With the progressive development of autonomous vehicles, LiDAR systems have become one of the essential technologies for the automotive industries. With the commercialization of autonomous vehicles, the emphasis is shifting from performance testing to qualification and certification testing. Suppliers of LiDAR systems have to qualify their products in order to meet the exceptionally high quality and safety standards in the automotive sector.
The qualification process for LiDAR systems in the automotive industries is based on four pillars:
Pillar 1: Development and production process certification
The IATF 16949:2016 technical specification for automotive quality management is a supplement to ISO 9001:2015. It does not only align the different assessment and certification systems in the global automotive supply chain, but also incorporates risk management and safety aspects regarding new electronic and software components.
LiDAR sensors and receivers, wafer fabrication, packaging, assembly, and testing must be certified according to ISO 9001:2015 and IATF 16949:2016.
Pillar 2: Qualification testing
The Automotive Electronics Council (AEC) has established a set of standards for the failure mechanism-based stress test qualification of electronic automotive components such as packaged integrated circuits, discrete semiconductors, multi-chip modules, and passive components.
Tests are performed using limited sample quantities in several lots. Amongst others they include the simulation of extreme environmental conditions as well as extreme operating temperatures.
Semiconductor chips must be qualified in their working environments. Therefore, suppliers have to closely cooperate with manufacturers and OEMs to ensure that the product meets the requirements of the specific application.
Pillar 3: Robustness validation
Robustness validation addresses the demand of automotive manufacturers for failure levels in parts-per-million. It assesses the safety margin between the capability of a semiconductor and the cumulated stress in the respective application to determine when the component actually breaks.
Robustness validation requires the definition of a mission profile containing all the stress conditions associated with the respective application – such as strong acceleration, high temperature levels, or sunlight intensity.
Simulating extreme operating conditions and statistical models help to understand failure mechanisms and figure out the actual failure rates of LiDAR sensors in autonomous vehicles.
Pillar 4: Functional safety
Safety-related electronic automotive environments are becoming increasingly complex. In order to prevent hazards and malfunctions, all development and manufacturing phases of safety-related automotive components must be in line with the Automotive Safety Integrity Levels (ASIL) of the ISO 26262 standard.
There are several methods to improve the functional safety of components, such as redundancy and early malfunction detection.
Would you like to learn more on LiDAR qualification for automotive applications? Our white paper shows you how to use the 4 pillars to increase your success with LiDAR systems in the automotive world.