AI Second-Life Battery Management
Machine learning for repurposing and managing second-life EV batteries
The Problem
“Optimize second-life batteries for safe grid value”
Organizations face these key challenges:
Highly variable SOH across modules/cells leads to imbalance, accelerated degradation, and frequent derating to meet warranty and safety limits
Incomplete or unreliable first-life history makes it difficult to predict RUL, plan spares, and underwrite performance guarantees
Reactive maintenance and late fault detection increase downtime, safety risk, and replacement costs, undermining project economics
Impact When Solved
The Shift
Real-World Use Cases
AI-Driven Battery Optimization and Lifecycle Management
Think of this like a smart mechanic for batteries: it constantly listens to how your batteries ‘feel’, predicts when they’ll get tired, and adjusts how they’re used so they last longer and work more efficiently in cars, homes, and the grid.
Energy Storage Optimization using AI
AI helps batteries work better by deciding when to store or release energy.