Energy Management Strategy for Hybrid Energy Storage System based on Model Predictive Control

Electric vehicle (EV) is developed because of its environmental friendliness, energy-saving and high efficiency. For improving the performance of the energy storage system of EV, this paper proposes an energy management strategy (EMS) based model predictive control (MPC) for the battery/supercapacitor hybrid energy storage system (HESS), which takes stabilizing the DC bus voltage and improving the efficiency of the system as two major optimization goals. In addition, an enumeration algorithm is presented to solve the optimization function. The experimental results show the performance of the proposed EMS which is able to enhance the overall instantaneous power and prevent the battery from overloading. Meanwhile, compared with the results of a single battery storage system, the maximum amplitude of the battery current in the HESS is reduced by 40.81% and whole system energy loss is reduced by 24.13% with the proposed power management strategy.

Automated summary

This paper proposes an energy management strategy based on model predictive control to improve the performance of the energy storage system in electric vehicles. The strategy aims to stabilize the DC bus voltage and improve system efficiency as optimization goals. An enumeration algorithm is used to solve the optimization function. Experimental results show that the proposed energy management strategy enhances overall instantaneous power and prevents battery overload. Compared to a single battery storage system, the proposed strategy reduces the maximum amplitude of battery current in the hybrid energy storage system by 40.81% and reduces overall system energy loss by 24.13%.