In the case of LIB simulations, the goal is to enable highly accurate voltage/capacity predictions while preserving the low computational complexity. If we compare this approach to other models used to simulate the voltage profiles of a battery, the target performance would be achieved by combining the high accuracy and low volume of data that PBMs offer, with the low computational cost of the ML models to get the best tradeoff between the techniques (Figure ). . This hybrid model used deep neural networks (DNNs) along with a reduced order PBM to predict the discharge curves, as well as end-of-discharge of batteries under different loading conditions. In particular, we highlight the high-flexibility of the ML component to correct for some of the missing physics and account for uncertainty in some model parameters.