3 Master’s Dissertation in 2022 from UAVR partner

INSTBAT was present to the BATTERY2030+ Annual conference May 9-10th 2023 Uppsala (Sweden)
13 Oct 2023
Publication on Advanced Sensor Journal
13 Oct 2023

The INSTABAT project resulted in 3 Master’s Dissertations in 2022 from UAVR partner:


  • Student: Fábio Henrique Baptista de Freitas

Title: “Development of optical fiber sensors to evaluate the performance and safety of lithium-ion batteries”.

Date: December, 2022.


Abstract: In this work, hybrid optical fiber sensors based on Fabry-Perot Interferometers (FPIs) and Fiber Bragg Grating (FBG) sensors were successfully developed and characterized to discriminate two impactful parameters (pressure and

temperature) internally and externally simultaneously on cylindrical lithium-ion batteries (LiB) in order to improve their operation in safety conditions.


  • Student: Paulo Alexandre Silva Cardoso

Title: “Numerical model and state estimator for thermal monitoring of a Li-ion battery”.

Date: December, 2022.


Abstract: The main focus of this work was the development of a virtual thermal model of a lithium battery for real time monitoring of its thermal behavior. For that effect, a thermal model based on a spatial discretization was implemented with an unscented kalman filter.


  • Student: Ana Carlota Cação Moreira

Title: “Commercial software-based numerical simulations to reproduce the 3D electrochemical-thermal behaviour

of lithium-ion batteries”.

Date: December, 2022.


Abstract: This thesis contributes to the development of a thermal virtual sensor by developing a 3D battery model. The model is developed using the softwares Siemens Battery Design Studio and StarCCM+. Their potential to model the batteries available at the laboratory is also evaluated. Electrochemical, equivalent-circuit, and thermal models are explored. The NTGP (Newman, Tiedemann, Gu, Peukert) and RCR (Resistance, Capacitive, Resistive) models are used to model the prismatic battery of choice.