车载工况下燃料电池电堆含水状态变化规律及其在线识别

In view of the uncertainty and inapplicability of the existing fuel cell water-content identification technology in driving cycle and complex operating environment, for the needs of water content online identification about high-power fuel cell stack in the process of cold start, dynamic load change and start-stop, this project lays the foundation for the existing water management research towards the expansion and application of high-power stack by defining the boundary of fuel cells for vehicles. It will improve the accuracy of the water content estimation model of liquid phase by exploring the monomer inconsistencies caused by spatial differences, analyzing the distribution of water content and the state transition mechanism of high-power stack monomers under different operating conditions, clarifing the conversion rules of different flow regimes, and extracting the characteristic parameters of fluid pressure fluctuations of the stack. And it will improve the reliability of on-board water-content identification algorithm based on high frequency impedance by quantifying the sensitivity of vehicle electromagnetic interference and transient load fluctuation to the accuracy of on-line electrochemical impedance identification results, exploring the method of improving the accuracy of identification based on signal filtering and condition parameter fusion identification and deriving boundary conditions which based on this method achieving accurate identification conditions. The sliding mode decision mechanism of data fusion is established based on working condition parameters and historical information. Combined with the environment and vibration simulation test of fuel cell engine, the recognition algorithm is optimized to meet the precision requirements of vehicle applications.

针对现有燃料电池含水状态识别技术在车用环境和复杂工况下应用的不确定性和不适用性，面向大功率电堆在低温冷启动、动态变载以及启停机过程中的含水量在线辨识需求，通过界定车用燃料电池工作的边界条件，为现有水管理研究成果向大功率电堆拓展应用奠定基础；探索空间差异引起的单体不一致性，分析不同工况下的大功率电堆单体含水量分布及含水状态变换机理，阐明不同流态的转换规律，提取电堆流体压力波动特征参数，提高液相含水量估算模型的精确性；量化车辆电磁干扰以及瞬态负载波动对在线电化学阻抗辨识结果准确性影响的敏感度，探索基于信号滤波和工况参数融合辨识提高辨识结果准确性的方法，推导基于该方法实现准确辨识的边界条件，提高基于高频阻抗在线含水状态识别算法的可靠性；利用工况参数和历史信息建立数据融合的滑模结构决策机制，结合燃料电池发动机的环境、振动模拟测试验证，优化识别算法使其达到满足车辆应用的精度要求。

车载工况燃料电池含水状态的识别与控制是保证其正常运行的关键因素。针对原有燃料电池含水状态识别技术在车用环境和复杂工况下应用的不确定性和不适用性，面向大功率电堆在低温冷启动、动态变载以及启停机过程中的含水量在线辨识需求，本项目开展了以下四项研究：.基于阻抗谱的含水状态识别方法研究。为了利用阻抗谱实现车用燃料电池含水状态识别，首先利用反应机理分析燃料电池含水状态对输出性能的影响规律，然后通过改变操作条件获得了不同燃料电池含水状态下的阻抗数据，结合机理分析和试验数据阐述了阻抗与含水状态之间的关联关系，构建了基于阻抗谱的大功率燃料电池含水状态识别方法。.车载阻抗测量装置设计。为了将基于阻抗谱的含水状态识别方法应用到车载领域，设计了适用于多种动力系统架构的交流激励模块；设计了阻抗巡检模块的硬件电路和阻抗计算方法；测试结果表明所设计的车载阻抗测量装置与标准仪器具有相同的测试效果。.基于排氢脉动电压的含水状态识别方法研究。为了满足无阻抗测量装置燃料电池系统的含水状态识别需求，通过建立燃料电池阳极排氢脉动电压模型和基于小波变换的脉动电压特征提取算法，提出了利用样机脉动电压能量强度的含水状态识别方法。40kW燃料电池系统测试结果表明脉动电压能量强度呈现与含水状态的强相关性，且与高频阻抗具有相同敏感度。.典型工况燃料电池含水状态控制策略研究。为了降低车用动态工况下燃料电池含水状态的波动，建立了面向车用环境变化特性建立燃料电池含水状态计算模型，阐明了不同燃料电池系统架构以及运行工况下燃料电池含水状态的变化规律，并构建了基于无增湿燃料电池系统单一干扰因素以及多干扰因素的含水状态优化控制策略。.通过上述研究，本项目建立了车载工况下燃料电池含水状态进行在线识别与控制方法，可有效提升燃料电池发电效率、寿命和环境适应性，为燃料电池系统在交通领域的大规模应用与推广奠定技术基础。