Article ID: | iaor2016340 |
Volume: | 31 |
Issue: | 8 |
Start Page Number: | 1495 |
End Page Number: | 1502 |
Publication Date: | Dec 2015 |
Journal: | Quality and Reliability Engineering International |
Authors: | Liu Xintian, Zheng Songlin, Feng Jinzhi, Chen Tie |
Keywords: | energy, quality & reliability, heuristics: genetic algorithms |
A fuel cell vehicle (FCV) is a type of alternative energy vehicle that could help resolve the energy crisis, mitigate environmental problems, and contribute to sustainable development. Developing an FCV with high reliability is an important goal for automobile factories and research institutions. Other key factors required by FCVs include mass production and customer approval. An FCV is a complex mechanism composed of many subsystems. During the development of the overall vehicle, steps should be taken to ensure that every subsystem is reliable. However, such development must also consider costs, which must be kept as low as possible. To ensure the reliability of FCV while operating under conditions that demand minimal cost, a genetic algorithm is employed to reallocate the reliability of the overall vehicle system. First, the growth factor of the reliability–feasibility of each subsystem is determined according to the complexity, importance, and technological level of the FCV subsystems. The FCV cost model is then established on the basis of such parameters as subsystem cost, reliability–feasibility growth factor, initial reliability, limit reliability, and so on. A genetic algorithm is then used to compute for the reliability of FCV subsystems. The rationality of reliability reallocation is verified according to the subsystem importance coefficient. This method considers the benefits for both enterprises and customers by applying principles of engineering and conducting a reliability study.