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Future government emission regulations have lead to the development and implementation of advanced aftertreatment systems to meet stringent emission standards for both on-road and off-road vehicles. These aftertreatment systems require sophisticated control and diagnostic strategies to ensure proper system functionality while minimizing tailpipe NOx and PM emissions across all engine operating conditions. In this paper, an integrated algorithm design approach with controls and diagnostics for an aftertreatment system consisting of a fuel doser, fuel reformer, LNT, DPF, and SCR is discussed.

The nonroad Final Tier 4 US EPA emission standards require 88% reduction in NOx emission from the Interim Tier 4 standards. It is necessary to utilize aftertreatment technologies to achieve the required NOx reduction. The development of a fuel reformer, lean NOx trap (LNT) and optional selective catalytic reactor (SCR) on a John Deere 4045 nonroad engine is described in this paper. The paper discusses aftertreatment system performance, catalyst formulations and system controls of a fuel vaporizer, fuel reformer, LNT and SCR system designed to meet the nonroad Final Tier 4 emission standards. The 4045 John Deere engine was calibrated and integrated with the aftertreatment system. The system performance was characterized in an engine dynamometer performance test cell, durability test cell and on a vehicle. The catalyst performance was evaluated using aged catalysts and a detailed description of the LNT, DPF and SCR catalysts is provided.

This paper addresses Hardware-In-the-Loop modeling and simulation for Diesel aftertreatment controls system development. Lean NOx Trap (LNT) based aftertreatment system is an efficient way to reduce NOx emission from diesel engines. From control system perspective, the main challenge in aftertreatment system is to predict temperature at various locations and estimate the stored NOx in LNT. Accurate estimation of temperatures and NOx stored in the LNT will result in an efficient system control with less fuel penalty while still maintaining the emission requirements. The optimization of the controls will prolong the lifespan of the system by avoiding overheating the catalysts, and slow the progressive process of component aging. Under real world conditions, it is quite difficult and costly to test the performance of a such complex controller by using only vehicle tests and engine cells.

In recent years, due to more and more stringent government regulations on diesel emissions, diesel aftertreatment systems have attracted great deal of attention from both academia and diesel engine industries. Many different devices and approaches, such as Urea SCR, LNT, engine control related EGR and in-cylinder post injection, have been developed and applied to reduce nitrogen oxides (NOx) emissions. Among those solutions, Lean NOx Trap (LNT)-based emission reduction control system is one of the common approaches. The NOx storage capacity of an LNT depends on many different factors and operating conditions. Accurate and real-time estimation of NOx storage is quite important for efficient system controls, particularly for enhancing system lifespan and reducing overall fuel consumption. A more precise modeling of NOx storage has more significant impact for overall system performance.

Due to more stringent emission standards as well as customer requirements on performance improvement, model-based controls in diesel engines are becoming more and more common and necessary. In fact, as diesel engines becoming increasingly complicated with additional hardware components such as electonic throttle, EGR, VVT, VGT, as well as aftertreatment devices, the dynamics of the systems with more freedom of multiple actuators become much more sophisticated. With such complexity in the diesel engine systems, the traditional simple PI control, single-input single-output type of controls will not be good enough to address the multivariable interactions among subsystems, instead the advanced model-based, multi-input multi-output and coordinated supervisory controls almost become the only effective ways to improve system performance and achieve emission standards.