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Electromagnetic Interference Mitigation in Switched Mode Power Converters Using Digital Sampling TechniquesHAMZA, DJILALI 08 November 2011 (has links)
Increasing power density of switch mode power supplies, by increasing their switching frequency has becoming a challenging obstacle for EMI mitigation. The passive EMI suppression technique has always been the primary solution to fulfill the EMC requirement in terms of conducted emission limits. However, the call for stringent power supplies specifications renders the passive techniques less desirable, due to their increasing size and power losses. In other words, the greater the power density of the converter, the bigger the passive filter. Other suppression techniques such as the spread spectrum frequency modulation (SSFM), and soft switching, prove to have less performance and much complex to implement. The active analog EMI filters provide the basic noise suppression technique; however, their performance is dramatically impeded at higher frequency. This solution requires an additional small size passive filter to complete the EMC spectrum for conducted emissions.
Digital active filtering techniques offer advantages of flexibility, fewer external components and reduced overall size and power losses as compared to conventional passive filtering techniques.
In this thesis DSP-based and FPGA-based EMI control techniques to mitigate the conducted emissions of switch mode power converters are proposed. These techniques are implemented in-lieu of the passive filtering techniques, by keeping equal or better performance. Moreover, these solutions can be configured as a stand-alone or integrated into the converter digital controller algorithm.
Finally, the proposed solutions are implemented into three types of power converters, namely, a AC-DC power factor corrected converter, DC-AC micro-inverter for Photovoltaic application, and DC-DC for Electric Vehicle (EV) battery charger. Analytical, simulation and experimental results are provided to verify the proposed solutions. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2011-11-07 10:48:49.191
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