Summary: | Digital control has become ubiquitous in the field of power electronics due to the ease of implementation, reusability, and flexibility. Practical engineers have been hesitant to use digital control rather than the more traditional analog control methods due to the unfamiliar theory, relatively complicated implementation and various challenges associated with digital quantization. This thesis presents discrete signal processing theory to solve issues in digitally controlled power converters including reference generation and filtering.
First, this thesis presents advancements made in the field of digital control of dc-ac and ac-dc power converters. First, a multi-carrier PWM strategy is proposed for the accurate and computationally inexpensive generation of sinusoidal signals. This method aims to reduce the cost of implementing a sine-wave generator by reducing both memory and computational requirements. The technique, backed by theoretical and experimental evidence, is simple to implement, and does not rely on any specialized hardware. The method was simulated and experimentally implemented in a voltage-controlled PWM inverter and can be extended to any application involving the digital generation of periodic signals.
The second advancement described in this thesis is the use of simple digital filters to improve the response time of single-phase active rectifiers. Under traditional analog control strategies, the bandwidth of an active rectifier is unduly restricted in order to reduce any unwanted harmonic distortion. This work investigates digital filters as a proposed means to improve the bandwidth, and thereby create a faster, more efficient ac-dc power converter. Finally, a moving average filter is proposed, due to its simple implementation and minor computational burden, as an efficient means to expand the bandwidth. Since moving average filters are well known and widely understood in industry, this proposed filter is an attractive solution for practicing engineers.
The theory developed in this thesis is verified through simulations and experiments.
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