Multi-Layer Control for Hybrid Balancing Systems

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Hybrid balancing is a recently-proposed class of battery balancing systems that simultaneously provide capacity and thermal equalization, while enabling hybridization with supercapacitors. This integration of functions poses a challenging control problem, requiring the fulfillment of multiple objectives (e.g., reduction of charge and temperature imbalances, energy losses and battery stress) and the coordination of a large number of power converters. To tackle this challenge, we propose a multi-layer model predictive control (MPC) framework, which splits the control tasks into two layers. The first layer uses long prediction horizons and a simplified model of the energy storage system to compute the state-of-charge reference for the supercapacitors. The second layer uses module-level models of the battery pack to track this reference, while minimizing charge and temperature imbalances with a small prediction horizon. Simulation results demonstrate that the multi-layer MPC provides similar performance as single-layer MPC, but at a fraction of the computational effort.

Original languageEnglish (US)
Title of host publicationCCTA 2021 - 5th IEEE Conference on Control Technology and Applications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages839-845
Number of pages7
ISBN (Electronic)9781665436434
DOIs
StatePublished - 2021
Event5th IEEE Conference on Control Technology and Applications, CCTA 2021 - Virtual, San Diego, United States
Duration: Aug 8 2021Aug 11 2021

Publication series

NameCCTA 2021 - 5th IEEE Conference on Control Technology and Applications

Conference

Conference5th IEEE Conference on Control Technology and Applications, CCTA 2021
Country/TerritoryUnited States
CityVirtual, San Diego
Period8/8/218/11/21

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science

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