Abstract: A machine learning model may be trained for a target battery system. Reference initialization data may be generated by a reference battery system sharing one or more characteristics with the target battery system. Synthetic training data may be generated for the target battery system by determining simulated input parameters and simulated output parameters by supplying the simulated input parameters to a physics model. Upon determining that a subset of the reference initialization data matches a subset of the synthetic training data, a trained machine learning model based on the synthetic training data is determined. The trained machine learning model may be trained to predict a state of the target battery system based at least in part on one or more observed input parameters generated by the target battery system.