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\documentclass[10pt]{article}
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\usepackage[english]{babel}
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% \usepackage[a4paper,top=2cm,bottom=2cm,left=2cm,right=2cm,marginparwidth=1.75cm]{geometry}
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\usepackage[a4paper, total={7in, 10in}]{geometry}
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\usepackage{multicol}
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\usepackage{lipsum}
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\usepackage{caption}
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\usepackage{graphicx}
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\usepackage{enumitem}
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\newenvironment{Figure}
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{\par\medskip\noindent\minipage{\linewidth}}
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{\endminipage\par\medskip}
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\graphicspath{{images/}}
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\title{B00st converter}
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\author{
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van Iterson, Arne\\
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Student Number: 1800000
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\and
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Selier, Tom\\
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Student Number: 1808444
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}
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2024-01-23 14:48:33 +01:00
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\begin{document}
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\maketitle
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\begin{multicols}{2}
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\section{Introduction}
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\lipsum[1-2]
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\section{Circuit Description}
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% Filler image, don't get attached
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\begin{Figure}
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\centering
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\includegraphics[scale=0.38]{SCHEMATIC_FULL.png}
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\captionof{figure}{WIP}
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\label{fig:schematic_full}
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\end{Figure}
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\lipsum[3-4]
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\section{Methodology}
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To characterize the system, several tests have been performed. The
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characteristics of interest are the following:
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\begin{enumerate}[nosep]
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\item Efficiency
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\item Noise
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\item Ripple characteristics
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\item Transients
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\end{enumerate}
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In this section a test or measurement will be described for each of the above
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characteristics.
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Each of the characteristics have been tested at two different output voltages
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and various load currents. The different voltages are $7V$ and $3.3V$. The
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chosen load currents are $10$, $20$, $30$, $40$ and $50 mA$. These values
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were chosen to give characterize the circuit over a broad range of conditions.
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\subsection{Efficiency}
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\begin{Figure}
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\centering
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\includegraphics[scale=0.34]{SCHEMATIC_EFFICIENCY.png}
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\captionof{figure}{WIP}
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\label{fig:schematic_efficiency}
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\end{Figure}
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To measure the efficiency of the circuit, four measurements were taken.
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A current and a voltage measurement were taken at the supply and load
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respectively. The measurements were taken as shown in figure
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\ref{fig:schematic_efficiency}. The energy used by the supply and the load
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can be calculated using the equation \ref{eq:power}. Then, using equation
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\ref{eq:efficiency}, efficiency can be calculated.
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\begin{equation}
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\label{eq:power}
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P [W] = U[V] \cdot I[A]
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\end{equation}
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\begin{equation}
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\label{eq:efficiency}
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\eta[\%] = \frac{P_{load}[W]}{P_{supply}[W]} \cdot 100\%
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\end{equation}
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\subsection{Noise}
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To measure the noice of the circuit an oscilloscope probe was placed on the
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variable resistor in figure \ref{fig:schematic_full}. Over the period of 1
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millisecond, 20,000 points were measured.
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Noise has several metrics in which it can be quantized. Two metrics were
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calculated, the standard devation (SD) and the peak to peak noise.
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\subsubsection{Peak to peak}\label{section:peak_to_peak}
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Peak to peak is the simplest way to look at noise. The signal has a stationary
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mean over the period of 1 millisecond. Thus the highest measured value can be
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subtracted from the lowest measured value.
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\subsubsection{Standard Deviation}
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The second metric used to measure noise was the standard deviation.
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Unlike, peak to peak it givesa better impression of the noise over a longer
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signal. SD can be calculated using equation \ref{eq:sd}.
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\begin{equation}
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\label{eq:sd}
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\sigma = \sqrt{\frac{1}{N}\sum^{N-1}_{i=0}(x[i] - \mu)^2}
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\end{equation}
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Where $x[i]$ is each voltage measurement, $\mu$ is the mean of the signal and
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$N$ is the total amount of samples.
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\subsection{Ripple characteristics}
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\begin{Figure}
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\centering
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\includegraphics[scale=0.5]{RIPPLE.png}
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\captionof{figure}{WIP}
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\label{fig:ripple}
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\end{Figure}
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A significant source of the noise was caused by a specific ripple, shown in
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figure \ref{fig:ripple}.
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This ripple coincided with the MOSFETs opening or closing.
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To further characterize this behaviour a close up measurement was taken.
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The oscilloscope was set to AC-coupling and the settigns were adjusted
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for the ripple to be full screen. Then, two additional characteristics can
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be calculated. The ripple's peak to peak voltage and the ripple's (most prevalent)
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frequency. The peak to peak value can be calculated using the method described in
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section \ref{section:peak_to_peak}.
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To measure the frequency of the signal using an FFT, it had to be pre-processed
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first using a Hamming window this eliminates sharp edges at the edge of the
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measurement, causing unwanted frequencies to appear in the frequency domain.
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\begin{equation}
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\label{eq:hamming}
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% 0.54 - 0.46 * cos(2*np.pi*(n/N))
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w(i) = 0.54 - 0.46 \cdot cos \left(2 \pi \frac{i}{N} \right)
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\end{equation}
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Where $i$ is the current sample and $N$ is the total amount of samples. Each
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sample in the signal can be multiplied by the corresponding value in the window,
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preparing the signal for the FFT.
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\subsection{Transients}
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The last measurements were hocus pocus
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\section{Results}
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\lipsum[1-2]
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\section{Conclusion}
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\lipsum[3-4]
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\end{multicols}
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\end{document}
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