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Selected Papers from the 2021 IEEE International Workshop on Metrology...
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Selected Papers from the 2021 IEEE International Workshop on Metrology for Automotive

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: closed (31 May 2022) | Viewed by 25296

Special Issue Editors

Dr. Stefano Cattini

E-Mail Website1 Website2
Guest Editor
Department of Engineering "Enzo Ferrari", University of Modena and Reggio Emilia, 41125 Modena, Italy
Interests: design and validation of measurement methods and measuring systems; measurements in automotive; biomedical measurements
Special Issues, Collections and Topics in MDPI journals
Prof. Roberto Tinarelli

E-Mail Website
Guest Editor
Department of Electrical, Electronic and Information Engineering “Guglielmo Marconi”, Alma Mater Studiorum, University of Bologna, Viale del Risorgimento 2, 40136 Bologna, Italy
Interests: power quality analysis in power networks; calibration of instrument transformers for power quality; diagnostic techniques for electric machines; instrumentation; uncertainty propagation in measurement algorithms
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The 2021 IEEE International Workshop on Metrology for Automotive (https://www.metroautomotive.org/home) will be held in Bologna, Italy, between the 1st and 2nd July 2021. Authors of papers related to sensors presented at the workshop are invited to submit extended versions of their work to this Special Issue for publication.

MetroAutomotive 2021 aims to be a credible reference that allows the technical community to present and discuss the most recent results of scientific and technological research for the automotive industry, with particular emphasis on applications and new trends.

The main focus of this Special Issue is new technology for metrology assisted production in the automotive industry, sensors and associated signal conditioning for automotive, and calibration methods of electronic testing and measurement for automotive.

The program is designed to attract interest from a wide range of researchers, operators, and decision makers from metrology and automotive fields, by presenting the most innovative solutions in this field from the scientific and technological point of view. The workshop covers all aspects of the segment focusing on electrical vehicles, connected autonomous cars, and related mobility.

Topics:

  • Electronic instrumentation for automotive;
  • Automatic test equipment for automotive;
  • Sensors and sensor systems for automotive applications;
  • Wireless sensor networks in automotive;
  • Automotive instrumentation and telematics;
  • Diagnostics;
  • Standards for automotive instrumentation;
  • Legal and ethical implications of metrology in the future automotive field.

Dr. Stefano Cattini
Prof. Roberto Tinarelli
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Published Papers (6 papers)

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Research

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22 pages, 3442 KiB  
Article
Development of an EEG Headband for Stress Measurement on Driving Simulators
by Antonio Affanni, Taraneh Aminosharieh Najafi and Sonia Guerci
Sensors 2022, 22(5), 1785; https://doi.org/10.3390/s22051785 - 24 Feb 2022
Cited by 21 | Viewed by 4109
Abstract
In this paper, we designed from scratch, realized, and characterized a six-channel EEG wearable headband for the measurement of stress-related brain activity during driving. The headband transmits data over WiFi to a laptop, and the rechargeable battery life is 10 h of continuous [...] Read more.
In this paper, we designed from scratch, realized, and characterized a six-channel EEG wearable headband for the measurement of stress-related brain activity during driving. The headband transmits data over WiFi to a laptop, and the rechargeable battery life is 10 h of continuous transmission. The characterization manifested a measurement error of 6 μV in reading EEG channels, and the bandwidth was in the range [0.8, 44] Hz, while the resolution was 50 nV exploiting the oversampling technique. Thanks to the full metrological characterization presented in this paper, we provide important information regarding the accuracy of the sensor because, in the literature, commercial EEG sensors are used even if their accuracy is not provided in the manuals. We set up an experiment using the driving simulator available in our laboratory at the University of Udine; the experiment involved ten volunteers who had to drive in three scenarios: manual, autonomous vehicle with a “gentle” approach, and autonomous vehicle with an “aggressive” approach. The aim of the experiment was to assess how autonomous driving algorithms impact EEG brain activity. To our knowledge, this is the first study to compare different autonomous driving algorithms in terms of drivers’ acceptability by means of EEG signals. The obtained results demonstrated that the estimated power of beta waves (related to stress) is higher in the manual with respect to autonomous driving algorithms, either “gentle” or “aggressive”. Full article
(This article belongs to the Special Issue Selected Papers from the 2021 IEEE International Workshop on Metrology for Automotive)
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20 pages, 4693 KiB  
Article
Optimal Control of Air Conditioning Systems by Means of CO2 Sensors in Electric Vehicles
by Luca Muratori, Lorenzo Peretto, Beatrice Pulvirenti, Raffaella Di Sante, Giovanni Bottiglieri and Federico Coiro
Sensors 2022, 22(3), 1190; https://doi.org/10.3390/s22031190 - 4 Feb 2022
Cited by 5 | Viewed by 1983
Abstract
Considering the consistent reduction in battery range due to the operation of the Heating Ventilation and Air Conditioning (HVAC) system, this study deals with the CO2 measurement inside the cabin of an electric crane and aims to reduce the energy consumption through [...] Read more.
Considering the consistent reduction in battery range due to the operation of the Heating Ventilation and Air Conditioning (HVAC) system, this study deals with the CO2 measurement inside the cabin of an electric crane and aims to reduce the energy consumption through the control of the air recirculation. A control strategy was defined and tested through an experimental set-up where the presence of a driver was simulated as a source of CO2. The cabin was placed inside a climatic wind tunnel and the benefits of this control strategy on the HVAC system energy consumption were assessed, both in the heating and the cooling modes. In addition, we discussed the optimal position of the CO2 sensor inside the cabin by comparing the results obtained from some sensors placed around the cabin occupant with the ones logged by three sensors in the breathing zone. Finally, an investigation of the uncertainty of the indirect measurement of the leakage flow and its dependence on the number of CO2 sensors installed in the cabin was made through the Monte Carlo method. Full article
(This article belongs to the Special Issue Selected Papers from the 2021 IEEE International Workshop on Metrology for Automotive)
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20 pages, 5803 KiB  
Article
Strain Modal Testing with Fiber Bragg Gratings for Automotive Applications
by Francesco Falcetelli, Alberto Martini, Raffaella Di Sante and Marco Troncossi
Sensors 2022, 22(3), 946; https://doi.org/10.3390/s22030946 - 26 Jan 2022
Cited by 22 | Viewed by 4060
Abstract
Strain Modal Testing (SMT), based on strain sensors signal processing, is an unconventional approach to perform Experimental Modal Analysis which is typically based on data measured by accelerometers. SMT is still mainly restricted to academia and requires additional investigation for a successful transition [...] Read more.
Strain Modal Testing (SMT), based on strain sensors signal processing, is an unconventional approach to perform Experimental Modal Analysis which is typically based on data measured by accelerometers. SMT is still mainly restricted to academia and requires additional investigation for a successful transition towards industry. This paper critically reviews why the automotive sector can benefit from this relatively new approach for a variety of reasons. Moreover, a case study representative of the automotive field is analyzed and discussed. Specifically, an SMT methodology is applied to evaluate the modal properties of a reinforced composite roof belonging to a racing solar powered vehicle. In the experimental activity, signals from Fiber Bragg Grating (FBG) sensors, strain gauges, and accelerometers were simultaneously acquired and further processed. The advantages of using optical fibers were discussed, together with their weaknesses and ongoing challenges. The FBG results were compared with the conventional analysis performed with the accelerometers, emphasizing the main similarities and discrepancies. Full article
(This article belongs to the Special Issue Selected Papers from the 2021 IEEE International Workshop on Metrology for Automotive)
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15 pages, 4726 KiB  
Article
Exploring Physiological Signal Responses to Traffic-Related Stress in Simulated Driving
by Pamela Zontone, Antonio Affanni, Alessandro Piras and Roberto Rinaldo
Sensors 2022, 22(3), 939; https://doi.org/10.3390/s22030939 - 26 Jan 2022
Cited by 13 | Viewed by 2482
Abstract
In this paper, we propose a relatively noninvasive system that can automatically assess the impact of traffic conditions on drivers. We analyze the physiological signals recorded from a set of individuals while driving in a simulated urban scenario in two different traffic scenarios, [...] Read more.
In this paper, we propose a relatively noninvasive system that can automatically assess the impact of traffic conditions on drivers. We analyze the physiological signals recorded from a set of individuals while driving in a simulated urban scenario in two different traffic scenarios, i.e., with traffic and without traffic. The experiments were carried out in a laboratory located at the University of Udine, employing a driving simulator equipped with a moving platform. We acquired two Skin Potential Response (SPR) signals from the hands of the drivers, and an electrocardiogram (ECG) signal from their chest. In the proposed scheme, the SPR signals are then processed through a Motion Artifact (MA) removal algorithm such that possible motion artifacts arising during the drive are reduced. An analysis considering the scalogram of the single cleaned SPR signal is presented. This signal, along with the ECG, is then fed to various Machine Learning (ML) algorithms. More specifically, some statistical features are extracted from each signal segment which, after being analyzed through a binary ML model, are labeled as corresponding to a stressful situation or not. Our results confirm the applicability of the proposed approach to identify stress in the two scenarios. This is also in accordance with our findings considering the SPR signal scalograms. Full article
(This article belongs to the Special Issue Selected Papers from the 2021 IEEE International Workshop on Metrology for Automotive)
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16 pages, 1869 KiB  
Article
Air Quality and Comfort Characterisation within an Electric Vehicle Cabin in Heating and Cooling Operations
by Luigi Russi, Paolo Guidorzi, Beatrice Pulvirenti, Davide Aguiari, Giovanni Pau and Giovanni Semprini
Sensors 2022, 22(2), 543; https://doi.org/10.3390/s22020543 - 11 Jan 2022
Cited by 12 | Viewed by 3212
Abstract
This work is aimed at the experimental characterisation of air quality and thermal profile within an electric vehicle cabin, measuring at the same time the HVAC system energy consumption. Pollutant concentrations in the vehicle cabin are measured by means of a low-cost system [...] Read more.
This work is aimed at the experimental characterisation of air quality and thermal profile within an electric vehicle cabin, measuring at the same time the HVAC system energy consumption. Pollutant concentrations in the vehicle cabin are measured by means of a low-cost system of sensors. The effects of the HVAC system configuration, such as fresh-air and recirculation mode, on cabin air quality, are discussed. It is shown that the PM concentrations observed in recirculation mode are lower than those in fresh-air mode, while VOC concentrations are generally higher in recirculation than in fresh-air mode. The energy consumption is compared in different configurations of the HVAC system. The novelty of this work is the combined measurement of important comfort parameters such as air temperature distribution and air quality within the vehicle, together with the real time energy consumption of the HVAC system. A wider concept of comfort is enabled, based on the use of low-cost sensors in the automotive field. Full article
(This article belongs to the Special Issue Selected Papers from the 2021 IEEE International Workshop on Metrology for Automotive)
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Review

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18 pages, 4627 KiB  
Review
A Review of Mechanical and Chemical Sensors for Automotive Li-Ion Battery Systems
by Matteo Dotoli, Riccardo Rocca, Mattia Giuliano, Giovanna Nicol, Flavio Parussa, Marcello Baricco, Anna Maria Ferrari, Carlo Nervi and Mauro Francesco Sgroi
Sensors 2022, 22(5), 1763; https://doi.org/10.3390/s22051763 - 24 Feb 2022
Cited by 11 | Viewed by 8088
Abstract
The electrification of passenger cars is one of the most effective approaches to reduce noxious emissions in urban areas and, if the electricity is produced using renewable sources, to mitigate the global warming. This profound change of paradigm in the transport sector requires [...] Read more.
The electrification of passenger cars is one of the most effective approaches to reduce noxious emissions in urban areas and, if the electricity is produced using renewable sources, to mitigate the global warming. This profound change of paradigm in the transport sector requires the use of Li-ion battery packages as energy storage systems to substitute conventional fossil fuels. An automotive battery package is a complex system that has to respect several constraints: high energy and power densities, long calendar and cycle lives, electrical and thermal safety, crash-worthiness, and recyclability. To comply with all these requirements, battery systems integrate a battery management system (BMS) connected to an complex network of electric and thermal sensors. On the other hand, since Li-ion cells can suffer from degradation phenomena with consequent generation of gaseous emissions or determine dimensional changes of the cell packaging, chemical and mechanical sensors should be integrated in modern automotive battery packages to guarantee the safe operation of the system. Mechanical and chemical sensors for automotive batteries require further developments to reach the requested robustness and reliability; in this review, an overview of the current state of art on such sensors will be proposed. Full article
(This article belongs to the Special Issue Selected Papers from the 2021 IEEE International Workshop on Metrology for Automotive)
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