Accuracy Assessment of Numerical Dosimetry for the Evaluation of Human Exposure to Electric Vehicle Inductive Charging Systems.
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| Title: | Accuracy Assessment of Numerical Dosimetry for the Evaluation of Human Exposure to Electric Vehicle Inductive Charging Systems. |
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| Authors: | Arduino, Alessandro1 (AUTHOR) a.arduino@inrim.it, Bottauscio, Oriano1 (AUTHOR) o.bottauscio@inrim.it, Chiampi, Mario1 (AUTHOR) m.chiampi@inrim.it, Giaccone, Luca2 (AUTHOR) luca.giaccone@polito.it, Liorni, Ilaria3 (AUTHOR) liorni@itis.swiss, Kuster, Niels3 (AUTHOR) kuster@itis.swiss, Zilberti, Luca1 (AUTHOR) l.zilberti@inrim.it, Zucca, Mauro1 (AUTHOR) m.zucca@inrim.it |
| Source: | IEEE Transactions on Electromagnetic Compatibility. Oct2020, Vol. 62 Issue 5, p1939-1950. 12p. |
| Subjects: | Electric vehicles, Radiation dosimetry, Electric potential, Electric charge, Electromagnetic fields |
| Abstract: | In this article, we discuss numerical aspects related to the accuracy and the computational efficiency of numerical dosimetric simulations, performed in the context of human exposure to static inductive charging systems of electric vehicles. Two alternative numerical methods based on electric vector potential and electric scalar potential formulations, respectively, are here considered for the electric field computation in highly detailed anatomical human models. The results obtained by the numerical implementation of both approaches are discussed in terms of compliance assessment with ICNIRP guidelines limits for human exposure to electromagnetic fields. In particular, different strategies for smoothing localized unphysical outliers are compared, including novel techniques based on statistical considerations. The outlier removal is particularly relevant when comparison with basic restrictions is required to define the safety of electromagnetic fields exposure. The analysis demonstrates that it is not possible to derive general conclusions about the most robust method for dosimetric solutions. Nevertheless, the combined use of both formulations, together with the use of an algorithm for outliers removal based on a statistical approach, allows to determine final results to be compared with reference limits with a significant level of reliability. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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