Torsional Oscillation-Considered Engine Start–Stop Coordinate Control for PSHEV via Scenario-Adaptive Composite Robust Control Strategy

The fuel consumption of power-split hybrid electric vehicles (PSHEVs) can be effectively reduced via mode transition that includes the engine process. However, factors such as engine torque ripple, system parameter uncertainties, and variations in torsional vibration characteristics can easily induce drivetrain vibration. These factors not only degrade ride comfort but also lead to a fundamental control challenge. The inherent trade-off between rapid response and stability is difficult to reconcile. In addition, the lack of adaptive mechanisms further limits consistent performance under varying conditions. To tackle these problems, a scenario-adaptive composite robust control (SACRC) strategy is proposed. The strategy consists of a UIO (unknown input observer)-based torque observation module, an adaptive VSS-LMS approach, and an H∞ controller with self-tuning parameters. Firstly, a six-degree-of-freedom dynamic model of the PSHEV transmission system is established with excitation sources, considering the characteristics of dual elastic elements. Secondly, a UIO-based torque observer is designed using a simplified dual-elastic-element model. By using engine speed and output shaft speed, the observer can accurately identify the torque transmitted by the torsional damper and drive shaft. Then, an adaptive VSS-LMS and H∞ controller with self-tuning parameters is constructed to ensure a balanced performance between fast torsional vibration suppression and control stability. Finally, simulation and experimental results demonstrate that the proposed strategy provides favorable adaptability to complex scenarios, and unifies the performance goals of rapidity, stability, and robustness.

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Publication Details

Journal
Machines
Published
2026-04-22
DOI
https://doi.org/10.3390/machines14050464
Primary Topic
Control Systems in Engineering
Type
article
Field-Weighted Citation Impact
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article

Torsional Oscillation-Considered Engine Start–Stop Coordinate Control for PSHEV via Scenario-Adaptive Composite Robust Control Strategy

Yudong Zhong, Dengfeng Zhao, Fang Zhou, Junjian Hou et al.
Machines
Control Systems in Engineering
article

Torsional Oscillation-Considered Engine Start–Stop Coordinate Control for PSHEV via Scenario-Adaptive Composite Robust Control Strategy

Yudong Zhong, Dengfeng Zhao, Fang Zhou, Junjian Hou, Zhijun Fu, Jinquan Ding, Zhenwei Wang
article en

Abstract

The fuel consumption of power-split hybrid electric vehicles (PSHEVs) can be effectively reduced via mode transition that includes the engine process. However, factors such as engine torque ripple, system parameter uncertainties, and variations in torsional vibration characteristics can easily induce drivetrain vibration. These factors not only degrade ride comfort but also lead to a fundamental control challenge. The inherent trade-off between rapid response and stability is difficult to reconcile. In addition, the lack of adaptive mechanisms further limits consistent performance under varying conditions. To tackle these problems, a scenario-adaptive composite robust control (SACRC) strategy is proposed. The strategy consists of a UIO (unknown input observer)-based torque observation module, an adaptive VSS-LMS approach, and an H∞ controller with self-tuning parameters. Firstly, a six-degree-of-freedom dynamic model of the PSHEV transmission system is established with excitation sources, considering the characteristics of dual elastic elements. Secondly, a UIO-based torque observer is designed using a simplified dual-elastic-element model. By using engine speed and output shaft speed, the observer can accurately identify the torque transmitted by the torsional damper and drive shaft. Then, an adaptive VSS-LMS and H∞ controller with self-tuning parameters is constructed to ensure a balanced performance between fast torsional vibration suppression and control stability. Finally, simulation and experimental results demonstrate that the proposed strategy provides favorable adaptability to complex scenarios, and unifies the performance goals of rapidity, stability, and robustness.

MachinesVol. 14(5)
Zhengzhou University of Light Industry (CN)
Affordable and clean energy
Openalex Percentile: Top 11%
Control Systems in Engineering
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