| 引用本文: | 申永鹏,谢俊超,梁伟华,等.电动汽车混合储能系统CEEMD-PE能量管理策略[J].电力系统保护与控制,2023,51(13):122-131. |
| SHEN Yongpeng,XIE Junchao,LIANG Weihua,et al.Electric vehicle hybrid energy storage system CEEMD-PE energy management strategy[J].Power System Protection and Control,2023,51(13):122-131 |
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| 摘要: |
| 针对电动汽车行驶过程中高频需求功率分量引起的锂离子动力电池寿命衰减问题，提出了一种完备集合经验模态分解-排列熵(complete ensemble empirical mode decomposition-permutation entropy, CEEMD-PE)能量管理策略。电动汽车功率需求被分解为有限个本征模态函数分量，并依据排列熵量度的各个本征模态函数分量的数据复杂度，将各个分量重构为低频分量和高频分量。最后，将包含瞬态功率和快速变化的高频分量分配给超级电容器，而将低频分量相应地分配给电池，实现了功率需求低频分量和高频分量在锂离子动力电池和超级电容之间的功率分流。实验结果表明，相较于Haar小波混合储能能量管理策略，在中速和高速区间的锂离子动力电池电流的均方根值分别减小5.91%和4.17%，电流峰值分别减小14.70%和5.77%。所提出的策略有助于抑制锂离子动力电池所承受的高频功率需求，降低大电流对锂离子动力电池的冲击。 |
| 关键词: 电动汽车 混合储能 完备集合经验模态分解 排列熵 能量管理 |
| DOI：10.19783/j.cnki.pspc.221497 |
| 分类号: |
| 基金项目:国家自然科学基金项目资助(62273313，62073127)；河南省科技攻关项目资助(222102240005)；郑州市协同创新专项资助(2021ZDPY0204) |
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| Electric vehicle hybrid energy storage system CEEMD-PE energy management strategy |
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SHEN Yongpeng1, 2, XIE Junchao1, LIANG Weihua1, YUAN Xiaofang2, 3, SUN Songnan1
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1. Zhengzhou University of Light Industry, Zhengzhou 450002, China; 2. National Engineering Laboratory for Robot Visua
Perception and Control Technology, Hunan University, Changsha 410082, China; 3. Hunan University, Changsha 410082, China
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| Abstract: |
| There is a problem of the life attenuation of lithium-ion batteries caused by high-frequency demand power components during electric vehicle driving. Thus a complete ensemble empirical mode decomposition-permutation entropy (CEEMD-PE) energy management strategy is proposed. The electric vehicle power demand is decomposed into a finite number of intrinsic mode functions (IMFs), and each component is reconstructed into low- and high frequency components according to the data complexity of each IMF measured by PE. Finally, the high-frequency components containing transient power and fast changes are assigned to the ultracapacitor, while the low-frequency components are assigned to the battery. The experimental results show that, compared with the Haar wavelet strategy, the root mean square (RMS) value of the lithium-ion battery current in the medium-speed and high-speed regions is reduced by 5.91% and 4.17%, respectively, and the current peak value is reduced by 14.70% and 5.77%, respectively. The proposed strategy helps to suppress the high-frequency power demand endured by lithium-ion batteries and reduce the impact of large currents on lithium-ion batteries. |
| Key words: electric vehicle hybrid energy storage system CEEMD PE energy management |
