The motor gear coupled system (MGCS) plays a critical role in electric drive systems, however, its dynamic performance is significantly constrained by nonlinear factors, including elastic coupling vibrations, gear friction torque, and backlash. Suppressing the resulting dynamic coupling and disturbances has therefore become a key challenge in improving overall system performance. In this study, a two-inertia system model incorporating gear friction and meshing nonlinearities is established for the MGCS. Based on this model, the dynamic interactions between the motor and load are systematically analyzed. Furthermore, an active disturbance suppression strategy based on pole placement is proposed. This strategy achieves precise regulation of electromagnetic torque through multi-loop control and optimizes the system’s dynamic response using three pole configuration methods. Simulations and experimental results validate the effectiveness of the proposed method in reducing overshoot and enhancing stability. These findings provide theoretical and methodological support for the design of high-performance electric drive systems.
LiuZHaoHChengX, et al. Critical issues of energy efficient and new energy vehicles development in China. Energy Policy2018; 115: 92–97. https://doi.org/10.1016/j.enpol.2018.01.006
2.
AzadFSRahmanABarmanSD, et al. Towards efficient energy management systems for electric vehicles: advances in control techniques and applications. Energy Convers Manag2025; 28: 101326. https://doi.org/10.1016/j.ecmx.2025.101326
3.
MarquesPMTMarafonaJDMMartinsRC, et al. A continuous analytical solution for the load sharing and friction torque of involute spur and helical gears considering a non-uniform line stiffness and line load. Mech Mach Theory2021; 161: 104320. https://doi.org/10.1016/j.mechmachtheory.2021.104320
4.
WangC. Measurement and analysis of dynamic load sharing in planetary gear trains considering high power operations and system errors. Measurement2025; 253: 117828. https://doi.org/10.1016/j.measurement.2025.117828
5.
XuJLiXChenR, et al. Modeling and control analysis of electric driving system considering gear friction based on dual-inertia system. J Franklin Inst2023; 360(5): 3633–3656. https://doi.org/10.1016/j.jfranklin.2023.02.005
6.
BouslemaMFakhfakhTNasriR, et al. Effect of elastic couplings on the dynamic behavior of transmission systems. Comptes Rendus Mécanique2022; 350: 343–359. https://doi.org/10.5802/crmeca.120
7.
ShangDLiXYinM, et al. Vibration suppression for two-inertia system with variable-length flexible load based on neural network compensation sliding mode controller and angle-independent method. IEEE/ASME Trans Mechatron2023; 28(2): 848–859. https://doi.org/10.1109/tmech.2022.3206342
8.
YokokuraYOhishiK. Fine load-side acceleration control based on torsion torque sensing of two-inertia system. IEEE Trans Ind Electron2020; 67(1): 768–777. https://doi.org/10.1109/tie.2018.2881944
9.
ZhouJLiuKZhangY, et al. Real-time compensation of dynamic load position error with pre-estimation of mechanical parameters for a two-inertia transmission system. IEEE Trans Energy Convers2026; 41(1): 160–171. https://doi.org/10.1109/tec.2025.3578145
10.
YangJChenWHLiS, et al. Disturbance/uncertainty estimation and attenuation techniques in PMSM drives—a survey. IEEE Trans Ind Electron2017; 64(4): 3273–3285. https://doi.org/10.1109/tie.2016.2583412
11.
WuZYangZDingK, et al. Transfer mechanism analysis of injected voltage harmonic and its effect on current harmonic regulation in FOC PMSM. IEEE Trans Power Electron2022; 37(1): 820–829. https://doi.org/10.1109/tpel.2021.3097103
12.
PetkarSGThippiripatiVK. A novel duty-controlled DTC of a surface PMSM drive with reduced torque and flux ripples. IEEE Trans Ind Electron2023; 70(4): 3373–3383. https://doi.org/10.1109/tie.2022.3181405
13.
LiHZhouHWangG, et al. Estimation for tire–road adhesion coefficient based on PMSM sensor less control for distributed drive electric vehicle. IEEE Sens J2025; 25(9): 15402–15418. https://doi.org/10.1109/jsen.2025.3537112
14.
TangZAkinB. A new LMS algorithm based deadtime compensation method for PMSM FOC drives. IEEE Trans Ind Appl2018; 54(6): 6472–6484. https://doi.org/10.1109/tia.2018.2853045
15.
BasitBAChoiHHJungJW. An online torque ripple minimization technique for IPMSM drives: fuzzy system-based d-axis current design approach. IEEE Trans Ind Electron2021; 68(12): 11794–11805. https://doi.org/10.1109/tie.2020.3044807
16.
ShinoharaAInoueYMorimotoS, et al. Maximum torque per ampere control in stator flux linkage synchronous frame for DTC-based PMSM drives without using q-axis inductance. IEEE Trans Ind Appl2017; 53(4): 3663–3671. https://doi.org/10.1109/tia.2017.2686800
17.
LiuHNiuWGuoY. Direct torque control for PMSM based on the RBFNN surrogate model of electromagnetic torque and stator flux linkage. Control Eng Pract2024; 148: 105943. https://doi.org/10.1016/j.conengprac.2024.105943
18.
WenJYuanXNiuS, et al. A robust complex vector PI current controller with deadbeat response for PMSM drives. IEEE Trans Ind Electron2025; 72(5): 4671–4681. https://doi.org/10.1109/tie.2024.3482013
19.
LiHSongBChenT, et al. Adaptive fuzzy PI controller for permanent magnet synchronous motor drive based on predictive functional control. J Franklin Inst2021; 358(15): 7333–7364. https://doi.org/10.1016/j.jfranklin.2021.07.024
20.
BudaiCTóth-KatonaTStumpfP. Novel design method for cascade control structure of electric drives: closed-form expressions for control gains via pole placement. IET Control Theory Appl2024; 18(17): 2448–2467. https://doi.org/10.1049/cth2.12747
21.
AraújoJMDantasNJBDóreaCET, et al. Pole-zero placement through the robust receptance method for multi-input active vibration control with time delay. J Sound Vib2025; 599: 118850. https://doi.org/10.1016/j.jsv.2024.118850
22.
BenarabABoussaadaINiculescuSI, et al. Over one century of spectrum analysis in delay systems: an overview and new trends in pole placement methods. IFAC-PapersOnLine2022; 55(36): 234–239. https://doi.org/10.1016/j.ifacol.2022.11.363
BaiWQinDWangY, et al. Dynamic characteristic of electromechanical coupling effects in motor-gear system. J Sound Vib2018; 423: 50–64. https://doi.org/10.1016/j.jsv.2018.02.033
26.
ChenQXuRWangZ, et al. Analysis of electromechanical coupling vibration characteristics of motor-gear system based on bond graph theory. AIP Adv2024; 14: 015315. https://doi.org/10.1063/5.0185079
27.
GeSHouSZhangG, et al. Electromechanical coupling dynamics of dual-motor electric drive system of hybrid electric vehicles. Proc Inst Mech Eng D J Automob Eng2025; 239(6): 2090–2105. https://doi.org/10.1177/09544070241230703
28.
FanXLiXWangH, et al. Integrated electromechanical modeling of electric powertrains considering dynamic load inertia and time-varying torque characteristics. Proc Inst Mech Eng D J Automobile Eng2025: 1–13. https://doi.org/10.1177/09544070251374731
29.
ZhangKLiHCaoS, et al. Dynamic characteristics and experimental verification of planetary gear-motor coupling system under unsteady and non-ideal states. Nonlinear Dyn2024; 112: 7909–7949. https://doi.org/10.1007/s11071-024-09520-z
30.
MoSLiuWWangZ, et al. Nonlinear dynamics of fault electromechanical coupling transmission system in electrical vehicles. Nonlinear Dyn2024; 112: 14879–14905. https://doi.org/10.1007/s11071-024-09842-y
31.
GeSQiuLZhangZ, et al. Electromechanical coupling dynamic characteristics of electric drive system for electric vehicle. Nonlinear Dyn2024; 112: 6101–6136. https://doi.org/10.1007/s11071-024-09327-y
32.
XuHCuiLLShangDG, et al. Study on coupling effect between the time-varying gear backlash and the different time-varying mesh parameters on the gear system. J Vibroengineering2017; 19(8): 5874–5891. https://doi.org/10.21595/jve.2017.18200
YangYTangJHuN, et al. Research on the time-varying mesh stiffness method and dynamic analysis of cracked spur gear system considering the crack position. J Sound Vib2023; 548: 117505. https://doi.org/10.1016/j.jsv.2022.117505
35.
ZhuSHuangWYanY, et al. High-damped complex vector current regulator for PMSM based on active damping function. IEEE Trans Power Electron2023; 38(4): 5204–5216. https://doi.org/10.1109/tpel.2022.3230350
36.
RanjanAMehtaUSaxenaS. A comprehensive review of modified internal model control (IMC) structures and their filters for unstable processes. Annu Rev Control2023; 56: 100895. https://doi.org/10.1016/j.arcontrol.2023.04.006
37.
XuJLiXLiB, et al. Analysis of dynamic characteristics of gear-bearing transmission system with shaft current damage. Nonlinear Dyn2024; 112: 12095–12111. https://doi.org/10.1007/s11071-024-09690-w
38.
WangCPengJPanJ. A novel friction compensation method based on Stribeck model with fuzzy filter for PMSM servo systems. IEEE Trans Ind Electron2023; 70(12): 12124–12133. https://doi.org/10.1109/tie.2022.3232667
