Analysis of carbon black oxidation
Doctoral thesis, 2017
Diesel engines are known to be a major source of a highly pollutant material known as particulate matter, PM, which is a strongly threatening agent to human health. Therefore, diesel particulate filters are used to reduce PM emissions by trapping soot. Regenerating the particulate filter is necessary to keep the exhaust back pressure below a certain limit and, thereby, to maintain efficient fuel consumption. Regeneration can be run in two modes: active or passive. The former mode is performed by injecting additional fuel into the exhaust to raise the temperature above 550 C and, thereby, burn the accumulated soot with oxygen. In contrast, passive regeneration can be performed at the exhaust temperature, i.e. ~350-450 C, which is more efficient. The key compound for passive regeneration that reacts with soot is NO2, which is more reactive than oxygen. It is formed by oxidizing NO over an oxidation catalyst.
The goal of this thesis is to develop both experimental and theoretical methodologies to study the soot-NO2 reaction from a fundamental perspective. To this end, a thorough characterization study of the experimental setup was conducted with respect to heat transfer and residence time distribution, which resulted in a number of guidelines to help increase the quality of experimental measurements. Moreover, a novel sample preparation method is proposed that ensures a highly controlled carbon deposition in each and every channel of the monolithic reactors, which was found to be crucial for obtaining reliable and reproducible results. Furthermore, a deconvolution algorithm was developed to decrease the unresolved time span of transient measurements. Numerical simulations, in particular computational fluid dynamics, were extensively employed to both aid as simulation tools and to gain a deeper insight into the subject of study.
Significant promoting effects were identified for both water vapor and molecular oxygen, which indicates the importance of studying automotive soot oxidation under realistic exhaust conditions. A global kinetic model was formulated that can express the observed rate of oxidation in the presence of water vapor, oxygen, and NO2 with very high accuracy over the entire 0-100% conversion interval. It thus serves as a predictive tool for optimizing both the operation of diesel engines and the design of soot traps.
diesel particulate filter (DPF)
deconvolution
inverse problems
residence time distribution
computational fluid dynamics (CFD)
kinetic modeling
transient kinetics
KB
Opponent: Prof. Michiel Makkee, Delft University of Technology, the Netherlands
Author
Soheil Soltani
Chalmers, Chemistry and Chemical Engineering, Chemical Technology
Time Resolution in Transient Kinetics
Springer Proceedings in Mathematics and Statistics: 3rd Annual Workshop on Inverse Problems, 2013, Stockholm, Sweden, 2-6 May 2013,;Vol. 120(2015)p. 81-96
Paper in proceeding
Enhancement of time resolution in transient kinetics
Chemical Engineering Journal,;Vol. 264(2015)p. 188-196
Journal article
Kinetic analysis of O2- and NO2-based oxidation of synthetic soot
Journal of Physical Chemistry C,;Vol. 117(2013)p. 522-531
Journal article
CFD Characerization of Monolithic Reactors for Kinetic Studies
Canadian Journal of Chemical Engineering,;Vol. 92(2014)p. 1570-1578
Journal article
Soltani, S., Andersson, R., Andersson, B., Oxidation of synthetic soot with NO2 in the presence of water vapor and oxygen
The combustion of diesel fuel in engines produces pollutant gases as well as particulate matter (PM). As a result, diesel exhaust has detrimental effects on human health and on the environment. Therefore, emissions from diesel exhaust have been regulated by legislations in many countries all around the globe. To comply with those regulations, diesel vehicles are equipped with a so-called “after-treatment” system in which gaseous pollutants are chemically treated via several catalytic reactions. Also involved in the after-treatment system is a diesel particulate filter (DPF) that collects the PM and thereby removes it from diesel exhaust.
The accumulation of PM in the filter has adverse effects on fuel consumption, and, therefore, the collected PM has to be burned regularly in a process known as regeneration. PM is largely composed of carbon, and regeneration can be achieved by letting it react with oxygen that is present in the exhaust in abundance. This, however, requires temperatures as high as 500 C that can be achieved with the combustion of additional fuel in the exhaust line known as “active regeneration.” In addition to the consequent fuel penalty, such high temperatures increase the risk of melting the filter due to uncontrolled chemical reactions. An auxiliary approach that can largely circumvent these drawbacks would be to utilize NO2; another component of diesel exhaust that can burn PM at the same temperature as diesel exhaust and is therefore referred to as passive regeneration. For this reason, it is undoubtedly beneficial to have control algorithms that account for the NO2-assisted reaction and that determine the optimal frequency of active regeneration cycles. Such algorithms would be strongly dependent on the mathematical models that are used to predict the required conditions for achieving optimality.
The main focus of this thesis is on the reaction between PM and NO2. Within this study, experimental and theoretical methods were developed to study this reaction in a more fundamental way. The achievements of this study include guidelines for conducting high-quality experiments, the method of sample preparation so that repeatable and consistent experimental results can be obtained, simulation methods for acquiring insight into the fundamental aspects of the reaction between PM and NO2, and a kinetic model for this reaction that also includes the influence of other components of diesel exhaust such as water vapor and oxygen that have promoting effects on the rate of the reaction.
The accumulation of PM in the filter has adverse effects on fuel consumption, and, therefore, the collected PM has to be burned regularly in a process known as regeneration. PM is largely composed of carbon, and regeneration can be achieved by letting it react with oxygen that is present in the exhaust in abundance. This, however, requires temperatures as high as 500 C that can be achieved with the combustion of additional fuel in the exhaust line known as “active regeneration.” In addition to the consequent fuel penalty, such high temperatures increase the risk of melting the filter due to uncontrolled chemical reactions. An auxiliary approach that can largely circumvent these drawbacks would be to utilize NO2; another component of diesel exhaust that can burn PM at the same temperature as diesel exhaust and is therefore referred to as passive regeneration. For this reason, it is undoubtedly beneficial to have control algorithms that account for the NO2-assisted reaction and that determine the optimal frequency of active regeneration cycles. Such algorithms would be strongly dependent on the mathematical models that are used to predict the required conditions for achieving optimality.
The main focus of this thesis is on the reaction between PM and NO2. Within this study, experimental and theoretical methods were developed to study this reaction in a more fundamental way. The achievements of this study include guidelines for conducting high-quality experiments, the method of sample preparation so that repeatable and consistent experimental results can be obtained, simulation methods for acquiring insight into the fundamental aspects of the reaction between PM and NO2, and a kinetic model for this reaction that also includes the influence of other components of diesel exhaust such as water vapor and oxygen that have promoting effects on the rate of the reaction.
Driving Forces
Sustainable development
Subject Categories
Energy Engineering
Chemical Process Engineering
Other Chemical Engineering
ISBN
978-91-7597-564-1
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4245
Publisher
Chalmers
KB
Opponent: Prof. Michiel Makkee, Delft University of Technology, the Netherlands