Frontloading and automating controller calibration and virtual verification

The recent advancement of ADAS/AD technology is placing new challenges to developing robust software calibrations. As the lines of software code continue to increase exponentially, companies are being challenged with the ability to tune the software and are even more to pursue this with the multitude of environmental scenarios that could potentially affect the performance of the control software.

Managing conflicting calibration requirements and attributes through physical validation and testing is no longer sustainable. Frontloading and automating controller calibration and virtual verification is a cost and time-efficient approach to reduce on-road testing and calibration.

Accelerate controller calibration by applying system simulation

Model-based development, including virtual verification, is a critical success factor in reducing on-road testing and calibration.

Watch the webinar and learn how to:

• Use system simulation for MiL, SiL, HiL, ViL, and controls validation
• Understand the requirement differences between controller calibration and verification models
• Address differences between virtual calibration and calibration challenges
• Frontload controller calibration at different stages of the development process
• Deploy optimization tools to find the optimal calibration parameter

Reduce vehicle testing by 40 percent by pre-defining major controller calibration values

Hyundai Motor Company and Simcenter engineers researched the possibility of saving development time and cost by implementing a more automated performance optimization process using state-of-the-art simulation capabilities. Together, they executed a project where they virtually tested, validated, and calibrated an HEV main controller using a real-time, closed-loop, model-based system simulation.

Using hardware-in-the-loop (HiL) test platforms, Hyundai was able to accurately capture fuel economy and drivability simultaneously. This approach allows for quick evaluation when designing hybrid control unit algorithms and defining calibration values to achieve a better starting point for physical prototyping.

Read the case study.