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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.

Efficient aftertreatment management requires accurate sensing of both particulate filter soot and ash levels for optimized feedback control. Currently a combination of pressure drop measurements and predictive models are used to indirectly estimate the loading state of the filter. Accurate determination of filter soot loading levels is challenging under certain operating conditions, particularly following partial regeneration events and at low flow rate (idle) conditions. This work applied radio frequency (RF)-based sensors to provide a direct measure of the particulate filter soot levels in situ. Direct measurements of the filter loading state enable advanced feedback controls to optimize the combined engine and aftertreatment system for improved DPF management. This study instrumented several cordierite and aluminum titanate diesel particulate filters with RF sensors. The systems were tested on a range of light- and heavy-duty applications, which included on- and off-road engines.

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.

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.

Increased demand for highly fuel efficient propulsion systems drives the engine development community to develop advanced technologies allowing improving the overall thermal efficiency while maintaining low emission levels. In addition to improving the thermal efficiencies of the internal combustion engine itself the developments of fuels that allow improved combustion as well as lower the emissions footprint has intensified recently. This paper will describe the effects of five different fuel types with significantly differing fuel properties on a state-of-the-art light-duty HSDI diesel engine. The fuels cetane number ranges between 26 and 76. These fuels feature significantly differing boiling characteristics as well as heating values. The fuel selection also contains one pure biodiesel (SME - Soy Methyl Ester). This study was conducted in part load and full load operating points using a state of the art HSDI diesel engine.

Due to raising interest in diesel powered passenger cars in the U.S. in combination with a desire to reduce dependency on imported petroleum, there has been increased attention to the operation of diesel vehicles on fuels blended with biodiesel. One of several factors to be considered when operating a vehicle on biodiesel blends is understanding the impact and performance of the fuel on the emission control system. This paper documents the impact of the biodiesel blends on engine-out emissions as well as the overall system performance in terms of emission control system calibration and the overall system efficiency. The testing platform is a light-duty HSDI diesel engine with a Euro 4 base calibration in a 1700 kg sedan vehicle. It employs 2nd generation common-rail injection system with peak pressure of 1600 bar as well as cooled high-pressure EGR. The study includes 3 different fuels (U.S.

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.

Beginning in 2010, implementation of on-board diagnostics (OBD) is mandatory for all the heavy-duty engine applications in the United States. The task of developing OBD strategies and calibrating them is a challenging one. The process involves a strong interdependency on base engine emissions, controls and regulations. On top of that the strategies developed as a result of the regulatory requirements need to go through a stringent and time-intensive process of software implementation and integration. The recent increasing demands to minimize the development process have been pushing the envelope on the methodologies used in developing the strategies and the calibration for robust monitoring. The goal of this paper is to provide a concise overview of a process utilized to help the development, testing and calibration of the OBD strategies on a 2010 model year heavy-duty diesel engine.

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.

Raising interest in Diesel powered passenger cars in the United States in combination with the government mandated policy to reduce dependency of foreign oil, leads to the desire of operating Diesel vehicles with Biodiesel fuel blends. There is only limited information related to the impact of Biodiesel fuels on the performance of advanced emission control systems. In this project the implementation of a NOx storage and a SCR emission control system and the development for optimal performance are evaluated. The main focus remains on the discussion of the differences between the fuels which is done for the development as well as useful life aged components. From emission control standpoint only marginal effects could be observed as a result of the Biodiesel operation. The NOx storage catalyst results showed lower tailpipe emissions which were attributed to the lower exhaust temperature profile during the test cycle. The SCR catalyst tailpipe results were fuel neutral.

Accelerated adoption of electric propulsion system in mobility industry has stressed the time and iterations of product development cycle which was traditionally known to go over multiple iterations and phases. Current market demands a timely introduction of compelling products that brings high value to end user. Further, a growing emphasis over reducing mineral content using sustainable options and process, adds further complexity to multi-objective-optimization of electric drive systems. At BorgWarner our engineers use Digital-Twins, physics-based models which closely represent BorgWarner products in greater dept (physics) thus allowing an improved assessment of product design (components and systems) to target application at very early stage in product development. The spring success with Digital-Twin, BorgWarner furthered enhanced the model through introducing Artificial Intelligent (AI) and Machine Learning (ML) technologies in both modelling and virtual sensing.

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.