[1] 谭忠富, 王抒祥, 何洋, 等. 电动汽车节能与减排潜力计算模型[J]. 现代电力, 2013, 30(2):78-82.
[2] 伍塞特. 混合动力汽车能量管理系统研究及展望[J]. 节能, 2019, 38(10):45-48.
[3] Sciarretta A, Serrao L, Dewangan P C, et al. A control benchmark on the energy management of a plug-in hybrid electric vehicle[J]. Control Engineering Practice, 2014, 29:287-298.
[4] 余卫平, 李明高. 现代车辆新能源与节能减排技术[M]. 北京:机械工业出版社, 2013.
[5] 殷承良, 张建龙. 新能源汽车整车设计——典型车型与结构[M]. 上海:上海科学技术出版社, 2013.
[6] Mi C, M.Abul M, Gao D W. 混合动力电动汽车原理及应用前景[M]. 北京:机械工业出版社, 2013.
[7] 穆邱倩. 数据驱动的锂离子电池剩余寿命预测方法研究[D]. 西安:长安大学, 2021.
[8] 蔡艳平, 陈万, 苏延召, 等. 锂离子电池剩余寿命预测方法综述[J]. 电源技术, 2021, 45(05):678-682.
[9] 罗承东, 吕桃林, 解晶莹, 等. 电池管理系统算法综述[J]. 电源技术, 2021, 45(10):1371-1375.
[10] Li W, Fan Y, Ringbeck F, et al. Electrochemical modelbased state estimation for lithium-ion batteries with adaptive unscented Kalman filter[J]. Journal of Power Sources, 2020, 476:228534.
[11] 卜少华, 代鹏, 叶华国, 等. 基于Arrhenius方程下EV用磷酸铁锂电池寿命预测[J]. 佳木斯大学学报(自然科学版), 2021, 39(2):98-104.
[12] Tran M K, DaCosta A, Mevawalla A, et al. Comparative study of equivalent circuit models performance in four common lithium-ion batteries:LFP, NMC, LMO, NCA[J]. Batteries, 2021, 7(3):51.
[13] Li Y, Vilathgamuwa M, Farrell T, et al. A physicsbased distributed-parameter equivalent circuit model for lithium-ion batteries[J]. Electrochimica Acta, 2019, 299:451-469.
[14] 王学远, 李日康, 魏学哲, 等. 基于传荷电阻的锂离子电池剩余寿命预测研究[J]. 机械工程学报, 2021, 57(14):105-117.
[15] 陈万, 蔡艳平, 苏延召, 等. 基于改进粒子滤波的锂离子电池剩余寿命预测[J]. 中国测试, 2021, 47(7):148-153.
[16] 张之琦, 郁亚娟, 李茜, 等. 相关向量机预测电池健康状态和剩余有效寿命[J]. 电源技术, 2021, 45(3):419-423.
[17] Chen Z, Shi N, Ji Y, et al. Lithium-ion batteries remaining useful life prediction based on BLS-RVM[J]. Energy, 2021, 234:121269.
[18] 王义, 刘欣, 高德欣. 基于BiLSTM神经网络的锂电池SOH估计与RUL预测[J]. 电子测量技术, 2021, 44(20):1-5.
[19] Richardson R R, Osborne M A, Howey D A. Battery health prediction under generalized conditions using a Gaussian process transition model[J]. Journal of Energy Storage, 2019, 23:320-328.
[20] 何星, 丁有军, 宋丽君, 等. 基于加速鱼群算法的锂离子电池剩余寿命预测[J]. 兵器装备工程学报, 2022, 43(02):163-169.
[21] 刘健. 基于高斯过程回归的锂离子电池剩余寿命预测研究[D]. 上海:上海交通大学, 2019.
[22] Li L L, Liu Z F, Tseng M L, et al. Enhancing the Lithium-ion battery life predictability using a hybrid method[J]. Applied Soft Computing, 2019, 74:110-121.
[23] Feng F, Teng S, Liu K, et al. Co-estimation of lithiumion battery state of charge and state of temperature based on a hybrid electrochemical-thermal-neural-network model[J]. Journal of Power Sources, 2020, 455:227935.
[24] 肖迁, 穆云飞, 焦志鹏, 等. 基于改进LightGBM的电动汽车电池剩余使用寿命在线预测研究[J/OL]. 电工技术学报,(2022-01-04)[2022-08-27]. https://kns.cnki.net/kcms/detail/11.2188.TM.20220104.1226.004.html.
[25] Li J, Li X, He D. A directed acyclic graph network combined with CNN and LSTM for remaining useful life prediction[J]. IEEE Access, 2019, 7:75464-75475.
[26] 姚远, 陈志聪, 吴丽君, 等. 采用GRU-MC混合算法的锂离子电池RUL预测[J]. 福州大学学报(自然科学版), 2022, 50(2):169-174.
[27] Xue Z, Zhang Y, Cheng C, et al. Remaining useful life prediction of lithium-ion batteries with adaptive unscented kalman filter and optimized support vector regression[J]. Neurocomputing, 2020, 376:95-102.
[28] 郑伟彦, 吴靖, 许杰, 等. 基于RVM-PF融合算法的锂离子电池剩余使用寿命预测[J]. 浙江电力, 2021, 40(4):54-64.
[29] Sabri M F M, Danapalasingam K A, Rahmat M F. A review on hybrid electric vehicles architecture and energy management strategies[J]. Renewable and Sustainable Energy Reviews, 2016, 53:1433-1442.
[30] M. Ali A, Söffker D, Realtime application of progressive optimal search and adaptive dynamic programming in multi-source HEVs[C]//Proceedings of the ASME 2017 Dynamic Systems and Control Conference. Tysons, Virginia, USA:American Society of Mechain Engineers, 2017, 58288:V002T17A003.
[31] Du G, Zou Y, Zhang X,et al. Intelligent energy management for hybrid electric tracked vehicles using online reinforcement learning[J]. Applied Energy, 2019, 251:113388.
[32] Xiong R, Chen H, Wang C, et al. Towards a smarter hybrid energy storage system based on battery and ultracapacitor-a critical review on topology and energy management[J]. Journal of Cleaner Production, 2018, 202:1228-1240.
[33] 金传琦. 新能源混合动力汽车能量管理策略研究[J]. 交通节能与环保, 2022, 18(2):27-30.
[34] Singh K V, Bansal H O, Singh D. Feed-forward modeling and real-time implementation of an intelligent fuzzy logic-based energy management strategy in a series-parallel hybrid electric vehicle to improve fuel economy[J]. Electrical Engineering, 2020, 102(2):967-987.
[35] 万鹤高. 并联混合动力系统能量管理策略研究[D]. 邯郸:河北工程大学, 2021.
[36] 张金柱, 韩玉敏, 孙远涛, 等. 基于模糊控制的混联式混合动力汽车能量管理策略[J]. 交通科技与经济, 2019, 21(5):53-59.
[37] Zheng Y, He F, Shen X, et al. Energy control strategy of fuel cell hybrid electric vehicle based on working conditions identification by least square support vector machine[J]. Energies, 2020, 13(2):426.
[38] 马琨其. 基于粒子群-模糊控制的并联式混合动力汽车能量管理策略仿真研究[D]. 天津:河北工业大学, 2020.
[39] 杨天. 基于新型动力系统的混合动力能量控制策略仿真研究[D]. 长春:吉林大学, 2017.
[40] 刘云. 并联混合动力汽车参数匹配与优化方法研究[D]. 武汉:武汉理工大学, 2017.
[41] 赵航, 史广奎. 混合动力电动汽车技术[M]. 北京:机械工业出版社, 2017.
[42] Li T, Rizzoni G, Onori S. Optimal energy management of HEVs with consideration of battery aging[C]//Proceedings of 2014 IEEE Conference and Expo Transportation Electrification Asia-Pacific. Beijing:IEEE, 2014:1-6.
[43] 孔泽慧, 熊继芬. 基于动态规划的混合动力汽车能量管理策略研究[J]. 时代汽车, 2021, 18(17):14-15.
[44] Liu C, Wang Y, Wang L, et al. Load-adaptive real-time energy management strategy for battery/ultracapacitor hybrid energy storage system using dynamic programming optimization[J]. Journal of Power Sources, 2019, 438:227024.
[45] 庞涵泽, 王立, 袁一卿. 基于DP算法的新双模PHEV系统能量管理策略[J]. 汽车安全与节能学报, 2020, 11(2):227-235.
[46] 曾小华, 王星琦, 宋大凤, 等. 考虑电池寿命的插电式混合动力汽车能量管理优化[J]. 浙江大学学报:工学版, 2019, 53(11):2206-2214.
[47] 陈渠, 殷承良, 张建龙, 等. 基于动态规划与机器学习的插电式混合动力汽车能量管理算法研究[J]. 汽车技术, 2020, 51(10):51-57.
[48] Li X, Wang Y, Yang D, 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.
[49] 鲍宸浩. 基于电池寿命的混合动力汽车能量管理策略研究[D]. 西安:长安大学, 2020.
[50] Serrao L, Onori S, Rizzoni G. ECMS as a realization of Pontryagin's minimum principle for HEV control[C]//Proceedings of the American Control Conference. St. Louis, MO, USA:IEEE, 2009:3964-3969.
[51] Ebbesen S, Elbert P, Guzzella L. Battery state-of-health perceptive energy management for hybrid electric vehicles[J]. IEEE Transactions on Vehicular Technology, 2012, 61(7):2893-2900.
[52] Sezer V, Gokasan M, Bogosyan S. A novel ECMS and combined cost map approach for high-efficiency series hybrid electric vehicles[J]. IEEE Transactions on Vehicular Technology, 2011, 60(8):3557-3570.
[53] 李淼林. 新能源汽车技术[M]. 北京:北京大学出版社, 2020.
[54] Borhan H, Vahidi A, Phillips A M, et al. MPC-based energy management of a power-split hybrid electric vehicle[J]. IEEE Transactions on Control Systems Technology, 2012, 20(3):593-603.
[55] Borhan H, Vahidi A, Phillips A M, et al. Predictive energy management of a power-split hybrid electric vehicle[C]//Proceedings of the American Control Conference. St. Louis, MO, USA:IEEE, 2009:3970-3976.
[56] Bonab S A, Emadi A. MPC-based energy management strategy for an autonomous hybrid electric vehicle[J]. IEEE Open Journal of Industry Applications, 2020, 1:171-180.
[57] Liu X, Qin D, Wang S. Minimum energy management strategy of equivalent fuel consumption of hybrid electric vehicle based on improved global optimization equivalent factor[J]. Energies, 2019, 12(11):2076.
[58] Zhang F, Xi J, Langari R. An adaptive equivalent consumption minimization strategy for parallel hybrid electric vehicle based on fuzzy PI[C]//Proceedings of 2016 IEEE Intelligent Vehicles Symposium. Gothenburg, Sweden:IEEE, 2016:460-465.
[59] 孙芳科. 混合动力汽车瞬时最优控制策略的研究[D]. 济南:山东大学, 2018.
[60] 郭俊利. 基于工况识别的混合动力汽车能量管理策略研究[J]. 粘接, 2020, 41(1):185-188.
[61] Wu Y, Zhang Y, Li G, et al. A predictive energy management strategy for multi-mode plug-in hybrid electric vehicles based on multi neural networks[J]. Energy, 2020, 208:118366.
[62] Sun Z, Wang Y, Chen Z, et al. Min-max game based energy management strategy for fuel cell/supercapacitor hybrid electric vehicles[J]. Applied Energy, 2020, 267:115086.
[63] 耿文冉, 楼狄明, 张彤. 基于粒子群优化的混合动力汽车多目标能量管理策略[J]. 同济大学学报(自然科学版), 2020, 48(7):1030-1039.
[64] 高建树, 尹尔乐, 陈煜, 等. 基于鱼群算法的复合电源模糊能量管理策略[J]. 计算机应用与软件, 2021, 38(11):86-90.
[65] Meng D, Zhang Y, Zhou M, et al. Intelligent fuzzy energy management research for a uniaxial parallel hybrid electric vehicle[J]. Computers & Electrical Engineering, 2016, 58:447-464.
[66] 徐福国. 混合动力汽车计及电池寿命的能量管理优化控制策略研究[D]. 秦皇岛:燕山大学, 2016.
[67] 陈景夫. 面向动力电池衰减的增程式电动客车能量管理策略研究[D]. 哈尔滨:哈尔滨理工大学, 2016.
[68] Akar F, Tavlasoglu Y, Vural B. An energy management strategy for a concept battery/ultracapacitor electric vehicle with improved battery life[J]. IEEE Transactions on Transportation Electrification, 2017, 3(1):191-200.
[69] Fu Z, Zhu L, Tao F, et al. Optimization based energy management strategy for fuel cell/battery/ultracapacitor hybrid vehicle considering fuel economy and fuel cell lifespan[J]. International Journal of Hydrogen Energy, 2020, 45(15):8875-8886.
[70] 李双双. 考虑动力电池寿命衰退的PHEV能量管理控制策略研究[D]. 重庆:重庆大学, 2018.
[71] Ferahtia S, Djeroui A, Mesbahi T, et al. Optimal adaptive gain LQR-based energy management strategy for battery-supercapacitor hybrid power system[J]. Energies, 2021, 14(6):1660.
[72] 杨轶成, 丁明进, 王响成, 等. 基于超级电容的双向DC-DC变换器控制研究[J]. 电源学报, 2021, 19(4):129-139.
