Simulating a system that changes over time is crucial to tuning the performance, checking the system constraints, and assessing it at the prototype stage. Software in the Loop (SiL) simulation is a test setup where the software is running in a virtual environment rather than on the real target hardware. In this case, the system under test is the software, and the virtual environment could be a host computer, a virtual computer, a server, or the cloud. Generally, in the automotive industry, testing the software on real hardware (an electrified bike (eBike) in our case) is time- and cost-intensive. By using SiL, one can already test the software even before the complete hardware is available. This helps reduce overall software development costs and time. Next to that, it helps to improve the algorithm, and the simulation results can be used as a benchmark to further compare the actual vehicle behavior. One more important aspect to consider here is the overall safety of the software or system. SiL will help verify the safety of the software by simulating scenarios that could potentially be dangerous in vehicle testing. SiL also enables rapid prototyping of the control logic and provides a platform for early validation of the logic in the development lifecycle. The primary goal of this thesis is to develop a SiL simulation environment for eBike Anti-lock Braking System (ABS) functionality so that it can be used in the development and release phases of the software development lifecycle. To determine the necessary simulation maneuvers for the SiL model, we considered the actual Vehicle Test Catalogues (VTCs) defined for eBike ABS. The work includes modifying the available SiL model to function in a variety of riding situations, such as on surfaces with high friction, low friction, and mue-jump scenarios. Additionally, we derive the Key Performance Indicators (KPIs) and perform a sensitivity analysis by varying certain bike and environment parameters and observing the impact on the derived KPIs. Finally, measurements derived from actual bike testing are used to confirm the effectiveness of the SiL model. Furthermore, the SiL model should include an Inertial Measurement Unit (IMU) sensor model to evaluate ABS performance during IMU sensor errors. By doing so, it is possible to identify the IMU errors that have the greatest impact on performance and the values for every error that are optimal for ABS operation. This enables us to characterize the errors and error values that affect the ABS functionality. The results demonstrate that the developed SiL model can be used during the development phase for rapid prototyping and provides an option for parameter application of the control software. Additionally, automated execution of maneuvers is developed, through which multiple maneuvers can be executed together, reducing the overall execution time. Furthermore, the IMU errors were identified, and the impact on the ABS function was assessed for a few of the errors related to the accelerometer and gyroscope. We focused on the IMU errors resulting in the incorrect estimation of the pitch angle, which could potentially lead to incorrect ABS activation and compromise vehicle safety.