Modeling of the signal of a resistive soot sensor, influence of the soot nature and of the polarization voltage

Abstract

Resistive soot sensors capable of measuring the mass concentration of particles in an exhaust pipe have been developed in a previous work. In particular, it has been shown that these sensors have an optimal sensitivity for a certain polarization voltage depending on the nature of the particles. This work shows that this effect can be explained by an equilibrium between the creation of soot bridges between the two collecting electrodes and their destruction initiated by Joule effect due to the polarization voltage. Based on this assumption, a model is proposed to predict the load curve (response versus time) of the sensor. In addition, the high frequency sampling of the sensor response has revealed some jumps of the sensor response (electrical conductance), which are exploited through a statistical approach to obtain additional information on the nature of the collected particles.

Impedance Spectroscopy for Enhanced Data Collection of Conductometric Soot Sensors

“…The simple equivalent circuit model considered for modeling is a parallel resistor and capacitor, where the resistor is a lumped element representing the distributed resistivity between the electrodes, while the parallel capacitor is a lumped element representing the distributed capacitance between the electrodes. It should be noted that models based on quantized, kinetic descriptions of dendrite growth, such as those in [15] and [16] are available for predicting the dynamic behavior of resistive PM sensors. Nevertheless, the simple RC-section is chosen here, because it allows a description of the sensor performance in electrical parameters.…”

“…There have been reports on the effect of electrophoresis in an IDE when combined with capacitive readout [8]. Moreover, when Joule heating of the dendrites themselves is considered, the voltage bias on an IDE structure should be limited to ensure optimal soot response time [9]. The disadvantage of this implementation is the long response time (dead time) until a conducting path is formed and a detectable current signal, that indicates a DPF leak, becomes available.…”

Optimization of soot deposition by high-temperature prepolarization of a resistive particulate matter sensor

“…The state-of-theart technology to reduce PM emissions in automotive exhaust aftertreatments includes ceramic wall flow diesel particulate matter filters (DPFs) which need to be regenerated when the PM load reaches a certain level. Two pressure sensors mounted up-and downstream from the DPFs monitor the differential pressure, which is used in combination with the engine specific emission model to predict the filter load (Guan et al, 2015). To ensure onboard diagnosis (OBD) of the DPFs, a PM sensor is applied downstream from the DPFs to detect soot particles passing through the filter in case of a malfunction (Bargende et al, 2016;Ochs et al, 2010).…”

Development of algorithms for estimation of particle emissions using soot sensor for on-board diagnostic systems

“…Hagen and Müller stated that electrophoresis is the main drive of particle deposition in the case of their examined conductometric soot sensor (Hagen et al, 2014 Operation of the soot bridges between the electrodes (Teike et al, 2012). To reduce the response of the sensor, increased electrophoresis via high polarisation voltage was tested, but this approach is limited by internally caused thermophoresis or Joule effect (Hagen et al, 2018;Grondin et al, 2019). Also, to the same aim, Bartscherer and Moos used an additional conductive cover layer (Bartscherer and Moos, 2013).…”

“…For example, electrophoresis is induced by a polarisation voltage applied between the electrodes. High voltage, though, leads to local heating of the element (Joule effect), which can oxidise the accumulated soot (Grondin et al, 2019).…”