Accuracy Assessment of Numerical Dosimetry for the Evaluation of Human Exposure to Electric Vehicle Inductive Charging Systems

被引:36
作者
Arduino, Alessandro [1 ]
Bottauscio, Oriano [1 ]
Chiampi, Mario [1 ]
Giaccone, Luca [2 ]
Liorni, Ilaria [3 ]
Kuster, Niels [3 ]
Zilberti, Luca [1 ]
Zucca, Mauro [1 ]
机构
[1] Ist Nazl Ric Metrol, I-10135 Turin, Italy
[2] Politecn Torino, Dipartimento Energia, I-10124 Turin, Italy
[3] ITIS Fdn, CH-8004 Zurich, Switzerland
关键词
Magnetic domains; Coils; Numerical models; Magnetic resonance imaging; Computational modeling; Mathematical model; Analytical models; Basic restrictions; electric vehicles; electro-magnetic fields; inductive charging; numerical dosimetry; safety; POWER TRANSFER SYSTEM; FREQUENCY MAGNETIC-FIELDS; ANATOMICAL MODELS;
D O I
10.1109/TEMC.2019.2954111
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页码:1939 / 1950
页数:12
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