Knowledge of the tire-road information is not only very crucial in many active safety applications but also significant for self-driving cars. The tire-road information mainly consists of tire-road friction coefficient and road-tire friction forces. However, precise measurement of tire-road friction coefficient and tire forces requires expensive equipment. Therefore, the monitoring of tire-road information utilizing either accurate models or improved estimation algorithms is essential. Considering easy availability and good economy, this paper proposes a novel adaptive unified monitoring system (AUMS) to simultaneously observe the tire-road friction coefficient and tire forces, i.e., vertical, longitudinal, and lateral tire forces. First, the vertical tire forces can be calculated considering vehicle body roll and load transfer. The longitudinal and lateral tire forces are estimated by an adaptive unified sliding mode observer (AUSMO). Then, the road-tire friction coefficient is observed through the designed mode-switch observer (MSO). The designed MSO contains two modes: when the vehicle is under driving or brake, a slip slope method (SSM) is used, and a recursive least-squares (RLS) identification method is utilized in the SSM; when the vehicle is under steering, a comprehensive friction estimation method is adopted. The performance of the proposed AUMS is verified by both the matlab/simulinkCarSim co-simulation and the real car experiment. The results demonstrate the effectiveness of the proposed AUMS to provide accurate monitoring of tire-road information.

References

References
1.
Tseng
,
H. E.
,
Ashrafi
,
B.
,
Madau
,
D.
,
Allen Brown
,
T.
, and
Recker
,
D.
,
1999
, “
The Development of Vehicle Stability Control at Ford
,”
IEEE/ASME Trans. Mechatronics
,
4
(
3
), pp.
223
234
.
2.
Xiong
,
L.
,
Yu
,
Z.
,
Wang
,
Y.
,
Yang
,
C.
, and
Meng
,
Y.
,
2012
, “
Vehicle Dynamics Control of Four In-Wheel Motor Drive Electric Vehicle Using Gain Scheduling Based on Tyre Cornering Stiffness Estimation
,”
Veh. Syst. Dyn.
,
50
(
6
), pp.
831
846
.
3.
Li
,
L.
,
Lu
,
Y.
,
Wang
,
R.
, and
Chen
,
J.
,
2017
, “
A Three-Dimensional Dynamics Control Framework of Vehicle Lateral Stability and Rollover Prevention Via Active Braking With MPC
,”
IEEE Trans. Ind. Electron.
, 64(4), pp. 3389–3401.
4.
Plessen
,
M. G.
,
Bernardini
,
D.
,
Esen
,
H.
, and
Bemporad
,
A.
,
2018
, “
Spatial-Based Predictive Control and Geometric Corridor Planning for Adaptive Cruise Control Coupled With Obstacle Avoidance
,”
IEEE Trans. Control Syst. Technol.
, 26(1), pp. 38–50.
5.
Ji
,
J.
,
Khajepour
,
A.
,
Melek
,
W. W.
, and
Huang
,
Y.
,
2017
, “
Path Planning and Tracking for Vehicle Collision Avoidance Based on Model Predictive Control With Multiconstraints
,”
IEEE Trans. Veh. Technol.
,
66
(
2
), pp.
952
964
.
6.
Wu
,
J.
,
Cheng
,
S.
,
Liu
,
B.
, and
Liu
,
C.
,
2017
, “
A Human-Machine-Cooperative-Driving Controller Based on AFS and DYC for Vehicle Dynamic Stability
,”
Energies
,
10
, p. 1737.
7.
Wang
,
F.
, and
Chen
,
Y.
,
2018
, “
Dynamics and Control of a Novel Active Yaw Stabilizer to Enhance Vehicle Lateral Motion Stability
,”
ASME J. Dyn. Syst., Meas., Control
,
140
(
8
), p.
081007
.
8.
Ray
,
L. R.
,
1995
, “
Nonlinear State and Tire Force Estimation for Advanced Vehicle Control
,”
IEEE Trans. Control Syst. Technol.
,
3
(
1
), pp.
117
124
.
9.
Wilkin
,
M. A.
,
Manning
,
W. J.
,
Crolla
,
D. A.
, and
Levesley
,
M. C.
,
2006
, “
Use of an Extended Kalman Filter as a Robust Tyre Force Estimator
,”
Veh. Syst. Dyn.
,
44
(
Suppl. 1
), pp.
50
59
.
10.
Baffet
,
G.
,
Charara
,
A.
,
Lechner
,
D.
, and
Thomas
,
D.
,
2008
, “
Experimental Evaluation of Observers for Tire–Road Forces, Sideslip Angle and Wheel Cornering Stiffness
,”
Veh. Syst. Dyn.
,
46
(
6
), pp.
501
520
.
11.
Dakhlallah
,
J.
,
Glaser
,
S.
,
Mammar
,
S.
, and
Sebsadji
,
Y.
,
2008
, “
Tire-Road Forces Estimation Using Extended Kalman Filter and Sideslip Angle Evaluation
,”
American Control Conference
(
ACC
),
Seattle, WA
,
June 11–13
, pp.
4597
4602
.
12.
Rezaeian
,
A.
,
Zarringhalam
,
R.
,
Fallah
,
S.
,
Melek
,
W.
,
Khajepour
,
A.
,
Chen
,
S.-K.
,
Moshchuck
,
N.
, and
Litkouhi
,
B.
,
2015
, “
Novel Tire Force Estimation Strategy for Real-Time Implementation on Vehicle Applications
,”
IEEE Trans. Veh. Technol.
,
64
(
6
), pp.
2231
2241
.
13.
Doumiati
,
M.
,
Victorino
,
A. C.
,
Charara
,
A.
, and
Lechner
,
D.
,
2011
, “
Onboard Real-Time Estimation of Vehicle Lateral Tire-Road Forces and Sideslip Angle
,”
IEEE/ASME Trans. Mechatronics
,
16
(
4
), pp.
601
614
.
14.
Hsiao
,
T.
,
2013
, “
Robust Estimation and Control of Tire Traction Forces
,”
IEEE Trans. Veh. Technol.
,
62
(
3
), pp.
1378
1383
.
15.
Cho
,
W.
,
Yoon
,
J.
,
Yim
,
S.
,
Koo
,
B.
, and
Yi
,
K.
,
2010
, “
Estimation of Tire Forces for Application to Vehicle Stability Control
,”
IEEE Trans. Veh. Technol.
,
59
(
2
), pp.
638
649
.
16.
Singh
,
K. B.
, and
Taheri
,
S.
,
2015
, “
Estimation of Tire–Road Friction Coefficient and Its Application in Chassis Control Systems
,”
Syst. Sci. Control Eng.
,
3
(
1
), pp.
39
61
.
17.
Gustafsson
,
F.
,
1997
, “
Slip-Based Tire-Road Friction Estimation
,”
Automatica
,
33
(
6
), pp.
1087
1099
.
18.
Rajamani
,
R.
,
Phanomchoeng
,
G.
,
Piyabongkarn
,
D.
, and
Lew
,
J. Y.
,
2012
, “
Algorithms for Real-Time Estimation of Individual Wheel Tire-Road Friction Coefficients
,”
IEEE/ASME Trans. Mechatronics
,
17
(
6
), pp.
1183
1195
.
19.
Cao
,
D.
,
Khajepour
,
A.
, and
Song
,
X.
,
2010
, “
Wheelbase Filtering and Characterization of Road Profiles for Vehicle Dynamics
,”
ASME
Paper No. DETC2010-28062.
20.
Wang
,
R.
,
Yin
,
G.
, and
Wang
,
J.
,
2012
, “
Vehicle Lateral Velocity and Tire-Road Friction Coefficient Estimation
,”
ASME
Paper No. DSCC2012-MOVIC2012-8575.
21.
Liu
,
Y. H.
,
Li
,
T.
,
Yang
,
Y. Y.
,
Ji
,
X. W.
, and
Wu
,
J.
,
2017
, “
Estimation of Tire-Road Friction Coefficient Based on Combined APF-IEKF and Iteration Algorithm
,”
Mech. Syst. Signal Process.
,
88
, pp.
25
35
.
22.
Ma
,
B.
,
Lv
,
C.
,
Liu
,
Y.
,
Zheng
,
M.
,
Yang
,
Y.
, and
Ji
,
X.
,
2017
, “
Estimation of Road Adhesion Coefficient Based on Tire Aligning Torque Distribution
,”
ASME J. Dyn. Syst., Meas., Control
,
140
(
5
), p.
051010
.
23.
Baffet
,
G.
,
Charara
,
A.
, and
Dherbomez
,
G.
,
2007
, “
An Observer of Tire-Road Forces and Friction for Active Security Vehicle Systems
,”
IEEE/ASME Trans. Mechatronics
,
12
(
6
), pp.
651
661
.
24.
Cheng
,
S.
,
Li
,
L.
, and
Chen
,
J.
,
2018
, “
Fusion Algorithm Design Based on Adaptive SCKF and Integral Correction for Side-Slip Angle Observation
,”
IEEE Trans. Ind. Electron.
,
65
(
7
), pp.
5754
5763
.
25.
Rath
,
J. J.
,
Veluvolu
,
K. C.
, and
Defoort
,
M.
,
2015
, “
Simultaneous Estimation of Road Profile and Tire Road Friction for Automotive Vehicle
,”
IEEE Trans. Veh. Technol.
,
64
(
10
), pp.
4461
4471
.
26.
Acosta
,
M.
,
Alatorre
,
A.
,
Kanarachos
,
S.
,
Victorino
,
A.
, and
Charara
,
A.
,
2017
, “
Estimation of Tire Forces, Road Grade, and Road Bank Angle Using Tire Model-Less Approaches and Fuzzy Logic
,”
IFAC-PapersOnLine
,
50
(
1
), pp.
14836
14842
.
27.
Chen
,
J.
,
Song
,
J.
,
Li
,
L.
,
Jia
,
G.
,
Ran
,
X.
, and
Yang
,
C.
, “
UKF-Based Adaptive Variable Structure Observer for Vehicle Sideslip With Dynamic Correction
,”
IET Control Theory Appl.
,
10
(
14
), pp.
1641
1652
.
28.
Boada
,
B. L.
,
Boada
,
M. J. L.
, and
Diaz
,
V.
,
2016
, “
Vehicle Sideslip Angle Measurement Based on Sensor Data Fusion Using an Integrated ANFIS and an Unscented Kalman Filter Algorithm
,”
Mech. Syst. Signal Process.
,
72–73
, pp.
832
845
.
29.
Li
,
L.
,
Song
,
J.
,
Li
,
H.-Z.
,
Shan
,
D.-S.
,
Kong
,
L.
, and
Yang
,
C. C.
,
2009
, “
Comprehensive Prediction Method of Road Friction for Vehicle Dynamics Control
,”
Proc. Inst. Mech. Eng., Part D
,
223
(
8
), pp.
987
1002
.
You do not currently have access to this content.