Journal Articles - SAE Mobilus
SAE journals provide rigorously peer-reviewed, archival research by subject matter experts--basic and applied research that is valuable to both academia and industry.
This article provides a comprehensive review of existing literature on AI-based functions and verification methods within vehicular systems. Initially, the introduction of these AI-based functions in these systems is outlined. Subsequently, the focus shifts to synthetic environments and their pivotal role in the verification process of AI-based vehicle functions. The algorithms used within the AI-based functions focus primarily on the paradigm of deep learning. We investigate the constituent components of these synthetic environments and the intricate relationships with vehicle systems in the verification and validation domain of the system. In the following, alternative approaches are discussed, serving as complementary methods for verification without direct involvement in synthetic environment development. These approaches include data-oriented methodologies employing statistical techniques and AI-centric strategies focusing solely on the core deep learning algorithm.
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Letter from the Guest Editors
Letter from the Focus Issue Editors
The flow structure and unsteadiness of shock wave–boundary layer interaction (SWBLI) has been studied using rainbow schlieren deflectometry (RSD), ensemble averaging, fast Fourier transform (FFT), and snapshot proper orthogonal decomposition (POD) techniques. Shockwaves were generated in a test section by subjecting a Mach = 3.1 free-stream flow to a 12° isosceles triangular prism. The RSD pictures captured with a high-speed camera at 5000 frames/s rate were used to determine the transverse ray deflections at each pixel of the pictures. The interaction region structure is described statistically with the ensemble average and root mean square deflections. The FFT technique was used to determine the frequency content of the flow field. Results indicate that dominant frequencies were in the range of 400 Hz–900 Hz. The Strouhal numbers calculated using the RSD data were in the range of 0.025–0.07. The snapshot POD technique was employed to analyze flow structures and their associated
Design validation plays a crucial role in the overall cost and time allocation for product development. This is especially evident in high-value manufacturing sectors like commercial vehicle electric drive systems or e-axles, where the expenses related to sample procurement, testing complexity, and diverse requirements are significant. Validation methodologies are continuously evolving to encompass new technologies, yet they must be rigorously evaluated to identify potential efficiencies and enhance the overall value of validation tests. Simulation tools have made substantial advancements and are now widely utilized in the development phase. The integration of simulation-based or simulation-supported validation processes can streamline testing timelines and sample quantities, all the while upholding quality standards and minimizing risks when compared to traditional methods. This study examines various scenarios where the implementation of advanced techniques has led to a reduction in
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