Resistance spot welding (RSW) is one of the oldest welding processes. While it has been the most successful sheet metal joining process in automotive industry, there are still certain quality and reliability issue due to the extremely fast and highly non-linear coupled electrical-thermal-mechanical welding process. Welding quality control has been studied by researchers in both industry and academia for many years. However, control of welding quality is difficult because the welding process is typically nonlinear and time-varying.

The relationship between quality and welding parameters is highly nonlinear and has not yet been systematically studied. Finite Element Modeling of RSW has been developed by many researchers and proves to be effective for welding process simulation. Most of them treat the welding process as an electrical-thermal process, while the mechanical deformation effect plays a key role in the welding process.

In this study, a finite element model based on dynamic resistance of RSW is set up to presented the highly nonlinear welding process. This model is not only helping us to have a clearly understanding of welding process but also predicting the welding quality. The entire spot welding process is treated as an electrical-thermal-mechanical process in the finite element model. After clearly understanding the welding process, from welding parameters to mechanical deformation, electrical field, then the thermal history, at last the nugget microstructure and nugget properties, the relationship between the welding parameters and the welding quality was found by this model. Welding experiments together with tensile test was used to verify the predicted parameters by finite element model which including welding current and nugget properties. Results show that the predicted parameters match very well with the experimental data. Overall, the present work indicated that finite element analysis can be very useful as an off-line observation tool to estimate the influence of welding parameters on the welding quality and predict/improve the welding quality.