At present,most fuel cell engines are single-stack systems,and high-power single-stack systems have bottlenecks in meeting the power requirements of heavy-duty trucks,mainly because the increase in the single active a...At present,most fuel cell engines are single-stack systems,and high-power single-stack systems have bottlenecks in meeting the power requirements of heavy-duty trucks,mainly because the increase in the single active area and the excessive number of cells will lead to poor distribution uniformity of water,gas and heat in the stack,which will cause local attenuation and reduce the performance of the stack.This paper introduces the design concept of internal combustion engine,takes three-stack fuel cell engine as an example,designs multi-stack fuel cell system scheme and serialized high-voltage scheme.Through Intelligent control technology of independent hydrogen injection based on multi-stack coupling,the hydrogen injection inflow of each stack is controlled online according to the real-time anode pressure to achieve accurate fuel injection of a single stack and ensure the consistency between multiple stacks.proves the performance advantage of multi-stack fuel cell engine through theoretical design,intelligent control and test verification,and focuses on analyzing the key technical problems that may exist in multi-stack consistency.The research results provide a reference for the design of multi-stack fuel cell engines,and have important reference value for the powertrain design of long-distance heavy-duty and high-power fuel cell trucks.展开更多
The durability of proton exchange membrane fuel cells (PEMFC) is an important issue that restricts their large-scale application. To improve their reliability during use, this paper proposes a short-term performance d...The durability of proton exchange membrane fuel cells (PEMFC) is an important issue that restricts their large-scale application. To improve their reliability during use, this paper proposes a short-term performance degradation prediction model using particle swarm optimization (PSO) to optimize the gate recurrent unit (GRU). After training using only the data from the first 300 h, good prediction accuracy can be achieved. Compared with the traditional GRU algorithm, the proposed prediction method reduces the root mean square error (RMSE) and mean absolute error (MAE) of the prediction results by 44.8 % and 35.1 %, respectively. It avoids the problem of low accuracy in predicting performance during the temporary recovery phase in traditional GRU models, which is of great significance for the health management of PEMFC.展开更多
文摘At present,most fuel cell engines are single-stack systems,and high-power single-stack systems have bottlenecks in meeting the power requirements of heavy-duty trucks,mainly because the increase in the single active area and the excessive number of cells will lead to poor distribution uniformity of water,gas and heat in the stack,which will cause local attenuation and reduce the performance of the stack.This paper introduces the design concept of internal combustion engine,takes three-stack fuel cell engine as an example,designs multi-stack fuel cell system scheme and serialized high-voltage scheme.Through Intelligent control technology of independent hydrogen injection based on multi-stack coupling,the hydrogen injection inflow of each stack is controlled online according to the real-time anode pressure to achieve accurate fuel injection of a single stack and ensure the consistency between multiple stacks.proves the performance advantage of multi-stack fuel cell engine through theoretical design,intelligent control and test verification,and focuses on analyzing the key technical problems that may exist in multi-stack consistency.The research results provide a reference for the design of multi-stack fuel cell engines,and have important reference value for the powertrain design of long-distance heavy-duty and high-power fuel cell trucks.
基金supported in part by the Research on Key Technologies of Low Temperature and Long Life Fuel Cells,under Grant 20220301010Gxin part by Qingdao postdoctoral support project under Grant QDBSH20220202020Qingdao Natural Science Foundation under Grant 23-2-1-110-zyyd-jch,Shandong Natural Science Foundation under Grants ZR2023QE208.
文摘The durability of proton exchange membrane fuel cells (PEMFC) is an important issue that restricts their large-scale application. To improve their reliability during use, this paper proposes a short-term performance degradation prediction model using particle swarm optimization (PSO) to optimize the gate recurrent unit (GRU). After training using only the data from the first 300 h, good prediction accuracy can be achieved. Compared with the traditional GRU algorithm, the proposed prediction method reduces the root mean square error (RMSE) and mean absolute error (MAE) of the prediction results by 44.8 % and 35.1 %, respectively. It avoids the problem of low accuracy in predicting performance during the temporary recovery phase in traditional GRU models, which is of great significance for the health management of PEMFC.
