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An automated process was developed for the calibration of numerical aftertreatment models. The chemical kinetic mechanism examined in this case was part of a simplified SCR model. The process adopted for calibrating the SCR model was based on a micro-population multi-objective genetic algorithm. The algorithm developed was used to calibrate the SCR model using data derived from another, more detailed model to ensure that the evaluation focused only on the effectiveness of the calibration process and was not affected by issues of experimental inaccuracies or details of the model chemistry involved.

Spark-plug lifetime is limited by the ability of the ignition coil to generate a spark channel. Electrode erosion during operation causes the geometry to deform and the maximum voltage required to form a spark increases until the ignition coil is no longer able to form the spark channel. Numerical models that can analyze the breakdown of the plasma in a spark plug have typically been limited to vacuum electrical field simulations and full-fidelity plasma models. In the present work, we present a fast, predictive breakdown model that blends the speed and computational efficiency of electric field model and incorporates the essential physics of the breakdown event without having to pay the cost of solving the full set of plasma governing equations.

The wall Flow Diesel Particulate Filter (DPF) is one of the major technologies used to meet the current and future Particulate Matter (PM) emission regulations on heavy duty applications. This technology, however, adds significant engine backpressure. This has a negative impact on fuel consumption, and in turn, on CO2emissions. In order to better understand the DPF impact on engine backpressure, a large amount of DPF pressure drop models have been published, especially over the last ten years. Even though each published model has slight variations, they were all derived from Konstandopoulos approach of the problem [1]. However, in 1998, Opris developed a unique pressure drop model [2,4], that is radically different from Konstandopoulos’ method. In the Opris model, Navier-Stockes equations were analytically solved in the context of a DPF. Along with Darcy’s law, and the 2D flow-field solution, a fundamental expression of the DPF pressure drop was obtained.

Tier 4 Final legislation commences from 2008 - 2015, depending on engine power. At the same time the use of biodiesel is being incentivized or mandated in many countries. This is driving up the proportion of biodiesel available to the diesel engine fleet and so it is important to understand its impact on possible Tier 4 Final engine and aftertreatment systems. One of the solutions being explored to meet Tier 4 Final emissions regulations is selective catalytic reduction (SCR) using urea and an appropriate catalyst. Previous researchers have highlighted the potential for biodiesel to have a much greater impact on percentage increase in tailpipe NOx on engines equipped with Urea SCR aftertreatment than has historically been the case for engine-out NOx increase. Increases of as much as 80% have been presented, but without knowledge of the engine-out or absolute NOx emission data, it has not been possible to draw any conclusions from some of these publications.

Properly characterizing input forces is an important part of simulating structure-borne noise problems. The purpose of this work was to apply a known force reconstruction technique to an earthmoving machinery cab to obtain input functions for modeling purposes. The technique was performed on a cab under controlled laboratory conditions to gain confidence in the method prior to use on actual machines. Forces were measured directly using force transducers and compared to results from the force reconstruction technique. The measured forces and vibrations were used as input power to an SEA model with favorable results.

Turbocharged diesel engines are widely used in off-road applications including construction and mining machinery, electric power generation systems, locomotives, marine, petroleum, industrial and agricultural equipment. Such applications contribute significantly to both local air pollution and CO₂ emissions and are subject to increasingly stringent legislation. To improve fuel economy while meeting emissions limits, manufacturers are exploring engine downsizing by increasing engine boost levels. This allows an increase in IMEP without significantly increasing mechanical losses, which results in a higher overall efficiency. However, this can lead to poorer transient engine response primarily due to turbo-lag, which is a major penalty for engines subjected to fast varying loads. To recover transient response, the turbocharger can be electrically assisted by means of a high speed motor/generator.

A predictive numerical model was developed to determine the impact of phosphorus exposure on the performance of flow through aftertreatment components such as Diesel Oxidation Catalysts (DOC) or Selective Catalytic Reduction (SCR) catalysts. The model is able to successfully determine the distribution of the phosphorus over the catalyst as a function of the aging history (temperature, flow rates, oil consumption rate, phosphorus content of the oil) as well as the component properties (diameter, length, cell density, wall thickness). The model then incorporates this information regarding the distribution of phosphorus over the catalyst surface to determine the impact of the phosphorus exposure on the overall catalytic activity. The model results were successfully validated using accelerated bench aging tests for the oxidation of hydrocarbons over DOC's and NH₃ oxidation and NOx reduction over SCR catalysts.

The vehicle pass-by exterior noise tests are generally subjected to several variables including the weather and test track surface conditions. Additionally, validity of test results depends on test driver judgment and consistency. In a time when vehicle manufacturers need to tap into all resources to control noise emissions to meet stringent limits, a more reproducible and accessible tool than the actual pass-by noise test will provide a development edge. As a major partner to vehicle manufacturers on noise control, the engine manufacturer (particularly diesel engine manufacturers) can additionally benefit from a development tool free of vehicle chassis and accessory effects. A technique developed and in use at Caterpillar simulates the pass-by noise test in-cell. This technique simulates the engine loading under vehicle acceleration with a prescribed external inertia.

This paper presents a novel 6-DOF multi-physics model of a cab suspension system. The model consists of a cab with six degrees of freedom supported by four fluid filled viscous mounts. In the literature, to the best of the authors' knowledge, all 6-DOF cab models have simplified fluid filled mounts as spring damper combinations. In its best case, a nonlinear stiffness relationship is allowed in the simplified models to capture the nonlinear behavior of the mounts and include geometric constraints and hard-stops. The novel model presented in this paper, however, includes a multi-physics model of the mounts. Each mount is represented by a molded assembly, two fluid chambers, a fluid track that connects the two chambers, and a gas chamber. Each mount can be pressurized or vented. A simple cavitation model is also used as an indicator of fluid cavitation in each mount.

This paper builds upon recent publication (SAE Technical Paper 2011-01-1388, 2011, doi:10.4271/2011-01-1388) and outlines the on-going development of an advanced simulator for virtual engine mapping and optimization of engine performance, combustion and emissions characteristics. The model is further advanced through development of new sub-models for turbulent mixing, multiple injection events, variable injection pressures, engine breathing and gas exchange, as well as particulates formation and oxidation. The result is a simulator which offers engine design and performance data typically associated with 1D thermodynamic engine cycle simulations but with the "physics-based" model robustness usually associated with 3D CFD methods. This combination then enables efficient optimization of engine design with respect to engine performance, combustion characteristics and exhaust gas emissions.

The complex eigenvalue analysis has been used by the brake research community to study friction-induced squeal in automotive disk brake assemblies. The analysis process uses a nonlinear static pre-stressed normal modes analysis simulation sequence followed by a complex eigenvalue extraction algorithm to determine the dynamic instabilities. When brake hardware exists, good correlation between analysis results and experimental data can be obtained. Consequently, complex eigenvalue analysis can be a valuable method in an effort to understand brake components that might have a propensity to influence the noise behavior of a brake system. However, when hardware does not exist and the complex eigenvalue method is asked to be predictive, it becomes a difficult, if not impossible task. This paper will focus on some of the reasons the complex eigenvalue analysis method is not a reliable predictor of friction-induced squeal in automotive disk brake assemblies.