image: The concept of virtual position offset injection is to virtually apply a position offset to current and voltage measurements to effectively cancel the influence from winding temperature rise and inverter deadtime effect. Without loss of generality, let the position-offset be ε and the relation between the actual and virtual dq-axis is presented in this figure.
Credit: CES Transactions on Electrical Machines and Systems
Research content
The study of virtual frame temperature estimation model is to calculate the permanent magnet temperature (PMT) directly from the measurements with computation efficiency. The method mathematically applies a position-offset to derive the estimation model with resistance and inverter distortion cancelled. The position offset is not actually injected, so the estimation will not affect the motor operation. The estimation is independent from winding temperature rise and inverter distortion, and there is no need for fixing winding temperature in building compensation model, which can greatly simplify the implementation.
The research results and their significance
For practical applications, high performance control of the PMSMs is critical. However, PMT rise can greatly affect the control performance and excessive temperature rise can cause the permanent demagnetization of PMs and thus break the motor. In other words, accurate PMT is critical to achieve high-performance and reliable control of PMSM. On one hand, PMT can be measured by thermal imagers or Hall sensors. However, direct measurement is not feasible in practical applications due to installation cost, accuracy and reliability concerns.
The estimation model that is independent from winding temperature rise and inverter distortion was developed in this study, and there is no need for fixing winding temperature in building compensation model, which can greatly simplify the implementation. In comparison to existing invasive methods, the proposed approach is noninvasive and independent from winding temperature rise; in comparison to existing noninvasive methods, the proposed approach is computation-efficient and independent from winding temperature rise, inverter distortion and magnetic saturation. In comparison to the data driven based approaches, the proposed approach is computation-efficient and does not require massive offline data and training procedure. The results of extensive tests under various operating conditions on the test motor have demonstrated the improvement of PMT, in which the estimation error is no more than four degrees.
Future outlook
The Sun Yat-sen University research team plans to optimize their techniques further to improve the accuracy and robustness of the PMT estimation. Future work will focus on investigating the influence of core loss in the deep flux-weakening region and compensate this to further improve the estimation performance. "Our next goal is to optimize our approach to be applicable for high-speed conditions, such as electrical vehicle traction applications by compensating core loss effect," explained Feng.
Journal
CES Transactions on Electrical Machines and Systems
Method of Research
Computational simulation/modeling
Subject of Research
Not applicable
Article Title
Permanent Magnet Temperature Estimation for PMSMs Using Virtual Position-Offset Injection
Article Publication Date
25-Apr-2024