Competent Discrete Time Modeling For analogue controlled PWM Converter Considering State-Feedback

TL;DR

This paper reviews and analyzes various small signal models for PWM converters, focusing on their accuracy, analytical simplicity, and applicability, especially in high-bandwidth control scenarios.

Contribution

It provides a comprehensive overview of existing models, highlighting their strengths and limitations in high-bandwidth PWM converter control.

Findings

Existing models often assume low-frequency and small ripple conditions.

High-bandwidth applications violate traditional model assumptions.

The paper identifies gaps and proposes directions for improved modeling.

Abstract

Ever since R.D.Middlebrook proposed the state space averaging notion. The small signal model has been widely used as a design tool to tune control parameters. As Moore's law is continuing and the AI chip's high demand for power consumption and dynamic response, the control bandwidth needs to be boosted. However, the average model has two basic assumptions: the low-frequency assumption, the small ripple assumption. In high-bandwidth design, these two assumptions are violated. In order to solve this, various methods have been proposed. This paper gives a comprehensive overview of the existing small signal model for PWM converters from the following perspectives: 1. model fidelity, 2. analytical tractability. 3. complexity of the derivation process and result 4.generality.