Analytical modeling and optimization of electrostatic particle sensors for particle number detection: incorporating particle size influence

Tanja Wallner*, Markus Bainschab, Manuel Kubicka, Reinhard Klambauer, Alexander Bergmann

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Developing measurement devices and methods to track increasingly stringent emission standards, including particle number, is crucial. This paper presents a novel analytical model to describe the signal response of an electrostatic particle sensor not only to particle mass concentration, but also to the particle number concentration of in-flowing particles. The uniqueness of this model lies in its ability to calculate the signal as a function of particle diameter, enabling the determination of particle number concentration from the signal. The model considers the effects of aerosol flow, electrode voltage and temperature, and can be used for the optimization of the sensor geometry parameters, length, width, and electrode gap. The model was designed to optimize the sensor’s geometry and signal retrieval as well as the optimization of the electric field between the electrodes. Comparative analysis was conducted between the proposed model and a model from the literature as well as experimental data from literature and experimental data collected in this paper.

Original languageEnglish
Article number055112
JournalMeasurement Science and Technology
Volume35
Issue number5
DOIs
Publication statusPublished - May 2024

Keywords

  • analytic model for sensor optimization and signal retrieval
  • dendrite formation
  • electrostatic particle sensor
  • exhaust particles

ASJC Scopus subject areas

  • Instrumentation
  • Engineering (miscellaneous)
  • Applied Mathematics

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