Impedance optimization method for porous gradient anode supported solid fuel cell

By deploying multiple impedance sensors and optimization controllers in the porous gradient anode, an impedance state matrix is constructed to predict the electrode impedance distribution, which solves the problems of uneven impedance distribution and dynamic changes in traditional methods, and dynamic optimization of the spatiotemporal distribution characteristics of the electrode impedance is achieved, which improves the performance and stability of solid fuel cells.

CN120373152AActive Publication Date: 2025-07-25CHANGSHU INSTITUTE OF TECHNOLOGY
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Patent Information

Application Number
CN202510855711.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-25
Publication Date
2025-07-25
Estimated Expiration
2045-06-25

AI Technical Summary

Technical Problem

In the existing solid fuel cell management system, in porous gradient anode-supported solid fuel cells, traditional single-point measurement methods are difficult to capture the spatiotemporal distribution characteristics of electrode impedance. The static model cannot adapt to impedance changes under dynamic operating conditions, resulting in increased impedance optimization complexity, and insufficient processing capabilities for sensor network deployment and algorithm fusion, making it impossible to achieve high-precision and real-time impedance optimization.

Method used

By deploying multiple impedance sensors at the porous gradient anode, a distributed sensor network is built, voltage and current data are collected to generate impedance state data sets, the optimization controller constructs a regional impedance state matrix, combines the potential gradient and electrolyte path information to predict the impedance distribution, and builds an impedance optimization model to achieve dynamic optimization of the spatiotemporal distribution characteristics of the electrode impedance.

Benefits of technology

Accurate prediction and dynamic regulation of the spatial and temporal distribution of electrode impedance is achieved, the spatial resolution and integrity of data acquisition are improved, the impact of inter-electrode interference and transmission delay is overcome, the accuracy and reliability of impedance analysis is ensured, and the performance and stability of solid fuel cells are significantly improved.

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Abstract

The invention relates to the technical field of solid fuel cells, and discloses a porous gradient anode supported solid fuel cell impedance optimization method which is applied to a system comprising a plurality of porous gradient anode impedance sensors and an optimization controller. The method comprises the steps that a sensor collects voltage and current data to generate an impedance state data set; the optimization controller constructs a regional impedance state matrix, extracts features through processing, performs impedance distribution prediction in combination with a potential gradient and the like, outputs spatial and temporal distribution features through an impedance optimization model, and updates a data set; and dynamically optimizing regional electrode parameters according to the distribution characteristics, including voltage adjustment, current aggregation, resistance distribution and other operations. According to the method, through multi-sensor distributed acquisition, multi-dimensional feature analysis and dynamic modeling, accurate prediction and parameter dynamic regulation and control of electrode impedance spatial and temporal distribution are realized, the performance and stability of the solid fuel cell are improved, and the method is suitable for the field of solid fuel cell management.
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