M. Mimer, L. E. Svensson, Volvo Trucks Corp, Gothenburg, Sweden
Spot welding will continue to be the dominating process for joining of thin steel sheets in the automotive industry for many years, due to the reliability and low cost of the process. The overall strength of a component is determined by the strength of the individual spot welds, together with parameters like spot interdistance, number of spot welds etc. Thus, the mechanical properties of spot welds are essential to know. From work based on mild strength steels, it is known that the strength of a spot weld is closely related to the properties of the base material and the size of the nugget in the spot weld. However, with the introduction of higher strength steels more complex relationships may appear. For example, joints between steels having large differences in strength are becoming much more common. Such joints may also be more difficult to weld, due to the differences in steel characteristics. To reduce cost and increase speed of product development, simulation is becoming more important. Simulation of the spot welding process can now be made on standard PC’s using the simulation program Sorpas™. With Sorpas™ the size of the nugget in a spot weld can be estimated. For prediction of the strength and hardness of spot welds, two different approaches have been used. A model was constructed using a DOE program, relating spot weld strength to base metal strength and hardness. As an alternative approach the hardness of a spot weld was estimated from the chemical composition of the spot welds, following equations given by Blondeau et al. In the paper, it is demonstrated how the chain of simulation programs can be used to predict the mechanical properties of spot welds in a wide range of steels.
Summary: In the finite element analysis used in development of new products of spot-welded steels, the mechanical properties of each spot weld is a key parameter. Prediction of such properties can be made using a chain of simulation software. Firstly, the spot size is simulated and secondly its properties are predicted using material composition and data from previous testing.