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Radio frequency (RF)-based sensors provide a direct measure of the particulate filter loading state. In contrast to particulate matter (PM) sensors, which monitor the concentration of PM in the exhaust gas stream for on-board diagnostics purposes, RF sensors have historically been applied to monitor and control the particulate filter regeneration process. This work developed an RF-based particulate filter control system utilizing both conventional and fast response RF sensors, and evaluated the feasibility of applying fast-response RF sensors to provide a real-time measurement of engine-out PM emissions. Testing with a light-duty diesel engine equipped with fast response RF sensors investigated the potential to utilize the particulate filter itself as an engine-out soot sensor.

Diesel Particulate Filters (DPF) are a key component in many on- and off-road aftertreatment systems to meet increasingly stringent particle emissions limits. Efficient thermal management and regeneration control is critical for reliable and cost-effective operation of the combined engine and aftertreatment system. Conventional DPF control systems predominantly rely on a combination of filter pressure drop measurements and predictive models to indirectly estimate the soot loading state of the filter. Over time, the build-up of incombustible ash, primarily derived from metal-containing lubricant additives, accumulates in the filter to levels far exceeding the DPF's soot storage limit. The combined effects of soot and ash build-up dynamically impact the filter's pressure drop response, service life, and fuel consumption, and must be accurately accounted for in order to optimize engine and aftertreatment system performance.

Direct Injection (DI) fueled gasoline engines provide higher efficiency than port fueled injected (PFI) engines. However, emission of small particulates is greatly increased when DI is used. Particulate mass emission is increased by more than a factor of 10 and particulate number is increased by a factor of 10-100 relative to PFI engines leading to health concerns and to implementation and consideration of new regulations. Optimized combinations of PFI and DI can greatly reduce DI-generated particulate emissions without compromising efficiency and performance. A DI enhanced PFI mode of engine operation is employed where PFI is the dominant means in dual-injection fueling over a drive cycle, and the fuel fraction that is directly injected is reduced/minimized while still preventing knock at high loads. Further reduction can be obtained by optimal use of spark retard.

The increasing use of gasoline direct injection (GDI) engines coupled with the implementation of new particulate matter (PM) and particle number (PN) emissions regulations requires new emissions control strategies. Gasoline particulate filters (GPFs) present one approach to reduce particle emissions. Although primarily composed of combustible material which may be removed through oxidation, particle also contains incombustible components or ash. Over the service life of the filter the accumulation of ash causes an increase in exhaust backpressure, and limits the useful life of the GPF. This study utilized an accelerated aging system to generate elevated ash levels by injecting lubricant oil with the gasoline fuel into a burner system. GPFs were aged to a series of levels representing filter life up to 150,000 miles (240,000 km). The impact of ash on the filter pressure drop and on its sensitivity to soot accumulation was investigated at specific ash levels.

Accurate knowledge of diesel particulate filter (DPF) particulate matter (PM) loading is critical for robust and efficient operation of the combined engine-exhaust aftertreatment system. Furthermore, upcoming on-board diagnostics regulations require on-board technologies to evaluate the status of the DPF. This work describes the application of radio frequency (RF) - based sensing techniques to accurately measure DPF particulate matter levels. A 1.9L GM turbo diesel engine and a DPF with an RF-sensor were studied. Direct comparisons between the RF measurement and conventional pressure-based methods were made. Further analysis of the particulate matter loading rates was obtained with a mass-based total PM emission measurement instrument (TEOM) and DPF gravimetric measurements.

Internal combustion engines for plug-in hybrid heavy duty trucks, especially long haul trucks, could play an important role in facilitating use of battery power. Power from a low carbon electricity source could thereby be employed without an unattractive vehicle cost increase or range limitation. The ideal engine should be powered by a widely available affordable liquid fuel, should minimize air pollutant emissions, and should provide lower greenhouse gas emissions. Diesel engines could fall short in meeting these objectives, especially because of high emissions. In this paper we analyze the potential for a flex fuel gasoline-alcohol engine approach for a series hybrid powertrain. In this approach the engine would provide comparable (or possibly greater) efficiency than a diesel engine while also providing 90 around lower NOx emissions than present cleanest diesel engine vehicles. Ethanol or methanol would be employed to increase knock resistance.

Long-haul and other heavy-duty trucks, presently almost entirely powered by diesel fuel, face challenges meeting worldwide needs for greatly reducing nitrogen oxide (NOx) emissions. Dual-fuel gasoline-alcohol engines could potentially provide a means to cost-effectively meet this need at large scale in the relatively near term. They could also provide reductions in greenhouse gas emissions. These spark ignition (SI) flexible fuel engines can provide operation over a wide fuel range from mainly gasoline use to 100% alcohol use. The alcohol can be ethanol or methanol. Use of stoichiometric operation and a three-way catalytic converter can reduce NOx by around 90% relative to emissions from diesel engines with state of the art exhaust treatment.

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.

The Cu-zeolite (CuZ) SCR catalyst enables higher NOx conversion efficiency in part because it can store a significant amount of NH3. “NH3 storage control”, where diesel exhaust fluid (DEF) is dosed in accord with a target NH3 loading, is widely used with CuZ catalysts to achieve very high efficiency. The NH3 loading actually achieved on the catalyst is currently estimated through a stoichiometric calculation. With future high-capacity CuZ catalyst designs, it is likely that the accuracy of this NH3 loading estimate will become limiting for NOx conversion efficiency. Therefore, a direct measurement of NH3 loading is needed; RF sensing enables this. Relative to RF sensing of soot in a DPF (which is in commercial production), RF sensing of NH3 adsorbed on CuZ is more challenging. Therefore, more attention must be paid to the “microwave resonance cavity” created within the SCR assembly. The objective of this study was to develop design guidelines to enable and enhance RF sensing.

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.

Although designed for the purpose of reducing engine-out Particulate Matter (PM) emissions to meet or exceed mandated emissions regulations, the particulate filter also incurs a fuel economy penalty. This fuel penalty is due to the increased exhaust flow restriction attributed to the PM accumulated in the filter, in addition to fuel consumed for active regeneration. Unlike the soot which may be oxidized through the regeneration process, incombustible material or ash continues to build-up in the filter following each regeneration event. Currently pressure- and model-based controls are used to provide an indirect estimate of the loading state of the particulate filter, in order to manage the filter operation and determine when to regenerate the filter. The challenges associated with pressure- and model-based particulate filter control over real-world operating conditions are well-known.