End User
EMOT
Description
The Degradation-Aware Lifecycle Optimisation service integrates battery aging models directly into operational and strategic decision-making for EV batteries and stationary storage. By embedding degradation cost into dispatch decisions, the service enables operators to evaluate energy flexibility strategies not only for short-term economic performance but also for long-term battery health, lifecycle cost, and sustainability — avoiding premature battery replacement from aggressive operation.
Core Capabilities
Monitoring & Anomaly Detection
Predictive & Prescriptive Analytics
Optimization & Decision Support
Business Need
Traditional optimisation approaches that ignore battery degradation may produce attractive short-term results while generating hidden long-term costs. Energy communities, aggregators, and fleet operators need visibility into the trade-off between flexibility revenue and battery lifetime to make sustainable operational decisions, justify investment cases, and comply with sustainability reporting commitments.
Key Performance Indicators
Annual capacity fade and equivalent full cycle accumulation
Degradation cost per unit of delivered energy
Lifecycle-adjusted return on investment comparison across strategies
Remaining useful life estimation accuracy against historical maintenance records
Data Provided
Incremental battery degradation estimates and cumulative metrics (equivalent full cycles, remaining capacity)
Lifecycle outputs: capacity fade trajectories, degradation-adjusted revenue, remaining useful life
Comparative scenario analysis across different operational strategies
Inputs: battery operational trajectories, depth of discharge, cycling intensity, calendar aging, temperature
TEF
TEF EV