Optimal Cell Balancing with Model-based Cascade Control by Duty Cycle Adaption

Abstract Achieving higher provided battery capacity for operation by equalizing battery cell imbalances is the goal of passive and active battery balancing systems. The idea of energy transfer between battery cells is to increase the minimal energy level of the weakest cell in a battery stack of interconnected cells. For system modeling and balancing control the drifting balancing current and changing current slope caused by the change of cell voltage has not been given attention in literature so far, as well as the formulation of balancing systems from a point of view of control theory and applying optimization algorithms to realistic scenario. Firstly, we introduce an approach based on an average mean current model for the aggregated system of battery cells and inductive balancing circuits with dependency of voltage and duty cycle. The presented non-linear model is applied to the optimization of energy distribution to minimize energy differences in a battery system in an optimal manner, which can be done for any balancing topology with the presented model. Secondly, an adaption of the duty cycle for energy transfer switching is proposed for hard realtime constraints, so that the balancing currents are maximal for the whole balancing interval. The performance of an energy-based optimization algorithm compared to a voltage-based state of the art algorithm is demonstrated by simulations as well as the proposed subordinate control approach compared without duty cycle adaption.