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The resistive particulate matter sensor (PMS) is rapidly becoming ubiquitous on diesel vehicles as a means to diagnose particulate filter (DPF) leaks. By design the device provides an integrated measure of the amount of PM to which it has been exposed during a defined measurement period within a drive cycle. The state of the art resistive PMS has a large deadband before any valid output related to the accumulated PM is realized. As a result, most DPF monitors that use the PMS consider its output only as an indicator that a threshold quantity of PM has amassed rather than a real-time measure of concentration. This measurement paradigm has the unfortunate side effect that as the PM OBD threshold decreases, or the PMS is used on a vehicle with a larger exhaust volume flow, a longer measurement is required to reach the same PM sensor output. Longer PMS measurement times lead to long particulate filter monitoring durations that may reduce filter monitor completion frequency.

The pre EGR valve pressure is an important measurement for the Diesel engine air handling system. It is commonly used for the EGR flow calculation during engine transient operation. Due to the erosive exhaust gas, an EGR pressure sensor will eventually have gold corrosion resulting in drive-ability issues. Therefore, a software replacement for the EGR pressure sensor is desirable. However, when the EGR valve is on the cold side of the EGR cooler, the accuracy of the EGR pressure estimation deteriorates because of the variability of the pressure drop across the EGR cooler due to EGR cooler fouling. In this paper, an adaptive scheme is developed to improve the accuracy of pre EGR valve pressure estimation in the presence of EGR cooler fouling for diesel engines. The pressure drop across the EGR cooler is shown to be proportional to the velocity pressure of the EGR flow through the cooler.

Diesel particulate filters (DPFs) are a technology likely to be deployed to meet future stringent emission levels for heavy and light duty diesel powertrains in North America and Europe. This paper discusses experimental results in the active regeneration of DPFs. Attention is given to the system components, the information based on which regeneration is triggered, and the means to achieve a regeneration. The paper will report on successful regenerations under several extreme conditions.

A control strategy is presented to limit the rate of heat release by Diesel Particulate Filters (DPF) during regeneration reactions between oxygen and the collected soot. Heat release is managed by limiting the oxygen supplied to the DPF, which limits the rate of the regeneration reaction. Three actuators are used to control the amount of oxygen flowing in the exhaust system: an exhaust gas re-circulation (EGR) valve, an intake throttle (ITH), and a hydrocarbon injector located upstream of the DPF in the exhaust system. The EGR valve and ITH are low-bandwidth actuators that control slowly varying changes in oxygen flow, while the hydrocarbon injector is a high-bandwidth actuator that controls the corresponding fast changes in oxygen flow.

While not commonly in production today, Gasoline Particulate Filters (GPFs) are likely to see widespread deployment to meet stringent EU6.2 and China particulate number (PN) standards. In many ways the operating conditions for GPFs are orthogonal to those of their diesel counterparts, and this leads to different and interesting requirements for the control strategy. We will present some generic system architectures for exhaust systems containing a GPF and will lay out an architecture for the GPF control strategy components which include: regeneration assist feature, soot estimation algorithm, GPF protection. The regeneration assist feature uses spark retard to increase exhaust temperature. The soot estimation algorithm describes how we can estimate soot from an open loop model or from a normalized pressure metric. The GPF protection feature controls oxygen flow to limit the soot burn rate. We will show validation data of the control strategy under different operating conditions.

Over the past decade urea-based selective catalytic reduction (SCR) has become a leading aftertreatment solution to meet increasingly stringent Nitrogen oxide (NOx) emissions requirements in diesel powertrains. A common trend seen in modern SCR systems is the use of "split-brick" configurations where two SCR catalysts are placed in thermally distinct regions of the aftertreatment. One catalyst is close-coupled to the engine for fast light-off and another catalyst is positioned under-floor to improve performance at high space velocities. Typically, a single injector is located upstream of the first catalyst to provide the reductant necessary for efficient NOx reduction. This paper explores the potential benefit, in terms of improved NOx reduction, control of NH3 slip or reduced reductant consumption, of having independently actuated injectors in front of each catalyst.

Many excellent papers have been written about the subject of estimating engine-out NOx on diesel engines based on real-time available data. The claimed accuracy of these models is typically around 6-10% on validation data sets with known inputs. This reported accuracy typically ignores input uncertainties, thus arriving at an optimistic estimate of the model accuracy in a real-time application. In our paper we analyze the effect of input uncertainty on the accuracy of engine-out NOx estimates via a numerical Monte Carlo simulation and show that this effect can be significant. Even though our model is based on an in-cylinder pressure sensor, this sensor is limited in its capability to reduce the effect of other measured inputs on the model.

To meet stringent 2010 NOx emissions, many manufacturers are expected to deploy urea selective catalytic reduction systems. Indications from ARB are that a threshold monitor must be developed to monitor their performance. The most capable monitoring technology at this time relies on NOx sensors. This paper assesses the capability of the NOx sensor as an SCR monitoring device. To this end, the NOx sensor must be able to distinguish between a marginal and a threshold catalyst with enough separation to allow for variability. We present the noise factors associated with the NOx conversion of the SCR system, and analyze what NOx sensor accuracy we need to preserve separation in the face of those noise factors. It is shown that a 1.75 threshold monitor is not feasible with current NOx sensor technology. We analyze the benefit of a partial volume monitor, and show there is no advantage unless the slope error of the NOx sensor is drastically reduced from current levels.

Modern diesel engines are frequently equipped with an exhaust gas recirculation (EGR) valve and intake throttle (ITH). The intake throttle serves to depress intake manifold pressure, create a greater pressure differential across the EGR valve, and enhance the ability to flow EGR at low speed and load conditions. A conventional approach to controlling the intake throttle is to schedule its desired position as a function of engine speed and load. In this paper we present a coordinated approach to the control of EGR valve and intake throttle.

Regulatory authorities are actively revising and updating the rules for on board diagnostics of diesel powertrains. Diesel oxidation catalysts are among the parts that will have to be monitored. This paper discusses some of the issues related to the feasibility of monitoring these catalysts. We concentrate on the effect of real world noise factors on the ability to distinguish marginal from threshold catalysts and demonstrate that with current sensor and catalyst technology the separation between the two is poor.

Gasoline particulate filters (GPFs) are extremely effective at reducing tailpipe emissions of particulate mass and particulate number. Especially in the European and Chinese markets, where a particulate number standard is legislated, we see gasoline particulate filters being deployed in production on gasoline direct injected engines. Due to the high temperature in gasoline exhaust, most applications are expected to be passively regenerating without the help of an active regeneration strategy. However, for the few cases where a customer drive cycle has consistently low speed over a long time frame, an active regeneration strategy may be required. This involves increasing the exhaust temperature at the GPF up to around 600 degC so that soot can be combusted. We compare two different ways of achieving these temperatures, namely spark retard and air fuel ratio modulation. The former generates heat in the engine, the latter generates heat in one or more catalysts in the exhaust system.

The availability of connectivity and autonomy enabled resources, within the automotive sector, has primarily been considered for driver assist technologies and for extending the levels of vehicle autonomy. It is not a stretch to imagine that the additional information, available from connectivity and autonomy, may also be useful in further improving powertrain functions. Critical powertrain subsystems that must operate with limited or uncertain knowledge of their environment stand to benefit from such new information sources. Unfortunately, the adoption of this new information resource has been slow within the powertrain community and has typically been limited to the obvious problem choices such as battery charge management for electric vehicles and efforts related to fuel economy benefits from adaptive/coordinated cruise control. In this paper we discuss the application of connectivity resources in the management of an aftertreatment sub-system, the Diesel Particulate Filter (DPF).

This paper analyzes the use of an ammonia sensor for feedback control in diesel exhaust systems. We build our case around the specific example of the heavy duty transient cycle, and an exhaust system with an SCR catalyst, a single urea injector and an upstream and downstream NOx sensor. A key component in our analysis is the inclusion of the tolerance of the ammonia sensor. We show that with the current understanding of the sensor tolerance, the ammonia sensor has limited benefit for controls.

Gasoline particulate filters (GPF) are used as an efficient solution to reduce particulate matter (PM) emissions on gasoline vehicles. GPFs are ceramic wall-flow filters and are normally located downstream of conventional three-way catalysts (TWC) [1]. The study in this paper is intended to evaluate the impact of drive cycle and ambient temperature on modelled GPF soot accumulation and regeneration. The test data were obtained through real road testing in Chinese cities including Nanjing, Hainan and Harbin. Five 2.0 L gasoline turbo direct-injection (GTDI) prototype vehicles from several China Stage 6 applications were employed for the road tests. The results of the testing indicated that a drive cycle with low engine speed and engine load, like a typical city road in rush hour traffic in Nanjing, had a low probability of generating high GPF temperatures (> 600 °C) and sufficient oxygen to regenerate the GPF.

This paper analyzes the potential benefit of a model based DPF leakage monitor over a conventional DPF leakage monitor that checks pressure drop after a complete regeneration. We analyze the most important noise factors involved in both approaches and demonstrate that the model based leakage monitor does not improve on the conventional leakage monitor in accuracy. It does improve on completion frequency, but at the expense of a great modeling effort.