Evaluation of algorithms for temperature estimation in a crankcase

Matthias Rath; Pascal Piecha; Markus Neumayer

doi:10.1109/I2MTC.2018.8409663

Evaluation of algorithms for temperature estimation in a crankcase

Matthias Rath, Pascal Piecha, Markus Neumayer

Institute of Thermodynamics and Sustainable Propulsion Systems (3130)

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

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.

Original language	English
Title of host publication	I2MTC 2018 - 2018 IEEE International Instrumentation and Measurement Technology Conference
Subtitle of host publication	Discovering New Horizons in Instrumentation and Measurement, Proceedings
Publisher	Institute of Electrical and Electronics Engineers
Pages	1-6
Number of pages	6
ISBN (Electronic)	9781538622223
DOIs	https://doi.org/10.1109/I2MTC.2018.8409663
Publication status	Published - 10 Jul 2018
Event	2018 IEEE International Instrumentation and Measurement Technology Conference - Houston, United States Duration: 14 May 2018 → 17 May 2018

Conference

Conference	2018 IEEE International Instrumentation and Measurement Technology Conference
Abbreviated title	I2MTC
Country/Territory	United States
City	Houston
Period	14/05/18 → 17/05/18

Keywords

estimation
temperature

ASJC Scopus subject areas

Safety, Risk, Reliability and Quality
Instrumentation

Access to Document

10.1109/I2MTC.2018.8409663

Cite this

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 (pp. 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. p. 1-6.

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

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, pp. 1-6, 2018 IEEE International Instrumentation and Measurement Technology Conference, Houston, United States, 14/05/18. https://doi.org/10.1109/I2MTC.2018.8409663

@inproceedings{fb8d3acb3a1146419c5514c44a3fd4c9,

title = "Evaluation of algorithms for temperature estimation in a crankcase",

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.",

keywords = "estimation, temperature",

author = "Matthias Rath and Pascal Piecha and Markus Neumayer",

year = "2018",

month = jul,

day = "10",

doi = "10.1109/I2MTC.2018.8409663",

language = "English",

pages = "1--6",

booktitle = "I2MTC 2018 - 2018 IEEE International Instrumentation and Measurement Technology Conference",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "2018 IEEE International Instrumentation and Measurement Technology Conference, I2MTC ; Conference date: 14-05-2018 Through 17-05-2018",

}

TY - GEN

T1 - Evaluation of algorithms for temperature estimation in a crankcase

AU - Rath, Matthias

AU - Piecha, Pascal

AU - Neumayer, Markus

PY - 2018/7/10

Y1 - 2018/7/10

N2 - 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.

AB - 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.

KW - estimation

KW - temperature

UR - http://www.scopus.com/inward/record.url?scp=85050767783&partnerID=8YFLogxK

U2 - 10.1109/I2MTC.2018.8409663

DO - 10.1109/I2MTC.2018.8409663

M3 - Conference paper

AN - SCOPUS:85050767783

SP - 1

EP - 6

BT - I2MTC 2018 - 2018 IEEE International Instrumentation and Measurement Technology Conference

PB - Institute of Electrical and Electronics Engineers

T2 - 2018 IEEE International Instrumentation and Measurement Technology Conference

Y2 - 14 May 2018 through 17 May 2018

ER -

Evaluation of algorithms for temperature estimation in a crankcase

Abstract

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this