Optimal Adaptive Gain LQR-Based Energy Management Strategy for Battery-Supercapacitor Hybrid Power System

This paper aims at presenting an energy management strategy (EMS) based upon optimal control theory for a battery-supercapacitor hybrid power system. The hybrid power system consists of a lithium-ion battery and a supercapacitor with associated bidirectional DC/DC converters. The proposed EMS aims at computing adaptive gains using the salp swarm algorithm and load following control technique to assign the power reference for both the supercapacitor and the battery while achieving optimal performance and stable voltage. The DC/DC converter model is derived utilizing the first-principles method and computes the required gains to achieve the desired power. The fact that the developed algorithm takes disturbances into account increases the power elements' life expectancies and supplies the power system with the required power.

Automated summary

This paper introduces an energy management strategy based on optimal control theory for a battery-supercapacitor hybrid power system. The strategy calculates adaptive gains and utilizes load following control technique to assign power reference, aiming at achieving optimal performance and stable voltage. By considering disturbances, the developed algorithm increases power elements' life expectancies and ensures supply of required power to the system.