Sifa Zheng

Modelling and simulation study on application of sliding-mode control for an active anti-roll system in a passenger car with air suspension

A hydraulic and pneumatic suspension was introduced to reduce the vehicle roll angle during cornering. A two-track vehicle model was used to dynamically analysis the body motion of the vehicle. The modelling and simulation of the suspension are validated with experiment. The design of the sliding-mode controller is introduced. The simulation results of the suspension with different control methods were compared. The results show the performance of active suspension with sliding-mode control is superior to that of a passive system. The sliding-mode controller leads to lower power consumption and longer lifetime of valve actuators of the suspension.

Acoustic Modelling and Analysis of Vehicle Interior Noise Based on Numerical Calculation

In this paper, various numerical calculation methods are rigorously combined to model and analyze the acoustic characteristics of a heavy truck cab. Firstly a brief introduction of different numerical calculation methods is given, then the finite element structure model and cavity model of the cab are built. The statistical energy analysis models of the cab, including structural subsystems and cavity subsystems, are also built and used in the high-frequency range. The panel acoustic contribution analysis and the energy transfer path contribution analysis are carried out to find the panels which contribute most to the sound pressure inside the cab. Based on the analysis results, structure modification of these panels has been proposed with acoustics topology optimized. The optimization result shows that the sound pressure level on the side of the driver’s right ear can be reduced by a few decibels. Necessary tests to validate the models are also administered.

Video visualization for moving sound sources based on binocular vision and short-time beamforming

Visualization of moving sound sources is very important for noise source identification of moving objects. In this paper, we introduce binocular vision technology to sound sources visualization. Binocular technology can not only obtain the visualization, but also is able to achieve the spatial measurement of moving objects and determine the relative position of moving sound sources and the microphone array automatically, so that the sound reconstruction plane can be closely attached to the moving object. Together with the short-time beamforming method, the sound map is accurately registered on to the video images, generating the sound video close to the moving sound sources. Then, by video slow motion, noises originated from moving sound sources in a real world are shown in a sound movie. To verify this method, an experiment for a non-stationary speaker in the anechoic room is conducted, where the speaker sound source is visualized and located accurately. Further verification experiments for an outdoor moving vehicle carrying speakers have also been conducted. Sound sources of the moving speakers are successfully visualized and located. The generated sound movie shows the origin of noises under real world conditions making noise source investigation easier and more accurate. These experimental results suggest that our visualization approach has potential for noise identification and control

Time-domain transfer path analysis of multiple moving noise sources

Identifying the contribution of different noise sources is a major step in reducing the impact of moving noise sources. Compared with classic transfer path analysis, operational transfer path analysis could improve efficiency of the identification process.To analyze the transient characteristics and their contribution of multiple moving noise sources, a method of time-domain transfer path analysis (TPA) is proposed. The dynamic transfer path model and transfer matrix calculation method are introduced. Simulation with three point sources is used to compare the identification results of the time-domain TPA and frequency-domain TPA. The application of the time-domain TPA to the identification of the pass-by noise source of a heavy duty truck is illustrated. The simulation and the application results show that time-domain TPA could be used to analyze the contribution of moving noise sources, and it takes less computational effort compared with frequency-domain TPA

Generation method for a two-dimensional random array for locating noise sources on moving vehicles.

Array based signal processing is a method for identifying important noise sources. Different array configurations have been used in the past. Random arrays are thought to have better resolution and precision for identifying moving noise sources than linear or cross arrays. But how to design optimal random configurations is a challenge. Based on property analysis and simulation of random arrays with different configurations, evaluation criteria for parameters of two-dimensional random arrays are proposed, and a random array generation method to locate the noise sources on moving vehicles is presented. It consists of an array unit partition, baseline filter and simulation based evaluation. The performance of the generated array is shown by identifying noise sources on a passenger car.

Decomposition and visualization of vehicle noise sources with transfer path acoustical holography

Decomposition of noise sources is an essential step to reduce the vehicle pass-by noise. Dynamic transfer path analysis has been used to describe the relation between the noise sources of the vehicle and the response point in the pass-by test. A transfer path acoustical holography method is introduced to decompose and visualize the vehicle pass-by noise sources, and the method is illustrated with a simulation of four moving point sources. The decomposition results for the four sources using transfer path acoustical holography are compared with that using acoustical holography method. It shows that the transfer path acoustical holography method has a better decomposition result. Finally, the proposed method is used to decompose the contributions of the sources in a commercial truck. The results show that the transfer path acoustical holography can be used to decompose and visualize the vehicles noise sources in the pass-by test.

Intelligent Vehicle Platform and Signal Processing Method Applied to Cooperative Vehicle Infrastructure

The technology of intelligent cooperative vehicle infrastructure helps to improve road traffic safety and efficiency. The intelligent vehicle platform is the key equipment for research and validation of the technology of intelligent cooperative vehicle infrastructure. First, the general requirements of intelligent vehicle platform as well as the platform vehicle motion and the way of gaining status information based on external sensors are introduced with a focus on the signal filtering and calibration of vehicle sensors. The intelligent vehicle platform established is demonstrated to gain status information of vehicle motion accurately through a comparison test and becomes the key device for the intelligent cooperative vehicle infrastructure research.

DGPS-based Vehicle State Estimation in V2I Cooperative System

A sideslip angle estimation algorithm based on DGPS in V2I cooperative system is proposed. The vehicle kinematic model is built to estimate vehicle yaw angle and sideslip angle; meanwhile a two-order kalman filter is used to fuse information from different sources. The first order kalman filter is available for processing lateral acceleration, longitudinal acceleration and yaw rate collected by IMU (inertia measurement unit); this information is used as the time update of vehicle model. The second order kalman filter is utilized to fuse vehicle location heading angle, which are collected by DGPS in cooperative system. This information is used as the measurement update of vehicle model. Steady-state cornering test results show that the algorithm is effective, even if the vehicle is in high lateral acceleration. The algorithm suits vehicle safety control requirements in V2I cooperative system.

Contribution of Pass-by Noise Sources with Acoustic Holograph and Dynamic Transfer Path Model

A dynamic transfer path model was used to describe the relation between the sources on the vehicle and the test point on the ground for pass-by test. The noise signals both from the vehicle and the pass-by test were simultaneously recorded with a wireless device. The Tikhonov regularization method was described. The contribution of the pass-by noise was further analyzed and visualized with acoustic holograph. Finally, the contribution of a commercial vehicle is checked with the proposed method.

Decomposition of moving vehicle noise with dynamic transfer model and acoustic holograph

Identifying the moving noise of vehicles is the important step to make the optimal countermeasures. A dynamic transfer path model was proposed to describe the relation between the sources on the vehicle and the test point on the ground.The noise signals both from the vehicle and the pass-by test were simultaneously recorded with a wireless device. The parameters in the dynamic model were estimated, and the results with singular value decomposition and Tikhonov regularization were compared using simulation and experiment. The contribution of the sources was decomposed with the dynamic transfer model and acoustic holograph at any test location. Finally, the proposed method was used to decompose the contributions of the sources in a bus. The results show: the dynamic transfer path analysis could be used to identify each of the noise sources and decompose their contribution in the pass-by test.