Abstract
This paper investigates the performance of a newly developed particle filter (PF) algorithm for sensorless control of the Brushless DC (BLDC) machines. A number of modifications have also been incorporated to the proposed PF algorithm in order to improve its performance with respect to resampling process and robust operation when unpredicted disturbances are occurred. The disturbances investigated in this paper include the presence of unconventional Non-Gaussian noises, changes in machine’s parameters, and occurrence of inter-turn short circuit fault. In addition, the paper proposes several measures in order to improve the estimation accuracy of the filter and enhance the filter robustness against system uncertainties. In order to evaluate the performance of the PF algorithm, the sensorless control system of a 1.5 kW BLDC machine is simulated in MATLAB/Simulink environment. Simulation results show that the introduced techniques considerably improve the performance of the PF algorithm as state estimator.
Original language | English |
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Pages | 1067-1073 |
Number of pages | 7 |
DOIs | |
Publication status | Published - 1 Dec 2020 |
Event | International Conference on Electrical Machines (ICEM) - Gothenburg, Sweden Duration: 23 Aug 2020 → … |
Conference
Conference | International Conference on Electrical Machines (ICEM) |
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Country/Territory | Sweden |
City | Gothenburg |
Period | 23/08/20 → … |
Keywords
- Brushless DC (BLDC) Machine
- Inter-turn Short Circuit Fault
- Particle Filter
- Resampling Process
- Sensorless Drives