Sensorless control of PMSM for DC micro‐grid flywheel energy storage based on EKF

Zhang, Dan; Jian, Jiang

doi:10.1049/joe.2018.8604

Cited by 6 publications

(3 citation statements)

References 18 publications

(15 reference statements)

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“…At the same time, it also has good robustness to motor parameters. EFK algorithm is a recursive algorithm, which is divided into prediction stage and correction stage [43][44][45][46] .…”

Section: Sensor-less Controlmentioning

confidence: 99%

Control technology and development status of flywheel energy storage system

Jia

Zhang

et al. 2022

ITM Web Conf.

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Flywheel energy storage technology has attracted more and more attention in the energy storage industry due to its high energy density, fast charge and discharge speed, long service life, clean and pollution-free characteristics. It is wwidely used in uninterruptible power system, grid frequency modulation, energy recovery and reuse and other fields. With the development of flywheel rotor materials, motors, bearings and control technology, flywheel energy storage technology has been greatly developed. Introducing the basic structure of the flywheel energy storage system in the above three applications. Typical charge-discharge control strategies are given for the three sensor-less algorithms of model reference adaptive control, sliding mode observer andextended Kalman filter, which are suitable for flywheel energy storage devices.

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“…At the same time, it also has good robustness to motor parameters. EFK algorithm is a recursive algorithm, which is divided into prediction stage and correction stage [43][44][45][46] .…”

Section: Sensor-less Controlmentioning

confidence: 99%

Control technology and development status of flywheel energy storage system

Jia

Zhang

et al. 2022

ITM Web Conf.

View full text Add to dashboard Cite

show abstract

“…Unlike high-frequency signal injection methods, back-EMF model-based methods have no restriction regarding the structure of the PMSM and do not need extra highfrequency signal sources. Commonly used back-EMF model-based methods include sliding-mode-control (SMO) [11]- [16], model reference adaptive system (MRAS) [17]- [23] and extended Kalman filter (EKF) [24]- [26]. The design of the observers in these methods is very important because the quality of the estimation directly affects the performance of the whole control scheme.…”

Section: Introductionmentioning

confidence: 99%

“…Compared to EKF, the model-based method has been adopted for sensorless control in many applications as it is simple and easy to implement [26]. Rotor flux MRAS was first introduced by Schauder [19], and a lot of effort has been focused on improving its performance [8], [33].…”

Section: Introductionmentioning

confidence: 99%