Model predictive control of a hybrid energy storage system using load prediction

Hybrid Energy Storage Systems (HESS) enable the use of the advantages from different energy storages. In this work, the HESS comprises a battery with high energy density and a supercapacitor with high power density. To fully exploit the advantages of both modules within the HESS, a control strategy is needed. In this contribution, a computationally efficient model predictive control (MPC) strategy is presented for this task. Special focus is directed to the prediction of the power demand in a range of several seconds. This information is useful to follow a given power profile within the given limits of the energy storage system. Therefore, an energy transfer between battery and supercapacitor occurs depending on the expected power demand. Furthermore, the MPC manages nonlinear model equations, whereby the system behavior is accurately represented, while the presented control algorithm for a HESS is still real-time capable.