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Journal Article

On-Board Particulate Filter Failure Prevention and Failure Diagnostics Using Radio Frequency Sensing

2017-03-28
2017-01-0950
The increasing use of diesel and gasoline particulate filters requires advanced on-board diagnostics (OBD) to prevent and detect filter failures and malfunctions. Early detection of upstream (engine-out) malfunctions is paramount to preventing irreversible damage to downstream aftertreatment system components. Such early detection can mitigate the failure of the particulate filter resulting in the escape of emissions exceeding permissible limits and extend the component life. However, despite best efforts at early detection and filter failure prevention, the OBD system must also be able to detect filter failures when they occur. In this study, radio frequency (RF) sensors were used to directly monitor the particulate filter state of health for both gasoline particulate filter (GPF) and diesel particulate filter (DPF) applications.
Journal Article

Ash Accumulation and Impact on Sintered Metal Fiber Diesel Particulate Filters

2015-04-14
2015-01-1012
While metal fiber filters have successfully shown a high degree of particle retention functionality for various sizes of diesel engines with a low pressure drop and a relatively high filtration efficiency, little is known about the effects of lubricant-derived ash on the fiber filter systems. Sintered metal fiber filters (SMF-DPF), when used downstream from a diesel engine, effectively trap and oxidize diesel particulate matter via an electrically heated regeneration process where a specific voltage and current are applied to the sintered alloy fibers. In this manner the filter media essentially acts as a resistive heater to generate temperatures high enough to oxidize the carbonaceous particulate matter, which is typically in excess of 600°C.
Technical Paper

Continuous Particulate Filter State of Health Monitoring Using Radio Frequency Sensing

2018-04-03
2018-01-1260
Reliable means for on-board detection of particulate filter failures or malfunctions are needed to meet diagnostics (OBD) requirements. Detecting these failures, which result in tailpipe particulate matter (PM) emissions exceeding the OBD limit, over all operating conditions is challenging. Current approaches employ differential pressure sensors and downstream PM sensors, in combination with particulate filter and engine-out soot models. These conventional monitors typically operate over narrowly-defined time windows and do not provide a direct measure of the filter’s state of health. In contrast, radio frequency (RF) sensors, which transmit a wireless signal through the filter substrate provide a direct means for interrogating the condition of the filter itself.
Technical Paper

Direct Measurement of Aftertreatment System Stored Water Levels for Improved Dew Point Management Using Radio Frequency Sensing

2019-04-02
2019-01-0739
Reducing cold-start emissions to meet increasingly stringent emissions limits requires fast activation of exhaust system sensors and aftertreatment control strategies. One factor delaying the activation time of current exhaust sensors, such as NOx and particulate matter (PM) sensors, is the need to protect these sensors from water present in the exhaust system. Exposure of the ceramic sensing element to water droplets can lead to thermal shock and failure of the sensor. In order to prevent such failures, various algorithms are employed to estimate the dew point of the exhaust gas and determine when the exhaust system is sufficiently dry to enable safe sensor operation. In contrast to these indirect, model-based approaches, this study utilized radio frequency (RF) sensors typically applied to monitor soot loading levels in diesel and gasoline particulate filters, to provide a direct measurement of stored water levels on the ceramic filter elements themselves.
Technical Paper

Modeling Study of Metal Fiber Diesel Particulate Filter Performance

2015-04-14
2015-01-1047
Sintered metal fiber (SMF) diesel particulate filters (DPF) has more than one order of magnitude lower pressure drop compared to a granular or reaction-born DPF of the same (clean) filtration efficiency. To better understand the filtration process and optimize the filter performance, metal fiber filter models are developed in this study. The major previous theoretical models for clean fibrous filter are summarized and compared with experimental data. Furthermore, a metal fiber DPF soot loading model, using similar concept developed in high efficiency particulate air (HEPA) filter modeling, is built to simulate filter soot loading performance. Compared with experimental results, the soot loading model has relatively good predictions of filter pressure drop and filtration efficiency.
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