摘要
为保证燃料电池系统在负载工况变化条件下仍能无扰动地运行在最大效率点,提出一种基于遗忘因子递推最小二乘(forgetting factor recursive least square,FFRLS)在线辨识和Super-Twisting滑模算法的燃料电池系统实时最大效率跟踪方法。该方法基于非线性曲线拟合原理,根据系统实时测量数据,在单位控制周期内实现对燃料电池最大效率点功率的实时估计。采用Super-Twisting滑模算法,保证燃料电池系统在负载工况变化情况下仍能运行在最大效率点。在搭建的测试平台上,开展了多指标性能测试与对比分析。实验结果表明,与扰动观测(perturb and observe,P&O)算法相比,所提出的方法优势更加明显。另外,针对燃料电池输出存在大扰动问题,与PID控制效果进行了对比实验。实验结果显示:Super-Twisting滑模控制变换器在输入电压大扰动下具有较强的鲁棒性,有利于燃料电池系统长期稳定运行。
In order to guarantee the fuel cell system working at maximum efficiency point without disturbance under the varying load conditions. This paper proposed a method based on forgetting factor recursive least square(FFRLS) online identification and Super-Twisting sliding mode control algorithm for tracking the real-time maximum efficiency point of fuel cell system. The proposed method is based on the nonlinear curve fitting principle, according to the real-time data of the system, the maximum efficiency point power of the fuel cell can be estimated in real time within the unit control period. Then, the Super-Twisting sliding mode algorithm was used to ensure that the fuel cell system can still operate at the maximum efficiency point under the varying load conditions. On the test bench, a multi-index performance test and comparative analysis were carried out. The experimental results show that, the proposed real-time maximum efficiency point tracking method has obvious advantages compared with the traditional disturbance observation(P&O) method. A comparative experiment with the traditional PID algorithm was carried out. The results show that, under the large disturbances in input, the converter controlled by the Super-Twisting sliding mode algorithm has stronger robustness, which is beneficial to the long-term stable operation of the fuel cell power system.
作者
王天宏
李奇
尹良震
苏波
黄文强
陈维荣
WANG Tianhong;LI Qi;YIN Liangzhen;SU Bo;HUANG Wenqiang;CHEN Weirong(School of Electrical Engineering,Southwest Jiaotong University,Chengdu 610031,Sichuan Province,China)
出处
《中国电机工程学报》
EI
CSCD
北大核心
2019年第17期5118-5128,共11页
Proceedings of the CSEE
基金
国家自然科学基金项目(61473238)
国家重点研发计划(2017YFB1201003-019)
国家轨道交通电气化与自动化工程技术研究中心开放课题(NEEC-2017-B01)~~
