AVL Route Studio

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Route Studio is a software solution designed to move test activities from real-world environments to virtual ones, reducing costs and saving development time. However, the lack of modern vehicle models in Route Studio (RS) was limiting its use and the integration of new features, especially for future technologies like range estimation algorithms for battery electric vehicles. To address this, the old RS vehicle model components were converted into Simulink models, providing a clear view of the existing architecture. Missing elements of modern vehicle architectures, such as electric motors, basic and advanced battery models, and regeneration strategies, were then added. After successfully creating a working model in Matlab/Simulink, these models were migrated back to Python for integration into the RS project. A real driving emission cycle generator, an algorithm for automatically generating random and compliant cycles, was refactored, enhanced, and integrated into the Python library of the RS project. Design principles and solid patterns were applied to create well-structured code. This approach was also used for the model factory algorithm, which identifies 3RC battery equivalent model parameters. An automated HIL project creation module was developed using the API provided by dSpace for ConfigurationDesk and ControlDesk software. Within the project scope, HIL project files were created automatically using inputs defined by customers. The process can create project folders, import required files like CAN files and simulation model files, connect models and IO components including CAN signals, define real-time requirements such as sampling periods and core assignment for each thread, build the project, and deploy it to a control desk project template to run the headless control desk project. Advanced vehicle system models were successfully introduced to the project, significantly enhancing its capabilities. Using Matlab/Simulink provided a structured approach that facilitated understanding of the Python code and interconnected system architectures. Challenges arose during integration, but the gradual transitions between Python and Simulink helped resolve these issues. Analyzing the system in Simulink also addressed persistent legacy problems, such as correcting erroneous brake force calculations. The integration of advanced vehicle components, the automated HIL project creation module, and enhancements to the real driving emission cycle generator and model factory algorithm collectively improved the RS project's accuracy and functionality. This comprehensive effort underscores the importance of a structured, interdisciplinary approach in engineering, paving the way for future innovations in vehicle system modeling and control algorithm development.