Imad Hassan Makki

Linear Parameter-Varying Lean Burn Air-Fuel Ratio Control for a Spark Ignition Engine

In 2003, U.S. consumed about 20 million barrels of oil per day. The gasoline for cars and light trucks accounts for 45% of the total oil consumption. Lean burn technology for gasoline engines has drawn great attention during the past decade, largely due to its potential for improving fuel economy and reducing CO2 emissions 1. A lean burn engine is designed to operate at high intake manifold pressure with an air-fuel ratio greater than 10 and less than 23. Consequently, combustion efficiency can be improved through reduced pumping losses and enhanced thermodynamic efficiency. Compared to the conventional port fuel injection PFI engine, the gasoline lean burn engine presents a new set of challenges to the engine control community. The main challenge for lean burn technology is that, under lean operating conditions, the conventional three-way catalyst TWC system is no longer effective in reducing NOx pollutants. A special TWC with NOx trapping and conversion capabilities, known as lean NOx trap LNT, has to be used downstream of the conventional TWC to meet the government emission standards. During the lean operation, NOx in the feed gas is stored in the LNT. When the stored NOx reaches a certain threshold, the trap must be purged by switching to rich operation for a short period of time to regenerate the storage capacity and recover the efficiency. The NOx released from the LNT during the purge period is converted into non-polluting nitrogen by the rich air-fuel mixture 2‐5. Properly managing the storage and purge cycles is critical for achieving the fuel economy and NOx emission control targets of the lean burn gasoline engine. The desired tailpipe air-fuel ratio profile reference air-fuel ratio is defined by the LNT purge control 6,7, with the objectives of optimizing fuel economy while satisfying emission constraints. Therefore, it is necessary to design a controller to regulate the tailpipe air-fuel ratio to follow the air-fuel reference for both the NOx storage phase lean operation and the purge phase rich operation in order to accomplish the LNT purge control. In this paper, we concentrate on the air-fuel ratio control for the storage phase, that is, the design of the “outer-feedback loop” air-fuel ratio controller is considered. A linear universal exhaust gas oxygen UEGO sensor is used downstream of the LNT to measure the tailpipe air-fuel ratio. The air-fuel ratio controller to be designed is used to generate the commanded air-fuel ratio for the fuel injection system. During the storage phase when the engine is operating under lean conditions, the air-fuel ratio is selected to i meet the driver’s demand, ii maximize fuel economy, and iii satisfy other constraints, such as lean burn limit 7. These requirements dictate the set-point selection, and the optimal choice for the air-fuel ratio in the storage phase is usually a constant set-point for steady state operation.

Intake Air Path Diagnostics for Internal Combustion Engines

Presented is the detection, isolation, and estimation of faults that occur in the intake air path of internal combustion engines during steady state operation. The proposed diagnostic approach is based on a static air path model, which is adapted online such that the model output matches the measured output during steady state conditions. The resulting changes in the model coefficients create a vector whose magnitude and direction are used for fault detection and isolation. Fault estimation is realized by analyzing the residual between the actual sensor measurement and the output of the original (i.e., healthy) model. To identify the structure of the steady state air path model a process called system probing is developed. The proposed diagnostics algorithm is experimentally validated on the intake air path of a Ford 4.6 L V-8 engine. The specific faults to be identified include two of the most problematic faults that degrade the performance of transient fueling controllers: bias in the mass air flow sensor and a leak in the intake manifold. The selected model inputs include throttle position and engine speed, and the output is the mass air flow sensor measurement.

Vibration-based NVH control during idle operation of an automobile powertrain

A system and method of operating a vehicle powertrain that employs active control to reduce NVH, particularly during idle. The method includes selectively operating the powertrain in at least a non-idle condition and an idle condition; receiving vibration signals from a sensor disposed on an internal combustion engine; controlling spark timing of the internal combustion engine based on vibration signals received from the sensor; and during the idle condition, modifying a speed and/or a load of the internal combustion engine based on vibration signals received from the sensor.

Linear Parameter-Varying Lean Burn Air-Fuel Ratio Control

Maximization of the fuel economy of the lean burn SI engine strongly depends on precise air-fuel ratio control. A great challenge associated with the air-fuel ratio feedback control is the large variable time delay in the exhaust system. In this paper, a systematic development of an air-fuel ratio controller based on post-LNT UEGO sensor feedback using linear parameter-varying (LPV) control is presented. Satisfactory stability and disturbance rejection performance is obtained in the face of the variable time delay. The LPV controller is simplified to an explicit parameterized gain scheduled 1st order controller form for the ease of implementation. A Ford F-150 truck with a V8 4.6 Liter lean burn engine was used to demonstrate the LPV air-fuel ratio control design. Both simulation and experimental results demonstrate that the designed controller regulates the tailpipe air-fuel ratio to the preset reference for the full engine operating range.

Transient lean burn air-fuel ratio control using input shaping method combined with linear parameter-varying control

Transient air-fuel ratio control for lean burn engines is critical to achieve desired fuel economy and meet federal emission regulations. Unlike conventional SI engines, lean burn engines are no longer operating in a narrow band around stoichiometry resulting in a very challenging air-fuel ratio tracking problem. An approach to combine an input shaping method together with a linear parameter varying (LPV) feedback controller is proposed to solve the transient air-fuel ratio tracking problem. In the work of Zhang et al. (2005), a feedback LPV air-fuel ratio controller has been designed to regulate the air-fuel ratio at steady state engine operating conditions, reduce the variability of the closed-loop system, reject disturbances and guarantee robustness and stability. In this paper, an input shaping method is proposed to reduce the cost of feedback, and thereby enhance the air-fuel ratio tracking performance during engine transient operations. The prefilter is designed based on the closed-loop dynamics resulting from the LPV design. A systematic input shaping prefilter design process is developed. The designed prefilter successfully extends the closed-loop air-fuel ratio tracking bandwidth. Simulation results are used to demonstrate the effectiveness of the input shaping prefilter. Moreover, the designed prefilter is structurally simple and computationally efficient

A non-intrusive three-way catalyst diagnostics monitor based on support vector machines.

The three-way catalytic converter performance degrades as it ages over time due to many phenomenon such as catalyst poisoning, sintering or physical damage of the instrument. To reduce the emission impact on environment, the Environmental Protection Agency (EPA) regulations requires the on-board diagnostics (OBD) method to set a flag (fault code) once the catalyst reaches its threshold. In this work, we propose a support vector machine based non-intrusive classification method to diagnose the catalyst as it ages. To further improve the model robustness and to reduce the size of support vectors, multiple clustering algorithms were evaluated. The model was tested on multiple catalyst systems under various operating conditions and good results were observed.

An evaluation of detection metrics for an integrated catalyst controller and diagnostic monitor

Abstract An integrated, model-based methodology for three-way automotive catalyst control and diagnostic monitoring utilizing a limited integrator model with an adaptive integral gain is outlined in this work. This adaptive gain, which is a measure of the catalyst oxygen storage capacity, is used both by the controller to provide information on the dynamic catalyst behavior and by the diagnostic monitor to provide information on long-term catalyst deactivation and short-term emission control device failure. Nonparametric test statistics using various metrics computed from a moving window sample of the adaptive gain are compared to determine their ability to detect changes in catalyst system performance with a number of differently aged catalysts. These diagnostic monitoring metrics have been applied to 4.6 liter ULEV II gasoline engine data tested over an EPA Federal Test Procedure drive cycle.

Transient lean burn air-fuel ratio linear parameter-varying control using input shaping

Transient air-fuel ratio control for lean burn engines is essential to achieve improved fuel economy and strict federal emission regulations. Unlike conventional Spark Ignition (SI) engines, lean burn engines are no longer operating in a narrow band around stoichiometric resulting in a very challenging air-fuel ratio tracking problem. An approach to combine an input shaping method together with Linear Parameter Varying (LPV) feedback control is proposed in this paper to solve the transient air-fuel ratio tracking problem. LPV air-fuel ratio control has been shown to regulate the air-fuel ratio at steady state engine operating conditions, reduce the variability of the closed-loop system, reject disturbance and guarantee robustness and stability in the presence of variable time delays. In this paper, an input shaping method is used to reduce the cost of feedback, and thereby enhance the air-fuel ratio tracking performance during engine transient operations. The prefilter is designed based on the closed-loop dynamics resulting from the LPV design. A systematic input shaping prefilter design process is developed. The designed prefilter successfully extends the closed-loop air-fuel ratio tracking bandwidth. Simulation results using Federal Test Procedure (FTP) drive cycle data are used to demonstrate the effectiveness of the input shaping prefilter. Moreover, the designed prefilter is structurally simple and computationally efficient.

Feed-forward control of purge flow in internal combustion engines

Presented is a feed-forward controller that coordinates engine fueling with a purge event to reduce air–fuel ratio excursions. The controller employs a linear parameter-varying model to estimate the necessary changes in fuel pulse-width based on a hydrocarbon sensor located in the purge line. Synchronization between the purge fuel vapor arrival at the intake manifold and the fueling command is realized using a transport delay model. The proposed controller is experimentally validated on a Ford 5.4-L port injected engine and a 3.6-L EcoBoost engine. Significant reductions in air–fuel ratio excursions are achieved during the steady-state engine operating conditions associated with highway conditions.

Statistics Based Detection and Isolation of UEGO Sensor Faults

Stringent emission regulations mandated by California air regulation board (CARB) require monitoring the upstream exhaust gas oxygen (UEGO) sensor for any possible malfunction causing the vehicle emissions to exceed certain thresholds. Six faults have been identified to potentially cause the UEGO sensor performance to deteriorate and potentially lead to instability of the air-fuel ratio (AFR) control loop. These malfunctions are either due to an additional delay or an additional lag in the transition of the sensor response from lean to rich or rich to lean. Current technology detects the faults the same way (approximated by a delay type fault) and does not distinguish between the different faults. In the current paper, a statistics based approach is developed to diagnose these faults. Specifically, the characteristics of a non-normal distribution function are estimated based on the UEGO sensor output and used to detect and isolate the faults. When symmetric operation is detected, a system identification process is employed to estimate the parameters of the dynamic system and determine the type of operation. The proposed algorithm has been demonstrated on real data obtained from both Ford F150 and Mustang V6 vehicles.© 2013 ASME