Fast Charge of Li-ion Batteries using a Two-Layer Distributed MPC with Electro-Chemical and Thermal Constraints

This paper presents a two-layer distributed model predictive control (MPC) algorithm developed for safe and fast charge of Li-ion batteries. The low-level MPC makes use of an equivalent hydraulic model (EHM) that captures the dynamics of relevant internal electro-chemical states. This controller calculates the optimal charging current that satisfies the constraints associated with side reactions in anode and cathode. The high-level MPC solves a temperature feasibility problem using a battery thermal model by setting boundaries on the square of the current defined by the low-level control in the previous step. Information is exchanged between layers until the current proposed by low-level controller is feasible for the high-level controller requirements. Simulation results of the aforementioned scheme are compared with an alternative case in which the lower layer predictor uses an equivalent circuit model (ECM). We show that for the same thermal model and tuning parameters, similar performance regarding constraints satisfaction and convergence of the solution for the control action can be obtained for the EHM and ECM. Finally, the distributed approach is compared to a single MPC in which the temperature constraint is enforced by resorting to the thermal equilibrium current, which is calculated off-line. The latter achieves similar results to the reference case at lower computational cost.