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The usage of the universal exhaust gas oxygen (UEGO) sensor to control the air-fuel ratio (AFR) in gasoline engines allowed to significantly improve the efficiency of the combustion process and reduce tailpipe emissions. The diagnostics of this sensor is very important to ensure proper operation and indicate the need for service when the sensor fails to accurately determine the AFR upstream of the catalyst. California air resources board (CARB) has imposed several legislations around the operation of the UEGO sensor and particularly when specific faults would cause tailpipe emissions to exceed certain limits. In this paper, the possible sensor faults are reviewed, and a non-intrusive diagnostics monitor is proposed to detect, identify and estimate the magnitude of the fault present. This paper extends the approach in [4] where technical details are emphasized and algorithm improvements are discussed.

Air Fuel Ratio (AFR) imbalance between engine cylinders remains one of the most challenging problems in powertrain systems diagnostics. California Air Resources Board(CARB) has started imposing specific requirements on automotive companies since 2011 that required the integration of on-board diagnostics (OBD) monitor for the detection and reporting of this type of powertrain malfunction. In this paper, some methodologies of AFR cylinder imbalance monitoring are investigated and a novel approach is proposed that shows reliable detection capability compared to the other methods. The proposed method requires certain conditions during deceleration fuel shutoff events to intrusively reactivate the cylinders and determine the imbalance condition. The method was evaluated on a V6 3.7L engine in an experimental Lincoln MKZ vehicle. Vehicle results are shown and discussed.

In this work, a discrete,time-based, delay-compensated, adaptive PID control algorithm for air fuel ratio control in an SI engine is presented. The controller operates using feedback from a wide-ranging Universal Exhaust Gas Oxygen (UEGO) sensor situated in the exhaust manifold. Time delay compensation is used to address the difficulties traditionally associated with the relatively long and time-varying time delay in the gas transport process and UEGO sensor response. The delay compensation is performed by computing a correction to the current control move based on the current delay and the corresponding values of the past control moves. The current delay is determined from the measured engine speed and load using a two dimensional map. In order to achieve good servo operation during target changes without compromising regulator performance a two degree of freedom controller design has been developed by adding a pre-filter to the air fuel ratio target.

Engine-Off Natural Vacuum (EONV) principles based leak detection monitors are designed to determine the presence of a small leak in the fuel tank system. It was introduced to address the ever more stringent emission requirement (currently at 0.02”) for gasoline engine equipped vehicles as proposed by the Environmental Protection Agency (EPA) and California Air Resources Board (CARB) in the United States [2, 3]. Other environmental protection agencies including the ones in EU and China will be adopting similar regulations in the near future. Due to its sensitivity to known noise factors such as the ambient temperature, barometric pressure, drive pattern and parking angle, it has been historically a lower performing monitor that is susceptible to warranty cost or even voluntary recalls. The proposed new model based monitor utilizes production pressure signal and newly instrumented temperature sensors [15].

A three-way catalytic converter (TWC) is an emissions control device, used to treat the exhaust gases in a gasoline engine. The conversion efficiency of the catalyst, however, drops with age or customer usage and needs to be monitored on-line to meet the on board diagnostics (OBD II) regulations. In this work, a non-intrusive catalyst monitor is developed to diagnose the track the remaining useful life of the catalyst based on measured in-vehicle signals. Using air mass and the air-fuel ratio (A/F) at the front (upstream) and rear (downstream) of the catalyst, the catalyst oxygen storage capacity is estimated. The catalyst capacity and operating exhaust temperature are used as an input features for developing a Support Vector Machine (SVM) algorithm based classifier to identify a threshold catalyst. In addition, the distance of the data points in hyperspace from the calibrated threshold plane is used to compute the remaining useful life left.

Traditionally, a three-way catalyst (TWC) is controlled to a set heated exhaust gas oxygen (HEGO) sensor voltage (typically placed after the monitored catalyst) that corresponds to optimal catalyst efficiency. This limits the control action, as we rely on emissions breakthrough at the HEGO sensor to infer the state of catalyst. In order to robustly meet the super ultra-low emission regulations, a more precise TWC control around the oxidation level of catalyst is desirable. In this work, we developed a comprehensive set of models to predict the oxygen storage capacity using measured in-vehicle signals only. This is accomplished by developing three models; the first model is a linear in parameter regression model to predict the feed gas emissions from measured signals like engine speed and air-to-fuel ratio (A/F). The second model is a low-dimensional physics based model of the three-way catalyst to predict the exhaust emissions and oxidation state of the catalyst.