Lithium-ion Battery Management Using Physics-based Model Predictive Control and DC-DC Converters

This paper presents a novel application of model predictive control (MPC) to the problem of managing lithiumion cell performance using reduced-order physics-based electrochemical cell models and implemented via individual cell-mounted dual active bridge DC-DC converters. The proposed method uses MPC to safeguard cell-level electrochemical limits and has the potential to extend lifetime by mitigating certain mechanisms of cell degradation leading to capacity fade. The modular architecture is described and the control concepts are developed and demonstrated on an identified physics-based model of a 25 Ah lithium ion battery cell.