Abstract
Multi-Criteria Decision Making (MCDM) methods have rapidly developed and have been applied to many areas for decision making in engineering. Apart from that, the process to select fault-diagnosis sensor for Fuel Cell Stack system in various options is a multi-criteria decision-making (MCDM) issue. However, in light of the choosing of fault diagnosis sensors, there is no MCDM analysis, and Fuel Cell Stack companies also urgently need a solution. Therefore, in this paper, we will use MCDM methods to analysis the fault-diagnosis sensor selection problem for the first time. The main contribution of this paper is to proposed a fault-diagnosis sensor selection methodology, which combines the rank reversal resisted AHP and TOPSIS and supports Fuel Cell Stack companies to select the optimal fault-diagnosis sensors. Apart from that, through the analysis, among all sensor alternatives, the acquisition of the optimal solution can be regarded as solving the symmetric or asymmetric problem of the optimal solution, which just maps to the TOPSIS method. Therefore, after apply the proposed fault-diagnosis sensor selection methodology, the Fuel Cell Stack system fault-diagnosis process will be more efficient, economical, and safe.
Highlights
Jin Wu and Chong LiA Fuel Cell Stack system (FCS) refers to a power generation system with fuel cell as the core, fuel supply and circulation system, oxidizer supply system, water/heat management system, control system, etc., and able to continuously output electronic power [1]
When we consider the stability between the COPRAS and TOPSIS techniques with a value variable, we find that TOPSIS is better and more insensitive when the value does not change much, and compared with other technologies, the priority result is different [47]
After all the considerations above, we have found that the Analytic Hierarchy Process (AHP) and TOPSIS method is the most adaptable for the fault-diagnosis sensor selection
Summary
Jin Wu and Chong Li. A Fuel Cell Stack system (FCS) refers to a power generation system with fuel cell as the core, fuel supply and circulation system, oxidizer supply system, water/heat management system, control system, etc., and able to continuously output electronic power [1]. The main research interests for FCS include using lightweight materials, optimizing design, and improving the specific power of the fuel cell system, improving the fast cold start capability and dynamic response performance of the FCS system, researching fuel processors with load following capabilities, optimizing supercapacitors and hydrogen storage for system design to improve system efficiency and peak shaving capabilities, recover braking energy, etc. The FCS is mainly composed of a stack, a fuel processor, a power regulator, and an air compressor. The fault diagnosis is the process of using various detection and testing methods to find out whether there is a fault in the system and equipment [4]
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