Research on Drive Torque Command Optimization and System Disturbance Rejection Mechanism for Torsional Vibration Control of Electromechanical Transmission System

The electromechanical transmission (EMT) system integrates the electric drive system and transmission system in vehicles, and its performance can degrade rapidly under specific operating conditions. This issue can be effectively improved by active torsional vibration suppression strategies. However, vibration suppression and dynamic response inherently contradict each other. In addition, many vibration suppression strategies are based on overly simplified models, resulting in poor alignment with real-world scenarios. To improve these issues, an active vibration suppression strategy based on feedforward-feedback control (AVS-FFC) is proposed. The feedforward strategy selects parameters based on dynamic response speed constraints, separates the main frequency of the drive torque from the EMT low-order natural frequencies, and minimizes the energy of the drive torque in the high-order natural frequency regions to reduce EMT torsional vibration. To address the challenges in strategy development due to inaccuracies in simplified models, a model reduction method based on modal contribution evaluation and stiffness sensitivity analysis is proposed. Using the reduced-order model, a feedback control strategy based on the EMT ideal characteristics is developed to mitigate the impact of disturbances on the vibration suppression effectiveness of the feedforward strategy. Simulations and experiments confirm the effectiveness of the AVS-FFC in suppressing torsional vibration.

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Publication Details

Journal
IEEE Transactions on Transportation Electrification
Published
2025-01-16
DOI
https://doi.org/10.1109/tte.2025.3530444
Citations
4
Primary Topic
Industrial Technology and Control Systems
Type
article
Field-Weighted Citation Impact
4.86

Funders

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article

Research on Drive Torque Command Optimization and System Disturbance Rejection Mechanism for Torsional Vibration Control of Electromechanical Transmission System

Dianzhao Yang, Pu Gao, Wei Zhang, Hui Liu et al.
4 citations
IEEE Transactions on Transportation Electrification
Industrial Technology and Control Systems
4.86
article

Research on Drive Torque Command Optimization and System Disturbance Rejection Mechanism for Torsional Vibration Control of Electromechanical Transmission System

Dianzhao Yang, Pu Gao, Wei Zhang, Hui Liu, Ke Chen, Huibin Yang, Qi Yan
article en
4 citations

Abstract

The electromechanical transmission (EMT) system integrates the electric drive system and transmission system in vehicles, and its performance can degrade rapidly under specific operating conditions. This issue can be effectively improved by active torsional vibration suppression strategies. However, vibration suppression and dynamic response inherently contradict each other. In addition, many vibration suppression strategies are based on overly simplified models, resulting in poor alignment with real-world scenarios. To improve these issues, an active vibration suppression strategy based on feedforward-feedback control (AVS-FFC) is proposed. The feedforward strategy selects parameters based on dynamic response speed constraints, separates the main frequency of the drive torque from the EMT low-order natural frequencies, and minimizes the energy of the drive torque in the high-order natural frequency regions to reduce EMT torsional vibration. To address the challenges in strategy development due to inaccuracies in simplified models, a model reduction method based on modal contribution evaluation and stiffness sensitivity analysis is proposed. Using the reduced-order model, a feedback control strategy based on the EMT ideal characteristics is developed to mitigate the impact of disturbances on the vibration suppression effectiveness of the feedforward strategy. Simulations and experiments confirm the effectiveness of the AVS-FFC in suppressing torsional vibration.

IEEE Transactions on Transportation ElectrificationVol. 11(3)
Beijing Institute of Technology (CN), Inner Mongolia Electric Power (China) (CN), Xiangtan University (CN)
National Natural Science Foundation of China, Beijing Nova Program
Affordable and clean energy
Openalex Percentile: Top 6%
Industrial Technology and Control Systems
4.86
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