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Bayesian Filtering and Smoothing to Measure Damper Characteristics
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.).
2014 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Bayesisk filtrering och glättning för mätning av stötdämparkaraktäristik (Swedish)
Abstract [en]

During the development of high performance damper products for vehicle applications, it is essential to measure the dampers’ characteristics to ensure their performance. Some of the measurements are performed in dynamometers. The dynamometer actuates the damper with a predefined position signal and measures the actual position and the resulting force. These measurements suffer from noise; the problem is especially bad if the signals are studied with respect to velocity. This is due to that the velocity is not directly measurable; it must be calculated from position by differentiation, which amplifies the noise. The purpose of this work was to improve these measurements by doing acomparison of different Bayesian filters and smoothers. The comparison included the Kalman filter, the extended Kalman filter, the unscented Kalman filter, the Rauch-Tung-Striebel smoother, the extended Rauch-Tung-Striebel smoother and the unscented Rauch-Tung-Striebel smoother. The smoothers are only applicable in offline applications, while the filters could be used in real time. The filters reduced the noise in the position signal and greatly reduced the noise in the velocity signal. The smoothers showed the same behaviors as the filters, but with much less noise. Only small improvements were visible in the force signal.

Abstract [sv]

Under utvecklingen av högpesterande dämparprodukter för fordonstillämpningar är det ett måste att mäta dämparnas karakteristik för att säkerställa deras prestanda. Vissa av mätningarna görs i dynamometrar. Dynamometern aktuerar dämparen med en fördefinierad positionssignal och mäter den faktiska positionen samt den resulterande kraften. Dessa mätningar påverkas av brus, problemet är extra tydligt om signalerna studeras med avseende på hastighet. Detta beror på att hastigheten inte är direkt mätbar, utan måste räknas ut genom derivering, vilken förstärker bruset. Syftet med detta arbete var att förbättra dessa mätningar genom att göra en jämförelse mellan olika Bayesiska filter och glättare. I jämförelsen ingick Kalmanfiltret, det utökade Kalmanfiltret, det oparfymerade Kalmanfiltret, Rauch-Tung-Stribel glättaren, den utökade Rauch-Tung-Striebelglättaren och den oparfymerade Rauch-Tung-Stribelglättaren. Glättarna kan endast användas offline, medan filternakan användas i realtid. Filterna minskade bruset i positionssignalen och minskade bruset avsevärt i hastighetssignalen. Glättarna uppvisade samma beteende som filterna, men med mycket mindre brus. Endast små förbättringar sågs i kraftsignalen.

Place, publisher, year, edition, pages
2014. , 58 p.
Series
MMK 2014:57 MDA 488
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-202293OAI: oai:DiVA.org:kth-202293DiVA: diva2:1075512
External cooperation
Öhlins Racing AB
Supervisors
Examiners
Available from: 2017-02-20 Created: 2017-02-20 Last updated: 2017-02-20Bibliographically approved

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