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Details

Autor(en) / Beteiligte
Titel
Accelerated performance optimization of drive axle housings based on the pseudo-damage reservation method
Ist Teil von
  • Sustainable energy technologies and assessments, 2022-10, Vol.53, p.102612, Article 102612
Ort / Verlag
Elsevier Ltd
Erscheinungsjahr
2022
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • [Display omitted] •Constrain the DAH by inertia relief. The unconstrained state of the DAH is simulated as realistically as when the vehicle is driving.•Initial load spectra are acquired at an automotive proving ground. The dynamic load on the DAH is simulated for the vehicle under driving conditions.•The pseudo-damage reservation method (PDRM) is proposed. Fatigue analyses and result comparisons are performed, which verify the scientific validity of the accelerated spectrum.•A direct optimization model is constructed. A lightweight system with high computational efficiency and accuracy is proposed. The pseudo-damage reservation method (PDRM) is proposed and applied for improving the efficiency of mature drive axle housing (DAH) optimization for the first time. Additionally, the PDRM can substantially reduce the period of the fatigue bench testing. Thereafter, the fatigue life of DAH products is calculated using the inertia relief method with the initial load spectrum and the accelerated load spectrum. Simultaneously, the PDRM’s life error is 1.6%, which meets the engineering accuracy requirements. Ultimately, with the first-order intrinsic frequency and lifetime as the constraints and the weights as the optimization objectives, five design variables are selected to obtain the optimized solutions by the NSGA-II. The optimization results show that the optimized DAH reduces the weight by 13.9%, the material cost by 11.7%, the fatigue test period by 34.9%, and the computational effort by 26.5%. Thus, the optimization solution through the PDRM is efficient, economical, and reliable, which provides a good reference for the low-cost, sustainable production of DAHs.
Sprache
Englisch
Identifikatoren
ISSN: 2213-1388
DOI: 10.1016/j.seta.2022.102612
Titel-ID: cdi_crossref_primary_10_1016_j_seta_2022_102612

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