Evaluation of algorithms for temperature estimation in a crankcase

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandForschungBegutachtung

Abstract

Ongoing research in emission reduction requires accurate load detection for combustion engines with a limited number of sensors. Therefore, fast estimation of load temperature is essential. Temperature measurements are influenced by the thermal properties of the sensor itself as well as its position and mounting method. In this paper, the transient thermal behavior of the engine's crankcase and the temperature sensor for load detection is modeled as a low-pass transfer function. The unknown parameters of the transfer function are identified from experimental measurements. Maximum likelihood estimation and Kalman filtering are used to estimate the original temperature from disturbed measurements. Estimator performance is evaluated via simulations of randomized test scenarios in a Monte Carlo fashion. Influences of the model errors, the measurement noise and the estimation window-time are investigated.

Originalspracheenglisch
TitelI2MTC 2018 - 2018 IEEE International Instrumentation and Measurement Technology Conference
UntertitelDiscovering New Horizons in Instrumentation and Measurement, Proceedings
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers
Seiten1-6
Seitenumfang6
ISBN (elektronisch)9781538622223
DOIs
PublikationsstatusVeröffentlicht - 10 Jul 2018
Veranstaltung2018 IEEE International Instrumentation and Measurement Technology Conference - Houston, USA / Vereinigte Staaten
Dauer: 14 Mai 201817 Mai 2018

Konferenz

Konferenz2018 IEEE International Instrumentation and Measurement Technology Conference
KurztitelI2MTC
LandUSA / Vereinigte Staaten
OrtHouston
Zeitraum14/05/1817/05/18

Fingerprint

Crankcases
transfer functions
Transfer functions
engines
evaluation
Engines
Maximum likelihood estimation
sensors
Sensors
temperature sensors
Temperature sensors
mounting
noise measurement
Mountings
estimators
Temperature measurement
Temperature
temperature
temperature measurement
Thermodynamic properties

Schlagwörter

    ASJC Scopus subject areas

    • !!Safety, Risk, Reliability and Quality
    • !!Instrumentation

    Dies zitieren

    Rath, M., Piecha, P., & Neumayer, M. (2018). Evaluation of algorithms for temperature estimation in a crankcase. in I2MTC 2018 - 2018 IEEE International Instrumentation and Measurement Technology Conference: Discovering New Horizons in Instrumentation and Measurement, Proceedings (S. 1-6). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/I2MTC.2018.8409663

    Evaluation of algorithms for temperature estimation in a crankcase. / Rath, Matthias; Piecha, Pascal; Neumayer, Markus.

    I2MTC 2018 - 2018 IEEE International Instrumentation and Measurement Technology Conference: Discovering New Horizons in Instrumentation and Measurement, Proceedings. Institute of Electrical and Electronics Engineers, 2018. S. 1-6.

    Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandForschungBegutachtung

    Rath, M, Piecha, P & Neumayer, M 2018, Evaluation of algorithms for temperature estimation in a crankcase. in I2MTC 2018 - 2018 IEEE International Instrumentation and Measurement Technology Conference: Discovering New Horizons in Instrumentation and Measurement, Proceedings. Institute of Electrical and Electronics Engineers, S. 1-6, Houston, USA / Vereinigte Staaten, 14/05/18. https://doi.org/10.1109/I2MTC.2018.8409663
    Rath M, Piecha P, Neumayer M. Evaluation of algorithms for temperature estimation in a crankcase. in I2MTC 2018 - 2018 IEEE International Instrumentation and Measurement Technology Conference: Discovering New Horizons in Instrumentation and Measurement, Proceedings. Institute of Electrical and Electronics Engineers. 2018. S. 1-6 https://doi.org/10.1109/I2MTC.2018.8409663
    Rath, Matthias ; Piecha, Pascal ; Neumayer, Markus. / Evaluation of algorithms for temperature estimation in a crankcase. I2MTC 2018 - 2018 IEEE International Instrumentation and Measurement Technology Conference: Discovering New Horizons in Instrumentation and Measurement, Proceedings. Institute of Electrical and Electronics Engineers, 2018. S. 1-6
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    abstract = "Ongoing research in emission reduction requires accurate load detection for combustion engines with a limited number of sensors. Therefore, fast estimation of load temperature is essential. Temperature measurements are influenced by the thermal properties of the sensor itself as well as its position and mounting method. In this paper, the transient thermal behavior of the engine's crankcase and the temperature sensor for load detection is modeled as a low-pass transfer function. The unknown parameters of the transfer function are identified from experimental measurements. Maximum likelihood estimation and Kalman filtering are used to estimate the original temperature from disturbed measurements. Estimator performance is evaluated via simulations of randomized test scenarios in a Monte Carlo fashion. Influences of the model errors, the measurement noise and the estimation window-time are investigated.",
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