基于超级电容的列车制动能量回收控制策略

doi:10.16180/j.cnki.issn1007-7820.2022.05.012

摘要/Abstract

摘要：

针对列车电制动回馈能量回收与利用问题,文中通过分析列车运行特性,重点探究了列车运行过程与牵引网电压波动之间的关系。结合牵引变电所供电功率与列车用电功率动态不匹配特性,采用车载式制动能量回收利用系统的方案,提出了基于列车用电功率动态变化的超级电容充放电控制策略。该方案主要由超级电容串并联储能单元和双向DC-DC变换器组成。利用MATLAB进行建模仿真分析,结果表明,该控制策略在有效回收利用列车制动能量的同时抑制了牵引网电压波动,为列车制动能量回收与利用提供了有效的解决方案。

关键词: 电制动, 能量回收, 超级电容, 变换器, 电压波动, 储能, 充放电, 控制策略

Abstract:

In view of the problem of recovery and utilization of energy feedback from train electric braking, this study analyzes train operation characteristics and focuses on the relationship between train operation process and traction network voltage fluctuations. Combining the dynamic mismatch between the power supplied by the traction substation and the electric power of the train, a vehicle-mounted braking energy recovery and utilization system is adopted, and a super capacitor charging and discharging control strategy based on the dynamic change of the electric power of the train is proposed. The program is mainly composed of super capacitor series-parallel energy storage units and bidirectional DC-DC converters. MATLAB is used for modeling and simulation analysis. The simulation experiment results show that the control strategy can effectively recover and utilize the braking energy of the train while restraining the voltage fluctuation of the traction network, which provides an effective solution for the recovery and utilization of the braking energy of the train.

Key words: electric braking, energy recovery, super capacitor, converter, voltage fluctuation, energy storage, charge and discharge, control strategy

中图分类号:

TP271

曾光,杨俭,宋瑞刚. 基于超级电容的列车制动能量回收控制策略[J]. 电子科技, 2022, 35(5): 74-80.

ZENG Guang,YANG Jian,SONG Ruigang. Control Strategy of Supercapacitor Based on Train Braking Energy Recovery[J]. Electronic Science and Technology, 2022, 35(5): 74-80.

图/表 11

图1

图2

图3

图4

图5

图6

图7

图8

表1

表2

图9

参考文献 18

[1]	杨俭, 李发扬, 宋瑞刚, 等. 城市轨道交通车辆制动能量回收技术现状及研究进展[J]. 铁道学报, 2011, 33(2):26-33.
	Yang Jian, Li Fayang, Song Ruigang, et al. Review of the utilization of vehicular braking energy in urban railway transportation[J]. Journal of the China Railway Society, 2011, 33(2):26-33.
[2]	Nasri A, Moghadam M F, Mokhtari H. Timetable optimization for maximum usage of regenerative energy of braking in electrical railway systems[C]. Pisa: Proceedings of the IEEE International Symposium on Power Electronics,Electrical Drives,Automation and Motion, 2010.
[3]	张哲. 地铁牵引电传动系统与其控制技术研究[D]. 北京: 北京交通大学, 2015.
	Zhang Zhe. Research on electric traction drive system and its control technology for metro vehicle[D]. Beijing: Beijing Jiaotong University, 2015.
[4]	李少龙, 杨晓洁, 李文龙, 等. 基于ADRC的异步电机DTC系统仿真研究[J]. 电子科技, 2018, 31(2):35-39.
	Li Shaolong, Yang Xiaojie, Li Wenlong, et al. Simulation research on DTC system of asynchronous motor based on ADRC[J]. Electronic Science and Technology, 2018, 31(2):35-39.
[5]	宋娟娟, 杨歆豪, 李则, 等. 重载混合动力汽车能量管理策略的优化研究[J]. 电子科技, 2018, 31(6):39-42.
	Song Juanjuan, Yang Xinhao, Li Ze, et al. Research on energy management strategies optimal for hybrid electric vehicles[J]. Electronic Science and Technology, 2018, 31(6):39-42.
[6]	邬明亮. 电气化铁路光伏发电技术及其经济性研究[D]. 成都: 西南交通大学, 2018.
	Wu Mingliang. Research on photovoltaic generation technology and its ecnomic performance in electrified railway[D]. Chengdu: Southwest Jiaotong University, 2018.
[7]	赵坤. 城轨交通车载超级电容储能系统能量管理及容量配置研究[D]. 北京: 北京交通大学, 2013.
	Zhao Kun. Energy management and capacity configuration of on-board EDLC energy storage system of railway vehicle[D]. Beijing: Beijing Jiaotong University, 2013.
[8]	付建哲, 郭昆丽, 闫东. 直流微电网内双向DC-DC变换器的自抗扰控制研究[J]. 国外电子测量技术, 2020, 33(3):47-52.
	Fu Jianzhe, Guo Kunli, Yan Dong. Research on active disturbance rejection control strategy of bidirectional DC-DC converters in dc microgrid[J]. Foreign Electronic Measurement Technology, 2020, 33(3):47-52.
[9]	杨丰萍, 郑文奇, 金林, 等. 基于MMC的车载超级电容储能系统综合控制策略[J]. 储能科学与技术, 2019, 8(6):1151-1158.
	Yang Fengping, Zheng Wenqi, Jin Lin, et al. Integrated control strategy of vehicle supercapacitor energy storage system based on MMC[J]. Energy Storage Science and Technology, 2019, 8(6):1151-1158.
[10]	Yanik M O, Yigit E A, Akansu Y E, et al. Magnetic conductive polymer-graphene nanocomposites based supercapacitors for energy storage[J]. Energy, 2017, 138(1):883-889. doi: 10.1016/j.energy.2017.07.022
[11]	秦斌, 张俊杰, 王欣, 等. 基于RBF网络的车载超级电容滑模控制系统[J]. 电气传动, 2018, 48(8):65-69.
	Qin Bin, Zhang Junjie, Wang Xin, et al. Sliding mode control system of vehicle supercapacitor based on RBF neural-network[J]. Electric Drive, 2018, 48(8):65-69.
[12]	余明扬, 余斌, 潘俊东, 等. CLC滤波电路参数对纹波抑制的影响[J]. 计算机仿真, 2014, 31(2):183-186.
	Yu Mingyang, Yu Bin, Pan Jundong, et al. Effects of CLC filter circuit parameters on ripple suppression[J]. Computer Simulation, 2014, 31(2):183-186.
[13]	何汀. 用于地铁制动能量吸收的超级电容储能装置研究[D]. 南京: 南京航空航天大学, 2014.
	He Ting. Research on super-capacitor-based storage system for regenerative braking energy in metro-transit systems[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2014.
[14]	蒋芹, 张轩雄. 电动汽车锂离子电池模型参数辨识和荷电状态估算[J]. 电子科技, 2020, 33(2):32-36.
	Jiang Qin, Zhang Xuanxiong.Parameter identification and state of charge estimation of lithium ion battery model for electric vehicles[J]. Electronic Science and Technology, 2020, 33(2):32-36.
[15]	Zhao J, Gao Y, Burke A F. Performance testing of supercapacitors: Important issues and uncertainties[J]. Journal of Power Sources, 2017, 36(3):327-340.
[16]	刘振烜, 易映萍, 石伟. 基于VSG的并网逆变器功率控制研究[J]. 电子科技, 2020, 33(10):6-14.
	Liu Zhenxuan, Yi Yingping, Shi Wei. Research on the power control of grid-connected inverter based on VSG[J]. Electronic Science and Technology, 2020, 33(10):6-14.
[17]	杜美君, 张伟, 谢亚莲. 基于粒子群算法的PID控制器参数优化[J]. 电子科技, 2019, 32(6):7-11.
	Du Meijun, Zhang Wei, Xie Yalian. Particle swarm optimization based PID controller parameter optimization[J]. Electronic Science and Technology, 2019, 32(6):7-11.
[18]	綦芳, 张弛, 林业. 有轨电车全线定时节能优化[J]. 机电信息, 2020(17):70-71.
	Qi Fang, Zhang Chi, Lin Ye. Timing energy saving optimization for all tram lines[J]. Mechanical and Electrical Information, 2020(17):70-71.

名称	元件	数值	单位
升降压电感	L	0.5	mH
滤波电容	CH/CL	3	mF
滤波电容内阻	CHr/CLr	1	mΩ
IGBT额定电压	IGBTH/IGBTL	3 300	V
IGBT额定电流	IGBTH/IGBTL	800	A
基波频率	PWM	20	kHz
死区时间	PWM	0.5	ms
超级电容理想容值	C	17	F
超级电容等效内阻	r	0.44	mΩ
充电限流电阻	R	1	Ω

名称	数值	单位
牵引电机功率	220	kW
最大速度	80	km·h^-1
0~40 km·h^-1加速度	1	m·s^-2
40~80 km·h^-1加速度	0.6	m·s^-2
常用制动减速度	1	m·s^-2
接触网阻抗	0.007	Ω·km^-1
钢轨阻抗	0.009	Ω·km^-1
超级电容组最大电压	800	V
超级电容组初始电压	50	V
辅助设备用电功率	86	kW