Automation of Energy Management Analysis in Automotive Engineering with Python - Pestana, Larissa; Costa, Thais Cohen; Carvalho, Rayan (Anais do Congresso Latino-Americano de Software Livre e Tecnologias Abertas (Latinoware); 2024: Anais do XXI Congresso Latino-Americano de Software Livre e Tecnologias AbertasDO - 10.5753/latinoware.2024.245339, 2024)
This paper presents the development and implementation of an automated application for the analysis of Energy Management tests in the automotive industry, using Python as the primary tool. The application automates the processing of data acquired from various test types, including Coast Down, Parasitic Losses, Full Load, Acceleration Metrics, and Fuel Consumption. By transforming data into dataframes and utilizing Python functions, the application achieves a significant reduction in the time required for data analysis, surpassing traditional methods reliant on Excel spreadsheets. The automation improves efficiency and enhances the precision of engineering calculations, making the process more dynamic and less prone to human errors. The results demonstrate a reduction of over 70% in data analysis time, with the potential for further improvements as all engineering calculations are fully transitioned to Python. This approach offers a competitive advantage for automotive companies, optimizing their processes and accelerating product development.