Parameter Determination of Dynamic Sensor Model with Particle Swarm Optimization Technique

Author

Wang, Xiaodong

Author_Institution

Dept. of Electron. Eng., Zhejiang Normal Univ., Jinhua, China

Volume

1

fYear

2009

fDate

11-12 April 2009

Firstpage

43

Lastpage

46

Abstract

An accurate mathematical model is a useful tool for analysis and design of sensor systems. In this paper, a novel approach based on particle swarm optimization (PSO) is applied to determine the parameters of dynamic sensor model. A hot-film mass airflow (MAF) sensor, which is used to measure the intake mass airflow in the engine systems of automobile, has been used as a simulation example for demonstration. The results indicate that the PSO is an effective technique for determining the parameters of dynamic sensor models.

Keywords

automotive components; engines; flow measurement; flow sensors; parameter estimation; particle swarm optimisation; PSO; automobile engine system; dynamic sensor model; hot-film mass airflow sensor; intake mass airflow measurement; parameter determination; particle swarm optimization technique; Design automation; Mathematical model; Mechatronics; Parameter estimation; Particle measurements; Particle swarm optimization; Sensor phenomena and characterization; Sensor systems; Transfer functions; Vehicle dynamics; dynamic model; parameter identification; particle swarm optimization; sensor;

fLanguage

English

Publisher

ieee

Conference_Titel

Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on

Conference_Location

Zhangjiajie, Hunan

Print_ISBN

978-0-7695-3583-8

Type

conf

DOI

10.1109/ICMTMA.2009.298

Filename

5202909