Powertrain Development with Artificial Intelligence (eBook)

History, Work Processes, Concepts, Methods and Application Examples

Aras Mirfendreski (Autor)

eBook Download: PDF

2022
XIII, 164 Seiten
Springer Berlin Heidelberg (Verlag)
978-3-662-63863-7 (ISBN)

Infos

The variety of future powertrain concepts has drastically increased the development cost for automotive manufactures. Profitable investment requires a significantly leaner and efficient powertrain development process. Traditional methods of test and model based development need to be assisted by big data and data analytics. For this purpose, a valuable tool is available at the right time - artificial intelligence (AI). But what does AI really mean in a narrower sense? What concepts lie behind it? And how are the methods and algorithms transferable to powertrain applications? For the first time, this book aims to bridge the gap between automotive engineering and computer science, by illuminating the complexity of current AI concepts and demystifying it for powertrain applications. By elaborating on work processes, it shows how AI could be implemented and how completely novel methods can help us reshape the future of mobility.

Dr. Aras Mirfendreski has developed into an engine-expert throughout the German and international scientific landscape (studied at RWTH Aachen University, doctorate at Audi AG). Through his experience as a powertrain developer at Stuttgart FKFS for various OEMs as well as his activities as a senior program manager at Toyota, his developments always thrive on the transfer of state-of-the-art methods into corporate structures. Today, he serves as Vice President Engine R&D at Aquarius Engines and is also an AI expert, keynote speaker and consultant on artificial intelligence topics.

Produkt-Details

• Erscheint lt. Verlag: 4.4.2022
• Zusatzinfo: XIII, 164 p. 155 illus., 124 illus. in color.
• Sprache: englisch
• Original-Titel: Künstliche Intelligenz für die Entwicklung von Antrieben
• Themenwelt: Technik ► Maschinenbau
• Schlagworte: Artificial Intelligence • Automotive • Big Data • Development • machine learning • Neural networks • Powertrain • Reinforcement Learning • Simulation • supervised learning • Unsuperised Learning
• ISBN-10: 3-662-63863-0 / 3662638630
• ISBN-13: 978-3-662-63863-7 / 9783662638637