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EMC Issues: Prospective Review on the Switch Control Strategies for
Converters
Conference Paper · November 2019
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Hermes LOSCHI1, Robert SMOLEŃSKI1, Piotr LEŻYŃSKI1, Waseem El SAYED1, Choon Long LOK1
Uniwersytet Zielonogórski, Instytut Inżynierii Elektrycznej (1)
EMC Issues: Prospective Review on the Switch Control
Strategies for Converters
Abstract. Converters switch control strategies to provide the possibility to disperse the spectrum of electromagnetic interferences. Also, it is possible to arrange the spectrum and reduce disturbances in specific frequency ranges. The article presents a theoretical analysis and computer simulations of selected switch control strategies in the context of electromagnetic compatibility.
Streszczenie. Strategie sterowania przekształtników umożliwiają rozpraszanie widma zaburzeń elektromagnetycznych. Ponadto, możliwe jest kształtowanie widma i ograniczanie zaburzeń w określonych zakresach częstotliwości. Artykuł prezentuje analizę teoretyczną i wyniki symulacji komputerowych wybranych strategii sterowania przekształtników w kontekście kompatybilności elektromagnetycznej. (Przegląd perspektywiczny
strategii sterowania przekształtników: Zagadnienia EMC).
Keywords: Computer Simulations; Spectrum Sharing; Switch Control, Electromagnetic Compatibility Słowa kluczowe: Symulacje komputerowe; Rozmywanie widma; Kompatybilność elektromagnetyczna EMC.
Introduction
Smart cities environments could be considered as limited space environments, such as electric vehicles, renewable energy systems, industrial uses, and even in-house equipment. All the most cases, these limited environments must deal with the spectrum sharing between power and telecommunication devices. Power Electronic Interfaces (PEI) perform a defined function in power systems and smart cities environments, withstanding many features, as high efficiency, low cost, the capability to work at different levels of voltages and currents, as well as easy control switch modulation strategies [1-3].
Energy processes realized in power systems containing PEI differ significantly, both in terms of the power and frequency of the signals. Electromagnetic interference (EMI), as side-effect consequences of the intentional processes (electric power conversion and control process), can appear in a wide frequency range; from the lower harmonics and inter-harmonics of the mains frequency up to the higher harmonics [3]. With a crowded electromagnetic (EM) spectrum, PEI is considered as the main factor in the EM environment deterioration. Therefore, meeting the electromagnetic compatibility (EMC) standards (e.g., CISPR22) rises as a severe challenge to PEI designers [1]. An increase in switching frequencies can provide high EMI interference, brought about by the realization of the primary energy conversion processes, and shifted in the frequency range corresponding to conducted EMI range from 9𝑘𝐻𝑧 to 30𝑀𝐻𝑧 [3].
In the majority of the PEI applications, the high 𝑑𝑣/𝑑𝑡 and 𝑑𝑖/𝑑𝑡 values of power switches, connected with short rising and falling times, of transistor voltages excite parasitic couplings forcing the flow of high-level EMI currents. Also, the high-level EMI noise can be attributed to the overvoltage, and leakage current generates by fast contactless switches and stray components [3]. Moreover, by their inherent design characteristics, PEIs with their power transistors supplies generate EMI composed of signals of multiple frequencies, and the switch control strategies take a vital role to improve it thought the efficiency control.
According to discusses in [1-3], recognizing the need for EMC compliance, designers should provide converters not only to accomplish the necessary electrical functions but also to achieve the lowest harmonic spectrum or to facilitate the sharing. To meet the limits of conducted EMI range, PEI typically requires an EMI filter at its input. Therefore, considering that measurements of the common-mode (CM) and differential-mode (DM) noise coming from the EMI
source, and it interferes in the EMI filter size and project, the core proposal of this paper is a review on EMC issues with a focus on the switch modulation strategies, to more comprehension on the spectrum sharing and EMI noise reduction, that might be interesting for designers to reach the EMC assurance.
Section II presents a brief concept of switch modulation strategies that is the primary aspect to understand the EMI noise shape from PEI. Also, section II offers a discussion about the core differences between the switch modulation strategies reviewed in this prospective review paper. Section III highlights the computer simulation results and the core differences between the switch modulation strategies discussed, considering the EMC, EMI noise reduction, and spectrum sharing point of view. Finally, section IV offers prospective considerations and future trends.
Switch Modulation Strategies
High-efficiency controllers (Electronic circuits, responsible for controlling the converter by measured signals, according to shown in Fig. 1), on the most case, are obtained by the switching transistors, which can be attributed as the primary source of EMI emissions. Also is related to the control strategy of the switches to convert the available AC or DC voltage/current waveforms of the power source into the AC or DC waveforms required by the load. Considering the fundamental components of waveforms involved in energy conversion (DC or AC) and the switching frequency (tens of kilohertz or more), the profile choice of the most convenient waveform depends on the target and Power electronic converters requirements [4-11].
Fig. 1 shows the conventional control scheme with a switching function, 𝑠𝑓(𝑡), where reference values, waveforms
of the desired steady-state for controlled voltages or currents are combined with these reference values to determine 𝑠𝑓(𝑡).
Fig. 1. Power converter with closed-loop control via modulation of the switching function.
The standards and performance specifications of PEI must attendance a lot of constraints related to their environmental effects, such as conducted low-frequency
emissions and EMI. In this context, the allowable harmonic content of some of these waveforms is often constrained; based on this, the PEI it's composed in most of their volume and weight by an input or output filter. Other solutions can be an increase in the switching frequency, which in turn increases the switching power losses [3]. Thus, considering the low-cost landscape for PEI applications and EM environment, switch modulation approaches could be viewed as the primary aspect to understand the profile of the EMI noise shape and might be interesting for designers as well as smart cities environments, involved in EMC assurance.
Spread-spectrum based on PWM techniques achieve EMI noise reduction technique and emerge as a promising and very effective solution to comply with EMC standards [1], [2]. The two most popular methods in this context were reviewed in this prospective review paper; the deterministic PWM (programmed switching) and randomized PWM (RPWM). The core difference of these approaches is that the effect of the randomization introduces a continuous EMI noise.
On the other hand, the sigma-delta modulation (SDM) strategies are also used to attenuate the discrete EMI noise spectrum, and to create spectral nulls at specified frequencies. These nulls are created based on a feedback control circuit that measures, amplify, and digitizes the difference between the output voltage of the converter and the reference voltage, to generate the control signal for the power transistor driver. Thus, according to discussed in the introduction, the choice of better EMI noise shape, considering PEI requirements and EM environment, can be done, also taking into account the switch modulation strategies to improve the EMC compliance.
Deterministic Modulation
The most traditional method is PWM. Consider one DC-DC converter; basically, the controlled switch is designed to “cut” the DC waveform into a pulse waveform. These alternates between the values of specific voltage and 0 at the switching frequency, and this DC-DC converter is controlling the duty cycle (𝐷), i.e., the fraction of time that the switch is closed in each cycle, we can control the fraction of time that the pulse waveform takes the value [4-6]. Typically, the waveforms from PEI are periodic functions of time in the steady-state.
Fig. 2(a) shows the 𝐷 of 𝑠𝑓(𝑡) that determines the nominal
output of a DC-DC converter, while the fundamental component of 𝑠𝑓(𝑡) determine the output of a DC-AC
converter (Fig. 2(b)); similar statements can be made for AC-DC and AC-AC converters [5].
Fig. 2. Nominal switching function, 𝑠𝑓(𝑡), and sample state variable, 𝑖(𝑡), in two types of power converters: (a) DC-DC converter operating with duty ratio 𝐷 and (b) DC-AC converter.
Fig. 2(b) also shows that the nominal waveform in the case of a single-phase DC-AC converter is periodic with the fundamental corresponding to the slow AC waveform that is being synthesized. In the case of three or more phase systems, named “polyphase systems,” the industry standard
today is the so-called space vector modulation, in which switching commands for all three phases are generated in a coordinated fashion [12-15].
In standard PWM strategy with the programmed switching frequency, the harmonics usually occur at fixed and well-defined frequencies and are thus named “discrete harmonics.” On the other hand, the concept of frequency modulation techniques is based on the modulating the original constant clock frequency to spread the energy of every single harmonic into the well-defined frequencies, thus reducing the peak amplitude of EMI at harmonic frequencies, however, doesn't introduce a continuous EMI noise spectrum.
Fig. 3(a) shows the spectrum and Fig. 3(b) shows the spectrogram of EMI noise shape of voltage output for a standard PWM with the programmed switching frequency of 70kHz implemented in one Buck-Converter with 𝐷 = 0.50, using the Simscape library from MatLab, and in accordance with CISPR A standard.
Fig. 3. EMI Noise shape of output voltage programmed switching frequency of 70𝑘𝐻𝑧: a) Spectrum and b) Spectrogram.
According shown in Fig. 3(a), the switching frequency of 70kHz, create a significative impact by the EMI noise shape as well as the second sideband of the harmonic contents was at the frequency of 140kHz. Fig. 3(b) shows the high peaks amplitude of EMI noise at the switching frequency and their multiple harmonics.
In the mid-1990s, the firsts researchers on frequency modulation techniques to reduce EMI emissions were developed with a focus on communications and microprocessor systems [5-7]. The main concern with these latter approaches is that EMI is equally spread along the whole frequency spectrum, and these approaches do not provide any control over the bands where EMI energy is spread.
Those above features are crucial for applications in the context of telecommunications, telematics, and automation systems where EMI at specific selective frequencies must be avoided. Investigations of such techniques applied to EMI reduction of digital systems is a subject of significant concern, inclusive opening a new area of research, with modulation techniques to power electronics converters with randomized modulation [9-11], [16-28].
Random Modulation
The concept of randomness is to spread the harmonic power which exists at well-defined frequencies (discrete harmonics) over a wide range of frequencies so that no harmonic of significant magnitude exists. As a result, discrete harmonics are significantly reduced, and the harmonic power is spread over the spectrum as “noise” (continuous spectrum) [29].
The strategy of most randomized modulation is based on schemes in which successive randomizations of the switching pulse train (or of the periodic segments of this pulse train) are statistically independent and governed by invariant probabilistic rules. Therefore, the randomized modulation strategy must enable precise control of the time-domain performance of randomized switching, in addition to spectral shaping in the frequency domain. The elemental analysis problem in randomized modulation is to relate the spectral characteristics of, 𝑠𝑓(𝑡), and other associated waveforms in a
converter to the probabilistic structure that governs the dithering of an underlying deterministic nominal switching pattern.
In this context, the better approach to study the randomized switching setup is the power spectrum (Fourier transform of the original signal autocorrelation), and not the harmonic spectrum (i.e., the Fourier transform of the signal itself). Note that the Fourier transform of a random signal is itself a random function, i.e., it is a random variable at each frequency. The power spectrum, on the other hand, has much better convergence properties and can be estimated reliably from the available signal [5], [30].
A random signal may be thought of as a signal selected from an ensemble (family) of possible signals by a random experiment governed by some specification of probabilistic structure. The group of signals and the specification of probabilities together comprise the random process (or stochastic process) generating the random signal [5], [30]. According to [5], randomized modulation strategy could be characterized by invariant deterministic and probabilistic structure:
• The nominal or reference on-off a pattern that is being dithered does not change from one switching cycle to the next;
• There are no variations in the requirements on average quantities such as the duty ratio;
• At each new cycle, the same probabilistic structure is used. The dithering (in time) is based on independent trials.
In this context, we can classify the randomized modulation strategies as stationary. Fig. 4, 𝜉𝑘, is the time at
which the, 𝑘 cycle starts. 𝑇𝑘, is the duration of the, 𝑘 cycle.
𝑎𝑘, is the duration of the on-state within this 𝑘 cycle, and, 𝜀𝑘,
is the delay to the turn-on within the 𝑘 cycle. The duty ratio can be express by, 𝑑𝑘= 𝑎𝑘/𝑇𝑘, and the, 𝑠𝑓(𝑡), consists of a
concatenation of 𝑘 cycles.
Fig.4. (a) The nominal switching function, 𝑠𝑓(𝑡); (b) the pulse, 𝑢𝑘(𝑡 − 𝜉𝑘), representing just the 𝑘 cycles of 𝑠𝑓(𝑡).
According [5], [25-28], [31], [32], some combinations used in power converts are:
• randomized pulse point modulation (RPPM): 𝜀𝑘,
changes. 𝑇𝑘, and 𝑎𝑘, fixed;
• RPWM: 𝑎𝑘, changes. 𝜀𝑘= 0. 𝑇𝑘, fixed;
• simplified asynchronous modulation: 𝑇𝑘, changes.
𝑎𝑘, fixed;
• asynchronous modulation: 𝑇𝑘, changes. 𝜀𝑘= 0. 𝑑𝑘,
fixe.
With the, 𝑢𝑘(𝑡 − 𝜉𝑘), denoting the single pulse waveform,
we can write the switching function as:
(1) 𝑠𝑓
(𝑡)= ∑ 𝑢𝑘(𝑡 − 𝜉𝑘) ∞
𝑘=−∞
where, 𝑈𝑘𝑓, denote the Fourier transform of, 𝑢𝑘(𝑡).
The power spectrum of, 𝑠𝑓(𝑡), can be computed according
to procedures described in [5], [31], [32]. This procedure, in effect, computes the autocorrelation and takes its Fourier transform, precisely as required by the definition of the power spectrum (expression 1). According to mentioned in [5], alternatively, one could derive the power-spectrum using the Wiener–Khintchine relation, expression (2).
(2) 𝑆 𝑞(𝑓) = 1 𝑇 ∑ 𝐸[𝑈0(𝑓)𝑈𝑘 ∗(𝑓)𝑒𝑗2Π𝑓(𝜉𝑘−𝜉0)] ∞ 𝑘=−∞
where 𝑇 is 𝐸[𝑇𝑘], is the expected duration of a cycle.
The expression (2) presented a general function, where 𝑈𝑘𝑓 is a function of 𝜀𝑘, 𝑎𝑘, 𝑑𝑘, 𝑇𝑘,. These expression
applications for any stationary randomized modulation strategies must consider the desirable properties of power spectra are dependent on randomization parameters.
Fig. 5(a) shows the spectrum of EMI noise shape of voltage output for RPWM with the switching frequency of 70kHz, using the Simscape library from MatLab, and in accordance with CISPR A standard.
Fig. 5. EMI Noise shape of output voltage: a) Spectrum for RPWM and b) Spectrogram for RPWM.
Fig. 5(b), shows the spectrogram of EMI noise shape of voltage output for an RPWM, where is possible to note (also in Fig. 5(a)) that randomization process introduces the
continuous EMI noise shape, and in low-frequencies, the EMI noise shape follows oscillatory mode with their noise value decreasing across the spectrum.
It is essential to note that the PWM and RPWM [25-28], could be considered as complementary techniques, since the process to generate control signal is the same, only with a difference on the comparator reference; triangular waveform (in case of PWM) or random distribution (in case of RPWM).
Sigma-Delta Modulation
According to discusses in the previous sections, PWM and RPWM vary its duty cycle to control the ratio of the on-state and off-on-state of the power transistor and adjust the output voltage level of the converter. Also, the standard control strategy to generate the control signal used for switch modulation is based on the comparator, where; the triangular waveform (in case of PWM) or random distribution (in case of RPWM) is compared with the 𝐷 command. On the other hand, the control strategy to generate the control signal with SDM is based on three blocks. They are the subtract block (delta), the integrator block (sigma), and the quantizer, according shown in Fig. 6.
Fig.6. Diagram of Sigma–delta modulator
The modulator uses a high gain loop to digitize the input signal 𝑥. The integrator block contributes the gain 𝐴. 𝐴 is very large in the low-frequency band and attenuates according to switching frequency, and their multiple harmonics arise. This means that the output of the modulator almost equals the input signal 𝑥 in the low-frequency band and differs much with it in the high-frequency band [33-35]. In the frequency domain, the undesired contents are moved out from the frequency band to the high-frequency band. In the low-frequency band, the transfer function of the sigma-delta modulator can express by (3).
(3) y = 𝐴 𝐴 + 1𝑥 + 𝐴 𝐴 + 1𝑒 ≈ 𝑥 + 1 𝐴𝑒,
where 𝑒 is a quantization error.
Feedback control circuit (Fig.6) measure, amplify and digitize the difference between the output voltage of the converter and the reference voltage, to generate the control signal for the power transistor driver. Also, the frequency compensator makes sure that the closed-loop has enough phase margin to maintain the stability of the DC-DC converter.
The Fig. 7(a) shows the spectrum of EMI noise shape of voltage output for SDM with the switching frequency of 70kHz, using the Simscape library from MatLab, and in accordance with CISPR A standard.
Fig. 7(b) shows the spectrogram of EMI noise shape of voltage output for SDM, where it is possible to note (also in Fig. 7(a)) that SDM creates communication channels by producing spectral nulls at the switching frequency and their multiple primary harmonics. At the same time, it maintains the continuous spectrum and low noise levels, similarly to the RPWM.
Fig. 7. EMI Noise shape of output voltage: a) Spectrum for SDM and b) Spectrogram for SDM.
EMC Considerations
According to computer simulations presented and discussed in the previous sections, standard PWM with a programmed switching frequency generate harmonics in the spectrum of converter voltages and currents. RPWM techniques allow the elimination of the harmonics, resulting in a continuous spectrum of EMI noise. Besides, the SDM introduces a continuous spectrum of EMI noise; it also allows the removal of EMI noise at a specific range of frequencies. In this context and according to the definition adopted by IEEE, electromagnetic compatibility means "the ability of a device, equipment, or system to function satisfactorily in its EM environment without introducing intolerable electromagnetic disturbances to anything in that environment," Fig. 8 present the spectrum for a defined range, up to 500kHz. Typically, this range of frequency is used in the industry environments for well-sensitive telecommunication devices, and considering our simulation is the range of frequency of switching frequency and their multiple primary harmonics.
Fig.8. EMI noise in the spectrum for a defined range, up to 500𝑘𝐻𝑧. Fig. 8 shows that considering the PWM, the EMI noise shape distribution is as expected, high dB peaks corresponding to the switching frequency and their multiple harmonics. Both RPWM and SDM modulations introduce EMI noise shape from the frequency spectrum continuously.
However, SDM enables communication channels by producing spectral nulls at the switching frequency and their multiple primary harmonics.
From the EMC point of view, EM environments that have telecommunication devices, using specific spectrum bands for communication, data sending, etc., they can be benefited from spectrum-sharing strategies or spread spectrum instead of standard modulation strategies. In this context, through the measure of complementary cumulative distribution (CCD), we can know the probability of a signal's instantaneous power to be a specified noise level above its average power. This measure of CCD can validate the adoption of spread-spectrum or spread-spectrum-sharing techniques in limited space environments. Model the EMI noise shape from a specific band means moving it to another band in the same spectrum. In this context, to know how much the signal power will exceed it`s average and what`s is the probability, it can be beneficial for PEI designs in Smart Cities environments. Fig. 9 shows the CCD of EMI noises analyzed.
Fig.9. The measure of complementary cumulative distribution. Fig. 9 presents the relationship between probability (%) vs. dB above-average power. Despite presented high dB peaks (Fig. 3 (b)), the EMI noise shape with PWM, when analyzed over the whole spectrum, maintains an almost linearity, with a lower probability for high dB values. RPWM follows PWM at a low-frequency band; however, the spread spectrum technique effect observed in Fig. 5 (b), can also be seen by the probability distribution in Fig. 9. The introduction of EMI noise shape continuously over the whole spectrum spreads the high dB peaks in the intermediate bands, thus decreasing the probability of high dB values in these bands. However, increasing the probability of high dB values at the high-frequency band.
Fig. 9 also shows the communication channels created by spectral nulls at the switching frequency and their multiple primary harmonics with SDM, and the increasing probability of lower dB values at low-frequency band, due to the effect of attenuation according to switching frequency, and their multiple harmonics arise. Fig. 7(b) also shows this effect. Moreover, SDM decreases the probability of high dB values for intermediate bands. This happens due the undesired contents are moved out from the low-frequency band to the high-frequency band, which explains the high probability for high dB values in the high-frequency band.
Conclusion and Prospects
This paper presented a prospective review on EMC issues with a focus on the switch modulation strategies, to more comprehension on the spectrum sharing and EMI noise reduction, that might be interesting for designers to reach the EMC assurance. The main benefit of randomized switching strategies is better utilization of the available harmonic
content. When compared with deterministic switching strategies, the effect of randomization generates a reduction of the discrete and introduction of a continuous spectrum. The key difference lies in the requirements of each application, i.e., the tight control in the voltage level of an inverter is not as important as that in a switched PEI.
On the other hand, SDM has been shown to suppress the specified frequency components effectively. SDM strategies are also used to attenuate the discrete EMI noise spectrum, equal to RPWM, and to create spectral nulls at specified frequencies, based on a feedback control circuit. The spectral-null strategy may find several applications, notably for lower frequencies applications.
Thus, switch modulation strategies with spectrum-sharing and spread spectrum techniques is not merely a way to take advantage of existing regulations, but also a flexible approach to minimizing EMI undesirable effects. The choice of better EMI noise shape, considering PEI requirements and EM environment, can be made, even taking into account the switch modulation strategies to improve EMC compliance.
As future development, besides computer simulations of others random distribution (in case of RPWM), improve the order of SDM (number of gains), and Hardware implementation, the references analyzed on this draft suggests that randomized modulation schemes based on Markov. The conclusion of the most references analyzed, suggests a decomposition of the Markov chain optimization problem into two subproblems:
• The transition matrix optimization, and it is concerned mostly with time-domain requirements (ripple control), and to a certain extent with the wide-band constraints in the frequency domain; and; • The optimization of the waveforms at each state and
its primary effects are in satisfying the narrow-band requirements. The proposed decomposition could significantly improve the tractability of the optimization of Markov chains with many states. Also, it's important to note that the lowering of maximum levels of EMI noise, caused by even distribution of interference over frequency range in the case of RPWM and SDM, does not imply lowering of interference waveforms in the time domain. There are significant switching losses associated with 𝑑𝑣/𝑑𝑡 and 𝑑𝑖/𝑑𝑡. Several issues are responsible for these losses, such characteristics of power transistors, control signals, gate drives, stray parameters, and operating points of the systems. Therefore, the choice of the most convenient EMI mitigation techniques depends on the target of the PEI project.
Acknowledgment
This paper is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 812391 - SCENT
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Authors: mgr inż.Hermes Loschi, Uniwersytet Zielonogórski, Instytut Inżynierii Elektrycznej, ul. Licealna 9, 65-417 Zielona Góra, E-mail: eng.hermes.loschi@ieee.org;
prof. dr hab. inż. Robert Smolenski,Uniwersytet Zielonogórski, Instytut Inżynierii Elektrycznej, ul. Licealna 9, 65-417 Zielona Góra, E-mail: r.smolenski@iee.uz.zgora.pl;
dr hab. inż. P. Lezynski, Uniwersytet Zielonogórski, Instytut Inżynierii Elektrycznej, ul. Licealna 9, 65-417 Zielona Góra,
E-mail: p.lezynski@iee.uz.zgora.pl;
mgr inż.Waseem El Sayed, Uniwersytet Zielonogórski, Instytut Inżynierii Elektrycznej, ul. Licealna 9, 65-417 Zielona Góra, E-mail: waseem.elsayed@ieee.org;
mgr inż. Choon Long Lok, Uniwersytet Zielonogórski, Instytut Inżynierii Elektrycznej, ul. Licealna 9, 65-417 Zielona Góra, E-mail: marshall.lok@gmail.com;
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