Uncertainty analysis and optimization of automotive driveline torsional vibration with a driveline and rear axle coupled model. Issue 11 (2nd November 2018)

• Record Type: Journal Article
• Authors: Hao, Y. D.; He, Z. C.; Li, G. Y.; Li, Eric; Huang, Y. Y.
• Is Part Of: Engineering optimization. Volume 50:Issue 11(2018)
• Page Start: 1871
• Page End: 1893
• Publication Date: 2018-11-02
• Subjects: Driveline -- rear axle -- torsional vibration -- truncated probability model -- robust-based design optimization; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2017.1421952
• Languages: English
• ISSNs: 0305-215X

Abstract

ABSTRACT: The driveline torsional vibration issue is one of the most significant Noise, Vibration and Harshness (NVH) problems, especially in rear-wheel drive vehicles with manual transmission. In this article, a new driveline and rear axle coupled torsional vibration model (DRCTVM) is developed that considers the relationship between the driveline and the rear axle. The experiments show that the DRCTVM can provide much better results than the traditional model. In addition, for the first time, uncertainty theory is introduced to the analysis and optimization of driveline torsional vibration based on the DRCTVM. A truncated normal distribution is used to describe the uncertainty of DRCTVM, which considers both the probability distribution and the bounds of uncertain variables. Furthermore, robustness of the driveline torsional vibration was analysed using the Monte Carlo (MC) process and optimized using the Multi-Island Genetic Algorithm. The optimization results show that the proposed model and method are effective and improve the robustness of driveline torsional vibration performance.