Classification method for coal spontaneous combustion tendency based on excess oxidation reaction rate model

The oxygen consumption rate is commonly used as a characteristic parameter to evaluate the severity of coal–oxygen reactions; however, its applicability is limited under oxygen-deficient conditions in high-temperature environments. To address this limitation, this study selects single-particle-size coal samples from multiple mines with self-ignition risks and develops two oxidation reaction optimization models: excess oxygen consumption rate (EOCR) and excess CO generation rate (ECOGR). The macroscopic effects of coal rank, particle size, and temperature on spontaneous combustion behavior are examined through controlled heating experiments. The results indicate that EOCR and ECOGR increase continuously with temperature and provide more suitable indicators for evaluating the self-heating oxidation behavior of coal compared with the traditional oxidation reaction model. The relationship between the optimization models and particle size follows a power function, reflecting the fractal characteristics of porous media, where the regression factors At and Bt correspond to the experimental ambient temperature and physical structure of coal, respectively. These findings suggest that coal spontaneous combustion is influenced not only by its physical and chemical properties but also by environmental conditions. Accordingly, a set of identification indices (Vm, Vn) is proposed to classify the spontaneous combustion tendency of coal. The results indicate that a larger Vm corresponds to a higher degree of spontaneous combustion tendency, while a larger Vn indicates a greater combustion risk. This study provides a more robust characterization model and evaluation framework for identifying potential hazards in self-igniting or easily ignitable coal seams.