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Positionering av tågvagn med hjälp av ett Kalmanfilter
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics and Logistics.
2019 (Swedish)Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesisAlternative title
Railcar positioning using a Kalman filter (English)
Abstract [sv]

Positionering av tågvagnar är en viktig del av järnvägen. Dagligen används Sveriges järnvägar av 1000-tals tåg, vilket medför en säkerhetsrisk om inte det finns teknik för att upptäcka tågvagnstapp.

Projektet undersökte om det med hjälp av ett Kalmanfilter på en Raspberry Pi med variablerna latitud och longitud kunde positionera en tågvagn i realtid. Projektet undersökte även om Kalmanfiltret som programmerades kunde ersätta en GPS där täckning inte fanns i området.

En prototyp framställdes och utvärderades genom att ett Kalmanfilter programmerades och implementerades på en enkortsdator tillsammans med en GPS-modul.

Simuleringar av flera värden gjordes för att säkerställa de värden som uppkom. Prototypen visar att metoden fungerar inom den felmarginal järnvägen kräver för ett säkert system. Resultatet visar en avvikelse av den positionen som eftersöktes med Kalmanfiltret. Koordinaterna för latitud hade en differens med 0,9 m jämfört med det Kalmanfilter som programmerades. Longitud hade också en differens men med 0,001 m jämfört mot de värdena som GPS-modulen genererade.

Abstract [en]

Positioning of railcars is an important part of the railway industry. In Sweden there are 1000 of trains on the railway which leads to a security risk if a railcar is lost.

This project examined if it were possible to position a railcar in real time using Kalman filter on a raspberry pi with the variable’s latitude and longitude. The project also examined if the Kalman filter could replace an GPS were there was no coverage in that area.

A prototype was produced and evaluated with a Kalman filter programmed and implemented on it together with a GPS-module. Simulations of several values was made to secure the values that the algorithm did show.

The prototype shows that the method in this project is within the error margin that the railway demands for a safe system. The results show a deviation of the position that was sought after with the Kalman filter. The coordinates for latitude had a difference of 0,9 m compared to the Kalman filter that was programmed. Longitude also had a difference but with 0,001 m compared to the values that the GPS-module generated.

Place, publisher, year, edition, pages
2019. , p. 40
Series
TRITA-CBH-GRU ; 2019:040
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-252755OAI: oai:DiVA.org:kth-252755DiVA, id: diva2:1322445
Subject / course
Electrical Engineering
Educational program
Bachelor of Science in Engineering - Electrical Engineering
Supervisors
Examiners
Available from: 2019-06-11 Created: 2019-06-10 Last updated: 2019-06-11Bibliographically approved

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