Crankshaft is one of the most important components of the engine, its function is to summarize the reciprocating work of each cylinder piston, and in the form of rotating motion on the flywheel, and then output work, this paper aims to study the manufacturing and application of automobile engine crankshaft relying on computational fluid mechanics. In this paper, we first analyze the crankshaft structure using fluid mechanics. It focuses on several issues that are not currently yet agreed upon in crankshaft manufacturing, and on the process of detecting and incorporating multi-source information related to the remanufacturing process. Secondly, one of the key techniques, quality analysis and process parameter optimization based on nonlinear multivariate fitting, is deeply explored. We thoroughly study quality analysis based on multivariate nonlinear multivariate fitting and methods to optimize process parameters. The effect of the control parameters on the crankshaft performance is also analyzed. As an example, the effect of the spindle circularity and the crankshaft curvature on the final radial slip mass of the crankshaft is investigated. Based on constructing an uncertainty measurement model of the main crankshaft circularity and the crankshaft curvature, a nonlinear multivariate model is developed to illustrate the effect of the uncertainty on the radial flow of the heavy crankshaft. A batch of actually produced crankaxes was used as an example to study the effectiveness of the model. The experiment proved that the algorithm can increase the production qualified rate to about 85%.

Bulychev Nikolay. Manufacturing of Automobile Engine Crankshaft Dependent on Computational Fluid Mechanics. Kinetic Mechanical Engineering (2021), Vol. 2, Issue 4: 1-10. https://doi.org/10.38007/KME.2021.020401.

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