Measurement uncertainties of a CMOS-based piezoresistive stress sensor are studied for low cycle thermal loading applications. After the fundamentals of the sensor are reviewed briefly, the random uncertainties associated with the data acquisition unit are evaluated first using raw current signals obtained from uniquely fabricated free-standing stress sensor chips. The free-standing sensor chips are tested further for systematic uncertainties associated with the manufacturing-induced residual stresses by subjecting them to a thermal cycle. Finally, the stress measurement accuracy of the sensor chip under an in-situ thermal loading is quantified by a numerical model verified by a sub-micron sensitivity optical technique while incorporating the quantified uncertainties.

Recent advancements in automotive technologies, most notably autonomous driving, demand electronic systems much more complex than those realized in the past. The automotive industry has been forced to adopt advanced consumer electronics to satisfy the demand, and thus it becomes more challenging to assess system reliability while adopting the new technologies. The system-level reliability can be enforced by implementing a process called condition monitoring. In this paper, a piezoresistive silicon-based stress sensor is implemented to recognize in situ failure in outer molded electronic control units subjected to reliability testing conditions. The test vehicle consists of six double decawatt package power packages and three stress sensors mounted on a printed circuit board. A unique algorithm is proposed and implemented to handle the data obtained from the piezoresistive stress-sensing cells. The accuracy of measured data is examined by finite-element method, and the physical changes are validated with scanning acoustic microscope. One-class support vector machines are used to autonomously classify data based on a training set of measurements from healthy state, and the reported results confirm that robust classification is possible based on data from the silicon stress sensor.

Recent advancements in automotive technologies, most notably autonomous driving, demand electronic systemsmuch more complex than realized in the past. The automotiveindustry has been forced to adopt advanced consumerelectronics to satisfy the demand, and thus it becomes morechallenging to assess system reliability while adopting the newtechnologies. The system level reliability can be enforced byimplementing a process called condition monitoring. In thispaper, a piezoresistive silicon based stress sensor isimplemented to detect physical damages in outer moldedelectronic control units (ECU) subjected to reliability testingconditions. The test vehicle consists of six DPAK powerpackages and three stress sensors mounted on a PrintedCircuit Board (PCB). A unique algorithm is proposed andimplemented to handle the data obtained from thepiezoresistive stress sensing cells. The accuracy of measureddata is examined by Finite Element method (FEM), and thephysical changes are validated with Scanning AcousticMicroscope (SAM).