Devesh Upadhyay

MULTIVARIABLE CONTROL DESIGN FOR INTAKE FLOW REGULATION OF A DIESEL ENGINE USING SLIDING MODE

Abstract Stringent CAFE regulations along with technological advances in materials, high-pressure fuel injection and complex turbo charging systems have rekindled interest in the area of Diesel engines for passenger vehicle applications. A modern Diesel engine is not only clean and quiet but also allows comparable drivability relative to gasoline engines with considerable improvements in fuel economy. However the current generation diesel engine is a complex system. It is not uncommon to find features like Variable Geometry Turbo charging (VGT), Exhaust Gas Recirculation (EGR) and High Pressure Common Rail (HPCR) fuel injection. In this paper we discuss the design of a multivariable controller for the VGT-EGR system for intake flow regulation. Control design is carried out under the sliding mode framework.

Modeling of a Urea SCR Catalyst With Automotive Applications

A zero order lumped parameter control oriented model of a Selective Catalytic Reduction (SCR) catalyst is presented. The lumped parameter model is developed using two approaches. in the first approach it was assumed that the catalyst behaves as an Isothermal Continuously Stirred Tank Reactor (ICSTR). The second approach involved deriving the lumped parameter model from a 1D model using the method of weighted residuals. Both approaches led to a three state model, with the gas phase concentrations of NOx and NH3 and the surface coverage fraction as the states. The model depends on chemical properties specific to the SCR catalyst; consequently model validation requires knowledge of these parameters, either via laboratory-based experiments or as supplied by the catalyst supplier. We present an alternate approach that allows estimation of the essential parameters through a minimization of the l2 errors between measured and simulated results.Copyright

Control Design of Electrically Assisted Boosting Systems for Diesel Powertrain Applications

In this paper, we investigate the control design problem associated with the use of an electrically assisted turbo-charger (TC) for a modern Diesel engine plant. It is shown that the proposed system has the potential of improving the control bandwidth of air charge regulation relative to conventional systems. The improved control authority creates the potential for precise regulation of the fresh air fraction in the air charge. A previously developed model of a Diesel engine with variable geometry turbocharging (VGT) and Exhaust Gas Recirculation (EGR) is augmented with the model of a permanent magnet synchronous motor (PMSM) to create the model of the Turbo Electrical Assist (TEA) system. The effect of exhaust gas recirculation (EGR) on the electric power requirement of the PMSM is examined over a federal test procedure (FTP) test drive cycle. Control design is performed using the sliding mode framework.

Observer design of critical states for air path flow regulation in a variable geometry turbocharger exhaust gas recirculation diesel engine

Modern automotive diesel engines rely on control strategies that must optimally manage the flows of fresh air and recirculated exhaust gas to achieve the best trade-off between torque demand and engine out emissions. An important aspect of the gas exchange regulation problem is the complex interaction between the variable geometry turbocharger (VGT) and the exhaust gas recirculation (EGR) valve and their associated flows. Control strategies that seek to optimize these flows must either have direct flow measurements or have access to the state variables that provide information on these flows. Furthermore, while the precise control of high-pressure (HP) EGR flow is essential, minimizing its usage is desirable given the engine durability concerns related to the excessive use of HP EGR, such as EGR valve coking and sticking, plugged EGR cooler, cylinder deposits, and valve deposits, to name a few. Exhaust gas recirculation may be optimally used if information on the level of inertness or leanness (oxygen content) of the exhaust gases is available. This paper presents the systematic design of observers for state variables that facilitate the design of such an optimal gas exchange control policy, thereby eliminating the need for direct sensing of the state variables for which the observer designs are proposed.

Identification of a Mean Value Model of a Modern Diesel Engine for Control Design

The modern diesel engine with its multiple subsystem interactions is a very complex plant. Especially fascinating are the interactions of the VGT and EGR control actions in their cumulative effect on the overall air loop dynamics. To circumvent the problem of manpower intensive engine mapping for determining the best operating control map, a generic mean value model of a diesel engine, based on physical principles and empirical definitions where necessary, was developed. In this paper we present the identification of this model with respect to a Fiat 2.4L JTD 166. It will be shown that there is an essential set of parameters that must be identified in order to model processes that are too complicated for physics based modeling. The parameter set is utilized in simplified empirical relationships to model complex engine phenomena such as combustion and orifice flow through the EGR and VGT, facilitating model portability. Results from matching these empirical relationships to the engine of interest and model predictions of air loop system response to EGR and VGT control inputs show good agreement with actual engine performance and are presented in this paper.Copyright

NOx Prediction in Diesel Engines for Aftertreatment Control

Modern Diesel engines are faced with two major emission challenges in their quest to become an environmentally compatible source of motive power, Nitrogen Oxides (NOx ) and Particulate Matter (PM). Advanced techniques, such as High Pressure Common Rail (HPCR) fuel injection combined with multiple injections per cycle, are commonly employed to minimize in-cylinder production of NOx and PM. However, to meet the EPA mandated standards it is essential that an aftertreatment system be used. Typical Diesel aftertreatment systems will employ some form of a NOx reducing catalyst and a particulate trap for PM removal. Lean NOx traps and Selective Catalytic Reduction (SCR) are examples of aftertreatment techniques frequently used in Diesel engine applications. Whatever the method of choice, knowledge of the feed-gas NOx concentration is essential for not only assessing the performance of the NOx reduction catalyst but also for defining the control strategy for the aftertreatment system with respect to the management of the reductant quantity to be injected. In the absence of a dynamic NOx emission model the control algorithm has to depend on either a NOx sensor upstream of the catalyst or a static map of the feedgas NOx level as some function of engine influence factors. While NOx sensors add to the overall system cost, creating an accurate and representative NOx map over the entire engine operating range can be a challenging task. A dynamic NOx model would, in theory solve, both of these problems, however it is essential that the model be simple and implementable in real time. A model that uses inputs that are not available from the standard measurement set is of little use for real time control applications as is a model that predicts the temporal and spatial NOx evolution in the engine combustion chamber as such models tend to be computationally expensive. However, it is essential that the model behave like a fast NOx sensor in predicting cycle averaged NOx emission. In this paper we present an approach to developing such a model and present results from model validation against vehicle data. The basic structure of the model relies on well-known mechanisms that describe the NOx creation and decomposition chemical kinetics. Simplifying assumptions are made to allow available measurements to be used as inputs to the model. This leads to a parametric model where the unknown parameters are estimated using Nelder Mead optimization routine available in Matlab®. Model validation against vehicle data is also presented.Copyright

Experiments in Active Diesel Particulate Filter Regeneration

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.

Control Design of an Automotive Urea SCR Catalyst

The leading aftertreatment technologies for NOx removal from the exhaust gas of lean burn engines, Diesels in particular, are urea based Selective Catalytic Reduction (SCR), Lean NOx Traps (LNT) and Active Lean NOx Catalysts (ALNC). It is generally believed that the SCR technique has the potential of providing the best NOx conversion efficiency relative to the other techniques. Nonetheless, it is crucial that the high conversion efficiencies be achieved with a minimum slippage of unreacted ammonia as tail pipe emissions. This necessitates a precise control over the urea injection process. The complex behavior of the catalyst substrate with respect to adsorption and desorption of ammonia in conjunction with a lack of “stored ammonia” sensing capabilities makes the control problem challenging. In this paper we present a model-based control design approach using a lumped parameter model of an SCR system that includes the essential dynamics of the plant. The model includes the adsorption, desorption and surface coverage dynamics, along with the NOx reduction and ammonia oxidation dynamics based on the relevant chemical reaction rates.© 2002 ASME

Control of diesel engines with electrically assisted turbocharging through an extended state observer based nonlinear MPC

A two-layer controller for a diesel engine equipped with an electrically assisted turbocharger is proposed. A previously identified control-oriented plant model is used for control design. A GT-SUITE based high fidelity engine model is used as the plant. The high-level controller is designed based on the active disturbance rejection control method and uses an extended state observer for added robustness. The high-level controller tracks the boost pressure and intake manifold oxygen concentration. The low-level controller seeks to deliver the desired compressor power through an optimal affine split between the exhaust turbine power and the electric power. The optimal power split is determined by an optimal vane position for the variable geometry turbine. The corresponding optimization problem is solved using a nonlinear model predictive control algorithm that is adapted for fast numerical solution. Controller validation is conducted on the GT-SUITE engine model over the FTP-75 cycle. Results confirm the effectiveness the proposed control design and also illustrate engine performance benefits of an assisted turbocharging system, in terms of transient response (~70% reduction in accumulated boost pressure tracking error) and fuel economy (~4.4% reduction in brake specific fuel consumption) relative to a conventionally boosted system.

Robust Separation of Signal Domain From Single Channel Mixed Signal Output of Automotive Urea Based Selective Catalytic Reduction Systems

There is a class of sensor constrained, uncertain, chemical reactor systems that pose unique challenges with regard to the feedback signal. We refer specifically to the urea based selective catalytic reduction (SCR) of nitrogen oxides (NOx) in the engine exhaust of diesel powertrains. These catalysts rely on adsorbed ammonia (NH3), produced from aqueous urea, for the catalytic reduction of NOx to N2. Typically, underinjection of urea will result in the slip of NOx, whereas overinjection will induce NH3 slip. The ideal control objective of such a plant is, therefore, to regulate urea injection such that the net slip over the catalyst is minimized. Meeting these control objectives is made difficult due to the presence of an output sensor that is cross sensitive to both NOx and NH3, thereby producing a mixed feedback signal. This signal confounding poses significant challenges with regard to the stability and robustness of both closed loop control as well as on board diagnostics. In the absence of a robust NH3 sensor, it becomes necessary to create alternate methods of signal disambiguation. However, so far in open literature, there has not been a detailed discussion of this problem nor has a concrete solution been proposed to robustly and continuously identify the nature of slip as NOx or NH3. In this paper, we discuss the systematic development of a new method that allows a robust and continuous determination of the slip regime from the mixed signal output of a standard NOx sensor. The full scope of the practical problem is discussed and the performance of the proposed method is shown via experimental data.