基于新型虚拟矢量调制方法的IPMSM模型预测电流控制方法

doi:10.19595/j.cnki.1000-6753.tces.230105

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Abstract

The model predictive control method has been widely applied in the control of internal permanent magnet synchronous motor (IPMSM). Conventional model predictive control methods can only select voltage vectors from the basic voltage vector, so the number of candidate voltage vectors is limited, which will generate large current and torque harmonics during motor operation. In order to increase the number of candidate voltage vectors, some papers have proposed methods for constructing virtual voltage vectors. However, when applying virtual vector modulation methods, the computational burden of the system will increase with the increase of the virtual vectors number, so the control performance will be limited by the system's computing power. To address this problem, this article proposes a novel virtual voltage vector modulation method, which reduces the burden of system computation by calculating the angle of the voltage vector.
The specific steps of the proposed novel virtual voltage vector modulation method are as follows. First, coordinate transformation is performed on the command voltage vector, and the command voltage vector is normalized by incorporating the magnitude of the DC bus voltage. After obtaining the coordinates of the normalized command voltage vector, the sector where the command voltage vector is located is determined by the the coordinate values. And the composite relationship between the command voltage vector and the adjacent two basic voltage vectors is obtained. By obtaining the composite relationship, the angle of the command voltage vector in the sector is obtained, and then the processing of the voltage vector is equivalent to the first voltage sector. Subsequently, each voltage sector is evenly divided into N parts to construct virtual voltage vectors, and the virtual voltage vectors in the first voltage sector are numbered. Then the virtual voltage vector with the closest angle to the command voltage vector is selected through the rounding function. Finally, the optimal duty cycle is obtained through the cost function. The opening time of each phase of the three-phase switch is calculated based on the obtained optimal voltage vector number and duty cycle.
In order to verify the effectiveness and reliability of the proposed method, this article conducted experiments on an IPMSM with a rated power of 1.5kW. The experimental results show that under steady-state conditions, compared to the predictive control method using a limited number of voltage vectors, this method reduces the harmonic content of the three-phase current by up to 3.4%. Moreover, when the number of sector partitions N is large enough, the proposed method can achieve current control performance close to that of the deadbeat predictive current control using SVPWM modulation at different speeds without SVPWM modulation. In dynamic situations, the proposed method can achieve faster dynamic response and smaller current harmonics during sudden changes in torque and speed. In addition, due to the omission of the traversal optimization process, the proposed method effectively reduces the system execution time, and the execution time of the system is the same for different N values.
In conclusion, the proposed method simplifies the modulation process of the model predictive control method, avoids the complex calculation caused by traversal optimization, and achieves the goal of increasing the number of virtual voltage vectors unrestricted.

Key words： Permanent magnet synchronous motor model predictive current control virtual voltage vector duty cycle modulation

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TM351

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	Articles by authors
	Wang Yizhe
	Huang Sheng
	Liao Wu
	Zhang Ji
	Huang Shoudao

Cite this article:

Wang Yizhe,Huang Sheng,Liao Wu等. IPMSM Model Predictive Current Control Method Based on a Novel Virtual Vector Modulation Method[J]. Transactions of China Electrotechnical Society, 0, (): 8920-.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.230105 OR https://dgjsxb.ces-transaction.com/EN/Y0/V/I/8920

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