A Model Predictive Control Approach for Lithium-ion Capacitor Optimal Charging

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1 Citation (Scopus)

Abstract

Lithium-ion capacitors (LiCs) benefit from high power and energy density. They outperform Li-ion batteries in fast charging. The charging protocol is vital for LiCs, affecting the cell’s efficiency, safety, and lifetime. In this paper, an optimal charging scheme for LiCs has been developed. The charging current trajectory is obtained using model predictive control (MPC)-based optimization that minimizes the charging time, satisfying the cell’s operating conditions. An equivalent electro-thermal model of LiC has been considered in designing the charging scheme. The model parameters are experimentally identified considering the commercially available 2100F Musashi LiC cells. The performance of the proposed charging scheme has been evaluated via simulation studies. The results show that the MPC scheme charges LiC up to the desired SOC level in a CC-CV protocol, respecting the provided boundary conditions. For different initial SOC levels, power acceptance variation has been examined between CC and CV charging phases. Finally, the proposed scheme has been evaluated for different C-rates.
Original languageEnglish
Title of host publication2023 25th European Conference on Power Electronics and Applications, EPE 2023 ECCE Europe
Number of pages8
PublisherIEEE
Publication date8 Sept 2023
Pages1-8
Article number10264525
ISBN (Print)979-8-3503-1678-0
ISBN (Electronic)9789075815412
DOIs
Publication statusPublished - 8 Sept 2023
Event2023 25th European Conference on Power Electronics and Applications (EPE'23 ECCE Europe) - Aalborg, Denmark
Duration: 4 Sept 20238 Sept 2023

Conference

Conference2023 25th European Conference on Power Electronics and Applications (EPE'23 ECCE Europe)
Country/TerritoryDenmark
CityAalborg
Period04/09/202308/09/2023

Keywords

  • Capacitors
  • Europe
  • Fast charging strategies
  • Lithium ion
  • Model Predictive Control
  • Power electronics
  • Predictive models
  • Real-time systems
  • State estimation
  • Optimal charging
  • Lithium-ion capacitor (LiC)
  • Modeling
  • Model predictive control

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