Abstract
While new generative methods (e.g., ChatGPT) of artificial intelligence (AI) have been accessible and well-known to the general public since the beginning of 2023, data-based or data-centric engineering is still largely in its infancy. This overview article sheds light on several AI approaches for application during the development and operation of (automotive) friction brakes. The increasing regulatory requirements on particulate emissions, ongoing electrification, and fundamentally new vehicle and operational concepts pose new challenges to the development of friction brakes. At this juncture, data-based methods, novel decision-making processes, and the overall utilization of Artificial Intelligence hold significant potential for the future. This contribution focuses on some promising applications of AI methods in the context of brake development, discusses data management requirements, and provides an outlook on the importance of AI methods in the context of trends in the automotive industry. Since successful (and especially publicly accessible) use scenarios are rare, this overview article does not claim to be exhaustive regarding the current use of AI methods in the development of braking systems.
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© 2023 Der/die Autor(en), exklusiv lizenziert an Springer-Verlag GmbH, DE, ein Teil von Springer Nature
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Stender, M. (2023). Artificial Intelligence for Friction Brakes: Applications and Potentials. In: Mayer, R. (eds) XL. Internationales μ-Symposium 2023 Bremsen-Fachtagung. IµSBC 2023. Proceedings. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-68167-1_12
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DOI: https://doi.org/10.1007/978-3-662-68167-1_12
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