On-board impedance diagnostics method of Li-ion traction batteries using pseudo-random binary sequences. Method evaluation and feasibility study of concept.
This thesis deals with the on-board impedance measurements of Li-ion batteries on hybrid electric
vehicles/electric vehicles by using pseudo-random binary sequences (PRBSs). The impedance of the battery
can be related to its state of charge but the accurate impedance measurements are difficult to perform in the
vehicles. By using an excitation signal like PRBS, it is possible to extract the impedance information of the
battery packs.
Both experiments and simulations are performed with different set-ups to verify the PRBS method. A
non-parametric method is used to process the data and extract the impedance measurement. Experiments
in the laboratory at different SOC levels and temperatures are made to validate the PRBS method. In the
simulations, the noise sensitivity is analyzed.
It is shown that the PRBS method can produce a valid electrochemical impedance spectrum in a limited
frequency range, similar to the result from a high accuracy laboratory impedance analyzer. The method
is stable at different SOC levels and temperatures. However, the battery impedance at high frequency is
difficult to obtain with the PRBS method in the experiments.
A simulation of the excitation signal in the vehicle is performed where the electric motor is used as
the load. It shows that it is possible to some extent to use the drive line in a hybrid electric vehicle/electric
vehicle to perform an on-board battery impedance measurement