Passenger Exposure to Magnetic Fields in Electric Vehicles

In electric vehicles, passengers sit very close to an electric system of significant power, usually for a considerable amount of time. The relatively high currents achieved in these systems and the short distances between the power devices and the passengers mean that the latter could be exposed to relevant magnetic fields. This implies that it becomes necessary to evaluate the electromagnetic environment in the interior of these vehicles before releasing them in the market. Moreover, the hazards of magnetic field exposure must be taken into account when designing electric vehicles and their components. For this purpose, estimation tools based on finite element simulations can prove to be very useful. With appropriate design guidelines, it might be possible to make electric vehicles safe from the electromagnetic radiation point of view

Passenger Exposure to Magnetic Fields due to the Batteries of an Electric Vehicle

In electric vehicles, passengers sit very close to an electric system of significant power. The high currents achieved in these vehicles mean that the passengers could be exposed to significant magnetic fields. One of the electric devices present in the power train are the batteries. In this paper, a methodology to evaluate the magnetic field created by these batteries is presented. First, the magnetic field generated by a single battery is analyzed using finite elements simulations. Results are compared to laboratory measurements, taken from a real battery, in order to validate the model. After this, the magnetic field created by a complete battery pack is estimated and results are discussed

Best practice guide for the assessment of EMF exposure from vehicle Wireless Power Transfer systems

open11sì(Editors: Roberta Guilizzoni, Stuart Harmon, Mauro Zucca)This document is based on the experience gained by the partners involved in the EMPIR Project 16ENG08 "Metrology for inductive charging of electric vehicles (MICEV)" (www.micev.eu). The project addressed the electromagnetic metrology and human exposure problems related to inductive charging of electric vehicles, both from a modelling and a measurement point of view. The guidelines reported here are designed for people who approach the assessment of human exposure in vehicles and around inductive charging stations. These guidelines are intended to complement the published standards in use and those currently being developed by international technical organisations and bodies. This document concerns the charging of electric vehicles, for transmitted power up to 200 kW. The frequency range of interest is related to resonant coils that produce significant electromagnetic field (EMF) emissions from the charging station. Resonant coils operate in the frequency range between 20 kHz and 85 kHz. Their electric current, and thus the magnetic field and harmonic distortion, is very low and not significant in relation to human exposure guidelines. Consequently, the frequency range of interest for human exposure does not exceed 100 kHz. This guide seeks to assemble the experience gained in the field of human exposure assessment and to provide information for the assessment of exposure through experimental measurements and validated calculations. The calculation of the induced quantities, in particular the induced electric field and electric currents in the tissues, is of fundamental importance for the determination of human exposure. From the point of view of dosimetry, for obvious reasons of feasibility, the calculation replaces the measurement. Therefore, a whole chapter of this guide covers the choice of instruments and the description of the correct settings for both the magnetic field calculations and the dosimetric calculations. The document particularly focuses on the following challenges: • the testing framework, including the common layout of charging stations, with reference to the normative and EU Directive on magnetic field exposure (Sections 4 to 6); • means and methods to perform: o measurements of the magnetic flux density in and around a vehicle; o measurements of limb currents (Section 7); • means and methods to perform: o analytical calculation of magnetic flux density levels for EMF exposure assessment; o computation of the induced electric fields in human beings (Section 8). The guidelines contain some appendices, which include the following: a real example of a charging station; some tables with the exposure limits referred to in this guide; a brief comparison between two existing standards; a test case of a numerical code to calculate the sources; some results on the sensitivity of simulated exposure metrics to the variations in tissue properties and, finally, the measurement capabilities of European national metrological institutes concerning AC magnetic fields at the frequency range of interest for Wireless Power Transfer systems (WPTs). These guidelines do not intend to discuss the implementation of wireless charging systems, the design of their components or the optimisation of their performance, as they do not discuss the interoperability or the techniques for building the systems, or their classification. Risk analysis and mitigation measures are beyond the scope of this guideopenAnkarson, Peter; Bottauscio, Oriano; Clarke, Bob; Freschi, Fabio; Guilizzoni, Roberta; Harmon, Stuart; Laporta, Erika; Pichon, Lionel; Bruna Romero, Jorge; Zilberti, Luca; Zucca, MauroAnkarson, Peter; Bottauscio, Oriano; Clarke, Bob; Freschi, Fabio; Guilizzoni, Roberta; Harmon, Stuart; Laporta, Erika; Pichon, Lionel; Bruna Romero, Jorge; Zilberti, Luca; Zucca, Maur

Active Reduction of Magnetic Fields in Vehicles

This paper presents an innovative solution for the challenging problem of suppressing low frequent magnetic fields generated by electrical driven powertrains. The solution is based on active field reduction by generating a counter phase magnetic field to suppress the original field. Main principles and technical challenges of such a system are described and discussed. To illustrate the achievable suppression levels, measurement results under different drive modes of two commercially available electrically powered vehicle models (from two different makers) are presented

Estimation of real traffic radiated emissions from electric vehicles in terms of the driving profile using neural networks

The increment of the use of electric vehicles leads to a worry about measuring its principal source of environmental pollution: electromagnetic emissions. Given the complexity of directly measuring vehicular radiated emissions in real traffic, the main contribution of this PhD thesis is to propose an indirect solution to estimate such type of vehicular emissions. Relating the on-road vehicular radiated emissions with the driving profile is a complicated task. This is because it is not possible to directly measure the vehicular radiated interferences in real traffic due to potential interferences from another electromagnetic wave sources. This thesis presents a microscopic artificial intelligence model based on neural networks to estimate real traffic radiated emissions of electric vehicles in terms of the driving dynamics. Instantaneous values of measured speed and calculated acceleration have been used to characterize the driving profile. Experimental electromagnetic interference tests have been carried out with a Vectrix electric motorcycle as well as Twizy electric cars in semi-anechoic chambers. Both the motorcycle and the car have been subjected to different urban and interurban driving profiles. Time Domain measurement methodology of electromagnetic radiated emissions has been adopted in this work to save the overall measurement time. The relationship between the magnetic radiated emissions of the Twizy and the corresponding speed has been very noticeable. Maximum magnetic field levels have been observed during high speed cruising in extra-urban driving and acceleration in urban environments. A comparative study of the prediction performance between various static and dynamic neural models has been introduced. The Multilayer Perceptron feedforward neural network trained with Extreme Learning Machines has achieved the best estimation results of magnetic radiated disturbances as function of instantaneous speed and acceleration. In this way, on-road magnetic radiated interferences from an electric vehicle equipped with a Global Positioning System can be estimated. This research line will allow quantify the pollutant electromagnetic emissions of electric vehicles and study new policies to preserve the environment

Estimation of real traffic radiated emissions from electric vehicles in terms of the driving profile using neural networks

The increment of the use of electric vehicles leads to a worry about measuring its principal source of environmental pollution: electromagnetic emissions. Given the complexity of directly measuring vehicular radiated emissions in real traffic, the main contribution of this PhD thesis is to propose an indirect solution to estimate such type of vehicular emissions. Relating the on-road vehicular radiated emissions with the driving profile is a complicated task. This is because it is not possible to directly measure the vehicular radiated interferences in real traffic due to potential interferences from another electromagnetic wave sources. This thesis presents a microscopic artificial intelligence model based on neural networks to estimate real traffic radiated emissions of electric vehicles in terms of the driving dynamics. Instantaneous values of measured speed and calculated acceleration have been used to characterize the driving profile. Experimental electromagnetic interference tests have been carried out with a Vectrix electric motorcycle as well as Twizy electric cars in semi-anechoic chambers. Both the motorcycle and the car have been subjected to different urban and interurban driving profiles. Time Domain measurement methodology of electromagnetic radiated emissions has been adopted in this work to save the overall measurement time. The relationship between the magnetic radiated emissions of the Twizy and the corresponding speed has been very noticeable. Maximum magnetic field levels have been observed during high speed cruising in extra-urban driving and acceleration in urban environments. A comparative study of the prediction performance between various static and dynamic neural models has been introduced. The Multilayer Perceptron feedforward neural network trained with Extreme Learning Machines has achieved the best estimation results of magnetic radiated disturbances as function of instantaneous speed and acceleration. In this way, on-road magnetic radiated interferences from an electric vehicle equipped with a Global Positioning System can be estimated. This research line will allow quantify the pollutant electromagnetic emissions of electric vehicles and study new policies to preserve the environment

Evaluation of electric and magnetic fields distribution and SAR induced in 3D models of water containers by radiofrequency radiation using FDTD and FEM simulation techniques

In this study, two software packages using different numerical techniques FEKO 6.3 with Finite-Element Method (FEM) and XFDTD 7 with Finite Difference Time Domain Method (FDTD) were used to assess exposure of 3D models of square, rectangular, and pyramidal shaped water containers to electromagnetic waves at 300, 900, and 2400 MHz frequencies. Using the FEM simulation technique, the peak electric field of 25, 4.5, and 2 V/m at 300 MHz and 15.75, 1.5, and 1.75 V/m at 900 MHz were observed in pyramidal, rectangular, and square shaped 3D container models, respectively. The FDTD simulation method confirmed a peak electric field of 12.782, 10.907, and 10.625 V/m at 2400 MHz in the pyramidal, square, and rectangular shaped 3D models, respectively. The study demonstrated an exceptionally high level of electric field in the water in the two identical pyramid shaped 3D models analyzed using the two different simulation techniques. Both FEM and FDTD simulation techniques indicated variations in the distribution of electric, magnetic fields, and specific absorption rate of water stored inside the 3D container models. The study successfully demonstrated that shape and dimensions of 3D models significantly influence the electric and magnetic fields inside packaged materials; thus, specific absorption rates in the stored water vary according to the shape and dimensions of the packaging materials.Comment: 22 pages, 30 figures and 2 table

Assessment of Exposure to Electric Vehicle Inductive Power Transfer Systems: Experimental Measurements and Numerical Dosimetry

open8High-power inductive power transfer (IPT) systems for charging light and heavy electric vehicles pose safety concerns if they are installed in uncontrolled environments. Within the framework of the European Project EMPIR-16ENG08 MICEV, a wide experimental and numerical study was conducted to assess the exposure of the general public to IPT stray magnetic fields for two different exposure scenarios: (1) for an IPT model system derived from the SAE J2954 standard operating at 85 kHz for a light electric vehicle coupled with the model of a realistic car-body model; and (2) for an IPT model system with a maximum rated power of 50 kW at 27.8 kHz for a real minibus that was reproduced with some simplifications in two different 3D finite element method (FEM) simulation tools (Opera 3D and CST software). An ad hoc measurement survey was carried out at the minibus charging station to validate the simulations of the real bus station for both aligned and misaligned IPT coils. Based on this preliminary study, a safety factor was chosen to ensure a conservative dosimetric analysis with respect to the model approximations. As highlighted in this study, the vehicle-body serves as an efficient screen to reduce the magnetic field by at least three orders of magnitude close to the coils. By applying FEM, computed spatial distribution to the Sim4Life software, the exposure of three Virtual Population human anatomical phantoms (one adult, one child, and a newborn) was assessed. The three phantoms were placed in different postures and locations for both exposure scenarios. The basic restriction limits, established by the current guidelines, were never exceeded within the vehicles; however, the basic restrictions were exceeded when an adult crouched outside the minibus, i.e., near the coils, or when a newborn was placed in the same location. Borderline values were observed in the light car. In the case of the bus, limits coming from the Institute of Electrical and Electronics Engineers (IEEE) guidelines are never exceeded, while basic restrictions coming from the International Commission on Non-Ionizing Radiation Protection (ICNIRP) guidelines are exceeded up to 12% for an adult and up to 38% for a newborn. This paper presents novel dosimetric data generated in an IPT system for heavy vehicles and confirms some of the literature data on light vehicles.openIlaria Liorni; Oriano Bottauscio; Roberta Guilizzoni; Peter Ankarson; Jorge Bruna; Arya Fallahi; Stuart Harmon; Mauro ZuccaLiorni, Ilaria; Bottauscio, Oriano; Guilizzoni, Roberta; Ankarson, Peter; Bruna, Jorge; Fallahi, Arya; Harmon, Stuart; Zucca, Maur

The pitch-heave dynamics of transportation vehicles

The analysis and design of suspensions for vehicles of finite length using pitch-heave models is presented. Dynamic models for the finite length vehicle include the spatial distribution of the guideway input disturbance over the vehicle length, as well as both pitch and heave degrees-of-freedom. Analytical results relate the vehicle front and rear accelerations to the pitch and heave natural frequencies, which are functions of vehicle suspension geometry and mass distribution. The effects of vehicle asymmetry and suspension contact area are evaluated. Design guidelines are presented for the modification of vehicle and suspension parameters to meet alternative ride quality criteria

Dynamic inductive power transfer lane design for e-bikes

This paper presents the concept and initial test results of an inductive lane design capable of dynamic and wirelessly transfer power to electric bicycles (e-bikes). On the lane side, a sequence of oblong primary coils embedded underneath ground surface, along the vehicle path, can be independently excited by high frequency alternating current. The oscillating magnetic field of each primary coil is individually enabled when a Radio Frequency Identification (RFID) tag on board of the e-bike is detected and authenticated by an auxiliary coil laying close to that primary coil. On the e-bike, energy for the powertrain is harvested from the lane by a secondary coil that is installed around its rear wheel. When the e-bike is moving over inter-coil gaps, or anywhere away from the inductive lane, on-board power is sustained with the excess energy stored during transits over energized coils. Preliminary results from a prototyped module demonstrate the feasibility of the system, which could also be used by similarly adapted lightweight electric vehicles, such as rickshaws, electric wheel chairs and other electric personal mobility devices, favoring a new, low cost, sustainable urban modal variant.Research partially supported by grant SFRH/BD/52349/2013 from FCT, the Portuguese funding agency supporting science, technology and innovation, under the scope of the MIT-Portugal Program. L. A. Lisboa Cardoso and J. L. Afonso are with the Centro ALGORITMI, Department of Industrial Electronics, University of Minho, Campus de Azurém, 4800-058 Guimarães, Portugal (tel. 351-253-510183; e-mails: [email protected], [email protected]). M. Comesaña Martinez and A. A. Nogueiras Meléndez, are with the Department of Electronics Technology, University of Vigo, Vigo, Pontevedra 36310, Spain (e-mail: [email protected])