Automotive Aftertreatment Systems Research Articles

Applying 3D X-ray Microscopy to Model Coated Gasoline Particulate Filters under Practical Driving Conditions.

Recent progress in 3D X-ray microscopy allows the analysis of coated gasoline particulate filters on a detailed pore-scale level. However, derivable detailed three-dimensional models for filter simulation are not applicable under transient driving conditions of automotive aftertreatment systems due to their inherent complexity. Here, we present a novel concept to utilize highly resolved 3D X-ray microscopy scans and their quantitative analysis for a macroscopic model of coated gasoline particulate filters intended to be applied in a driving cycle. A previously developed filtration model build on a 1D + 1D flow model on the channel scale of a filter is utilized. Accompanying measurements conducted on a dynamic engine test bench serve as validation for pressure drop and filtration characteristics. With the determined properties from 3D X-ray microscopy, the macroscopic model successfully replicates the measurements. Regarding the filter coating, the reduced porosity and a decrease of medium sized pores relative to an uncoated substrate reduce the filtration efficiency under steady-state as well as transient conditions.

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 k-ω turbulence 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.

Adaptive Ensemble Methods for Tampering Detection in Automotive Aftertreatment Systems

Control and diagnostic processes in modern vehicles incorporate nowadays a wide set of functionalities to preserve the vehicle’s health. Automotive vehicles contain embedded systems that must perform a diverse palette of tasks, ranging from less critical tasks (e.g, audio/video media control), to crucial ones, such as controlling the engine, fuel consumption, or the aftertreatment system. This paper identifies and addresses one emerging threat, namely, automotive tampering. Tampering denotes a procedure that changes the behavior of the system to gain financial or functional advantages, without damaging the system and without triggering the built-in safety features of the vehicle. Numerous studies show a growing number of tampered vehicles worldwide and considering that tampered vehicles contribute to air and atmosphere pollution, tampering remains a serious environmental threat. This paper proposes two ensemble-based approaches for tampering detection, both using Long Short-Term Memory neural network predictors, together with Cumulative Sum and Histogram distance-based detectors. Additionally, an Adaptive Majority Weighted Voting fusion methodology is proposed, that considers the historical decisions of the detectors. Experimental results are based on three unique datasets that incorporate a multitude of tampering scenarios. The results prove the efficiency of the proposed ensembles, with a 0% false alert rate and up to 100% detection rate, even when dealing with intelligent tamperers, and even in comparison with modern tampering detection solutions. Moreover, this paper offers resource consumption and scalability measurements on a reference embedded system, further demonstrating the integrability of the proposed techniques in a real embedded environment.

Conductometric Soot Sensors: Internally Caused Thermophoresis as an Important Undesired Side Effect.

Particulate matter sensors are of interest for application in the exhaust of any combustion processes, especially for automotive aftertreatment systems. Conductometric soot sensors have been serialized recently. They comprise planar interdigital electrodes (IDE) on an insulating substrate. Between the IDEs, a voltage is applied. Soot deposition is accelerated by the resulting electric field due to electrophoresis. With increasing soot deposition, the conductance between the IDE increases. The timely derivative of the conductance can serve as a sensor signal, being a function of the deposition rate. An increasing voltage between the IDE would be useful for detecting low particle exhausts. In the present study, the influence of the applied voltage and the sensor temperature on the soot deposition is investigated. It turned out that the maximum voltage is limited, since the soot film is heated by the resulting current. An internally caused thermophoresis that reduces the rate of soot deposition on the substrate follows. It reduces both the linearity of the response and the sensitivity. These findings may be helpful for the further development of conductometric soot sensors for automotive exhausts, probably also to determine real driving emissions of particulate matter.

Reliability Challenges for Automotive Aftertreatment Systems: a State-of-the-art Perspective

This paper provides a critical review and discussion of major challenges with automotive aftertreatment systems from the viewpoint of the reliability of complex systems. The aim of this review is to systematically explore research efforts towards the three key issues affecting the reliability of aftertreatment systems: physical problems, control problems and fault diagnostics issues. The review covers important developments in technologies for control of the system, various methods proposed to tackle NOx sensor cross-sensitivity as well as fault detection and diagnostics methods, utilized on SCR, LNT and DPF systems. This paper discusses future challenges and research direction towards assured dependability of complex cyber-physical systems.

Wireless communication-based state estimation of automotive aftertreatment systems

We propose a novel approach for a cheap and easy implementable microwave-based system for the state determination of emission control and exhaust gas aftertreatment systems in motor vehicles, trucks, combustion installations, and similar equipment. It is particularly important to monitor the state of diesel particulate filters (DPF), three-way catalytic converters (TWC), and selective catalytic reduction (SCR) catalysts. It is proposed to consider the volume inside the housing of the DPF, TWC, or SCR as a communications channel between two terminals of a wireless communications system. From the transmission channel characteristics, the properties of the catalyst, such as the catalyst state, can be estimated. Measurement results for both soot-loaded and empty DPFs are presented. The technique involves a small-size and cost-effective modular architecture and has the potential for serial application.

Hyperbranched polyethyleneimine towards the development of homogeneous and highly porous CuO–CeO2–SiO2 catalytic materials

A novel templating strategy for the development of composite nanoporous CuO/CeO2/SiO2 materials with advanced properties and significant thermal stability is proposed in this work, for potential use in automotive catalysts. The synthetic process is based on the dual role of low cost hyperbranched polyethyleneimine (PEI) acting both as a reactive template to control the formation of a siliceous porous network and as a metal chelating agent to facilitate the incorporation of finely dispersed CuO/CeO2 nanoparticles into the silica matrix. Direct Ce(III)/Cu(II) introduction into the reaction mixture or post-synthetic impregnation of a preformed hybrid organic/inorganic xerogel was employed. Materials properties were assessed by means of XRD, SEM, TEM, N2 adsorption, TPR and XPS techniques. Final Cu loading was determined by a novel UV–Vis spectroscopic method. Activity tests were performed under stoichiometric, O2-deficient and O2-rich conditions simulating realistic exhaust environment. Catalytic performance was found to be strongly depended on the employed synthetic pathway. The CuO/CeO2/SiO2 composites prepared by direct introduction, exhibited enhanced structural characteristics (BET≈680m2/g), high homogeneity, superior oxidation performance and notable thermal stability, with great potential for use in automotive aftertreatment systems.