Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

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

Version 1 : Received: 17 January 2021 / Approved: 19 January 2021 / Online: 19 January 2021 (10:56:21 CET)

How to cite: Ferahtia, S.; Djerioui, A.; Mesbahi, T.; Houari, A.; Zeghlache, S.; Rezk, H.; Paul, T. Optimal Adaptive Gain LQR-based Energy Management Strategy for Battery-Supercapacitor Hybrid Power System. Preprints 2021, 2021010371 (doi: 10.20944/preprints202101.0371.v1). Ferahtia, S.; Djerioui, A.; Mesbahi, T.; Houari, A.; Zeghlache, S.; Rezk, H.; Paul, T. Optimal Adaptive Gain LQR-based Energy Management Strategy for Battery-Supercapacitor Hybrid Power System. Preprints 2021, 2021010371 (doi: 10.20944/preprints202101.0371.v1).

Abstract

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 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 compute the required gains to achieve the desired power. The fact that the developed algorithm takes disturbances into account increases the power ele-ments’ life expectancies and supplies the power system with the required power

Subject Areas

Battery; Supercapacitor; Hybrid power system; Optimal control; DC/DC converter; Energy management strategy

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.