6128 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 61, NO. 11, NOVEMBER 2014
Suppressing EMI in Power Converters via Chaotic
SPWM Control Based on Spectrum
Analysis Approach
Hong Li, Member, IEEE, Yongdi Liu, Jinhu Lü, Fellow, IEEE,
Trillion Zheng, Senior Member, IEEE, and Xinghuo Yu, Fellow, IEEE
Abstract—This paper aims at developing a spectrum analysis
approach for suppressing the electromagnetic interference (EMI)
in power converters via chaotic sinusoidal pulse width modulation
(CSPWM) control signals based on double Fourier series. In de-
tail, we prove that the total harmonics of power converters under
CSPWM control are the same with those of power converters
under traditional SPWM control. Then, we introduce a novel
spectrum analysis approach based on sawtooth carrier and double
Fourier series. Moreover, a photovoltaic (PV) inverter is used to
validate the proposed spectrum analysis approach based on the
calculation of the output voltage spectrum for CSPWM control
signals. In particular, this proposed method can also be used for
the spectrum analysis of multiperiodic signals. Indeed, this devel-
oped spectrum analysis approach provides a rigorous theoretical
foundation for the CSPWM control in EMI suppression.
Index Terms—Double Fourier series, electromagnetic interfer-
ence (EMI), sinusoidal pulsewidth modulation (SPWM), spectrum
calculation.
I. I NTRODUCTION
W
ITH THE wide applications of power converters and the
emergence of high-frequency full-controlled switching
devices, sinusoidal pulse width modulation (SPWM) has be-
come the main switching control method for inverters [1]–[7].
Compared with the phase-shifting technology, SPWM has some
specific advantages, including the realization of frequency
modulation and voltage regulation at the same time, rapid
dynamic response, reducing or eliminating the harmonics in
low-frequency band, and so on [8]. However, the harmonics in
high-frequency band have received an increasing attention.
Manuscript received October 29, 2013; revised December 28, 2013; accepted
January 10, 2014. Date of publication February 26, 2014; date of current
version June 6, 2014. This work was supported by the National Science and
Technology Major Project of China under Grant 2014ZX10004-001-014; by
the 973 Project under Grant 2014CB845302; by the National Natural Science
Foundation of China under Grant 51007004, Grant 61025017, Grant 50937001,
and Grant 11072254; by the Fundamental Research Funds for the Central Uni-
versities under Grant 2012JBM096; by the Beijing Natural Science Foundation
under Grant 3142015; by the Beijing Higher Education Young Elite Teacher
Project under Grant YETP0569; and by the Specialized Research Foundation
of Doctoral Subjects of Education Ministry under Grant 20114420110003.
H. Li, Y. Liu, and T. Zheng are with the School of Electrical Engineering,
Beijing Jiaotong University, Beijing 100044, China (e-mail: hli@bjtu.edu.cn).
J. Lü is with LSC, ISS, Academy of Mathematics and Systems Science,
Chinese Academy of Sciences, Beijing 100190, China (e-mail: jhlu@iss.ac.cn).
X. Yu is with the School of Electrical and Computer Engineering, Royal
Melbourne Institute of Technology University, Melbourne, VIC 3001, Australia
(e-mail: x.yu@rmit.edu.au).
Color versions of one or more of the figures in this paper are available online
at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TIE.2014.2308131
They are caused by the rapid turn-on and turn-off of switching
devices under SPWM control. Moreover, the harmonics could
result in the electromagnetic compatibility (EMC) of the con-
verters out of limits as well as serious electromagnetic pollution
[9]–[12].
To suppress the electromagnetic interference (EMI) and
improve the EMC of power converters, the random PWM
technique was proposed [13]–[15]. According to the imple-
mentation method, the random PWM can be divided into three
kinds: random switching frequency, random pulse position, and
random switching [16], where each kind of random PWM is
based on the generation of random signals. Since it is very dif-
ficult to obtain the true random signals in practice, the pseudo-
random signals are usually used to replace the aforementioned
random PWMs [17], [18]. As we know now, chaotic signals
are one kind of typical pseudorandom signals, which are easily
obtained by the chaotic maps. Therefore, the chaotic PWM
and chaotic SPWM (CSPWM) have attracted an increasing
attention over the last decade [19]–[21].
Most of the aforementioned CSPWM approaches only focus
on the operating principle analysis or the EMI suppression
effectiveness test of power converters by using numerical simu-
lations and experimental observations [22]–[24]. However, the
spectrum quantitative analysis of CSPWM on EMI suppression
is woefully inadequate, since the traditional spectrum calcu-
lation methods are not able to deal with the chaotic signals
effectively. Recently, many researchers have already realized
the fundamental importance of theoretical analysis and begin
to track these works [25]–[27]. For instance, a qualitative
spectral analysis method was introduced to analyze the random
frequency modulation and chaotic frequency modulation in
[25], which can be used to predict the spectra peaks under
different modulation indexes. In [26], Yang et al. analyzed
the chaotic spectrum characteristics of time-frequency energy
distribution based on wavelet transform and also explained the
inherent mechanism of EMI suppression from the point of en-
ergy spectrum. Moreover, Yang et al. applied statistical theory
to further investigate the spectrum of chaotic PWM signals in
[27]. However, the aforementioned approaches lack a rigorous
theoretical analysis, where only the qualitative analysis results
can be obtained. Based on the double Fourier transform of
CSPWM control signals, this paper aims to introduce a new
spectrum calculation method with rigorous theoretical analysis.
It establishes a strict theoretical basis for the CSPWM control
in EMI suppression and practical applications [28]–[34].
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