电动汽车复合能源系统能量管理策略研究

胡杰; 刘迪; 杜常清; 颜伏伍

doi:10.13433/j.cnki.1003-8728.20190303

电动汽车复合能源系统能量管理策略研究

doi: 10.13433/j.cnki.1003-8728.20190303

胡杰^{1, 2, 3,},
刘迪^{1, 2, 3},
杜常清^{1, 2, 3},
颜伏伍^{1, 2, 3}

1.
武汉理工大学现代汽车零部件技术湖北省重点实验室，武汉　430070
2.
武汉理工大学汽车零部件技术湖北省协同创新中心，武汉　430070
3.
新能源与智能网联车湖北工程技术研究中心，武汉　430070

基金项目: 国家自然科学基金项目（51775393）与柳州市科技计划项目（2018BC20501）资助

详细信息

作者简介:
胡杰（1984−），副教授，博士生导师，博士，研究方向为汽车控制与诊断、车联网与大数据，auto_hj@163.com

中图分类号: U469.72
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- 文章访问数: 317
- HTML全文浏览量: 84
- PDF下载量: 41
- 被引次数: 0
出版历程
- 收稿日期: 2019-07-28
- 网络出版日期: 2020-10-12
- 刊出日期: 2020-10-05

Study on Energy Management Strategy of Hybrid Energy Storage System for Electric Vehicles

Hu Jie^{1, 2, 3
,},
Liu Di^{1, 2, 3},
Du Changqing^{1, 2, 3},
Yan Fuwu^{1, 2, 3}

1.
Hubei Key Laboratory of Modern Auto Parts Technology, Wuhan University of Technology, Wuhan 430070, China
2.
Auto Parts Technology Hubei Collaborative Innovation Center, Wuhan University of Technology, Wuhan 430070, China
3.
Hubei Technology Research Center of New Energy and Intelligent Connected Vehicle Engineering, Wuhan 430070, China

摘要

摘要: 针对电动汽车单一动力电池功率密度低、循环寿命短、接收暂态功率等问题，设计了由动力电池和超级电容组成的复合能源系统，提出了基于小波变换-模糊控制的能量管理策略，并对不同分解层数的小波变换进行评价和选择。该控制策略利用小波变换将需求功率分解成低频成分和高频成分，并根据能量源的动态响应特性进行分配，避免动力电池接收暂态功率；为了充分利用超级电容“削峰填谷”的作用来提高电池的性能和循环寿命，采用模糊控制将超级电容的荷电状态(State of charge, SOC)维持在合适的范围内。建立MATLAB/Simulink仿真模型基于随机组合的循环工况验证所提策略的有效性，并与传统的控制策略进行比较。仿真结果表明：采用所提出的能量管理策略可以有效地减少峰值电流对动力电池的冲击，并且相比于单一电源的电动汽车还可以将能量利用率提高5.96%，电池的最大输出电流降低了57.1%，电池的温升降低了35.3%。
- 电动汽车 /
- 暂态功率 /
- 复合能源系统 /
- 小波变换 /
- 模糊控制
Abstract: Aiming at the low power density, short cycle life and transient power reception of single battery in electric vehicle, a hybrid energy storage system being composed of power battery and supercapacitor was designed. The energy management strategy based on the wavelet transform-fuzzy control was proposed, and the wavelet transform of different decomposition levels was evaluated and selected. The present control strategy used wavelet transform to decompose the power demand into low frequency and high frequency components, and distributed them according to the dynamic response characteristics of the energy sources, so as to avoid the reception of transient power of battery. In order to fully utilize the load shifting rule of supercapacitor to improve the performance and cycle life of battery, fuzzy control was adopted to maintain the SOC value of supercapacitor within appropriate limits. MATLAB/Simulink simulation model was established to verify the effectiveness of the present control strategy based on the driving cycles randomly combined, and compared with the conventional control strategy. The simulation results show that the present energy management strategy can not only effectively prevent the battery from high-current impact, but also improve the energy utilization rate by 5.96% comparing with the single battery used in electric vehicle. The maximum battery output current decreases by 57.1%, and battery temperature rise decreases by 35.3%.
- electric vehicle /
- transient power /
- hybrid energy storage system /
- wavelet transform /
- fuzzy control

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图 1 复合能源系统的拓扑结构

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图 2 部件模型

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图 3 逻辑门限控制策略流程图

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图 4 Haar小波分解和重构模型

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图 5 滑动窗口移动示意图

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图 6 模糊逻辑控制模型

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图 7 模糊规则输出界面

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图 8 能量管理策略框架图

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图 9 仿真循环工况

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图 10 复合能源系统动力电池

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图 11 复合能源系统超级电容

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图 12 电池工作温度变化

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表 1 复合能源系统电动汽车主要参数

部件名称	参数名称	数值
整车	迎风面积	2.19 m²
	车轮滚动半径	0.262 m
	空气阻力系数	0.32
	滚阻系数	0.02
	主减速比	5.67
镍氢动力电池	额定电压	12 V
	容量	90 Ah
	数量	27
Maxwell PC2500 超级电容	额定电压	2.7 V
	容量	1000 F
	数量	119

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表 2 复合能源电动汽车动力性能

名称	最大速度/ (km·h⁻¹)	0~50 km/h 加速时间/s	最大爬坡度/%	续驶里程/km
性能需求	>120	<5	>20(50 km/h)	>170
匹配结果	149	2.8	32.4	174.6

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表 3 典型循环工况的能量源性能需求

性能参数	NYCC	China	UDDS	NEDC	HWFET
正能量需求/kJ	1680.36	7266.48	8093.61	7266.99	10336.5
负能量需求/kJ	−659.13	−2523.82	−2134.61	−1395.64	−613.31
正平均功率/kW	6.72	11.39	9.79	10.18	14.79
负平均功率/kW	−4.74	−8.56	−7.52	−8.07	−10.05
正峰值功率/kW	40.64	44.44	44.86	46.69	37.00
负峰值功率/kW	−23.87	−32.79	−27.90	−29.19	−39.94

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表 4 不同工况下的评价参数

工况分解层数	CYC_NYCC	CYC_UDDS	CYC_US06
2	0.9779	1	1
3	0.3235	0.4903	0.4306
4	0.1621	0.1991	0.1470

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表 5 不同控制策略下电池SOC变化

控制类型	起始 SOC	终止 SOC	SOC变化量	SOC相对变化	百分比
单一电源	1	0.7896	0.2104	0	0
A控制策略	1	0.7952	0.2048	0.0056	2.66%
B控制策略	1	0.8021	0.1979	0.0125	5.94%

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