Automotive component suppliers and original equipment manufacturers (OEMs) face the challenge of individualizing each car, considering factors such as its usage, design, driving conditions, and the environment it operates in. To ensure optimal performance, it’s crucial to understand and manage each vehicle and its unique conditions.
Ekkono Solutions AB, a Swedish software firm, specializes in edge machine learning, allowing machine learning to operate directly on physical products in real-world settings. The company’s technology is utilized by leading clients across various sectors, such as industrial equipment, automotive, and energy, to accelerate the creation and implementation of personalized and automated condition-based maintenance and performance enhancement solutions for their products. Established in 2016, Ekkono’s product is the culmination of more than seven years of research conducted at the University of Borås.
Infineon Technologies AG stands as a prominent force in the global semiconductor industry, particularly excelling in power systems and IoT. The company plays a pivotal role in advancing decarbonization and digitalization through its extensive array of products and solutions. With a workforce of approximately 58,600 individuals worldwide, Infineon boasts a remarkable revenue of roughly €16.3 billion in the 2023 fiscal year, concluding on 30 September. It is publicly traded on the Frankfurt Stock Exchange under the ticker symbol IFX, as well as on the OTCQX International market in the USA under the ticker symbol IFNNY.
Infineon Technologies AG (FSE: IFX / OTCQX: IFNNY) offers the AURIX™ microcontroller (MCU) family, providing advanced real-time computing hardware for embedded AI in safety-critical automotive applications. Ekkono Solutions, an ecosystem partner of Infineon, now provides a user-friendly software development kit (SDK) for creating AI algorithms for embedded systems based on AURIX TC3x and TC4x. Rikard König, CTO and co-founder at Ekkono, stated, “We’ve been an Infineon ecosystem partner since 2019. Now we have a mature solution together that meets the needs and requirements of the automotive industry. We take great pride in going to market with Infineon, who is one of the leaders in high-performance MCUs in this space.”
Thomas Boehm, Senior Vice President Microcontroller at Infineon, highlighted, “Artificial intelligence is on the rise, and there is no question that this technology will also play a crucial role in tomorrow’s transportation solutions. The latest Infineon AURIX microcontrollers provide versatile AI capabilities for customer projects. We are excited to work with Ekkono to further simplify the development of AI-based automotive applications. We believe that these applications will not only serve convenience purposes but will also improve road safety and security.”
Ekkono Solutions AB specializes in individual incremental learning at the edge, a process that occurs when a vehicle is started up and during operation. This innovative approach allows for the creation of virtual sensors that can either enhance or replace physical sensors in various automotive systems, including climate control, battery management, and emissions control. Additionally, Ekkono’s technology enables the detection of deviations in transmission, gearboxes, and braking systems, which facilitates condition-based maintenance.
Furthermore, Ekkono’s solutions include simulations that determine the optimal driveline settings for each individual vehicle, resulting in improved performance, reliability, and energy efficiency. Ekkono has specifically tailored its Software Development Kit (SDK) to be compatible with Infineon’s AURIX core and accelerators, making it ideal for the automotive market. This adaptation allows developers to train and deploy AI algorithms on AURIX TC3x and TC4x platforms without needing to make additional hardware adjustments. The integration of embedded artificial intelligence into vehicles enhances their ability to understand their environment and the driver’s needs, which is essential for future applications such as autonomous driving.