Design and Validation of a Full Vehicle Model for a Formula SAE Race Car

The goal of this master's thesis is to develop a comprehensive simulation tool for a Formula Student vehicle, aimed at both modeling and validation, with the purpose of enhancing overall performance and accurately estimating powertrain behavior, cooling efficiency, and energy management. Thus, a secondary objective of the thesis is to create a modular simulation framework capable of linking all key subsystems, enabling cross-validation within a single platform. The final outcome includes lap-time estimation as well as electrical and thermal performance accurate simulation. To facilitate this multi-domain integration, the vehicle model is developed using Simscape, a relatively recent MATLAB & Simulink library that allows coupling of mechanical, electrical, and thermal components. This environment provides the flexibility required to connect and test all relevant subsystems maintaining a coherent workflow. Furthermore, it allows for a wide range of simulations, from open-loop to closed-loop configurations, with the capability to include or exclude individual subsystems as needed, enabling the investigation of causal relationships behind various phenomena. The process begins with the fundamentals of tire modeling and vehicle dynamics, which are the first to be validated in order to ensure a solid foundation. Once the virtual vehicle demonstrates sufficient correlation with real-world behavior, the focus shifts to the other subsystems. The thesis then explores electric powertrain modeling, including basic electrical machine principles, thermal generation, and heat exchange. Particular attention is given to electrical and thermal management systems, which are carefully modeled and validated. Special focus is placed on the powertrain subsystem, representing the first iteration of a simulation architecture with significant potential for future development and refinement. Finally, performance evaluation and subsystem validation are conducted through dedicated MATLAB scripts, which compare simulation outputs with real-world data from track testing and race events. The results are critically assessed to highlight consistency with experimental observations and to identify any discrepancies. In an endurance scenario, the simulation demonstrates an energy consumption error of approximately 5%, and a deviation in motor temperature prediction of less than 10% compared to actual measurements. These results enable the development of lap-time strategies based on accurate energy usage and thermal behavior.