Description
Introduces chaos theory, its analytical methods and the means to apply chaos to the switching power supply design
DC-DC converters are typical switching systems which have plenty of nonlinear behaviors, such as bifurcation and chaos. The nonlinear behaviors of DC-DC converters have been studied heavily over the past 20 years, yet researchers are still unsure of the practical application of bifurcations and chaos in switching converters. The electromagnetic interference (EMI), which resulted from the high rates of changes of voltage and current, has become a major design criterion in DC-DC converters due to wide applications of various electronic devices in industry and daily life, and the question of how to reduce the annoying, harmful EMI has attracted much research interest. This book focuses on the analysis and application of chaos to reduce harmful EMI of DC-DC converters.
After a review of the fundamentals of chaos behaviors of DC-DC converters, the authors present some recent findings such as Symbolic Entropy, Complexity and Chaos Point Process, to analyze the characters of chaotic DC-DC converters. Using these methods, the statistic characters of chaotic DC-DC converters are extracted and the foundations for the following researches of chaotic EMI suppression are reinforced. The focus then transfers to estimating the power spectral density of chaotic PWM converters behind an introduction of basic principles of spectrum analysis and chaotic PWM technique. Invariant Density, and Prony and Wavelet analysis methods are suggested for estimating the power spectral density of chaotic PWM converters. Finally, some design-oriented applications provide a good example of applying chaos theory in engineering practice, and illustrate the effectiveness on suppressing EMI of the proposed chaotic PWM.
- Introduces chaos theory, its analytical methods and the means to apply chaos to the switching power supply design
- Approaches the subject in a systematic manner from analyzing method, chaotic phenomenon and EMI characteristics, analytical methods for chaos, and applying chaos to reduce EMI (electromagnetic interference)
- Highlights advanced research work in the fields of statistic characters of nonlinear behaviors and chaotic PWM technology to suppress EMI of switching converters
- Bridges the gap between numerical theory and real-world applications, enabling power electronics designers to both analyze the effects of chaos and leverage these effects to reduce EMI
Chapter
1.2.5 Discrete Model of DC–DC Converters
1.3 Overview of the Nonlinear Behavior of DC–DC Converters
1.4 Review of Basic Dynamics Concepts
1.4.2 Linear and Nonlinear Dynamical Systems
1.4.3 Characterization of Nonlinear Behavior
Chapter 2 Symbolic Analysis of the Nonlinear Behavior of DC–DC Converters
2.2 Overview of the Time Series Principle of Discrete Systems
2.2.1 Symbolic Dynamics and Symbolic Time Series
2.2.2 Symbolization Method
2.2.3 Symbolic Dynamics of a Period-Doubling Cascade
2.4 Symbolic Time Series Analysis of DC–DC Converters
2.4.1 Period-Doubling Bifurcation and Chaos of DC–DC Converters
2.4.2 Border Collision Bifurcation and Chaos of DC–DC Converters
Chapter 3 Complexity of the Nonlinear Behavior of DC–DC Converters
3.2 Lempel–Ziv Complexity and Analysis of Nonlinear Behavior of DC–DC Converters Based on L–Z Complexity
3.2.1 Lempel–Ziv Complexity
3.2.2 Analysis of Lempel–Ziv Complexity of Buck Converter
3.3 Switching Block of DC–DC Converters
3.4 Weight Lempel–Ziv Complexity and Analysis of Nonlinear Behavior of DC–DC Converters Based on Weight L–Z Complexity
3.4.1 Weight Lempel–Ziv Complexity
3.4.2 Weight Lempel–Ziv Complexity of Buck Converter
3.4.3 Qualitative Analysis of Bifurcation Phenomena Based on Complexity
3.5 Duplicate Symbolic Sequence and Complexity
3.5.1 Main Switching Block and Main Symbolic Sequence
3.5.2 Secondary Switching Block and Secondary Symbolic Sequence
3.5.3 Duplicate Symbolic Sequence
3.5.4 Analysis of Border Collision and Bifurcation in DC–DC Converters Based on Duplicate Symbolic Sequence
Chapter 4 Invariant Probability Distribution of DC–DC Converters
4.2 Invariant Probability Distribution of Chaotic Map
4.3 Calculating Invariant Probability Distribution of the Chaotic Discrete-Time Maps with Eigenvector Method
4.4 Invariant Probability Distribution of the Chaotic Mapping of the Boost Converter
4.5 Application Examples of Invariant Probability Distribution
4.5.1 Power Spectral Density of the Input Current in a DC–DC Converters
4.5.2 Average Switching Frequency
4.5.3 Parameter Design with Invariant Probability Distribution
Chapter 5 EMI and EMC of Switching Power Converters
5.2 EMI Origin of Electric Circuits
5.3 Characteristics of Switching Processes of Power Semiconductors
5.4 Overview of EMI and EMC
5.4.1 Basic Principles of EMI
5.5 EMI of Power Electronic Converters
5.5.1 Parasitic Parameters of Flyback Converters
5.5.2 Primary Rectifying Circuit
Chapter 6 Discrete Subsystem Chaotic Point Process of DC–DC Converters and EMI Suppression
6.2 Description of Chaotic Point Process of DC–DC Converters
6.2.1 Model of Chaotic Point Process of DC–DC Converters
6.2.2 Statistical Characteristics of the Chaotic Point Process in Converter
6.3 Spectral Quantification Analysis of the PWM Pulse Process
6.3.1 Spectral Quantification Analysis of the Periodic PWM Pulse
6.3.2 Spectral Quantification Analysis of PWM Chaotic SPSP
Chapter 7 Basis of Spectral Analysis
7.3 Fourier Analysis and Fourier Transform
7.4.1 Energy Signals and Power Signals
7.4.2 Energy Spectral Density
7.4.3 Power Spectral Density
7.5 Autocorrelation Function and Power Spectral Density
7.6 Classic Power Spectrum Estimation
7.6.4 Blackman and Tukey Method
7.6.5 Summary of Classic PSD Estimators
7.7 Modern Spectral Density Estimation
Chapter 8 Dynamic Chaos Spectrum of Chaotic Switching Converters I: Wavelet Method
8.1.1 Lack of Time and Frequency Positioning
8.1.2 Limitation for the Time-Variant Signals
8.1.3 Limitation for Resolution
8.2 Basic Principle of Wavelet Analysis
8.3 Multiresolution Analysis and Orthogonal Wavelets Basis
8.4 Wavelet Transform and Filter Bank
8.5 Wavelet Analysis of Chaotic PWM
8.5.1 Basic Principle of Chaotic PWM Control
8.5.3 Wavelet Reconstruction of Chaotic PWM
8.5.4 Time-Frequency Analysis of the Chaotic PWM
8.5.5 Information on the Time-Frequency Image of P(t)
Chapter 9 Dynamic Chaos Spectrum of Chaotic Switching Converters II: Prony Method
9.2.1 Basic Principle of Prony Method
9.2.2 Classical Computing Process of Prony Analysis
9.3 Estimating PSD Using the Prony Method
9.4 Chaotic Spectral Estimation of DC–DC Converters Based on the Prony Method
Chapter 10 Chaotic PWM Suppressing EMI of Power Electronic Converters
10.2 The Principle of Chaotic PWM Suppressing EMI
10.2.1 Basic Theory of Frequency Modulation
10.2.2 The Frequency Characteristics of Fixed Frequency PWM Wave
10.2.3 Frequency Characteristics of Spreading Frequency PWM Wave
10.2.4 The Principle of Chaotic PWM Suppressing EMI
10.3 The Key Techniques of Chaotic PWM for Power Electronic Converters
10.3.1 Parameter Selection of Chaotic PWM
10.3.2 Choice of a Chaotic PWM Modulation Signal
10.4 Chaotic PWM Suppressing EMI Experiments
10.4.1 Modulation Circuit of Piecewise-Linear Capacitor Chaos Circuit
10.4.2 The DC–DC Converter Suppressing EMI Based on UC3842
10.4.3 EMI Suppression of Full Bridge Inversion Based on SG3525
10.5 EMI Suppression of Commercial Switching Power Supply
10.6 Characteristics of Chaotic Modulated by Different Chaotic Maps
Chaos Analysis and Chaotic EMI Suppression of DC-DC Converters
( Wiley - IEEE )
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