Abstract：Conventional control strategies of on-board energy storage systems (OESSs) based on catenary voltage or artificial intelligence algorithms can achieve a certain level of regenerative braking energy recovery. However, they ignore the charging and discharging characteristics of energy storage elements and fail to provide an explicit analytical solution to the corresponding control parameters due to the complicated model. On the other hand, according to the characteristics of the supercapacitor, its power is at odds with the amount of energy it can absorb. If the initial voltage of the supercapacitor is low, the energy it can absorb would be large while the charging power would be low, and vice versa. Therefore, it is an issue worth studying how to set a reasonable initial voltage and charging/discharging current to balance the power and absorbable energy of a supercapacitor so that the best regenerative braking energy recovery effect can be achieved. The OESS is charged when the urban rail train is braking and discharged when the train is in traction. The power profile of the train was divided into two parts in this paper: "braking" and "traction", and the charging and discharging processes of the OESS were studied, respectively. When the train was braking, the OESS should be charged as much as possible to ensure the optimal energy-saving effect. By applying the area-equivalent principle, the problem of maximizing the charge of OESS could be transformed into a mathematical problem of maximizing the area enclosed by the braking power curve of the train and the power curve of the supercapacitor. When the initial voltage and charging current of the supercapacitor varied, the shape enclosed by the two power curves was also different. Therefore, the enclosed area with various shapes was modeled with respect to different initial voltages and charging currents. Finally, the optimal initial voltage and charging current corresponding to the largest enclosed area were picked out, and the energy-saving effect of the OESS was the best in this case. As for the discharging process, the design principle of the OESS discharge strategy was to ensure that the voltage of the supercapacitor at the end of the train traction reached the optimal initial voltage of the braking stage obtained above. According to the area-equivalent principle, this goal could be achieved by making the area enclosed by the two power curves equal to the discharged energy of the supercapacitor during train traction. Furthermore, to maximize the "valley-filling" effect of the OESS, the charging time of the OESS was set equal to the traction time of the train to obtain the optimal discharge current. In this way, the maximum height of the area difference between the train traction power curve and the supercapacitor power curve could be cut down; in other words, the peak power absorbed by the train from the traction network could be reduced. Finally, a case study was conducted based on the single-train operation scenario to verify the effectiveness of the proposed control strategy. The result shows that, compared with the traditional voltage-based double-loop PI control strategy, the control strategy proposed in this paper can further improve the charging and discharging capacity of OESS and thus have a more significant energy-saving effect.
米佳雨, 杨中平, 钟志宏, 林飞, 邵一晨. 基于等效面积法的车载制动能量回收装置控制策略[J]. 电工技术学报, 2025, 40(3): 975-986.
Mi Jiayu, Yang Zhongping, Zhong Zhihong, Lin Fei, Shao Yichen. Optimal Control of On-Board Supercapacitor Energy Storage Systems for Regenerative Braking Energy Recovery Based on Area-Equivalent Principle. Transactions of China Electrotechnical Society, 2025, 40(3): 975-986.
[1] 中国城市轨道交通协会. 城市轨道交通2022年度统计和分析报告[EB/OL]. (2023-03-31)[2024-01-01]. https://www.camet.org.cn/tjxx/11944. [2] 陈冲, 贾利民, 赵天宇, 等. 去碳化导向的轨道交通与新能源融合发展—形态模式、解决方案和使/赋能技术[J]. 电工技术学报, 2023, 38(12): 3321-3337. Chen Chong, Jia Limin, Zhao Tianyu, et al.Decarbonization-oriented rail transportation and renewable energy integration development-configurations, solutions, and enabling/empowering technologies[J]. Transactions of China Electrotechnical Society, 2023, 38(12): 3321-3337. [3] 程鹏, 刘文泉, 陈冲, 等. 面向电气化铁路牵引供电的光伏发电分相电流控制策略[J]. 电力系统自动化, 2022, 46(19): 145-153. Cheng Peng, Liu Wenquan, Chen Chong, et al.Individual phase current control strategy of photovoltaic power generation for traction power supply of electrified railway[J]. Automation of Electric Power Systems, 2022, 46(19): 145-153. [4] 赵荣华, 庞涛, 米佳雨, 等. 替代制动电阻的车载储能系统容量配置研究[J]. 机电工程技术, 2023, 52(9): 269-273. Zhao Ronghua, Pang Tao, Mi Jiayu, et al.Study on capacity configuration of on-board energy storage systems substituting braking resistors[J]. Mechanical & Electrical Engineering Technology, 2023, 52(9): 269-273. [5] 林锦杰, 李勇, 胡斯佳, 等. 计及再生制动能量的铁路潮流控制器功率柔性分配方法[J]. 电工技术学报, 2023, 38(22): 6121-6132. Lin Jinjie, Li Yong, Hu Sijia, et al.Flexible power assignment method for railway power flow controller considering regenerative braking energy[J]. Transactions of China Electrotechnical Society, 2023, 38(22): 6121-6132. [6] 钟志宏, 李炎, 米佳雨, 等. 基于牵引网电压和空载电压的多储能系统区间能量管理策略[J]. 电工技术学报, 2024, 39(15): 4583-4598. Zhong Zhihong, Li Yan, Mi Jiayu, et al.Interval energy management strategy for multiple energy storage systems based on traction network voltage and no-load voltage[J]. Transactions of China Electrotechnical Society, 2024, 39(15): 4583-4598. [7] 陈艳波, 刘宇翔, 田昊欣, 等. 基于广义目标级联法的多牵引变电站光伏-储能协同规划配置[J]. 电工技术学报, 2024, 39(15): 4599-4612. Chen Yanbo, Liu Yuxiang, Tian Haoxin, et al.Collaborative planning and configuration of photovoltaic and energy storage in multiple traction substations based on generalized analytical target cascading method[J]. Transactions of China Electrotechnical Society, 2024, 39(15): 4599-4612. [8] 刘宇嫣. 城市轨道交通地面式混合储能系统自适应能量管理策略与容量配置研究[D]. 北京: 北京交通大学, 2022. Liu Yuyan.Adaptive energy management and capacity configuration of stationary hybrid energy storage system in urban rail transit[D]. Beijing: Beijing Jiaotong University, 2022. [9] 李欣, 卢景涛, 肖林润, 等. 高速铁路列车长大坡道混合储能系统容量优化配置[J]. 电工技术学报, 2023, 38(20): 5645-5660. Li Xin, Lu Jingtao, Xiao Linrun, et al.Capacity optimization configuration of hybrid energy storage system for long steep slope of high-speed railway[J]. Transactions of China Electrotechnical Society, 2023, 38(20): 5645-5660. [10] 金勇, 黄先进, 石春珉, 等. 城市轨道交通地面储能技术应用综述[J]. 电工技术学报, 2024, 39(15): 4568-4582, 4642. Jin Yong, Huang Xianjin, Shi Chunmin, et al.Review on wayside energy storage technology for urban rail transit[J]. Transactions of China Electrotechnical Society, 2024, 39(15): 4568-4582, 4642. [11] Meishner F, Sauer D U.Wayside energy recovery systems in DC urban railway grids[J]. eTransportation, 2019, 1: 100001. [12] Mi Jiayu, Yang Zhongping, Zhong Zhihong, et al.Optimal sizing of on-board and wayside energy storage systems for braking energy recovery[C]//2022 IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC Asia-Pacific), Haining, China, 2022: 1-6. [13] Khodaparastan M, Mohamed A A, Brandauer W.Recuperation of regenerative braking energy in electric rail transit systems[J]. IEEE Transactions on Intelligent Transportation Systems, 2019, 20(8): 2831-2847. [14] 王虎高, 屈海洋, 陈中杰. 储能电源应用于地铁车辆应急牵引的设计研究[J]. 电力机车与城轨车辆, 2016, 39(1): 50-53. Wang Hugao, Qu Haiyang, Chen Zhongjie.Design and research on energy storage power supply used on metro vehicle emergency traction[J]. Electric Locomotives & Mass Transit Vehicles, 2016, 39(1): 50-53. [15] 赵坤, 王椹榕, 王德伟, 等. 车载超级电容储能系统间接电流控制策略[J]. 电工技术学报, 2011, 26(9): 124-129. Zhao Kun, Wang Shenrong, Wang Dewei, et al.Indirect current control strategy of on-board supercapacitor energy storage system of railway vehicle[J]. Transactions of China Electrotechnical Society, 2011, 26(9): 124-129. [16] Di Pasquale A, Fedele E, Iannuzzi D, et al.Centralised control strategy for an urban rail network in the presence of onboard storage systems[C]//2023 AEIT International Annual Conference (AEIT), Rome, Italy, 2023: 1-6. [17] Wu Chaoxian, Lu Shaofeng, Tian Zhongbei, et al. Energy-efficient train control with onboard energy storage systems considering stochastic regenerative braking energy[J]. IEEE Transactions on Transportation Electrification, 2024, PP(99): 1. [18] Liu Wei, Xu Jiaxuan, Tang Jingkun.Study on control strategy of urban rail train with on-board regenerative braking energy storage system[C]//IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, Beijing, China, 2017: 3924-3929. [19] Talla J, Streiť L, Peroutka Z, et al.Fuzzy energy management strategy for tram with supercapacitors[C]//IECON 2015-41st Annual Conference of the IEEE Industrial Electronics Society, Yokohama, Japan, 2015: 3963-3968. [20] Wang Xin, Luo Yingbing, Qin Bin, et al.Power allocation strategy for urban rail HESS based on deep reinforcement learning sequential decision optimization[J]. IEEE Transactions on Transportation Electrification, 2023, 9(2): 2693-2710. [21] 何晔, 胡彩凤, 吴能峰, 等. 地铁车辆牵引仿真计算[J]. 铁道机车车辆, 2015, 35(6): 63-68. He Ye, Hu Caifeng, Wu Nengfeng, et al.Simulation calculations of metro tractions[J]. Railway Locomotive & Car, 2015, 35(6): 63-68. [22] 杨中平, 林飞. 储能技术在地面式再生制动能量吸收和利用装置中的应用[J]. 都市快轨交通, 2021, 34(6): 1-8. Yang Zhongping, Lin Fei.Application of energy storage technology in stationary regenerative braking energy absorption and utilization devices[J]. Urban Rapid Rail Transit, 2021, 34(6): 1-8. [23] 周强, 王金全, 杨波. 超级电容器:性能优越的储能器件[J]. 电气技术, 2006, 7(6): 64-68. Zhou Qiang, Wang Jinquan, Yang Bo.Supercapacitor: excellent energy storage element[J]. Electrical Engineering, 2006, 7(6): 64-68. [24] 诸斐琴. 城市轨道交通地面式超级电容储能系统自适应协调控制与容量配置综合优化研究[D]. 北京: 北京交通大学, 2020. Zhu Feiqin.Research on adaptive coordinated control and comprehensive optimization of capacity allocation of ground-based supercapacitor energy storage system in urban rail transit[D]. Beijing: Beijing Jiaotong University, 2020.
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