Examenspresentation av Mir Arash Keshavarz Kelachayeh och Yuhui Bi

Examiner: Torsten Wik

Abstract:
Li-ion battery cells, as the main energy source component of Electric Vehicles (EV), demonstrate complex electrical, chemical, thermal, and mechanical behaviour. Additionally, they sum up in large quantities to form the overall Energy Storage System (ESS) of targeted applications. Hence, real-time management, monitoring, and control of cells is necessary to ensure safe and efficient operation which is handled by Battery Management Systems (BMS). Due to strong dependency of batteries to temperature, one of the key tasks of a BMS is thermal management. This master’s project is aimed at developing a BMS function for battery cells’ core temperature estimation to provide more detailed thermal information alongside battery cells’ geometry. Two model-based estimation approaches are implemented using Kalman filtering and sliding-mode observation. Both approaches are implemented upon electro-thermal cell model derived by second order RC equivalent circuits where the coupled thermal side of the model are either of 1D lumped mass, or 2D finite difference types having heat transferred in conduction and convection modes. While all suggested solutions are shown to be executable in real-time, a detailed comparison for accuracy evaluation is performed. The reference for verification has been Computational Fluid Dynamics (CFD) 3D simulations performed under validated and known thermal parameters for a specific candidate battery cell. The proposed modelling approaches and estimation methods are evaluated in terms of estimation accuracy, performance, and parameter uncertainty.

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Mir Arash, Yuhui and Torsten