Energy management and component sizing for a fuel cell/battery/supercapacitor hybrid powertrain based on two-dimensional optimization algorithms
Optimal algorithms for energy management and component sizing play essential roles in reducing energy consumption and prolonging fuel cell durability of fuel cell electric vehicles. These two problems are usually coupled together, and it is of great importance to study. In this work, an energy consu...
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Veröffentlicht in: | Energy (Oxford) 2019-06, Vol.177, p.386-396 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Optimal algorithms for energy management and component sizing play essential roles in reducing energy consumption and prolonging fuel cell durability of fuel cell electric vehicles. These two problems are usually coupled together, and it is of great importance to study. In this work, an energy consumption and durability model of a bus with a combined fuel cell, battery, and supercapacitor powertrain are introduced. A two-dimensional (2D) dynamic programing (DP) algorithm was designed to minimize energy consumption and system degradation. A real-time energy management strategy based on a 2D Pontryagin's Minimal Principle (2DPMP) was then proposed. Simulation results indicated that the proposed 2DPMP strategy can approximate the optimal strategy of dynamic programming well and showed a reduction in energy consumption and an increase in durability over other strategies. Component parameters and energy management strategy were simultaneously optimized based on the 2DPMP strategy, thus providing a set of optimal powertrain parameters on a Pareto front. Design rules for energy management strategy and component sizing were concluded from the set of optimal solutions.
•Fuel cell hybrid powertrain with three power sources is studied.•Two-Dimensional algorithms are used to obtain optimal operating cost.•Optimal strategies significantly reduce the energy consumption and degradation of fuel cell and battery.•Component parameters and energy management strategy are simultaneously optimized. |
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ISSN: | 0360-5442 1873-6785 |
DOI: | 10.1016/j.energy.2019.04.110 |