G. N. Pontikakis

Three-Way Catalytic Converter Modeling as a Modern Engineering Design Tool

The competition to deliver ultra low emitting vehicles at a reasonable cost is driving the automotive industry to invest significant manpower and test lab resources in the design optimization of increasingly complex exhaust aftertreatment systems. Optimization can no longer be based on traditional approaches, which are intensive in hardware use and lab testing. This paper discusses the extents and limitations of applicability of state-of-the-art mathematical models of catalytic converter performance. In-house software from the authors lab, already in use during the last decade in design optimization studies, updated with recent, important model improvements, is employed as a reference in this discussion. Emphasis is on the engineering methodology of the computational tools and their application, which covers quality assurance of input data, advanced parameter estimation procedures, and a suggested performance measure that drives the parameter estimation code to optimum results and also allows a less subjective assessment of model prediction accuracy. Extensive comparisons between measured and computed instantaneous emissions overfull cycles are presented, aiming to give a good picture of the capabilities of state of the art engineering models of automotive catalytic converter systems.

Computer aided engineering in diesel exhaust aftertreatment systems design

Abstract Computer aided engineering (CAE) methodologies are increasingly being applied to assist the design of spark-ignition (SI) engine exhaust aftertreatment systems in view of the stage III and IV emissions standards. Following this trend, the design of diesel exhaust aftertreatment systems is receiving more attention owing to the capabilities of recently developed mathematical models. The design of diesel exhaust systems must cope with three major aftertreatment categories: diesel oxidation catalysts, diesel particulate filters and de-NOx catalytic converters. An integrated CAE methodology that could assist the design of all these classes of systems is described in this paper. It employs the following computational tools: a computer code for modelling transient exhaust system heat transfer, a computer code for modelling the transient operation of a diesel oxidation or a de-NOx catalytic converter, a database containing chemical kinetics data for a variety of oxidation and de-NOx catalyst formulations and a computer code for modelling the loading and regeneration behaviour of a wall-flow filter, assisted by catalytic fuel additives. Application of the CAE methodology, which helps the exhaust aftertreatment system design engineer to meet the future emissions standards, is highlighted by referring to a number of representative case studies.

Identification of catalytic converter kinetic model using a genetic algorithm approach

Abstract The need to deliver fast-in-market and right-first-time design for ultra-low-emission vehicles at a reasonable cost is driving the automotive industries to invest significant manpower in computer-aided design and optimization of exhaust after-treatment systems. To serve the above goals, an already developed engineering model for the three-way catalytic converter kinetic behaviour is linked with a genetic algorithm optimization procedure, for fast and accurate estimation of the set of tuneable kinetic parameters that describe the chemical behaviour of each specific washcoat formulation. The genetic-algorithm-based optimization procedure utilizes a purpose-designed performance measure that allows an objective assessment of model prediction accuracy against a set of experimental data that represent the behaviour of the specific washcoat formulation over a typical legislated test procedure. The identification methodology is tested on a demanding case study, and the best-fit parameters demonstrate high accuracy in matching the measured test data. The results are definitely more accurate than those usually obtained by manual or gradient-based tuning of the parameters. Moreover, the set of parameters identified by the genetic algorithm methodology is proven to describe in a valid way the chemical kinetic behaviour of the specific catalyst, and this is tested by the successful prediction of the performance of a smaller-size converter. The parameter estimation methodology developed fits in an integrated computer-aided engineering methodology assisting the design optimization of catalytic exhaust systems that extends all the way through from model development to parameter estimation, and quality assurance of test data.

DYNAMIC FILTRATION MODELING IN FOAM FILTERS FOR DIESEL EXHAUST

Abstract Diesel Particulate Filters (DPFs) are probably the most effective means for trapping the exhaust emitted particulate from diesel engines. Foam type filters become a promising alternative to the common wall flow filters, since they are effective in filtering small size particles and provide a larger specific surface area for catalytic coatings. A mathematical model taking into account the significant phenomena during the dynamic filtration of foam fitters is developed. The model predicts the filtration efficiency and the induced backpressure as function of the geometric filter properties and operating conditions. A novel approach is employed which considers both “deep-bed” and “cake”filtration characteristics in the filter. Due to the particular structure properties of the foam filters it is necessary to define a characteristic parameter, which differentiates among different filter types. This parameter, which has a physical meaning, is easily derived by simple experimental measurements. The model is employed to. identify and understand the critical parameters of the phenomenon. Indicative parametric runs are presented, which illustrate the applicability of the model in system optimization procedures.

Experimental and modeling study on zeolite catalysts for diesel engines

The work presented in this paper was aimed at detecting, understanding and modeling some critical behavior aspects of zeolite-containing diesel catalysts. An already available mathematical model for precious metal catalysts was used as a starting point. A specially designed set of experiments provided the information needed to improve certain modeling features. New submodels were introduced to account for hydrocarbon and H2O adsorption, as well as diffusion limitations in the zeolite. The effect of flow maldistribution during real world operation was investigated experimentally and computationally. Although a number of issues (especially regarding the DeNOx mechanisms) are not yet fully resolved, significant progress was achieved as regards the understanding and computational prediction of diesel catalyst operation.

Three-Dimensional Catalytic Regeneration Modeling of SiC Diesel Particulate Filters

Increasingly stringent diesel particulate emissions standards have reestablished international interest in diesel filters, whose first series application dates back to 1985. Modern diesel engine technology, with computerized engine management systems and advanced, common rail injection systems, needs to be fully exploited to support efficient and durable diesel filter systems with catalytic aids, as standard equipment in passenger cars. Efficient system and components optimization requires the use of mathematical models of diesel filter performance. The three-dimensional model for the regeneration of the diesel particulate filter presented in this paper has been developed as an engineering tool for the detailed design optimization of SiC diesel filters of modular structure. The 3-D modeling is achieved by interfacing an existing 1-D model to commercial finite element method software for the computation of the 3-D temperature field within the whole filter assembly, including the adhesive of the filter blocks, the insulation mat, and the metal canning. The 3-D model is applied to real-world component optimization studies of diesel filter systems.

Mathematical modelling of catalytic exhaust systems for EURO-3 and EURO-4 emissions standards

Abstract The application of computer simulation in the development of catalytic exhaust aftertreatment systems for cars is over thirty years old. However, ever-increasingly stringent exhaust emissions legislation requires an ever-increasing degree of accuracy and complexity in the mathematical models applied. Traditionally, the Langmuir-Hinshelwood kinetics were applied in the majority of the models available, with a small number of representative chemical reactions. In this paper it is proved, by means of typical case studies, that the above modelling approach, with the necessary refining, can be brought to the level of accurately predicting the behaviour of advanced catalyst systems employed in EURO-3 and EURO-4 emissions homologation. An essential characteristic that was introduced to this end is the computer-aided selection (best fit) of the tunable parameters representing the apparent chemical kinetics and oxygen storage and release properties of each different catalyst-washcoat combination. Other modelling improvements are also discussed in the present paper, setting the scene for high accuracy simulations in view of the current and future emissions standards for spark-ignited, diesel and gasoline direct injection (GDI)-engined vehicles. These include the modelling of the aged catalyst, as well as taking into account the effect of precious metal loading variation on the apparent kinetics.

Experimental validation of a fuel additive assisted regeneration model in silicon carbide diesel filters

Abstract In this paper, an experimental validation procedure is applied to an improved one-dimensional model of fuel additive assisted regeneration of a diesel particulate filter. Full-scale tests on an engine bench of the regeneration behaviour of a diesel filter fitted to a modern diesel engine run on catalyst- doped fuel are employed for this purpose. The main objectives of the validation procedure concern the ability of the model to predict the effects of exhaust mass flowrate, initial soot loading mass, volatile organic fraction of the soot and additive concentration in the fuel. The results of the validation procedure are intended to demonstrate the scope and extent of applicability of models of this type to real-world design and optimization studies with diesel filters.

3-D Catalytic Regeneration and Stress Modeling of Diesel Particulate Filters by ABAQUS FEM Software

The design of reliable DPF systems has proved a complex and demanding task that is increasingly being assisted by modeling. 1-D but also 2-D (axisymmetric) modeling has already been applied in design optimization case studies, with varying degrees of success. The introduction of advanced technology SiC and cordierite filters with modular structure and the need to accurately model transient temperature and stress fields in low space velocity scenarios, made necessary the shift to 3-D modeling. In this paper, 3-D modeling is carried out in an effective and reliable way, by interfacing a well-documented and validated 1-D model with the ABAQUS commercial FEM software. The new modeling methodology proves a powerful tool in the hands of the filter and diesel exhaust system design engineer.

KINETIC PARAMETER ESTIMATION BY STANDARD OPTIMIZATION METHODS IN CATALYTIC CONVERTER MODELING

The application of mathematical models to the prediction of the performance of automotive catalytic converters is gaining increasing interest, both for gasoline and diesel engined-vehicles. This article addresses converter modeling in the transient state under realistic experimental conditions. The model employed in this study relies on Langmuir-Hinshelwood kinetics, and a number of apparent kinetic parameters must be tuned to match the behavior of each different catalyst formulation. The previously applied procedure of manually tuning kinetics parameters requires significant manpower. This article presents a methodology for kinetic parameter estimation that is based on standard optimization methods. The methodology is being applied in the exploitation of synthetic gas experiments and legislated driving cycle tests and the assessment of the quality of information contained in the test results. Although the optimization technique employed for parameter estimation is well known, the development of the specific parameter estimation methodology that employs the results of the available types of experiments is novel and required significant development. Application of this refined tuning methodology increases the quality and reliability of prediction and also greatly reduces the required manpower, which is important in the specific engineering design process. The parameter estimation procedure is applied to the example of modeling of a diesel catalytic converter with adsorption capabilities, based on laboratory experiments and vehicle driving cycle tests.