The accuracy of a low-cost inertial navigation system is highly dependent on the overall accuracy provided by the respective sensors and the quality of the mathematical modeling of the error sources. Sensor fusion allows to alleviate and bound the occurring errors, resulting in increased precision of the navigation solution. This paper investigates the standard integration techniques of aiding sources in an inertial navigation system for vehicular applications illustrated by the example of Pedelecs. For the realization of this application, a loosely-coupled integration scheme using an error-state Kalman \,ter in a closed-loop fashion is employed. As the tuning of the \,ter requires a delicate adjustment of the respective covariance matrices, a time domain technique was assessed to analyze and quantify the error sources in the reported measurements by the respective sensors. Evaluation is based on real data obtained from two \feld tests using the developed GPS-aided inertial navigation system.