Search Results

With the development of light weight design and the high power output of an engine, and since the damping of rubber materials is relatively low, the effectiveness of torsional vibration (TV) control for an engine crankshaft with an ordinary Single Mode and rubber-damped TV Absorber (SMTVA) is limited. Here, a SMTVA references to a TVA with only one inertial mass. In this paper, the configurations of some Multi-Mode and rubber-damped TV Absorbers (MMTVA) having more than one inertial mass are introduced firstly, then a detailed procedure for modeling a torsional vibration system for a generic crankshaft system is presented. Thirdly, an optimization method for determining the design parameters of a MMTVA (mass ratios, frequency ratios and damping ratios) is developed. The proposed calculation method is based on reducing the torsional vibration of a crankshaft. An example is given for demonstrating the effectiveness of the proposed method and the MMTVA in reducing the TV of a crankshaft.

An Inline 4-cylinder engine is equipped with second-order balance shafts. When the engine is running under no-load acceleration conditions, the gear system of the balance shaft generated whine noise. In this paper, an analysis and experiment method for reducing the whine noise is presented. First, a flexible multi-body dynamic model of the engine is established, which includes shaft and casing deformation, micro-modification of the gears. Taking the measured cylinder pressure as input, the load on each gear of balance shaft gear system is calculated. In addition, the influence of tooth surface micro-modification on the meshed noise was analyzed. The results show that the dynamic meshing force between the crank gear and the shim gear is large under the original tooth surface micro-modification parameters, which is the main reason of the whine noise.

Electronic expansion valve as a throttle element is widely used in heat pump systems and flow characteristics are its most important parameter. The flow characteristics of the electronic expansion valve (EXV) with a valve port diameter of 3mm are studied, when the refrigerant R134a is used as the working fluid. The main factors affecting the flow characteristics are researched by adopting the orthogonal experiment method and single factor control method, for example, inlet pressure, inlet temperature, outlet pressure and valve opening. The results show that the expansion valve opening degree has the greatest influence on mass flow rate. In view of the complicated phase change of the refrigerant passing through electronic expansion valve, it is difficult to model the flow characteristics accurately.

The thermal management system, which is used to improve driving safety and thermal comfort, is one of the most important systems in electric vehicles. In recent years, researchers have coupled the heat pump system and the battery cooling system to effectively improve the heating COP (Coefficient of Performance). Therefore an accurate dynamic model of thermal management system plays a key role in investigating system performance and optimal control strategies. In this paper, an electric vehicle thermal management system based on four-way valve heat pump system is designed. The moving boundary method is improved by considering the unsteady flow of the external fluid, and then a 13-order dynamic model of the thermal management system is established. Firstly, the control equations of evaporator, condenser and chiller are derived according to the principle of conservation, and then a dynamic model of thermal management system is established in Simulink.

Uniaxial fatigue tests of rubber dumbbell specimens under different mean and amplitude of strain are carried out. An Extreme Learning Machine (ELM) model optimized by Dragonfly Algorithm (DA) is proposed to predict the fatigue life of rubber based on measured rubber fatigue life data. Mean and amplitude of strain and measured rubber fatigue life are taken as input variables and output variables respectively in DA-ELM model. For comparison, genetic algorithm (GA) and particle swarm optimization (PSO) are used to optimize ELM parameters, and GA-ELM and PSO-ELM models are established. The comparison results show that DA-ELM model performs better in predicting the fatigue life of rubber with least dispersion. The coefficients of determination for the training set and test set are 99.47% and 99.12%, respectively. In addition, a life prediction model equivalent strain amplitude as damage parameter is introduced to further highlight the superiority of DA-ELM model.

In the automotive industry, testing the sound absorption coefficient of acoustic materials through reverberation chambers has been widely used. The advantage of this method is that sound waves are incident on the surface of acoustic materials randomly, which is more in line with actual engineering. At present, most of the reverberation chamber design and construction refers to the international standard ISO 354-2003. However, although the design indicators of the reverberation chamber have already met the requirements of the standard ISO 354-2003, there are still some differences between the test results of different reverberation chambers on the same group of samples to be tested, and sometimes the differences are so big they affect the engineering applications. In this paper, the sound absorption coefficients of the same group of samples in different reverberation chambers are tested, and there are some differences in the sound absorption coefficients.

The mount bracket is an important part of the mount system, and its dynamic characteristics will affect dynamic characteristics of the mount system, which means it will affect NVH(Noise, Vibration, Harshness) of the vehicle. Based on the large error between the test result and the finite element analysis(FEA) result, the dynamic finite element model of the mount bracket can be modified from the material parameters and the equivalent boundary of the bolt joint. In this paper, a method to identify the parameters of the mount bracket model by combining modal test, FEA, and the mathematical optimization model was presented. Firstly, based on HyperStudy platform, the optimization objective was minimizing the natural frequency error between FEA and free mode test, and the material parameters of the bracket to be identified were used as design variables to build the optimization function. The global response surface method was used for iteration to complete the identification.

To enhance the transient vibration performance of the vehicle at key on and key off, a method for optimizing mount parameters of a powertrain mounting system (PMS) is proposed. Uncertainties of mount parameters widely exist in a PMS, so a method for optimizing mount parameters of a PMS, which treats the mount parameters of a PMS as uncertain, is also proposed in this paper. Firstly, a 13 degrees of freedom (DOFs) model including car body with 3 DOFs, a PMS with 6 DOFs and unsprung mass with 4 DOFs is established, and the acceleration of the active side of mounts is calculated. An experiment is carried out to measure the accelerations located at active and passive sides of each mount and the accelerations of seat track. A comparison is made between the measured and estimated accelerations, and the proposed model is validated. Two optimization methods for the PMS are proposed based on the developed 13 DOFs model.