CPU-FPGA based real-time simulation of fuel cell electric vehicle

被引:29
|
作者
Ma, Rui [1 ]
Liu, Chen [2 ,3 ]
Zheng, Zhixue [2 ,3 ]
Gechter, Franck [4 ]
Briois, Pascal [5 ]
Gao, Fei [2 ,3 ]
机构
[1] Northwestern Polytech Univ, Sch Automat, Xian 710072, Peoples R China
[2] Univ Bourgogne Franche Comte, UTBM, Energy Dept, FEMTO ST,UMR CNRS 6174, F-90010 Belfort, France
[3] Univ Bourgogne Franche Comte, UTBM, FCLAB, FR CNRS 3539, Rue Thierry Mieg, F-90010 Belfort, France
[4] Univ Bourgogne Franche Comte, UTBM, Le2i, UMR CNRS 6306, F-90010 Belfort, France
[5] Univ Bourgogne Franche Comte, UTBM, Dept MN2S, FEMTO ST,UMR CNRS 6174, F-25200 Montbeliard, France
基金
欧盟地平线“2020”;
关键词
Proton exchange membrane fuel cell; Real-time simulation; FPGA; Electric vehicle; PARAMETER SENSITIVITY-ANALYSIS; NONLINEAR CONTROL; CONVERTER; STRATEGY; OPTIMIZATION; EMULATION; SYSTEM; STACK;
D O I
10.1016/j.enconman.2018.08.099
中图分类号
O414.1 [热力学];
学科分类号
摘要
Proton exchange membrane fuel cell (PEMFC) has been considered as one of the promising renewable power technologies for the vehicular application. This paper proposes a fuel cell electric vehicle (FCEV) power system model that can be implemented in the hardware-in-the-loop (HIL) emulation for real-time execution on field-programmable gate arrays (FPGAs). The FCEV model comprises three parts: a PEMFC, a Z-source inverter and a squirrel cage motor. To achieve an accurate and efficient FPGA resources' utilization, the PEMFC model is implemented by CPU whereas the models of the DC-AC inverter and the electrical motor are built in FPGA. For the validation of the proposed power system, the real-time simulation tests are conducted with a high accuracy. The developed hybrid system model can reach a simulation time step of 100 ns for FPGA and 500 mu s for CPU under the co-simulation mode. Moreover, the simulation under various system operating conditions indicates that the high performance can be reached by the hybrid system computed in real-time. The proposed real-time model can be used to design the on-line diagnostic and model predictive control method, which can help to test the FCEV before the commercial applications.
引用
收藏
页码:983 / 997
页数:15
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