ZF has launched TempAI, a production-ready, AI-based temperature administration know-how designed to enhance the efficiency and effectivity of electrical motors in electrical automobiles. Using a self-learning temperature mannequin, TempAI enhances temperature prediction accuracy by over 15 %, enabling extra exact thermal utilization of electrical motors and rising efficiency with out compromising reliability.
The TempAI platform mechanically generates physics-based fashions from intensive measurement information, changing into operational rapidly and requiring minimal computing sources. Current management items are adequate, permitting for cost-efficient implementation in sequence manufacturing. In accordance with ZF, TempAI delivers focused electrical motor management proper as much as thermal working limits, leading to as much as six % greater peak energy and measurable effectivity enhancements within the Worldwide Harmonized Mild Automobile Check Process (WLTP) cycle. Underneath dynamic driving eventualities—comparable to high-performance circuits just like the Nürburgring Nordschleife—the know-how reduces power consumption by 6 to 18 %, depending on load situations.
TempAI additionally allows ecological advantages, as its optimized thermal design can considerably cut back the reliance on heavy uncommon earth supplies. The answer additionally presents substantial time financial savings throughout growth, decreasing durations from a number of months to merely a couple of days by way of AI-driven modeling.
Throughout motor growth, AI-driven TempAI fashions successfully study and predict inner motor thermal processes which are in any other case troublesome or costly to measure straight, comparable to rotor temperatures. The know-how capitalizes on intensive dataset analyses collected throughout purposeful exams on take a look at benches and in take a look at automobiles, involving tens of millions of knowledge factors associated to variables like ambient temperatures, rotor speeds and driver habits patterns.
“This know-how allows us to additional enhance the effectivity and reliability of our drives,” mentioned Dr. Stefan Sicklinger, Head of AI, Digital Engineering, and Validation in R&D, ZF. “On the similar time, TempAI demonstrates how data-driven growth could be not solely sooner, but in addition extra sustainable and extra highly effective.”
Supply: ZF
