能耗优化控制的研究综述
Research Review on Energy Consumption Optimization Control
DOI: 10.12677/se.2026.162006, PDF,    科研立项经费支持
作者: 贺 琛, 王加东：江麓机电集团有限公司车辆电器公司，湖南 湘潭；李 明*, 王研文：湖南科技大学信息与电气工程学院，湖南 湘潭
关键词: 能源；节能；能耗优化；最优控制；综述；Energy； Energy Conservation； Energy Consumption Optimization； Optimal Control； Review
摘要: 能源危机是当今人类面临最严峻的挑战之一，节能降耗是解决能源危机的重要途径。对于大能耗工业对象与工业过程或系统，能耗优化控制(Energy-Optimization Control, EOC)是实现节能降耗的重要手段。本文从控制理论与工程角度出发，简要回顾了能耗优化控制理论与工程应用的发展，综述了近年来能耗优化控制理论研究和应用领域发展的新动向，分析了现有理论和技术所存在的局限性，并指出能耗优化控制理论研究与工程应用研究将重点放在面向多时间尺度扰动的EOC鲁棒控制策略上，以建立融入能耗指标的经典控制系统性能评价体系。
Abstract: Energy crisis is one of the most severe challenges facing humanity today, and energy conservation and consumption reduction are important approaches to addressing it. For high-energy-consuming industrial objects, industrial processes or systems, Energy-Optimization Control (EOC) serves as a key means to achieve energy saving and consumption reduction. This paper, from the perspective of control theory and engineering, briefly reviews the development of energy consumption optimization control theory and its engineering applications. It summarizes recent new trends in theoretical research and application development in this field. It also analyzes the limitations of existing theories and technologies. Furthermore, it points out that research in energy consumption optimization control theory and its engineering applications will focus on EOC robust control strategies for multi-timescale disturbances, with the aim of establishing a performance evaluation system for classical control systems that incorporates energy consumption indicators.
文章引用：贺琛, 王加东, 李明, 王研文. 能耗优化控制的研究综述[J]. 可持续能源, 2026, 16(2): 53-62. https://doi.org/10.12677/se.2026.162006

参考文献

[1] 胡中楫. 控制与能源[J]. 浙江大学学报(工学版), 1981(2): 57-64.
[2] 李伟. 探究我国能源利用效率的影响因素[J]. 经济视野, 2014(2): 276.
[3] 胡寿松. 自动控制原理[M]. 第5版. 北京: 科学出版社, 2007: 543.
[4] 胡中楫. 最小能耗控制及其应用[J]. 制造业自动化, 1982(4): 10-13.
[5] 任兴权. 近代控制理论在电力拖动系统中的应用[J]. 冶金自动化, 1985(4): 33-39.
[6] Selvaraj, D.E., Karthik, C.R., Arun, R., Geethadevi, S. and Ganesan, J. (2014) Energy Efficient Three Phase Squirrel Cage Induction Motor Fed AC Drives. International Journal of Science and Engineering Applications, 3, 18-21. [Google Scholar] [CrossRef] 
[7] 童调生. 考虑电枢电感的电力拖动最小能耗控制及奇异解算法的研究[J]. 自动化学报, 1988(3): 199-206.
[8] 任兴权, 田扬. 电力拖动能耗最小状态反馈闭环最优控制系统[J]. 鞍钢自动化, 1992(3): 1-6.
[9] 任兴权. 最优控制理论在电力拖动系统中应用——电力拖动最优控制[J]. 控制工程, 1994(4): 1-7.
[10] 任兴权. 直流拖动系统位置最优控制及准确定位[J]. 冶金自动化, 1982(3): 24-30.
[11] Shreelakshmi, M.P. and Agarwal, V. (2018) Trajectory Optimization for Loss Minimization in Induction Motor Fed Elevator Systems. IEEE Transactions on Power Electronics, 33, 5160-5170. [Google Scholar] [CrossRef] 
[12] 王鉴光. 泵站最优节能控制[J]. 石油钻采工艺, 1995(3): 80-84.
[13] 刘家春, 吴鹰. 能耗最小法确定泵站经济运行方案[J]. 水泵技术, 2005(2): 39-41.
[14] 曾励, 朱派龙, 黄民双, 等. 以耗能最小为指标优化设计液压伺服马达[J]. 大众用电, 1994(2): 28-31.
[15] 魏武, 蔡钊雄, 邓高燕. 基于能耗目标优化的多足爬墙机器人足力控制研究[J]. 中国机械工程, 2012, 23(9): 1099-1104.
[16] 张尚星, 朱学军, 泉照之. 关节驱动系统非线性摩擦最小能耗分析[J]. 微计算机信息, 2010, 26(8): 157-158.
[17] 张奇峰, 张艾群. 基于能源消耗最小的自治水下机器人-机械手系统协调运动研究[J]. 机器人, 2006, 28(4): 444-447.
[18] 王宏健, 王琳琳, 潘立鑫. 水下机器人近水面横摇与能耗控制[C]//中国自动化学会控制理论专业委员会. 中国自动化学会控制理论专业委员会D卷. 哈尔滨: 哈尔滨工程大学自动化学院; 呼和浩特: 内蒙古工业大学信息工程学院; 北京: 中国空间技术研究院北京控制工程研究所, 2011: 25-30.
[19] Sarkar, M., Nandy, S. and Shome, S.N. (2015) Energy Efficient Trajectory Tracking Controller for Underwater Applications: Arobust Approach. Aquatic Procedia, 4, 571-578. [Google Scholar] [CrossRef] 
[20] 汪洪洲, 施呜歧. 机床电机节能控制器原理及优越性[J]. 节能技术, 1986(5): 11-16.
[21] 王守鹏. 电动机的节能运行分析[J]. 华东科技, 2013(2): 278, 280.
[22] 王宏健, 王琳琳, 潘立鑫. 水下机器人近水面横摇与能耗控制[C]//中国自动化学会控制理论专业委员会. 中国自动化学会控制理论专业委员会D卷. 哈尔滨: 哈尔滨工程大学自动化学院; 呼和浩特: 内蒙古工业大学信息工程学院; 北京: 中国空间技术研究院北京控制工程研究所, 2011: 25-30.
[23] Chen, K.Y., Huang, M.S. and Fung, R.F. (2013) Adaptive Minimum-Energy Tracking Control for the Mechatronic Elevator System. IEEE Transactions on Control Systems Technology, 25, 1790-1799.
[24] 钟斌, 韩致信, 张秀秀. 机械手的近最小时间-能耗控制[J]. 机械与电子, 2012(5): 75-77.
[25] Snider, D.R. (1992) A Control for a Crank Shear That Minimizes the RMS Current. IEEE Transactions on Industry Applications, 28, 1309-1313. [Google Scholar] [CrossRef] 
[26] Halevi, Y., Carpanzano, E. and Montalbano, G. (2014) Minimum Energy Control of Redundant Linear Manipulators. Journal of Dynamic Systems, Measurement, and Control, 136, 562-576. [Google Scholar] [CrossRef] 
[27] 邱夏陶, 韩小良. 加热炉最低能耗控制模型的研究[J]. 工业炉, 1990(1): 44-47.
[28] 梁道君, 郑金吾. 燃煤热水锅炉节能优化控制研究[J]. 节能, 1999(2): 5-9.
[29] 王鉴光. 工业锅炉热效率自寻优计算机控制系统[J]. 化工自动化及仪表, 1994(3): 31-35.
[30] 杜佳璐, 林叶锦. 加热炉最小能耗优化控制策略的研究[J]. 自动化与仪器仪表, 2000(2): 9-11.
[31] 齐昕, 任佳仕, 石向阳, 等. 具有低开关频率的感应电机无传感器控制[J]. 工程科学学报, 2024, 46(3): 491-502.
[32] Hajian, M., Arab Markadeh, G.R., Soltani, J. and Hoseinnia, S. (2009) Energy Optimized Sliding-Mode Control of Sensorless Induction Motor Drives. Energy Conversion and Management, 50, 2296-2306. [Google Scholar] [CrossRef] 
[33] 王锋, 潘莹月, 林立松, 等. 感应电机预测功率控制器设计与调优策略[J]. 电气工程学报, 2023, 18(1): 24-31.
[34] 刘鹏. 感应电机固定时间预定性能位置跟踪优化控制[J]. 制造业自动化, 2025, 47(7): 108-120.
[35] Albalawi, H., Zaid, S.A., El-Shimy, M.E. and Kassem, A.M. (2023) Ant Colony Optimized Controller for Fast Direct Torque Control of Induction Motor. Sustainability, 15, Article 3740. [Google Scholar] [CrossRef] 
[36] Bertoluzzo, M., Buja, G. and Menis, R. (2006) Direct Torque Control of an Induction Motor Using a Single Current Sensor. IEEE Transactions on Industrial Electronics, 53, 778-784. [Google Scholar] [CrossRef] 
[37] Ben Salem, F., Almousa, M.T. and Derbel, N. (2024) Direct Torque Control with Space Vector Modulation (DTC-SVM) with Adaptive Fractional-Order Sliding Mode: A Path Towards Improved Electric Vehicle Propulsion. World Electric Vehicle Journal, 15, Article 563. [Google Scholar] [CrossRef] 
[38] Rodríguez, J., Pontt, J., Silva, C., Huerta, R. and Miranda, H. (2004) Simple Direct Torque Control of Induction Machine Using Space Vector Modulation. Electronics Letters, 40, 412-413. [Google Scholar] [CrossRef] 
[39] 郭新峰, 孟春岩. 汽车发动机节能优化控制仿真与研究[J]. 计算机仿真, 2014, 31(12): 160-163.
[40] Cabezas Rebolledo, A.A. and Valenzuela, M.A. (2015) Expected Savings Using Loss-Minimizing Flux on IM Drives—Part I: Optimum Flux and Power Savings for Minimum Losses. IEEE Transactions on Industry Applications, 51, 1408-1416. [Google Scholar] [CrossRef] 
[41] 林歆悠, 孙冬野. 基于ECMS混联式混合动力客车工况识别控制策略[J]. 湖南大学学报: 自然科学版, 2012, 39(10): 43-49.
[42] Chen, J., He, H., Wang, Y., Quan, S., Zhang, Z., Wei, Z., et al. (2024) Research on Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles Based on Improved Dynamic Programming and Air Supply Optimization. Energy, 300, Article 131567. [Google Scholar] [CrossRef] 
[43] Fang, Y., Fan, C., Ye, Y. and Chen, Y. (2003) Application of Stochastic Method to Optimum Design of Energy-Efficient Induction Motors with a Target of LCC. Journal of Zhejiang University-SCIENCE A, 4, 270-275. [Google Scholar] [CrossRef] 
[44] Kim, D.H. (2007) GA-PSO Based Vector Control of Indirect Three Phase Induction Motor. Applied Soft Computing, 7, 601-611. [Google Scholar] [CrossRef] 
[45] Kim, D.H. and Hirota, K. (2008) Vector Control for Loss Minimization of Induction Motor Using GA-PSO. Applied Soft Computing, 8, 1692-1702. [Google Scholar] [CrossRef] 
[46] Pryymak, B., Moreno-Eguilaz, J.M. and Peracaula, J. (2006) Neural Network Flux Optimization Using a Model of Losses in Induction Motor Drives. Mathematics and Computers in Simulation, 71, 290-298. [Google Scholar] [CrossRef] 
[47] Tang, W., Wang, Y., Jiao, X. and Ren, L. (2023) Hierarchical Energy Management Strategy Based on Adaptive Dynamic Programming for Hybrid Electric Vehicles in Car-Following Scenarios. Energy, 265, Article 126264. [Google Scholar] [CrossRef] 
[48] Zhang, L., Liu, J. and Wen, X. (2005) A New Fuzzy Logic Based Search Control for Efficiency Optimization of Induction Motor Drives. 2005 International Power Engineering Conference, Singapore, 29 November 2005-2 December 2005, 1-526. [Google Scholar] [CrossRef] 
[49] 张立伟. 电动汽车用异步电机系统效率优化控制研究[D]: [博士学位论文]. 北京: 中国科学院研究生院(电工研究所), 2006.
[50] Sahwal, C.P., Sengupta, S. and Dinh, T.Q. (2024) Advanced Equivalent Consumption Minimization Strategy for Fuel Cell Hybrid Electric Vehicles. Journal of Cleaner Production, 437, Article 140366. [Google Scholar] [CrossRef] 
[51] Yao, D., Lu, X., Chao, X., Zhang, Y., Shen, J., Zeng, F., et al. (2023) Adaptive Equivalent Fuel Consumption Minimization Based Energy Management Strategy for Extended-Range Electric Vehicle. Sustainability, 15, Article 4607. [Google Scholar] [CrossRef] 
[52] Onori, S., Serrao, L. and Rizzoni, G. (2010) Adaptive Equivalent Consumption Minimization Strategy for Hybrid Electric Vehicles. ASME 2010 Dynamic Systems and Control Conference, Volume 1, Cambridge, 12-15 September 2010, 499-505. [Google Scholar] [CrossRef] 
[53] 曾小华, 王庆年, 王伟华. 混合动力汽车能耗最优数学建模与仿真[J]. 系统仿真学报, 2007, 19(18): 4309-4311.
[54] 刘昌盛, 何清华, 龚俊, 等. 液压挖掘机混合动力系统节能特性及试验研究[J]. 湖南大学学报(自然科学版), 2015, 42(8): 40-46.
[55] 金立生, 赵丁选, 黄运华, 等. 液压挖掘机节能用油门模糊控制器的开发研究[J]. 中国公路学报, 2004, 17(1): 119-122.
[56] 高峰, 冯培恩. 挖掘机载荷自适应节能控制策略[J]. 同济大学学报, 2001(9): 1036-1040.
[57] 何清华, 郝鹏, 常毅华. 基于功率协调控制的液压挖掘机节能系统研究[J]. 机械科学与技术, 2007, 26(2): 188-191.
[58] 张强. 电动轮矿用自卸车节能技术研究[J]. 矿用汽车, 2011(1): 17-20.
[59] 邓熙. 浅谈电动轮矿用自卸车节能技术[J]. 中国机械, 2014(5): 57.
[60] 李洪亮, 樊平. 基于超级电容器的矿用电动轮自卸车再生制动的研究[J]. 煤矿机械, 2013, 34(3): 61-63.
[61] 李浩. 架线式电动轮自卸车再生制动储能系统研究[D]: [硕士学位论文]. 成都: 西南交通大学, 2014.
[62] Graciola, C.L., Goedtel, A., Castoldi, M.F., Souza, W.A., Nunes, E.A., Santos, T.H., et al. (2025) Comparison between Predictive and Scalar Control Strategies for Minimizing Losses in Induction Motors. Systems Science & Control Engineering, 13, Article 2481942. [Google Scholar] [CrossRef] 
[63] Liu, J.L., Pan, S., Cui, Y. and Liu, Y.Q. (2026) Comparative Analysis of Algorithmic Paradigms for HVAC Control across Diverse Building Systems: A Systematic Review. IOP Conference Series: Earth and Environmental Science, 1587, Article 012042. [Google Scholar] [CrossRef] 
[64] Boukoberine, M.N., Zia, M.F., Berghout, T. and Benbouzid, M. (2025) Reinforcement Learning-Based Energy Management for Hybrid Electric Vehicles: A Comprehensive Up-to-Date Review on Methods, Challenges, and Research Gaps. Energy and AI, 21, Article 100514. [Google Scholar] [CrossRef] 
[65] Zhang, C. (2024) Cyber-Physical Merged Learning for Online Optimisation of Multi-Mode Hybrid Vehicles with Diverse Time-Scale Objectives. Ph.D. Thesis, University of Birmingham.

为你推荐