Four Quadrant Operation and Regenerative Braking Control of PMSM Drive Systems

Authors

Abstract

A novel control strategy of permanent magnet synchronous motor (PMSM) drive systems is proposed. Based on radial basis function neural network (RBFNN) and direct model reference adaptive control (MRAC), the grid-side controller is designed to regulate output direct current (DC) bus voltage. The coordination control combined sliding model control (SMC) based on signal and port-controlled Hamiltonian (PCH) control based on energy is used to motor-side and achieves the fast speed tracking control and the real-time energy optimization. The controllers based on regenerative braking ensure that the motor can run in four quadrant, energy is bidirectional flow, and the DC bus voltage is controllable. The simulation results demonstrate the validity of the strategy.

Keywords

coordination control, four quadrant, rbfnn, regenerative braking

Citation

ISBN: 9789811064449
Publisher: Springer Singapore
DOI: 10.1007/978-981-10-6445-6_62
Note: Chinese Intelligent Automation Conference

BibTeX

@inbook{Cheng_2017,
  title={{Four Quadrant Operation and Regenerative Braking Control of PMSM Drive Systems}},
  ISBN={9789811064456},
  ISSN={1876-1119},
  DOI={10.1007/978-981-10-6445-6_62},
  booktitle={{Proceedings of 2017 Chinese Intelligent Automation Conference}},
  publisher={Springer Singapore},
  author={Cheng, Xinxin and Yu, Haisheng and Yu, Jinpeng},
  year={2017},
  pages={571--579}
}

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References

Pillay, P. & Krishnan, R. Control characteristics and speed controller design for a high performance permanent magnet synchronous motor drive. IEEE Trans. Power Electron. 5, 151–159 (1990) – 10.1109/63.53152
Kaynak, O., Erbatur, K. & Ertugnrl, M. The fusion of computationally intelligent methodologies and sliding-mode control-a survey. IEEE Trans. Ind. Electron. 48, 4–17 (2001) – 10.1109/41.904539
Pan, C. et al. Research on motor rotational speed measurement in regenerative braking system of electric vehicle. Mechanical Systems and Signal Processing 66–67, 829–839 (2016) – 10.1016/j.ymssp.2015.06.001
Zhou, D., Zhao, J. & Li, Y. Model-Predictive Control Scheme of Five-Leg AC–DC–AC Converter-Fed Induction Motor Drive. IEEE Trans. Ind. Electron. 63, 4517–4526 (2016) – 10.1109/tie.2016.2541618
SM Gadoue, IEEE Int Symp Ind Electron (2008)
Ortega, R., van der Schaft, A., Maschke, B. & Escobar, G. Interconnection and damping assignment passivity-based control of port-controlled Hamiltonian systems. Automatica 38, 585–596 (2002) – 10.1016/s0005-1098(01)00278-3
Yu, H., Yu, J., Liu, J. & Song, Q. Nonlinear control of induction motors based on state error PCH and energy-shaping principle. Nonlinear Dyn 72, 49–59 (2012) – 10.1007/s11071-012-0689-3
Lin, S. & Zhang, W. An adaptive sliding-mode observer with a tangent function-based PLL structure for position sensorless PMSM drives. International Journal of Electrical Power & Energy Systems 88, 63–74 (2017) – 10.1016/j.ijepes.2016.12.006
Turker, T., Buyukkeles, U. & Bakan, A. F. A Robust Predictive Current Controller for PMSM Drives. IEEE Trans. Ind. Electron. 63, 3906–3914 (2016) – 10.1109/tie.2016.2521338
H Yu, Syst Eng Electron (2006)