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Enhanced Circuit Model for Insertion Loss
Prediction of Active EMI Filters Considering
Non-ideal Parameters
Enrico Mazzola
Schaffner Group, Automotive Division and
Politecnico di Milano, DEIB enrico.mazzola@schaffner.com
Flavia Grassi
Politecnico di Milano DEIB 20133 Milan, Italy flavia.grassi@polimi.itAlessandro Amaducci
Schaffner Group Automotive Division 4542 Luterbach, Switzerland alessandro.amaducci@schaffner.comAbstract—Effective design of active filters for specific applica-tions poses several challenges to EMC engineers. If on the one hand, the theoretical considerations available in the literature are complete and exhaustive, on the other hand, when moving to actual filter implementation, some practical considerations on the final application are mandatory. The first aspect to be carefully accounted for regards the actual source and load impedances of the system where the filter is installed. Concerning this, it will be proven that not only the impedance magnitude but also the phase plays a significant role, since disregarding it may lead to undesired oscillations, noise amplification or saturation of the electronics.Also, the non ideal behavior of the involved circuitry has to be considered when predicting the insertion loss of an active EMI filter. An enhanced circuit model of the filter is proposed and its effectiveness for the prediction of the filter insertion loss is proven by measurements on a common mode active filter in the frequency interval from 10 kHz up to 108 MHz.
I. INTRODUCTION
Active EMI filters (AEF) are aimed at suppressing the electromagnetic interference (EMI) generated by electri-cal/electronic devices, e.g., Switched-Mode Power Supplies (SMPSs), by the use of active electronic circuits.
Compared to passive filters, active EMI filters can bring advantages in terms of cost, weight, and performance [1], especially when filtering at relatively low frequencies, e.g., in the interval from 9 kHz up to 1 MHz, is the target. According to authors experience, in the aforementioned frequency band, which is regulated by CISPR25 [2] or SAEJ551 [3] for the automotive sector, the maximum filtering effort is required since cost and volume of passive components is definitely higher than at higher frequencies. This is mainly due to the relatively low switching frequency of the majority of motor drivers available at the moment, that usually spans from 2 kHz up to 13 kHz.
However, when designing an AEF, the focus on the final application is often forgotten even though it dramatically im-pacts on AEF design and performance. As a matter of fact, the This work is supported by Schaffner Group (Nordstrasse 11e, 4542 Luter-bach, Switzerland). See https://www.schaffner.com/.
system in which the AEF is expected to be installed determines some fundamental design parameters, such as the terminal impedances seen by the filter, and the actual noise level the filter should compensate. If these aspects are not properly accounted for in filter design, undesired oscillations, noise amplification or saturation of the involved electronics may occur. This work stresses on the importance of considering the actual impedances of the system when designing an AEF, with particular focus on the phase information, which is usually neglected. An enhanced circuit model accounting for the non-idealities of AEF components is proposed and used to derive an accurate IL analytical expression for an ad hoc designed common mode (CM) AEF, which is afterwards experimentally validated.
Although the presented analysis and experimental assess-ment are carried out for a specific AEF architecture, i.e. the feedback current sensing and current injecting structure for CM filtering, the results of this research are more general and apply also to other AEF topologies.
The article is organized as follows. In Section II, the standard theoretical approach to the AEF design is explained. Then, in Section III and Section IV, the source and load impedances seen by a CM AEF are analyzed, referring to the impedances measured in a real system, to show the impact of magnitude and phase on AEF performance. In Section V the enhanced circuit model is introduced and exploited to derive and validate an accurate expression of AEF IL. Eventually, in Section VI, recommendations for accurate prediction of the IL are suggested.
II. BASICS OFCM ACTIVEFILTERING
The theoretical approach to active filtering is well known in the literature, and it has been already deepened by several researchers [4]–[6]. The concept of active filtering is very intuitive. First, the filter senses the high frequency (HF) noise entering the victim circuit. Then, it elaborates such a noise making use of analog or digital electronics. Eventually, it injects a compensation signal aimed at reducing the HF harmonic content of the conducted noise.
Fig. 1: Four possible AEF feed-back architectures.
Fig. 2: CM AEF topology analyzed in this work.
Most of the studies on active filters done in the last decades are collected in [1], where different design solutions and corre-sponding performance are compared. The conducted noise can be sensed either as a current or as a voltage. In a similar fash-ion, also the compensation signal provided by the filter can be a current or a voltage. In addition, two different architectures are possible, typically denoted as feed-back and feed-forward topologies. All possible combinations have been thoroughly analyzed and tested in the literature [4]. For instance, possible feed-back configurations are exemplified in Fig. 1. The choice of a specific topology rather than another is usually triggered by the final application. Particularly, requirements on CM and/or differential mode (DM) IL, assumptions about the expected source and load impedances, as well as practical considerations, such as possible saturation of the magnetic core used for noise sensing/injection [7], contribute in determining the most suitable configuration.
Although the study presented in this work can be readily extended to all AEF configurations, the theoretical analysis and experimental results presented in this work refer to the CM AEF with current sensing - current injecting feed-back topology shown in Fig. 2.
For this specific configuration, the theoretical IL of the filter is cast [4] as:
IL = 1 + A ZS ZS+ ZL
(1) where A is the open loop transfer function (T FOL) of the
AEF, whereas ZS and ZL denote the complex impedances of
the source and load of the system under analysis.
104 105 106 107 108 Frequency [Hz] 10-2 100 102 104 |Z| [ ] Z S SMPS Z S filter Z L filter Z L LISN
Fig. 3: Common Mode source and load impedances comparison, different cases.
From this expression it is straightforward noticing that AEF performance depends on design parameters of the involved electronic circuitry, which give the open loop transfer function A, and on the source and load impedances of the system. Fur-thermore, according to equation (1) the maximum theoretical insertion loss is achieved when ZS >> ZL.
III. IMPEDANCECHARACTERIZATION OF AREAL APPLICATION
The standard conducted emission test set-up is described in the international standards, e.g., for the automotive sector in CISPR 25 [2]. Hence, during the design of an EMI filter either active or passive, the load impedance ZL is usually
considered to be equal to the LISN input impedance, whereas the source impedance ZS is usually considered to be equal to
the equivalent impedance of the switched-mode power supply (SMPS).
However, if the impedance of automotive LISNs is defined in CISPR 16 [8] and can be easily characterized by mea-surement, measuring the SMPS complex impedance is not a trivial task, and several methods have been recently proposed towards this purpose [9]–[12]. Among them, in this work the method in [9] is used to characterize the CM noise source impedance of the automotive 48 V motor driver under study. The blue and purple traces in Fig. 3 represent the SMPS CM impedance, ZSSM P S, and the CM LISN impedance (ZLLISN)
obtained from measurement. Results are shown from 10 kHz up to 108 MHz, since automotive standards usually require conducted emission measurement in such a frequency interval. Comparison of the two curves show that starting from 1 MHz the difference between the two impedances is less than one order of magnitude, which is not in line with the assumption ZS >> ZL, sometimes found in the literature when choosing
the CM AEF topology to base the design on.
Moreover, as far as the source impedance is concerned, it is worth noticing that the installation of a passive filter between the SMPS and the active filter is often required. This hybrid solution, combining both active and passive filters, is quite common [13], since it allows decreasing the noise peak amplitude, thus avoiding saturation of the AF electronic circuitry. For instance, the use of a passive filter is necessary in power applications, where the high impulsive noise currents,
which can reach peaks of more than 10A, cannot be easily handled by the AEF electronics. The introduction of such an additional passive-filtering stage significantly modifies the source impedance seen by the AEF. The red trace in Fig. 3 is the measured CM equivalent impedance of the SMPS with an input L-C filter at the input (L = 1.2µH and C = 100nF). The comparison with the blue trace, i.e., the magnitude of the SMPS impedance in the absence of the passive filter, proves that the presence of the passive filter may significantly (by two orders of magnitude in this example) reduce the source impedance seen by the CM AEF for frequencies up to some tens of MHz.
Moving to the load side, it has to be considered that the LISN is present during the conducted emissions test only. Conversely, in a practical automotive installations, the AEF can interface to a wide spectrum of impedances, such as a power distribution unit (PDU), a battery pack or other converters, which can all have their own EMI filter. It follows that the load impedance seen by the AEF can significantly differ from the LISN one. This is shown in Fig. 3, where, as a practical example, the yellow trace represents the measured input impedance magnitude of a PDU filter.
The measured source and load impedances displayed in Fig. 3 makes the reader understand that the AEF topology cannot be chosen a priori, with no information on the final application. Thus, either a passive network to stabilize the impedances seen by the AEF, both at source and load side, is included in the design, or the AEF is designed after collecting impedances information on the external system.
IV. IMPACT OF THEPHASE
From (1), it can be observed that not only the actual magni-tude, but also the phase of the source and load impedances may play a non-negligible role in determining AEF performance.
Actually, as long as the load impedance magnitude is much lower than the source impedance magnitude, the impact of the phase can be neglected. However, if this condition is not satisfied (as is the case in Fig. 3), the phase can play an important role, especially in consideration of the fact that also the AEF transfer function A is a complex quantity.
The impact of the phase on IL calculation can be appre-ciated in Fig. 4, where the filter IL is shown for different combinations of external impedances. For the IL calculation, the transfer function A refers to the AEF topology shown in 2, that hereinafter will also be used to collect experimental data. Dashed curves show the theoretical IL calculated with (1) considering only the magnitude of A, ZS and ZL, while
solid lines were obtained by taking into consideration also their phase. The blue traces, obtained for ZS two orders of
magnitude larger than ZL for all the frequency spectrum, are
in perfect agreement, and confirm that in this case the IL is not affected by the phase. This is no longer true when considering the other two cases, i.e., the red and yellow traces, which were calculated by considering the LISN as load impedance and the SMPS impedance (with and without input filter, respectively) as source impedance (see Section
104 105 106 107 108 Frequency [Hz] -40 -20 0 20 40 IL [dB] |Z S| >> |ZL| ZS=ZSMPS; ZL=ZLISN Z S=Zfilter; ZL=ZLISN
Fig. 4: IL variation due to magnitude (dashed line) and phase (solid line) in different source and load impedances scenarii.
Fig. 5: Impact of the phase difference (δ) between ZS and ZL on
the calculated IL.
III). In these cases, neglecting the phase can lead to incorrect estimation of the actual IL in the frequency interval in which the magnitude of the source and load impedances are similar, i.e. around 1 MHz for the red trace and around 300 kHz for the yellow trace.
In order to quantify the impact of the phase of the source and load impedances on the filter IL, the extreme case, still occurring at some frequencies, in which the two impedances are equal in magnitude is considered. The 3D plot in Fig. 5 was obtained by keeping constant (and equal) the magnitude of the two impedances, yet varying their reciprocal phase difference δ. The x-axis and the y-axis are the frequency and the phase difference δ, while the z-axis shows the IL calculated at each possible value of δ. In this example, the phase difference δ spans from 0°, i.e., ZS and ZL have the same phase, to 180°
(in this case, one impedance has phase +90° and the other -90°). It is observed that the larger the phase difference between ZS and ZL, the larger is the error affecting the calculated
IL compared to the case where the phase is neglected. For instance, the IL peak around 300 kHz increases from 27 dB to 44 dB. In addition, the AEF bandwidth is also affected, since the frequency at which the IL becomes 0 dB moves from 17 MHz to 64 MHz depending on the value of δ.
V. ILDERIVATION ACCOUNTING FOR THEAEF NON-IDEAL BEHAVIOR
For accurate IL calculation, the equivalent circuit shown in Fig. 6 is here introduced. As a matter of fact, modelling the AEF under analysis as an ideal current source only (as
Fig. 6: Enhanced AEF equivalent circuit for IL prediction.
in the ideal circuit in Fig. 2) does not allow accounting for the real behavior of the involved circuit components. In this circuit, impedance (Zi) is used to model the passive part
of the injection branch. Particularly, since the current source cannot be directly dc-coupled to the external system, at least a capacitor is required. The impedance zo, in parallel with
the current source, is introduced to account for the fact that, depending on the specific design of the electronic circuitry, the current source stage exhibit an impedance that is not infinite. Such an impedance decreases with frequency [14], thus becoming no longer negligible for high frequencies. Eventually, impedance (Zct) is included to account for the
non-negligible impedance of the current sensor used to sense the noise current.
According to the circuit in Fig. 6, filter IL is cast as:
IL = z 2 oK1+ zoK3 z2 oK2+ zoK4+ K5 (2) where the coefficients Kn are:
K1= Zx(Zct+ ZL+ ZS) + AZSZx (3) K2= Zx(Zct+ ZL+ ZS) (4) K3= ZSZy(Zct+ ZS+ Zy) + ZiZx(Zct+ ZL+ ZS) (5) K4= ZSZy(Zy+ ZS) + Zx(ZiZy+ ZSZL+ ZSZct) (6) K5= ZiZSZx(ZL+ Zct) (7) and Zx= ZS+ ZL+ Zct (8) Zy = ZL+ Zct (9)
For zo approaching infinity, i.e. the ideal case, the IL
expression in (2) simplifies to: IL ' K1
K2
= 1 + A ZS
ZS+ ZL+ Zct
(10) which differs from the ideal expression in (1) for the additional impedance Zctin series with ZL.
Equation (2) has been experimentally validated by compar-ing prediction and measurement of the CM IL of an ad hoc designed AEF with the architecture in Fig. 2. For validation purposes, three test cases were considered, involving different source and load impedances, that is:
Fig. 7: Common mode AEF IL measurements with a VNA, from 10kHz to 108MHz. 104 105 106 107 108 Frequency [Hz] -5 0 5 10 15 20 25 30 ILm a g [dB] -80 -60 -40 -20 0 20 40 60 80 ILp h a s e [deg] ILm Analytical IL m VNA ILp Analytical ILp VNA
Fig. 8: Test case I. Calculated vs Measured IL.
• Test case I: ZS = 50Ω and ZL= 50Ω.
• Test case II: ZS = [50 +jωC1 ]Ω and ZL= [50 + jωL]Ω. • Test case III: ZS = [50 + jωL]Ω and ZL= [50 +jωC1 ]Ω.
where C = 10 nF and L = 22µH.
For IL prediction by equation (2), the complex open loop transfer function (T FOL= A) of the AEF was calculated as the product of the transfer functions of the sensing block, the driver stage and the current source stage.For IL measurement, the test set-up shown in Fig. 7 was exploited. The internal 50Ω impedances of a Vector Network Anlayzer (VNA) has been used as source and load impedances for the first test case. For the other two test cases, the required capacitors and inductors were installed in series to the VNA ports.
For the three test cases under analysis, IL prediction and measurement are compared in Fig. 8, Fig. 9 and Fig. 10, show-ing satisfactory agreement in the overall frequency interval from 10 kHz up to 108 MHz.
VI. CONCLUSION
In this work, a design approach to active EMI filtering which takes into account the main characteristics of the system where
104 105 106 107 108 Frequency [Hz] -10 0 10 20 30 40 IL mag [dB] -150 -100 -50 0 50 100 IL phase [deg] ILm Analytical ILm VNA ILp Analytical ILp VNA
Fig. 9: Test case II. Calculated vs Measured IL.
104 105 106 107 108 Frequency [Hz] -10 0 10 20 30 IL mag [dB] -150 -100 -50 0 50 100 150 IL phase [deg] ILm Analytical ILm VNA ILp Analytical ILp VNA
Fig. 10: Test case III. Calculated vs Measured IL.
the filter will be installed is proposed, and key aspects often neglected or underestimated during the design are outlined. Specific attention was devoted to the impact not only of the magnitude but also of the phase of the external (source and load) impedances, which are proven to play a significant role in determining AEF performance. Hence, these impedances shall be preliminary characterized and used during the design process.
Moreover, an enhanced AEF equivalent circuit was intro-duced, which augments the ideal circuit model (involving an ideal current source only) by the inclusion of additional components, accounting for the actual frequency response of the electronic circuitry used to realize the AEF. Experimental measurements carried out on an ad hoc designed AEF proto-type proved the accuracy of such a circuit in predicting the actual IL of the filter in the frequency interval foreseen by automotive standards for conducted emission testing.
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