基于云车协同的数据驱动燃料电池系统的预测控制方法
By using a data-driven approach that integrates cloud and vehicle technologies, a scenario-based model is constructed and real-time adaptive control is performed. This solves the problems of low efficiency, high hydrogen consumption, and fuel cell stack degradation in fuel cell systems, enabling efficient operation and long lifespan of fuel cell systems in different scenarios.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- TIANJIN UNIV
- Filing Date
- 2026-05-19
- Publication Date
- 2026-07-17
AI Technical Summary
Existing fuel cell systems suffer from low efficiency, high hydrogen consumption, severe water management and stack degradation issues in actual vehicle operation, and lack scenario-based control strategies. Existing models also lack accuracy and adaptability, and cannot effectively utilize massive amounts of vehicle operating data for optimization.
Through cloud-vehicle collaboration, real-time data from the fuel cell system is collected, cloud-based data processing and scenario clustering are performed, scenario-based hydrogen consumption and degradation models are constructed, and real-time adaptive model predictive control is executed on the vehicle to optimize the control strategy of the fuel cell system.
It enables more precise hydrogen consumption management and stack degradation control in different scenarios, reduces total life cycle cost, extends fuel cell life, and improves system efficiency and reusability.
Smart Images
Figure CN122219121B_ABST