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Review Paper

An Overview of Voltage-Regulation Control for DC-DC Converters

JINSUNG KIM

Presenter

jinsung.kim@inha.edu

E-mail

Electrical Engineering, INHA University

Department

LCIS

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Table of Contents

Introduction

Topology of DC-DC Converters

Control methods for DC-DC Converters

Configuration
Features

Time-Optimal Control using PMP

Problem Formulation
Concept Figure
Simulation Result

FCS-MPC

Principle & Features
Need for Value Function Approximation
3-phase Inverter Simulation

Conclusion

References

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In our lives, power electronics is widely used in many fields.

In automotive, they have many power electronics components.

In renewable energy systems, they need energy storage systems and conversion systems.

Typical application of power electronics include power conversion.

Types of power conversion

DC-to-DC (DC-DC Converter)

AC-to-AC (AC-AC Converter)

AC-to-DC (Rectifier)

DC-to-AC (Inverter)

1. Introduction

Importance of controlling in power electronics

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The objective of DC-DC Converters

To generate a constant dc voltage level despite variations in input voltage or load.

Types of DC-DC Converters

Buck Converter
Boost Converter
Buck-Boost Converter

1. Introduction

DC-DC Converter

DC-DC Converter

DC Voltage

DC Voltage

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2. Topology of DC-DC Converters

Dynamics of DC-DC Converters

The switch-controlled dynamics

Figure 1 : Switched DC-DC Converters

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2. Topology of DC-DC Converters

State Space Model of DC-DC Converters

Buck Converter

Boost Converter

Buck-Boost Converter

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3. Control Methods for DC-DC Converter

Control Methods for DC-DC Converters

Optimization-based Controller

Linear Controllers

Pontryagin’s Minimum Principle

Dynamic Programming

Voltage Mode Control

Current Mode Control

Dead-Beat Control

Model Predictive Control

Nonlinear Controllers

Sliding Mode Control

Fuzzy Logic Control

Configuration

CCS-MPC

FCS-MPC

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Features

	Linear Controller		Nonlinear Controller
	VMC	CMC	SMC	FLC
Advantage	Implementation High noise tolerance	Application Improved transient response Stability in Feedback loop	Simplicity Implementation Stability Robustness Fast dynamic response	Simplicity Low-cost implementation Easy adaptation Robustness
Disadvantage	Reliability Stability Simplicity Slow and Inefficient	Sub-harmonic oscillations High sensitivity (Low noise tolerance)	Variable frequency Not available in IC forms	Inaccuracy Lower speed

3. Control Methods for DC-DC Converter

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Features

	Optimization-based Control
	PMP	DP	MPC
Advantage	Less computational time Implementation Simplicity Slow and Inefficient	Achieves global optimum Simple and Efficient Systematic procedure	Control law is straightforward Apply with multivariable Enhanced transient response Considering nonlinearity and constraints
Disadvantage	Achieves sub-optimal Difficult Tunning of co-state	Curse of dimensionality Not suitable for real-time implementation	Computational complexity

3. Control Methods for DC-DC Converter

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4. Time-Optimal Control using PMP

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State-dependent switching curve

4. Time-Optimal Control using PMP

State Feedback Optimal Control Law : Concept Figure

Figure 2 : Switching curves and controlled time-optimal trajectories

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4. Time-Optimal Control using PMP

State Feedback Optimal Control Law : Simulation Results

Figure 3 : Switching curve for the case 1

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4. Time-Optimal Control using PMP

State Feedback Optimal Control Law : Simulation Results

Figure 4 : Switching curve for the case 2

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4. Time-Optimal Control using PMP

State Feedback Optimal Control Law : Simulation Results

Figure 5 : Switching curve for the case 3

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Types of MPC

Continuous Control Set (CCS)-MPC

Continuous switching states
Need a modulator and generates fixed switching frequency

Finite Control Set (FCS)-MPC

Finite number of switching states
No need modulator and generates variable switching frequency
FCS-MPC applies well to power converters requiring fast control.

Principle of MPC

5. FCS-MPC

Predictive Model

Minimization of the cost function

DC-DC Converter

Load

measurement

Figure 6: The procedure of MPC

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The advantage of FCS-MPC

Evaluating only a finite number of times.
Thus, the total number of control inputs is small, the computational burden is reduced. (Attractive for Embedded Control)

Long prediction problem

However, the converter requires long prediction horizon inherently.
Thus, we need to approximate the optimization problem to solve the computational burden.

Need for Value Function Approximation (Future Work)

Thus, we consider the value function approximation.
The planning horizon are split into two segments.

At first segment, the problem does not change.
At Second segment, the optimal cost is approximated as quadratic function.

5. FCS-MPC

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5. FCS-MPC

Figure 7: 3-Phase Inverter Model

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5. FCS-MPC

Figure 8 : Voltage Vectors

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5. FCS-MPC

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5. FCS-MPC

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Three-phase Inverter : Simulation Results

Reference

Figure 9 : Reference signal of current

5. FCS-MPC

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Three-phase Inverter : Simulation Results

Figure 10 : Controlled signal of current

5. FCS-MPC

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Three-phase Inverter : Simulation Results

5. FCS-MPC

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Summary

Presenting some control methods for DC-DC Converters.
Analyzed the pros and cons about each control methods.
Above them, we focusing on PMP and FCS-MPC
Simulating time-optimal control using PMP and obtained switching curves.
For the fast control which applies well to power converter, FCS-MPC is essential.
The inverter control using FCS-MPC is shown and the controlled current signal is well fitted to reference sine-wave.
To solve long prediction problem of FCS-MPC, Value Function Approximation is important.

Future Work

Study on Value Function Approximation as Quadratic Function.
Investigate some papers using DSP or FPGA in power electronics.

6. Conclusion

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S. V. Dhople, K. A. Kim, A. D. Domnguez-Garca, “Time-optimal control in DC-DC converters: A maximum principle perspective,” in Proc. 2014 IEEE Applied Power Electronics Conference and Exposition – APEC 2014, pp. 2804-2808, March. 2014.

S. Kouro, P. Cortes, R. Vargas, U. Ammann, and J. Rodriguez, “Model predictive control—A simple and powerful method to control power converters,” IEEE Trans. Ind. Electron., vol. 56, no. 6, pp. 1826–1838, Jun. 2009.

P. Cortes, M. P. Kazmierkowski, R. M. Kennel, D. E. Quevedo, and J. Rodriguez, “Predictive control in power electronics and drives,” IEEE Trans. Ind. Electron., vol. 55, no. 12, pp. 4312–4324, Dec. 2008.

J. Rodrıguez et al., “State of the art of finite control set model predictive control in power electronics,” IEEE Trans. Ind. Inf., vol. 9, no. 2, pp. 1003–1016, May. 2013.

N. Moehle and S. Boyd, “Value Function Approximation for Direct Control of Switched Power Converters,” Proc. IEEE Conference on Industrial Electronics and Applications (ICIEA), pp. 360-367, June. 2017.

S. Vazquez, J. Rodriguez, M. Rivera, L. G. Franquelo, and M. Norambuena, “Model predictive control for power converters and drives: Advances and trends,” IEEE Trans. Ind. Electron., vol. 64, no. 2, pp. 935–947, Feb. 2017.

J. Rodriguez, J. Pontt, C. A. Silva, P. Correa, P. Lezana and P. Cortes, “Predictive Control of a Voltage Source Inverter,” IEEE Trans. Ind. Electron., vol. 54, no. 1, pp. 499-503, February. 2007.

7. References

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Thank you