A Reduced-Order Energy Balance Model for Weld Lobe Prediction in Resistance Spot Welding

                                  Resistance Spot Welding (RSW) remains the dominant joining process in automotive body-in-white manufacturing. Accurate prediction of weld nugget size and weldability lobe boundaries is essential for ensuring joint quality and process robustness. While finite element method (FEM)-based commercial tools provide high-fidelity multi-physics simulations, their computational cost, parameter sensitivity, and limited interpretability restrict their direct applicability for production-level decision making. This paper presents a reduced-order energy balance framework, commonly referred to as the Asari–Rashidi model, for predicting weld nugget diameter and weld lobe boundaries. The model is derived from first principles of electrical resistance heating and thermal energy balance, structured through a block-diagram representation linking equipment, material, and process parameters. Model formulation, governing equations, and assumptions are detailed, followed by a critical comparison with FEM-based techniques in terms of accuracy, robustness, computational efficiency, and industrial relevance.