Particle Emissions and Soot Reactivity using Renewable Fuels in a Diesel Engine

Introduction\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 The Internal combustion engine is a well-established technology for transportation of people and goods. Due to the global warming effect, fossil fuels need to be replaced by renewable fuels. Moreover, local emissions and especially particulate emissions pose serious concerns because of the associated health issues. The particulate matter (PM) emitted by the engine is efficiently trapped in the Diesel Particulate Filter (DPF). However, the performance of the DPF depends on the characteristics of the PM emissions which in turn, depends on the properties of the fuel used. The characterization of the PM emissions is important to understand the performance of exhaust gas aftertreatment system (EATS) as well as the contribution to health issues.Experimental Setup\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 In this experimental study, a methodology was developed to sample PM from the exhaust flow. By controlling the evaporation of volatile components in an upstream oxidation catalyst, the solid particles were captured in a miniaturized diesel particulate filter (DPF). The sampling flow was high in order to enable short engine operation. The captured PM was subsequently oxidized using O2 and NO2 in order to extract the soot reactivity. By running a heavy-duty diesel engine using different fuels, both the particle size distribution and the soot reactivity could be compared. The results presented here compares traditional diesel fuel and an oxygenated fuel (5% oxygen). The oxygenated fuel was a mixture of Propylheptanol (46%), HVO (34%) and diesel fuel (20%). Both fuels had the same cetane number and very similar combustion.ResultsThe soot reactivity was similar when oxidized by NO2 (passive regeneration) whereas the reactivity with O2 (active regeneration) was higher for the oxygenated fuel. This can be attributed to the smaller particles and higher surface area.Conclusions\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 By capturing PM in a mini-DPF and oxidizing in a controlled way, useful information about the PM emissions was obtained. This type of information is very useful when evaluating renewable fuels to be used in the future

Ethics in Automotive Engineering

The need for reflecting engineers that can deal with ethical dilemmas are increasingly important. In the automotive field, the “diesel gate” in 2015[1] has put the ethical aspect in focus. However, this scandal can be explained by a consequence of (bad) political decisions and (insufficient) technological development. The dilemma for the students (and the society as well) is that these problems are complex and that there are no clear “right or wrong”. Nevertheless, no matter how difficult the problem, ethical dilemmas will need to be dealt with and the future engineers from Chalmers can contribute to a more (ethically) sustainable future.In the master’s program Automotive Engineering (MPAUT), the course in Internal Combustion Engines (MTF240) is used as the platform for practice in ethical reflections. With central support (from Karl Fine de Licht), the “applied ethics” approach is implemented using a bottom-up approach, working with a hypothetical but realistic ethical dilemma. The TLA consists of one lecture and one assignment. By applying a “generic model for critical thinking on ethical issues”, the students write a small assignment (two by two) within the course.The students perform reasonably well, and the correction of the PMs is not very rigorous. In the future, the assessment may need to be more stringent as well as the lecture and instruction also need to be continuously improved. The course evaluations are generally positive (however not excellent, average 4.0) and the students are not used to this kind of assignment. However, it’s very interesting and rewarding (as a teacher) to read the students reflections and even if their ethical reflection skills are not very advanced, the reflection exercise is hopefully a valuable experience in their future career. \ua0\ua0\ua0[1] https://en.wikipedia.org/wiki/Volkswagen_emissions_scanda

Transient Flow Uniformity Evolution in Realistic Exhaust Gas Aftertreatment Systems using 3D-CFD

To precisely control a vehicle powertrain to minimize emissions, accurate and detailed models are needed to capture the spatio-temporal variability of the variables of interest. The aim of this work is to analyze flow and temperature fields in a geometrically realistic —\ua0and thus complex\ua0— exhaust gas aftertreatment system under transient conditions. The spatio-temporal response of these fields to upstream step changes is predicted using three-dimensional unsteady Reynolds-averaged Navier-Stokes (URANS) κ- ω simulations where the catalytic converter is described as a porous medium. A catalytic converter geometry with a 90∘-bend and a partially dead volume is used to demonstrate the effects of time-resolved flow maldistribution on the profiles of velocity and temperature. Two sets of transient simulations in terms of step changes in velocity and temperature are performed. Uniformity indices are used to characterize the distribution and variability of the different catalyst channels under transient conditions. The evolution of the uniformity indices as functions of time and axial distance into the catalyst are calculated at different cross-sectional planes. The results show that the evolution of the temperature uniformity is rate controlling, continuously modulating the otherwise much faster flow uniformity response via the fluid properties. The temperature uniformity time scale is determined by the balance of flow, thermal inertia, and the heat losses from the system. The interplay between pressure drop and heat losses governs the transition to the new steady state in uniformity. These types of transient simulations and analyses can contribute essential information when developing reduced-order engineering models to represent the spatio-temporal variability in exhaust aftertreatment systems, in particular during rapid events such as cold start

A reactor-scale CFD model of soot formation during high-temperature pyrolysis and gasification of biomass

Soot generation is an important problem in high-temperature biomass gasification, which results in both air pollution and the contamination of gasification equipment. Due to the complex nature of biomass materials and the soot formation process, it is still a challenge to fully understand and describe the mechanisms of tar evolution and soot generation at the reactor scale. This knowledge gap thus motivates the development of a comprehensive computational fluid dynamics (CFD) soot formation algorithm for biomass gasification, where the soot precursor is modeled using a component-based pyrolysis framework to distinguish cellulose, hemicellulose and lignin. The model is first validated with pyrolysis experiments from different research groups, after which the soot generation during biomass steam gasification in a drop-tube furnace is studied under different operating temperatures (900–1200 \ub0C) and steam/biomass ratios. Compared with the predictions based on a detailed tar conversion model, the current algorithm captures the soot generation more reasonably although a simplified tar model is used. Besides, the influence of biomass lignin content and the impact of tar and soot consumptions on the soot yield is quantitatively studied. Moreover, the impact of surface growth on soot formation is also discussed. The current work demonstrates the feasibility of the coupled multiphase flow algorithm in the prediction of soot formation during biomass gasification with strong heat/mass transfer effects. In conclusion, the model is thus a useful tool for the analysis and optimization of industrial-scaled biomass gasification

A Control-Oriented Spatially Resolved Thermal Model of the Three-Way-Catalyst

The three-way-catalyst (TWC) is an essential part of the exhaust aftertreatment system in spark-ignited powertrains, converting nearly all toxic emissions to harmless gasses. The TWC’s conversion efficiency is significantly temperature-dependent, and cold-starts can be the dominating source of emissions for vehicles with frequent start/stops (e.g. hybrid vehicles). In this paper we develop a thermal TWC model and calibrate it with experimental data. Due to the few number of state variables the model is well suited for fast offline simulation as well as subsequent on-line control, for instance using non-linear state-feedback or explicit MPC. Using the model could allow an on-line controller to more optimally adjust the engine ignition timing, the power in an electric catalyst pre-heater, and/or the power split ratio in a hybrid vehicle when the catalyst is not completely hot. The model uses a physics-based approach and resolves both axial and radial temperature gradients, allowing for the thermal transients seen during heat-up to be represented far more accurately than conventional scalar (i.e. lumped-temperature) real-time models. Furthermore, we also use a physics-based chemical kinetics reaction model for computing the exothermic heat of reaction and emission conversion rate which is temperature and residence-time-dependent. We have performed an experimental campaign with a standard spark-ignited engine and a commercial TWC, where we measured steady-state operation and cold-start transient behavior. This experimental data allowed us to tune the model, where we found excellent matching between the measured and modeled tailpipe emissions. Modeling the radial temperature gradient improved the relative accuracy of the conversion efficiency by 15%, and simulations indicate the potential for an absolute improvement by 15 percentage points for some cases. Furthermore, the modeled TWC temperature evolution for a cold-start was typically within \ub110 \ub0 C of the measured temperature (with a maximal deviation of 20 \ub0C). The proposed model thus bridges a gap between heuristic models suited for on-line control and accurate models for slower off-line simulation

Numerical Assessment of Flow Pulsation Effects on Reactant Conversion in Automotive Monolithic Reactors

Highly transient engine-out emissions imply significant challenges for the optimization and control of automotive aftertreatment systems, motivating studies of the effects of flow pulsations on the system behavior. In this work, an axisymmetric aftertreatment system with a first-order reaction in the monolith section is chosen to demonstrate the role of pulsations on the time-averaged conversion at the exit. Reactive computational fluid dynamics simulations under transient conditions are performed by applying the SST\ua0k-ω\ua0turbulence model along with a reactant species balance equation and a porous medium description of the catalyst. Four different types of temporal velocity variations (constant, step-like, sawtooth and sinusoidal) are applied at the inlet. Additionally, the corresponding fluctuations driven by a prescribed inlet pressure are also investigated. It was found that the fluctuations in the incoming flow affect the transient response of the monolith, the time-averaged conversion, the evolution of the flow uniformity index and the dispersion downstream of the catalyst. It is also shown that the retention time distribution is modulated by the pulsations and that the mixed-cup conversion span is different for geometrically identical systems having the same velocity span if the fluctuation characteristics are different. In conclusion, simulations of phenomena that depend on time-resolved boundary conditions from experiments require proper characterization of fluctuations present in the real-world systems; otherwise, the method of recreating the signal at the boundary may influence the obtained results

Cold-Start Modeling and On-Line Optimal Control of the Three-Way Catalyst

We present a three-way catalyst (TWC) cold-start model, calibrate the model based on experimental data from multiple operating points, and use the model to generate a Pareto-optimal cold-start controller suitable for implementation in standard engine control unit hardware. The TWC model is an extension of a previously presented physics-based model that predicts carbon monoxide, hydrocarbon, and nitrogen oxides tailpipe emissions. The model axially and radially resolves the temperatures in the monolith using very few state variables, thus allowing for use with control-policy based optimal control methods. In this paper, we extend the model to allow for variable axial discretization lengths, include the heat of reaction from hydrogen gas generated from the combustion engine, and reformulate the model parameters to be expressed in conventional units. We experimentally measured the temperature and emission evolution for cold-starts with ten different engine load points, which was subsequently used to tune the model parameters (e.g. chemical reaction rates, specific heats, and thermal resistances). The simulated cumulative tailpipe emission modeling error was found to be typically − 20% to + 80% of the measured emissions. We have constructed and simulated the performance of a Pareto-optimal controller using this model that balances fuel efficiency and the cumulative emissions of each individual species. A benchmark of the optimal controller with a conventional cold-start strategy shows the potential for reducing the cold-start emissions

A unified framework for online trip destination prediction

Trip destination prediction is an area of increasing importance in many applications such as trip planning, autonomous driving and electric vehicles. Even though this problem could be naturally addressed in an online learning paradigm where data is arriving in a sequential fashion, the majority of research has rather considered the offline setting. In this paper, we present a unified framework for trip destination prediction in an online setting, which is suitable for both online training and online prediction. For this purpose, we develop two clustering algorithms and integrate them within two online prediction models for this problem. We investigate the different configurations of clustering algorithms and prediction models on a real-world dataset. We demonstrate that both the clustering and the entire framework yield consistent results compared to the offline setting. Finally, we propose a novel regret metric for evaluating the entire online framework in comparison to its offline counterpart. This metric makes it possible to relate the source of erroneous predictions to either the clustering or the prediction model. Using this metric, we show that the proposed methods converge to a probability distribution resembling the true underlying distribution with a lower regret than all of the baselines

Light my fire but don’t choke on the smoke: Wellbeing and pollution from fireplace use in Sweden

Fireplaces are popular in Northern Europe. However, particle emissions from fireplaces have been identified as an environmental problem and a health problem. User behaviors affect particle emissions and the success of particle reducing technologies to a large extent. This interdisciplinary study aims to investigate why and how people use their fireplaces, including what emotions people associate with fire, and their interest in learning more about fire making and changing behavior related to fire making. It does so by applying an emotion regulation model in a novel way. In total, 146 Swedish individuals owning a fireplace (the majority had wood stoves, a few had tiled stoves, boilers or other types of fireplaces) participated in an online questionnaire about motives, behaviors, knowledge, and interest in learning and changing behavior. The most common motives for using a fireplace in this sample were complementary heating and “cozy fire making”. Our results suggest that watching a fire can aid in regulating emotions from unpleasant stress towards joy and provide a pleasant atmosphere for socialization, and that wood fuel may be a preferred complementary energy choice because it provides beautiful light, comfortable warmth, beautiful design and safety. People reporting emotional motives for using a fireplace also reported an interest in changing behavior

Robust parameter estimation methodology for heterogeneous catalytic reactors

Modeling of Exhaust-Gas Aftertreatment Systems is an important tool for improved understanding and thus improved performance and durability. The challenges for accurate modeling of the multi-scale reactor are many and one important challenge is the interplay between mass transfer and kinetics. Although intrinsic kinetics (without effects from mass transfer) are possible to obtain by analysis of the washcoat separately, many challenges (e.g. washcoat distribution, ageing effects) are best studied using the monolith reactor structure.In this study, a 1+1D diesel oxidation catalyst model was tuned to synthetic catalyst activity test (SCAT) bench data using a robust parameter estimation algorithm based on response surface methodology (RSM). The final residuals (SSE) were compared with experimental uncertainties to enable a statistical F-test to assess the model fit. Two different design of experiment (DoE) design matrices were compared to evaluate potential interaction effects between parameters. While the choice of DoE had different benefits, problems with each design could easily be circumvented.Several parameter estimation cases were compared to investigate the importance of some key algorithm choices:(a) the choice of a weight function for the residual calculation. A weight function sensitive to the experimental observation distribution obtained different fits with different parameter sets.(b) The importance of carefully designed experimental observations. Simulations with catalysts containing an inert washcoat layer proved invaluable for tuning of internal mass transfer coefficients.(c) The importance of experimentally measured constants as initial guesses. The use of intelligent gravimetric analysis (IGA) showed to give a much more suitable initial guess for tortuosity compared to literature data.For all cases, the model fit gave insignificant F-test values (experimental uncertainties were larger than the model residuals), rendering that none of the parameter sets could be rejected. To demonstrate the significance of the different cases, the final parameter set for each case were compared through comparison of ratios of classical timescales, showing the experimental conditions for the various controlling regions of mass transfer and kinetics