<p>Coaxial magnetic gears are widely used in low-maintenance and high-reliability fields due to their non-contact transmission advantages. While the non-contact characteristics of magnetic gear transmission bring significant advantages, they also come with two key technical challenges. Firstly, the system is highly sensitive to dynamic load changes. When the sudden load torque exceeds the critical value or the load change rate is too high, it will cause the magnetic coupling between the master and slave shafts to fail, leading to protective slippage. Although this nonlinear out-of-step characteristic has reversible advantages over mechanical gear overload damage, it still needs to be optimized through control strategies to minimize its frequency of occurrence. Secondly, the inherent flexible coupling of magnetic coupling and the nonlinear torque angle relationship exacerbate system oscillations. Based on the above issues, this study constructs a dimensionless dynamic model under the coupling of constant acceleration and external load, derives the closed-form solution of the vibration period, and establishes an acceleration disturbance model to analyze parameter sensitivity. Simulation shows that when the disturbance intensity <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\sigma\)</EquationSource> <EquationSource Format="MATHML"><math> <mi>σ</mi> </math></EquationSource> </InlineEquation> increases from 0 to 0.05, the system undergoes a conservative periodic motion → parameter resonance → subharmonic bifurcation → quasi-periodic oscillation evolution, with an increase in phase trajectory area of 18% and an angular displacement amplitude of 2.3 times that of free oscillation; Anomalous divergence phenomenon occurs in the disturbance frequency range of 12–15&#xa0;Hz, revealing that the frequency matching effect affects the stability boundary by modulating the pole-to-pole ratio. This provides a theoretical basis for optimizing the parameter design of magnetic transmission devices and improving the reliability of system operation.</p>

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Research on the dynamic behavior and dynamic stability mechanism of coaxial magnetic gear transmission system

  • Jun-gang Wang,
  • Zhi-liang Zeng

摘要

Coaxial magnetic gears are widely used in low-maintenance and high-reliability fields due to their non-contact transmission advantages. While the non-contact characteristics of magnetic gear transmission bring significant advantages, they also come with two key technical challenges. Firstly, the system is highly sensitive to dynamic load changes. When the sudden load torque exceeds the critical value or the load change rate is too high, it will cause the magnetic coupling between the master and slave shafts to fail, leading to protective slippage. Although this nonlinear out-of-step characteristic has reversible advantages over mechanical gear overload damage, it still needs to be optimized through control strategies to minimize its frequency of occurrence. Secondly, the inherent flexible coupling of magnetic coupling and the nonlinear torque angle relationship exacerbate system oscillations. Based on the above issues, this study constructs a dimensionless dynamic model under the coupling of constant acceleration and external load, derives the closed-form solution of the vibration period, and establishes an acceleration disturbance model to analyze parameter sensitivity. Simulation shows that when the disturbance intensity \(\sigma\) σ increases from 0 to 0.05, the system undergoes a conservative periodic motion → parameter resonance → subharmonic bifurcation → quasi-periodic oscillation evolution, with an increase in phase trajectory area of 18% and an angular displacement amplitude of 2.3 times that of free oscillation; Anomalous divergence phenomenon occurs in the disturbance frequency range of 12–15 Hz, revealing that the frequency matching effect affects the stability boundary by modulating the pole-to-pole ratio. This provides a theoretical basis for optimizing the parameter design of magnetic transmission devices and improving the reliability of system operation.