Abstract Summary
Printed Circuit Boards (PCB) used in electric vehicles are subject to mechanical vibrations that affect reliability. Here, especially solder joints are a critical point of PCBs that can be damaged by mechanical vibrations. The surface strain at the solder location is often seen as a critical mechanical parameter for the failure of solder joints and is used as a design criterion. Therefore, simulation during the design process needs to provide accurate results for the surface strains on the PCBs under specified loads. Due to model parameter uncertainty, a parameter calibration and model validation step is usually necessary. In this work, Bayesian model updating using experimental measurements is performed on PCBs. A comparison of the weights of the investigated PCBs shows that the material parameters are subject to considerable uncertainty. These uncertainties are likely due to small variations in the material composition or the production process. Thus, hierarchical Bayesian model updating is chosen as model updating method. This approach makes it possible to determine probability distributions that reflect the uncertainty of the model parameters. Since the PCBs only weigh a few grams, a sensor and its electric cables could have an impact on their mechanical behavior. Therefore, the dynamic behavior is measured by a laser Doppler vibrometer (LDV). The measurements are carried out on printed circuit boards that are fixed with adhesive joints. The model updating process considers modal data as well as frequency response functions. The updated parameters include the stiffness and damping properties of the PCB’s basic material and the adhesive. Since the updated numerical model of the PCB is to be used for the simulation of surface strains at the solder joints, further measurements are necessary for model validation. For this purpose, additional measurements of surface strains at different excitation frequencies are carried out with strain gauges.
