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隧道建设(中英文) ›› 2022, Vol. 42 ›› Issue (4): 621-629.DOI: 10.3973/j.issn.2096-4498.2022.04.010

• 研究与探索 • 上一篇    下一篇

基于亮度优化的绿色隧道照明模糊PID控制算法

王海英1, 毛明磊1*, 何佳2   

  1. (1. 长安大学工程机械学院, 陕西 西安〓710064 2. 陕西交通控股集团有限公司,陕西 西安〓710054)
  • 出版日期:2022-04-20 发布日期:2022-05-01
  • 作者简介:王海英(1971—),女,河北故城人,2003年毕业于长安大学,机械设计及自动化专业,博士,副教授,现从事高速公路隧道、桥梁结构健康监测与智能控制方面的研究工作。 E-mail: whying@chd.edu.cn。*通信作者: 毛明磊, E-mail: 727131332@qq.com。

A Fuzzy Packet Identifier Tunnel Lighting Control Algorithm Based on Variable Brightness Reduction Coefficient

WANG Haiying1, MAO Minglei1, *, HE Jia2   

  1. (1. School of Construction Machinery, Changan University, Xian 710064, Shaanxi, China; 2. Shaanxi Transportation Holding Group Co., Ltd., Xi′an 710054, Shaanxi, China)

  • Online:2022-04-20 Published:2022-05-01

摘要: 为解决隧道内部照明过度造成的能源浪费问题,设计了一种基于亮度折减系数K优化的隧道照明模糊PID控制算法。首先,利用Matlab软件对《公路隧道照明细则》中提出的亮度折减系数K采用线性拟合法进行优化计算,分别得到大车流量和小车流量基于实时车速的K值;接着,利用线性内插取值法计算实时车流量下K的优化取值,得到隧道内部各段实时车流量和车速下的按需照明亮度值;然后,将按需照明亮度偏差值及偏差值变化率作为输入变量,设计自适应模糊PID控制器对灯具进行调光控制,以实现隧道按需照明节能控制模式;最后,通过模拟仿真试验和现场试验证明: 基于亮度折减系数K优化后的隧道内部照明在满足照明需求的情况下,相较于传统的基于细则设定照明亮度值的控制模式,可使隧道照明耗电量降低约21.2%

关键词: 隧道照明, 节能, 亮度折减系数, 模糊控制, PID控制

Abstract:

The energy waste due to excessive lighting in a tunnel is addressed by designing a fuzzy packet identifier(PID) control algorithm for tunnel lighting based on optimizing the brightness reduction coefficient. First, using Matlab software, the brightness reduction coefficient proposed in Guidelines for Design of Lighting of Highway Tunnels 

 is optimized using the linear fitting method, obtaining the value based on realtime vehicle speed under large and small vehicle flow conditions. Second, the linear interpolation method calculates the optimal  value based on the realtime traffic flow, obtaining ondemand lighting brightness values under realtime traffic flow and vehicle speed in each tunnel section. Third, the ondemand lighting brightness deviation value and change rate are considered as input variables. An adaptive fuzzy PID controller is designed to control lamp light input variables, revealing an energy conservation control mode of tunnel lighting on demand. Finally, the simulation and field tests are conducted. The results show that under the condition of ondemand tunnel lighting, the internal tunnel lighting based on optimized brightness reduction coefficient  can reduce power consumption by approximately 21.2% compared with the traditional control mode setting, positively affecting energy conservation and emission reduction of the tunnel lighting system.

Key words: tunnel lighting, energy conservation, brightness reduction coefficient, fuzzy logic controller, packet identifier control