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Abstract This article is motivated by observations of the wind tunnel measurement data acquired during benchmarking and program development for a variety of passenger vehicles over the years. In wind noise development, contribution analysis is a common practice to screen and identify the most significant sources and paths. In order to shed light on the whole picture of the contribution analysis, the work presented in this article falls into two categories. One is the analysis of underlying mechanisms for a better understanding of the phenomena observed in the contribution results. The other is the summarization of wind noise contributions obtained by wind tunnel testing for some representative subsystems, e.g., the contributions based on different reference states, the effect of grilles, underbody, acoustic glass, and auditory masking.

Abstract The use of appropriate loads and regulations is of great importance in weld fatigue assessment of rail on-track maintenance equipment and similar vehicles for optimized design. The regulations and available loads, however, are often generalized for several categories, which proves to be overly conservative for some specific categories of machines. EN (European Norm) and AAR (Association of American Railroads) regulations play a pivotal role in determining the applicable loads and acceptance criteria within this study. The availability of track-induced fatigue load data for the cumulative damage approach in track maintenance machines is often limited. Consequently, the FEA-based validation of rail track maintenance equipment often resorts to the infinite life approach rather than cumulative damage approach for track-induced travel loads, resulting in overly conservative designs.

Abstract The project of lean management is implemented in General Motors India Private Limited, Pune, India plant. The aim of the project is to improve manpower utilization by removing seven types of wastes using lean management system in kitting process. Lean manufacturing or management is the soul of Just-In-Time philosophy and is not new in Automobile manufacture sector where it born. Kitting area is analogs to the modern supermarket where required components, parts, consumables, subassemblies are kept in bins. These bins are placed in racks so that choosing right part at right time can be achieved easily. Video recording, in-person observation, feedback from online operators and other departments such as maintenance, control, supply chain etc. are taken. It is observed that the work content performed by current strength of operators can be performed by less number of operators. After executing this project, it was possible to reduce one operator and increase manpower utilization.

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 The lack of traceability in today’s supply-chain system for auto components makes counterfeiting a significant problem leading to millions of dollars of lost revenue every year and putting the lives of customers at risk. Traditional solutions are usually built upon hardware such as radio-frequency identification (RFID) tags and barcodes, and these solutions cannot stop attacks from supply-chain (insider) parties themselves as they can simply duplicate products in their local database. This industry-academia collaborative work studies the benefits and challenges associated with the use of distributed ledger (or blockchain) technology toward preventing counterfeiting in the presence of malicious supply-chain parties. We illustrate that the provision of a distributed and append-only ledger jointly governed by supply-chain parties themselves makes permissioned blockchains such as Hyperledger Fabric a promising approach toward mitigating counterfeiting.

Abstract This work develops a comprehensive thermohydrodynamic (THD) model for high-speed squeeze film dampers (SFDs) in the presence of lubricant inertia effects. Firstly, the generalized expression for Reynolds equation is developed. Additionally, in order to reduce the complexity of the hydrodynamic equations, an average radial viscosity is defined and integrated into the equations. Subsequently, an inertial correction to the pressure is incorporated by using a first-order perturbation technique to represent the effect of lubricant inertia on the hydrodynamic pressure distribution. Furthermore, a thermal model, including the energy equation, the Laplace heat conduction equations in the surrounding solids (i.e. the journal and the bush), and the thermal boundary conditions at the interfaces is constructed. Moreover, the system of partial differential hydrodynamic and thermal equations is simultaneously solved by using an iterative numerical algorithm.

Abstract In this study, a novel assessment approach of in-vehicle speech intelligibility is presented using psychometric curves. Speech recognition performance scores were modeled at an individual listener level for a set of speech recognition data previously collected under a variety of in-vehicle listening scenarios. The model coupled an objective metric of binaural speech intelligibility (i.e., the acoustic factors) with a psychometric curve indicating the listener’s speech recognition efficiency (i.e., the listener factors). In separate analyses, two objective metrics were used with one designed to capture spatial release from masking and the other designed to capture binaural loudness. The proposed approach is in contrast to the traditional approach of relying on the speech recognition threshold, the speech level at 50% recognition performance averaged across listeners, as the metric for in-vehicle speech intelligibility.

Abstract Neutron diffraction is a powerful tool for noninvasive and nondestructive characterization of materials and can be applied even in large devices such as internal combustion engines thanks to neutrons’ exceptional ability to penetrate many materials. While proof-of-concept experiments have shown the ability to measure spatially and temporally resolved lattice strains in a small aluminum engine on a timescale of minutes over a limited spatial region, extending this capability to timescales on the order of a crank angle degree over the full volume of the combustion chamber requires careful design and optimization of the engine structure to minimize attenuation of the incident and diffracted neutrons to maximize count rates.

Abstract Vehicle noise and vibration is a major focus during the design of the vehicle. The tire is a large contributor to the noise and vibration experienced inside the vehicle cabin. Any unevenness or asperities in the road cause the tire structure to vibrate, which in turn causes components in the vehicle to vibrate and generate noise. It is common in the industry to use foam inserts inside the tire air cavity that reduces the noise generated. This foam is typically intended to reduce a specific resonance in the tire-the resonance due to the air cavity. Recently, there is interest in using foam as a structural damper to reduce structural resonances in the tire. A new analytical tire model for determining the effect that structural damping foam has on the noise and vibration characteristics of the tire has been developed. The theoretical formulation of this model is presented, as well as comparison with experiments and a parametric analysis of the model.

Abstract Heavy commercial vehicles play an important role in creating the trade and economic balance of countries. Also, the durability and safety of heavy commercial vehicles come to the fore. Heavy commercial vehicles consist of two parts. These are the chassis area with the equipment that allows the vehicle to move and the cabin section where the driver is located. The cabin area is the most important area that ensures the highest level of driver safety. Considering that the production of trucks is increasing day by day, it is inevitable for companies to increase their R&D activities in the field of cabin and cabin suspension systems for much safer, durable, and comfortable trucks. This study aims to determine the safe torque value of the fasteners and their assembly sequence of the Cab Suspension Console, which is one of the most important connection parts in a truck and which can cause a fatal accident by breaking.

Abstract This study implements Flame Image Velocimetry (FIV), a diagnostic technique based on post-processing of high-speed soot luminosity images, to show the in-flame flow field development impacted by after-injection in a single-cylinder, small-bore optical diesel engine. Two after-injection cases with different dwell times between the main injection and after-injection, namely, close-coupled and long-dwell, as well as a main-injection-only case are compared regarding flow fields, flow vector magnitude, and turbulence intensity distribution. For each case, high-speed soot luminosity movies from 100 individual combustion cycles are recorded at a high frame rate of 45 kHz for FIV processing. The Reynolds decomposition using a spatial filtering method is applied to the obtained flow vectors so that bulk flow structures and turbulence intensity distributions can be discussed.

Abstract TOC

Abstract We survey the state of the art in off-board diagnostics for vehicles, their occupants, and environments, with particular focus on vibroacoustic (VA) approaches. We identify promising application areas including data-driven management for shared mobility and automated fleets, usage-based insurance, and vehicle, occupant, and environmental state and condition monitoring. We close by exploring the particular application of VA monitoring to vehicle diagnostics and prognostics and propose the introduction of automated vehicle- and context-specific model selection as a means of improving algorithm performance, e.g., to enable smartphone-resident diagnostics. Towards this vision, four strong-performing, interdependent classifiers are presented as a proof of concept for identifying vehicle configuration from acoustic signatures. The described approach may serve as the first step in developing “universal diagnostics,” with applicability extending beyond the automotive domain.

Abstract Statistical machine learning classification methods have been widely used in the fault detection analysis in several engineering domains. This motivates us to provide in this article an overview on the application of these methods in the fault diagnosis strategies and also their successful use in unmanned aerial vehicles (UAVs) systems. Different existing aspects including the implementation conditions, offline design, and online computation algorithms as well as computation complexity and detection time are discussed in detail. Evaluation and validation of these aspects have been ensured by a simple demonstration of the basic classification methods and neural network techniques in solving the fault detection and diagnosis problem of the propulsion system failure of a multirotor UAV. A testing platform of an Hexarotor UAV is completely realized.

Abstract The civil aircraft nosewheel is clamped, lifted, and retained through the pick-up and holding system of the towbarless towing vehicle (TLTV), and the aircraft may be moved from the parking position to an adjacent one, the taxiway, a maintenance hangar, a location near the active runway, or conversely only with the power of the TLTV. The TLTV interfacing with the nose-landing gear of civil transport aircraft for the long-distance towing operations at a high speed could be defined as a towbarless aircraft taxiing system (TLATS). The dynamic loads induced by the system vibration may cause damage or reduce the certified safe-life limit of the nose-landing gear or the TLTV when the towing speed increases up to 40 km/h during the towing operations due to the maximum ramp weight of a heavy aircraft.

Abstract The mechanical efficiency of the current continuously variable transmission (CVT) suffers from high pump loss induced by a high-pressure system. A novel wedge mechanism is designed into the CVT clamp actuation system to generate the majority of clamp force mechanically. Therefore, the hydraulic system can operate at a low-pressure level most of the time, and the pump loss is greatly reduced to improve the CVT’s mechanical efficiency. Through dynamic analysis and design optimization, 90% of clamp force is contributed by the wedge mechanism and the rest of the 10% is generated by a conventional hydraulic system. The optimal design is validated through dynamic modeling using Siemens Virtual.Lab software by simulating the wedge clamp force generation, ratio change dynamics, and system response under tip-in conditions. After that, we built prototype components that target 70% of the clamp force contributed by the wedge mechanism and tested them on a transmission dynamometer.

Abstract The gear whine in the electric drive system of an electric vehicle is important and remains a challenge in developing novel electric vehicles. A gearbox dynamic model is established, and the effects of modification parameters on the sound pressure level, transmission error, and contact stress of the gear pair are introduced to reduce the gear whine. A multi-objective optimization study of four modification variables under multiple torque conditions is carried out by using transmission error and maximum contact stress as the objective functions. The eclectic programming method is imported to solve the convergence problem of multi-objective optimization. The influence of modification variables on objective functions is studied by establishing an approximate model of the optimal Latin hypercube design.

Abstract The methods for improving the torsion stiffness of a pickup chassis frame were discussed, including increasing the part thickness on frame, enlarging the cross section of rails, and adding bulkhead feature inside the rails. Sizing optimization was conducted to get the optimal thickness configuration for frame parts and meet the siffness requirement. The cross section of frame rails were parameterized and shape optimization was conduted to get the optimal rail cross sections for stiffness improvement. Additional bulkheads were added to the frame rails, and sizing optimization conducted to find the most effective bulkheads to add and their optimal gauge. A material efficiency ratio μ is used to evaluate the efficiency of a design change with respect to torsion stiffness. Among those torsion improvement methods, adding bulkhead feature gives the highest material efficiency ratio, but the stiffness improvement range is very limited.

Abstract Structural optimization evolved as a preferred technique across industries to develop lightweight products. One of the widely studied topics in structural optimization is to develop methods that reduce the radiated noise from a structure, where responses like Equivalent Radiated Power (ERP) and natural frequencies used to indirectly address the noise levels. This article compares freeform optimization with topology optimization technique and investigates their effectiveness for reducing radiated noise and weight. To illustrate the same, Finite Element Method (FEM) and Boundary Element Method (BEM) analysis are performed on a sheet metal flat plate (panel) as an example and correlated the same with experimental data. Further, different optimization problem formulations have been explored on those examples and results have been compared.

Abstract The broadband aeroacoustics of a side mirror is investigated with a stochastic noise source method and compared to scale-resolving simulations. The setup based on an already existing work includes two geometrical variants with a plain series side mirror and a modified mirror with a forward-facing step mounted on the inner side. The aeroacoustic near- and farfield is computed by a hydrodynamic–acoustic splitting approach by means of a perturbed convective wave equation. Aeroacoustic source terms are computed by the Fast Random Particle-Mesh method, a stochastic noise source method modeling velocity fluctuations in time domain based on time-averaged turbulence statistics. Three RANS models are used to provide input data for the Fast Random Particle-Mesh method with fundamental differences in local flow phenomena.