Battery management systems must select charging protocols in real time while keeping operation within safe limits, yet current systems enforce fixed, non-adaptive constraints that sacrifice performance over the battery lifetime. We propose an Adaptive Safety Certificate (ASC) framework that defines state-dependent safety constraints derived from public aging data and a gradient-boosting risk classifier, tightening automatically as battery health degrades. Integrated into a safe online learning policy, the framework progressively eliminates empirically unsafe protocols as state of health decreases, concentrating selections on protocols that balance charging speed with long-term sustainability. In simulation over 2,000 charging batches, the ASC achieves 41% longer expected battery life than a random baseline, corresponding to $3,528 in deferred replacement cost per vehicle and 2,578 tonnes of avoided CO2 per 1,000-vehicle fleet. Ablation studies con- firm that state-of-health-dependent adaptation is the single most important property of the framework, with direct implications for sustainable fleet management policy.