Affiliation:
1. Iran University of Science and Technology, Tehran, Iran
Abstract
Prediction of available energy storage power is essential for increasing the energy management performance of fuel cell hybrid electric systems (FCHES). A simple yet effective power prediction index is proposed to estimate the supercapacitor state of power. It prevents the supercapacitor’s total depletion in the battery/supercapacitor combination. Modern energy management is equipped with an equivalent consumption minimization strategy. The power prediction index is simple compared with other predictive algorithms while providing excellent efficiency compared with supercapacitor-based management strategies. A supercapacitor-based strategy is presented which extends battery life, at the cost of increased fuel consumption. However, it cannot predict the future low state of charge for the supercapacitor. In such conditions, the battery provides the demand power while fuel cells generate more current. On the other hand, the modern power prediction index energy management strategy significantly increases battery life without adding extra hardware. Moreover, fuel consumption decreased by 15.1 percent. The results show that the modern energy management strategy provides outstanding performance for battery life and fuel consumption compared with other energy management strategies due to its power limitation prediction.
Subject
Electrical and Electronic Engineering,Energy Engineering and Power Technology,Modeling and Simulation
Cited by
2 articles.
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