Predictive co-optimization of energy and thermal management in heavy-duty fuel cell vehicles

In heavy-duty fuel cell vehicles, predictive energy management improves fuel economy and favors lifetime-promoting fuel cell operation. The resulting battery load, however, yields severe thermal conditions during challenging driving missions, which may not be sufficiently mitigated by battery cooling alone. This work therefore combines energy management and battery thermal management into a route-based predictive co-optimization, integrating fuel economy and battery thermal objectives. Unlike hierarchical strategies that optimize energy and thermal management sequentially, co-optimization adapts the power split during thermally critical route sections and reduces battery heat generation itself. Real-world truck missions demonstrate substantially mitigated temperature peaks, maintaining both battery temperature and charge within admissible limits. Fuel economy benefits are largely retained, while battery functionality to support the fuel cell is ensured even during demanding sections. Moreover, co-optimization trade-offs underscore the potential to shift degradation-relevant operating conditions between fuel cell and battery, providing a basis for component lifetime balancing.