储能科学与技术 ›› 2021, Vol. 10 ›› Issue (5): 1631-1642.doi: 10.19799/j.cnki.2095-4239.2021.0237

• 物理储能十年专刊·飞轮 • 上一篇    下一篇

飞轮储能轴承结构和控制策略研究综述

于苏杭1,2(), 郭文勇1,2(), 滕玉平1,2, 桑文举1,2, 蔡洋1,2, 田晨雨1,2   

  1. 1.中国科学院大学,北京 100049
    2.中国科学院电工研究所,北京 100190
  • 收稿日期:2021-05-31 修回日期:2021-06-22 出版日期:2021-09-05 发布日期:2021-09-08
  • 作者简介:于苏杭(1997—),男,硕士研究生,研究方向为高温超导飞轮储能控制系统,E-mail:ysh@mail.iee.ac.cn|郭文勇,研究员,研究方向为储能技术、风力发电和电力电子技术,E-mail:wyguo@mail.iee.ac.cn
  • 基金资助:
    国家重点研发计划项目(2018YFB0905800);国家自然科学基金项目(51877206)

A review of the structures and control strategies for flywheel bearings

Suhang YU1,2(), Wenyong GUO1,2(), Yuping TENG1,2, Wenju SANG1,2, Yang CAI1,2, Chenyu TIAN1,2   

  1. 1.University of Chinese Academy of Sciences, Beijing 100049, China
    2.Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, China
  • Received:2021-05-31 Revised:2021-06-22 Online:2021-09-05 Published:2021-09-08

摘要:

飞轮储能具有高功率密度、高效率和低损耗的特点,在不间断电源和电网调频等领域有广阔的应用前景。飞轮储能轴承起到支撑飞轮重量、降低摩擦阻力的作用,是决定飞轮储能量、充放电效率和使用寿命的关键。结构和控制是飞轮轴承的两个核心关键技术。本文分析了应用于飞轮储能的机械轴承、电磁轴承、高温超导磁悬浮轴承以及混合轴承的结构,并总结了不同轴承飞轮储能的损耗、转速、储能量和承载力等性能参数,指出混合磁轴承性能最优,可以降低飞轮的损耗和提高飞轮的转速。另外归纳了目前应用于电磁轴承系统的控制方法,介绍了PID控制、滑模控制、模型预测控制和神经网络控制和解耦控制在电磁轴承控制方面的应用,并进一步分析了未来飞轮磁悬浮轴承控制技术的发展方向。对各种控制方法的比较分析结果表明:在飞轮转子线性工作范围内PID控制方法能保持系统稳定;在飞轮转子非线性工作区域,滑模控制、模型预测控制和神经网络控制效果更优;而解耦控制进一步提高了飞轮在高转速下的控制精度。本文可为开展飞轮储能轴承结构和控制方法的研究提供参考。

关键词: 飞轮储能, 电磁轴承, 高温超导磁悬浮, 非线性控制, 解耦控制

Abstract:

Flywheel energy storage has the high power density characteristics of high efficiency and low losses. It has been widely applied in uninterruptible power supplies and grid frequency regulation. Flywheel bearings play an important role in supporting the weight of a flywheel and reducing frictional resistance. It is the key component for determining energy storage capability, charging and discharging efficiency, and the service life of a flywheel. This paper investigates the mechanical structure of active magnetic, high-temperature superconducting magnetic, and hybrid bearings for a flywheel energy storage system. The results showed that hybrid magnetic bearings had the best performance and could lower the losses and increase the rotating speed of the flywheel. Furthermore, the control strategies for active magnetic bearings, including proportional-integral-differential (PID) control, sliding mode control, model predictive control, neural network control, and decoupling control, were introduced and compared. The flywheel bearings' future development trends were also analyzed. The study concludes that the PID control method can keep the system stable in the flywheel rotor linear working range. Contrastingly, the sliding mode, model predictive, and neural network control approaches showed better performance in a nonlinear working range. The advantage of the decoupling control was a high control accuracy at a high speed. This paper contributes to providing guidelines for the study of the flywheel bearing structure and control system.

Key words: flywheel energy storage, electromagnetic bearing, high temperature superconducting magnetic levitation, nonlinear control, control decoupling

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