Non-Linear Characterization and Control of Interior Permanent Magnet Synchronous Machines
2022-06
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Non-Linear Characterization and Control of Interior Permanent Magnet Synchronous Machines
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2022-06
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The dissertation will present a systematic process for advanced characterization and control of a popular class of synchronous machines called Interior Permanent Magnet Synchronous Machines (IPMSM). The IPMSM machine exhibits several non-linear properties such as flux saturation and cross-coupling to name a few. Knowledge of the non-linear properties of the machine requires access to advanced design tools such as Finite Element Analysis (FEA) which may not be easily accessible within industries that do not design or manufacture these motors. The performance and efficiency of these motors are reliant on precise knowledge of advanced parameters. This body of work develops into two focus areas - experimental characterization of the IPM machine and Maximum Torque Per Amp (MTPA) based control of the machine using the experimental data. Firstly, the dissertation proposes an experimental method for extraction of Direct (D) and Quadrature (Q) axis flux linkages of the IPMSM considering both saturation and cross-magnetization effects over the entire range of the machine’s rated current. A key constraint placed is a standstill estimation of the machine in its targeted application. A novel method for generating the current pulse pattern is proposed which enables the automatic creation of 2D Flux Linkage maps of the motor using any standard controller. Analytical expressions are developed to determine the constraints for pulse pattern considering the power converter-based current control and minimizing rotor movement during the test. The flux maps obtained experimentally are seen to match the FEA-generated equivalent within an acceptable tolerance of error. The second focus area consists of developing MTPA control schemes that address practical issues such as complex offline/online calculations/excitation methods seen in classic literature. Initial research focused on developing an offline numerically efficient MTPA trajectory generation that uses FEA data to create a torque profile related to the optimal solution of net space vector current and corresponding current angle. Further research removed the dependency of the offline MTPA trajectory generation scheme on the FEA dataset by developing a method that utilizes simple motor datasheet parameters to get an initial non-efficient trajectory. This trajectory is fine-tuned during motor operation (online) via a novel discrete extremum-seeking state controller. While the offline method is shown to execute with minimal computational demand in a 32-bit MCU controller, the online method is shown to have comparable real-time performance while achieving equivalent MTPA tracking accuracy without introducing electrical or mechanical instability. Both methods have been implemented in a classic Field Oriented Control (FOC) scheme for the IPM motor using a standard 2-level Voltage Source Inverter (2L-VSI) prototype supplied from a 650V DC power supply. The methods have been experimentally verified on a 3 HP dynamometer with custom-built data acquisition instrumentation as well as software. Experimental results show good correspondence to simulations thus proving the effectiveness of the proposed methods.
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University of Minnesota Ph.D. dissertation. June 2022. Major: Electrical/Computer Engineering. Advisors: Ned Mohan, Kaushik Basu. 1 computer file (PDF); xiv, 199 pages + 2 supplemental files.
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Chandrasekaran, Visweshwar. (2022). Non-Linear Characterization and Control of Interior Permanent Magnet Synchronous Machines. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/241760.
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