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Fuel optimization strategy for hydrogen fuel cell range extender vehicles applying genetic algorithms

期刊

RENEWABLE & SUSTAINABLE ENERGY REVIEWS
卷 81, 期 -, 页码 655-668

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rser.2017.08.047

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Electric vehicle; Fuel cell; Extended range; Genetic algorithm; Simulation; Optimization

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Whether or not alternative fuel vehicles (AFVs) will finally find a place in the global mass-market or even will dominate the vehicle segment will depend on several success factors: reduction of customer anxiety, fast recharging, better charging infrastructure, environmental justice policies and some others. Current technological advances in battery electric vehicles and hydrogen fuelled electric vehicles could represent a hopefully option in the near future. Nevertheless, and until electric/hydrogen technological barriers are not torn down, both power architecture do not have an opportunity to be fully introduced in the vehicle market. In this paper, the authors present a powertrain architecture concept based in current fossil fuel extender range, but changing it to a hydrogen fuel cell stack system that works as range extender. The objective is to probe how optimization techniques, by the inclusion of genetic algorithms, could be a crucial help when planning the fuel consumption/selection. The paper ambition is to highlight the possibilities of this powertrain and its appropriated management to allow hydrogen become an energy carrier feasible today in the automotive world.

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