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IEEE TRANSACTIONS ON POWER ELECTRONICS, VOL. 21, NO. 3, MAY 2006 693
Active Attenuation of Electromagnetic Noise in anInverter-Fed Automotive Electric Drive System
Andrzej M. Trzynadlowski, Fellow, IEEE
AbstractElectromagnetic noise, typical for systems withswitching power converters, is especially troublesome in automo-tive electric drive systems because of the multitude of sensitiveelectronic equipment onboard of modern cars. To satisfy therelevant engineering norms, passive radio-frequency (RF) filtersmust be installed in the power electronic part of a drive. The RFfilters add to the cost and size of the drive, which car designersstrive to minimize to increase the passenger space. In this paper,active attenuation of the electromagnetic noise by means of theso-called random-delay pulse width modulation is described inapplication to an inverter-fed automotive ac drive. Based oncomputer simulations and experimental investigation, this simpleand inexpensive method is shown to be highly effective.
Index TermsAutomotive drives, electromagnetic noise, filters,pulse width modulation (PWM).
I. INTRODUCTION
ELECTROMAGNETIC noise is generated in electric drive
systems as a result of switching operation of the power
electronic converter feeding the motor. Considering the level of
saturation of modern cars with various control and communi-
cation devices, the noise poses a serious threat to undisturbed
operation of the car. In an electric or hybrid automobile, the cur-
rent noise in cables connecting the battery and the converter isespecially troublesome, because the cables act as antennas and
radiate the resultant electromagnetic noise throughout the small
and enclosed space of the vehicle. Relevant engineering stan-
dards limit the allowable maximum levels of the conducted and
radiated noise within specified frequency ranges. A given stan-
dard also specifies the type of the noise considered, that is, de-
pending on the type of a detector employed, the average, peak,
or quasipeak values of the noise are subjected to the limitations.
Radio-frequency (RF) filters are most commonly used for re-
duction of the electromagnetic interference (EMI). The filters,
which are simple inductive-capacitive networks, constitute pas-
sive means of noise attenuation. In the context of continuous ef-forts to cut down the volume and cost of automotive drives, elim-
ination or size reduction of the filters is a worthy engineering
objective.
In this paper, an active approach to electromagnetic noise mit-
igation is described. It is based on the addition of a random
factor to the switching pattern of the power electronic converter.
In this way, most of the harmonic power in the frequency spectra
Manuscript received February 21, 2005; revised October 26, 2005. Recom-mended by Associate Editor J. Shen.
The author is with the Electrical Engineering Department, University ofNevada, Reno, NV 89557-0153 USA (e-mail: [email protected]).
Digital Object Identifier 10.1109/TPEL.2006.872368
of voltage and current is transferred to the continuous power
density. As a result, the spectra are flattened, significantly re-
ducing the required degree of attenuation of the noise by the RF
filters, which can thus be greatly reduced too. Computer simu-
lations and the results of an experimental investigation illustrate
advantages of the proposed method.
II. BACKGROUND
There exist many national and international engineering
standards on electromagnetic compatibility (EMC). The Inter-
national Electrotechnical Commission (IEC) standards, most ofwhich became European Norms (EN), are the most influential.
U.S. organizations involved in EMC product standards include
the Federal Communication Commission (FCC), The IEEE,
Inc., and the American National Standards Institute (ANSI)
[1]. EMC testing of novel electric and electronic products is
required in order to ensure the immunity of individual devices,
as well as the safety of other equipment within the reach of
electromagnetic effects of the tested product. Electromagnetic
disturbances causing the EMI can be classified as noise, im-
pulses, and transients. They travel mostly by conduction on
wiring and by radiation in space, and can get into closely spaced
circuits via inductive and capacitive coupling. In the frequency
range of 0.15 to 30 MHz it is the conducted EMI that is ofmain concern and, in that range, most EMC standards address
conducted disturbances only[2].
Noise components in the range of 0.15 to 30 MHz, and
eventually down to 10 kHz, are measured by EMI receivers.
The peak, average, effective (rms), or quasipeak measurements
of the electromagnetic noise are taken and compared with
relevant standards[3]. The quasipeak detection developed by
CISPR (IECs International Committee for Radio Interference)
is most common in practice, yielding the best correlation be-
tween the EMI receiver readings and the broadcast disturbances
heard by human ear[2]. Still, many engineering norms, among
them those of automobile manufacturers, define limits on themaximum peak and average values of the noise. For example,
in the GM Worldwide Engineering Standard GMW3097, the
limits for the radiated EMI for artificial networks (AN) within
the 0.531.71 MHz frequency range are 42 dB V, peak, for
nonspark noise sources (and 50 dB V, quasipeak, for spark
sources)[4].
In the same standard, the automobile equipment tested for
immunity to the radiated and conducted emissions is classified
into the following categories:
A components/modules containing active electronic
devices, such as op-amp circuits, switching power
supplies, microprocessors, and displays;
0885-8993/$20.00 2006 IEEE
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694 IEEE TRANSACTIONS ON POWER ELECTRONICS, VOL. 21, NO. 3, MAY 2006
Fig. 1. EMIfilter for an automotive ac drive.
AS electronic components/modules operated from a
regulated power source in another module, typically
sensors;
AM electronic components/modules containing magnetically
sensitive elements;
AX electronic modules containing inductive devices, e.g.,
motors and solenoids;
BM brush-commutated electric motors;
EM electronically controlled or commutated electric motors.
Categories A, AS, and AM must meet the nonspark limits,
Categories AX and EM must meet both the nonspark and
spark limits, and Category BM must meet the sparklimits
[4].
So far, RFfilters are the only means employed for EMI miti-
gation in automobile electric drives. An examplefilter arrange-
ment, which screens the supply cables from noise to preventthem from radiating the EMI throughout the vehicle, is shown in
Fig. 1. The filter contributes to the cost and bulk of the drive. It is
worth mentioning that active EMIfilters for inverter-fed indus-
trial ac drives have recently gained attention of researchers [5].
Their application in automobile drives remains yet to be consid-
ered.
The magnitude of peaks in frequency spectra of the electro-
magnetic noise is the major factor affecting the size of RF filters.
As an example, consider a simple low-pass filter shown in
Fig. 2. In the attenuation frequency range (well above the reso-
nance frequency), its voltage attenuation, , is given, with
good approximation, by
(1)
where and denotefilters inductance and capacitance, re-
spectively, and is the frequency. Thus, the bigger the mag-
nitude of the spectral peaks, the larger inductor and capacitor
are required. Consequently, if the peaks were reduced, thefilter
components could be reduced too, both parametrically (lower
inductance and capacitance) and physically (lower volume and
weight).
The dependence of voltage attenuation on the square of fre-
quency implies that the high-frequency electromagnetic noise,resulting mostly from the high rates accompanying state
Fig. 2. Simple low-pass filter.
transitions of inverter switches, can be mitigated with relatively
low inductances and capacitances of the filters. However, the
current ripple associated with the low-frequency train of voltage
pulses of the inverter causes EMI that is more difficult tofight.
In the frequency spectrum, the current ripple appears in the form
of harmonic clusters centered about multiples of the switching
frequency.
Flattening a frequency spectrum, without reducing its total
power content, is tantamount to transferring the discrete har-
monic power (watts) to the continuous power spectral density(watts/hertz). This can be accomplished by random pulse width
modulation (RPWM) of gate pulses of the inverter switches [6].
Many RPWM methods have proposed in the literature, e.g.,
[7][10]. Those with a randomized switching frequency or,
more precisely, with a randomized length of switching periods,
turned out to be most effective[11].
Almost all the existing RPWM techniques with randomized
switching periods are characterized by a random sampling rate
of the digital modulator, because individual sampling periods
are synchronized with corresponding switching periods. This,
in most practical cases, is highly inconvenient. In a complex
digital system, the sampling frequency should be a constant,representing the best tradeoff between various bandwidth re-
quirements of multiple tasks of the system. The modulation is
only one of those tasks. The sampling and switching frequencies
can be made constant by employing a random sequence of in-
verter states[12].However, this approach detrimentally affects
the quality of both the switching patterns and frequency spectra
[13]. As a result, RPWM, despite its undeniable advantages, still
has not gained much popularity in practice. The novel random
modulation method described in the subsequent sections of this
paper combines the features of spectral continuity and of quality
of a space-vector PWM. In addition, the method, further called
a random-delay PWM (RDPWM) technique, is characterized
by exceptional algorithmic simplicity and minimum computa-tional overhead.
It is worth mentioning that a similar approach to EMI reduc-
tion has been proposed with respect to high-speed digital sys-
tems, such as computers. A randomly varied clock rate has been
shown to be an effective means of mitigation of EMI[14][16].
III. RANDOM-DELAYPWM TECHNIQUE
Although the classic space-vector PWM method is very well
known, its basics are invoked here because of certain twists in
realization of that method, described in this paper. The space-
vector technique with afixed switching frequency is illustrated
inFigs. 3and4. As shown inFig. 3,the reference space vector,, of output voltage of the inverter is synthesized
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TRZYNADLOWSKI: ACTIVE ATTENUATION OF ELECTROMAGNETIC NOISE 695
Fig. 3. Illustration of the space-vector PWM method.
Fig. 4. Single switching cycle in the space-vector PWM method.
TABLE IINVERTER STATES ANDTHEIRFRACTIONALTIMES
by time averaging of stationary space vectors , , and
of the inverter. Non-zero vectors and , framing the ref-
erence vector , are generated when the inverter is in State
and State , respectively. A state is defined here as , where
, , and are switching variables associated with phases A,
B, and C of the inverter. The active states and , resulting in
nonzero voltages of the inverter, are 1, 2, , 6. The zero vector,, can be produced by either State 0 or State 7.
Fig. 5. Sampling and switching cycles: (a) DPWM, (b) RPWM, and (c)
VDPWM.
Fig. 6. Frequency spectra of the input current noise at the low-speed, high-torque operating point and frequency range of 0.0130 MHz: (a) DPWM, (b)RPWM, and (c) RDPWM.
Fig. 4illustrates division of a switching cycle into five timeintervals, whose lengths are 2, 2, , 2, and 2.
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696 IEEE TRANSACTIONS ON POWER ELECTRONICS, VOL. 21, NO. 3, MAY 2006
Fig. 7. Frequency spectra of the input current noise at the low-speed, high-
torque operating point and frequency range of 10150 kHz: (a) DPWM, (b)RPWM, and (c) RDPWM.
This is the so-called minimum-loss switching strategy, which
within switching cycles produce as few as 3 1 pulses
of each switching variable[17]. Times and are expressed
by simple formulas involving cosine functions of the angular
position, , of the reference vector with respect to vector
. Specifically
(2)
(3)
where denotes the modulation index, defined here as the ratio
of magnitude of the reference vector to the highest available
value of that magnitude. Time is given by
(4)
Thus, subdivision of a switching cycle involves the following
computations: (a) determination of the sextant of the vector
plane in which the reference voltage vector is located, (b)
calculation of angle based on the known components of
vector , and (c) calculation of times , , and using
trigonometric equations(2) and (3)and an arithmetic equation(4).
Fig. 8. Frequency spectra of the input current noise at the medium-speed,medium-torque operating point and frequency range of 0.0130 MHz: (a)DPWM, (b) RPWM, and (c) RDPWM.
A fullyarithmeticapproach to the space-vector PWM, em-
ployed in simulations and experiments described in this paper,
lowers the computational overhead. It is assumed that the refer-
ence voltage vector is expressed in the per-unit format using
the maximum available vector as the base. In thefirst step, three
auxiliary variables, , , and , are calculated as
(5)
(6)
(7)
Next, based on the signs of , , and ,Table Iis used for de-
termination of times , , and .
It can be seen that simple arithmetic formulas are employed
only. The table-driven algorithm lends itself to simple imple-
mentation in a digital modulator. For minimization of switching
activity, only State 7 is used as the zero state.
As already mentioned, for active attenuation of the electro-
magnetic noise, the switching period, , must be randomly
varied from one switching cycle to another. That can be accom-
plished, while maintaining a constant sampling period, ,
by random variation of the delay, , between the beginning ofa sampling cycle and that of the corresponding switching cycle.
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TRZYNADLOWSKI: ACTIVE ATTENUATION OF ELECTROMAGNETIC NOISE 697
Fig. 9. Frequency spectra of the input current noise at the medium-speed,medium-torque operating point and frequency range of 10150 kHz: (a)
DPWM, (b) RPWM, and (c) RDPWM.
This is illustrated inFig. 5,which, for comparison, also shows
the relation between sampling and switching cycles for the de-
terministic PWM (DPWM) and the classic RPWM with simul-
taneous variations of the sampling and switching periods.
In the classic RPWM method, consecutive switching (and
sampling) periods are randomly drawn from a uniform-proba-
bility pool of values ranging from to , where
denotes the desired average switching period and the co-
efficient determines the shortest period as a fraction of the
average period. In the novel RD-PWM technique, the randomdelay is calculated as , where is a random number
from the 0 to 1 range. When in two consecutive switching cy-
cles, the and , is close to 1 and is close
to 0, the second, , switching cycle may be too short,
that is, its length, , may be lower than the minimum al-
lowable length, . Therefore, in case of such occurrence,
, is set to or another value of is drawn. As a
result, lengths of switching cycles vary from to .
Comparing RPWM with RD-PWM by assuming ,
and it can be seen that the difference be-
tween the longest switching period and the shortest one equals
for the RPWM method and for the
RD-PWM technique. Thus, RD-PWM offers a larger variety ofswitching periods than does RPWM.
Fig. 10. Frequency spectra of the input current noise at the maximum-speed,maximum-power operating point and frequency range of 0.0130 MHz: (a)DPWM, (b) RPWM, and (c) RD-PWM.
IV. COMPUTERSIMULATIONS
Computer simulations of an electric ac drive for an electric
car developed by a major automobile manufacturer were per-
formed using the SABER software package. Comparative eval-
uation of the impact of PWM technique employed in control of
the drives inverter on various characteristics of the drive was the
object of the simulations. The characteristics in question were:
a) frequency spectra of the current noise in supply cables, b) ef-
ficiency of the drive, c) torque ripple, and d) controllability of
the drive, in particular, response to torque andflux commands.Example frequency spectra of the input current noise in the
ranges of 10 kHz to 30 MHz and 10 kHz to 150 kHz are shown
in Figs. 611, each figure showing the spectra when the DPWM,
RPWM, and RD-PWM are used. The 10150 kHz spectra were
computed with the same number of samples as the 10 kHz to
30 MHz spectra, thus the former spectra can be considered more
accurate. Three operating points of the drive are represented: (a)
low speed and high torque (Figs. 6and 7), (b) medium speed
and medium torque (Figs. 8 and 9), and (c) maximum speed
and maximum power (Figs. 10and11). The average switching
period, , equal to the sampling period, , was 83.3 s,
which represents the sampling frequency of 12 kHz. The min-
imum switching period, was set to 40 s (a reciprocalof 25 kHz), so that the switching periods varied from 40 s to
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Fig. 11. Frequency spectra of the input current noise at the maximum-speed,maximum-power operating point and frequency range of 10150 kHz: (a)DPWM, (b) RPWM, and (c) RDPWM.
166.6 s, that is, with an approximately one to four shortest-to-
longest ratio.
A significant difference of 1020 dB V between the spectra
with deterministic and random PWM techniques can be ob-
served for all spectra. As seen in Figs. 6,8, and10, the choice
of modulation strategy ceases to affect the frequency spectra
above some 3 MHz. However, as indicated by (1), it is the
low-frequency region in which the current harmonics are mostdifficult to attenuate. Also, in the 0.531.71-MHz frequency
range specified in the GMW3097 standard (seeSection II), the
random modulation yields distinctly flatter spectra than does
the DPWM.
Additional simulations, although of limited scope due to ex-
cessive computation times, have been performed using a high-
frequency model of the motor described in[18]. The model in-
troduces distributed stray capacitances. Apart from minor am-
plitude differences in the high frequency range, the obtained fre-
quency spectra were very similar to those for the low-frequency
model of the motor.
Efficiency of the drive is unaffected by the type of modula-
tion, while the torque ripple increases by an order of 30% whenDPWM is replaced with RPWM or RD-PWM. However, the
Fig. 12. Rapid changes of the reference torque-producing current: DPWM.
fundamental frequency of the ripple, which well exceeds the av-erage switching frequency, is so high that its effects on speed of
the car would be imperceptible.
When the average orfixed sampling frequency is sufficiently
high to provide the required control bandwidth, there is no
significant impact of the modulation strategy on the quality of
torque andflux control. This is illustrated inFigs. 1214,which
compare the reference and actual waveforms of the torque-pro-
ducing current, and , and those of theflux-producing
current, and , following an up-and-down step com-
mand signal, , while remains unchanged. Although
the waveforms of and with RPWM (see Fig. 13) and
RD-PWM (seeFig. 14) are less regular than those with DPWM(see Fig. 12), both the overshoot and settling time are similar for
all the three modulation methods. However, it must be pointed
out that when the average switching frequency decreases, the
quality of current control deteriorates faster when random
modulation, instead of DPWM, is employed. That is mostly the
result of nonuniform current sampling, as opposed to the at
peak or at valley patterns typical for DPWM. In effect, the
measurement errors of the locally-averaged current are more
pronounced.
V. EXPERIMENTAL INVESTIGATION
For confirmation of theoretical expectations and simulationresults, a 40-hp laboratory drive system with an induction
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TRZYNADLOWSKI: ACTIVE ATTENUATION OF ELECTROMAGNETIC NOISE 699
Fig. 13. Rapid changes of the reference torque-producing current: RPWM.
motor driving a loaded dc generator was set up and investi-
gated. The motor was fed from a commercial inverter from
Danfoss, with the original control system replaced with a
digital modulator based on the TMS320F243 DSP controller
from Texas Instruments. The modulator generated switching
signals in accordance with the DPWM, RPWM, and RDPWM
algorithms. The drive was operated in the constant volts/hertz
mode, with the average (for RPWM and RD-PWM) or fixed (for
DPWM) switching period of 0.5 ms, representing a switching
frequency of 2 kHz. In the steady state, the drive run with
the fundamental frequency of 9 Hz (the value of fundamentalfrequency does not affect the electromagnetic noise). The goal
of the investigation was to assess qualitative features of the
PWM techniques compared, rather than to perform precise
measurements of the noise. Therefore, the noise was sensed
directly in the wires connecting the inverter to the power line,
without a line impedance stabilization network (LISN).
Frequency spectra of the input current noise with the drive op-
erating on full load are shown inFigs. 1517. Due to equipment
limitations on the number of collected samples, the frequency
range is narrower than that in computer simulations, specifi-
cally, 0 to 20 kHz. Also, in contrast to the simulated system,
the dc supply voltage in the experimental setup was obtained
not from a battery but from a diode rectifier, which contributedcurrent harmonics at the lower end of frequency range. Still,
Fig. 14. Rapid changes of the reference torque-producing current: RDPWM.
Fig. 15. Experimental frequency spectrum of the input current noise: DPWM.
the mitigating effect of random PWM techniques on the elec-
tromagnetic noise in the low end of the spectrum, which is most
difficult forfiltration, is clearly observable.
VI. CONCLUSION
Electromagnetic noise, a highly undesirable side effect ofswitching operation of power electronic converters in adjustable
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Fig. 16. Experimental frequency spectrum of the input current noise: RPWM.
Fig. 17. Experimental frequency spectrum of the input current noise:RDPWM.
speed ac drives, especially those used in automobiles, can be at-
tenuated by random PWM employed in the power inverter. Flat-
tering the frequency spectrum of noise allows for size reduction
of EMI filters, contributing to compactness and cost reduction of
the drive. Conveniently, the novel random-delay PWM methodis characterized by a constant sampling frequency of the dig-
ital modulator. Implementation of the RDPWM technique is
a simplesoftwarefix,requiring no modifications of the drive
system.
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Andrzej M. Trzynadlowski (M83SM86F99)received the M.S. degree in electrical engineering,the M.S. degree in electronics, and the Ph.D. degreein electrical engineering from the Technical Univer-sity of Wroclaw (TUW), Wroclaw, Poland, in 1964,1969, and 1974, respectively.
From 1966 to 1979, he was a faculty member
with TUW. Later, he worked at the University ofSalahuddin, Iraq, the University of Texas, Arlington,and the University of Wyoming, Laramie. Since
1987, he has been with the University of Nevada,Reno, where he is a Professor of electrical engineering. In 1997, he spent sevenmonths at Aalborg University, Aalborg, Denmark, as the Danfoss VisitingProfessor. In 1998, he was a Summer Faculty Research Fellow at the NavalSurface Warfare Center, Annapolis, MD. He has authored or co-authored over150 publications on power electronics and electric drive systems and holds12 patents. He is the author of The Field Orientation Principle in Controlof Induction Motors (Norwell, MA: Kluwer, 1994), Introduction to ModernPower Electronics (New York: Wiley, 1998), andControl of Induction Motors
(New York: Academic, 2001). He wrote chapters for Modern Electrical Drives(Norwell, MA: Kluwer, 2000) and Control in Power Electronics (New York:
Academic, 2002).Dr. Trzynadlowski received the 1992 IAS Myron Zucker Grant and has
been listed in Whos Who in the World, Whos Who in America, and WhosWho in Science and Engineering. He is an Associate Editor of the IEEETRANSACTIONS ON POWER ELECTRONICS and the IEEE TRANSACTIONS ON
INDUSTRIAL ELECTRONICS, and a member of the Industrial Drivesand IndustrialPower Converters Committees, IEEE Industry Applications Society (IAS).