Position Detection in Automotive Application by Adaptive Inter Symbol Interference Removal
Incremental magnetic field sensors are frequently used in automotive applications for crankshaft and camshaft position measurements. Highest possible phase accuracy and disturbance immunity (air gap and temperature variations, noise) are the primary performance requirements for such sensor systems....
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creator | Hainz, S. Ofner, E. Hammerschmidt, D. Werth, T. |
description | Incremental magnetic field sensors are frequently used in automotive applications for crankshaft and camshaft position measurements. Highest possible phase accuracy and disturbance immunity (air gap and temperature variations, noise) are the primary performance requirements for such sensor systems. An analog signal is generated from a magnetic field sensor and the position information is obtained using state of the art peak or zero crossing detection in the analogue or digital domain. While phase jitter of peak or zero crossings can be minimized by optimizing zero crossing and peak detection methods, these techniques cannot take into account variations of peak and zero crossing positions due to air gap variations. A Decision Feedback Equalizer (DFE) was adapted to remove this systematic error. For this purpose a physical model of the measurement environment (magnetic field) was derived and verified by Finite Element simulations (FEM). With simplifications the model delivered an analytical function for magnetic field calculations, which serve the adaptive algorithm for the DFE. |
doi_str_mv | 10.1109/ICSENS.2007.355818 |
format | Conference Proceeding |
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Highest possible phase accuracy and disturbance immunity (air gap and temperature variations, noise) are the primary performance requirements for such sensor systems. An analog signal is generated from a magnetic field sensor and the position information is obtained using state of the art peak or zero crossing detection in the analogue or digital domain. While phase jitter of peak or zero crossings can be minimized by optimizing zero crossing and peak detection methods, these techniques cannot take into account variations of peak and zero crossing positions due to air gap variations. A Decision Feedback Equalizer (DFE) was adapted to remove this systematic error. For this purpose a physical model of the measurement environment (magnetic field) was derived and verified by Finite Element simulations (FEM). 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Highest possible phase accuracy and disturbance immunity (air gap and temperature variations, noise) are the primary performance requirements for such sensor systems. An analog signal is generated from a magnetic field sensor and the position information is obtained using state of the art peak or zero crossing detection in the analogue or digital domain. While phase jitter of peak or zero crossings can be minimized by optimizing zero crossing and peak detection methods, these techniques cannot take into account variations of peak and zero crossing positions due to air gap variations. A Decision Feedback Equalizer (DFE) was adapted to remove this systematic error. For this purpose a physical model of the measurement environment (magnetic field) was derived and verified by Finite Element simulations (FEM). With simplifications the model delivered an analytical function for magnetic field calculations, which serve the adaptive algorithm for the DFE.</description><subject>Automotive applications</subject><subject>Camshafts</subject><subject>Decision feedback equalizers</subject><subject>Interference</subject><subject>Magnetic field measurement</subject><subject>Magnetic noise</subject><subject>Magnetic sensors</subject><subject>Phase noise</subject><subject>Position measurement</subject><subject>Temperature sensors</subject><issn>1930-0395</issn><issn>2168-9229</issn><isbn>1424403758</isbn><isbn>9781424403752</isbn><isbn>9781424403769</isbn><isbn>1424403766</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2006</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1jstKw0AUhscb2Na-gG7yAonnzGQyM8sQqwaKitWNmzJJTmAkN5Kx0Le3tLr6Lx_8_IzdIkSIYO7zbLN62UQcQEVCSo36jC2N0hjzOAahEnPOZhwTHRrOzQWb_wOpL9kMjYAQhJHXbD5N3wAcJNcz9vXWT867vgseyFN5dK4L0h_ft713OwrSYWhcaY-k2AdpZYdjn3eexmCzb4u-OYWaRupKCt6p7Xe2uWFXtW0mWv7pgn0-rj6y53D9-pRn6Tp0qKQPa6PBoCIrsLJoNJrKiqQU9vBdKgUqllVxQKpONEhBRUlVpRJCYWJC4GLB7k67joi2w-haO-63MSqtUYhfqV5XZg</recordid><startdate>200610</startdate><enddate>200610</enddate><creator>Hainz, S.</creator><creator>Ofner, E.</creator><creator>Hammerschmidt, D.</creator><creator>Werth, T.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>200610</creationdate><title>Position Detection in Automotive Application by Adaptive Inter Symbol Interference Removal</title><author>Hainz, S. ; Ofner, E. ; Hammerschmidt, D. ; Werth, T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-f980917ea31da19819da36c3a4035770745db1da7f68053ebcedd76e1394e1023</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Automotive applications</topic><topic>Camshafts</topic><topic>Decision feedback equalizers</topic><topic>Interference</topic><topic>Magnetic field measurement</topic><topic>Magnetic noise</topic><topic>Magnetic sensors</topic><topic>Phase noise</topic><topic>Position measurement</topic><topic>Temperature sensors</topic><toplevel>online_resources</toplevel><creatorcontrib>Hainz, S.</creatorcontrib><creatorcontrib>Ofner, E.</creatorcontrib><creatorcontrib>Hammerschmidt, D.</creatorcontrib><creatorcontrib>Werth, T.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Hainz, S.</au><au>Ofner, E.</au><au>Hammerschmidt, D.</au><au>Werth, T.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Position Detection in Automotive Application by Adaptive Inter Symbol Interference Removal</atitle><btitle>2006 5th IEEE Conference on Sensors</btitle><stitle>ICSENS</stitle><date>2006-10</date><risdate>2006</risdate><spage>1103</spage><epage>1106</epage><pages>1103-1106</pages><issn>1930-0395</issn><eissn>2168-9229</eissn><isbn>1424403758</isbn><isbn>9781424403752</isbn><eisbn>9781424403769</eisbn><eisbn>1424403766</eisbn><abstract>Incremental magnetic field sensors are frequently used in automotive applications for crankshaft and camshaft position measurements. Highest possible phase accuracy and disturbance immunity (air gap and temperature variations, noise) are the primary performance requirements for such sensor systems. An analog signal is generated from a magnetic field sensor and the position information is obtained using state of the art peak or zero crossing detection in the analogue or digital domain. While phase jitter of peak or zero crossings can be minimized by optimizing zero crossing and peak detection methods, these techniques cannot take into account variations of peak and zero crossing positions due to air gap variations. A Decision Feedback Equalizer (DFE) was adapted to remove this systematic error. For this purpose a physical model of the measurement environment (magnetic field) was derived and verified by Finite Element simulations (FEM). 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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Automotive applications Camshafts Decision feedback equalizers Interference Magnetic field measurement Magnetic noise Magnetic sensors Phase noise Position measurement Temperature sensors |
title | Position Detection in Automotive Application by Adaptive Inter Symbol Interference Removal |
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