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Torque Estimation Based Virtual Crank Angle Sensor
KTH, School of Electrical Engineering (EES).
2016 (English)In: SAE Technical Papers, Vol. 2016-AprilArticle in journal (Refereed) Published
Abstract [en]

In engine management systems many calculations and actuator actions are performed in the crank angle domain. Most of these actions and calculations benefit from an improved accuracy of the crank angle measurement. Improved estimation of crank angle, based on pulse signals from an induction sensor placed on the flywheel of a heavy duty CI engine is thus of great importance. To estimate the crank angle the torque balance on the crankshaft is used. This torque balance is based on Newton's second law. The net torque gives the flywheel acceleration which in turn gives engine speed and crank angle position. The described approach was studied for two crankshaft models: A rigid crankshaft approach and a lumped mass approach, the latter having the benefit of being able to capture the torsional effects of the crankshaft twisting and bending due to torques acting on it. These methods were then compared to a linear extrapolation of the engine speed, a common method to estimate crank angle today. The modelled results were compared to experimental data from 36 operating points. The results indicate that using a torque based model to predict torsion improves the accuracy of the crank angle measurement, especially for higher engine loads and in the combustion part of the engine cycle. The rigid crankshaft approach on the other hand does not give enough improvement of the accuracy compared to plain extrapolation to warrant further work.

Place, publisher, year, edition, pages
SAE International , 2016. Vol. 2016-April
Keyword [en]
Angle measurement, Crankcases, Crankshafts, Engines, Extrapolation, Flywheels, Speed, Wheels, Engine management systems, Induction sensors, Linear extrapolation, Newton's second law, Operating points, Torque balance, Torque estimation, Torsional effect
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-195396DOI: 10.4271/2016-01-1073ScopusID: 2-s2.0-84978952273OAI: oai:DiVA.org:kth-195396DiVA: diva2:1049093
Conference
SAE 2016 World Congress and Exhibition, Detroit, United States, 12 April 2016 through 14 April 2016
Note

QC 20161123

Available from: 2016-11-23 Created: 2016-11-03 Last updated: 2016-11-23Bibliographically approved

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