Accommodating the needs of ISO26262 in MEMS Gyro based automotive applications

March 19, 2015 // By Jan Pekkola, Murata Europe
MEMS gyros and accelerometers are finding their way into many consumer and industrial applications today. From smartphones to domestic appliances “white goods” more and more designs are using these miniature devices. Automobiles are a good example of where you will find an increasing number of these sensors being utilized.

Not so many years ago these were limited to the high-end vehicle models but today, driven mainly by the reducing cost of such sensors, they are finding their way into most models. Although for some applications there has been a viewpoint that MEMS gyros and accelerators have not been well balanced in terms of costs and performance. For example, active suspension applications require four extremely accurate and stable sensors mounted on the wheels in order to meet the necessary input signals to achieve a smooth reliable chassis dynamics. The cost of such highly stable and accurate sensors has traditionally been high.

Another application that is now mandatory in the US is preventing front passengers being ejected from the vehicle during an accident. This is particularly the case for vehicles with a high centre of gravity such as SUVs and pick-up trucks where cases of passengers being flung from the vehicle in a roll-over situation is very high. In most automotive applications using a MEMS gyro it is only the yaw rate that is detected. However for roll-over detection you also need to measure the roll rate. This requires another gyro be employed to detect the X-axis of the vehicle. Similar movement detection is also used for adjusting the high light angle when a vehicle is heavily loaded and is mandatory for Xenon headlights. MEMS-based sensors are already part of our everyday life, but compared to those commonly found in popular applications, such as smartphones, but the sensors used in such applications are nowhere near as stable and accurate as those used for automotive applications and their characteristics vary widely due to temperature, vibration and other environmental factors.

The MEMS device is also just the core component of a system that in most cases requires software filtering of noise, adaptive learning algorithms and being able to zero any offset of effects of changing temperature and vibration, not to mention changes that

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