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Abstract Gasoline particulate filters (GPFs) are important aftertreatment components that enable gasoline direct injection (GDI) engines to meet European Union (EU) 6 and China 6 particulate number emissions regulations for nonvolatile particles greater than 23 nm in diameter. GPFs are rapidly becoming an integral part of the modern GDI aftertreatment system. The Active Exhaust Tuning (EXTUN) Valve is a butterfly valve placed in the tailpipe of an exhaust system that can be electronically positioned to control exhaust noise levels (decibels) under various vehicle operating conditions. This device is positioned downstream of the GPF, and variations in the tuning valve position can impact exhaust backpressures, making it difficult to monitor soot/ash accumulation or detect damage/removal of the GPF substrate. The purpose of this work is to present a unique example of subsystem control and diagnostic architecture for an exhaust system combining GPF and EXTUN.

Abstract Tire-pavement interaction noise (TPIN) dominates for passenger cars above 40 km/h and trucks above 70 km/h. Numerous studies have attempted to uncover and distinguish the basic mechanisms of TPIN. However, intense debate is still ongoing about the validity of these mechanisms. In this work, the physical mechanisms proposed in the literature were reviewed and divided into three categories: generation mechanisms, amplification mechanisms, and attenuation mechanisms. The purpose of this article is to gather the published general opinions for further open discussions.

Abstract The high-frequency noise issue is one of the most significant noise, vibration, and harshness problems, particularly in battery electric vehicles (BEVs). The sound package treatment is one of the most important approaches toward solving this problem. Owing to the limitations imposed by manufacturing error, assembly error, and the operating conditions, there is often a big difference between the actual values and the design values of the sound package components. Therefore, the sound package parameters include greater uncertainties. In this article, an uncertainty analysis method for BEV interior noise was developed based on an interval model to investigate the effect of sound package uncertainty on the interior noise of a BEV. An interval perturbation method was formulated to compute the uncertainty of the BEV’s interior noise.

Abstract Sleep quality and maintenance of the optimal cognitive functioning is of crucial importance for aviation safety. Fatigue Risk Management (FRM) enables the operator to achieve the objectives set in their safety and FRM policies. As in any other risk management cycle, the FRM value can be realized by deploying suitable tools that aid robust decision-making. For the purposes of our article, we focus on fatigue hazard identification to explore the possible developments forward through the enhancement of objective tools in air transport operators. To this end we compare subjective and objective tools that could be employed by an FRM system. Specifically, we focus on an exploratory survey on 120 pilots and the analysis of 250 fatigue reports that are compared with objective fatigue assessment based on the polysomnographic (PSG) and neurocognitive assessment of three experimental cases.

Abstract The main focus of this article is the online estimation of the terminal airspace sector capacity from the Air Traffic Controller 0ATC) dynamical neural model using Neural Partial Differentiation (NPD) with permissible safe separation and affordable workload. For this purpose, a primarily neural model of a multi-input-single-output (MISO) ATC dynamical system is established, and the NPD method is used to estimate the model parameters from the experimental data. These estimated parameters have a less relative standard deviation, and hence the model validation results show that the predicted neural model response is well matched with the intervention of the ATC workload. Moreover, the proposed neural network-based approach works well with the experimental data online as it does not require the initial values of model parameters, which are unknown in practice.

Abstract Effects of process parameters such as rotational speed, feed rate, and drill diameters on the drilling behavior of basalt-epoxy-based composites including 2.5 wt.% Al2O3 particles manufactured by mixing and compression method were investigated by Taguchi’s technique. The experimental results showed that the burr height (BH) increased considerably almost linearly with an increase in the drill diameter, while it remained stable with speed and decreased the feed rate slightly. There was an excellent correlation between the control factors and responses, BH of basalt fiber-reinforced plastics (BFRPs) through the Taguchi approach. The model had an adjusted R2 value of 96.3%. Generally, the inclusion of Al2O3 particles in BFRP increased its cutting force properties. Optimized drilling conditions for the input variables to produce the lowest response of the BH for composites were rotational speed of 560 rpm and feed rate of 0.28 mm/rev and a drill diameter of 4.5 mm.

Abstract In the selection of automobile noise reduction schemes, the lack of comprehensive quantitative index system and objective evaluation method is a serious problem. In this article, the methods of analytic hierarchy process (AHP) and gray target decision were used to solve the problem. Firstly, AHP and gray target decision method were introduced respectively in detail. Secondly, three automobile noise reduction schemes were illustrated. Four types of data were selected as the decision indexes, and the weight coefficients of all the decision indexes were calculated using the AHP. Then multi-attribute mixed weighted gray target decision model was established. The optimum scheme was obtained by the calculation of the off-target distance and the sorting of the calculation results. The proposed method can quantify the evaluation process and overcome the disadvantages of the traditional analogy method. The example shows that the method is feasible.

Abstract Automated guided vehicle systems (AGVS) are the prominent one in modern material handling systems used in small manufacturing enterprises (SMEs) due to their exciting features and benefits. This article pinpoints the need of AGVS in SMEs by describing the material handling selection in SMEs and enlightening recent technological developments and approaches of the AGVS. Additionally, it summarizes the analytical and simulation-based tools utilized in design problems of AGVS along with the influence of material handling management and key hurdles of AGVS. The current study provides a limelight towards making smart automated guided vehicles (AGVs) with the simplified and proper routing system and favorable materials and more importantly reducing the cost and increasing the flexibility.

Abstract In this study, active-passive filling friction stir repairing (A-PFFSR) process was employed to repair the volume defects in friction stir welding (FSW) joints of Al-Cu alloy. The volume defects with varied geometries were first machined into taper holes, which are similar to keyhole defect by a rotational tool with a threaded pin. Then, the keyhole defect was effectively filled with the materials around the keyhole and an additional filler using a number of nonconsumable pinless tools with the shoulders having six spiral flutes. The macro/microstructures, microhardness, and tensile properties of the repaired joints were investigated. The influences of plunge speed on macro/microstructures and mechanical properties of the repaired joints have been analyzed too. It was noticed that decreasing plunge speed was effective to improve the frictional heat and material flow, which increased joint surface integrity avoiding interfacial drawbacks.

Abstract In an automated machining process, monitoring the conditions of the tool is essential for deciding to replace or repair the tool without any manual intervention. Intelligent models built with sensor information and machine learning techniques are predicting the condition of the tool with good accuracy. In this study, statistical models are developed to identify the conditions of the abrasive grinding wheel using the Acoustic Emission (AE) signature acquired during the surface grinding operation. Abrasive grinding wheel conditions are identified using the abrasive wheel wear plot established by conducting experiments. The piezoelectric sensor is used to capture the AE from the grinding process, and statistical features of the abrasive wheel conditions are extracted in time and wavelet domains of the signature. Machine learning algorithms, namely, Classification and Regression Trees (CART) and Support Vector Classifiers (SVC), are used to build statistical models.

Abstract The proposed approach present the development of a computer tool that allows, in the first phase, the modeling of the electric vehicle power chain. This phase is based on a library developed under the Matlab-Simulink simulation environment. This library contains all the components of the power chain; it offers the selection of the desired configuration of each component. In the second phase, the tool solves the autonomy optimization problem. This problem is resolved by a program based on genetic algorithms. This program permits to optimize the configuration parameters maximizing the vehicle autonomy of the chosen chain. This tool is based on a graphical interface developed under the Matlab simulation environment.

Abstract The brake squeal phenomenon has bothered automobile manufacturers for a long time. Although having no ill effects on the braking performance, the squeaky noise is often a nuisance and one of the major complaints of many customers. In order to design quality and noise-free automobiles, the brake squeal issue has to be permanently tackled. Controlling brake squeal by the addition of damping on the disk and shape optimization has been suggested by many researchers. Other methods proposed in the literature include the use of a different brake pad material or an anti-squeal paste. However, the effect of the type of brake pad suspension on brake squeal has not been studied. In this article, we demonstrate that the use of a 4-element viscoelastic support can help prevent brake squeal for the practical vehicle speed range. For a 2-element support, we have identified a suitable control parameter and proposed an efficient active control for squeal prevention based on that.

Abstract Automotive vehicle includes various systems like engine, transmission, exhaust, air intake, cooling and many more systems. No doubt the performance of individual system depends upon their core design. But for performance, the system needs to be fastened properly. In automotive, most of the joints used fasteners which helps in serviceability of the components. There are more than thousands of fasteners used in the vehicle. At various locations, we found issue of bolt loosening and because of this design intent performance has not met by the system. During product development of ECS (Engine cooling system), various issues reported to loosening the bolt. The pre-mature failure of bolt loosening, increases the interest in young engineers for understanding the behavior of fastener in vehicle running conditions. This paper focuses on the design of wedge shape of washer to avoid bolt loosening.

Abstract This article investigates an adaptive test design approach for the purpose of a model-based engine calibration. Two different new algorithms are presented to take engine boundaries during test execution into account and selectively calculate new test points to increase engine model quality and its input domain. The algorithms are implemented into an adaptive test design framework and evaluated by an engine simulation with artificial Brownian noise added. The results highlight an increase in input space evaluation volume and a decrease in engine model error, while meeting calculation time constraints.

Abstract Numerous operational procedures regulate aerodrome ground traffic. Detailed solutions in these procedures often come from preventive recommendations formulated as a result of accident cause analysis. With time, the conclusions drawn based on incidents, i.e., events that did not result in material damage or casualties, are becoming increasingly significant. In this article, we propose a new method for determining the probability of an incident turning into an air accident, based on the example of aerodrome traffic operations. Premises conducive to an accident in the considered class of events depend on both human and physical factors. Thus a hybrid approach was applied. We used a fuzzy inference system to analyze the premises dependent on vehicle operators, while the simulation method was selected to examine the premises dependent on physical factors. Both were integrated using the technique of event trees with fuzzy probabilities (ETFP).

Abstract Powder metallurgy is a widely used manufacturing methodology in the gearbox industry. Noise and vibration is a common cause for concern in the gearbox industry due to the continuous contact between gear teeth at high rotational frequencies. Despite this, limited research has been performed investigating the modal properties of powder metal products. This work investigates the damping ratios of a copper-infiltrated steel powder metal ring and a hot-rolled steel ring both experimentally and computationally. Negligible difference was observed between the damping ratios of the powder metal and hot-rolled steel rings. Two proportional damping models were investigated to predict the damping ratios of the powder metal ring. It was found that the Caughey damping model was the most accurate, generating damping ratios within 2.36% for a frequency bandwidth of up to 4000 Hz.

Abstract Currently, the governments are encouraging automotive vehicle manufacturers to produce electric vehicles (EVs) as these vehicles have a zero-emission footprint. Generally, the EVs are expected to be quieter compared to internal combustion engine (ICE) vehicles. But the absence of engine noise in EVs brings more challenges for noise, vibration, and harshness (NVH) as the other noise sources become more audible. Most of these noise sources are tonal in nature and, hence, cause discomfort to the passengers. The present work is related to the noise refinement in a pure EV. The dominant noise sources observed in this vehicle are the electric powertrain, cooling fan, and air compressor. The powertrain consists of a traction motor and a gearbox (GB) with a planetary gear system. The root cause identification of electric powertrain noise has been investigated with masking trials and with the acoustic camera.

Abstract Aircraft lift bag is the equipment used for the recovery of an aircraft and is considered as a lifting equipment. Boeing 737 is a domestic aircraft considered for designing this bag. The aircraft lift bag is made of composite material, and the most widely used materials are nylon and neoprene. A composite material is used to make the bag lightweight and easy to handle. For calculation of properties and the engineering constant of the respective composite materials, micromechanics approach is used, in which the method of Representative Volume Element (RVE) is taken into consideration. The loading and boundary conditions are the exact replica of the working conditions. The operation of this bag is completely pneumatic. The stresses induced in the bag are analyzed in finite element software and are compared with the calculated theoretical values. CATIA is used to model the bag, and ABAQUS is used for the finite element calculations.

Abstract Squeak and rattle (S&R) are nonstationary annoying sounds inside the car cabin that impose high warranty costs on car manufacturers. The need for taking S&R preventing measures and the maturity level and cost considerations of the physical prototypes during the predesign-freeze stages justifies the use of virtual simulation methods. Squeak is a friction-induced high-frequency sound that is attributed to the stick-slip friction phenomenon. The importance of the friction parameters in the squeak severity prognosis is analytically and experimentally mentioned in the literature. However, studying the variation of these parameters, as regards the changes in loading and driving conditions, with the aim of application in virtual simulations has remained limited or too simplistic. In this work, the rate weakening effect of the friction coefficient curve was involved in the nonlinear finite element (FE) simulation of stick-slip events by an exponential decay formulation.

Abstract In the following, a multiphysics simulation approach for the calculation of the noise, vibration, and harshness (NVH) behavior of a three-phase permanent magnet synchronous machine is presented. Based on a defined operating point, the electromagnetic force densities in the air gap between the rotor and stator are determined on the basis of the flowing currents using the finite element method (FEM). In addition to the electromagnetic force densities, the structural modes with natural frequency and natural mode shapes are also determined by modal analysis. The electromagnetic forces and structural modes can then be reduced to the most important contributions in the modal space to significantly reduce the computation time. Using a frequency-dependent damping model, a full motor run-up is simulated and the resulting velocities at the surface of the machine are evaluated. The simulation results are then compared with a measurement and validated.