Endre søk
Link to record
Permanent link

Direct link
Publikasjoner (5 av 5) Visa alla publikasjoner
Dahlbom, S., Sanfridson, M. & Sjöblom, T. (2023). Evaluation of Detection Principles and Challenges in Early Detection of Thermal Runaway in Batteries.
Åpne denne publikasjonen i ny fane eller vindu >>Evaluation of Detection Principles and Challenges in Early Detection of Thermal Runaway in Batteries
2023 (engelsk)Rapport (Annet vitenskapelig)
Abstract [en]

The amount of battery electrical vehicles (BEVs) carried as cargo on ro-ro ships is increasing. The possibility of thermal runaway in a lithium-ion battery makes BEVs a different fire risk compared to internal combustion engine vehicles (ICEV). One of the challenges that arise is how to detect a thermal runaway early. Current detection systems in ro-ro spaces generally consist of smoke and/or heat detection. To identify potential techniques and challenges for detection of a thermal runaway, as early as possible, tests with batteries and detectors are needed. Tests with one battery cell were performed inside an ISO container (with almost negligible ventilation) as well as in an open room with moderate ventilation (14 air changes per hour). Point-type detectors (two smoke and heat detectors, one CO detector, and one LEL detector), thermal imaging, video analytics, and light detection and ranging (LIDAR) were evaluated in the tests. A total of 14 tests were conducted. The detectors were evaluated in different positions relative to the battery cell and comparative tests with wood-sticks were performed to investigate the detectors’ ability to detect a more conventional source of fire. Based on the results, it can be concluded that early detection of thermal runaway in batteries is possible in principle. However, detection is a matter of circumstances e.g., ventilation, gas/smoke production and the location of the detector(s). The result indicates that detection in a small and confined space is relatively manageable, but detection in a large and open space could be more of a challenge. If the gas/smoke is cooled down it may sink and spread along the floor/deck, instead of rising and spreading along the ceiling. This would be a challenge with current smoke detectors installed in the ceiling. Shielding may be a problem, especially with LIDAR and thermal imaging. Future research should address full-scale tests, and it is recommended to include Optical Gas Imaging (OGI) as a mean of detection.

Publisher
s. 37
Serie
LASHFIRE Internal Report IR09.15
HSV kategori
Identifikatorer
urn:nbn:se:ri:diva-67747 (URN)
Merknad

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 814975. 

Horizon H2020-MG-2018-Two-Stages. Starting date: 2019-09-01 Duration: 48 months. MG-2.2-2018: Marine Accident Response, Subtopic C

Tilgjengelig fra: 2023-11-13 Laget: 2023-11-13 Sist oppdatert: 2023-11-13bibliografisk kontrollert
Hadj-Bachir, M., Bagheri, T., Toss, H., de Souza, P. & Sanfridson, M. (2023). Over-the-Air Automotive Radars Hardware-in-Loop Test for Development and Validation of Active Safety Systems and Autonomous Cars. In: 2023 IEEE International Workshop on Metrology for Automotive (MetroAutomotive): . Paper presented at IEEE International Workshop on Metrology for Automotive (MetroAutomotive). 28-30 June 2023 (pp. 205-210).
Åpne denne publikasjonen i ny fane eller vindu >>Over-the-Air Automotive Radars Hardware-in-Loop Test for Development and Validation of Active Safety Systems and Autonomous Cars
Vise andre…
2023 (engelsk)Inngår i: 2023 IEEE International Workshop on Metrology for Automotive (MetroAutomotive), 2023, s. 205-210Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Due to the development of new radar technology for advanced driver-assistance systems (ADAS) and automated driving (AD) applications, testing radars for real world conditions is highly desirable. However, testing autonomous driving functions on public roads can be dangerous and the tests results are not always reproducible. In this paper, we present a novel Over-the-Air (OTA) Hardware-In-the-Loop (HIL) radar target simulator for testing radar systems. The complete simulation setup including hardware and software implementations will be presented in this article. We illustrate a test procedure by creating Euro NCAP scenarios, and explain the benefits and importance of realtime HIL testing of automotive radars.

HSV kategori
Identifikatorer
urn:nbn:se:ri:diva-66366 (URN)10.1109/metroautomotive57488.2023.10219135 (DOI)
Konferanse
IEEE International Workshop on Metrology for Automotive (MetroAutomotive). 28-30 June 2023
Tilgjengelig fra: 2023-09-07 Laget: 2023-09-07 Sist oppdatert: 2023-09-07bibliografisk kontrollert
Sjöblom, T., Benderius, O., Blanch, K., Berger, C., Rylander, R., Karlsson, F., . . . Lundman, J. (2023). REEDS: Reference data and algorithms for research and development of smart ships. Göteborg
Åpne denne publikasjonen i ny fane eller vindu >>REEDS: Reference data and algorithms for research and development of smart ships
Vise andre…
2023 (engelsk)Rapport (Annet vitenskapelig)
Alternativ tittel[sv]
Referensdata och algoritmer till stöd för forskning och utveckling av smarta fartyg
Abstract [en]

The Swedish Transport Administration Research and Innovation fund for Maritime research funded the project "Reference data and algorithms to support research and development of smart ships". The project goes by the working name, and is communicated as, Reeds. It responds to a synthesis of a number of different needs identified in previous projects and studies. The background to the project is that in recent years the focus has been on developing algorithms to interpret and act on the physical environment around different types of craft. In order to be able to develop and evaluate these algorithms, it has become clear that open datasets and a fair benchmarking platform are required that allow various developers in industries and researchers to evaluate algorithms. In the road vehicle sector, Kitti, as of 2013, is the largest dataset used as a reference dataset. The dataset in this project contains sensor data from several data collection occasions within a maritime context, from high-precision sensors such as cameras, radar, lidar, and IMU. For marine applications, there has been no similar dataset with anywhere near the same amount of data and time synchronisation between sensors. The reference data and reference algorithms were available periodically during the project through an online service where researchers and developers could upload their algorithms to use the dataset.

In addition to the dataset itself, Reeds adds additional strengths compared to other reference datasets:

-        New approach to comparing algorithms fairly, where new algorithms are always compared on a centralised hardware in a cloud service and re-evaluated when new data is added, i.e. an unbiased algorithm evaluation service.

-        Method that combines NTP and PTP time protocols for synchronisation between the sensors with microsecond accuracy

-        More types and more modern sensors that can be used at a higher level of abstraction and can thus be applied in more areas.

-        Sensor fusion of both onboard and land-side sensors

-        Identify areas of application for navigation and surveillance on land based on the algorithms developed during the project and the use of new sensor types not established in shipping.

-         

The project built up a maritime reference data set that enables the creation of a digital description for the ship's surrounding environment and developed reference algorithms to demonstrate new navigation and monitoring methodology in the area of "enhanced navigation".

"Enhanced navigation" is defined under the project as the use of new technology based on developments in digitisation and autonomous functions, where new navigation methods use sensors both on board and ashore to increase maritime safety and robustness. The project has built a web-based user interface referred to in the report as "Crowsnest" that handles these new sensors and visualises this data in a familiar interface similar to an overlay in ECDIS that is openly available for the public to build on. Which was used for the evaluation and concept development of new user interfaces based on feedback from pilots and VTS operators.

By providing reference datasets and reference algorithms with demonstrations, researchers and companies now have the opportunity to develop algorithms for the intelligent and autonomous ships of the future.

Abstract [sv]

Projektet “Referensdata och algoritmer till stöd för forskning och utveckling av smarta fartyg” har finansierats av Trafikverkets Forsknings - och Innovationsportfölj för sjöfart. Projektet går under arbetsnamnet och kommuniceras som Reeds svarar mot en syntes av ett antal olika behov som identifierats i tidigare projekt och studier. Bakgrunden till projektet är att de senaste åren har fokus lagts på att ta fram algoritmer för att tolka och agera på den fysiska miljön kring olika typer av farkoster. För att kunna utveckla och utvärdera dessa algoritmer har det blivit tydligt att det krävs öppna dataset och en rättvis benchmarkingplattform som tillåter olika utvecklare inom industrier och forskare att utvärdera algoritmer. Inom vägfordonssektorn är Kitti , från 2013, det största datasetet som används som referensdata set. Datasetet i detta projekt innehåller sensordata från flertalet datainsamlingstillfällen i en maritim kontext, från högprecisionssensorer som kameror, radar, lidar, och IMU. För maritima applikationer har det inte funnits något liknande dataset med tillnärmelsevis lika stor datamängd och med tidssynkronisering mellan sensorer. Referensdata och referensalgoritmerna var tillgängliga periodvis under projektet genom en onlinetjänst där forskare och utvecklare kunde ladda upp sina algoritmer för att använda datasetet. 

Utöver själva datasetet tillför Reeds ytterligare styrkor jämfört andra referensdata set:

-        Nytt tillvägagångssätt för att jämföra algoritmer rättvist, där nya algoritmer alltid jämförs på en centraliserad hårdvara i en molntjänst och omvärderas när nya data läggs till, dvs en opartisk tjänst för utvärdering av algoritmer. 

-        Metod som kombinerar NTP och PTP tidsprotokoll för synkronisering mellan sensorerna med mikrosekunds noggrannhet  

-        Fler typer och modernare sensorer som kan användas på en högre abstraktionsnivå, och kan därmed tillämpas inom fler områden. 

-        Sensorfusion av både ombord sensorer och av sensorer på landsidan

-        Identifiera tillämpningsområden för navigation och övervakning i land baserat på algoritmerna som togs fram under projektet och användning av nya sensortyper som ej är etablerade inom sjöfarten

-         

Projektet har etablerat ett maritimt referensdataset som möjliggör att skapa en digital beskrivning av fartygets omgivande miljö samt utvecklade referensalgoritmer för att demonstrera nya navigations- och övervakningsmetoder inom området för “enhanced navigation”.

“Enhanced navigation” definieras inom projektet som användandet av ny teknik för navigation som bygger på utvecklingen inom digitalisering och autonoma funktioner, där nya navigationsmetoder använder sensorer både ombord och iland för att öka sjösäkerheten och robustheten. Projektet har byggt upp ett webbaserat användargränssnitt, “Crowsnest”, som hanterar dessa nya sensorer och visualiserar denna data i ett familjärt gränssnitt, liknande en overlay i ECDIS som finns öppet tillgängligt för allmänheten att bygga vidare på. Detta användes för utvärdering och konceptutveckling av nya användargränssnitt baserat på erfarna lotsar och VTS-operatörers åsikter.Genom att tillhandahålla referensdataset och referensalgoritmer med demonstrationer ges nu forskare och företag möjligheten att utveckla algoritmer för framtidens intelligenta och autonoma fartyg.

sted, utgiver, år, opplag, sider
Göteborg: , 2023. s. 92
Serie
RISE Rapport ; 2023:83
Emneord
autonomous shipping, MASS, sensor fusion, enhanced navigation, reference dataset, algorithm benchmarking, massive data, shore sensors, algorithm benchmarking, shore sensors, beyond application dataset, lidar, IMU, radar, time synchronisation
HSV kategori
Identifikatorer
urn:nbn:se:ri:diva-65755 (URN)978-91-89821-56-9 (ISBN)
Forskningsfinansiär
Swedish Transport Administration, P105354
Merknad

Projektet har finansierats av Trafikverkets Forskning och Innovations sjöfartsportfölj (P105354). Trafikverket projektnummer: TRV2019/120103

Tilgjengelig fra: 2023-08-10 Laget: 2023-08-10 Sist oppdatert: 2024-03-04bibliografisk kontrollert
Warg, F., Johansson, R., Skoglund, M., Thorsén, A., Brännström, M., Gyllenhammar, M. & Sanfridson, M. (2020). The Quantitative Risk Norm - A Proposed Tailoring of HARA for ADS. In: Proceedings of 2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W): . Paper presented at 6th International Workshop on Safety and Security of Intelligent Vehicles (SSIV 2020). Los Alamitos
Åpne denne publikasjonen i ny fane eller vindu >>The Quantitative Risk Norm - A Proposed Tailoring of HARA for ADS
Vise andre…
2020 (engelsk)Inngår i: Proceedings of 2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W), Los Alamitos, 2020Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

One of the major challenges of automated drivingsystems (ADS) is showing that they drive safely. Key to ensuringsafety is eliciting a complete set of top-level safety requirements(safety goals). This is typically done with an activity called hazardanalysis and risk assessment (HARA). In this paper we argue thatthe HARA of ISO 26262:2018 is not directly suitable for an ADS,both because the number of relevant operational situations maybe vast, and because the ability of the ADS to make decisionsin order to reduce risks will affect the analysis of exposure andhazards. Instead we propose a tailoring using a quantitative risknorm (QRN) with consequence classes, where each class has alimit for the frequency within which the consequences may occur.Incident types are then defined and assigned to the consequenceclasses; the requirements prescribing the limits of these incidenttypes are used as safety goals to fulfil in the implementation.The main benefits of the QRN approach are the ability to showcompleteness of safety goals, and make sure that the safetystrategy is not limited by safety goals which are not formulatedin a way suitable for an ADS.

sted, utgiver, år, opplag, sider
Los Alamitos: , 2020
Emneord
ADS, automated driving, hazard analysis, HARA, functional safety, ISO 26262, risk norm
HSV kategori
Identifikatorer
urn:nbn:se:ri:diva-46354 (URN)10.1109/DSN-W50199.2020.00026 (DOI)978-1-7281-7263-7 (ISBN)
Konferanse
6th International Workshop on Safety and Security of Intelligent Vehicles (SSIV 2020)
Prosjekter
ESPLANADE
Forskningsfinansiär
Vinnova, 2016-04268
Tilgjengelig fra: 2020-08-17 Laget: 2020-08-17 Sist oppdatert: 2024-04-11bibliografisk kontrollert
Gyllenhammar, M., Johansson, R., Warg, F., Chen, D., Heyn, H.-M., Sanfridson, M., . . . Ursing, S. (2020). Towards an Operational Design Domain That Supports the Safety Argumentation of an Automated Driving System. In: 10th European Congress on Embedded Real Time Systems (ERTS 2020): . Paper presented at 10th European Congress on Embedded Real Time Systems (ERTS 2020). Toulouse, France
Åpne denne publikasjonen i ny fane eller vindu >>Towards an Operational Design Domain That Supports the Safety Argumentation of an Automated Driving System
Vise andre…
2020 (engelsk)Inngår i: 10th European Congress on Embedded Real Time Systems (ERTS 2020), Toulouse, France, 2020Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

One of the biggest challenges for self-driving road vehicles is how to argue that their safety cases are complete.The operational design domain (ODD) of the automated driving system (ADS) can be used to restrict where the ADS is valid and thus confine the scope of the safety case as well as the verification. To complete the safety case there is a need to ensure that the ADS will not exit its ODD. We present four generic strategies to ensure this. Use cases (UCs) provide a convenient way providing such a strategy for a collection of operating conditions (OCs) and furth erensures that the ODD allows for operation within the real world. A framework to categorise the OCs of a UC is presented and it is suggested that the ODD is written with this structure in mind to facilitate mapping towards potential UCs. The ODD defines the functional boundary of the system and modelling it with this structure makes it modular and generalisable across different potential UCs. Further, using the ODD to connect the ADS to the UC enables the continuous delivery of the ADS feature. Two examples of dimensions of the ODD are given and a strategy to avoid an ODD exit is proposed in the respective case.

sted, utgiver, år, opplag, sider
Toulouse, France: , 2020
Emneord
ADS, automated driving system, functional safety, ODD, operational design domain
HSV kategori
Identifikatorer
urn:nbn:se:ri:diva-43696 (URN)
Konferanse
10th European Congress on Embedded Real Time Systems (ERTS 2020)
Prosjekter
ESPLANADE
Forskningsfinansiär
Vinnova, 2016-04268
Tilgjengelig fra: 2020-02-01 Laget: 2020-02-01 Sist oppdatert: 2024-04-11bibliografisk kontrollert
Organisasjoner
Identifikatorer
ORCID-id: ORCID iD iconorcid.org/0000-0002-1007-6848
v. 2.41.0