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As a key component of in-vehicle intelligent voice technology, speech enhancement can extract clean speech signals contaminated by environmental noise to improve the perceptual quality and intelligibility of speech. It has extensive applications in the field of intelligent car cabins. Although some end-to-end speech enhancement methods based on time domain have been proposed, there is often limited consideration given to designing model architectures based on the characteristics of the speech signal. In this paper, we propose a new U-Net based speech enhancement framework that utilizes the temporal correlation of speech signals to reconstruct higher-quality and more intelligible clean speech.

During light to moderate braking at high speed, the local high temperature phenomenon can be observed on the brake disc surfaces, known as hot spots. The occurrence of hot spots will lead to negative effects such as brake performance fade, thermal judder and local wear, which seriously affect the performance of vehicle NVH. In this paper, based on the bench test of a ventilated disc brake, the basic characteristics of hot spots is obtained and the evolution process of temperature field and disc deformation is analyzed in detail. In temperature field, hot bands appear first and grow, migrate from inner and outer radius to the middle, with the growing temperature fluctuation and finally hot spots appear in the middle radius of the brake disc. The stable SRO waviness forms much earlier than the temperature fluctuation. In the stop brake studied in this paper, the SRO waviness stabilizes in main 7 order state which is lower than the final hot spot order.

Speech enhancement can extract clean speech from noise interference, enhancing its perceptual quality and intelligibility. This technology has significant applications in in-car intelligent voice interaction. However, the complex noise environment inside the vehicle, especially the human voice interference is very prominent, which brings great challenges to the vehicle speech interaction system. In this paper, we propose a speech enhancement method based on target speech features, which can better extract clean speech and improve the perceptual quality and intelligibility of enhanced speech in the environment of human noise interference. To this end, we propose a design method for the middle layer of the U-Net architecture based on Long Short-Term Memory (LSTM), which can automatically extract the target speech features that are highly distinguishable from the noise signal and human voice interference features in noisy speech, and realize the targeted extraction of clean speech.

Image corruptions due to noise, blur, contrast change, etc., could lead to a significant performance decline of Deep Neural Networks (DNN), which poses a potential threat to DNN-based autonomous vehicles. Previous works attempted to explain corruption from a Fourier perspective. By comparing the absolute Fourier spectrum difference between corrupted images and clean images in the RGB color space, they regard the noise from some corruptions (Gaussian noise, defocus blur, etc.) as concentrating on the high-frequency components while others (contrast, fog, etc.) concentrate on the low-frequency components. In this work, we present a new perspective that unifies corruptions as noise from high frequency and thus propose an image augmentation algorithm to achieve a more robust performance against common corruptions. First, we notice the 1/fα statistical rule of the natural image's spectrum and the channels-wise differential sensitivity on the YCbCr color space of the Human Visual System.

The vibration characteristics of hybrid vehicles are very different from that of traditional fuel vehicles. In this paper, the active and passive control schemes are used to inhibit the vibration issues in vehicle hybrid powertrain system. Firstly the torsional vibration mechanical model including engine, motor and planetary gear subsystems is established. Then the transient vibration responses of typical working condition are analyzed through power control strategy. Consequently the active and passive control of torsional vibration in hybrid powertrain system is proposed. The active control of the motor and generator torque is designed and the vehicle longitudinal vibration is reduced. The vibration of the planetary gear system is ameliorated with passive control method by adding torsional vibration absorbers to power units. The vibration characteristics in vehicle hybrid powertrain system are effectively improved through the active and passive control.

In view of the vibration and noise problem in the electric drive system, the vibration characteristics of its high-speed reducer are analyzed and studied. Through the vibration and noise bench test of the integrated electric drive system, the contribution of high-speed reducer gear meshing order vibration noise to the vibration noise of the electric drive system was studied. A rigid-flexible coupling dynamic model of high-speed reducer was established, and the accuracy of the model was verified. At the same time, based on the gear modification theory, the effects of different gear modification parameters on the peak-to-peak value of high-speed reducer gear transmission error, the amplitude of each order harmonic of the transmission error, and the vibration acceleration response of the high-speed reducer shell surface were studied. Genetic algorithm was used to optimize the gear modification parameters, and the optimization method was simulated and verified.

Driver behaviors provide abundant information and feedback for future Advanced Driver Assistance Systems (ADAS). Driver’s eye and head may present some typical movement patterns before executing driving maneuvers. It is possible to use driver’s head and eye movement information for predicting driver intention. Therefore, to determine the most important features related to driver intention has attracted widespread research interests. In this paper, a method to analyze the correlation between driver’s visual features and driver intention is proposed, aiming to determine the most representative features for driver intention prediction. Firstly, naturalistic driving experiment is conducted to collect driver’s videos during executing lane keeping and lane change maneuvers. Then, driver’s head and face visual features are extracted from those videos. By using boxplot and independent samples T-test, features which have significant correlation with driver intention are found.

Brake judder severely affects the riding comfort and safety of vehicle. For the brake corner system, a rigid-flexible coupling model is established based on ADAMS. In the model, brake pads, caliper, anchor and knuckle are flexible bodies, and the contacts between pads and disc and the contacts between pads and caliper are defined in detail. Meanwhile, the vibration acceleration of the brake corner components and the contact forces between disc and pads are used as evaluation index and the evaluation system of brake judder are improved. The analysis results show that the novel model and evaluation system can be used to predict brake judder effectively.

In order to establish the correlation between objective and subjective evaluation of brake pedal feel for passenger cars, road tests of brake pedal feel were carried out and an evaluation method was proposed. In the road tests, subjective scores and objective measurements were obtained under the conditions of uniform and emergency braking. The objective measurements include pedal preload, low deceleration pedal force and travel, moderate deceleration pedal force and travel, brake response time and brake linearity. Using the theory of analytic hierarchy process (AHP), the design process of the evaluation method was established. Key setups including the hierarchical structure model, the judgement matrix and the score calculation method of objective measurements were described in detail. Then, the correlation between subjective and objective scores was analyzed. It can be concluded that the evaluation method is effective and it can be applied to brake pedal feel assessment and adjustment.

It’s significant to analyze the Experimental performance of active control system for road noise. In this paper, a 2-channel active control system of vehicle road noise based on FXLMS algorithm is established. The complexity of Filtered-x Least Mean Square algorithm (FXLMS) is analyzed. The bench test and road test are carried out to test and analyze the performance of the control system. Firstly, the general mathematic model of the multi-channel active control system based on FXLMS algorithm is established. The computational complexity of the algorithm is analyzed. Secondly, a hardware-in-the-loop (HIL) test bench based on multi-channel FXLMS algorithm and a measurement system based on DASP are set up, to measure the noise reduction performance of active noise control system under various working conditions. Finally, the bench test and the road test are carried out and the results are analyzed.

It is a worldwide technical difficulty to predict brake squeal uncertainty and its propagation regularity due to key parameters’ randomcity. However, as a widely used stochastic finite element method, Monte Carlo Method costs a large amount of time in calculation. It is very important to establish a fast prediction method for brake squeal uncertainty due to key parameters. In this paper, perturbation concept was applied for disc brake squeal uncertainty prediction. Firstly, a simplified, parameterized finite element model of disc brake was established for complex eigenvalues calculation. Then sensitivity analysis of real parts and frequencies of complex eigenvalues to influence parameters was carried out based on the finite element model. A series of second order perturbation polynomial formulas were fitted from the sensitivity analysis results, which were used for calculation of uncertain complex eigenvalues.

Contact pressure distribution is one of the key influence factors and the essential causes of brake squeal. In this study, a drum brake finite element model is established using ABAQUS. The contact pressure distribution is simulated and the brake squeal instability is predicted based on the complex eigenvalue analysis method. Different contact pressure distributions are obtained by changing the structure and material parameters of the drum brake as well as altering the friction coefficient and the brake pressure. Then, the effect of contact pressure distribution on brake squeal is investigated, and the mechanism of the key contributing factors of brake squeal is studied. The innovation of the study is that it correlates squeal properties directly to the contact pressure distribution characteristics, which is considered as the essential influence mechanism of brake squeal.

In this paper, the initial disc thickness variation (DTV) of a ventilated disc in automotive brake system is modeled as sinusoidal function of the second order. The transient thermomechanical coupling properties of the brake system is simulated using finite element (FE) modeling. The system models and results were verified by a thermomechanical coupling test of a disc brake conducted on a brake dynamometer. By using varied evaluation indexes such as the temperature distribution, the normal stress and the elastic deformation of disc surfaces, the influences of the initial DTV and its direction as well as its amplitude on the thermomechanical coupling characteristics were analyzed.

The transient thermo-mechanical coupling dynamic model of ventilated disc brake with asymmetrical outer and inner thickness was established by means of Msc-marc software. In the model, pad backplate is simplified as a rigid surface with the same shape of brake lining and is bonded together with brake lining. Control node is associated with the rigid surface and the equivalent force that replaces the pressure is applied on the control nodes, of which the degrees of freedom in radial and rotational directions are constrained. With distribution characteristics of disc temperature field, normal stress field and lateral thermo-elastic deformation and thickness for the evaluation, the impacts of brake pad constraints on brake thermomechanical coupling characteristics were analyzed. The simulation results show that the brake pad back plate is an important structure in brake thermo-mechanical coupling analysis, which can’t be ignored in simulation computing.

The mechanism of automobile brake hot spots is unclear, which is a problem in the brake industry. Complex coupling between friction, heat, contact, and structure is the main difficulty in revealing the mechanism of brake hot spots. This paper proposes a new way to study the mechanism of hot spots by analyzing the deformation behavior of brake discs under asymmetric mechanical loading. The actual brake is simplified into a brake disc and friction lining system, and a transient dynamic finite element model under asymmetric mechanical loads is established to analyze the deformation characteristics of the brake disc. The normal deformation of the brake disc under asymmetric mechanical loads consists of two parts: low-frequency bending deformation and high-frequency waviness deformation, which are caused by the squeezing effect of the asymmetric brake pressure on the brake disc and the constraint modal vibration of the brake disc.

Disc brake squeal has always been a great challenge to the automotive industry. Based on the pin-on-disc system, a series of frictional squeal bench tests are carried out, which show significant time-varying characteristics on occurrence, sound pressure and frequency of frictional squeal. To investigate the generation mechanism of time-varying characteristics of frictional squeal, a four-degree-of-freedom (4DOF) lumped parameter model considering the time-varying tangential contact stiffness, the normal contact stiffness and the friction coefficient is established in this paper. Through both the system stability analysis and the transient response analysis, the time-varying frictional squeal is predicted successfully, and the generation mechanism and the key impact factors are also investigated in depth.

The vehicle permanent magnet synchronous motor has the advantages of high power density, compact structure and small size, which makes it generate heat obviously in the process of energy conversion, which seriously affects the service life of the motor and the performance of permanent magnet. Predicting magnet temperature is a challenging task, in lab and various specialized applications, infrared sensors or thermocouples are used to measure the temperature, but it cost a lot. In order to predict the temperature field of the motor, the hysteresis characteristic test of the core material of the motor is carried out in this paper. The hysteresis characteristic and loss of electrical steel under different temperature, magnetic field intensity and magnetic field frequency are tested. It is found that the loss of electrical steel increases with the increase of magnetic induction intensity and magnetic field frequency.

As the key assembly of new energy vehicles, the noise and vibration, and harshness (NVH) performance of integrated electric drive system directly affects the driving quality of new energy vehicles. In this paper, the vibration noise characteristic test of 3in1 electric drive system is carried out in the semi-muffler chamber. In order to compare and analyze the difference between 2in1 and 3in1 electric drive system NVH performance, the power electronics unit (PEU) in the 3in1 system was removed and placed on the ground away from the platform, and vibration noise test was carried out. In order to analyze the difference of NVH performance between 2in1 status and 3in1 status, the PEU in the 3in1 system was removed and placed on the ground far away from the bench, and the NVH test was carried out. The microphone signal at 1m position and the vibration acceleration signal of the key structural surface of the system are measured experimentally.

The noise, vibration, and harshness (NVH), also known as noise and vibration (N&V), is a critical feature for customers to assess the performance and quality of vehicles. NVH characteristics are higher among factors that customers use to judge the vehicle's quality.This book sets out to introduce the basic concepts, principles, and applications of the NVH development and refi nement of Battery Electric Vehicles (BEV), Hybrid Electric Vehicles (HEV), and Fuel Cell Electric Vehicles. Each type comes with its own set of challenges.

The parameter setting has a great influence on the noise reduction performance of the road noise active control (RNC) system. This paper analyzes and optimizes the parameters of the RNC system. Firstly, the model of the RNC system is established based on the FxLMS algorithm. Based on this model, taking the maximum noise reduction as the evaluation index, the sensitivity analysis of convergence coefficient, filter order, and reference signal gain was carried out using the Sobol method with the data measured by a real vehicle on asphalt pavement at 40km/h. The results show that there is no significant interaction between the three parameters. Then, using the idea of orthogonal experiment, the simulation results of the control model are analyzed by taking the maximum noise reduction as the evaluation index. It is found that the convergence coefficient has the greatest effect on the maximum noise reduction, followed by the filter order, and the reference signal gain has the least effect.