Abstract
Integrated sensor systems, which are produced in high volume for safety-critical applications such as automotive, require careful design and optimization strategies. To increase their reliability, such systems are often used in redundant configurations. However, this is in many cases not sufficient: requirements of high production yield, reliability in operation, low probabilities for non-detected system faults, in combination with fast development speed and low production costs require more detailed and careful design approaches. We consequently suggest statistical design, estimation and optimization approaches for efficient product definition and design. This methodology is summarized in a general way for redundant sensor systems. In a first step, the individual sensing channel performance is optimized statistically. In a second step, the dependability figures are optimized dependent on the redundant sensor output function and its diagnostic mechanism parameters based on statistical considerations of faults. The suggested methodology is shown exemplary for a redundant integrated linear Hall magnetic field sensor system for safety-critical automotive applications.
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