Recent Trends in Multi-Physics Simulation and Testing of New E-Mobility Technologies

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electrical and Autonomous Vehicles".

Deadline for manuscript submissions: closed (10 February 2022) | Viewed by 14265

Special Issue Editors


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Guest Editor
Dipartimento di Ingegneria Industriale, Università di Padova, 35131 Padova, Italy
Interests: computational electromagnetics; multiphysics modeling; multiscale modeling; MEMS; energy storage; energy harvesting
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Guest Editor
Department of Industrial Engineering, University of Padova, 35131 Padova, Italy
Interests: mechanical vibrations and identification; energy harvesting; robot vibrations; multiphysics systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The research of new technologies for improving the efficiency of e-mobility solutions has now become of crucial importance in order to address market scale-up within the automotive industry. Multiphysics simulation and testing tools are therefore key issues to accelerate the development of next-generation electric vehicles and related components. Research on e-mobility is multidisciplinary, involving, e.g., control systems, micro- and power electronics, computational electromagnetics, and mechanics.

The current Special Issue aims at addressing new trends in theory, practice, and applications of the most recent technologies for e-mobility systems. The topics of interest include but are not limited to:

  • Multiphysics and integrated modeling;
  • Smart sensors and energy harvesters;
  • Dynamics and control of electric vehicles;
  • Power supply and battery design;
  • Wireless charging systems;
  • Energy efficient powertrain design.

Prof. Dr. Federico Moro
Prof. Dr. Alberto Doria
Guest Editors

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Keywords

  • multiphysics
  • dynamics
  • testing
  • simulation
  • mobility
  • electric
  • vehicles
  • batteries
  • sensors
  • control

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Published Papers (3 papers)

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Research

19 pages, 3585 KiB  
Article
Energy Harvesting from Bicycle Vibrations by Means of Tuned Piezoelectric Generators
by Alberto Doria, Edoardo Marconi and Federico Moro
Electronics 2020, 9(9), 1377; https://doi.org/10.3390/electronics9091377 - 25 Aug 2020
Cited by 10 | Viewed by 6099
Abstract
Vibrations of two typical bicycles are measured by means of road tests in bicycle lanes. The analysis of experimental results in terms of power spectral density (PSD) of the acceleration components shows that most of the energy associated to bicycle vibrations is concentrated [...] Read more.
Vibrations of two typical bicycles are measured by means of road tests in bicycle lanes. The analysis of experimental results in terms of power spectral density (PSD) of the acceleration components shows that most of the energy associated to bicycle vibrations is concentrated in a low frequency band (<30 Hz). Since piezoelectric cantilever harvesters achieve the best performance in resonance and the resonant frequency is well above 30 Hz, specific tuning strategies are adopted. A novel mathematical model for simulating the electro-mechanical behaviour of a piezoelectric harvester equipped with an auxiliary oscillator is proposed. Calculated results show the potentialities of this tuning device in terms of generated voltage and stress inside the piezoelectric layer. Prototypes of harvesters equipped with auxiliary oscillators are built and tested in the laboratory obtaining the frequency response function (FRF) of generated voltage. Finally, the average electric power generated by these harvesters (which are assumed to be interfaced to an electronic load by a power management unit based on synchronous rectifying technique) is simulated by using the measured FRFs and PSDs of bicycle vibrations. Full article
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16 pages, 3537 KiB  
Article
Frequency Tuning in Inductive Power Transfer Systems
by Manuele Bertoluzzo and Giuseppe Buja
Electronics 2020, 9(3), 527; https://doi.org/10.3390/electronics9030527 - 23 Mar 2020
Cited by 4 | Viewed by 3031
Abstract
Inductive power transfer systems (IPTSs) systems are equipped with compensation networks that resonate at the supply frequency with the inductance of the transmitting and receiving coils to both maximize the power transfer efficiency and reduce the IPTS power sizing. If the network and [...] Read more.
Inductive power transfer systems (IPTSs) systems are equipped with compensation networks that resonate at the supply frequency with the inductance of the transmitting and receiving coils to both maximize the power transfer efficiency and reduce the IPTS power sizing. If the network and coil parameters differ from the designed values, the resonance frequencies deviate from the supply frequency, thus reducing the IPTS efficiency. To cope with this issue, two methods of tuning the IPTS supply frequency are presented and discussed. One method is aimed at making resonant the impedance seen by the IPTS power supply, the other one at making resonant the impedance of the receiving stage. The paper closes by implementing the first method in an experimental setup and by testing its tuning capabilities on a prototypal IPTS used for charging the battery of an electric vehicle. Full article
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15 pages, 1376 KiB  
Article
A Virtual Sensor for Electric Vehicles’ State of Charge Estimation
by Giambattista Gruosso, Giancarlo Storti Gajani, Fredy Ruiz, Juan Diego Valladolid and Diego Patino
Electronics 2020, 9(2), 278; https://doi.org/10.3390/electronics9020278 - 6 Feb 2020
Cited by 21 | Viewed by 3910
Abstract
The estimation of the state of charge is a critical function in the operation of electric vehicles. The battery management system must provide accurate information about the battery state, even in the presence of failures in the vehicle sensors. This article presents a [...] Read more.
The estimation of the state of charge is a critical function in the operation of electric vehicles. The battery management system must provide accurate information about the battery state, even in the presence of failures in the vehicle sensors. This article presents a new methodology for the state of charge estimation (SOC) in electric vehicles without the use of a battery current sensor, relying on a virtual sensor, based on other available vehicle measurements, such as speed, battery voltage and acceleration pedal position. The estimator was derived from experimental data, employing support vector regression (SVR), principal component analysis (PCA) and a dual polarization (DP) battery model (BM). It is shown that the obtained model is able to predict the state of charge of the battery with acceptable precision in the case of a failure of the current sensor. Full article
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