Lightweight design of drive axle housing based on reliability

2020 ◽  
Vol 6 (3) ◽  
pp. 294
Author(s):  
Yang Chen ◽  
Xiandong Liu ◽  
Yingchun Shan ◽  
Tian He
Keyword(s):  
Lightweight Design ◽  
Drive Axle ◽  
Drive Axle Housing

Lightweight design of drive axle housing based on reliability

2020 ◽  
Vol 6 (3) ◽  
pp. 294
Author(s):  
Tian He ◽  
Yingchun Shan ◽  
Yang Chen ◽  
Xiandong Liu
Keyword(s):  
Lightweight Design ◽  
Drive Axle ◽  
Drive Axle Housing

Finite Element Analysis of Automobile Drive Axle Housing Based on ANSYS

2015 ◽  
Vol 741 ◽  
pp. 223-226
Author(s):  
Hai Bin Li
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Dynamic Performance ◽  
Element Analysis ◽  
Shell Elements ◽  
Fea Model ◽  
Automobile Design ◽  
Housing Structure ◽  
Drive Axle ◽  
Drive Axle Housing

The performance of automobile drive axle housing structure affects whether the automobile design is successful or not. In this paper, the author built the FEA model of a automobile drive axle housing with shell elements by ANSYS. In order to building the optimization model of the automobile drive axle housing, the author studied the static and dynamic performance of it’s structure based on the model.

Statistical Analysis of Loader’s Drive Axle Housing Random Load Spectrum

2011 ◽  
Vol 338 ◽  
pp. 456-459 ◽  
Author(s):  
Bu Zheng Wen ◽  
Jian Min Li ◽  
Zhong Tao Pei ◽  
Sheng Yu ◽  
Cuan Yang Sun ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Weibull Distribution ◽  
Fatigue Reliability ◽  
Load Spectrum ◽  
Distribution Fitting ◽  
Random Load ◽  
Structural Fatigue ◽  
History Of ◽  
Drive Axle ◽  
Drive Axle Housing

Statistical analysis of load spectrum is an important part on structural fatigue life and reliability research, it is generally considered that axle’s load spectrum follows Weibull distribution. This paper tested ZL50 loader’s loading history of different working conditions , and obtained the corresponding load spectrum by rain-flow counting method, then analyzed three distributions’ (normal distribution, lognormal distribution, Weibull distribution) fitting degree of load spectrum and effect on the fatigue reliability. Results show that the highest fitting degree of distribution function should be used to fit load spectrum, which can reduce the error in structural fatigue reliability prediction.

Structural Strength and Modal Analysis of Heavy Truck Driving Axle Housing

2014 ◽  
Vol 556-562 ◽  
pp. 1119-1122 ◽  
Author(s):  
Teng Fei Ma ◽  
Kai Song Wang
Keyword(s):  
Modal Analysis ◽  
Optimization Design ◽  
3D Model ◽  
Structural Strength ◽  
Analysis Software ◽  
Element Analysis ◽  
Actual Use ◽  
Heavy Truck ◽  
Drive Axle ◽  
Drive Axle Housing

The automobile drive axle housing is an important safety component in vehicle. The 3D model of the drive axle housing is established in CATIA,Based on the actual use conditions for a heavy truck drive axle housing, this paper used finite element analysis software ANSYS to analyze the strength, stiffness and modal of the axle housing, which results show that the design of the axle housing is rational. These results of static analysis and modal analysis can provide some references for the development of new products and the structure optimization design in the future.

The Prediction for the Residual Life of Waste Drive Axle Housing Basing on Neural Network

2011 ◽  
Vol 308-310 ◽  
pp. 246-250
Author(s):  
Shou Xu Song ◽  
Ji Ru Zhao ◽  
Tao Liu
Keyword(s):  
Neural Network ◽  
Residual Stress ◽  
Fatigue Damage ◽  
Network Performance ◽  
Residual Life ◽  
Characteristic Parameter ◽  
Magnetic Intensity ◽  
Damage Degree ◽  
Drive Axle ◽  
Drive Axle Housing

In order to estimate the residual life of waste drive axle housing, the prediction model of waste axle housings with artificial neural networks is built in this paper. Take the deformation, residual stress and the gradient of magnetic intensity Kmax relating to axle housing’s fatigue damage degree as the input of neural network, and compare the testing residual life of the waste drive axle housing with its predicting residual life. The result demonstrates that: the deformation, residual stress and the gradient of magnetic intensity Kmax of axle housing as the characteristic parameter estimating the degree of fatigue damage, adopting trainbr training function can get good network performance and comparatively high precision of prediction. Besides, the longer the residual life of the waste axle housing is, the more precise the prediction life will be.

scholarly journals Analysis and experimental study on compound mechanical bulging process for medium-sized vehicle drive axle housing

2017 ◽  
Vol 207 ◽  
pp. 1737-1742
Author(s):  
Chun-guo Xu ◽  
Pan Li ◽  
Yong-qiang Guo ◽  
Jian Zeng ◽  
Hong Jin
Keyword(s):  
Experimental Study ◽  
Drive Axle ◽  
Drive Axle Housing

Analysis and Optimization Design on Drive Axle Housing of Light Commercial Vehicle

2013 ◽  
Vol 753-755 ◽  
pp. 1314-1317 ◽  
Author(s):  
Yu Cun Zhou ◽  
Miao Zhong Sun ◽  
Li Juan He
Keyword(s):  
Finite Element Analysis ◽  
Optimization Design ◽  
Commercial Vehicle ◽  
Weak Links ◽  
Stress And Strain ◽  
Element Analysis ◽  
Light Commercial Vehicle ◽  
The Finite Element Analysis ◽  
Drive Axle ◽  
Drive Axle Housing

Drive axle housing is one of the major load-supporting components of trucks. This paper takes a drive axle housing of a light commercial vehicle as the research object. The model of the drive axle housing is established by Pro/E software, on the basis of this model, the finite element analysis is carried by ANSYS to get the results of stress and strain under the defined constraints and loads, to find the weak links in the design. Aiming at achieving the goal of the least weight, the permission stress and displacement are defined and the thickness of the drive axle housing is considered as the design variable to optimize the design. The result of optimization design provides a theoretical guidance for truck driving axle housing designing.

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