Automated driving: ZF and Infineon use AI algorithms to optimize software and control units for driving dynamics

Sep 12, 2024 | Business & Financial Press

  • AI algorithms from ZF accelerate development and bring AI into ZF products
  • AURIX™ TC4x microcontroller from Infineon enables AI algorithms thanks to Parallel Processing Unit (PPU)
  • EEmotion: Project co-funded by the German Federal Ministry for Economic Affairs and Climate Action

Friedrichshafen and Munich, Germany – 12 September 2024 – Trucks automatically driving behind one another on the highway, 'platooning', or cars automatically changing lanes: Here vehicle movements have to be calculated and executed precisely and quickly without a human driver. Software and AI algorithms safely control the drive, brakes, front and rear wheel steering and damping systems. The more efficient the AI algorithms are, the better the available computing power can be used. 

The ZF Group and Infineon Technologies AG (FSE: IFX / OTCQX: IFNNY) have jointly developed and implemented AI algorithms for the development and control of vehicle software as part of the EEmotion project. The project was co-funded by the German Federal Ministry for Economic Affairs and Climate Action. The AI algorithms developed in the project, proven in a test vehicle, control and optimize all actuators during automated driving according to the specified driving trajectory.

ZF has added AI algorithms to its two existing software solutions cubiX and Eco Control 4 ACC, which have been implemented on Infineon’s AURIX™ TC4x microcontroller (MCU) with integrated Parallel Processing Unit (PPU). The result: More efficient artificial intelligence algorithms and better utilization of computing power. This in turn leads to better driving performance and increased driving safety. Compared to conventional approaches without AI, the two companies have now proven that their solution can for example carry out automated lane changes much more accurately. The energy efficiency of driver assistance systems such as Adaptive Cruise Control has also been increased. The improved driving performance combined with lower computing power demands paves the way for cost-efficient Level 2+ assistance systems. 

"The EEmotion funding project shows that our artificial intelligence-based algorithms provide our customers with new advantages: AI makes it possible for products to be equipped with new functions and to be developed faster and more efficiently," said Torsten Gollewski, Head of Research and Development at ZF. 

“With our world-leading semiconductor products, software and services, Infineon enables customers to develop their own AI applications,” said Peter Schiefer, President of Infineon’s Automotive Division. “Our AURIX TC4x is ideally suited for in-car AI applications because its Parallel Processing Unit enables the fast and parallel processing of data that is essential for artificial intelligence, heralding the next stages of automated and ultimately autonomous driving."

"The EEmotion project successfully integrated artificial intelligence into the safety-critical functions of the vehicle control system; this was validated on the software side, making further progress towards highly automated driving possible," said Ernst Stoeckl-Pukall, Head of the Digitization and Industry 4.0 department at the Federal Ministry for Economic Affairs and Climate Action. "The project has thus provided important impetus that has strengthened the innovative power and competitiveness of the German automotive industry."

Software-based chassis control optimized with AI

ZF's cubiX software makes it possible to control all chassis components in passenger cars and commercial vehicles. This includes longitudinal and lateral dynamics as well as the vehicle's vertical dynamics. In addition, the Eco Control 4 ACC predictive cruise control system is being further developed using a computationally intensive optimization algorithm and model-predictive control to achieve as much as 8 percent more range under real driving conditions. The EEmotion project has also developed AI algorithms which are applied as early as during the development phase. This allows more efficient design of vehicle software which can then be made available to customers more quickly. The accelerated and AI-supported application of vehicle software offers vehicle manufacturers clear advantages when adapting to different vehicle models.

Microcontroller from Infineon enables use of AI algorithms

Lean, AI-based algorithms require a lot of computing power, which makes it advisable to integrate them into high-performance microcontrollers such as the AURIX TC4x. Infineon's AURIX TC4x microcontrollers offer high real-time performance and implement the latest trends in AI modelling, virtualization, functional safety, cybersecurity and networking functions. They pave the way for new E/E architectures and the next generation of Software-Defined Vehicles (SDV). An important part of the AURIX TC4x is the Parallel Processing Unit, which supports powerful AI applications thanks to fast and parallel data processing.

About the EEmotion project

The EEmotion project's objective was to develop an AI algorithm-based control system for automated driving that ensures more precise trajectory control in various driving situations. The implementation of the project included the definition of the requirements for the AI-based functions, the development of an overall concept and corresponding hardware as well as developing the integration of AI in control architectures for safety-critical applications. It also took aspects such as the development of secure AI-monitored communication and the investigation of the simulative development and validation of vehicle dynamics systems into account. Infineon Technologies AG acted as the consortium coordinator for the project, with a total volume of 10.4 million euros, 59 percent of which was funded by the German Federal Ministry for Economic Affairs and Climate Action. The project ran from September 2021 to August 2024 and included partnerships with ZF Friedrichshafen AG, b-plus technologies GmbH, samoconsult GmbH, RWTH Aachen University and the Universität zu Lübeck.

Press contacts

Mirko Gutemann , Technology Communications, ZF Group,
Phone: +49 7541 77-960136, e-mail: mirko.gutemann@zf.com 

Reinhard von Faltin , Media Relations, Infineon Technologies AG
Phone: +49 89 234 39694, e-mail: Reinhard.VonFaltin@infineon.com

About ZF

ZF is a global technology company supplying advanced mobility products and systems for passenger cars, commercial vehicles and industrial technology. Its comprehensive product range is primarily aimed at vehicle manufacturers, mobility providers and start-up companies in the fields of transportation and mobility. ZF electrifies a wide range of vehicle types. With its products, the company contributes to reducing emissions, protecting the climate as well as enhancing safe mobility. Alongside the automotive sector – passenger cars and commercial vehicles – ZF also serves market segments such as construction and agricultural machinery, wind power, marine propulsion, rail drives and test systems.

With some 168,700 employees worldwide, ZF reported sales of €46.6 billion in fiscal 2023. The company operates 162 production locations in 31 countries.

For further press information and photos, please visit www.zf.com

About Infineon

Infineon Technologies AG is a global semiconductor leader in power systems and IoT. Infineon drives decarbonization and digitalization with its products and solutions. The company has around 58,600 employees worldwide and generated revenue of about €16.3 billion in the 2023 fiscal year (ending 30 September). Infineon is listed on the Frankfurt Stock Exchange (ticker symbol: IFX) and in the USA on the OTCQX International over-the-counter market (ticker symbol: IFNNY).

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Information Number

INFATV202409-139

Press Photos

  • ZF and Infineon have jointly developed and implemented AI algorithms for the development and control of vehicle software as part of the publicly funded EEmotion project.
    ZF and Infineon have jointly developed and implemented AI algorithms for the development and control of vehicle software as part of the publicly funded EEmotion project.
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