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Table 1 Summary of estimation methods based on vehicle longitudinal dynamics

From: Tire Road Friction Coefficient Estimation: Review and Research Perspectives

Number Models Methodology References
1 Torque-to-force transfer function Analytical model [34,35,36, 39, 40]
2 Anisotropic brush model Least square method [37]
3 Magic formula model Kalman filter [21, 22]
4 Eight DOF vehicle model Extended Kalman–Bucy filtering [63]
5 Magic formula model Reduced order observer [23, 24]
6 Magic formula model Analytical model [38]
7 Torque-to-force transfer function State observer [28]
8 LuGre dynamic model State observer [41, 42]
9 Magic formula model RLS [25, 26]
10 Magic formula model Nonlinear curve fitting technique [29]
11 Pseudostatic lugre model Sliding mode observer [43]
12 Burckhardt model Recursive least squares [52]
13 Tire torsion model Sliding mode observer [51]
14 Longitudinal vehicle model Nonlinear curve fitting technique [30, 32, 33]
15 Burckhardt model Nonlinear curve fitting technique [44, 45]
16 Longitudinal vehicle model RLS [54, 56,57,58]
17 Single wheel model RLS [59]
18 Magic formula model Improved nonlinear observer [48]
19 Burckhardt model Sliding mode observer [46]
20 Six DOF vehicle model RLS [60]
21 Three DOF vehicle model Extended Kalman filter [61]
22 Longitudinal vehicle model Proportional integral observer [55]
23 Quarter wheel model Nonlinear Lipschitz observer [50]
24 Four wheel vehicle model Fuzzy logic and Kalman filter [62]
25 Frequency response function Analytical model [64, 65]
26 Modified Burckhardt tire model Nonlinear estimator [47]
27 Magic formula model Genetic algorithm [67]
28 Novel TRFC slip curve Nonlinear curve fitting technique [31]
29 Longitudinal vehicle model Fuzzy logic [66]
30 Magic formula model Linear extended state observer [49]
31 Longitudinal vehicle model Rules-based method [27]
32 Lugre and Burckhardt models T–S fuzzy and RLS [53]