GPC 2001 GLOBAL POWERTRAIN CONGRESS:

GPC 1 GLOBAL POWERTRAIN CONGRESS: Detroit, MI, June 5-7, 1 Storage of Chemical Species in Emission Control Systems: The Role of Mathematical Modeling Grigorios C. Koltsakis, Anastassios M. Stamatelos Mechanical & Industrial Engineering Department, University of Thessaly, Pedion Areos, 383 34 Volos, GREECE ABSTRACT The importance of mathematical modeling in the cost-efficient optimization of automotive emission control systems is widely recognized today. During the last three decades, a variety of models have been developed and applied to the performance prediction of emission control devices, including 3-way catalysts, diesel catalysts, hydrocarbon adsorbers and NO x traps. An eminent feature of modern catalytic exhaust after-treatment systems is the periodic storage and release of several chemical species on the catalytic surface. Specifically, oxygen storage is critical for 3-way catalysts; hydrocarbon storage is applied in trapping the cold start hydrocarbon emissions of spark-ignition and diesel engines; NO x storage is a promising candidate for GDI and diesel emission control. The development of mathematical models to simulate these transient phenomena in a rational and practical way, is a challenging task. This paper discusses work that has been carried out by ours and other researchers in this direction. The main storage mechanisms for each catalyst type are outlined and respective, simplified modeling approaches are presented and evaluated against experimental data. The results show that even with simple engineering approaches, it is possible to attain an acceptable accuracy level. Finally, the specific difficulties applying to each case are discussed and directions for future work are indicated. INTRODUCTION Mathematical modeling is widely applied today in the cost-efficient optimization of exhaust after-treatment systems. Historically, the first modeling attempts were applied on the oxidation catalyst fitted on engines without feedback control. This technology, usually referred to as first generation catalyst was aiming at the reduction of CO and HC emissions under oxygen surplus. The governing chemical phenomena were the reactions of CO and HC with oxygen, which could be described adequately by Langmuir-Hinshelwood kinetics. The underlying assumption of these reaction models is that the rate limiting (slowest) step of the process is the reaction between the species adsorbed on the catalyst surface. On the other hand, the adsorption and desorption of the species to and from the catalytic surface is comparatively very fast. Therefore, the core assumption of these models was that the gas diffusion rates are equal to the rates by the L-H mechanism [1]. The majority of the modeling studies carried out so far, employed rate expressions and kinetic parameters based on the fundamental and pioneering work of Voltz et al. []. The introduction of the closed-loop engine management with lambda sensor, enabled the employment of 3-way catalysts to simultaneously convert CO, HC and NO x emissions (second generation catalysts). Theoretically, this is only possible at exactly stoichiometric, steady-state conditions. With the conventional lambda sensor technology it was not possible to maintain such conditions under all modes of real driving. Instead, the catalyst was subjected to a periodically alternating lean/rich exhaust. The inclusion of Ceria and Zirconia in the washcoat composition, enabled the storage of oxygen under lean conditions, which was used later during rich conditions to compensate for oxygen deficiency. This phenomenon is critical for overall catalyst efficiency and should be included in any modeling approach of the 3-way catalyst if one wants to attain the accuracy levels required by modern systems conversion efficiency. Since oxygen is periodically stored and released in the washcoat, the quasi-steady assumption is no longer applicable. More advanced modeling approaches were developed to account for this problem, ranging from simple engineering approaches to more complicated fundamental studies. Zeolites have been proposed for application in both gasoline and diesel aftertreatment systems as hydrocarbon adsorbing materials. Under low temperatures, normally occurring during the first couple of minutes after engine start, hydrocarbons are adsorbed on the zeolite. These hydrocarbons are desorbed at increased temperatures. With a successful matching of a zeolite with a conventional oxidation catalyst, it is possible to control desorption and oxidation phenomena, so that almost no breakthrough of desorbed hydrocarbons occurs. The storage and release phenomena in real world conditions are quite complicated and usually affected by the presence of other exhaust species. For example, H O is also adsorbable in most zeolitic materials, thus competing with hydrocarbons for storage. A reasonable approach seems to be the employment of simple phenomenological models, keeping a small number of parameters that can be fitted to represent zeolite behavior under realistic conditions. NO x storage catalyst is a promising technology for GDI as well as diesel emission control. These catalysts are able to store NO x at a certain temperature range until they are saturated. This means that at specific time intervals the catalyst should be cleaned and restored to its original state. This regeneration is possible under rich operating conditions. During regeneration, the stored NO x is removed and reacts with reducing species (mainly CO). Obviously, a reliable simulation model could be very helpful to optimize the design and operation characteristics of such a system. However, it is generally agreed that this is a very challenging task. Only a few attempts have

been presented in the related literature. Again, the chemical phenomena taking place are not fully understood and therefore semiempirical approaches are employed in some modeling steps. Generally, there is an increasing interest in catalyst systems that are based on periodic storage and release of chemical species. This leads to an interest in an in-depth study of the main transient phenomena in order to develop reliable, yet practical mathematical models. In this paper the work that has been carried out on transient phenomena modeling is discussed. The problems for each catalyst type are separately presented and the respective modeling equations are briefly outlined. Selected modeling cases are illustrated by comparing simulation and experimental results. Finally, directions for future work are indicated. OXYGEN STORAGE IN CERIA Importance The 3-way catalytic converter, an indispensable device for the control of CO, HC and NO x emissions of spark-ignition engines, is a chemical reactor operating at highly transient conditions. The temperature, flow rate and composition of the exhaust gas flowing through the monolithic honeycomb converter change significantly according to the driving mode, with a typical time - scale of several seconds. At the same time, the closed loop control of the fuel management system induces further, more severe, transients of the feed gas composition with a typical time scale of less than a second. The latter effect is attributed to the interaction between the engine and the lambda sensor, which is used as a feedback control signal for the fuel injection system in order to ensure that a stoichiometric fuel-air mixture is supplied in the engine cylinders. However, the system s response lag (mainly attributed to the exhaust gas travel time and the sensor s response delay) causes the Air-to-Fuel ratio to oscillate around the stoichiometric value with the limit - cycle frequency of the control system. Since the beginning of the eighties, it has been recognized that the 3-way catalyst efficiency can be significantly affected when the composition of the feed gas is oscillating with different amplitudes and frequencies [3, 4, 5]). This behavior is mainly attributed to the ability of some washcoat components to be periodically oxidized and reduced depending on the exhaust gas redox environment. The advent of stricter US and European emission standards has increased the need for reliable 3-way catalytic converter models to support the design optimization of demanding exhaust systems with overall catalytic conversion exceeding 95% for all three main pollutants. A number of mathematical models working in this direction are already presented in the literature and employed in optimization procedures [6, 7, 8]. On the other hand, the research on the effect of oscillating has been restricted mainly to experimental studies with mostly empirical explanations of the results. In a number of previous papers, a modeling approach has been presented, aiming at the simulation of the transient adsorption, desorption and surface reactions occurring in a 3-way catalyst under oscillating conditions with simple gas mixtures [9, 1]. Such models are considered difficult to apply in realistic automotive conditions, where many interacting exhaust species are present and participating in numerous heterogeneous reactions. Phenomena modeling The most common washcoat component involved in dynamic oxidation - reduction phenomena is Ceria (CeO ). Ceria is normally present in high quantities in the washcoat (order of 3% w. or 1 g/ft 3 ) and has multiple functions: stabilization of the washcoat layer and improvement of thermal resistance, enhancement of precious metal catalytic activity and function as an oxygen storage component. The function of cerium as oxygen storage component is based on its ability to form both 3- and 4-valent oxides (11). Under net oxidizing conditions the following Ce oxide reaction is the most representative for the realization of oxygen storage: Ce O 3 + 1/ CeO (1) This reaction represents the storage of an oxygen atom by increasing the oxidation state of cerium oxide Ce O 3. On the other hand the CeO may function as an oxidizing agent of the exhaust gas species under net reducing conditions according to the following possible global reactions: CO + CeO Ce O 3 + CO () y y y C H + x y x+ CeO x + CeO3 + xco H O + (3) Each of the above reactions denotes the release of an oxygen atom, which is made available to react with a reducing species of the exhaust gas (CO or HC). For modeling purposes, we define the auxiliary number ψ as: ψ = x moles CeO x moles CeO + moles Ce O 3 (4)

which can be considered as fractional extent of oxidation of the oxygen storage component. The extent of oxidation is changing continuously during transient converter operation and is affected, among others, by the relative reaction rates of reactions () - (4). The rate of reaction () (oxidation rate) is expected to be proportional to the available active sites of reduced-state Cerium oxides, wh cap (1- -solid interface. The linear dependence on O concentration is considered as a realistic assumption. The oxidation reaction rate is thus: R ox = k ox (T) c s,o cap (1 - (5) where k ox is a characteristic rate constant, which exhibits an Arrhenius type dependence on temperature: k ox = A ox e E ox RT Analogous considerations are made for the reduction reactions rates. Here, the cap and should exhibit a dependence on the local CO and HC concentration, respectively: R red,co = k red,co (T) c CO cap (7) R red,hc = k red,hc (T) c HC cap (8) R red = R red,co + R red,hc (9) with k k A red, CO = red, CO A red, HC = red, HC e e E red RT E red RT d dt 1 = Ψ cap ( R R ) red ox 3 (6) (1) (11) ψ (1) which is solved numerically by the implicit Euler method for each node, along the catalyst channels. ratio oscillations In gasoline cars the conventional fuel management systems, the catalytic converter operates at periodically oscillating. The frequency and the width of the oscillation are determined by the response characteristics of the fuel management control loop. Several and often contradicting views have been expressed in the past, regarding the effect of the oscillation on catalyst efficiency. [1, 13, 14]. In the interesting review of Silveston [15] it is concluded that the periodic oscillations are beneficial during the cold start phase, when the catalyst operates at low temperatures, but they can be unfavorable at high temperature operation. However, we cannot consider the above statement as a general rule, since the operating parameters that determine the final effect are numerous and sometimes interacting with each other. These parameters are: Precious metal loading and composition Loading and dispersion of oxygen storage components Catalyst temperature Feed gas flow rate oscillation frequency oscillation amplitude Mean value of oscillation The number of these parameters can be even larger if we consider other possible forms of oscillation, e.g. with different times in the lean and rich region. The large number of possible combinations renders the problem of optimizing fuel management very difficult to solve. In practice, most of modern fuel management systems aim at keeping as close as possible to stoichiometry. However, given the capabilities offered by modern electronic control units, it is believed, that there exists a significant margin to optimize such systems, by exploiting oscillations. The importance of including the transient oxygen storage phenomena in 3-way catalyst simulations has been illustrated in a previous experimental and computational study [16]. The measured catalyst efficiency as function of for the three species of interest is presented in Figure 1a. It is interesting to note that the efficiency curves are all dependent on the direction to which the scan is performed. Specifically, the "window" is wider for CO and HC when shifting from lean to rich environment, whereas the contrary is observed for NO. During transition from lean to rich environment, the catalyst presents a higher activity for CO and HC, which can

be attributed to the previously stored oxygen. At the same time, the lower availability of CO and HC limits the NO conversion capability. The dynamic mathematical model was employed to simulate the above phenomena. Figure 1b presents the results of the simulation of the previously described scan test. It can be observed, that the model can successfully describe the catalyst efficiency as function of the. Furthermore, the model predicts the dependence of catalyst efficiency on the direction of the scanning. The same experiments were repeated by superimposing an oscillation (amplitude.9, frequency.5 Hz). The measured conversion efficiencies for the three species as functions of the mean value are presented in Figure a. We can remark the following: As in the case with no oscillation, the efficiency depends on the direction to which the scan is realized, although the "lag" here is smaller. oscillations result in higher CO and HC efficiencies for substoichiometric, which remain high in stoichiometry and oxygen abundance conditions. Especially, HCs are practically 1% converted in the whole scan range. However, CO efficiency at stoichiometry is 85-95%, compared to the 1% of the no oscillation case. The oscillation is clearly beneficial for NO conversion at lean operation and remains high in the rich region. At stoichiometry, the efficiency is significantly lower than 1%. The results of the mathematical model in the case of the above experiment are given in Figure b. In the same figure, we present the results of a simulation, without taking account of the dynamic submodels (oxygen storage and water gas reaction). In fact, the latter results describe the "quasi-steady" behavior of the catalyst. It is obvious, that the effects of the dynamic phenomena in this test are very important and actually favorable for catalyst efficiency. At the same time, we can observe that the model results compare well with the respective experimentally measured. Of course, an exact quantitative prediction was not expected, taking into account, that the assumptions underlying the dynamic submodels are rather simplistic, due to lack of sufficient kinetic studies in the field. 1 1 1 8 8 8 6 4 6 4 6 4 14.5 14.6 14.7 14.8 14.9 15. 15.1 15. 14.5 14.6 14.7 14.8 14.9 15. 15.1 15. 14.5 14.6 14.7 14.8 14.9 15. 15.1 15. CO HC NO x (a) 1 1 1 8 8 8 6 4 6 4 6 4 14.5 14.6 14.7 14.8 14.9 15. 15.1 15. 14.5 14.6 14.7 14.8 14.9 15. 15.1 15. 14.5 14.6 14.7 14.8 14.9 15. 15.1 15. CO HC NO x (b) Fig. 1 : Measured (a) and (b) catalyst conversion efficiency as function of during transition from lean to rich environment and vice-versa. 4

1 8 1 8 1 8 6 4 6 4 6 4 14.5 14.6 14.7 14.8 14.9 15. 15.1 15. 14.5 14.6 14.7 14.8 14.9 15. 15.1 15. 14.5 14.6 14.7 14.8 14.9 15. 15.1 15. CO HC NO x (a) 1 8 1 8 1 8 6 4 "quasi-steady simulation" 6 4 "quasi-steady simulation" 6 4 "quasi-steady simulation" 14.5 14.6 14.7 14.8 14.9 15. 15.1 15. 14.5 14.6 14.7 14.8 14.9 15. 15.1 15. 14.5 14.6 14.7 14.8 14.9 15. 15.1 15. CO HC NO x (b) Fig. : Measured and catalyst conversion efficiencies as functions of during scan with oscillation. Results of quasi - steady simulations are also presented. Transients in driving cycles During specific transient operation modes the control of most vehicles may shift instantaneously to the rich region, since the closed loop control cannot react infinitely fast. In this case, the oxygen stored in Ceria may prevent undesired CO breakthroughs. Figure 3 presents the CO emissions of a vehicle measured in the hot start part of the FTP cycle. In this part of the FTP test the catalyst is adequately warm (in this case appr. 4 C), therefore CO breakthroughs are only expected from rich transients. The rich spikes are easily recognized from the measured peaks in the inlet CO concentration. From the measurements presented in Figure 3a, it is obvious that most of the rich spikes are accompanied with CO emissions at catalyst exit. Interestingly, no CO breakthroughs are observed during the rich spikes at appr. 3 and 1 s. This part of the cycle has been also simulated by the 3-way catalyst modeling software, including the oxygen storage reactions. Figure 3b presents the CO concentration at catalyst exit, as well as the OSC filling level. Before examining the results, it should be stated that the accuracy of the simulation in transient phenomena strongly depends on the response of the analyzers used to measure inlet gas composition, which serve as model input. In general, the accuracy of the simulation is considered sufficient for this test case. It is interesting to note the model capability of predicting the occurrence of the CO breakthroughs and how they are correlated with the calculated oxygen storage filling level. The sudden increases of the OSC filling level are attributed to short duration fuel cuts, which are sufficient to fill up the catalyst with oxygen. For some period after the fuel cut, the catalyst is able to withstand the rich spikes (appr. 3 and 1 s). This behavior is well predicted by the model. This example illustrates the importance of managing the oxygen storage of the catalyst in order to avoid rich spikes breakthroughs, as well as the potential of modeling applications in this field. A recent research work [17] illustrated a methodology targeting at increasing catalyst efficiency during warmed up modes was based on forcing the engine to operate periodically for short periods slightly lean (approximately s lean excursions every 1 seconds of engine operation). This strategy resulted actually in higher catalyst efficiency during the extra-urban part of the European driving cycle. Our analysis presented here is in agreement and probably explains the behavior observed in this work [17]. 5

Fig.3: CO emissions in the hot start part of the FTP driving cycle. (a) experimental: measured inlet and outlet concentrations, (b) simulation: calculated outlet CO, OSC filling level. 6

HYDROCARBON STORAGE IN ZEOLITES Importance The HC adsorber (trap) is a promising technology to minimize the cold start HC emissions. The key component of such a system is the zeolite based HC adsorber catalyst, which is able to adsorb hydrocarbons at low temperatures. At higher temperatures the hydrocarbons are desorbed and subsequently oxidized in a downstream placed conventional 3-way catalyst. In the hybrid approach the catalyst for the oxidation reactions is mixed with the zeolite adsorber in the same monolith. A variety of HC trap configurations have been developed and evaluated in the last years [18, 19,, 1, ]. A basic problem faced by these systems is the undesired hydrocarbons breakthrough during the desorption phase. To avoid this, the downstream 3-way catalyst should be sufficiently warmed up before the HC adsorber exceeds the critical desorption temperature. A number of techniques have been proposed to overcome this problem. Flow management techniques seem to be more efficient compared to complex heat exchanger systems [18]. The exhaust gas flow through the adsorber should be maximized during the cold start phase. After the adsorber reaches the desorption temperature, the flow should be directed through the downstream catalyst. In the system presented in [3], this is achieved by creating a central passage in the adsorber ( barrel type adsorber) and managing the exhaust flow through the passage using a fluidic air diverter. In the system of [], the fluidic air diverter is dispensed of and the diameter of the central passage is experimentally optimized to attain best overall emission performance. In a more recent work, the central passage has been eliminated and the adsorber material has been modified to act simultaneously as a 3-way catalyst [4]. In this case, the adsorber is placed downstream the two 3-way catalyst bricks. A numerical study on the heat transfer phenomena in such systems (neglecting any reaction or adsorption phenomena) has been carried out by the authors [5]. In a more recent work [6], an extended mathematical model for the transport and reaction phenomena in a HC adsorber with by-pass hole has been presented. The experience gained so far indicates that the design optimization of such systems for real world applications relies on a large number of individual parameters including the geometry of individual monoliths, catalyst properties, additional air management, flow diversions etc. However, it is very difficult to attain significant emission reductions with by-pass adsorbers unless some modifications are made to the main catalyst, in order to accelerate its thermal response. Computational investigations illustrated that there are numerous options for main catalyst modifications, which should be very carefully optimized. On the other hand, hybrid systems are more promising for cold start HC reduction of gasoline cars. Hydrocarbon adsorption is also extensively applied to diesel exhaust emission control. Diesel exhaust is substantially colder than gasoline exhaust, especially at part load. This favours hydrocarbon adsorption for a relatively longer period after cold start. Typical washcoats of diesel catalysts include a zeolite adsorber together with an active precious metal, which acts as the promoter of the CO and HC oxidation reactions. The design of such a catalyst should ensure that there is no breakthrough of adsorbed HC s. This may occur when the HC desorption is initiated whereas the precious metal is not yet active for oxidation. Although modeling can be quite helpful in this task, only a few relative efforts have been presented in the literature so far [7, 8]. In a previous work, it has been shown that relatively simple reaction schemes are sufficient to describe the light-off and temperature - window behavior of precious metal diesel catalysts [9]. Recently, the application of a comprehensive mathematical model with HC and H O adsorption features has been illustrated in synthetic gas bench as well as real engine exhaust gas conditions [3]. Modeling In our modelling of adsorption in microporous zeolite, we followed the principles of the Polanyi adsorption theory, extended by Dubinin and Radushkevich [31]. According to this approach, the adsorbate in intimate contact with the solid is assumed to be in liquid form. The equation of the D-R isotherm gives the adsorbed mass at equilibrium x eq as function of temperature and partial pressure: ln p x eq ln ρ D, = ( W ) ln p RT D = A β (13) where W is the total volume of all micropores and A is a constant characteristic of the pore size distribution (both depend on the zeolite only). is the affinity coefficient, which depends on the adsorbate. ρ is the liquid phase density, p is the saturation pressure and p is the partial pressure of the adsorbate at the gas-solid interface. To predict the adsorption-desorption rates towards equilibrium, the commonly used linear driving force is employed: x R = = k t ( x x) eq (14) 7

where k is a rate constant, which is constant in case of adsorption (x<x eq ), but exhibits an exponential temperature dependence in case of desorption (x>x eq ). H O also interferes in the adsorption process, inhibiting HC adsorption in the zeolite [3, 33]. Water adsorption is also taken into account based on the same theory. An interesting feature of H O adsorption is the high amount of latent heat released during the process. The simulation of the adsorption of H O and two different HC species (decane, toluene) leads to a system of 3 differential equations for the adsorbed mass of each species versus time, which is solved by an implicit numerical procedure. Results The validity of the HC adsorption model presented above has been checked against measurements with synthetic gas, as well as real exhaust presented in [3]. An adsorption test was performed with synthetic gas containing only HC and H O. The catalyst was initially saturated by feeding the synthetic gas for about 5 s at 13 C. Afterwards, the inlet HC concentration was zeroed and the inlet temperature was gradually increased. Figure 4a presents the comparison between the measured and the HC (decane) concentration curves during the adsorption test with a standard diesel catalyst. In the first 5 s the catalyst is gradually saturated with decane with a characteristic asymptotic behavior, which is accurately predicted by the model, after the fitting of the related parameters (micropore volume, adsorption rate constant). In the desorption phase (time>5 s), the HC concentration at exit is initially low. By increasing the temperature, the desorption becomes faster and the HC concentration at exit increases up to a maximum value. Afterwards, due to the decreased availability of adsorbed decane in the catalyst, the desorption is slowed down, until it is totally completed. By fitting the respective model parameters (desorption kinetics), it is possible to obtain successful prediction of the above phenomena. To verify the physical relevance of the model, we checked it against the adsorption test performed with a catalyst identical to the standard one in all aspects except zeolite content (5% higher than the standard catalyst). Therefore, in the simulation of the second catalyst the only modification was the increase of the micropore volume by 5%. The results are presented in Figure 4b. Obviously, the model is able to predict with remarkable accuracy the expected response, when using larger zeolite amounts. E-3 Concentration [HC1] 1.6E-3 1.E-3 8E-4 4E-4 Inlet Outlet, experimental Outlet, Concentration [HC1] E-3 1.6E-3 1.E-3 8E-4 4E-4 4 6 8 1 Time [s] Inlet Outlet, experimental Outlet, 4 6 8 1 Time [s] Fig. 4: Measured vs- HC concentration at catalyst exit during a decane adsorption test. (a) standard catalyst, (b) catalyst with 5% higher zeolite content compared to standard case [3] 8

15 Inlet HC concentration [ppm] 15 1 75 5 Outlet, experimental Outlet, 5 1 3 4 5 Time [s] Fig 5: Experimentally measured and instantaneous HC emissions in the MVEG driving cycle (first 4 s) The main goal of a realistic catalyst model is to predict the catalyst performance under real world conditions. The measurements carried out on a car driven on a legislated driving cycle (MVEG) were employed to assess the capabilities of the adsorption model. A common problem encountered in such simulation problems regards the knowledge of the hydrocarbon speciation of the exhaust gas. Only a portion of the total exhaust hydrocarbons participates in the adsorption and desorption phenomena. Moreover, the adsorbable HC molecules present in the exhaust do not have exactly the same adsorption properties. Therefore, it is meaningful to consider four different HC species: Usually decane and toluene represent the adsorbable species, with decane being keener to adsorption even at higher temperatures. Propene and propane represent the non-adsorbable species, while propane represents further the slow oxidizing hydrocarbons. Apparently, the success of a diesel catalyst simulation will strongly depend on the knowledge of HC speciation of the real exhaust. Figure 5 illustrates the agreement between measured and instantaneous HC emissions before and after the catalyst in the first 5 seconds of the european driving cycle. The model is able to predict successfully the HC efficiency due to adsorption taking place during the first seconds, as well as the HC oxidation after the warm-up phase. The above results indicate that even with a large number of simplifications and assumptions, it is possible to construct efficient mathematical models that can be used in exhaust system optimization tasks. In any case, these models rely on a small number of parameters that need to be determined by a small number of simple laboratory tests. NO X STORAGE Importance NO x storage is the state-of-the-art solution for emission control of lean burn GDI engines. They are also promising candidates for future diesel engine aftertreatment, both for passenger car and heavy-duty applications. Therefore, there is an increasing interest in the investigations and applications of such systems. CAE is expected to provide substantial aid to the emissions engineer, since the design parameters engaged are increased and the complexities introduced are difficult to solve empirically. More specifically, the following features of the NO x storage catalyst (NSC) system could be pointed out: NO x is stored in the form of nitrate on the storage species (usually Ba), which is included in the catalyst washcoat. Precious metals are known to be necessary in the storage process (most probably needed to oxidize NO to NO ) [34]. the catalyst should regenerate periodically by rich engine operation. The possible regeneration strategies are numerous and the parameters involved difficult to optimize (driveability, fuel consumption and catalyst efficiency should be optimized). Usually, empirical experimental methods are used to find the best possible strategy (lean/rich cycling) at specified operating conditions. contrary to the 3-WCC, the NSC exhibits a "temperature window" behavior, which requires careful thermal control of the catalyst over a wide range of engine operating conditions. Limited efforts regarding the modeling of the NO x storage catalyst have appeared in the known literature. Phenomenological models for engine control optimization have been presented in [35, 36]. A more detailed one-dimensional reactor model consisting of mass balances for the bulk gas and the catalyst washcoat has been presented in [37]. Phenomena reactions - modeling 9

The main difficulties in the development of a mathematical model are related to the lack of a universally accepted theory for the mechanisms and kinetics governing the operation of the NO x trap. A main purpose is to find the best compromise between model simplicity (applicability) and prediction capabilities. Unlike most other catalyst types, the operation of the NO x trap is largely governed by the thermodynamic limitations of various reactions (mainly the oxidation of NO and the storage of NO x ). The difficulty that arises here is the uncertainty of the thermochemical properties of the storage component, since the exact form of the storage component itself is not perfectly known. As a first approximation, we consider that the thermochemical properties of the storage component are represented by those of BaCO 3. The main features of the modeling approach presented here, are the following: NO->NO reversible oxidation (kinetically & thermodynamically controlled) NO and NO storage (kinetically & thermodynamically controlled) Ba(NO 3 ) regeneration is effected predominantly with CO Since NO x storage catalysts typically contain one or more of the Platinum Group Metals as well as oxygen storage components, the reactions of the 3-way catalyst model should also be accounted for in the NO x storage catalyst model. Especially interesting is the contribution of the oxygen storage/release phenomena during regeneration. During the NO x storage phase, the abundance of oxygen in the exhaust will probably lead to "saturation" of the oxygen storage. Switching to rich mode for regeneration, the stored oxygen will tend to react with the reducing species entering the catalyst, mainly CO. This reaction will probably consume a significant amount of the reducing species available for catalyst regeneration and thus limit the regeneration efficiency. NO x trap mechanism For modelling purposes, the NO x trap and regeneration mechanism could be adequately described by the following apparent reaction scheme and the respective reaction rates: 3 3 3 CO 1. BaCO NO O Ba( NO ) RT + + +, R = A1 e c c Ψ ψ Eq1. 1 BaCO 3 NO + O Ba( NO3) + CO R E 1 1 NO O cap BaCO3 E A e cno c O cap ψ BaCO3 RT +, = Ψ Ba ( NO + NO 3) CO BaCO R 3. + RT 3, 3 = 3 CO Ψcap Ba( NO3 ) 3 where cap is the storage capacity in moles Ba /m 3, Ba(NO3) is the percentage of storage capacity in the chemical state of Ba(NO 3 ) and BaCO3 is the percentage of storage capacity in the chemical state of BaCO 3. The above reaction rate expressions are built, based on the following assumptions: Eq exponential dependency on temperature A e E 3 linear dependency on the gas phase reacting species concentrations c the saturation extent of the storage component acts as a linear driving force (the rate is proportional to the available active storage sites) the rate is adjusted to take into account thermodynamic equilibrium of the reactions. Thus, the reaction rate at equilibrium conditions is zeroed. Near equilibrium, the rate is adjusted by the parameters Eq I, as given in the reaction rate expressions. Taking as an example reaction : = 1 K p ( T ) c c NO CO c 1 O K p (T) is the thermodynamic equilibrium constant of the reaction. Although storage of nitrogen monoxide is observed experimentally, the exact mechanism is not clear. In the above, indicative reaction scheme, we assumed storage of NO in the form of Barium nitrate. However, other mechanisms of NO storage (e.g. reaction with Ceria) could also be likely. At this early stage, the storage reaction scheme could mostly be phenomenological. The reaction scheme of the NOx storage catalyst includes also all the reactions applicable to noble metal de-nox catalysts as described in a previous publication [9] (oxidation of CO, H, HC, reversible oxidation of NO to NO, reaction of HC with NO ). To summarize, the NOx efficiency during the storage phase in this type of catalysts is governed by the following phenomena: Oxidation of NO to NO : This reaction is kinetically controlled at low temperatures (up to ~5 C). At higher temperatures the reaction is controlled by the chemical equilibrium, which limits the NO formation. 1 ψ Eq Eq

Reaction of HC with NO : This reaction is kinetically controlled at low temperatures. At higher temperatures this reaction is mainly limited by the low availability of hydrocarbons due to the competitive HC oxidation, which becomes important above the HC light-off temperature. Storage of NO on Barium carbonate: At lower temperatures, this reaction seems to be governed mainly by the availability of NO. At temperatures above ~4 C the storage reaction is limited by the chemical equilibrium. Storage of NO: As mentioned above, the mechanism of NO storage is not perfectly clear. However, NO storage is observed even at low temperatures (~1 C). However, the amount of the NO storage does not seem to be critical on the overall behavior of NO x storage catalysts in real world conditions. Results To illustrate the predictive capabilities of the NOx adsorption model the experimental data presented in [38] are exploited for validation purposes. These data refer to a storage experiment carried out at lean conditions (corresponding to =1.5), which follows a catalyst pre-treatment with pure nitrogen. The saturation process of the catalyst is monitored in terms of NO x removal efficiency vs time at different temperatures. The kinetic parameters of the model have been fitted to represent the catalyst behavior. Figure 6 shows that the model can adequately predict and explain the NOx storage behavior for the fresh catalyst. More specifically, at C feed gas temperature, most of the NOx efficiency is due to the so-called "de-nox" reaction with hydrocarbons. At 3 C the de-nox reaction is obviously less important due to the low HC availability and the storage reaction proceeds fast, since this temperature is favourable for NO formation as well as the storage reaction equilibria. At 4 C the de-nox reaction is almost negligible. A limited NOx adsorption is observed at the first 1s of this test. A possible explanation of this behavior as predicted by the model is the following: The catalyst temperature at the beginning of this test is marginally adequately low to allow the storage process. However, as the time proceeds, the oxidation of hydrocarbons in the catalyst induce a significant exothermal heat release which gradually increases the catalyst temperature by up to ~5 C. Thus, the catalyst temperature after ~1s reaches a value that no longer favours the storage reaction. 1 1% Efficiency.9.8.7.6.5.4.3..1 1 3 4 5 6 Time [s] C measured 3 C measured 4 C measured C 3 C 4 C NOx storage [% of maximum] 9% 8% 7% 6% 5% 4% C 3% 3 C % 1% 4 C % 1 3 4 5 6 Time [s] (a) (b) Fig. 6: (a) Measured [38] versus NOx efficiency data for a fresh NOx storage catalyst. (b) Computed amount of stored NO x. Figure 7 presents the respective results for an hydrothermally aged catalyst. To simulate the aged catalyst, it is assumed that the total availability/accessibility of the storage component has been reduced by % whereas the active surface area of the noble metals contributing to the different reactions has been reduced by an order of magnitude. Based on these rough approximations the simulation shows that the major trends observed in the aged catalyst behavior can be predicted. The simulation results deviate significantly only for the C case. Work is still in progress on the investigation of the different storage mechanisms to refine the reaction scheme. 11

Efficiency 1.9.8.7.6.5.4.3..1 C measured 3 C measured 4 C measured C 3 C 4 C NOx storage [% of maximum] 1% 9% 8% 7% 6% 5% 4% 3% % 1% C 3 C 4 C 1 3 4 5 6 Time [s] % 1 3 4 5 6 Time [s] (a) (b) Fig. 7: Measured [38] versus NOx efficiency data for an aged NOx storage catalyst.. CONCLUSIONS Some years ago, the optimization work in catalytic exhaust aftertreatment was mainly aimed at: increasing the catalyst activity by optimizing the catalytic materials and washcoat technology bringing the catalyst as quickly as possible to its operating temperature (thermal response problem), maintaining high stability and durability of the catalyst Today, the achievement of ultra low emission levels for modern vehicles necessitates the use of even more sophisticated systems, which also benefit from the storage and release of chemical species on the catalyst surface. Interestingly, this approach is met in almost all catalytic control devices ranging from 3-way catalysts and diesel catalysts to HC adsorbers and NO x traps for GDI and diesel engines. Reliable and practical mathematical models of the main transient physic-chemical phenomena are expected to support substantially the management and optimum utilization of the different storage and release phenomena. The benefits of oxygen storage properties of the 3-way catalyst are already well documented. However, in view of the future near zero emission standards, marginal optimizations may be possible by carefully managing the oxygen storage filling level of the catalyst. The results presented in this paper seem to support this direction. The latest advances in fuel management technologies offer large capabilities towards this direction. The need to further develop oxygen storage models and define methodologies to characterize the kinetic parameters of the related processes is not fully solved. One of the main reasons is the finite time response of conventional exhaust gas analysis equipment, which is usually insufficient for detailed studies of fast transient phenomena. Hydrocarbon adsorption tends to become common practice for diesel emission control, since adsorption phenomena are favored by the low exhaust gas temperatures of the diesel engine. Nevertheless, the process needs careful control, in order to combine adsorption and oxidation phenomena, avoiding HC breakthroughs due to early desorption. The problem is more difficult with HC traps for gasoline engines, due to the higher temperature levels. The difficulties in describing the physical mechanisms are numerous: HC speciation depends on the driving mode, complex interactions between HC and H O, non-ideal adsorption conditions in complex exhaust gas. Therefore, theoretical models such as the adsorption isotherms of Dubinin-Radushkevic can only be viewed as a starting point towards the development of a practical numerical model that will be based on tunable parameters. The results presented here indicate that this approach is promising, although more validation tests would be necessary to draw clear conclusions. NO x storage is probably the most challenging emission control technology, due to the large number of design parameters that affect the overall performance. On the other hand, the developments on the understanding and characterizing the kinetics of the NO x storage catalyst in real exhaust conditions are still in an early stage. Nevertheless, engineering models with rough approximations in the reaction kinetics may still be quite useful in the design process. Further research work will be necessary on the improvement of the reaction understanding and modelling, as well as the study of the effect of SO poisoning on the NO x storage catalyst performance. NOTATION 1

Variables 3WCC 3 way catalytic converter A reaction rate constant, pore size distribution constant (zeolites) c species concentration, mole fraction D Parameter used in the adsorption isotherm HC Hydrocarbon k Rate constant used in the adsorption model k ox oxidation rate constant, mole/m 3 s k red reduction rate constant, mole/m 3 s K p chemical equilibrium constant p, p Pressure, saturation pressure of adsorbate R reaction rate or gas constant, mole/m s or J/mole K t time, s T temperature, K W Zeolite capacity [m 3 ] x Adsorbed mass of adsorbate in zeolite Greek letters β Affinity coefficient of adsorbate ρ Density of the liquid phase of the adsorbate [kg/m 3 ] Ψ Oxygen storage capacity cap ψ oxidation fraction Subscripts Cap Eq k ox red s capacity equilibrium indication of reaction k (Equations) Oxidation Reduction Solid REFERENCES 1 Oh S. H. and Cavendish J. C., Transients of Monolithic Catalytic Converters: Response to Step Changes in Feedstream Temperature as Related to Controlling Automobile Emissions, Ind. Eng. Chem. Prod. Res. Dev., 198, 1, 9-37. Voltz S. E., Morgan C. R., Liederman D, Jacob S. M., Ind. Eng. Chem. Prod. Res. Dev., 1973, 1, 94. 3 Shulman M. A., Hamburg D. R., Throop M. J., "Comparison of Measured and Predicted Three-way Catalyst Conversion Efficiencies Under Dynamic Air-fuel Ratio Conditions", SAE paper 876, 198 4 Herz R. K., Klela J. B., Sell J. A., "Dynamic Behavior of Automotive Catalysts.. Carbon Monoxide Conversion under Transient Air/Fuel Ratio Conditions", Ind. Eng. Chem. Prod. Res. Dev.,, 387-396, 1983 5 Matsunaga Schin-ichi, Yokota K., Muraki H., Fujitani Y., "Improvement of Engine Emissions Over Three-Way catalyst by the Periodic Operations", SAE paper 8798, 1987. 6 Oh S. H., Cavendish J. C., "Mathematical Modeling of Catalytic Converter Lightoff - Part III: Prediction of Vehicle Exhaust Emissions and Parametric Analysis", AIChE Journal, Vol. 31, No. 6, 1985. 7, Dubien C., Schweich D., Mabilon G., Martin B., Prigent M., «Three-way catalytic converter modeling: fast- and slow-oxidizing hydrocarbons, inhibiting species, and steam-reforming reaction», Chemical Engineering Science, Vol. 53, No. 3, pp. 471-481, 1998. 13

8 Koltsakis G. C., Konstantinidis P. A., Stamatelos A. M., Development and Application range of mathematical Models for 3-way Catalytic Converters, Applied Catalysis B: Environmental 1 (1997) 161-191. 9 Racine B. N., Herz R. K., Modeling dynamic CO oxidation over Pt/Al O 3 : Effects of Intrapellet diffusion and Site Heterogeneity, Journal of Catalysis, 137, 158 (199) 1 Hoebink J. H B. J., Nievergeld A. J. L., Marin G. B., CO oxidation in a fixed bed reactor with high frequency cycling of the feed, Chemical Engineering Science 54 (1999) 4459-4468. 11 Herz R. K. 'Dynamic behavior of automotive catalysts. 1. Catalyst oxidation and reduction' Ind. Eng. Chem. Prod. Res. Dev., 451-457 (1981) 1 Cho B. K., Performance of Pt/Al O 3 Catalysts in Automobile Engine Exhaust with Oscillatory Air/Fuel Ratio, Ind. Eng. Chem. Res. 1988, 7, 3-36. 13 Shinjoh H., Muraki H. Fujitani Y., Periodic operation effects in propane and propylene oxidation over noble metal catalysts, Appl. Catal., 49, 195-4, 1989. 14 Skoglundh M., Thormahlen P., Fridell E., Hajbolouri F., Jobson E., Improved light-off performance by using transient gas compositions in the catalytic treatment of car exhausts, Chemical Engineering Science 54 (1999) 4559-4566. 15 Silveston P. L., Automotive Exhaust Catalysis: Is Periodic Operation Beneficial?, Chem. Eng. Sci., Vol. 51, No. 1, pp. 419-46, 1996. 16 Koltsakis G. C. and Stamatelos A. M., Modeling Dynamic Phenomena in 3-way catalytic converters, Chemical Engineering Science 54 (1999) 4567-4578. 17 Campbell B., Farrington R., Inman G., Dinsdale S., Gregory D., Eade D., Kisenyi J., Improved Three-Way Catalyst Performance Using an Active Bias Control Regeneration System, SAE paper -1-499,. 18 Hochmuth J. K., Burk P. L., Tolentino C., Mignano M. J., 1993, Hydrocarbon Traps for Controlling Cold Start Emissions, SAE paper 93739. 19 Abthoff J., Kemmler R., Klein H., Matt M., Robota H.J., Wolsing W., Wiehl J., Dunne S.R., 1998, Application of In-Line Hydrocarbon Adsorber Systems, SAE paper 984. Noda N., Takahashi A., Shibagaki Y., Mizuno H., In-Line Hydrocarbon Adsorber for Cold Start Emissions Part II, SAE paper 9843 (1998) 1 Patil M. D., Peng L. Y., Morse K. E., 1998, Airless In-Line Adsorber System for Reducing Cold Start HC Emissions, SAE paper 98419. Silver R. G., Dou D., Kirby C.W., Richmond R.P., Balland J., Dunne S., 1997, A Durable In-Line Hydrocarbon Adsorber for Reduced Cold Start Exhaust Emissions, SAE paper 97843. 3 Buhrmaster C.L., Locker R. J., Patil M. D., Nagel J. N., Socha L. S., 1997, Evaluation of In-Line Adsorber Technology, SAE paper 9767. 4 Noda N., Mizuno H., Suzuki J., Hiramatsu T., Busch P., In-Line Hydrocarbon Adsorber, SAE paper 1999-1-13 (1999) 5 Koltsakis G. C. and Stamatelos A. M., Thermal Response of Automotive Hydrocarbon Adsorber Systems, Transactions of the ASME: Journal of Gas Turbines and Power, Vol. 1, pp.11-118. 6 Koltsakis G. C. and Stamatelos A. M., Modeling of Hydrocarbon Trap Systems, SAE paper -1-655,. 7 Ansell G., Bennet P., Cox J., Frost J., Gray P., Jones A., Rajaram R., Walker A., Litorell M. and G. Smedler, "The development of a model capable of predicting diesel lean NO x catalyst performance under transient conditions", Applied Catalysis B: Environmental, 1, pp. 183-1, 1996. 8 Wilber R. A., Boehman A. L., Numerical Modeling of the Reduction of Nitric Oxide by Ethylene over Cu-ZSM-5 under lean conditions, Catalysis Today 5 (1999) 15-13. 9 Kandylas I.P., Koltsakis G.C., Stamatelos A.M, Mathematical Modelling of Precious Metals Catalytic Converters for Diesel NO x Reduction, Proceedings of the Institution of Mechanical Engineers, Journal of Automobile Engineering, Vol. 13 (1999), pp. 79-9. 3 Pontikakis G. N., Koltsakis G. C., Stamatelos A. M., Noirot R., Agliany Y., Colas H., Versaevel Ph., Bourgeois C., Experimental and Modeling Study on Zeolite Catalysts for Diesel Engines, Catalysis and Automotive Pollution Control 5, Brussels,. 31 Thomas K. M. and Thomas W. J., Principles and Practice of Heterogeneous Catalysis (VCH Verlagsgesellschaft mbh, Weinheim, Germany), 1997. 3 Otto K., Montreuil C. N., Todor O., McCabe R. W., Gandhi H. S., Adsorption of Hydrocarbons and Other Exhaust Components on Silicalite, Ind. Eng. Chem. Res. (1991), 3, 333-34. 14

33 Lafyatis D. S., Ansell G. P., Bennett S. C., Frost J. C., Millington P. J., Rajaram R. R., Walker A.P., Ballinger T. H., Ambient temperature light-off for automobile emission control, Applied Catalysis B: Environmental 18 (1998) 13-135. 34 Fridell E., Skoglundh M., Westerberg B., Johansson S., Smedler G., NOx Storage in Barium-Containing Catalysts, Journal of Catalysis 183, 196-9 (1999). 35 Larsson M, Andersson L., Fast O., Litorell M., Makuie R., NOx Trap Control by Physically Based Model, SAE paper 1999-1- 353, 1999. 36 Ketti-Cheriff A., von Visssel D., Beurthey S., Sorine M., Modeling and Control of a NOx Trap Catalyst, SAE paper -1-1199,. 37 Hepburn J., Kenney T., McKenzie J., Thanasiu E., Dearth M., Engine and Aftertreatment Modeling for Gasoline Direct Injection, SAE paper 98596, 1998. 38 Bailey O. H., Dou D., Denison G. W., "Regeneration Strategies for NOx Adsorber Catalysts", SAE paper 97845, 1997. 15