Examenspresentation av Soleil Kylander och Stefan Momente

Abstract:
The percentage of available electric charge in an electrical vehicle's battery is referred to as the state of charge (SOC). The accuracy of the estimated minimum, maximum, and average SOC is of great importance to safely operate the vehicle. However, the SOC estimations are computationally expensive and so this thesis aims to reduce this cost while maintaining accuracy. Six different algorithms are proposed using sigma point- and extended Kalman filters. The methods' accuracy and complexity are tested in different operating conditions and evaluated against an algorithm estimating each cell individually.

The result shows that the optimal algorithm is equally as accurate with an execution time one thousand times faster in comparison to the algorithm estimating each cell individually. Additionally, the analysis has shown that the extended Kalman filter is less computationally demanding than the sigma point Kalman filter, with similar performance. The algorithm has a high dependency on the capacity and thus a joint SOC and capacity estimation was implemented. The estimation was simulated without disturbances and showed to be a promising method for future development. The findings in this thesis suggest how computational complexity can be reduced without the cost of losing a significant amount of accuracy.

Welcome!

Soleil, Stefan and Torsten