[1] 国务院办公厅. 新能源汽车产业发展规划(2021−2035年) [Online]: https://wap.miit.gov.cn/jgsj/ghs/zlygh/art/2022/art_158cc63ebe76470cbff2458c4328ea22.html, 2020-10-20
General Office of the State Council. New energy vehicle industry development plan (2021−2035) [Online], available: https://wap.miit.gov.cn/jgsj/ghs/zlygh/art/2022/art_158cc63ebe76470cbff2458c4328ea22.html, October 20, 2020
[2] 欧阳明高. 中国新能源汽车技术路线的回顾与展望. 见: 中国电动汽车百人会论坛. 北京, 中国: 2019.
Ouyang Ming-Gao. Review and outlook of Chinese NEV technology pathway. In: Proceedings of China EV100 Forum. Beijing, China: 2019.
[3] 中国汽车工程学会. 节能与新能源汽车技术路线图2.0. 北京: 机械工业出版社, 2021.
China Society of Automotive Engineer. Technology Roadmap for Energy Saving and New Energy Vehicles 2.0. Beijing: China Machine Press, 2021.
[4] 国家市场监督管理总局, 国家标准化管理委员会. 电动汽车能量消耗率限值, GB/T 36980-2018, 2018.
State Administration for Market Regulation, Standardization Administration of the People's Republic of China. Energy Consumption Limits for Electric Vehicles, GB/T 36980-2018, 2018.
[5] 中华人民共和国国家质量监督检验检疫总局, 中国国家标准化管理委员会. 电动汽车−能量消耗率和续驶里程−试验方法, GB/T 18386-2017, 2017.
General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China, Standardization Administration of the People's Republic of China. Electric Vehicles-Energy Consumption and Range-Test Procedures, GB/T 18386-2017, 2017.
[6] Campanari S, Manzolini G, De la Iglesia F G. Energy analysis of electric vehicles using batteries or fuel cells through well-to-wheel driving cycle simulations. Journal of Power Sources, 2009, 186(2): 464-477 doi: 10.1016/j.jpowsour.2008.09.115
[7] 卢东斌, 欧阳明高, 谷靖, 李建秋. 电动汽车永磁同步电机最优制动能量回馈控制. 中国电机工程学报, 2013, 33(3): 83-91
Lu Dong-Bin, Ouyang Ming-Gao, Gu Jing, Li Jian-Qiu. Optimal regenerative braking control for permanent magnet synchronous motors in electric vehicles. Proceedings of the CSEE, 2013, 33(3): 83-91
[8] 王耀南, 孟步敏, 申永鹏, 魏跃远, 尹颖, 易迪华, 等. 燃油增程式电动汽车动力系统关键技术综述. 中国电机工程学报, 2014, 34(27): 4629-4639
Wang Yao-Nan, Meng Bu-Min, Shen Yong-Peng, Wei Yue-Yuan, Yin Ying, Yi Di-Hua, et al. Researches on power systems of extended range electric vehicles. Proceedings of the CSEE, 2014, 34(27): 4629-4639
[9] Gantt L R. Energy Losses for Propelling and Braking Conditions of an Electric Vehicle [Master thesis], Virginia Tech, USA, 2011.
[10] Björnsson L H, Karlsson S. The potential for brake energy regeneration under Swedish conditions. Applied Energy, 2016, 168: 75-84 doi: 10.1016/j.apenergy.2016.01.051
[11] 陈虹, 郭露露, 宫洵, 高炳钊, 张琳. 智能时代的汽车控制. 自动化学报, 2020, 46(7): 1313-1332
Chen Hong, Guo Lu-Lu, Gong Xun, Gao Bing-Zhao, Zhang Lin. Automotive control in intelligent era. Acta Automatica Sinica, 2020, 46(7): 1313-1332
[12] NEXTCAR. Next-generation energy technologies for connected and automated on-road vehicles [Online], available: https://arpa-e.energy.gov/technologies/programs/nextcar, November 2, 2016
[13] 洪金龙, 高炳钊, 董世营, 程一帆, 王玉海, 陈虹. 智能网联汽车节能优化关键问题与研究进展. 中国公路学报, 2021, 34(11): 306-334
Hong Jin-Long, Gao Bing-Zhao, Dong Shi-Ying, Cheng Yi-Fan, Wang Yu-Hai, Chen Hong. Key problems and research progress of energy saving optimization for intelligent connected vehicles. China Journal of Highway and Transport, 2021, 34(11): 306-334
[14] Vahidi A, Sciarretta A. Energy saving potentials of connected and automated vehicles. Transportation Research Part C: Emerging Technologies, 2018, 95: 822-843 doi: 10.1016/j.trc.2018.09.001
[15] 郭露露, 高炳钊, 陈虹. 汽车经济性行驶优化. 中国科学: 信息科学, 2016, 46(5): 560-570 doi: 10.1360/N112015-00290
Guo Lu-Lu, Gao Bing-Zhao, Chen Hong. Optimal ecodriving control of vehicles. Scientia Sinica Informationis, 2016, 46(5): 560-570 doi: 10.1360/N112015-00290
[16] Huang G M, Yuan X F, Shi K, Liu Z X, Wu X R. A 3-D multi-object path planning method for electric vehicle considering the energy consumption and distance. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(7): 7508-7520 doi: 10.1109/TITS.2021.3071319
[17] Ozatay E, Onori S, Wollaeger J, Ozguner U, Rizzoni G, Filev D, et al. Cloud-based velocity profile optimization for everyday driving: A dynamic-programming-based solution. IEEE Transactions on Intelligent Transportation Systems, 2014, 15(6): 2491-2505 doi: 10.1109/TITS.2014.2319812
[18] Pei J Z, Su Y X, Zhang D H, Qi Y, Leng Z W. Velocity forecasts using a combined deep learning model in hybrid electric vehicles with V2V and V2I communication. Science China Technological Sciences, 2020, 63(1): 55-64 doi: 10.1007/s11431-018-9396-0
[19] He H W, Wang Y L, Han R Y, Han M, Bai Y F, Liu Q W. An improved MPC-based energy management strategy for hybrid vehicles using V2V and V2I communications. Energy, 2021, 225: Article No. 120273 doi: 10.1016/j.energy.2021.120273
[20] Kim D, Eo J S, Kim K K K. Service-oriented real-time energy-optimal regenerative braking strategy for connected and autonomous electrified vehicles. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(8): 11098-11115 doi: 10.1109/TITS.2021.3099812
[21] Xiong H Y, Tan Z R, Zhang R H, He S. A new dual axle drive optimization control strategy for electric vehicles using vehicle-to-infrastructure communications. IEEE Transactions on Industrial Informatics, 2020, 16(4): 2574-2582 doi: 10.1109/TII.2019.2944850
[22] Zhang B, Xu F G, Shen T L. MPC based energy management strategy with on-board parameter identification. In: Proceedings of the 13th Asian Control Conference (ASCC). Jeju, South Korea: IEEE, 2022. 357−362
[23] Liu R, Liu H, Han L J, He P, Zhang Y B. A multi-objective regenerative braking control strategy combining with velocity optimization for connected vehicles. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2023, 237(6): 1465-1474 doi: 10.1177/09544070221085960
[24] Du A M, Han Y Y, Zhu Z P. Review on multi-objective optimization of energy management strategy for hybrid electric vehicle integrated with traffic information. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2022, 44(3): 7914-7933 doi: 10.1080/15567036.2022.2117437
[25] Oncken J, Chen B. Real-time model predictive powertrain control for a connected plug-in hybrid electric vehicle. IEEE Transactions on Vehicular Technology, 2020, 69(8): 8420-8432 doi: 10.1109/TVT.2020.3000471