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2017
Conference Paper
Title
Application driven reliability research of next generation for automotive electronics: Challenges and approaches
Abstract
The revolutionary changes in automotive industry towards fully connected automated electrical vehicles necessitates developments in automotive electronics at unprecedented speed. Signal, control, and power electronics will heterogeneously be integrated at minimum space with sensors and actuators to form highly compact and ultra-smart systems for functions like traction, lighting, energy management, computation, and communication. Most of these systems will be highly safety relevant with the requirements in system availability exceeding today's already high automotive standards. Other than the human drivers of today, passengers in the automated car do not pay constant attention to the driving actions of the vehicle. Hence, reliability research is massively challenged by the new automotive applications. Guaranteeing the specified lifetime at statistical average is no longer sufficient. Assuring that no failure of an individual safety relevant part occurs unexpectedly, becomes most important. The paper surveys the priority actions underway to cope with the tremendous challenges. It highlights practical examples in all three directions of reliability research. i) Experimental reliability tests and physical analyses: New and highly efficient accelerated stress tests are able to cover the complex and multi-fold loading situation in the field. New analytics techniques can identify the typical failure modes and their physical root causes. ii) Virtual techniques: Schemes of validated simulations allow capturing the physics of failure proactively in the design for reliability process. iii) Prognostics health management (PHM): A new concept is introduced for adding a minimum of PHM features at the various levels of automotive electronics to provide functional safety as required for autonomous vehicles. This way, the new generation of reliability methods will continuously provide estimates of the remaining useful life (RUL) for each relevant part under the actual use conditions to allow triggering maintenance in time.