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Life time prediction for lead-free solder joints under vibration loads

15

Citations

1

References

2011

Year

Abstract

In this work the life time of solder joints of SMD components is studied under vibration loading. This kind of purely mechanical load is one of the main failure causes in automotive electronics. A test vehicle has been designed to enable vibration testing on SMD capacitors (size 0805). The test vehicle is distinguished with a line clamping and stripe shape which both leads to a concerted loading of the component solder joints. The test vehicles were analysed for their resonant frequency prior test and loaded with a sinusoidal vibration close to the resonant frequency for certain numbers of cycles. The loading of the individual components was measured using a vibrometer. Components were stressed with wave amplitudes from 0.3 mm up to 0.8 mm and normalised cycle counts from 1 up to 12. All tests were accomplished at room temperature. Cross sectioning was performed to evaluate damage location within and cracking of the solder joints. The observed damage location clearly differs to results from temperature cycling tests. Cracking of the intermetallic interface was not observed. Cracks propagated in the solder bulk. This enables a solder fatigue model since no interface effect is involved in the damage process. For a detailed analysis of the stress distribution within the solder joints and the determination of a damage criterion a 3D finite element model of the test vehicle was utilised. Transient analysis was performed to gain stress data for various settings of wave amplitudes. Characteristic stress values are derived for the different load intensities. The Basquin equation provides a possibility to model the life time for high cycle fatigue scenarios where only elastic deformations are assumed. Based on this Basquin equation a life time model for the solder joints was determined finally. Numbers of cycles to failure are taken from experiments and characteristic stress values from simulation to determine the model parameters.