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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 Energy management strategies for charge-sustaining hybrid electric vehicles reduce fuel consumption and maintain battery pack state of charge while meeting driver output power demand. The equivalent consumption minimization strategy is a real-time energy management strategy that makes use of an equivalence ratio to quantify electric power consumption in terms of fuel power consumption. The magnitude of the equivalence ratio determines the hybrid electric vehicle mode of operation and influences the ability of the energy management strategy to reduce fuel consumption as well as maintain the battery pack state of charge. The equivalent consumption minimization strategy in this article uses three Willans line models, which have an associated marginal efficiency and constant offset, to model the performance in the hybrid electric vehicle controller.

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 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 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.

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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 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.

Abstract In order to improve the squeak and rattle (S&R) performance level of automotive interiors, the contact nonlinear characteristics of structural components need to be considered when performing interior noise analysis. The finite element model of S&R analysis of the interior assembly is built, and the time-domain vibration characteristics of the contact points between the interior panels are analyzed by applying external forced excitation. The interaction force between contact points is obtained according to the contact equivalent model between interior materials. The external excitation and internal interaction force are analyzed as the total excitation to obtain the response results. Through experimental verification, compared with the S&R performance division method, the analysis results are consistent with the test results. Based on this model, S&R risk optimization is carried out, and the risk level is significantly reduced.

Abstract Connected fuel cell vehicles (C-FCVs) have gained increasing attention for solving traffic congestion and environmental pollution issues. To reduce operational costs, increase driving range, and improve driver comfort, simultaneously optimizing C-FCV speed trajectories and powertrain operation is a promising approach. Nevertheless, this remains difficult due to heavy computational demands and the complexity of real-time traffic scenarios. To resolve these issues, this article proposes a two-level eco-driving strategy consisting of speed planning and energy management layers. In the top layer, the speed planning predictor first predicts dynamic traffic constraints using the long short-term memory (LSTM) model. Second, a model predictive control (MPC) framework optimizes speed trajectories under dynamic traffic constraints, considering hydrogen consumption, ride comfort, and traffic flow efficiency.

Abstract In recent years, active sound design (ASD) has become one of the most important research topics in the field of active sound control technology. For electric vehicles (EVs), road noise and wind noise become the dominant contributors to the interior noise level due to the elimination of internal combustion engines (ICEs). In this case, different vehicle brands tend to resemble each other in the perspective of the interior sound quality, leading to the loss of the distinctive interior sound characteristics and brand image. In order to restore the brand DNA characteristics, ASD is a viable and implementable choice to break the dilemma the next-generation EVs would confront. Sound amplitude control strategy plays a key role in drivers’ subjective perception during dynamically operating an EV equipped with an ASD system.

Abstract This article presents a method to estimate the State of Charge (SOC) in Lithium-ion batteries of Hybrid Electric Vehicles (HEVs) with Artificial Neural Networks (ANNs). The inputs of the SOC estimation algorithm are the measured values of current, voltage, and temperature. In the article, two different battery packs are considered for a power-split full HEV. The training and validation datasets needed for developing the ANNs are generated exploiting a numerical model of two different configurations of an HEV performing real-world driving missions or the Worldwide Harmonized Light Vehicle Test Procedure (WLTP) cycle, while the testing dataset is collected experimentally on battery cells. Specifically, the capacity values for the considered battery pack sizes are 1.82 kWh and 1.06 kWh. The proposed method uses a Nonlinear AutoRegressive with eXogenous input (NARX) recurrent ANN, which has been observed to have reasonable computational cost in prior research.

Abstract The power battery cooling system of a hybrid electric vehicle is composed of a fan and duct assembly with its inlet positioned inside the vehicle cabin. For the prototype vehicle considered in this work, the air inlet is positioned on the package tray due to limited feasible choices. When the battery temperature is over rated limit, the cooling fan starts to operate to cool the battery system. Propelled by the fan in the cooling system, the air in the passenger compartment enters the duct inlet, and rushes through the air duct to reach the battery pack to fulfill the intended cooling function. In this case, the rear seat occupants could clearly perceive the existence of an annoying whirring noise. In this paper, the characteristics of the battery air cooling system and its working principles are briefly described. The air inlet noise generation mechanism and its frequency characteristics are then analyzed.

Abstract The control of road structure noise has always been the focus and difficulty of automobile vibration and noise reduction. Aiming at the control of road structural noise, a maglev actuator suitable for automobile suspension was designed. First, the working principle of the maglev actuator and the actuator output force with the finite element model were analyzed. Based on this analysis, the structural design of the maglev actuator was completed. Second, based on a domestic SUV passenger car as a platform, the overall layout of the maglev suspension and its control system design were completed, and a suspension model equipped with a maglev actuator was established. Finally, the vibration isolation effect of maglev suspension was compared and analyzed under random road excitation.

Abstract Noise, vibration, and harshness (NVH) is a key aspect in the vehicle development. Reducing noise and vibration to create a comfortable environment is one of the main objectives in vehicle design. In the literature, many theoretical and experimental methods have been presented for improving the NVH performances of vehicles. However, in the great majority of situations, physical prototypes are still required as NVH is highly dependent on subjective human perception and a pure computational approach often does not suffice. In this article, driving simulators are discussed as a tool to reduce the need of physical prototypes allowing a reduction in development time while providing a deep understanding of vehicle NVH characteristics. The present article provides a review of the current development of driving simulator focused on problems, challenges, and solutions for NVH applications.

Abstract Various internal combustion (IC) engine condition monitoring techniques exist for early fault detection and diagnosis to ensure smooth operation, increased durability, low emissions, and prevent breakdowns. A fault, such as piston slap, can damage critical components like the piston, piston rings, and cylinder liner and is among those faults that may lead to such consequences. This research has been conducted to monitor piston slap conditions by analyzing the engine vibration and acoustic emission (AE) signals. An experimental setup has been established for acquiring vibration and AE sensor signatures for various piston slap severity conditions. Time-domain features are extracted from vibration and AE sensor signatures, and among them, the best features are selected using one-way analysis of variance (ANOVA) to create machine learning (ML) models. Apart from individual sensor feature classification, the feature fusion method increases the prediction accuracy.

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