Abstract
To suppress the torsional vibration of the hub electric drive system in wheeled armored vehicles and reduce its output torque fluctuation under the complex operational conditions such as high-speed maneuvering, off-road bumping and heavy-load climbing, this paper proposes a parameter matching and optimization method for the coupling of hub electric drive system for multi-condition vibration suppression. An electromechanical coupling dynamics model which considers the time-varying mesh stiffness of gear is established for the hub electric drive system, and the dynamic response characteristics of the system under high-speed, off-road, and climbing conditions are analyzed. Subsequently, a system dynamic behavior optimization model based on Kriging surrogate model is constructed by taking the torsional stiffness and damping of the coupling as design variables and the minimization of output torque fluctuation as the objective. The optimal coupling parameter set is obtained through single-condition Bayesian optimization and multi-condition NSGA-II multi-objective optimization. Finally, the accuracy of the established dynamics model is verified through the vibration bench test. The results show that the output torque fluctuations under high-speed, off-road and climbing conditions are reduced by 8.69, 29.77, and 31.86, respectively, after multi-objective optimization, demonstrating the effective suppression of torsional vibration and torque fluctuation under multiple operating conditions. This study provides a theoretical and methodological foundation for addressing the multi-condition torsional vibration challenges in hub electric drive systems for distributed-drive vehicles.
| Translated title of the contribution | 面向多工况振动抑制的轮毂电驱动系统联轴器参数匹配优化 |
|---|---|
| Original language | English |
| Article number | 250964 |
| Journal | Binggong Xuebao/Acta Armamentarii |
| Volume | 47 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 2026 |
| Externally published | Yes |
Keywords
- elastic coupling
- hub electric drive
- multi-condition
- multi-objective optimization
- surrogate model
- vibration suppression
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