qTSL: A Multilayer Control Framework for Managing Capacity, Temperature, Stress, and Losses in Hybrid Balancing Systems

Ricardo de Castro, Helder Pereira, Rui Esteves Araujo, Jorge Varela Barreras, Herschel C. Pangborn

Research output: Contribution to journalArticlepeer-review

Abstract

This work deals with the design and validation of a control strategy for hybrid balancing systems (HBSs), an emerging concept that joins battery equalization and hybridization with supercapacitors (SCs) in the same system. To control this system, we propose a two-layer model predictive control (MPC) framework. The first layer determines the optimal state-of-charge (SoC) reference for the SCs considering long load forecasts and simple pack-level battery models. The second MPC layer tracks this reference and performs charge and temperature equalization, employing more complex module-level battery models and short load forecasts. This division of control tasks into two layers, running at different time scales and model complexities, enables us to reduce computational effort with a small loss of control performance. Experimental validation in a small-scale laboratory prototype demonstrates the effectiveness of the proposed approach in reducing charge, temperature, and stress in the battery pack.

Original languageEnglish (US)
JournalIEEE Transactions on Control Systems Technology
DOIs
StateAccepted/In press - 2021

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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