Automated Hardware-in-the-Loop Testing Using a Cloud-Based Architecture
2021-01-0133
04/06/2021
- Features
- Event
- Content
- The software gradually takes over more and more tasks of the driver and paves the way to autonomous driving. Software development and software verification is therefore crucial for manufacturer's success. Standards such as ISO 26262 highly recommend requirements-based verification. Agile development uses continuous integration testing based on test automation and evaluation. All this pushed the creation of a model-based software verification environment that provides test generation and test automatization for all kinds of signal-based tests along the V-model. This paper presents a novel core component of this environment, which is as far as to the extent possible a standard-compliant cloud-based solution to test automation at the hardware level. Based on characteristic properties of testbenches, such as the wiring or the connected ECUs, hardware resources available at remote locations can be fully automated. Thus, costly equipment only available in a limited number can be optimally utilized for testing purposes. As the availability of testing resources is a crucial aspect in software verification, a cloud-based solution can cut down the overall amount of time required for testing considerably. In close cooperation between the Ford Motor Company and Mindmotiv, a microservice-based test execution engine with an integrated scheduler was developed and adapted to XIL compliant testbenches for HIL-based Advanced Driver Assistance System (ADAS) testing. We present the design decisions for the software verification environment, barriers not yet covered by standards, the necessary additions to realize a cloud-based test automation as well as the ensuing unique advantages of our approach.
- Pages
- 8
- Citation
- Wiechowski, N., Chevalier, A., Stefan, F., Roettger, D. et al., "Automated Hardware-in-the-Loop Testing Using a Cloud-Based Architecture," SAE Technical Paper 2021-01-0133, 2021, https://doi.org/10.4271/2021-01-0133.