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- W4312748112 abstract "This paper presents an efficiency-improved solution using non-dominated sorting genetic algorithm (NSGA-II) when multiple power electronic building blocks (PEBB) are paralleled to charge a battery. Instead of equal distribution on the power of each PEBB, maximum efficiency points at different power and voltage levels have been calculated as one of the objectives to get different power distribution for each PEBB. Then, the NSGA-II algorithm is adapted to avoid system instabilities by eliminating unpredictable changes in the output current. A multi-objective optimization problem with the efficiency of each PEBB as the objective function and the efficiency database with voltage and power parameters as the constraints is established. The Pareto Front gives the trade-off solution between the optimal working point and controllability of the system. Simulation results show that the proposed method can achieve efficiency-improved battery charging, as well as more stable operation of PEBBs." @default.
- W4312748112 created "2023-01-05" @default.
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- W4312748112 date "2022-01-01" @default.
- W4312748112 modified "2023-09-30" @default.
- W4312748112 title "Efficiency-improved battery charging strategy for paralleled PEBBs using NSGA-II" @default.
- W4312748112 doi "https://doi.org/10.1049/icp.2022.1840" @default.
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