E2Packman

Within the E2PACKMAN project, Saykal will lead the adaptation and integration of advanced GaN packaging into HV-LV DC/DC converters, which are essential in vehicle electrification. The improved packaging will enable higher efficiency, smaller footprint, and reduced thermal load, aligning with the automotive industry's stringent reliability and size constraints.

Responsible for the adaptation and integration of GaN-packaged components to enable high-efficiency, compact, and thermally optimized converter systems. Designs and prototypes GaN-based On-Board Chargers (OBC) and Traction Inverter systems tailored for electric vehicle applications. Performs reliability testing under real-world automotive conditions, including thermal cycling, aging, and electrical measurements. Provides performance feedback on semiconductor components developed by project partners to support iterative improvement. Collaborates with BigTRI to implement AI-driven reliability and quality testing infrastructures.Ensures alignment with automotive industry standards regarding system durability, thermal management, and space constraints.

By integrating the newly developed packaging solutions into real-world converter applications, Saykal will contribute to achieving key project KPIs: higher efficiency and system miniaturization.

As an end user of failed semiconductor technologies in power and sensing, Saykal will be involved in the testing and maintenance of new semiconductors produced with laboratory-developed assembly and packaging technology. Development and prototyping of GaN-based On-Board Charger and Traction Inverter systems for EVs, enhancing power conversion efficiency and thermal performance.

Ownership of a use case focusing on the integration of low-power GaN-packaged components for HV-LV DC/DC converters. Execution of in-line and end-of-line tests, including thermal cycling, aging, and electrical validation, contributing to real-world system robustness. Providing performance feedback on semiconductor components and supporting AI-based reliability infrastructure in collaboration with BigTRI.