Voltage and Resistance Estimation of Battery-Integrated Cascaded Converters

Nima Tashakor, Farshid Naseri, Jingyang Fang, Hans Schotten, Stefan Goetz

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review


Modular reconfigurable batteries, also known as smart batteries, are gaining significant traction, mainly due to the large environmental incentives and falling price of electronic components. Although they have many advantages compared to a hard-wired battery pack, complex monitoring circuit and numerous sensor requirement make it harder to compete with conventional systems in a cost-driven application. This paper proposes a novel approach to estimate parameters of each individual battery module without any direct measurement at their terminals. The proposed algorithm uses the output voltage and current of the load combined with the exact knowledge of the modules’ states to estimate the open-circuit voltage, ohmic resistance, and polarization resistance in the electric circuit model for each battery module. The method combined with Kalman filter demonstrates the feasibility of this method through simulations, where the proposed method achieves above 98% and 96% accuracies for estimation of the open-circuit voltage and equivalent resistance of the battery, respectively. Additionally, the method can decouple the two resistances with
Original languageEnglish
Title of host publicationIECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society
Number of pages6
Publication dateDec 2022
ISBN (Print)978-1-6654-8026-0
ISBN (Electronic)978-1-6654-8025-3
Publication statusPublished - Dec 2022
Event48th Annual Conference of the IEEE Industrial Electronics Society - Brussels, Belgium
Duration: 17 Oct 202220 Oct 2022


Conference48th Annual Conference of the IEEE Industrial Electronics Society
Internet address


  • Battery
  • Battery Management System


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