In this paper, a nonlinear observer design to estimate different gas species profiles and partial pressures in a fuel delivery system (FDS) with gas permeation is presented. Precise knowledge of critical internal states is of great importance to ensure reliable and efficient operation for FDS. First, a nonlinear isothermal dynamic model including fuel supply, hydrogen consumption, mixture recirculation and exhaust is formulated. Then a nonlinear observer based on projection algorithm is proposed, giving detailed information on internal conditions of FDS online. Without calculation of inverse matrix, the stack output voltage is treated as the only measurable observer input. The voltage estimation error is obtained from the difference between the prediction and the actual measurement, and nonlinear error injection matrix and projection term are employed as correction inputs. Finally, the proposed dynamic state observer is validated and compared with second order sliding mode (SOSM) observer on RT-LAB platform, the results indicate that the observer shows better real-time estimation performance and robustness. Furthermore, the observer demonstrates good robustness in terms of hydrogen partial pressures observation, but less robustness in nitrogen partial pressures estimation. Moreover, the sequence of key system parameters effecting the estimations are analyzed deeply and some conclusions are extracted.

在本文中，提出了一种非线性观测器设计，用于估计具有气体渗透的燃油输送系统（FDS）中的不同气体种类分布和分压。对关键内部状态的准确了解对于确保FDS的可靠和有效运行非常重要。首先，建立了一个非线性等温动力学模型，包括燃料供应，氢消耗，混合物再循环和排气。然后提出了一种基于投影算法的非线性观测器，在线给出了FDS内部情况的详细信息。如果不计算逆矩阵，则将堆栈输出电压视为唯一可测量的观察者输入。根据预测值与实际测量值之间的差值获得电压估算误差，非线性误差注入矩阵和投影项用作校正输入。最后，对提出的动态状态观测器进行了验证，并与RT-LAB平台上的二阶滑模观测器进行了比较，结果表明该观测器具有较好的实时估计性能和鲁棒性。此外，观察者在观察氢分压方面显示出良好的鲁棒性，但在氮分压估计中却缺乏鲁棒性。此外，深入分析了影响估计的关键系统参数的顺序，并得出了一些结论。结果表明观察者表现出更好的实时估计性能和鲁棒性。此外，观察者在观察氢分压方面显示出良好的鲁棒性，但在氮分压估计中却缺乏鲁棒性。此外，深入分析了影响估计的关键系统参数的顺序，并得出了一些结论。结果表明观察者表现出更好的实时估计性能和鲁棒性。此外，观察者在观察氢分压方面显示出良好的鲁棒性，但在氮分压估计中却缺乏鲁棒性。此外，深入分析了影响估计的关键系统参数的顺序，并得出了一些结论。