大型伺服冲压线中的主驱动电机功率通常达到MW量级,由于需要驱动滑块频繁加减速,容易造成巨大的电网冲击和电能损失。为了保证大型伺服冲压线的平稳高效运行,能量管理系统是不可或缺的重要功能模块。该文针对采用飞轮储能的大型伺服冲压线的能量管理方法展开研究,基于梯度投影算法和B-样条曲线速度规划,提出了一种半周期飞轮转速自适应规划算法。该算法在引入约数周期正弦扰动时表现出较好的抗干扰能力,避免了飞轮转速突变的问题。利用Simulink建立了伺服冲压线的理论仿真模型,仿真结果表明:所提出的飞轮转速自适应规划算法能够显著改善进线功率和母线电压的波动,为大型伺服冲压线的能量管理提供了一种有效方法。
The main drive motors in large servo press lines often draw megawatts of power with frequent acceleration and deceleration of the slider, which strongly affects the power grid and power usage. Thus, effective energy management is indispensable to ensure smooth, efficient operation of large servo press lines. This paper studies how to improve the energy management of large servo press lines using flywheel energy storage. A gradient project algorithm and B-spline speed planning are used to develop a half-period flywheel speed adaptive planning algorithm. This algorithm better optimizes the power usage by introducing an approximately sinusoidal disturbance which avoids sudden changes in the flywheel speed. Finally, the servo press line model is analyzed theoretically in Simulink. The simulation results show that the half-period adaptive flywheel speed planning algorithm significantly improves the incoming line power and bus voltage fluctuations as an effective method for energy management of large servo press lines.
[1] HALICIOGLU R, CANAN DULGER L, TOLGA BOZDANA A. Modeling, design, and implementation of a servo press for metal-forming application[J]. The International Journal of Advanced Manufacturing Technology, 2017, 91(5-8):2689-2700.
[2] 戴绍祥, 孙立岩. 伺服冲压自动化生产工艺及装置浅析[J]. 锻压装备与制造技术, 2018, 53(1):15-18. DAI S X, SUN L Y. Analysis of automatic production process and device for servo stamping[J]. China Metalforming Equipment and Manufacturing Technology, 2018, 53(1):15-18. (in Chinese)
[3] 常超, 史阳. 基于超级电容储能的直流风电机组协调控制[J]. 现代电力, 2017, 34(6):65-70. CHANG C, SHI Y. Coordinated control of DC wind power generator based on super capacitor energy storage[J]. Modern Electric Power, 2017, 34(6):65-70. (in Chinese)
[4] 汤凡, 刘天琪, 李兴源. 用于风电场功率控制的飞轮储能系统仿真研究[J]. 电网与清洁能源, 2010, 26(2):63-68. TANG F, LIU T Q, LI X Y. Simulation of flywheel energy storage system for power control in wind farms[J]. Power System and Clean Energy, 2010, 26(2):63-68. (in Chinese)
[5] 王业斌. 电动汽车电池能量管理策略研究[J]. 汽车文摘, 2019(5):58-62. WANG Y B. Research on battery energy management strategies for electric vehicles[J]. Automotive Digest, 2019(5):58-62. (in Chinese)
[6] 周晓东, 郭为忠. 伺服压力机能量管理系统的研究[J]. 传动技术, 2018, 32(4):31-36. ZHOU X D, GUO W Z. Research on energy management system of servo press[J]. Drive System Technique, 2018, 32(4):31-36. (in Chinese)
[7] 黄宇淇, 姜新建, 邱阿瑞. 飞轮储能能量回馈控制方法[J]. 清华大学学报(自然科学版), 2008, 48(7):1085-1088. HUANG Y Q, JIANG X J, QIU A R. Energy feedback control for flywheel energy storage system[J]. Journal of Tsinghua University (Science and Technology), 2008, 48(7):1085-1088. (in Chinese)
[8] 李伟. 风力发电系统中飞轮储能装置的控制分析[J]. 中国设备工程, 2018(20):103-104. LI W. Control analysis of flywheel energy storage device in wind power generation system[J]. China Plant Engineering, 2018(20):103-104. (in Chinese)
[9] 梁晓. 非最小相位系统的最小方差自适应控制[J]. 兵工自动化, 2004(6):54-55. LIANG X. Adaptive control of minimum square error for non-minimum phase system[J]. Ordnance Industry Automation, 2004(6):54-55. (in Chinese)
[10] 任宏彬, 王丽梅. 基于极点配置的数控机床磁悬浮系统自适应同步控制[J]. 电气技术, 2010(2):16-19. REN H B, WANG L M. Adaptive synchronous control for suspension system of numerically controlled machine tool based on pole-placement[J]. Electrical Engineering, 2010(2):16-19. (in Chinese)
[11] 刘丽影, 李雪松, 张建成. 飞轮储能系统发电运行控制技术的研究[J]. 华北电力技术, 2007(9):8-10. LIU L Y, LI X S, ZHANG J C. Research on flywheel energy storage system on generator controlling technology[J]. North China Electric Power, 2007(9):8-10. (in Chinese)
[12] 王彬彬, 张飞, 王京. 基于递推最小二乘法的无模型自适应厚度控制[J]. 冶金自动化, 2015, 39(3):34-38. WANG B B, ZHANG F, WANG J. Model-free adaptive thickness control based on recursive least squares[J]. Metallurgical Industry Automation, 2015, 39(3):34-38. (in Chinese)
[13] 宫立达, 李智敏. 基于单神经元自适应PID的普通车床智能控制研究[J]. 机电产品开发与创新, 2017, 30(3):108-109. GONG L D, LI Z M. Ordinary lathe intelligent control research based on single neuron adaptive PID[J]. Development and Innovation of Machinery and Electrical Products, 2017, 30(3):108-109. (in Chinese)
[14] 陈运华, 高凤岐, 王广龙. 基于自适应模糊算法的无刷直流电机控制系统研究[J]. 微电机, 2012, 45(12):31-35. CHEN Y H, GAO F Q, WANG G L. Study on control cystem of crushless DC motor based on adaptive fuzzy algorithm[J]. Micromotors, 2012, 45(12):31-35. (in Chinese)
[15] 侯忠生, 于百胜, 黄文虎. 非线性系统参数估计的投影算法[J]. 哈尔滨工业大学学报, 2000(3):25-28. HOU Z S, YU B S, HUANG W H. The projection algorithm for estimation of nonlinear system parameter[J]. Journal of Harbin Institute of Technology, 2000(3):25-28. (in Chinese)