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“Spotlight on Design: Insight” features an in-depth look at the latest technology breakthroughs impacting mobility. Viewers are virtually taken to labs and research centers to learn how design engineers are enhancing product performance/reliability, reducing cost, improving quality, safety or environmental impact, and achieving regulatory compliance. Extreme environment sensors require extreme environment cables that can reliably perform in temperatures up to 2300° F, withstand intense vibration, and have extraordinary strength. In the episode “Sensors: Noise Avoidance and Cable Manufacturing” (8:53), an engineer at Meggitt Sensing Systems demonstrates the intricate process of developing cable for sensors used in these situations.

This technical paper collection contains 53 technical papers. Topics covered include engine exhaust aftertreatment and integration; hybrid vehicle integration and optimization; powertrain and drivetrain NVH; advanced transmission and driveline component design; diesel engine system design; fuel economy; alternative fuels; and advanced engine component design.

This Technical Paper Collection covers experimental, computational, and analytical efforts related to the basic mechanisms and control techniques of noise and vibration in the breathing system (induction, combustion chamber, and exhaust) of naturally aspirated and supercharged/turbocharged engines. Noise sources include airborne, flow, flow-acoustic and flow-structure coupling.

This Technical Paper Collection deals with analytical, computational and experimental studies of the dynamic response including noise and vibration of automotive driveline system and components. Typical topics of interests include, but not limited to, torque converters, gear noise, axle noise driveline system dynamics, transmission noise and vibrations, powertrain dynamics, transient dynamic response and propshaft balancing.

This Technical Paper collection covers instrumentation sensors, systems and methods used in the measurement and analysis of noise and vibration. Analysis methods internal to instrumentation will also be covered.

The focus of this Technical Paper Collection is to share experiences on analyzing, testing, and developing solutions to structural noise and vibration problems from powertrain sources. Analytical modeling, experimental testing and predictive correlation are just a few of the tools used in this endeavor.

This Technical Paper collection focuses on the development and application of analytical methods for characterizing the dynamic behavior of structural systems. Analysis methods for all structural components, subsystems and complete systems found in automotive vehicles will be considered. Examples include (but are not limited to) body structure, chassis structure, seats and interior structures.

This Technical Paper Collection covers noise sources, measurement techniques, noise attenuation strategies, case studies, prediction and modeling methods, and community regulations related to drive-by noise.

This Technical Paper Collection covers materials used to solve noise and vibration problems in vehicles. Topics covered will include new and traditional NVH materials, materials with unique or special NVH properties, case studies covering applications of NVH materials to solve specific vehicle problems, modeling of materials, manufacturing or processing of NVH materials, and engineering and design principles for the use of NVH materials.

This Technical Paper collection covers the relationships between vibration and noise that can be generated throughout the vehicle. Included in this product are modal vibration studies related to noise, vibration transfer paths throughout the vehicle, and coupling of vibration and acoustical modes. Both experimental and analytical approaches are included.

The approximately 17 papers in this technical paper collection focus on noise and vibration, including vehicle interior comfort and advanced methods, intake, exhaust, PT and chassis. The approximately 17 papers in this technical paper collection focus on noise and vibration, including vehicle interior comfort and advanced methods, intake, exhaust, PT and chassis.

The papers in this collection reflect the recent advances on the research, development and practices of Powertrain NVH treatment. The technical papers are of interest to powertrain system designers, testing specialists, NVH experts, and other individuals who evaluate and develop technologies to control powertrain NVH. The coverage includes: engine, engine subsystem and components noise and vibration; powertrain systems noise measurement and instrumentation; powertrain systems noise analysis.

Abstract Lane changes are stressful maneuvers for drivers, particularly during high-speed traffic flows. However, modeling driver’s lane-changing decision and implementation process is challenging due to the complexity and uncertainty of driving behaviors. To address this issue, this article presents a personalized Lane-Changing Model (LCM) for Advanced Driver Assistance System (ADAS) based on deep learning method. The LCM contains three major computational components. Firstly, with abundant inputs of Root Residual Network (Root-ResNet), LCM is able to exploit more local information from the front view video data. Secondly, the LCM has an ability of learning the global spatial-temporal information via Temporal Modeling Blocks (TMBs). Finally, a two-layer Long Short-Term Memory (LSTM) network is used to learn video contextual features combined with lane boundary based distance features in lane change events.

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 Real-time reconstruction of 3D environment attributed with semantic information is significant for a variety of applications, such as obstacle detection, traffic scene comprehension and autonomous navigation. The current approaches to achieve it are mainly using stereo vision, Structure from Motion (SfM) or mobile LiDAR sensors. Each of these approaches has its own limitation, stereo vision has high computational cost, SfM needs accurate calibration between a sequences of images, and the onboard LiDAR sensor can only provide sparse points without color information. This paper describes a novel method for traffic scene semantic segmentation by combining sparse LiDAR point cloud (e.g. from Velodyne scans), with monocular color image. The key novelty of the method is the semantic coupling of stereoscopic point cloud with color lattice from camera image labelled through a Convolutional Neural Network (CNN).

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 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 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.