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Severe problem of aerodynamic heating and drag force are inherent with any hypersonic space vehicle like space shuttle, missiles etc. For proper design of vehicle, the drag force measurement become very crucial. Ground based test facilities are employed for these estimates along with any suitable force balance as well as sensors. There are many sensors (Accelerometer, Strain gauge and Piezofilm) reported in the literature that is used for evaluating the actual aerodynamic forces over test model in high speed flow. As per previous study, the piezofilm also become an alternative sensor over the strain gauges due to its simple instrumentation. For current investigation, the piezofilm and strain gauge sensors have mounted on same stress force balance to evaluate the response time as well as accuracy of predicted force at the same instant. However, these force balance need to be calibrated for inverse prediction of the force from recorded responses.

Modern combat aircraft demands efficient maintenance strategies to ensure operational readiness while minimizing downtime and costs. Innovative approaches using Digital Twining models are being explored to capture inter system behaviours and assessing health of systems which will help maintenance aspects. This approach employs advanced deep learning protocols to analyze the intricate interactions among various systems using the data collected from various systems. The research involves extensive data collection from sensors within combat aircraft, followed by data preprocessing and feature selection, using domain knowledge and correlation analysis. Neural networks are designed for individual systems, and hyper parameter tuning is performed to optimize their performance. By combining the outputs of these during the model integration phase, an overall health assessment of the aircraft will be generated.

With the capability of avoiding failure in advance, failure prediction model is important not only to end users, but also to the service engineers in vehicle industry. This paper proposes an approach based on anomaly detection algorithms and telematic data to predict the failure of the engine air system with Turbo charger. Firstly, the relationship between air system and all obtained features are analyzed by both physical mechanism and data-wise. Then, the features including altitude, air temperature, engine output power, and charger pressure are selected as the input of the model, with the sampling interval of 1 minute. Based on the selected features, the healthy state for each vehicle is defined by the model as benchmark. Finally, the ‘Medium surface’ is determined for specific vehicle, which is a hyperplane with the medium points of the healthy state located at, to detect the minor weakness symptom (sub-health state).

The steam reforming of CH4 plays a crucial role in the high-temperature activity of natural gas three-way catalysts. Despite existing reports on sulfur inhibition in CH4 steam reforming, there is a limited understanding of sulfur storage and removal dynamics under various lambda conditions. In this study, we utilize a 4-Mode sulfur testing approach to elucidate the dynamics of sulfur storage and removal and their impact on three-way catalyst performance. We also investigate the influence of sulfur on CH4 steam reforming by analyzing CH4 conversions under dithering, rich, and lean reactor conditions. In the 4-Mode sulfur test, saturating the TWC with sulfur at low temperatures emerges as the primary cause of significant three-way catalyst performance degradation. After undergoing a deSOx treatment at 600 °C, NOx conversions were fully restored, while CH4 conversions did not fully recover.

In-cylinder fluid dynamics enhance performance and emission characteristics in internal combustion (IC) engines. Techniques such as helical ports, valve shrouding, masking, and modifications to piston profiles or vanes in ports are employed to achieve the desired in-cylinder flows in these engines. However, due to space constraints, modifications to the cylinder head are typically minimal. The literature suggests that introducing baffles into the combustion chamber of an IC engine can enhance in-cylinder flows, air-fuel mixing, and, subsequently, stratification. Studies have indicated that the height of the baffles plays a significant role in determining the level of improvement in in-cylinder flow and air-fuel mixing. Therefore, this study employs Computational fluid dynamics (CFD) analysis to investigate the impact of baffle height on in-cylinder flow and air-fuel mixing in a four-stroke, four-valve, spray-guided gasoline direct injection (GDI) engine.

This article analyzes the aerodynamic performance of Class 8 tractor-trailer geometries made available by the Environmental Protection Agency (EPA) using CFD simulation. Large Eddy Simulations (LES) were carried out with the CFD package, Simerics-MP+. A Sleeper tractor and a 53-foot box trailer configuration was considered. The configuration featured a detailed underbody, an open-grille under-hood engine compartment, mirrors, and the radiator and condenser. Multiple tractor-trailer variants were studied by adding aerodynamic surfaces to the baseline geometries. These include tank fairings and side extenders for the cabins, two types of trailer skirts, and a trailer tail. The effect of these devices towards reducing the overall vehicle drag was investigated. Mesh generation was carried out directly on the given geometry, without any surface modifications, using Simerics’ Binary-Tree unstructured mesher.

The current research focuses on enhancing the performance of Si solar cells by using Er2O3 (Erbium Oxide) in cubic crystalline nature serves as an anti-reflection coating material. An anti-reflective coating aims to improve the Efficient Power Conversion (EPC) of polycrystalline silicon wafers solar cells (PSSC) utilised in solar roof panels of the automotive sector. It also exhibits superior light transmittance and least light reflectance, which eventually leads to the increase EPC. Erbium oxide helps to convert low energy photons into high energy photons. The incident photons, which lies on the solar cell, gradually losses its energy to travel in a denser medium and dissipate in the form of heat energy. In order to overcome the rate of reflection, current research aims in synthesis of erbium oxide nanosheets using electrospinning deposition technique for varying deposition timings such as 1, 1.5 and 2 hours.

This research paper focuses on the modelling and analysis of a flywheel energy storage system (FESS) specifically designed for electric vehicles (EVs) with a particular emphasis on the flywheel rotor system associated with active magnetic bearings. The methodology used simulation approaches to investigate the dynamics of the flywheel system. The objective of this study is to explore the effects of implementing the flywheel energy storage system on the performance of the EV. The paper presents a comprehensive model of the flywheel energy storage system, considering the mechanical and electrical aspects. The mechanical model accounts for the dynamic behaviors of the flywheel, including parameters such as rotational speed, inertia, and friction. The electrical model describes the interaction between the flywheel and the power electronics, such as the converter and motor/generator. To evaluate the benefits of the flywheel energy storage system, simulations are conducted.

The primary function of an automotive horn is to alert pedestrians and other nearby vehicles to their safe passage on the road. Most of the human population is subjected to a certain amount of horn sound dosage daily. The study of automotive horn sound quality is equally important as their sound generation mechanism in passenger cars. The sound quality of automotive horns can be studied through subjective and objective test methods. In the present study, a subjective jury test and objective analysis using psychoacoustic parameters are conducted to classify car horn sound samples according to pleasantness. Twenty-two car horns, consisting of a disc and shell, are chosen for binaural sound recording. The recorded sound samples are used for subjective and objective analysis. Thirty members participated in the jury test, and a semantic differential method was used to collect the user response. The Tukey range test is used to classify the subjective test data.

The thermal performance of an engine coolant system is efficient when the engine head temperature is maintained within its optimum working range. For this, it is desired that air should not be entrapped in the coolant system which can lead to localized hot spots at critical locations. However, it is difficult to eliminate the trapped air pockets completely. So, the target is to minimize the entrapped air as much as possible during the coolant filling and deaeration processes, especially in major components such as the radiator, engine head, pump etc. The filling processes and duration are typically optimized in an engine test stand along with design changes for augmenting the coolant filling efficiency. However, it is expensive and time consuming to identify air entrapped locations in tests, decide on the filling strategy and make the design changes in the piping accordingly.

The lack of inherent security controls makes traditional Controller Area Network (CAN) buses vulnerable to Machine-In-The-Middle (MitM) cybersecurity attacks. Conventional vehicular MitM attacks involve tampering with the hardware to directly manipulate CAN bus traffic. We show, however, that MitM attacks can be realized without direct tampering of any CAN hardware. Our demonstration leverages how diagnostic applications based on RP1210 are vulnerable to Machine-In-The-Middle attacks. Test results show SAE J1939 communications, including single frame and multi-framed broadcast and on-request messages, are susceptible to data manipulation attacks where a shim DLL is used as a Machine-In-The-Middle. The demonstration shows these attacks can manipulate data that may mislead vehicle operators into taking the wrong actions.

The prediction accuracy of a three-way catalyst (TWC) model is highly associated with the ability of the model to incorporate the reaction kinetics of the emission process as a lambda function. In this study, we investigated the O2 and H2 concentration profiles of TWC reactions and used them as critical inputs for the development of a global TWC model. We presented the experimental data and global kinetic model showing the impact of thermal degradation on the performance of the TWC. The performance metrics investigated in this study included CH4, NOx, and CO conversions under lean, rich, and dithering light-off conditions to determine the kinetics of oxidation reactions and reduction/reforming/water-gas shift reactions as a function of thermal aging. The O2 and H2 concentrations were measured using mass spectrometry to track the change in the oxidation state of the catalyst and to determine the mechanism of the reactions under these light-off conditions.

Stoichiometric natural gas engines with three-way catalysts emit less NOx and CH4 due to their higher efficiency compared to lean-burn natural gas engines. Although hydrothermal aging of three-way catalysts has been extensively studied, a deeper understanding beyond hydrothermal aging is needed to explain real-world performance, especially for natural gas engines with near-zero NOx emissions. In this investigation, field-aged three-way catalysts were characterized to identify the contribution of chemical aging to their overall performance. It was found that the sulfur species on the field-aged TWCs were entirely distributed along the catalyst length, showing a decreasing trend, whereas phosphorous contamination was mainly observed at the inlet section of the three-way catalysts, and the phosphorous concentration declined sharply along the axial length.

Safety, fuel economy and uptime are key requirements for the operation of heavy-duty line-haul trucks within a fleet. With the penetration of connectivity and automation technologies, energy optimal and safe operation of the trucks are further improved through Advanced Driver Assistance System (ADAS) features and automated technologies as in truck platooning. Understanding the braking capability of the vehicle is very important for optimal ADAS and platooning control system design and integration. In this paper, the importance of tire connectivity and tire conditions on truck stopping distance are demonstrated through testing. The test data is further utilized to develop tire models for integration in an optimal vehicle automation for platooning. New ways to produce and use the tire related information in real-time optimal control of platooning trucks are proposed and the contribution of tire information in fuel economy is quantified through simulations.

Commercial automotive diesel engine service and repair, post a diagnostic trouble code trigger, relies on standard troubleshooting steps laid down to identify or narrow down to a faulty engine component. This manual process is cumbersome, time-taking, costly, often leading to incorrect part replacement and most importantly usually associated with significant downtime of the vehicle. Current study aims to address these issues using a novel in-house simulation-based approach developed using a Digital Twin of the engine which is capable of conducting in-mission troubleshooting with real world vehicle/engine data. This cost-effective and computationally efficient solution quickly provides the cause of the trouble code without having to wait for the vehicle to reach the service bay. The simulation is performed with a one-dimensional fluid dynamics, detailed thermodynamics and heat transfer-based diesel engine model utilizing the GT-POWER engine performance tool.

The application of cooperative adaptive cruise control (CACC) to heavy-duty trucks known as truck platooning has shown fuel economy improvements over test track ideal driving conditions. However, there are limited test data available to assess the performance of CACC under real-world driving conditions. As part of the Cummins-led U.S. Department of Energy Funding Opportunity Announcement award project, truck platooning with CACC has been tested under real-world driving conditions and the results are presented in this paper. First, real-world driving conditions are characterized with the National Renewable Energy Laboratory’s Fleet DNA database to define the test factors. The key test factors impacting long-haul truck fuel economy were identified as terrain and highway traffic with and without advanced driver-assistance systems (ADAS).

Cu-SSZ-13 selective catalytic reduction (SCR) catalysts are broadly applied in diesel aftertreatment systems for the catalytic conversion of oxides of nitrogen (NO + NO2). Diesel exhaust contains a wide range of water vapor concentrations depending on the operating condition. In this study, we evaluate the impact of water vapor on the relevant SCR catalytic functions including NOx conversion, NO oxidation, NH3 oxidation, and N2O formation under both standard and fast SCR conditions. Reactor-based experiments are conducted in the presence and absence of water vapor. Results indicate that water vapor can have both a positive and negative impact on low temperature NOx conversion for standard SCR reaction. At low inlet NOx concentrations, the presence of water vapor has a negative effect on NOx conversion, whereas, at high inlet NO concentrations, water vapor improves NOx conversion.

Evaluation of the platooning legislative space suggests a limited near-term opportunity for autonomous vehicles as currently only nine states have platooning and autonomous favorable legislations. An extensive closed-loop vehicle model simulation was conducted to quantify two-truck platooning fuel economy entitlement benefits across all United States (US) interstate routes (I-xx) spanning over 40,000 miles as compared to a single truck. A simultaneous study was carried out to identify the density of Class 8 heavy-duty trucks on these interstates, using the Freight Analysis Framework (FAF) 4 database. These two studies were combined to ascertain interstates that foresee the least fuel consumption due to platooning and thus identifying states with the most platooning benefits. Identification of states with most platooning benefits provides realistic data to push for autonomous driving and platooning legislations.

The present study examines the impact of using low thermal mass (LTM) turbine housing designs on the transient characteristics of the turbine outlet temperature for a light-duty diesel standard certification cycle (FTP75). For a controlled exhaust flow, the turbine outlet temperature will directly determine the impact on an aftertreatment system warm-up from a cold state, typical of engine-off and engine idling conditions. The performance of the aftertreatment system such as a Selective Catalytic Reduction (SCR) system is highly dependent on how quickly it warms up to its desirable temperature to be able to convert the harmful oxides of Nitrogen (NOx) to gaseous Nitrogen. Previous works have focused on mostly insulating the exhaust manifold and turbine housing to conserve the heat going into the aftertreatment system. The use of LTM turbine housing has not been previously considered as a means for addressing this requirement.

The upcoming Bharat Stage VI (BS VI) emission legislation has put enormous pressure on the future of small diesel engines which are widely used in the Indian market. The present work investigates the emission reduction potential of a common rail direct injection single cylinder diesel engine by adopting a holistic approach of lowering the compression ratio, boosting the intake air and down-speeding the engine. Experimental investigations were conducted across the entire operating map of a mass-production, light-duty diesel engine to examine the benefits of the proposed approach and the results are quantified for the modified Indian drive cycle (MIDC). By reducing the compression ratio from 18:1 to 14:1, the oxides of nitrogen (NOx) and soot emissions are reduced by 40% and 75% respectively. However, a significant penalty in fuel economy, unburned hydrocarbon (HC) and carbon monoxide (CO) emissions are observed with the reduced compression ratio.