Initial Rotor Position Estimation and Sensorless Control of SRM Based on Coordinate Transformation
Initial Rotor Position Estimation and Sensorless Control of SRM Based on Coordinate Transformation
复制标题
基于坐标变换的SRM转子初始位置估计与无传感器控制
DOI:
10.1109/tim.2014.2364699
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发表时间:
2015-04
影响因子:
5.6
通讯作者:
Deng, Zhiquan
中科院分区:
文献类型:
--
作者:
Cai, Jun;Deng, Zhiquan
Accurate estimation of the rotor position is essential for reliable start-up and sensorless control of switched reluctance motor drives. In this paper, a series of position estimation schemes based on phase inductance vector coordinate transformations are proposed. Using the rotating coordinate transformation and coordinate components normalization, the dc component and higher order harmonics of the normalized three-phase coordinate components can be eliminated effectively. According to the coordinate transformation theory, the rotating speed of the space vector is synchronized with the angular frequency of the three-phase inductance. Thus, through alpha-beta transformation, the synchronous rotating angle of the space vector and the rotor position can be estimated. Since the rotating angle can be arbitrary, it is possible to construct another coordinate system and find one of its normalized coordinate components that is perpendicular to the one in the former coordinate system. Based on the orthogonal coordinate transformation, the rotor position can also be estimated. Experiments have been implemented for verification. The proposed methods effectively solve the challenges in initial rotor position estimation and are also suitable for reliable sensorless starting under light-load conditions. However, these methods are not suitable for high-load driving-running conditions. To solve this problem, a combination of the phase current slope difference comparison-based method and the coordinate transformation-based method is developed in this paper. The experimental results verified the validity of this method. In addition, the proposed methods do not require additional hardware and complex computation, which simplifies the implementation.
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影响因子:
1.4
作者:
Jun Cai,;Zhiquan Deng
通讯作者:
Zhiquan Deng
影响因子:
6.7
作者:
Jun Cai;Z. Deng
通讯作者:
Jun Cai;Z. Deng
DOI:
--
发表时间:
2012
期刊:
--
影响因子:
--
作者:
Deng Zhiquan
通讯作者:
Deng Zhiquan
DOI:
10.1109/iecon.2013.6699572
发表时间:
2013-11
期刊:
IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society
影响因子:
--
作者:
Jun Cai;Qing-Chang Zhong;Z. Deng
通讯作者:
Jun Cai;Qing-Chang Zhong;Z. Deng
DOI:
10.1109/tim.2009.2017154
发表时间:
2009-06
影响因子:
5.6
作者:
K. Lu;Peter Omand Rasmussen;Andrew Ewen Ritchie
通讯作者:
K. Lu;Peter Omand Rasmussen;Andrew Ewen Ritchie