ASME Santa Clara Valley Section: Qualification of Robo-Taxi: Environments and Failure Modes for Autonomous Vehicles

Description

Robo-taxi has various potential applications, including the reduction of risky driver behaviors, transportation cost reduction, and lowered carbon emission, and the enhancement of road safety, independence for seniors and people with disabilities, and human productivity. It’s full of opportunities and challenges. In this presentation, we will share our qualification methodology as well as some technical lessons. First, the use cases for robo-taxi and conventional cars are compared. Due to the differences of use cases, the existing industry standards might not be suitable for the qualification of robo-taxi. Second, the customizations of stress profiles by instrumenting vehicles with accelerometers and thermocouples, and leveraging weather station data on the basis of operational design domain are demonstrated. This kind of stress profile customization can balance the design efforts and time-to-market, and avoid under-design or over-design. Vibration stress profile, temperature cycle stress profile, temperature humidity stress profile, and UV exposure stress profile are used as case studies. Vibration test and shock test of various PCB boards are used to show the impact of stress profiles. Third, several hardware failures and issues are discussed, including air bubbles inside liquid coolant, down-selection of camera connector sealing material, the buckling of cold plates, the leakage of liquid coolant, the electrical-open failure of LEDs, fatigue cracking of a Lidar bracket, the electrical-open failure of a mechanical relay, blistering of exterior paint, corrosion on a PCB board, the electrical breakdown of a power supplier unit, and the malfunction of Radar. Different approaches are applied to understand these failures and issues, including analytical modeling, numerical regression analysis, Finite Element Analysis, FTIR, I-V curve, SEM/EDX, 3D X-ray, and 3D depth profiling. Fourth, six methods to mitigate the low sample size issue are shared, including prioritization of tests by DFMEA, sequential waterfall tests, combination of tests at different levels, combination of tests at different phases, stress-to-fail, and some statistical methods. Presented by Dr. Fen Chen, Senior Staff Reliability/Validation Engineer, GM Cruise. ASME SCVS is co-sponsoring this meeting with IEEE, including IEEE Electronic Packaging Technology (EPT)(Lead), IEEE Vehicular Technology Society (VTS)(SCV,OEB,SF) and IEEE-VTS (Chicago). We hope you can join us!