The energy management plays more and more important role in different applications of the automotive industry like in the start-stop or in the drive-by-wire systems. One significant part of the energy management is the estimation of the battery’s state-of-charge. The online estimation of the state variables of the battery during operation (general use, charging, or discharging) is an essential, but non-trivial task. An intelligent sensor that has been developed by Robert Bosch Ltd. measures the current, the voltage, and the temperature of the battery. These data are used to calculate some of the energy management-related conditions, such as the state of the charge of the battery.
This thesis focuses on the measurement methods, which can be used to determine the internal, Ohmic resistance of the battery. First, the electrochemical impedance spectroscopy (EIS) is presented, which is used to perform a precise impedance analysis of batteries in a laboratory environment. This method can be used as a reference measurement for the internal resistance measurement. Furthermore, the thesis deals with the recursive parameter identification method, used for measurement of the internal resistance. As the conclusion of this thesis, an observing model has been developed in MATLAB Simulink, thus the internal resistance of the battery can be measured with this model in an automobile environment.