Power Inductors Behavioral Modeling Revisited

Stoyka, Kateryna; Femia, N.; Capua, Giulia Di

doi:10.1109/tcsi.2020.3002615

Cited by 19 publications

(13 citation statements)

References 26 publications

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“…The GPA has been largely used for chemical process modeling (e.g., for reactor systems [19]), for industrial production process (e.g., for fiber-to-yarn process [20]), and more recently for electronics systems modeling (e.g., for IGBTs [21], for power inductors [22] and power modules [23]). The scientific literature extensively describes the GPA [24] and its use in multi-objective evolutionary approach [25] [26].…”

Section: A Multi-objective Genetic Programmingmentioning

confidence: 99%

Self and Mutual Inductance Behavioral Modeling of Square-Shaped IPT Coils With Air Gap and Ferrite Core Plates

et al. 2022

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The design and optimization of coils for Inductive Power Transfer (IPT) systems is an iterative process conducted in Finite Element (FE) tools that takes a lot of time and computational resources. In order to overcome such limitations in the design process, new empirical equations for the evaluation of the self-inductance and mutual inductance values are proposed in this work. By means of a multi-objective genetic programming algorithm, the self-inductance, the mutual inductance and the coupling factor values obtained from FE simulations of IPT link are accounted by analytical equations based on the geometric parameters defining the IPT link. The behavioral modeling results are compared with both FE-based and experimental results, showing a good accuracy.

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Section: A Multi-objective Genetic Programmingmentioning

confidence: 99%

Self and Mutual Inductance Behavioral Modeling of Square-Shaped IPT Coils With Air Gap and Ferrite Core Plates

et al. 2022

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“…Other papers 49,50,61 focus instead on inductors within a family (i.e., with the same core), by exploiting the family models described in Section 4. In this way, only a few inductors within each family should be characterized, to derive a model valid for all components of the same family.…”

Section: Selection Of the Optimal Inductormentioning

confidence: 99%

Nonlinear models of power inductors: A survey

Oliveri

Lodi

Storace

2021

Circuit Theory & Apps

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Summary Switch‐mode power supplies (SMPSs) are widely exploited to interface electrical energy sources to motors and other electrical loads. Inductors are usually the biggest and heaviest components in SMPSs, limiting their overall power density. Therefore, there is an increasing interest in designing SMPSs with partially saturating inductors, because this significantly reduces their weight and size, thus increasing power density. This paper provides a review of nonlinear behavioral models (based on easy‐to‐measure quantities) of the inductance, power loss, and temperature rise of inductors working, at least partially, in magnetic saturation. This survey discusses the pros, cons, and ranges of validity of these models, with a glimpse at their application to SMPS simulation, design, monitoring, and control.

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“…The values (∆y, ∆z) listed in Table 6 correspond to the RX-TX coil reciprocal positions considered for the test (red circles in Figure 8). The mutual inductance M is experimentally evaluated by measuring the open-circuit voltage V OC at the receiver coil terminals by means of a differential voltage probe, according to (13): Figure 9 shows the behavioral model predictions (red square markers) of the total mutual inductance M tot,bhv obtained by using the model given in Equations (10)-(12), compared to the experimental measured values M tot,exp (green square markers). These results further validate the proposed behavioral model and confirm its good accuracy and generalization capability.…”

Section: Behavioral Model Experimental Validationmentioning

confidence: 99%

“…In this paper, we follow the second approach, by deriving, validating and using an analytical behavioral model of M. This modeling approach has been previously used to assess the losses and performances in power devices and power modules, like IGBTs [12], inductors [13], and inverter modules [14], and to study static WPTSs [15]. Compared to the static condition analyzed in [15], the dynamic problem analyzed herein introduces new challenges and features, related to the geometry and to the time-domain behavior.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Dynamic Wireless Power Transfer Systems Based on Behavioral Modeling of Mutual Inductance

et al. 2021

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This paper proposes a system-level approach suitable to analyze the performance of a dynamic Wireless Power Transfer System (WPTS) for electric vehicles, accounting for the uncertainty in the vehicle trajectory. The key-point of the approach is the use of an analytical behavioral model that relates mutual inductance between the coil pair to their relative positions along the actual vehicle trajectory. The behavioral model is derived from a limited training data set of simulations, by using a multi-objective genetic programming algorithm, and is validated against experimental data, taken from a real dynamic WPTS. This approach avoids the massive use of computationally expensive 3D finite element simulations, that would be required if this analysis were performed by means of look-up tables. This analytical model is here embedded into a system-level circuital model of the entire WPTS, thus allowing a fast and accurate analysis of the sensitivity of the performance as the actual vehicle trajectory deviates from the nominal one. The system-level analysis is eventually performed to assess the sensitivity of the power and efficiency of the WPTS to the vehicle misalignment from the nominal trajectory during the dynamic charging process.

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Power Inductors Behavioral Modeling Revisited

Cited by 19 publications

References 26 publications

Self and Mutual Inductance Behavioral Modeling of Square-Shaped IPT Coils With Air Gap and Ferrite Core Plates

Self and Mutual Inductance Behavioral Modeling of Square-Shaped IPT Coils With Air Gap and Ferrite Core Plates

Nonlinear models of power inductors: A survey

Analysis of Dynamic Wireless Power Transfer Systems Based on Behavioral Modeling of Mutual Inductance

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