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In this paper, a multiphysics simulation workflow based on the use of reduced-order models (ROMs) to decrease the computation time is presented. Using FE pre-computed flux-linkage and lumped force lookup-tables (LUTs) in function of dq0 currents and rotor position, an electromagnetic model of a permanent-magnet synchronous machine (PMSM) is developed. Coupled to a mechanical state-space representation, the complete workflow allows to predict the vibrations of the motor. Using our model, the influence of the 0-sequence current on the vibration spectrum is investigated. A detailed description on the parameter identification for homogenized stator core of the considered 12-slot 10-pole delta-connected fractional-slot concentrated-winding (FSCW) spoke-type PMSM is also given. The numerical results are validated with experimental data for the machine at hand. Because of the large amount of FE data required, the workflow is best suited for the optimization of motor control schemes (instead of the initial design optimization) with the purpose of reducing the noise, vibration, and harshness (NVH).

A high-speed motor in a drive system causes several challenges to the reliability of the mechanical parts of electric vehicles and leads to issues with noise, vibration and harshness (NVH). Thus, a two-speed powershift transmission is considered an effective way to improve the dynamic, economic and comfort performance of electric vehicles. A newly designed dual-pump hydraulic control system for a two-speed powershift transmission with two wet clutches is presented, in which the mechanical oil pump is linearly affected by the vehicle speed and the electric oil pump is controllable. By integrating the dynamic model of the hydraulic system into one of the powertrains with a two-speed transmission, a co-simulation dynamic model is proposed. To satisfy the flow and pressure demand of the hydraulic system, a dual-pump control strategy is presented, in which the electric oil pump is controlled by the mechanical oil pump following the minimum energy consumption principle. The World Light Vehicle Test Procedure (WLTP) cycle simulation results show that the energy consumption of the proposed hydraulic system can be reduced by 58.2% compared to the previous single-pump system developed by the authors with a constant main-line pressure control strategy. On the basis, the best configuration of the two pumps can further reduce the energy consumption of the hydraulic system by 23.2% compared to that of two-oil pumps with preset displacement.

Due to a large number of degrees of freedom and connected powertrain functionalities, the development of operating strategies for plug-in hybrid electric vehicles is an especially complex task. Besides optimizations of drivability, noise, vibrations and harshness as well as energy efficiency, the main challenge lies in ensuring emissions conformity. For this purpose, test vehicles are typically applied to achieve a realistic test and validation environment. However, operating strategy calibration using test vehicles has the drawbacks, that (i) it is very time consuming and cost intensive, (ii) it can only be conducted in late development phases and (iii) cannot be applied to reproducing driving loads for a valid comparison. To overcome these issues, this paper presents a consistent engine-in-the-loop approach combining real engine hardware and multiple software elements to represent PHEV behavior at the engine test bench. Thereby, an environment is created, which allows for realistic, flexible, cost efficient and reproducible testing. The effectiveness of the presented framework is evaluated by comparing relevant on-road measurements with their reproduction at the engine test bench. The results show that the vehicle on-road behavior can be replicated using the described testing environment. Particularly engine start/stop behavior and load levels—the core functionalities for operating strategy calibration—are matched. The proven level of realism in powertrain behavior enables further use cases beyond on-road measurement reproduction, i.e. varying individual component properties and observing real-world consequences at the test bench without the need for vehicle tests.

Noise, vibration, and harshness (NVH) issue in switched reluctance machines (SRMs), originating from their doubly salient structure and unique principle of operation, is addressed in this work by proposing a structural design modification in the stator, which increases stiffness to mass ratio of the structure. A 24-slot 16-pole (24s/16p) SRM designed with the aim of automotive application is studied here for the NVH optimization, at different target operating points, using stator pole bridges. Stator pole bridges link consecutive stator teeth to provide additional stiffness to the stator structure. Average torque reduction due to flux shorting in stator pole bridges is tackled by proposing a low-permeability material, with considerable stiffness, which has not yet seen its’ application in SRM NVH domain. Multiphysics aspects of stator pole bridge design encompassing electromagnetic radial force, mechanical stress, steady-state temperature distribution, and acoustic noise analyses are presented in this article. Possible manufacturing issues are considered during the design phase and appropriate measures are implemented to facilitate easier construction of two 100-kW prototypes. The final design with stator pole bridges and a baseline design without any stator pole bridges are prototyped, after rigorous multiphysics optimization, for extensive testing. Experimental results verify simulation outputs and report a maximum noise reduction of 12.52 dBA in the stator pole bridge model compared to the baseline SRM.

Under high-speed operating conditions, the noise caused by the vibration of the traction gear transmission system of the Electric Multiple Units (EMU) will distinctly reduce the comfort of passengers. Therefore, analyzing the dynamic characteristics of traction gears and reducing noise from the root cause through comprehensive modification of gear pairs have become a hot research topic. Taking the G301 traction gear transmission system of the CRH380A high-speed EMU as the research object and then using Romax software to establish a parametric modification model of the gear transmission system, through dynamics, modal and Noise Vibration Harshness (NVH) simulation analysis, the law of howling noise of gear pair changes with modification parameters is studied. In the small sample training environment, the noise prediction model is constructed based on the priority weighted Back Propagation (BP) neural network of small noise samples. Taking the minimum noise of high-speed EMU traction gear transmission as the optimization goal, the simulated annealing (SA) algorithm is introduced to solve the model, and the optimal combination of modification parameters and noise data is obtained. The results show that the prediction accuracy of the prediction model is as high as 98.9%, and it can realize noise prediction under any combination of modification parameters. The optimal modification parameter combination obtained by solving the model through the SA algorithm is imported into the traction gear transmission system model. The vibration acceleration level obtained by the simulation is 89.647 dB, and the amplitude of the vibration acceleration level is reduced by 25%. It is verified that this modification optimization design can effectively reduce the gear transmission. © 2021 Institute of Noise Control Engineering.

When a certain electric vehicle is driving at a constant speed of 40 km/h on the rough asphalt road, the rear passenger can obviously feel the ear pressure, which seriously affects the comfort. Through the analysis of objective data, it was found that the problem was caused by the road excitation, which leads to the coupling between the mode of the backup door and the mode of the acoustic cavity, and causes the resonance of the car cavity, thus causing the ear pressure sensation. To solve this problem, this paper optimizes the backup door by means of experiment and simulation, increases the dynamic vibration absorber, makes its modal frequency avoid the acoustic cavity modal frequency, and achieves the purpose of reducing the interior noise. After optimization, the vehicle noise is reduced by 8 dBA at 42 Hz under 40 km/h working condition of rough road surface, and the ear pressure sensation is reduced at the same time, thus improving the NVH (noise, vibration, and harshness) performance of the vehicle.

Considering the influence of mount structure parameters on the quality of vehicle noise, vibration and harshness (NVH), a multi-objective optimization method of the magneto-rheological (MR) mount based on vehicle vibration control was proposed. A lumped parameter model was used to establish the relationship between the structure parameters of the MR mount and the NVH performance of the vehicle. Considering the influence of current on the magneto-rheological fluid viscosity and flow rate in damping channel, the dynamic characteristics of MR mount was obtained by the lumped parameter model. Then, a 10 degrees of freedom (DOF) vehicle model with MR mounting system was established. Finally, a co-simulation optimal platform was developed by the ISIGHT, MATLAB, and ANSYS software, and the non-dominated sorting genetic algorithm II was used to optimize the design of the mount magnetic circuit with the goal of improving the quality of vehicle NVH. The results showed that under the start/stop and the constant speed conditions, the root mean square values of vibration acceleration of the driver’s seat rail of the vehicle with the optimal design magneto-rheological mount decreases by 31.6% and 7.8%, respectively compared with the initial design mount, improved the ride comfort of the vehicle.

Shift shock is an important index for evaluating the noise, vibration, and harshness performance of heavy-duty vehicles owing to the changeability of driving conditions. Hence, it is imperative to design a controller for a smooth shift to enhance the shift quality of automatic transmission. In this study, a novel robust control design against the uncertainties of heavy-duty vehicles is designed after dynamic modelling is performed. First, the clutch actuator model was developed by considering the uncertainty of electrohydraulic actuators, variations in friction coefficient due to clutch slip speed, and complex and volatile driving conditions of vehicles. Next, a robust control design for the inertial phase is proposed based on the clutch slip speed, including a feedforward controller, feedback controller, and disturbance controller. Finally, it is demonstrated that the control design is highly advantageous for the shift control of heavy-duty automatic transmission by comparison with a proportional-integral-derivative controller. Numerical results indicate that the proposed controller is effective in preventing shift shock, thereby improving ride comfort.

Owing to the continuous development of the automobile industry, increasingly stringent performance requirements for noise, vibration, and harshness of automobiles are being presented. Interior noise control in high-speed vehicles has not been adequately addressed, owing to the complex mechanism of noise generation. As simulations performed previously focused on vehicle wind noise and tyre noise cannot adequately predict the effect on passenger ear-side noise, these issues are investigated in this study. Their effects on passengers are investigated using transfer path analysis. An anti-noise operational transfer path analysis is proposed to study noise generated in high-speed vehicles. The established anti-noise operational transfer path analysis model can eliminate crosstalks between noise source signals of different transmission paths. The model is validated by comparing the measured and calculated values of the anti-noise operational transfer path analysis model. The coherence of the input noise signal and the ear-side noise signal of the passenger is assessed using coherence analysis. By calculating and categorising the contributions of different noise sources in different locations and types, the main noise sources affecting passenger comfort are determined. The result indicates that the main noise sources affecting the passenger’s ear-side noise change from engine noise to left-A wind noise and tyre radiation noise with increasing vehicle speed, in which the proportion also increase. The proposed anti-noise operational transfer path analysis is suitable for the interior-noise analysis of high-speed vehicles, and this study may serve as a reference for future studies regarding active and passive noise control in high-speed vehicles.

Noise, vibration, and harshness (NVH) simulators enable the subjective evaluation of vehicle interior noise and improvement of the NVH performance. To achieve a powerful and sporty engine sound, several original equipment manufacturers of automobile parts introduce the engine intake noise into the vehicle cabin through pipe systems that reinforce the low-frequency engine noise components. The present study proposes an intake-noise module that simulates an intake-noise reinforcing system and can be integrated with the previously developed NVH simulator. The intake- noise simulation module is based on the intake noise source model, pipe system model, and room impulse response model. The pipe system is modeled by the transfer-matrix method (TMM), and the room impulse response is modeled using the image-source method. The intake noise source is time variant because the noise source depends on the rotational speed of the engine and the crankshaft angle. TMM is also time variant because the noise propagation characteristics in TMM vary with the throttle valve angle. Intake noise source and TMM are designed in the frequency domain. In two cases of intake-noise reinforcing system, the loudness and sharpness (which are known to be correlated with a sporty engine noise) are calculated for the simulated data. The developed NVH simulator can assist the design of intake-noise reinforcing systems that reach the targeted sound quality.

Legislation mandating minimum distances for motorists passing cyclists is seen by advocates as a straightforward way to increase the perceived safety of cycling and thus remove a prominent barrier to the uptake of cycling. The evidence, however, is not as clear. The alternative to compliance-based enforcement via Minimum Passing Distance Laws (MPDLs) is performance-based enforcement as recently highlighted by UK Police forces under the name ‘Operation Close Pass’. This existing legislation and enforcement method relies on police officer judgement and discretion. For a MPDL to be introduced it has to show an improvement by identifying more manoeuvres that make cyclists feel unsafe, whilst at the same time not penalising drivers for manoeuvres that are benign. This study uses Signal Detection Theory to show that on almost every measure the current performance-based enforcement is preferable. Officer discretion is aligned more closely to cyclists’ real-world perceptions of risk than an objective, compliance-based MPDL. Any level of enforcement harshness can be achieved equally well, if not better, through officer discretion than through a fixed passing distance law, with the former being significantly easier to adjust if needed. Further discussion about the unintended effects of passing distance laws is discussed, such as the risk of a net loss to the effectiveness of cyclist safety because it is more difficult to prosecute and enforce manoeuvres which make cyclists feel unsafe than the performance-based alternative.

Road noise is expected to become even more important in the vehicle product development cycle due to electrification and challenging lightweight/emission targets. In this study, a topology optimization algorithm is applied to determine the damping pad layout on the roof and floor panels of a Body-in-White (BIW), being the dominant contributors on road noise, vibration and harshness (NVH) performance of an automotive. Optimization algorithm yields the prescribed % of the surface area of these panels where the damping pad should be distributed set by the automotive Original Equipment Manufacturers (OEMs). The objective function is the minimization of the overall acceleration of these panels for the frequencies up to 200 Hz, while the weight of the BIW is considered as the optimization constraint. The results of the optimization are compared with the road NVH performance of panels with full damping and no damping. The optimization results indicate that by using 25% of the damping pad on the roof and floor panels improve the vibration performance especially in the frequency range of 80 Hz to 150 Hz significantly compared to bare BIW panels. Besides, the performance of the 25% damping is almost same as the application of full damping pad for frequencies between 90 Hz to 110 Hz. The results show that the methodology is able to address the trade-offs between road NVH and weight targets effectively.

This article presents the optimal design and experimental prototype testing of a low-cost motor applied for a city battery electric vehicle, zero emission A-segment. Respecting the car performance specifications, the aluminum cage rotor induction machine is designed to reduce motor cost using totally enclosed fan-cooled technology and a commercial speed encoder of internal combustion engine. An optimization approach and finite elements analysis validation are coupled with thermal calculations and used to size the thermo-electromagnetic parts of the machine. The prototype is manufactured with full instrumentation. During the experiments, an indirect flux-oriented control model is built based on simulations in MATLAB/Simulink environment. Using this real time control platform, the motor control is calibrated on the prototype in test-bench, to ensure the optimum energy consumption and the current and speed regulations in the entire large operating range. Finally, the experimental prototype testing results are shared to show the ideal design solution in term of peak performances, efficiency, thermal and noise, vibration, and harshness behaviors.

The slamming acoustic of a vehicle door is objectively not associated to the inherent character of the automobile, however, it is associated to the inherent structure of the vehicle door, which is a vital subjective performance to evaluate the vehicle. Although it has been recognized that static indicators may engender an inferior design result in engineering practice, the majority studies in the literature have not considered dynamic indicators for the door slamming event. This paper presents a multi-objective optimization (MOO) framework of a vehicle door design in the slamming event for optimal dynamic performances. In our previous study we have obtained the transient excitation forces through the transfer path analysis (TPA), lab experiment and bench test. These transient excitation forces will be the input for the MOO algorithm. The dimensions of the vehicle door structure main components are considered as design variables. The objective functions include the first natural frequency obtained by semi-constrained modal analysis, the mass of the vehicle door, and the maximum amplitude of the target points on the vehicle door’s glass. The constraint functions include the design variable bounds, dynamic stiffness constraints of the four mounting points for the glass run channel system. In order to promote the efficiency of subsequent optimization, the response surface method (RSM) is employed instead of time-consuming finite element method. The multi-objective particle swarm optimization (MOPSO) algorithm is implemented to conduct the dynamic indicators optimization. The results show that the proposed optimization framework is successful of achieving a reliable solution with a uniformly distributed Pareto boundary, and it is recommended to choose an optimal result from relatively insensitive regions that meet the requirements. It is shown that the simulation response of the optimized door structure can reduce the acoustic pressure amplitude at the driver’s right ear employed BEA technique. The proposed framework can be adapted to optimize door structural design for any vehicle door to improve noise, vibration, and harshness (NVH) performance.

In recent years, the reduction of noise and vibrations caused by the road or internal components of vehicles have been a significant factor in the satisfaction and comfort of the occupants of cars. Therefore, to minimize these vibrations, the dynamic behaviour of the components of the vehicle should be considered in detail to reduce their level by setting useful parameters on structures. Nowadays, the conceptual model method can be regarded as a suitable alternative to the fundamental sophisticated computational techniques in measuring the vibration of vehicle components. Accordingly, the advanced finite element (FE) model examined for the subframe structure under the vehicle engine, and its conceptual model is developed by the one-dimensional beam elements to justify the dynamic behaviour of the subframe. The results of the experiments in the laboratory as well as the advanced subframe model are adapted, and the integrity of the natural frequencies and the mode shapes at low frequencies represented comprehensively. The result of the subframe concept model compared to the experimental model and computer-aided-engineering (CAE) model showed that the modal assurance criterion (MAC) is above 0.75 for the first four mode shapes of subframe structure and is above 0.9 for first and fourth mode shapes, and also the error percentage of natural frequency is lower than 8%. Therefore, for the analysis of the subframe performance in noise, vibration, and harshness (NVH) domain, the presented model could be considered in the conceptual phase design to reduce the solution time significantly.

A dominant spatial airgap force order-based reference current profiling scheme is proposed in this work for noise, vibration and harshness (NVH) mitigation in Switched Reluctance Machines (SRM). The current profile optimization strategy is coupled with a fast vibration prediction method. Extensive simulations and experimentations are done on an 18 slot/12 pole SRM to verify the proposed strategy. Worst case noise scenario for the 18 slot/12 pole SRM is determined through experimental run-up test under constant torque condition. The proposed current shaping strategy is applied at the operating point experiencing worst case noise and significant NVH reduction is obtained through simulation and experimentation. Experimental results show a peak noise reduction of 14.24 dBA compared to a conventional square wave based current reference.

Engine mount is an essential component to support the vehicle engine and to determine the vehicle dynamic property in terms of noise, vibration, and harshness (NVH). It works as the important interface between the engine and the chassis to reduce the bad impact of the engine-induced vibrations on the car body. To this end, this paper proposed a new semi-active engine mount capable of variable stiffness as an attempt to further improve the vibration reduction capability of the current semi-active engine mount which is only capable of varying damping. This study completed the characterization test of the proposed semi-active engine mount and evaluated its capability of stiffness variability. Then a test of an engine mounted with the new mount was performed to evaluate the vibration reduction capability. The experimental results demonstrate that this proposed engine mount show variable stiffness in response to the varied magnetic field, and that it performed well in protecting the chassis from the engine-induced vibration by reducing the vibration transmissibility.

The recent climate projections predict that the intensity and frequency of extreme events will increase as a result of overall increasing mean temperature and reduced precipitations in the temperate regions of the Northern Hemisphere. How these changes will influence the harshness of the environment and the performances of trees growing under natural conditions remains an open question. In this commentary article, we would like to look at the concept of suboptimal growth conditions, widening its application from the traditional in vitro manipulation to trees growing in open air, addressing the main limitations and strengths of the upscaling results from cell to tree. We believe that the traditional single dose–effect approach is not suitable to explain the complex interactions between genotype and environment, occurring in open field or forest stands, where the intensity and frequency of the events are uncontrolled and unpredictable. As forests provide a wide range of ecosystem services, new parameters should be considered in the definition of the response thresholds in addition to growth. Thus, within this Special Issue, we stimulate the discussion over the development of new approaches and technologies that are able to define suitable threshold responses of trees under suboptimal natural conditions, with the aim to furnish new insights on the acclimation and adaptation processes in woody species under global change.

In December 2019, the first reported case of COVID-19 was brought to notice in Wuhan, China. The virus has novel characteristics, its harshness is unpredictable, its transmission ability is extremely powerful, and its incubation period is comparatively larger. Thus the outbreak emerged as a pandemic worldwide. World health and socio-economy is getting continually affected by COVID-19 since its outbreak. It will be easier to handle the situation if an automated diagnostic system is developed, capable of separating COVID-19 affected images from bulk images obtained from a mass screening process. Kaggle’s online chest X-Ray image dataset has been considered for this work evaluation. Healthy and COVID-19 affected chest X-Ray images were used for evaluating the performance of content-based image retrieval. Image retrieval has been carried out based on the absolute difference between the encoded features of twin images obtained from the Siamese Convolutional Neural Network (SCNN). The retrieval performance is awe-inspiring as the Siamese network used for retrieval is a relatively shallow network. SCNN does not require resource-hungry training with huge samples as part of its underlying implementation characteristics. The execution time is also very encouraging as the simplicity of the method is concerned. The method achieves 94% average precision and 100% average reciprocal rank while rank = 5 has been considered. Till now, no work has been reported on content-based retrieval of COVID-19 chest X-Ray images. Thus, a comparative study of evaluation metrics and execution time requirements of similar work could not be provided.

Chapter 21 is contributed by a team of gear experts of Gear Research Center (FZG) at the Technical University of Munich, Germany. This chapter covers the noise, vibration, and harshness (NVH) behavior of geared transmissions as a major field in gear design and analysis. Gear noise is dependent on transmitted load and running speed of the gears and is characterized by distinct frequencies that may be clearly audible. In most applications gear noise is unwanted and has to be prevented. Major efforts in engineering are concentrated on low noise design on one hand and on gear noise analysis in operation on the other hand. In gear design a low noise generation is valued as a major quality criterion. Some design rules concerning gear main geometry or simple shapes of recommended micro geometry are available for the engineer. Nevertheless, a significant portion of developing silent gears is an iterative trial and error activity. That makes sound understanding of the underlying basics mandatory for today’s gear engineer. The chapter illustrates different mechanical approaches to gear mesh NVH. General basics of gear noise excitation are covered, in particular the influence of main geometry and of micro geometry. Evaluation of different design criteria (TE, etc.) will be explained. Widely used is the calculation of transmission error but also established are more complex methods like tooth force level or application force level. Gear noise analysis is a second relevant aspect. Based on general acoustics an evaluation of airborne sound and noise of transmissions will be described. More detailed methods of analysis techniques of transmissions and gear meshes will be documented which require greater effort. These include measurement of structure borne noise and measurement of transmission error in special test rig environment.

Transfer Path Analysis (TPA) is widely used to identify individual path contributions and to solve Noise, Vibration and Harshness (NVH) issues in different industries. However, the complexity and technical burden of the conventional TPA calls for alternative, faster techniques. One such alternative is the Operational Transfer Path Analysis (OTPA), which uses only operational data to estimate the contributions. However, this approach has its own limitations; in some situations, the OTPA results may be affected, which can lead to the wrong engineering decisions. This paper presents an alternative formulation of OTPA, in application to structure-borne noise: Operational Transfer Path Analysis – Difference (OTPA-D). The theoretical considerations and analytical model showed that OTPA-D solves one of the crucial issue regarding the OTPA technique. The paper provides theoretical considerations behind OTPA-D; also, a laboratory model is set up to compare the results of three versions of OTPA with the results of TPA. It is shown that two experimental OTPA versions matched TPA better compared to the traditional OTPA method.

Electric and hybrid vehicle engines produce a complex spectrum of vibration and noise. Various active mounting techniques have been developed to isolate them. These are designed to continuously control the dynamic characteristics of the mounts and improve the noise, vibration, and harshness (NVH) performance under various operating conditions. Active mounts have attracted attention as replacement for existing mounts by simultaneously realizing static and dynamic stiffness, which is important for supporting an engine. Therefore, this study focuses on the vibration isolation performance of the upper plate and lower plate when the structure, including the active mounting system, is applied to multifrequency excitation. The overall modeling is based on the lumped parameter model, and the input signal is applied to the amplitude modulated and frequency modulated signals. The adaptive filter is applied for control, and the normalization least mean square (NLMS) algorithm, which is commonly used in research, is extended to a multi-NLMS algorithm. It is shown that when multifrequency input is applied, the adaptive filter is effectively applied to the active mounting system to control vibration.

Consideration of internal combustion engine formats suitable for hybrid or range extender electric vehicles usually focuses on selecting a power plant, which is as compact as possible to meet the demands and constraints of the installation. In-line three-cylinder engines often provide an attractive solution for such vehicles. This article presents a low emission two-stroke engine of in-line three-cylinder format and draws a comparison with an equivalent four-stroke engine. The particular focus of the analysis is on strategies for minimization of noise, vibration and harshness with significant reduction in piston lateral force compared with the four-stroke unit. The design also considers a balance shaft arrangement to further assist with noise, vibration and harshness reduction. The presented arrangement demonstrates an integrated induction control/balance shaft arrangement, which erodes the usual cost penalties typical of balance shaft consideration in three-cylinder engines.

This paper describes a method to reduce the torque ripple for the Wound Field Synchronous Motor, which does not use a permanent magnet. When a WFSM is used in an Integrated Starter Generator system, it must have a higher power density than other automotive motors in order to satisfy the size constraints and required power. An increase in the power density creates a magnetic flux saturation in the rotor, and this soon becomes the cause of an increase in the torque ripple of motor. An increase in the torque ripple can degrade the Noise Vibration Harshness characteristics of automotive by creating vibration and noise in the engine start-up mode, in which the maximum torque is generated in an ISG system. This paper proposes a method of reducing the torque ripple via a design that uses a flux barrier model in the WFSM’s rotor. The Response Surface Method is used to optimize the flux barrier model, and Finite Element Method is used to to verify the torque ripple reduction.

The ride comfort, driving safety, and handling of the vehicle should be designed and tuned to achieve the expectations defined in the company’s design. The ideal method of tuning the characteristics of the vehicle is to modify the bushings and mounts used in the chassis system. To deal with the noise, vibration and harshness on automobiles, elastomeric materials in mounts and bushings are determinant in the automotive components design, particularly those related to the suspension system. For most designs, stiffness is a key design parameter. Determination of stiffness is often necessary in order to ensure that excessive forces or deflections do not occur. Many companies use trial and error method to meet the requirements of stiffness curves. Optimization algorithms are an effective solution to this type of design problems. This paper presents a simulation-based methodology to design an automotive bushing with specific characteristic curves. Using an optimum design formulation, a mathematical model is proposed to design and then optimize structural parameters using a genetic algorithm. To validate the resulting data, a finite element analysis (FEA) is carried out with the optimized values. At the end, results between optimization, FEA, and characteristic curves are compared and discussed to establish the correlation among them.

As battery electric vehicle (BEV) market share grows so must our understanding of the noise, vibration, and harshness (NVH) phenomenon found inside the BEVs which makes this technological revolution possible. Similar to the conventional vehicle having encountered numerous NVH issues until today, BEV has to face many new and tough NVH issues. For example, conventional vehicles are powered by the internal combustion engine (ICE) which is the dominant noise source. The noises from other sources were generally masked by the combustion engine, thus the research focus was on the reduction of combustion engine while less attention was paid to noises from other sources. A BEV does not have ICE, automatic transmission, transfer case, fuel tank, air intake, or exhaust systems. In their place, there is more than enough space to accommodate the electric drive unit and battery pack. BEV is quieter without a combustion engine, however, the research on vehicle NVH is even more significant since the elimination of the combustion engine would expose many noise behaviors of BEV that were previously ignored but would now seem clearly audible and annoying. Researches have recently been conducted on the NVH of BEV mainly emphasis on the reduction of noise induced by powertrain, tire, wind and ancillary system and the improvement of sound quality. This review paper will focus on recent progress in BEV NVH research to advance the BEV systems in the future. It is a review for theoretical, computational, and experimental work conducted by both academia and industry in the past few years.

This chapter describes the basic material selection considerations for designing lightweight vehicle body. It also includes design considerations for stiffness, strength, fatigue durability, crashworthiness, and noise, vibration, and harshness of body structure and body panels. Optimization processes for lightweight designs are briefly described.

The reduction in interior noise is an important concern in noise, vibration, and harshness (NVH) for different reasons. Noise and vibration of the passenger cabin are the signature points to the overall impression of the vehicle quality. Very high noise and vibration at the driver’s ear position make noise and vibration a key issue. Long exposure to high noise levels are major factors of risk to worker health and safety. Thus, it is very important to study the noise generated inside the cabin. Experimental method is carried out, but it is very expensive and time consuming. This article is based on the development of predictive finite element acoustic structural analysis to study the vibro-acoustic behavior of the excavator cabin. The displacement response of cabin under the external force excitation is analyzed between 0 and 300 Hz. The displacement response is mapped to acoustic cavity surface by the normal surface interaction. The distribution of internal acoustic field is calculated, and sound pressure level response is obtained at the driver’s ear. The methodology has been established for acoustic analysis of cabin, and sound pressure level has been reduced by 20 dB.

The Lincoln Corsair is a compact premium crossover vehicle on Ford's global C (compact class) platform, replacing the Lincoln MKC. The prime focus of the research and development workstreams of the integral bushing rear suspension architecture for the new Lincoln Corsair was to significantly improve the performance in terms of impact harshness as well as noise, vibration and harshness (NVH) behavior compared to the Lincoln MKC featuring a control blade rear suspension architecture. The new integral bushing rear suspension architecture is an evolution of the integral link rear suspension architecture developed for Ford's global CD (midsize class) platform. Compared to the integral link rear suspension architecture the integral bushing rear suspension architecture is significantly lighter and the cost structure could be improved without compromising the performance level of the integral link rear suspension architecture. With regards to the interior noise attribute the performance level could be significantly improved. The integral bushing rear suspension architecture development included benchmarking activities, definition of attributes and targets, suspension concept design as well as system evaluation and selection. The concept development work was conducted with special attention to key requirements implied by a compact premium crossover product like the Lincoln Corsair as well as design constraints introduced by the platform and the sister product Ford Kuga deploying a control blade rear suspension architecture. This paper focuses on the design aspects and the fundamental layout principles of the integral bushing rear suspension architecture by presenting the journey starting from the integral bushing rear suspension prototype development towards the final series production design of the premium rear suspension architecture of the new Lincoln Corsair.

This paper reports the results of a case study analyzing the intraspeaker variability of the prosodic level a professional lecturer under several factors at play, namely voice ageing, genre, pragmatics, and voice acting. The goal of the study is to establish the range of prosodic variability of David Crystal, a prominent lecturer. The prosodic features analyzed are frequency, intensity, duration, and voice quality; the method used is acoustic analysis. The results not only expand the existing theory on intraspeaker variability due to the newly received voice quality data, but will also serve as a measuring stick for analyzing other lecturers or public speakers. The key study findings comprise the ability of the speaker in question to resist age-related changes and to preserve the control over temporal parameters, pitch range, and harmonic-to-noise-ratio (HNR). The decline in shimmer and jitter values was documented to decrease harshness in voice and express agreeableness in an interview while high NHR values were noticed to accompany lectures. No voice quality parameter changed under the influence of pragmatic intention. Constructing several individual prosodic portraits of a speaker in different age, genre, pragmatics environments allowed for the recreation of the speaker’s prosodic level, but it is the examination of voice acting that proved to be vital as it allows to analyze the wider scope of the speaker’s variability.

A novel model order reduction (MOR) technique is presented to achieve fast and real-time predictions as well as high-dimensional parametric solutions for the electromagnetic force which will help the design, analysis of performance and implementation of electric machines concerning industrial applications such as the noise, vibration, and harshness in electric motors. The approach allows to avoid the long-time simulations needed to analyze the electric machine at different operation points. In addition, it facilitates the computation and coupling of the motor model in other physical subsystems. Specifically, we propose a novel formulation of the sparse proper generalized decomposition procedure, combining it with a reduced basis approach, which is used to fit correctly the reduced order model with the numerical simulations as well as to obtain a further data compression. This technique can be applied to construct a regression model from high-dimensional data. These data can come, for example, from finite element simulations. As will be shown, an excellent agreement between the results of the proposed approach and the finite element method models are observed. We thank Professor Jose Roger-Folch (Univer-sitat Politècnica de València) for useful discussion, comments and feedback about the present work.

The necessity to improve the Noise Vibration Harshness (NVH) performance and, in particular, to reduce the flow noise produced by turbulent exhaust gases is requiring automotive manufacturers to optimize Internal Combustion Engines (ICE) exhaust systems from the early design phases. Computational Aeroacoustics Analyses (CAA) can be seen as a promising tool to support engineering design and optimization, enabling the evaluation of system performance and allowing the selection of effective noise reduction strategies.

The noise, sound pollution, and harshness are steadily increasing alarmingly from various vehicles such as lorries, vans, cars, and buses. It is considered a significant concern in our modern life due to the long-term harmful effect on human health. The excessive vehicular noise and sound pollution mainly affecting in specific areas of smart cities such as hospitals, educational institutes, various private/public organizations. As a result, people are suffering from neurocognitive problems. Therefore, controlling the sound pollution from vehicles are incredibly essential to mitigate health issues globally. However, minimal research was conducted by monitoring vehicular noise intensity in a smart city area using smart, reliable, and sophisticated technologies such as the internet of things (IoT) to mitigate these issues. This paper presents an enhanced intelligent IoT-enabled vehicular noise intensity monitoring system to protect the city dweller’s health by reducing sound pollution in the smart city. We are planned to propose an architectural framework using noise intensity measuring sensors, 360° Camera, 360° LIDAR, GPS (Global Positioning System) in the vehicle with IoT technology for monitoring individual vehicles and their nearby vehicles over the smart city. The proposed system can monitor real-timely vehicular noises and notify designated stakeholders (i.e., vehicle owner, city authority) promptly and stored in the cloud with valid proofs. The proposed system helps to develop an ideal vehicular noise monitoring system over the smart cities and the widespread significance of mitigating health problems that relate to sound pollution and increase public awareness.

Noise, vibration, and harshness (NVH) in electric machines are mainly of electromagnetic and structural origin. This research focuses on isolating the structural and electromagnetic impacts on NVH performance, in a fractional slot concentrated winding (FSCW) permanent magnet synchronous machine (PMSM), brought by variation of different design parameters. A modification to the unit force response method is proposed for easier implementation in this work and is termed as lumped unit force response method. The modified method is experimentally verified before subsequent application for sensitivity analysis of various design parameters on NVH performance of a 12-slot/10-pole (12s10p) surface mounted PMSM. Separation of electromagnetic and structural impacts of different design parameters aids decision making during NVH performance optimization. Taguchi orthogonal array based mean and variance analysis are used during the sensitivity analysis in this work.

Phase current shaping is a common approach to reduce the radial force ripple and thus improve the noise, vibration, and harshness (NVH) performance of the switched reluctance machine (SRM). However, this method is reliant on the accuracy of the position and the current sensors. This paper presents an analytical approach to model the effect of position and current sensor errors on radial force ripple SRM and its impact on the NVH performance of the machine. As a phase current shaping method, current harmonics injection is chosen to analyze the sensor errors on its performance. Initially, the radial force is modelled using the Fourier series expansion. Then, position and current sensor errors in the SRM drive system are included in the analytical modelling. The harmonic orders of the radial force ripple are analyzed and simulated for different sensor errors. NVH performance of SRM is analyzed to show the effects of different sensor errors on the current profiling methods. Simulation and experimental results are provided to verify the proposed method of analysis.

This research focuses on wide speed range noise, vibration and harshness (NVH) performance comparison and optimization of different fractional slot concentrated winding permanent magnet synchronous machines (PMSM) for automotive application through a unit force response-based method of vibration prediction called vibration synthesis. Process verification is done for vibration synthesis through extensive testing of a 12 slot 10 pole (12s10p) PMSM before subsequent application for comparison of different PMSM designs. Most of the NVH comparison work available in the literature focus on single operating speed-based performance evaluation which is the drawback this work aims to remove. Different slot/pole combinations of PMSMs are compared in this work in regard to their NVH performances. Electromagnetic and/or mechanical impacts brought by one structural NVH performance improvement method is analyzed in detail using unit force response method, and subsequently, vibration synthesis is used to compare the NVH performances over the entire speed range of interest. This will offer a better understanding of different design modifications done for NVH performance improvement in electric machines.

The valve train system is an important source of vibration and noise in an engine. An in-depth study on the dynamic model of the valve train is helpful in understanding the dynamic characteristics of the valve train and improving the prediction accuracy of vibration and noise. In the traditional approaches of the dynamic analyses, the simulations of the valve train system and the engine are carried out separately. The disadvantages of these uncoupled approaches are that the impact of the cylinder head deformation to the valve train and the support and constraints of the valve train on the cylinder head are not taken into consideration. In this study, a full engine dynamic model coupled with a valve train system is established and a dynamic simulation and noise vibration harshness (NVH) analysis are carried out. In the coupled approach, the valve train system is simulated simultaneously with the engine, and the complexity of the model has been greatly increased. Compared with the uncoupled approach, more detailed dynamic results of the valve train can be presented, and the subsequent predictions of vibration and noise can also be more accurate. The acoustic results show that the difference from the experimental sound power level is reduced from 1.8 dB(A) to 0.9 dB(A) after applying the coupled approach.

Wide variety of road types like intersections, highways poses a real challenge to the computer vision algorithms. Hence, there is a need of efficient algorithm to detect the accident on road and also evaluate the severity of the incident. This can be used to improve the emergency services response time. The work demonstrated in this paper aims to develop such an algorithm by modifying existing CCTV surveillance system. In this work, the accident is detected by the dispersion in the motion field of the vehicles during collision. Motion field of the road is obtained from the optical flow of the video frames. The moving objects in the frames are segmented and tracked. The dispersion in the angle vector of the optical flow is derived for each of the moving object. The dispersion of angle vector for each object is monitored, and deviation of the same from the threshold is determined as an accident. The harshness of the accident can be found by the range of dispersion of the motion field. The algorithm developed here is capable of detecting accidents between any types of moving objects.

With the development of new energy vehicles, the NVH (Noise, Vibration, Harshness) performance of the permanent magnet synchronous motors (PMSM) for vehicles has attracted more and more attention. The rotor slotting optimization analysis is the critical issue in the NVH performance study of PMSM. In this paper, the theoretical formula of the PMSM radial electromagnetic force is presented. Based on which, the spatial order and frequency order characteristics of the radial force of a 6-pole 36-slot PMSM are analyzed. Firstly, electromagnetic simulation of the motor is carried out, and the specific force components, which may cause an NVH problem, is extracted. Secondly, the harmonics are calculated with a method of freezing the relative magnetic permeability. Thirdly, the motor is optimized by rotor slotting to reduce the amplitudes of these harmonics, and the effect on electromagnetic noise is analyzed in theory and simulation. Finally, the NVH test in original state and after rotor slotting state was performed in the semi-anechoic chamber. The accuracy of the theory and simulation was verified based on the comparison of the measured noise data. This paper provides a new NVH optimization idea, this method can quickly locate the fundamental problem location of electromagnetic NVH, provide a fast channel for electromagnetic NVH optimization from simulation to verification, and improve the optimization efficiency of NVH.

The various factors that affect ride comfort, including noise, vibrations and harshness (NVH) have been in focus in many research studies due to an increasing demand in ride comfort in the automotive industry. Vibrations have been highlighted as an important contribution to assess and predict overall ride comfort. The purpose of this paper is to present an approach to explain ride comfort with respect to vibration for the seated occupant based on a systematic literature review of previous fundamental research and to relate these results to the application in the contemporary automotive industry. The results from the literature study show that numerous research studies have determined how vibration frequency, magnitude, direction, duration affect human response to vibration. Also, the studies have highlighted how body posture, age, gender and anthropometry affect the human perception of comfort. An analysis was made of the consistency and inconsistency of the results obtained in the different studies. The deviations of the research results from real-world ride comfort in automotive vehicles were analyzed and divided into three groups: appreciable and consistent with industry results, appreciable and inconsistent with industry results and not appreciable in industrial results. The overall conclusion from this literature study was that there is much information available from laboratory studies regarding human response to vibrations, but there is a lack of studies that take into account all the different parameters that affect the overall ride comfort experience for automotive vehicle occupants.

Noise, harshness and vibrations are a non-trivial aspect of ride or human comfort, and car manufacturers often sought to improve the aforesaid comfort level. In previous studies, human biodynamic model and vehicle model are often modelled separately. Human model is used to study human alertness level and health while vehicle model is used to study on the car vibration to specifically understand the impact of vibration towards the model independently. In this study, a twelve degrees of freedom (12 DOF) human biodynamic model is incorporated with a two in-wheel electric car model to investigate the effect of vertical vibration towards the human brain based on different types of road profile and maneuver. MATLAB simulation environment is used to carry out the investigation, and it was established from the present study that the proposed model is able to provide significant insights on the impact experienced by the human brain to the skull based on the given vertical input of different road profile. The impact on the human brain to the skull is often associated with human alertness while driving where vibration exposure towards human driver influence the sleepiness level, human reaction times and lapses of attention which may lead to road accidents.

Summary & ConclusionsThe development of an engine-cooling module (ECM) for an European carmaker faced a major blocking point. The stalemate concerned the design of the suspension rubbers separating the engine-cooling radiator (the ECM carrier) from the chassis. The development of an engine-cooling module (ECM) for an European carmaker faced a major blocking point. The stalemate concerned the design of the suspension rubbers separating the engine-cooling radiator (the ECM carrier) from the chassis. From the one hand, the damping rubbers had to be soft, in order to be compliant with noise, vibration & harshness (NVH) criteria – acoustic noise and vibration transmitted to the cabin. On the other hand, their softness would provoke such high amplitude response during shaker tests that the module carrier (the radiator) would fail at the early stage of vibration testing – a leakage was observed after 10 hours of the targeted 90 hours duration. New rubbers, designed for durability purposes, would fail to meet the NVH criteria. The project development team went through a double-faced dilemma: how to design rubbers with an acceptable trade-off between NVH and durability of the engine-cooling radiator, and how to find a quick and efficient way to validate the design in order to be compliant with vibration validation tests. Together with the customer, our company (automotive tier-1 supplier) established an iterative design optimization of the damping rubbers, based on the simultaneous feedback from the acoustic response and the durability predictions. The goal was to develop a strategy permitting a quick an effective criteria for damage estimation for each design proposed.

Non-regular machining procedure like electro release machining (ERM) and wire electrical release machining (WEDM) assumes significant job in accuracy assembling process. This small-scale machining procedure may help defeat the confinements and limitation looked during customary mechanical machining procedure. The choice of machining stricture in any machining procedure essentially influences creation rate, item value and generation rate completed one part. Line ERM procedure includes an enormous number of factors that influence its exhibition. In this research, an attempt is made to contemplate the force of different procedure parameter, for instance, strike on schedule, strike off moment in time and existing for elevated-carbon elevated-chromium bitter job instrument make stronger (D2). The trial has been finished with the assistance of design of analysis by Taguchi strategy is applied to make a symmetrical cluster of information factors utilizing the ANOVA. The relapse examination is utilized to upgrade the procedure parameter of surface unpleasantness. The test investigation demonstrated that the mix of heartbeat going on timetable, strike off moment moreover current be ideal toward accomplish minimization of surface harshness (Ra).

Robotization is increasingly used in the agriculture since the last few decades. It is progressively replacing the human workforce that is deserting the agricultural sector, partly because of the harshness of its activities and health risks they may present. Moreover, robotization aims to improve efficiency and competitiveness of the agricultural sector. However, it leads to several research and development challenges regarding robots supervision, control and optimization. This paper presents a simulation and optimization approach for the optimization of robotized treatment tasks using type-c ultraviolet radiation in horticulture. The optimization of tasks scheduling problem is formalized and a heuristic and a genetic algorithms are proposed to solve it. These algorithms are evaluated compared to an exact method using a multiagent-based simulation approach. The simulator takes into account the evolution of the disease during time and simulates the execution of treatment tasks by the robot. Interreg North-West Europe Programme in context of UV-ROBOT.

There is a growing interest in new sensing technologies and processing algorithms to increase the level of driving automation towards self-driving vehicles. The challenge for autonomy is especially difficult for the negotiation of uncharted scenarios, including natural terrain. This paper proposes a method for terrain unevenness estimation that is based on the power spectral density (PSD) of the surface profile as measured by exteroceptive sensing, that is, by using a common onboard range sensor such as a stereoscopic camera. Using these components, the proposed estimator can evaluate terrain on-line during normal operations. PSD-based analysis provides insight not only on the magnitude of irregularities, but also on how these irregularities are distributed at various wavelengths. A feature vector can be defined to classify roughness that is proved a powerful statistical tool for the characterization of a given terrain fingerprint showing a limited sensitivity to vehicle tilt rotations. First, the theoretical foundations behind the PSD-based estimator are presented. Then, the system is validated in the field using an all-terrain rover that operates on various natural surfaces. It is shown its potential for automatic ground harshness estimation and, in general, for the development of driving assistance systems., 26 pages

Contains fulltext : 219353.pdf (Publisher’s version ) (Open Access) Evolutionary social scientists have argued that impulsive behavior is adaptive in harsh and unpredictable conditions. Is this true? This paper presents a mathematical model that computes the optimal level of impulsivity in environments varying in harshness and unpredictability. We focus on information impulsivity, or choosing to act without gathering or considering information about the consequences of one's actions. We explore two notions of harshness: the mean level of resources (e.g., food) and the mean level of extrinsic events (e.g., being the victim of a random attack). We explore three notions of unpredictability: variation in resources, variation in extrinsic events, and the interruption risk (the chance that a resource becomes unavailable). We also explore interactions between harshness and unpredictability. Our general model suggests four broad conclusions. First, impulsive behavior is not always adaptive in harsh and unpredictable conditions; rather, this depends on the exact definition of harshness, unpredictability, and impulsivity. Second, impulsive behavior may be adaptive in environments in which the quality of resources is low or high, but is less likely to be adaptive when their quality is moderate. Third, impulsive behavior may be adaptive when resource encounters are likely to be interrupted. Fourth, extrinsic events have only a limited effect on whether impulsive behavior is adaptive. We discuss the implications of these findings for future research, consider several limitations, and suggest future directions. 13 p.

This paper presents several Noise, Vibration, Harshness (NVH) post-processing techniques used on a dynamic acquisition system to troubleshoot acoustic noise and vibration issues due to electromagnetic forces in e-powertrains. Standard NVH post processing techniques based on Order Tracking (OT), Operation Deflection Shapes (ODS) and Experimental Modal Analysis (EMA) are presented and as well as their application to discriminate the frequencies of magnetic forces responsible for NVH issues. However, they do not filter the different wave-numbers of vibration waves. Some special NVH post processing techniques are introduced to go deeper in the analysis and quickly capture electromagnetically-excited NVH root cause. They are based either on “spatiogram” or on flux sensor waveform post processing. “Spatiogram” relies on the Discrete Fournier Transformation of accelerations measured on the machine. It aims at introducing a space information besides the standard time and frequency information. It can be seen as an extension of the spectrograms done at variable speed as it efficiently discriminates wavenumbers of magnetic forces responsible for NVH issues. Experimental measurements run on a Permanent Magnet Synchronous Motor (PMSM) are interpreted and confirmed by simulation results. Similarly flux sensor waveforms can be post-processed to quantify geometrical and magnetic asymmetries, to estimate radial magnetic forces per tooth and derive Frequency Response Functions (FRF) of stator teeth under radial electromagnetic excitations.

Over the past decades, automotive companies have sought lightweight and performant noise, vibration and harshness (NVH) solutions to comply with stringent regulations for CO2 emissions and noise pollution. Combining lightweight design with improved NVH solutions is often a challenging task: low mass and high stiffness materials are generally characterized by poor NVH behavior and low noise and vibration levels often require heavy and bulky additions, especially to be effective in the low frequency regime. To face this challenge, recently, locally resonant metamaterials (LRMs) have come to the fore. These materials combine in one solution lightweight design and superior noise and vibration attenuation performance, beating the mass law in tunable frequency ranges, referred to as stop bands. The LRM concept is used in this work to tackle a low frequency structure borne road noise problem in a commercial vehicle. A LRM solution is applied on the rear shock towers of the vehicle, with the goal of attenuating the vibrational energy entering into the vehicle body through the suspension assembly, which is excited by the interaction of the tire with the road while driving. This results in a reduction of the noise in the interior compartment around 190 Hz. In order to benchmark the performance of the LRM concept, a vehicle is chosen which is sold with a tuned vibration absorber installed on each of the rear shock towers as NVH solution. Each of the tuned vibration absorbers (TVAs) adds 1.46 kg of mass to the vehicle. The LRM concept is designed to reduce the mass of the current solution by 48% and to have similar NVH performance. The LRM concept is realized through additive manufacturing and it is added as patches on the rear shock towers to replace the TVAs. Both numerical and experimental results in lab and on a smooth road profile validate the performance of the LRM concept proposed.

The technical specifications of electrified vehicles (xEVs) will drastically change the way future vehicles might sound compared to conventional vehicles with internal combustion engines (ICEVs). The electrified powertrain is responsible for a profoundly different profile in vibro-acoustical characteristics (NVH: noise, vibration, and harshness) and offers the opportunity to create specific sounds related to certain requirements and endorsing associations for increasing the user experience and aesthetic appreciation. The present study’s main aim was to evaluate the perceived emergence of the electric powertrain noise and its implications for perceived quality conveyed by it. Utilizing a sophisticated acoustic simulator presenting ambisonic 3D stimuli from eleven different electrified cars in four different driving scenarios, N = 65 participants evaluated the perceptibility of e-powertrain noise and perceived quality of the vehicle’s interior soundscape. We revealed the auditory modality as an integral part of assessing the product’s quality and gathered qualitative reference points for further investigations.

Sentiment mining has been a helpful mechanism that targets to understand the market feedback on certain commodities by utilizing user comments. In general, the process of yielding each comment is essentially associated with his/her criteria for rating (i.e., the degree of harshness) , which makes users provide biased comments. For instance, for a tolerant user, although the user is extremely dissatisfied with the product, harshness still makes her yield a neutral comment which cannot indicate the product quality. Existing work straightforwardly removes the comments of harsh users and those of tolerant ones, which is not the best strategy. To this end, we propose a harshness-aware sentiment analysis framework for product review. First, we depict the process of providing comments from users as a probabilistic graphical model in which the harshness is incorporated. Second, we employ a Bayesian-based inference for sentiment mining. Extensive experimental evaluations have shown that the results of the proposed method are more consistent with the expert evaluations than those of the state-of-the-art methods, and even outperform the method which infers the final evaluations with the ground truth of comments without considering users’ harshness.