Display omitted •Automatic kinetic resolution of thermal runaway from peak overlapping DSC profiles.•Rapid initial parameter estimations with a Gaussian surrogate-assisted database.•Simplified dvisional kinetic resolution based on reaction temperature ranges.•Optimal solution selection fusing error-based and information-based criteria.•Algorithm validation with DSC datasets from types of lithium-ion batteries. Accurate kinetic resolution of thermal runaway (TR) for lithium-ion batteries (LIBs) plays a central role in battery safety design and early warning. However, simultaneous extraction of the number and kinetic parameters of TR reactions from multi-peak overlapping differential scanning calorimetry (DSC) profiles is a complicated nonlinear programming optimization problem. A Gaussian surrogate-assisted separate optimization framework is proposed to address the kinetic resolution problem. First, an offline equivalent kinetic database, based on the geometric similarity of heat flow peaks and Gaussian functions, is designed to provide initial parameter estimations for multiple reactions. Second, an adaptive range division method, based on priori local extrema, is proposed to divide the DSC profile into separate ranges of fitting (ROF) to assist the key mechanism selection. Third, divisional kinetic resolution is performed for each ROF where kinetic models initialized by the above database are utilized to fit sub-range profiles and then potential solutions are searched based on a posteriori error-based criterion. Finally, Bayesian information criterion is utilized for the optimal solution selection among the combinations of potential solutions for multiple ROFs. The proposed framework is validated through experimental data from the DSC tests of types of LIBs. The results illustrate the applicability and efficiency of the proposed framework.