Fig. 1: Workflow.
From: Accelerating the transition to cobalt-free batteries: a hybrid model for LiFePO4/graphite chemistry
a Starting from field data (electric vehicles, grid, or home stationary storage), the proposed hybrid model merges the strengths of physics-based and machine-learning approaches for improved prediction performance. In this paper, we use EV driving data to train the machine-learning hysteresis model. b The hybrid model can be employed in battery performance analysis, synthetic data generation, and as the basis for reduced-order models.
