Electric power steering (EPS) helps reduce steering effort, enhances steering feel, and improves safety while the vehicle is in motion. The EPS system offers several significant benefits compared to other power steering systems. Currently, no research comprehensively evaluates the power steering and the car dynamic models, which are utilized to compute the road reaction torque value. This approach makes the field of dynamics and control of EPS systems more challenging for practitioners. In this article, we conduct a thorough investigation and review of the mathematical models of various types of EPS systems, introducing their characteristics and highlighting their scope of application. Additionally, we present and analyze vehicle dynamics models, which determine the road resistant torque value, to determine the appropriate calculation method for each condition. The article's novel contribution lies in its thorough review and analysis of the latest advancements in EPS system dynamics and control, aimed at addressing the previously mentioned challenges. The results of this article are used as a theoretical basis for developing further in-depth studies in the future, making the approach to this field easier.
NguyenDNNguyenTA. Evaluate the stability of the vehicle when using the active suspension system with a hydraulic actuator controlled by the OSMC algorithm. Sci Rep2022; 12: 1–15.
2.
MannaSManiGGhildiyalS, et al.Ant colony optimization tuned closed-loop optimal control intended for vehicle active suspension system. IEEE Access2022; 10: 53735–53745.
3.
NguyenTAIqbalJTranTTH, et al.Application of hybrid control algorithm on the vehicle active suspension system to reduce vibrations. Adv Mech Eng2024; 16: 1–12.
4.
AtaeiMKhajepourAJeonS. Model predictive control for integrated lateral stability, traction/braking control, and rollover prevention of electric vehicles. Veh Syst Dyn2019; 58: 49–73.
5.
GuptaGSudeepRAshokB, et al.Intelligent regenerative braking control with novel friction coefficient estimation strategy for improving the performance characteristics of hybrid electric vehicle. IEEE Access2024; 12: 110361–110384.
6.
NguyenTA. Establishing a novel adaptive fuzzy control algorithm for an active stabilizer bar with complex automotive dynamics model. Ain Shams Eng J2023; 15: 1–24.
7.
TangZZhaoQPhamDT,et al.Enhancing active disturbance rejection control for a vehicle active stabiliser bar with an improved chicken flock optimisation algorithm. Processes2024; 12: 1–27.
8.
NguyenTA. Proposing a novel fuzzy control algorithm for automotive active stabilizer bars based on views of roll stability and ride comfort. Proc Inst Mech Eng, K: J Multi-Body Dyn2023; 237: 585–600.
9.
FatourehchiEMohammadpourMKingPD, et al.Effect of mesh phasing on the transmission efficiency and dynamic performance of wheel hub planetary gear sets. Proc Inst Mech Eng, C: J Mech Eng Scia2017; 232: 3469–3481.
10.
GkinisTRahmaniRRahnejatH. Integrated thermal and dynamic analysis of dry automotive clutch linings. Appl Sci2019; 9: 1–16.
11.
RahnejatHJohns-RahnejatPMDolatabadiN, et al.Multi-body dynamics in vehicle engineering. Proc Inst Mech Eng, K: J Multi-Body Dyn2023; 238: 3–25.
12.
BaharomMBHussainKDayAJ. Design of full electric power steering with enhanced performance over that of hydraulic power-assisted steering. Proc Inst Mech Eng, D: J Autom Eng2013; 227: 390–399.
13.
XiaLJiangH. An electronically controlled hydraulic power steering system for heavy vehicles. Adv Mech Eng2016; 8: 1–11.
14.
DellAmicoAKrusP. Modeling, simulation, and experimental investigation of an electrohydraulic closed-center power steering system. IEEE/ASME Trans Mechatron2015; 20: 2452–2462.
15.
TanYKongHMaL, et al.Testing and optimization of noise of an electrohydraulic power steering pump. J Braz Soc Mech Sci Eng2021; 43: 1–11.
16.
WangZKarimiHR. Experimental study on antivibration control of electrical power steering systems. J Appl Math2014: 1–7.
17.
AllousMMrabetKZanzouriN. Fast fault-tolerant control of electric power steering systems in the presence of actuator fault. Proc Inst Mech Eng, D: J Autom Eng2018; 233: 3088–3097.
18.
RamasamyD. An approach for steering wheel angle evaluation without using a true power-on steering angle sensor in electric power steering systems. J Inst Eng (India) Ser B2023; 104: 563–568.
19.
AmirkhaniAShirzadehMHeydariJ. Automotive electric power steering control with robust observer based neuroadaptive type-2 radial basis function methodology. IEEE Open J Veh Technol2024; 5: 592–605.
20.
HartonoRChaHRShinKJ. Design of electric power steering system identification and control for autonomous vehicles based on artificial neural network. IEEE Access2024; 12: 108460–108471.
21.
FuZLuYZhaoD, et al.A novel dual power-driven electric power steering system for electric commercial vehicles. Adv Mech Eng2023; 15: 1–12.
22.
ShiGSongMJuC, et al.Adaptive robust steering strategy for electro-hydraulic hybrid steering system based on backstepping method. Proc Inst Mech Eng, D: J Autom Eng2023; 238: 3328–3346.
23.
LuanZZhaoWWangC. Mode switching and consistency control for electric-hydraulic hybrid steering system. Autom Innov2024; 7: 166–181.
24.
HassanMKAzubirNAMNizamHMI, et al.Optimal design of electric power assisted steering system (EPAS) using GA-PID method. Proc Eng2012; 41: 614–621.
25.
NguyenTA. Development of a novel integrated control strategy for automotive electric power steering systems. IEEE Trans Autom Sci Eng2025; 22: 926–943.
26.
JiangHTangBGengG,et al.Test and design of controller for pinion-type EPS with brushless DC motor. Int Conf Electr Inf Contr Eng2011: 5428–5431.
27.
GuanXZhangYLuP, et al.The control strategy of the electric power steering system for steering feel control. Proc Inst Mech Eng, D: J Autom Eng2022; 238: 347–357.
28.
LeeDLoYGHanM, et al.A development of the model based torque feedback control with disturbance observer for electric power steering system. SAE Tech Papers2019: 1–7.
29.
DiabAValmorbidaGPasillas-LépineW. Linear assistance filter design for electric power steering systems with improved delay margin. Int J Control2023; 97: 1118–1135.
30.
SorialRRSolimanMHHasanienHM, et al.A vector controlled drive system for electrically power assisted steering using Hall–Effect sensors. IEEE Access2021; 9: 116485–116499.
31.
GuanXZhangYNDuanCG, et al.Study on decomposition and calculation method of EPS assist characteristic curve. Proc Inst Mech Eng, D: J Autom Eng2021; 235: 2166–2175.
32.
LiYWuGWuL, et al.Electric power steering nonlinear problem based on proportional–integral–derivative parameter self-tuning of back propagation neural network. Proc Inst Mech Eng, C: J Mech Eng Scia2020; 234: 4725–4736.
33.
GovenderVOrtmannLMüllerS. Synthesis and validation of a rack position controller for an electric power steering. IFAC-PapersOnLine2017; 50: 253–258.
34.
ChituCLacknerJHornM, et al.Controller design for an electric power steering system based on LQR techniques. COMPEL2013; 32: 763–775.
35.
ZhengZWeiJ. Research on active disturbance rejection control strategy of electric power steering system under extreme working conditions. Meas Control2023; 57: 90–100.
36.
FuDRakhejaSShangguanW-B, et al.Robust control for fuzzy electric power steering system: a two-layer performance approach. J Vib Control2021; 28: 536–550.
37.
HungY-CLinF-JHwangJ-C, et al.Wavelet fuzzy neural network with asymmetric membership function controller for electric power steering system via improved differential evolution. IEEE Trans Power Electron2014; 30: 2350–2362.
38.
NaSLiZQiuF, et al.Torque control of electric power steering systems based on improved active disturbance rejection control. Math Probl Eng2020: 1–13. doi:10.1155/2020/6509607
39.
LiSNiuJCuiG, et al.Research on friction compensation control for electric power steering system. Math Probl Eng2016: 1–5.
40.
SuXXiaoB. Actuator-integrated fault estimation and fault tolerant control for electric power steering system of forklift. Appl Sci2021; 11: 1–17.
41.
ParkJIJeonKYiK. An investigation on the energy-saving effect of a hybrid electric-power steering system for commercial vehicles. Proc Inst Mech Eng, D: J Autom Eng2018; 233: 1623–1648.
42.
JeongYWChungCCKimW. Nonlinear hybrid impedance control for steering control of rack-mounted electric power steering in autonomous vehicles. IEEE Trans Intell Transp Syst2019; 21: 2956–2965.
43.
LeeDJangBHanM, et al.A new controller design method for an electric power steering system based on a target steering torque feedback controller. Control Eng Pract2020; 106: 1–10.
44.
LeeDKimK-SKimS. Controller design of an electric power steering system. IEEE Trans Control Syst Technol2017; 26: 748–755.
45.
YangNT. A new control framework of electric power steering system based on admittance control. IEEE Trans Control Syst Technol2014; 23: 762–769.
46.
MuriloARodriguesRTeixeiraELS, et al.Design of a parameterized model predictive control for electric power assisted steering. Control Eng Pract2019; 90: 331–341.
47.
NguyenTA. A new approach to an optimal integrated control strategy for electric steering systems. Ain Shams Eng J2024; 15: 1–22.
48.
NguyenTAIqbalJ. Improving stability and adaptability of automotive electric steering systems based on a novel optimal integrated algorithm. Eng Comput (Swansea)2024; 41: 991–1034.
49.
KimSChoiMSungJ. Experimental verifications of electric power steering controller based on discrete-time sliding mode control with disturbance observer. Int J Autom Technol2023; 24: 883–888.
50.
KimGYouSLeeS, et al.Robust nonlinear torque control using steering wheel torque model for electric power steering system. IEEE Trans Veh Technol2023; 72: 9555–9560.
51.
KimWSonYSChungCC. Torque-overlay-based robust steering wheel angle control of electrical power steering for a lane-keeping system of automated vehicles. IEEE Trans Veh Technol2015; 65: 4379–4392.
52.
YamamotoKSenameOKoenigD, et al.Design and experimentation of an LPV extended state feedback control on electric power steering systems. Control Eng Pract2019; 90: 123–132.
53.
LinF-JChenS-GSunI-F. Intelligent sliding-mode position control using recurrent wavelet fuzzy neural network for electrical power steering system. Int J Fuzzy Syst2017; 19: 1344–1361.
54.
LinF-JHungY-CRuanK-C. An intelligent second-order sliding-mode control for an electric power steering system using a wavelet fuzzy neural network. IEEE Trans Fuzzy Syst2014; 22: 1598–1611.
55.
LeeDYiKChangS, et al.Robust steering-assist torque control of electric-power-assisted-steering systems for target steering wheel torque tracking. Mechatronics (Oxf)2017; 49: 157–167.
56.
JangBLeeDKimK, et al.Road torque modeling for electric power steering systems. Int J Autom Technol2022; 23: 765–773.
57.
PangHXuGSongZ, et al.EPS system of tractor automatic driving: an improved LMI with mixed sensitivity control method. J Electr Comp Eng2021: 1–13. doi:10.1155/2021/5513378
58.
MehrabiNMcPheeJAzadNL. Design and evaluation of an observer-based disturbance rejection controller for electric power steering systems. Proc Inst Mech Eng, D: J Autom Eng2015; 230: 867–884.
59.
ZhengZWeiJ. Research on electric power steering fuzzy PI control strategy based on phase compensation. Int J Dyn Contr2022; 11: 1867–1879.
60.
XueMXuGFengJ, et al.Control strategy of automotive electric power steering system based on generalized internal model control. J Algorithm Comput Technol2020; 14: –9.
61.
JieCYanlingG. Research on control strategy of the electric power steering system for all-terrain vehicles based on model predictive current control. Math Probl Eng2021: 1–15.
62.
YaohuaLJikangFJieH, et al.Novel electric power steering control strategies of commercial vehicles considering adhesion coefficient. Adv Mech Eng2020; 12: 1–11.
63.
LiYFengQZhangY, et al.Dual-motor full-weight electric power steering system for commercial vehicle. Int J Autom Technol2019; 20: 477–486.
64.
CaoZZhengS. MR-SAS and electric power steering variable universe fuzzy PID integrated control. Neural Comp Appl2017; 31: 1249–1258.
65.
LiSGuoLCuiG, et al.Return control of electronic power steering unequipped with an angle sensor. Int J Autom Technol2019; 20: 349–357.
66.
LeeMHHaSKChoiJY, et al.Improvement of the steering feel of an electric power steering system by torque map modification. J Mech Sci Technol2005; 19: 792–801.
67.
MaroufADjemaiMSentouhC, et al.A new control strategy of an electric-power-assisted steering system. IEEE Trans Veh Technol2012; 61: 3574–3589.
68.
LiXZhaoX-PChenJ. Controller design for electric power steering system using T-S fuzzy model approach. Int J Autom Comput2009; 6: 198–203.
69.
NasriMSaifiaDChadliM, et al.H∞ static output feedback control for electrical power steering subject to actuator saturation via fuzzy Lyapunov functions. Trans Inst Meas Control2019; 41: 3340–3351.
70.
ZhaoWZhangH. Coupling control strategy of force and displacement for electric differential power steering system of electric vehicle with motorized wheels. IEEE Trans Veh Technol2018; 67: 8118–8128.
71.
FujimuraYHashimotoSBanjerdpongchaiD. Design of model predictive control with nonlinear disturbance observer for electric power steering system. SICE Int Sympos Contr Syst2019: 49–56.
72.
SaifiaDChadliMKarimiHR, et al.Fuzzy control for electric power steering system with assist motor current input constraints. J Franklin Inst2014; 352: 562–576.
73.
NguyenDNNguyenTA. Fuzzy backstepping control to enhance electric power steering system performance. IEEE Access2024; 12: 88681–88695.
74.
NguyenTA. Designing a new integrated control solution for electric power steering systems based on a combination of nonlinear techniques. PLoS One2024; 19: 1–29.
75.
NguyenTAIqbalJ. Genetic algorithm inspired optimal integrated nonlinear control technique for an electric power steering system. J Braz Soc Mech Sci Eng2024; 46: 1–23.
76.
NguyenDNNguyenTA. Proposing a BSPID control strategy considering external disturbances for electric power steering (EPS) systems. IEEE Access2023; 11: 143230–143249.
77.
LuSLianMLiuM, et al.Adaptive fuzzy sliding mode control for electric power steering system. J Mech Sci Technol2017; 31: 2643–2650.
78.
KhalkhaliAShojaeefardMHDahmardehM, et al.Optimal design and applicability of electric power steering system for automotive platform. J Centr South Univ2019; 26: 839–851.
79.
JungD. A minimally configured hardware-in-the-loop simulator of electrical power steering system for human driver interaction on crosswind effect. IEEE Access2021; 9: 60470–60481.
80.
XuHZhaoYLinF, et al.Integrated optimization design of electric power steering and suspension systems based on hierarchical coordination optimization method. Struct Multidiscipl Optim2022; 65: 1–19.
81.
NguyenTA. A novel approach to the FPIBSC strategy for an electric power steering system. Trans Inst Meas Control2025; 47: 555–571.
82.
NguyenTA. Proposing a novel nonlinear integrated control technique for an electric power steering system to improve automotive dynamic stability. Proc Inst Mech Eng, K: J Multi-Body Dyn2024; 238: 445–460.
83.
MavrosGRahnejatHKingP. Analysis of the transient handling properties of a tyre, based on the coupling of a flexible carcass—belt model with a separate tread incorporating transient viscoelastic frictional properties. Veh Syst Dyn2005; 43: 199–208.
84.
JaiswalMMavrosGRahnejatH, et al.Influence of tyre transience on anti-lock braking. Proc Inst Mech Eng, K: J Multi-Body Dyn2009; 224: 1–17.
85.
GrigoriadisKMavrosGKnowlesJ,et al.Experimental investigation of tyre–road friction considering topographical roughness variation and flash temperature. Tribol Int2023; 181: 1–13.
86.
GipserM. FTire: a physically based application-oriented tyre model for use with detailed MBS and finite-element suspension models. Veh Syst Dyn2005; 43: 76–91.
87.
GipserM. FTire—the tire simulation model for all applications related to vehicle dynamics. Veh Syst Dyn2007; 45: 139–151.
88.
LiYYangZZhaiD, et al.Study on control strategy of electric power steering for commercial vehicle based on multi-map. World Electr Veh J2023; 14: 33.
