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• W2530203480 abstract "Abstract The powertrain system of a typical proton electrolyte membrane hybrid fuel cell vehicle contains a lithium battery package and a fuel cell stack. A multi-objective optimization for this powertrain system of a passenger car, taking account of fuel economy and system durability, is discussed in this paper. Based on an analysis of the optimum results obtained by dynamic programming, a soft-run strategy was proposed for real-time and multi-objective control algorithm design. The soft-run strategy was optimized by taking lithium battery size into consideration, and implemented using two real-time algorithms. When compared with the optimized dynamic programming results, the power demand-based control method proved more suitable for powertrain systems equipped with larger capacity batteries, while the state of charge based control method proved superior in other cases. On this basis, the life cycle cost was optimized by considering both lithium battery size and equivalent hydrogen consumption. The battery capacity selection proved more flexible, when powertrain systems are equipped with larger capacity batteries. Finally, the algorithm has been validated in a fuel cell city bus. It gets a good balance of fuel economy and system durability in a three months demonstration operation." @default.
• W2530203480 created "2016-10-21" @default.
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• W2530203480 date "2016-12-01" @default.
• W2530203480 modified "2023-10-17" @default.
• W2530203480 title "Multi-objective energy management optimization and parameter sizing for proton exchange membrane hybrid fuel cell vehicles" @default.
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• W2530203480 doi "https://doi.org/10.1016/j.enconman.2016.09.082" @default.
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