|Table of Contents|

Adaptive optimal energy management strategy of fuel cell vehicle by considering fuel cell performance degradation(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2022年01期
Page:
190-204
Research Field:
载运工具运用工程
Publishing date:

Info

Title:
Adaptive optimal energy management strategy of fuel cell vehicle by considering fuel cell performance degradation
Author(s):
WANG Ya-xiong1; 2;  YU Qing-gang1;  WANG Xue-chao2; 3;  SUN Feng-chun2
(1. School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, Fujian, China; 2.National Engineering Research Center of Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China; 3. China Automotive Engineering Research Institute Co., Ltd., Chongqing 401122, China)
Keywords:
automotive engineering;  fuel cell vehicle;  energy management strategy;  Pontryagin's minimum principle;  fuel cell performance degradation;  adaptive optimization
PACS:
U469.72
DOI:
10.19818/j.cnki.1671-1637.2022.01.016
Abstract:
To improve system efficiency and reduce the risk of working life reduction caused by the adverse operation conditions of fuel cell, an adaptive Pontryagin's minimum principle(PMP)energy management strategy with the fuel cell performance degradation consideration was proposed for the fuel cell/supercapacitor hybrid power system in the city bus. The off-line PMP energy distributions of the fuel cell/supercapacitor hybrid power system in five different driving conditions were analyzed, and the relation between the initial value of the costate variable and the difference of state variable of the energy management system, i.e., the state-of-charge difference of the supercapacitor, between the beginning and the end, was obtained. The corresponding relation between the initial value of the costate for online PMP and state-of-charge could be interpolated. Integrating with the normal equation of the PMP, the instant costate variable was obtained, and thus the adaptively updating costate variable in the online PMP leading to keep up state-of-charge could be formulated. Choosing the fuel cell performance degradation, the power change rate, number of start-stop, and maximal power of the fuel cell as the constraints of the energy management system, the fuel cell power change rate was further formulated as a penalty term in the cost function of the adaptive PMP to meet the energy management constraints as well as achieve better fuel economy. The controller hardware-in-the-loop(HIL)simulation test was carried out to validate the practical efficacy of the proposed energy management strategy.Research results show that, under the bus condition SC03 and New York City cycle condition(NYCC)that are different from the costate variable formulation used typical operation conditions, the adaptive PMP energy management can make the terminal state-of-charge approach the target value, and compared with the off-line PMP, the losses of fuel economy are only 1.27% and 0.94%, respectively. Under the China bus driving cycle(CBDC)comprehensive test condition that is different from the operation conditions used for the costate determination and cost function weighting adjustment, the proposed adaptive optimal energy management strategy can implement the energy distributions of fuel cell and supercapacitor under the provided constraints, and the fuel economy can keep up 90.76% compared with the off-line optimization. Under the CBDC and NurembergR36 test conditions, the average errors between HIL and numerical simulations are less than 5%. Consequently, the proposed adaptive optimal energy management strategy considering the performance degradation of fuel cell can implement the high operation of the hybrid power system with the potential of a long working life. 9 tabs, 13 figs, 29 refs.

References:

[1] 王 骞,李顶根,苗华春.基于模糊逻辑控制的燃料电池汽车能量管理控制策略研究[J].汽车工程,2019,41(12):1347-1355.WANG Qian, LI Ding-gen, MIAO Hua-chun. Research on energy management strategy of fuel cell vehicle based on fuzzy logic control[J]. Automotive Engineering, 2019, 41(12): 1347-1355.(in Chinese)
[2] TENG Teng, ZHANG Xin, DONG Han, et al. A comprehensive review of energy management optimization strategies for fuel cell passenger vehicle[J]. International Journal of Hydrogen Energy, 2020, 45(39): 20293-20303.
[3] LYU Xue-qin, QU Yan, WANG Yu-dong, et al. A comprehensive review on hybrid power system for PEMFC-HEV: issues and strategies[J]. Energy Conversion and Management, 2018, 171: 1273-1291.
[4] SULAIMAN N, HANNAN M A, MOHAMED A, et al. A review on energy management system for fuel cell hybrid electric vehicle: issues and challenges[J]. Renewable and Sustainable Energy Reviews, 2015, 52: 802-814.
[5] ZHANG Ri-dong, TAO Ji-li, ZHOU Hui-yu. Fuzzy optimal energy management for fuel cell and supercapacitor systems using neural network based driving pattern recognition[J]. IEEE Transactions on Fuzzy Systems, 2019, 27(1): 45-57.
[6] WANG Yu-jie, SUN Zhen-dong, CHEN Zong-hai. Energy management strategy for battery/supercapacitor/fuel cell hybrid source vehicles based on finite state machine[J]. Applied Energy, 2019, 254: 113707.
[7] MEBARKI N, REKIOUA T, MOKRANI Z, et al. PEM fuel cell/battery storage system supplying electric vehicle[J]. International Journal of Hydrogen Energy, 2016, 41(45): 20993-21005.
[8] 雷 霄,戴朝华,陈维荣,等.基于ADVISOR的燃料电池混合动力机车建模与仿真[J].电源技术,2015,39(12):2643-2646.LEI Xiao, DAI Chao-hua, CHEN Wei-rong, et al. Dynamic modeling and simulation of fuel cell hybrid locomotives based on ADVISOR[J]. Chinese Journal of Power Sources, 2015, 39(12): 2643-2646.(in Chinese)
[9] LYU Xue-qin, WU Yin-bo, LIAN Jie, et al. Energy management of hybrid electric vehicles: a review of energy optimization of fuel cell hybrid power system based on genetic algorithm[J]. Energy Conversion and Management, 2020, 205: 112474.
[10] ZHOU Wei, YANG Lin, CAI Yi-shan, et al. Dynamic programming for new energy vehicles based on their work modes Part Ⅱ: fuel cell electric vehicles[J]. Journal of Power Sources, 2018, 407: 92-104.
[11] SHI De-hua, LIU Sheng, CAI Ying-feng, et al. Pontryagin's minimum principle based fuzzy adaptive energy management for hybrid electric vehicle using real-time traffic information[J]. Applied Energy, 2021, 286: 116467.
[12] LI Xi-yun, WANG Yu-jie, YANG Duo, et al. Adaptive energy management strategy for fuel cell/battery hybrid vehicles using Pontryagin's minimal principle[J]. Journal of Power Sources, 2019, 440: 227105.
[13] SONG Ke, WANG Xiao-di, LI Fei-qiang, et al. Pontryagin's minimum principle-based real-time energy management strategy for fuel cell hybrid electric vehicle considering both fuel economy and power source durability[J]. Energy, 2020, 205: 118064.
[14] GAO Hui-zhong, WANG Zhi-jie, YIN Shao-ping, et al. Adaptive real-time optimal energy management strategy based on equivalent factors optimization for hybrid fuel cell system[J]. International Journal of Hydrogen Energy, 2021, 46(5): 4329-4338.
[15] ZHOU Yang, LI Han, RAVEY A, et al. An integrated predictive energy management for light-duty range-extended plug-in fuel cell electric vehicle[J]. Journal of Power Sources, 2020, 451: 227780.
[16] XU Liang-fei, OUYANG Ming-gao, LI Jian-qiu, et al. Application of Pontryagin's minimal principle to the energy management strategy of plugin fuel cell electric vehicles[J]. International Journal of Hydrogen Energy, 2013, 38(24): 10104-10115.
[17] 王 哲,谢 怡,臧鹏飞,等.基于极小值原理的燃料电池客车能量管理策略[J].吉林大学学报(工学版),2020,50(1):36-43.WANG Zhe, XIE Yi, ZANG Peng-fei, et al. Energy management strategy of fuel cell bus based on Pontryagin's minimum principle[J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(1): 36-43.(in Chinese)
[18] 杜泽学.车用燃料电池关键材料技术研发应用进展[J].化工进展,2021,40(1):6-20.DU Ze-xue. Application advances of manufacturing technology for key materials of vehicle fuel cell stack[J]. Chemical Industry and Engineering Progress, 2021, 40(1): 6-20.(in Chinese)
[19] SONG Ke, CHEN Huan, WEN Pei-min, et al. A comprehensive evaluation framework to evaluate energy management strategies of fuel cell electric vehicles[J]. Electrochimica Acta, 2018, 292: 960-973.
[20] WANG Y X, OU K, KIM Y B. Power source protection method for hybrid polymer electrolyte membrane fuel cell/lithium-ion battery system[J]. Renewable Energy, 2017, 111: 381-391.
[21] LIU Yong-gang, LIU Jun-jun, ZHANG Yuan-jian, et al. Rule learning based energy management strategy of fuel cell hybrid vehicles considering multi-objective optimization[J]. Energy, 2020, 207: 118212.
[22] AHMADI S, BATHAEE S M T, HOSSEINPOUR A H. Improving fuel economy and performance of a fuel-cell hybrid electric vehicle(fuel-cell, battery, and ultra-capacitor)using optimized energy management strategy[J]. Energy Conversion and Management, 2018, 160: 74-84.
[23] LI Tian-yu, LIU Hui-ying, WANG Hui, et al. Hierarchical predictive control-based economic energy management for fuel cell hybrid construction vehicles[J]. Energy, 2020, 198: 117327.
[24] CARIGNANO M G, COSTA-CASTELLÓ R, RODA V, et al. Energy management strategy for fuel cell-supercapacitor hybrid vehicles based on prediction of energy demand[J]. Journal of Power Sources, 2017, 360: 419-433.
[25] 苏 波,李 奇,王天宏,等.城轨交通用燃料电池/超级电容混合动力系统瞬时等效最小氢耗硬件在环方法研究[J].中国电机工程学报,2019,39(19):5714-5723,5899.SU Bo, LI Qi, WANG Tian-hong, et al. Research on hardware-in-the-loop methods for instantaneous equivalent minimum hydrogen consumption of fuel cell/ultracapacitor hybrid systems for urban rail transit[J]. Proceedings of the CSEE, 2019, 39(19): 5714-5723, 5899.(in Chinese)
[26] PEI Pu-cheng, CHANG Qian-fei, TANG Tian. A quick evaluating method for automotive fuel cell lifetime[J]. International Journal of Hydrogen Energy, 2008, 33(14): 3829-3836.
[27] 余 意.频繁启停对质子交换膜燃料电池堆性能的影响[J].电池,2015,45(2):74-77.YU Yi. Performance decay of PEMFC stack after startup-shutdown cycles[J]. Battery Bimonthly, 2015, 45(2): 74-77.(in Chinese)
[28] 王 诚,王树博,张剑波,等.车用燃料电池耐久性研究[J].化学进展,2015,27(4):424-435.WANG Cheng, WANG Shu-bo, ZHANG Jian-bo, et al. The durability research on the proton exchange membrane fuel cell for automobile application[J]. Progress in Chemistry, 2015, 27(4): 424-435.(in Chinese)
[29] 张新丰,杨代军,周 拓.车用燃料电池系统的性能衰退机理及影响因素分析[J].汽车安全与节能学报,2012,3(3):276-286.ZHANG Xin-feng, YANG Dai-jun, ZHOU Tuo. Review on degradation mechanism and in fluence factors for vehicular fuel cell systems[J]. Journal of Automotive Safety and Energy, 2012, 3(3): 276-286.(in Chinese)

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Last Update: 2022-03-20