification and fault estimation for the active steering system of a vehicle are considered in this paper. The vehicle studied is an electric ground vehicle, which operates mainly under normal driving conditions. First, a two-degree-of-freedom dynamic model of the lateral motion and the yaw motion of the vehicle is established and verified by experimental data. Then, an adaptive observer is proposed to estimate the steering motor fault by using measurements of the yaw rate of the vehicle. Residuals are defined for specific fault-type identification purposes. Experimental tests on the electric ground vehicle are carried out to assess the fault identification and estimation performance as well as to reveal the limitations of and possible improvement in the proposed method.
ChenYWangJ.Design and experimental evaluations on energy efficient control allocation methods for overactuated electric vehicles: longitudinal motion case. IEEE/ASME Trans Mechatronics2014; 19: 538–548.
2.
WangRChenYFengDet al. Development and performance characterization of an electric ground vehicle with independently actuated in-wheel motors. J Power Sources2011; 196: 3962–3971.
3.
HeJCrollaDALevesleyMCManningWJ.Coordination of active steering, driveline, and braking for integrated vehicle dynamics control. Proc IMechE Part D: J Automobile Engineering2006; 220(10): 1401–1420.
4.
AnwarSChenL.An analytical redundancy-based fault detection and isolation algorithm for a road-wheel control subsystem in a steer-by-wire system. IEEE Trans Veh Technol2007; 56: 2859–2869.
5.
YihPGerdesJC.Modification of vehicle handling characteristics via steer-by-wire. IEEE Trans Control Systems Technol2005; 13: 965–976.
6.
HaggagSAlstromDCetinkuntSet al. Modeling, control, and validation of an electro-hydraulic steer-by-wire system for articulated vehicle applications. IEEE/ASME Trans Mechatronics2005; 10: 688–692.
7.
KimJSongJ.Control logic for an electric power steering system using assist motor. Mechatronics2002; 12: 447–459.
8.
ZhangGZhangHHuangXet al. Active fault-tolerant control for electric vehicles with independently driven rear in-wheel motors against certain actuator faults. IEEE Trans on Control Systems Technol2016; 24(5): 1557–1572.
9.
NouraHTheilliolDPonsartJ-COnseddineA.Fault-tolerant control systems: design and practical applications. London: Springer, 2009.
10.
ZhangXPolycarpouMMParisiniT.A robust detection and isolation scheme for abrupt and incipient faults in nonlinear systems. IEEE Trans Autom Control2002; 47: 576–593.
11.
HuangJFukudaTMatsunoT.Model-based intelligent fault detection and diagnosis for mating electric connectors in robotic wiring harness assembly systems. IEEE/ASME Trans Mechatronics2008; 13: 86–94.
12.
GadsdenSASongYHabibiSR.Novel model-based estimators for the purposes of fault detection and diagnosis. IEEE/ASME Trans Mechatronics2013; 18: 1237–1249.
13.
IbarakiSSuryanarayananSTomizukaM.Design of Luenberger state observers using fixed-structure H∞ optimization and its application to fault detection in lane-keeping control of automated vehicles. IEEE/ASME Trans Mechatronics2005; 10: 34–42.
14.
MurpheyYLMasrurMAChenZet al. Model-based fault diagnosis in electric drives using machine learning. IEEE/ASME Trans Mechatronics2006; 11: 290–303.
15.
IsermannR.Model-based fault-detection and diagnosis – status and applications. A Rev Control2005; 29: 71–85.
16.
FengDWangJHuangD.Hand-wheel steering signal estimation and diagnosis approaches for ground vehicles. Control Engng Practice2012; 20: 654–662.
17.
LeeJLeeHKimJJeongJ. Model-based fault detection and isolation for electric power steering system. In: 2007 international conference on control, automation and systems, Seoul, Republic of Korea, 17–20 October 2007, pp. 2369–2374. New York: IEEE.
18.
ArogetiSWangDLowCBet al. Fault detection isolation and estimation in a vehicle steering system. IEEE Trans Ind Electron2012; 59: 4810–4820.
19.
ImJSOzakiFYeuTKet al. Model-based fault detection and isolation in steer-by-wire vehicle using sliding mode observer. J Mech Sci Technol2009; 23: 1991–1999.
20.
MasrurMWuHMiCet al. Fault diagnostics in power electronics-based brake-by-wire systems. Proc IMechE Part D: J Automobile Engineering2008; 222(1): 1–11.
21.
SchillingAAmstutzAGuzzellaL.Model-based detection and isolation of faults due to ageing in the air and fuel paths of common-rail direct injection diesel engines equipped with a λ and a nitrogen oxides sensor. Proc IMechE Part D: J Automobile Engineering2008; 222(1): 101–117.
22.
LeeH.Analysis of model-based sensor fault diagnosis with application to a motor-driven power steering system. Proc IMechE Part D: J Automobile Engineering2011; 225(10): 1317–1333.
23.
LiBHuRRenGFuJ.Engine fault diagnosis based on a morphological neural network using a morphological filter as a preprocessor. Proc IMechE Part D: J Automobile Engineering2013; 227(4): 490–505.
24.
PiDChenNZhangB.Experimental demonstration of a vehicle stability control system in a split-μ manoeuvre. Proc IMechE Part D: J Automobile Engineering2011; 225(3): 305–317.
25.
WilliamsDE.Handling benefits of steering a third axle. Proc IMechE Part D: J Automobile Engineering2010; 224(12): 1501–1511.
26.
CevherVChellappaRMcClellanJH.Vehicle speed estimation using acoustic wave patterns. IEEE Trans Signal Processing2009; 57: 30–47.
27.
LitzenbergerMBelbachirADonathNet al. Estimation of vehicle speed based on asynchronous data from a silicon retina optical sensor. In: 2006 IEEE intelligent transportation systems conference, Toronto, Ontario, Canada, 17–20 September 2006, pp. 653–658. New York: IEEE.
28.
LiXZhangQSuH.An adaptive observer for joint estimation of states and parameters in both state and output equations. Int J Adaptive Control Signal Processing2011; 25: 831–842.
29.
BrockettRW.Finite dimensional linear systems. Philadelphia, Pennsylvania: SIAM, 1970.
30.
WuLHoDW.Fuzzy filter design for Itô stochastic systems with application to sensor fault detection. IEEE Trans Fuzzy Systems2009; 17: 233–242.
