CAN-Based Aging Monitoring Technique for Automotive ASICs With Efficient Soft Error Resilience

Abstract

The modern automobile industry is rapidly shifting toward the era of self-driving cars. Due to rapid technological development, many mechanical parts in automobiles have been switched to electronic devices. Therefore, the proportion of electronic devices in modern cars is increasing. Even though many parts have been replaced by electronic devices, vehicles still require the periodic maintenance not only for mechanical parts, but also for automotive electronics. To guarantee the high reliability of automotive Application-Specific Integrated Circuits (ASICs), automotive chips are tested during manufacturing for functional and structural defects. Moreover, automobile chips are also tested using several in-field diagnostic techniques (e.g., online Built-In Self-Test (BIST), Software-Based Self-Test (SBST)) while the chips are operating. By using these in-field diagnostic techniques, functional and structural defects in automotive ASICs, which occur in the early-life cycle and normal operation, can be detected. However, automotive semiconductor devices still require testing for aging-induced defects and soft errors to prevent critical functional failures. Moreover, aging-induced defects are hard to detect with conventional in-field diagnostic techniques which is based on BIST techniques. Thus, this work presents a secure Controller Area Network (CAN) -based Test Access Mechanism (TAM) for aging defect diagnosis with efficient soft-error resilient scan cell design for automotive ASICs. The proposed TAM incurs area overhead of 6% to 9% depending upon the selection of mode identification. Further, the proposed Aging monitoring and Soft Error Resilience Flip Flop (ARFF) incurs 22% less area and power as compared to separate implementation of the Built-In Soft Error Resilience (BISER) and the Early Capture Flip Flop (ECFF).