Abstract: Embodiments disclosed herein include methods, systems and/or devices configured to generate historical parameters of a sigmoidal rate expression based on the sigmoidal rate expression and measured data of a battery. The embodiments may further be configured to predict future parameters of the sigmoidal rate expression based on the sigmoidal rate expression and the historical parameters. The embodiments may further be configured to predict an aging state of the battery based on the sigmoidal rate expression and the future parameters. Additional embodiments are directed to methods, systems, and/or devices configured to synthesize training data based on measured battery data, a sigmoidal rate expression, and ranges for parameters of the sigmoidal rate expression. The additional embodiments may further be configured to train a machine-learning model using the synthesized training data.