基于独立太阳能供电的照明系统控制及蓄电池状态监测研究
发布时间：2018-08-17 19:35
【摘要】：在太阳能的利用中,太阳能照明占有重要的位置,特别是太阳能路灯产业发展很快。但在太阳能路灯控制系统中,还存在着许多需要亟待解决的问题,主要是它的能源平衡问题和供电的稳定性和智能性控制,因此控制器性能和管理储能策略一直是研究的重点。本文依托成都金堂国际铁人三项赛场太阳能路灯照明系统,对基于独立太阳能供电的照明系统控制及蓄电池状态监测进行了研究。 本文首先对太阳能电池板特性和铅酸蓄电池特性和充放电方式进行了分析。在研究了太阳能电池的最大功率点跟踪问题和蓄电池优化充放电策略问题之后,设计出了一种基于单片机AT89S52的具有自适应功能的控制器,用以改进充放电控制方法。并采用反向传播(BP)神经网络算法预测阀控密封式铅酸蓄电池(VRLA)的剩余容量放电控制法的新思路,对蓄电池工作状态进行实时监测,提高了系统的工作效率,有效延长蓄电池的使用寿命。 系统采用PWM控制的三阶段充电方法,同时采用最大功率跟踪算法,增大光伏电池阵列的输出；放电时基于BP神经网络算法,预测荷电状态,调整LED灯功率大小和工作时长,并且完成了与上位机的串口通信,通过LabVIEW人机交互界面实时监测蓄电池工作状态。 为了验证研究的有效性,在实验室条件下对各模块硬件电路搭建了硬件平台,并利用C语言编写了单片机的控制程序和相应算法,通过实验结果,证明研究结论正确,实现了预期的功能。 最后对控制器系统主要功能进行测试,并对测试结果做了分析,系统能够满足实际应用的要求。
[Abstract]:Solar lighting plays an important role in the utilization of solar energy, especially the development of solar street lamp industry. However, there are still many problems to be solved in the solar streetlight control system, mainly the energy balance and the stability and intelligent control of the power supply. Therefore, the performance of the controller and the management of energy storage strategy have been the focus of research. In this paper, based on the solar lighting system of Chengdu Jintang International Triathlon, the control of the lighting system based on independent solar power supply and the monitoring of battery status are studied. In this paper, the characteristics of solar panels, lead acid batteries and charge-discharge modes are analyzed. After studying the problem of maximum power point tracking of solar cells and the optimal charging and discharging strategy of batteries, a controller with adaptive function based on single chip computer (AT89S52) is designed to improve the charging and discharging control method. A new idea of predicting the residual capacity discharge control method of valve-controlled sealed lead-acid battery (VRLA) by using the back-propagation (BP) neural network algorithm is presented. The real-time monitoring of the battery working state is carried out, and the working efficiency of the system is improved. Effectively prolong the service life of battery. The system adopts the three-stage charging method controlled by PWM and the maximum power tracking algorithm to increase the output of the photovoltaic cell array, and the discharge is based on BP neural network algorithm to predict the charged state, adjust the power size and the working time of the LED lamp. The serial port communication with the host computer is completed, and the storage battery working state is monitored by the LabVIEW man-machine interface. In order to verify the validity of the research, the hardware platform of each module hardware circuit is built under the condition of laboratory, and the control program and corresponding algorithm of single chip computer are compiled with C language. The experimental results show that the research conclusion is correct. The expected function is realized. Finally, the main functions of the controller system are tested, and the test results are analyzed. The system can meet the requirements of practical application.
【学位授予单位】：西南石油大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM912;TM914.4
本文编号：2188676
[Abstract]:Solar lighting plays an important role in the utilization of solar energy, especially the development of solar street lamp industry. However, there are still many problems to be solved in the solar streetlight control system, mainly the energy balance and the stability and intelligent control of the power supply. Therefore, the performance of the controller and the management of energy storage strategy have been the focus of research. In this paper, based on the solar lighting system of Chengdu Jintang International Triathlon, the control of the lighting system based on independent solar power supply and the monitoring of battery status are studied. In this paper, the characteristics of solar panels, lead acid batteries and charge-discharge modes are analyzed. After studying the problem of maximum power point tracking of solar cells and the optimal charging and discharging strategy of batteries, a controller with adaptive function based on single chip computer (AT89S52) is designed to improve the charging and discharging control method. A new idea of predicting the residual capacity discharge control method of valve-controlled sealed lead-acid battery (VRLA) by using the back-propagation (BP) neural network algorithm is presented. The real-time monitoring of the battery working state is carried out, and the working efficiency of the system is improved. Effectively prolong the service life of battery. The system adopts the three-stage charging method controlled by PWM and the maximum power tracking algorithm to increase the output of the photovoltaic cell array, and the discharge is based on BP neural network algorithm to predict the charged state, adjust the power size and the working time of the LED lamp. The serial port communication with the host computer is completed, and the storage battery working state is monitored by the LabVIEW man-machine interface. In order to verify the validity of the research, the hardware platform of each module hardware circuit is built under the condition of laboratory, and the control program and corresponding algorithm of single chip computer are compiled with C language. The experimental results show that the research conclusion is correct. The expected function is realized. Finally, the main functions of the controller system are tested, and the test results are analyzed. The system can meet the requirements of practical application.
【学位授予单位】：西南石油大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM912;TM914.4
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