Engineers developing electrified vehicles who are trying to move validation and system integration earlier in development through simulation-driven workflows need to simulate faster, optimize increasingly complex control strategies, and estimate quantities that sensors can’t measure. Teams using traditional methods need new ways to approach these challenges to keep pace with compressed development cycles.
With production case studies from Hyundai, Cummins, Subaru, Schaeffler, Yanmar, and Mercedes-Benz, this white paper shows how you can use MATLAB®, Simulink®, and AI-based approaches to accelerate electrified vehicle development:
- Create fast, accurate surrogate models from expensive component models or measured data through reduced-order modeling and system identification
- Use virtual sensors to estimate quantities the controller needs from signals already on the vehicle bus
- Optimize control strategies and calibration with reinforcement learning and other advanced control methods
- Detect battery and hardware degradation early with anomaly detection and predictive maintenance
- Compress, verify, and deploy AI to production ECUs
