Search Results

The powertrain module is being introduced to embedded System on Chips (SoCs) designed to increase available computational power. These high-performance SoCs have the potential to enhance the computational power along with providing on-board resources to support unexpected feature growth and on-demand customer requirements. This project will investigate the radial basis function (RBF) using the Gaussian process (GP) regression algorithm, the ETAS ASCMO tool, and the hardware accelerator Advanced Modeling Unit (AMU) being introduced by Infineon AURIX 2nd Generation. ETAS ASCMO is one of the solutions for data-driven modeling and model-based calibration. It enables users to accurately model, analyze, and optimize the behavior of complex systems with few measurements and advanced algorithms. Both steady state and transient system behaviors can be captured.

Cyber security is becoming increasingly critical in the car industry. Not only the entry points to the external world in the car need to be protected against potential attack, but also the on-board communication in the car require to be protected against attackers who may try to send unauthorized CAN messages. However, the current CAN network was not designed with security in mind. As a result, the extra measures have to be taken to address the key security properties of the secure CAN communication, including data integrity, authenticity, confidentiality and freshness. While integrity and authenticity can be achieved by using a relatively straightforward algorithms such as CMAC (Cipher-based Message Authentication Code) and Confidentiality can be handled by a symmetric encryption algorithm like AES128 (128-bit Advanced Encryption Standard), it has been recognized to be more challenging to achieve the freshness of CAN message.