Search Results (72)

The adoption of predictive maintenance in public transportation has gained increasing attention in the context of Industry 4.0. However, many urban bus fleets remain in early digital transformation stages, with limited historical data and fragmented infrastructures that hinder the implementation of data-driven strategies. This study proposes a reproducible Machine Learning pipeline tailored to such data-scarce conditions, integrating domain-informed feature engineering, lightweight and interpretable models (Linear Regression, Ridge Regression, Decision Trees, KNN), SMOGN for imbalance handling, and Leave-One-Out Cross-Validation for robust evaluation. A scheduled batch retraining strategy is incorporated to adapt the model as new data becomes available. The pipeline is validated using real-world data from hybrid diesel buses, focusing on the prediction of time spent in critical soot accumulation zones of the Diesel Particulate Filter (DPF). In Zone 4, the model continued to outperform the baseline during the production test, indicating its validity for an additional operational period. In contrast, model performance in Zone 3 deteriorated over time, triggering retraining. These results confirm the pipeline’s ability to detect performance drift and support predictive maintenance decisions under evolving operational constraints. The proposed framework offers a scalable solution for digitally emerging fleets. Full article

Compression–ignition engines emit particulate matter (PM) (soot), prompting the widespread use of diesel particulate filters (DPFs) in the automotive sector. An alternative method for PM reduction involves the use of ultrasonic waves to disperse and modify the structure of exhaust particles. This article presents experimental results of the effects of ultrasonic emitter parameters, including the number, arrangement, and power, along with the engine speed, on the exhaust smoke density. Tests were conducted on a laboratory prototype equipped with six ultrasonic emitters spaced 0.17 m apart. The exhaust source was a diesel engine from a construction excavator, based on the MTZ-80 tractor design, delivering 80 HP and a displacement of 4750 cm³. A regression model was developed to describe the relationship between the engine speed, emitter power and spacing, and smoke density. The optimal configuration was found to involve an emitter power of 319.35 W and a spacing of 1.361 m for a given engine speed. Under the most effective conditions—an engine speed of 1500 rpm, six active emitters, and a total power of 600 W—smoke emissions were reduced by 18%. These findings support the feasibility of using ultrasonic methods as complementary or alternative exhaust gas filtration techniques for non-road diesel engines. Full article

The transportation sector mainly relied on fossil fuel and is one of the major causes of climate change and environmental pollution. Advances in smart sensing technology are paving the way for the development of clean and intelligent vehicles that lead to a more sustainable transportation system. In response, the automotive industry is actively engaging in new sensor technologies and innovative control and diagnostic algorithms that improve energy sustainability and reduce vehicle emissions. In particular, recent regulations for diesel vehicles require the integration of smart soot sensors to deal with particulate filter on-board diagnostic (OBD) challenges. Meeting the recent, more stringent OBD requirements will be difficult using traditional diagnostic approaches. This study investigates an advanced diagnostic strategy to assess particulate filter health based on resistive soot sensors and available engine variables. The sensor data are projected to generate a 2D signature that reflects the changes in filtration efficiency. A relevant feature (character) is then extracted from the generated signature that can be transformed into an analytical expression used as an indicator of DPF malfunction. The diagnostic strategy uses an adaptive approach that dynamically adjusts the signature’s characters according to the engine’s operating conditions. A correction factor is calculated using an optimization algorithm based on the integral of engine speed measurements and IMEP set points during each sensor loading period. Different cost functions have been tested and evaluated to improve the diagnostic performance. The proposed adaptive approach is model-free and eliminates the need for subsystem models, iterative algorithms, and extensive calibration procedures. Furthermore, the time-consuming and inaccurate estimation of soot emissions upstream of the DPF is avoided. It was evaluated on a validated numerical platform under NEDC driving conditions with simultaneous dispersions on engine-out soot concentration and soot sensor measurements. The promising results highlight the robustness and superior performance of this approach compared to a diagnostic strategy solely reliant on sensor data. Full article

In recent years, the transition to electric vehicles has accelerated significantly. However, this shift does not imply the complete elimination of diesel engine vehicles, particularly in commercial and cargo transport, where diesel engines remain essential due to their high thermal efficiency and torque. Despite their advantages, diesel engines produce particulate matter (PM) in their exhaust, which poses environmental and health risks. To mitigate PM emissions, diesel particulate filters (DPFs) are integrated into exhaust systems. However, as PM accumulates in the DPF, pressure drops occur, increasing the load on the engine. Therefore, periodic removal of PM through oxidation, known as regeneration, is required. Optimizing the PM combustion temperature improves fuel efficiency, but since diesel engine exhaust temperatures typically range from 100 to 500 °C, catalysts that facilitate PM oxidation at lower temperatures are necessary. This study focuses on PM oxidation catalysts designed for low-temperature diesel exhaust conditions. One of the key challenges in this area is the difficulty in directly observing PM trapping and oxidation behavior within a catalyzed DPF. Additionally, changing the catalyst during experiments is not straightforward. To address these challenges, we have developed a numerical model that simulates the entire process—from PM deposition to oxidation—inside a DPF. This model allows for easy modification of catalyst properties, providing a flexible framework for analyzing PM oxidation behavior under various conditions. In this study, numerical simulations were conducted to analyze the PM deposition and oxidation processes within the DPF. The results were derived from a simplified model developed specifically for this research. The proposed calculation method allows for the qualitative assessment of DPF performance when catalysts are altered, contributing to the optimization of DPF design. Full article

Particle number concentration (PN) in vehicle exhaust and ambient air describes the number of ultrafine particles (UFPs) below 500 nm, which are recognized as a toxic and carcinogenic component of pollution and are regulated in several countries. Metal nuclei, ash, and organic matter contribute significantly to the ultrafine particle size fraction and, thus, to the particle number concentration. Exhaust gas filtration is increasingly being used worldwide to significantly reduce this pollution, both on diesel particulate filter (DPF) and gasoline particulate filter (GPF) engines. In recent years, the EU has also funded research projects dealing with the possibilities of retrofitting gasoline vehicles with GPFs. This paper presents the results and compares the PN emissions of different vehicles. An original equipment manufacturer (OEM) diesel car with a DPF is considered as a benchmark. The PN emissions of this car are compared with a CNG car without filtration and with gasoline cars equipped with GPFs. It can be concluded that the currently used GPFs still have some potential to improve their filtration efficiency and that a modern CNG car would still have remarkable possibilities to reduce PN emissions with an improved quality GPF. Full article

As a new type of aftertreatment technology, non-thermal plasma (NTP) can effectively decompose the particulate matter (PM) deposited in diesel particulate filters (DPFs). In this paper, a regeneration test of a DPF loaded with carbon black was carried out using an NTP injection system, and the changes of oxidative activity, elemental content, and occurrence state, microstructure and graphitization degree of carbon black were analyzed to reveal the evolution of the physicochemical properties of carbon black at different regeneration stages of the DPF regenerated by NTP. As the regeneration stage of the DPF advanced, Ti, Tmax, and Te of the carbon black at the bottom of the DPF decreased, which were higher than those at the regeneration interface. After the NTP reaction, the proportion of C element decreased to less than 80%, while the proportion of O element increased to more than 20%; C-O was converted to C=O and the relative content of C=O increased. The average microcrystalline length and average spacing decreased, while the average microcrystalline curvature increased. The I_D1/I_G (relative peak intensities) of carbon black samples decreased from 3.31 to 3.10, and the R3 (relative peak intensities, R3 = I_D3/(I_G + I_D2 + I_D3)) increased from 0.41 to 0.58. The content of carbon clusters had a great influence on the disorder of the microcrystalline structure, so the graphitization degree of carbon black decreased and the oxidation activity increased. Full article

The DOC (diesel oxidation catalyst), DPF (diesel particulate filter), SCR (selective catalytic reduction), and ASC (ammonia slip catalyst) are widely used in diesel exhaust after-treatment systems. The thermal management of after-treatment systems using DOC, DPF, SCR, and ASC were investigated to improve the efficiency of these devices. This paper aims to identify the challenges of this topic and seek novel methods to control the temperature. Insulation methods and catalysts decrease the energy required for thermal management, which improves the efficiency of thermal management. Thermal insulation decreases the heat loss of the exhaust gas, which can reduce the after-treatment light-off time. The DOC light-off time was reduced by 75% under adiabatic conditions. A 400 W microwave can heat the DPF to the soot oxidation temperature of 873 K at a regeneration time of 150 s. An SCR burner can decrease NOx emissions by 93.5%. Electrically heated catalysts can decrease CO, HC, and NOx emissions by 80%, 80%, and 66%, respectively. Phase-change materials can control the SCR temperature with a two-thirds reduction in NOx emissions. Pt-Pd application in the catalyst can decrease the CO light-off temperature to 113 °C. Approaches of catalysts can enhance the efficiency of the after-treatment systems and reduce the energy consumption of thermal management. Full article

In the regeneration mode, precise control of the Diesel Oxidation Catalyst (DOC) outlet temperature is crucial for the complete combustion of carbon Particulate Matter (PM) in the subsequent Diesel Particulate Filter (DPF) and the effective conversion of Nitrogen Oxides (NOx) in the Selective Catalytic Reduction (SCR). The temperature elevation process of the DOC involves a series of intricate physicochemical reactions characterized by high nonlinearity, substantial time delays, and uncertainties. These factors render effective and stable control of the DOC outlet temperature challenging. To address these issues, this study proposes an approach based on Long Short-Term Memory (LSTM) neural networks for Model Predictive Control (MPC), emphasizing precise control of the Diesel Oxidation Catalyst’s outlet temperature during the regeneration mode. To tackle the system’s nonlinear characteristics, LSTM is employed to construct a predictive model for the outlet temperature of the Diesel Oxidation Catalyst, thereby enhancing prediction accuracy. Simultaneously, model predictive control is applied to mitigate the significant time delays inherent in the system. The gradient descent algorithm is utilized within a rolling optimization cycle to optimize the objective function, enabling the rapid determination of the control law. To validate the performance of the proposed control strategy, tracking performance and disturbance rejection tests are conducted. Simulation results demonstrate that, compared to the traditional Proportional Integral Derivative (PID) controller, this control strategy exhibits superior tracking performance and disturbance rejection capabilities. In the regeneration mode, the adoption of this control strategy enables more effective and precise control of the Diesel Oxidation Catalyst’s outlet temperature. Full article

With increasingly stringent emissions legislation, such as that stipulated by the International Maritime Organization, for nitrogen oxide emission reduction in marine diesel engines, the imperative of curtailing nitrogen oxide emissions from marine diesel engines is intensifying. Consequently, the significance of aftertreatment technologies, including diesel particulate filters (DPFs) and selective catalytic reduction (SCR), is poised to grow substantially. In particular, a redesign is required to reduce the size of DPF and SCR systems for application in small ships. In this study, we varied the shape of the filters in DPF and SCR systems, aiming to achieve a distinct flow pattern and enable overall miniaturization. The performance metrics, including the nitric oxide (NO) reduction rate, NH₃ slip rate, and pressure drop, of the redesigned models were compared with those of the conventional model. Computational fluid dynamics simulations were used to compare the performance of the redesigned model with that of the conventional model in terms of NO reduction and pressure drop. The redesigned system achieved a NO reduction rate of 6.9% below that of the conventional system, offering additional noteworthy benefits such as a 50% reduction in both pressure and overall length. Full article

The present paper investigates two different strategies for model-based calibration and control of tailpipe nitrogen oxide emissions in a light-duty 3.0 L diesel engine equipped with an aftertreatment system (ATS). The latter includes a diesel oxidation catalyst (DOC), a diesel particulate filter (DPF), and an underfloor selective catalytic reduction (SCR) device, in which the injection of diesel exhaust fluid (DEF), marketed as ‘AdBlue’, is also taken into account. The engine was modeled in the GT-SUITE environment, and a previously developed model-based combustion controller was integrated in the model, which is capable of adjusting the start of injection of the main pulse and the total injected fuel mass, in order to achieve desired targets of engine-out nitrogen oxide emissions (NOx) and brake mean effective pressure (BMEP). First, a model-based calibration strategy consisting of the minimization of an objective function that takes into account fuel consumption and AdBlue injection was developed and assessed by exploring different weight factors. Then, a direct model-based controller of tailpipe nitrogen oxide emissions was designed, which exploits the real-time value of the SCR efficiency to define engine-out NOx emission targets for the combustion controller. Both strategies exploit the model-based combustion controller and were tested through a Model-in-the-Loop (MiL) under steady-state and transient conditions. The advantages in terms of tailpipe NOx emissions, fuel consumption, and AdBlue injection were finally discussed. Full article

The upcoming Euro 7 regulation for Heavy-Duty (HD) vehicles is calling for a further tightening of the Solid Particle Number (SPN) emissions by means of both lowering the applicable limits and shifting the lowest detectable size from 23 nm (SPN₂₃) to 10 nm (SPN₁₀). A late-technology diesel HD truck was tested on a chassis dynamometer in order to assess the necessary particle filtration requirements for a continuously regenerating system. The study showed that passive regeneration under real-world operating conditions can lead to a significant release of SPN₁₀ particles from the current technology Diesel Particulate Filter (DPF) when soot-loaded, even exceeding the currently applicable emission limits. The actual emissions during passive regeneration and following the clean-up of the DPF exceeded the proposed Euro 7 limits by more than an order of magnitude. A prototype DPF, exhibiting a 99% filtration efficiency when clean, was shown to effectively control SPN₁₀ emissions under both operating conditions. The shift to SPN₁₀ also necessitates control of nanoparticles forming inside the Selective Catalytic Reduction (SCR) system, which for the tested truck exceeded the proposed (hot) limit by up to 56%. A dedicated particle filter specifically designed to capture these particles was also evaluated, showing a better than 60% efficiency. The key message of this study is that SPN emissions can be kept at low levels under all conditions. Full article

Stringent regulations have been implemented to address vehicle exhaust emissions and mitigate air pollution. However, the introduction of exhaust gas reduction devices, such as Three-Way Catalytic converters, has raised concerns about the generation and release of additional pollutants such as NH₃. This study utilized a chassis dynamometer to investigate the characteristics of exhaust pollutants, including carbon monoxide (CO), hydrocarbons (HC), nitrogen oxides (NOx), particulate matter (PM), ammonia (NH₃), organic carbon (OC), and elemental carbon (EC). The emissions were examined across various vehicle fuel types, namely liquefied petroleum gas, gasoline, and diesel (EURO4, EURO6), to assess their individual contributions to exhaust emissions. The results revealed significant variations in the emission levels of regulated pollutants (CO, HC, NOx, and PM) during driving, depending on factors such as engine technology, emissions control strategies, fuel type, and test cycle. Notably, NH₃ emissions analysis according to driving mode indicated that gasoline vehicles exhibited the highest NH₃ emissions, while diesel vehicles emitted negligible amounts. This observation can be attributed to the production of NH₃ as a byproduct of catalytic reduction processes implemented by exhaust gas reduction devices targeting CO, HC, and NOx. In addition, EURO4 vehicles demonstrated higher emission levels of OC and EC compared with other fuel types. Furthermore, the presence of diesel particulate filters (DPFs) in diesel vehicles effectively reduced PM emissions. Moreover, this study investigated the emission characteristics of organic molecular markers within the organic carbon fraction, revealing distinct emission profiles for each vehicle and fuel type. These findings contribute to the identification of emission sources by discerning the primary components emitted by specific fuel types. Full article

A diesel particulate filter (DPF) is an after-treatment device designed to capture and store exhaust particulate matter emitted by diesel vehicles. DPFs are damaged owing to complex reasons, such as regeneration processes and loads generated during driving. While DPFs can be damaged, they can also be manipulated, especially DPFs with hollow damage. In such cases, the filtration performance deteriorates significantly, and excessive amounts of smoke and ash are emitted during driving, resulting in environmental pollution. In this study, DPF damage types were observed using the CR X-ray imaging technique without removing the DPF. In addition, it was experimentally determined that the five types of DPF shapes (normal, crack, melt, plug, and hollow) caused increases in the particle number (PN) and smoke concentration. Experiments were conducted in the Korea Diesel 147 (KD-147) vehicle driving mode, and the PN and smoke concentration were measured using a nanoparticle emission tester 3795 (NPET-3795-HC) and opacimeter (OPA-102). The experiment was conducted 10 times for each type of DPF damage. As a result of the experiment, no significant difference was found between the normal DPF and crack-damaged DPF in terms of smoke emission, but there was a definite difference in the smoke concentration relative to the other DPF damage types. DPF of all damage types satisfied Korea’s smoke concentration regulation. In addition, the PN emission characteristics differed clearly in terms of the values measured for each damage type, and, unlike the smoke concentration characteristics, there was a clear difference in the PN emission characteristics of various DPF damage types. In addition, the PN concentration tended to increase in the rapid acceleration section of the KD-147 vehicle driving mode for all DPF damage types. Full article

Particulate matter (PM) is a major pollutant in the exhaust of marine diesel engines, which seriously endangers human health and the atmospheric environment, and how to reduce particulate matter emissions from marine engines has become a key research direction in the field of environmental protection and diesel engines. In this study, we analyzed the components and sources of PM from marine engines and conducted tests on the performance of Wärtsilä 20DF Diesel Particulate Filter (DPF) catalysts to verify the capture efficiency, gaseous pollutant removal rate, regeneration effect and the relationship between carbon loading and pressure loss of DPF catalysts in the context of Tier III emission regulations. The results showed that PM emissions of 20DF in diesel mode after adding the DPF system meet the requirements of the regulatory limit, but the pressure drop of the engine increases after adding the DPF system. Therefore, numerical simulation was used to optimize the DPF structure by evaluating the system velocity field, flow field distribution uniformity and system pressure drop to improve the pressure drop. Full article

The emissions of diesel engines in terms of particulate matter are limited all over the world. One possible solution for reaching the target imposed by the various regulations could be the adoption of a catalytic diesel particulate filter (CDPF). Nevertheless, the effect of CDPFs on the particle size distributions (PSDs) during the regeneration process needs to be deeply investigated. Therefore, this research work is focused on a detailed PSD analysis during the active regeneration of a 30 %wt CuFe₂O₄ loaded CDPF at the exhaust of an L-D diesel engine to reach a more complete understanding of the filter behavior. The results of the experimental tests evidence that at the CDPF outlet, compared to a standard DPF: (i) during the start-up of the regeneration, the particle emissions are three orders of magnitude lower and remain two orders of magnitude lower for particle sizes larger than 50 nm; (ii) the PSDs measured in the time range of 200–450 s exhibit the bimodality observed during the accumulation phase, with a peak that is three orders of magnitude lower; (iii) at the end of the regeneration, the PN distribution exhibits reductions of two and three orders of magnitude for particle sizes of 5 nm and above 50 nm, respectively. Full article