Search Results

Based on the technology of the order tracking and extraction, a software for the modulation of sound quality of automotive order sound is developed in this paper. The order analysis, the amplitude modulation of order sound in specific speed range and the calculation of the functional expression of the order sound amplitude are integrated in this software. Furthermore, a side-valve interpolation correction algorithm (SV-ICA) is proposed to solve the problem that the smooth transition of the order sound curve at endpoints cannot be guaranteed, which would result in the appearance of abnormal noise in the modulated sounds. The application of built software in constructing the automobile sounds with the sound quality of sportiness is demonstrated.

During the drivability test process, a large amount of noise generated by a series of internal and external factors of the vehicle reduces the accuracy of the drivability evaluation. To solve this problem, this paper introduces the EEMD denoising method and compares the denoising effects of the EMD denoising method and EEMD denoising method on the original signal using the entropy weight evaluation index. In addition, the optimal parameter setting is obtained by comparing the denoising results of different parameter settings in the EEMD denoising method. The results show that when the white noise is integrated 3000 times and the standard deviation of white noise is 0.1, the EEMD noise reduction method is the best, and the comprehensive score of noise reduction is 0.732 points higher than that of EMD.

Signage recognition is one of the hot topics in recent years. It has important applications in intelligent traffic and autonomous driving of smart cars. This paper designs a road marking recognition method combining OPSA point set distance and wavelet transform. The method consists of three main phases: 1) image denoising, restoration, 2) feature extraction, and 3) image recognition. First, a Gaussian-smoothing filter used to attenuate or remove irrelevant information in the image, enhance related information in the image, and achieve image denoising. In the feature extraction stage, the feature extraction and recognition method based on wavelet transform adopted to overcome the deficiency of the traditional Fourier feature extraction method, ensure that high frequency information is not lost, and low frequency information is not lost. Finally, the OSPA point set used to identify distance markers.

The aerodynamic noise of the reactive muffler is generated inside the muffler and mixed with the noise of the muffler body, which is difficult to be measured in the exhaust system. Based on two-microphone transfer function method and transmission loss of mufflers in the absence of airflow, this paper proposes a method for measuring the aerodynamic noise of the muffler. On the built-in muffler aerodynamic noise test bench, a special sampling tube was designed to measure the aerodynamic noise of the muffler at different flow velocity. For the sound absorption end with large reflection coefficient, the test and simulation data have large error at low frequency, and a correction formula that can eliminate the reflection of sound waves at the end of the test pipeline and form multiple reflections in the upstream and downstream is derived.

Blade Electric Vehicle (BEV) with a light body plays an important role in saving the energy and reducing the exhaust emission. However, reducing the body weight need to meet the heterogeneous attributes such as structural, safety and NVH (Noise, Vibration and Harshness) performance. With the rapid development of finite element (FE) analysis technology, simulation analysis is widely used for researching the complex engineering design problem. Multidisciplinary Design Optimization (MDO) of a BEV body is a challenging but meaningful task in the automotive lightweight. In present research, the MDO is introduced to optimize a BEV Body-in-White (BIW).

The multi-functional mechanical arm equipped on engineering vehicle can achieve different functions by installing different mechanism devices through the interface at the end of the mechanical arm. It can achieve functions like engineering construction and road rescue. Mechanical arm systems often work in complex environments, which requires good reliability and safety of the boom system. When the mechanical boom is working, the pressure of each luffing cylinder is large, and the contact force and acceleration of each boom are complex, which requires a certain degree of verification and optimization before it can be put into production. In this paper, a virtual prototype of a vehicle mounted hydraulic mechanical arm with four booms is established. Through ADAMS, the dynamic analysis of mechanical arm under multiple working conditions is carried out, the movement parameter changes and the pressure changes of each luffing cylinder are analyzed.

Squeal noise in vehicle disc brakes is perceived by comsumers as both annoying and warranty cost. The mechanism is considered a mode coupling phenomenon also referred to as coalescence. In this paper, the system eigenvalues have been computed using a technique based on the • nite element method in order to obtain the dynamical properties of the disc brake assembly. The simulated squeal results were compared with the brake noise test that was in accordance with SAE J2521 standard and showed good correlation for some squeal frequencies which indicated that the research on disc brake squeal using complex mode could predict squeal propensity of the disc brake. Among the methods that have been used to control squeal noise, increasing the system damping has been shown to be very effective. The most commonly used method to increase system damping consists of attaching multi-layer laminates on the back of the brake pads.

As motor assembly of Battery Electric Vehicle (BEV) replaces engine system of Internal Combustion Engine (ICE) vehicle, interior structure-borne noise induced by road random excitation becomes more prominent under middle and high speed. The research is focused on central driving type BEV. In order to improve interior noise in middle and low frequency range, dynamic load of BEV body must be identified. Consequently the structural noise induced by road excitation is conducted. The limitations of common identification method for dynamic body load are analyzed. The applied several identification methods are proposed for deterministic dynamic load such as engine or motor. Random dynamic load generated by road excitation is different from deterministic dynamic load. The deterministic load identification method cannot be applied to the random load directly. An identification method of dynamic body load for BEV is presented based on power spectrum decomposition.