感應馬達向量控制系統之高效能控制器設計

Design of High Efficiency Controller for Induction Motor Vector Control System

郭博禎(Po-Chen Kuo)

指導教授 ： 王順源

國立臺北科技大學/機電學院/電機工程系所/碩士(2013年)

摘要

一般感應馬達在額定轉速內運轉時，不論負載大小為何，其磁通命令皆維持定值，所以當馬達運轉在輕載時，產生的磁場電流命令大小將大於馬達激磁所需，而造成效率不佳。因此，本研究加入高效能控制於向量控制系統中以降低轉子磁通，使馬達的損失降低並提高運轉效率。本研究採用的方法為model-based類型的高效率能量控制，並考慮銅損及鐵損來建立出馬達損失模型和方程式，以找出損失最小化的最佳解。使系統在穩態時能依據交直軸電流比降低磁通電流，除了使馬達能穩定負載操作外，又可以達到節省電能之目的。
另外，由於受內部溫升效應影響，定轉子電阻值會變動，造成轉子磁通估測器準確性降低。因此本研究以直接轉子磁場導向感應馬達控制系統為基礎，設計適應性Takagi-Sugeno (T-S) 模糊降階型磁通估測器與適應性Takagi-Sugeno-Kang (TSK) 模糊定轉子電阻估測器，以精確估測轉子磁通與定轉子電阻。並利用TSK模糊估測器作轉速估測，將估測之轉速回授至適應性監督式模糊小腦模型速度控制器，以達到無轉速量測器向量控制之目的。
經由模擬和實驗結果證明，感應馬達向量控制系統中，植入高效能控制器、適應性監督式模糊小腦模型速度控制器、適應性T-S模糊磁通估測器、適應性TSK模糊定轉子電阻估測器與轉速估測器，在300 rpm到1800 rpm之轉速下運轉，負載為8 Nm、4 Nm、2 Nm及無載時轉速皆有優異的動態響應，同時估測器亦能達到準確的參數估測。高效能方面則有明顯的損失降低以達到省能的效果，在1200 rpm之轉速下無载運轉時，省能可達到37.18 W，效率可提升26.58 %。在1800 rpm之轉速下無載運轉時，省能可達到32.05 W，效率可提升25.16 %。在300 rpm之轉速下無載運轉時，省能可達到24.91 W，效率可提升44.2 %。

關鍵字

高效能控制 ； 向量控制 ； 適應性理論

並列摘要

Generally, no matter what the level of load torque, the flux command remain constant when induction motor operating within rated speed. So that the d axis current command of stator is larger than the required of motor excitation, and resulting in inefficient. This theis embeds loss-minimisation algorithms and vector control system in order to reduce the rotor flux, and to improve motor efficiency. The methods are using the model-based types of high-efficiency control which consider the copper loss and iron loss to establish the motor loss model and equations, and find the optimal flux solution for minimizing the loss. Therefore, this system can be based on d-q axis current ratio to reduce flux current in the steady state, to achieve not only stable operation of the motor load but also saving energy.
It is well known that the rotor flux of induction motor cannot be accurately estimated owing to the fluctuation of rotor resistance caused by temperature variation, so that this thesis proposes an adaptive pseudo reduced-order Takagi-Sugeno (T-S) fuzzy flux estimator and an adaptive Takagi-Sugeno-Kang (TSK) rotor resistance estimator, to accurately estimate the rotor flux and the stator and rotor resistance. Moreover, the thesis utilizes a TSK technique to estimate the rotor speed precisely, and the estimated rotor speed is fed back to the adaptive supervisory fuzzy cerebellar model articulation speed controller (ASFCMAC) to achieve an induction motor sensorless control system.
To verify the practicality and effectiveness of the proposed schemes, experiments are performed under the conditions that the speed command 300 rpm, 1200 rpm and 1800 rpm, and the torque load 0 Nm, 2 Nm, 4 Nm and 8 Nm are applied. The experimental results indicate that the proposed system has not only superior speed dynamic response but also accurate parameter estimation, and the motor losses reduce significantly to achieve the energy saving target. When the motor is operating at 1200 rpm and 0 Nm, energy saving can be achieved 37.18 W and efficiency can be improved 26.58 %. When the motor is operating at 1800 rpm and 0 Nm, energy saving can be achieved 32.05 W and efficiency can be improved 25.16 %. When the motor is operating at 300 rpm and 0 Nm, energy saving can be achieved 24.91 W and efficiency can be improved 44.2 %.

並列關鍵字

Loss-Minimisation Algorithms ； Vector Control ； Adaptive Theory

參考文獻

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