Predicting the fatigue life of an automotive coil spring considering road surface roughness

Putra, T. E.; Husaini, Husaini; Machmud, M. Nizar

doi:10.1016/j.engfailanal.2020.104722

Cited by 33 publications

(10 citation statements)

References 16 publications

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“…This is important so as to collect loading signals with various behaviours. The car velocity in the university campus, industrial, and rural areas was maintained at 20–40 km/h, while on the highway, it was 70–80 km/h [ 22 ]. The road tests were repeated to collect 30 loading signals from each type of road.…”

Section: Methodsmentioning

confidence: 99%

Fatigue Life Modelling of Steel Suspension Coil Springs Based on Wavelet Vibration Features Using Neuro-Fuzzy Methods

et al. 2023

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This study proposed wavelet-based approaches to characterise random vibration road excitations for durability prediction of coil springs. Conventional strain-life approaches require long computational time, while the accuracy of the vibration fatigue methods is unsatisfactory. It is therefore a necessity to establish an accurate fatigue life prediction model based on vibrational features. Wavelet-based methods were applied to determine the low-frequency energy and multifractality of road excitations. Strain-life models were applied for fatigue life evaluation from strain histories. ANFIS modelling was subsequently adopted to associate the vibration features with the fatigue life of coil springs. Results showed that the proposed wavelet-based methods were effective to determine the signal energy and multifractality of vibration signals. The established vibration-based models showed good fatigue life conservativity with a data survivability of more than 90%. The highest Pearson coefficient of 0.955 associated with the lowest RMSE of 0.660 was obtained by the Morrow-based model. It is suggested that the low-frequency energy and multifractality of the vibration signals can be used as fatigue-related features in life predictions of coil springs under random loading. Finally, the proposed model is an acceptable fatigue life prediction method based on vibration features, and it can reduce the dependency on strain data measurement.

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Section: Methodsmentioning

confidence: 99%

Fatigue Life Modelling of Steel Suspension Coil Springs Based on Wavelet Vibration Features Using Neuro-Fuzzy Methods

et al. 2023

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“…The higher amplitudes in fatigue damage analysis represent high damage. Kurtosis is affected by peaks present in a variable load data [ 48 ].…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Vibration-Based Fatigue Analysis of Octet-Truss Lattice Infill Blades for Utilization in Turbine Rotors

et al. 2022

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Vibration fatigue characteristics are critical for rotating machinery components such as turbine rotor blades. Lattice structures are gaining popularity in engineering applications due to their unique ability to reduce weight and improve the mechanical properties. This study is an experimental investigation of octet-truss lattice structure utilization in turbine rotor blades for weight reduction and to improve vibration fatigue characteristics. One completely solid and three lattice infilled blades with variable strut thickness were manufactured via additive manufacturing. Both free and forced experimental vibration analyses were performed on the blades to investigate their modal and vibration fatigue characteristics. The blades were subjected to random vibration using a vibration shaker. The response was measured using a triaxial accelerometer in terms of vibration acceleration time histories in the X, Y, and Z directions. Results indicate a weight reduction of up to 24.91% and enhancement in the first natural frequency of up to 5.29% were achieved using lattice infilled blades. The fatigue life of the blades was investigated using three frequency domain approaches, namely, Lalanne, Dirlik and narrow band. The fatigue life results indicate that the 0.25 mm lattice blade exhibits the highest fatigue life, while the solid blade exhibits the lowest fatigue life of all four blades. The fatigue life of the 0.25 mm lattice blade was 1822-, 1802-, and 1819- fold higher compared to that of the solid blade, using the Lalanne, Dirlik, and narrow-band approaches, respectively. These results can serve as the first step towards the utilization of lattice structures in turbine blades, with thermal analysis as the next step. Therefore, apart from being light weight, the octet-truss lattice infilled blades exhibited superior vibration fatigue characteristics to vibration loads, thereby making them a potential replacement for solid blades in turbine rotors.

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“…Putra et al determined the life of an automotive coil spring due to road surface roughness. However, there have been few studies on how the surface flaw defects generated during the manufacturing process affect the life of the automotive coil spring 6 .…”

Section: Introductionmentioning

confidence: 99%

Influence of the surface flaws in oil-tempered wires on the fatigue life of automotive engine valve springs

Ahn²,

Lee

2022

Sci Rep

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The purpose of this study is to evaluate the fatigue life of an automotive engine valve spring when the micro defect is applied to a 2300 MPa-class oil-tempered wire (OT wire) with 2.5 mm of diameter as the critical flaw depth. First, the deformation of the surface flaws in the OT wire during the valve spring manufacturing processes was derived via FE analysis using the sub-modeling technique, and the residual stress of the final spring was measured and applied to the spring stress analysis model. Second, the strength of the valve spring was analyzed to examine the presence of residual stress and compare the applied stress levels by the surface flaw. Third, the influence of micro defects on the fatigue life of the spring was evaluated by applying the stress on the surface flaw derived through the spring strength analysis to the S–N curve derived through a rotary bending fatigue test with the OT wire. The flaw depth of 40 µm, which is the existing criterion for surface flaw management, does not reduce the fatigue life.

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Predicting the fatigue life of an automotive coil spring considering road surface roughness

Cited by 33 publications

References 16 publications

Fatigue Life Modelling of Steel Suspension Coil Springs Based on Wavelet Vibration Features Using Neuro-Fuzzy Methods

Fatigue Life Modelling of Steel Suspension Coil Springs Based on Wavelet Vibration Features Using Neuro-Fuzzy Methods

Vibration-Based Fatigue Analysis of Octet-Truss Lattice Infill Blades for Utilization in Turbine Rotors

Influence of the surface flaws in oil-tempered wires on the fatigue life of automotive engine valve springs

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