Fatigue Evaluation of Electric Powertrain from ADT Using Python GUI

In the automotive industry, the reliability and durability of electric powertrains (ePT) are paramount to ensuring optimal performance, structural integrity, customer satisfaction, and reduced warranty costs. It is crucial to verify that the structural components of the ePT can endure the demands of daily use without failure to maintain vehicle reliability, performance, and safety. However, traditional testing methods and Design Verification Plans (DVPs) often face challenges such as being time-intensive, costly, and resource-demanding. Moreover, these methods may not fully account for the variability of real-world operating conditions. Accelerated testing provides a solution to these limitations by simulating long-term usage within a condensed timeframe. This approach facilitates the early identification of potential failure points and delivers comprehensive data on powertrain behaviour under extreme conditions. By integrating Road Load Data Acquisition (RLDA) with fatigue analysis, designers can improve the accuracy of predictions regarding warranty life and fatigue failure, enabling a deeper understanding of structural durability and operational reliability. As a result, this process not only expedites the development cycle but also minimizes costs while ensuring the production of robust and reliable electric powertrains. The scope of this study encompasses the significance of Accelerated Durability Testing (ADT), RLDA signal processing, rainflow counting, ePT simulation under various loading conditions, and post-processing using a Python-based graphical user interface (GUI). Additionally, real-world life prediction derived from ADT is explored. These methodologies enable precise fatigue analysis and visualization, supporting better design optimization and material selection. The findings of this study aim to mitigate premature failures arising from real-world usage patterns, empowering designers to create cost-effective, lightweight, and durable products. Ultimately, this ensures the delivery of robust and reliable electric powertrains to end-users.