Automotive & EV
Model battery degradation, thermal drift, and structural stress. Enable predictive workflows for critical EV systems—faster than traditional simulation, and built for production deployment.
Electrification, autonomy, and lightweighting are pushing vehicle design into new complexity. The MIND Platform equips engineering teams with AI tools to accelerate material discovery, optimize battery performance, simulate thermal behavior, and predict system degradation—backed by interpretable, production-grade modeling workflows.
Battery Innovation & Health Prediction
Design better batteries—and make them last longer—with AI-powered insights across materials, usage, and environmental conditions.
- Identify high-performance chemistries and formulations using AI-driven materials modeling
- Predict battery degradation and thermal drift from real-world usage data
- Optimize charge cycles, cooling strategies, and lifespan with interpretable models
Structural and Mechanical Optimization
Simulate stress, fatigue, and failure modes across vehicle architectures—faster and more flexibly than with FEA alone.
- Use AI to augment or accelerate structural simulations
- Model the impact of new geometries, loads, and materials across drive cycles
- Generalize insights across variants and design iterations
Thermal Management Across Systems
Control temperature with precision across batteries, powertrains, and electronics.
- Run thermal simulations faster using AI surrogates trained on FEA or CFD data
- Predict heat concentration zones and failure-prone areas under real-world usage
- Improve cooling system design and test new configurations virtually
Predictive Maintenance & Digital Twin Modeling
Move from reactive service schedules to predictive maintenance models that account for wear, conditions, and use.
- Ingest field and sensor data to build component-specific degradation models
- Deploy early warning systems for battery packs, motors, and control systems
- Power digital twins with interpretable AI that engineers trust
Solving Hard Problems Starts Here.
Let’s solve yours next. From simulation bottlenecks to multiscale manufacturing complexity—tell us what you’re up against. We’ll dig in together.
