矿用储能电池荷电状态精确估计方法
|
摘要
针对基于安时积分法的矿用储能电池荷电状态估计易产生累计误差的问题,提出一种基于改进安时积分法的矿用储能电池荷电状态精确估计方法。该方法引入温度校正系数、老化程度校正系数和充放电倍率校正系数,通过校正电池容量实现电池荷电状态精确估计;在电池荷电状态为0~15%,90%~100%时,用电池端电压代替开路电压,对改进安时积分法所得结果进行实时校正。实验结果表明,该方法可提高矿用储能电池荷电状态估计精度,估计误差基本控制在±3%以内。
For the problem that accumulative error was easy to occur in estimation for state of charge(SOC)of mine-used energy storage battery based on ampere-hour integration method,an accurate estimation method for SOC of mine-used energy storage battery based on improved ampere-hour integration method was put forward.In the method,temperature correction coefficient,aging degree correction coefficient and charging-discharging ratio correction coefficient are introduced to correct battery capacity,so as to realize accurate estimation of battery SOC.Battery terminal voltage is used to replace open circuit voltage when battery SOC is from 0 to 15%or from 90%to 100%,then the estimation results obtained by the improved ampere-hour integration method are corrected real-timely.The experimental results show that the method can improve estimation precision of SOC of mine-used energy storage battery,and the estimation error is within±3%.
For the problem that accumulative error was easy to occur in estimation for state of charge(SOC)of mine-used energy storage battery based on ampere-hour integration method,an accurate estimation method for SOC of mine-used energy storage battery based on improved ampere-hour integration method was put forward.In the method,temperature correction coefficient,aging degree correction coefficient and charging-discharging ratio correction coefficient are introduced to correct battery capacity,so as to realize accurate estimation of battery SOC.Battery terminal voltage is used to replace open circuit voltage when battery SOC is from 0 to 15%or from 90%to 100%,then the estimation results obtained by the improved ampere-hour integration method are corrected real-timely.The experimental results show that the method can improve estimation precision of SOC of mine-used energy storage battery,and the estimation error is within±3%.
引文
[1]孙继平.煤矿井下紧急避险与应急救援技术[J].工矿自动化,2014,40(1):1-4.SUN Jiping.Technologies of emergency refuge and rescue used in underground coal mine[J].Industry and Mine Automation,2014,40(1):1-4.
[2]孙继平.煤矿井下避难硐室与救生舱关键技术研究[J].煤炭学报,2011,36(5):713-717.SUN Jiping.The key technologies of the refuge chamber and rescue capsule in the underground coal mine[J].Journal of China Coal Society,2011,36(5):713-717.
[3]孙继平.煤矿井下紧急避险系统研究[J].煤炭科学技术,2011,39(1):69-71.SUN Jiping.Research on emergency refuge system in underground mine[J].Coal Science and Technology,2011,39(1):69-71.
[4]欧阳佳佳.储能电池管理系统研究[D].杭州:浙江大学,2016.
[5]童广浙.磷酸铁锂储能电池管理系统设计[D].南宁:广西大学,2013.
[6]华周发,李静.电动汽车动力电池SOC估算方法综述[J].电源技术,2013,37(9):1686-1689.HUA Zhoufa,LI Jing.Summary of methods for state of charge estimation of EV power batteries[J].Chinese Journal of Power Sources,2013,37(9):1686-1689.
[7] HE Hongwen,XIONG Rui,PENG Jiankun.Realtime estimation of battery state-of-charge with unscented Kalman filter and RTOSμCOS-II platfrom[J].Applied Energy,2016,162:1410-1418.
[8]张金龙,佟微,漆汉宏,等.平方根采样点卡尔曼滤波在磷酸铁锂电池组荷电状态估算中的应用[J].中国电机工程学报,2016,36(22):6246-6253.ZHANG Jinlong,TONG Wei,QI Hanhong,et al.Application of square root sigma point Kalman filter to SOC estimation of LiFePO4 battery pack[J].Proceedings of the CSEE,2016,36(22):6246-6253.
[9]尹安东,张万兴,赵韩,等.基于神经网络的磷酸铁锂电池SOC预测研究[J].电子测量与仪器学报,2011,25(5):433-437.YIN Andong,ZHANG Wanxing,ZHAO Han,et al.Research on estimation for SOC of LiFePO4 Li-ion battery based on neural network[J].Journal of Electronic Measurement and Instrument,2011,25(5):433-437.
[10]于海芳,逯仁贵,朱春波,等.基于安时法的镍氢电池SOC估计误差校正[J].电工技术学报,2012,27(6):12-18.YU Haifang,LU Rengui,ZHU Chunbo,et al.State of charge estimation calibration for Ni-MH battery based on ampere-hour method[J].Transactions of China Electrotechnical Society,2012,27(6):12-18.
[11]林成涛,陈全世,王军平,等.用改进的安时计量法估计电动汽车动力电池SOC[J].清华大学学报(自然科学版),2006,46(2):247-251.LIN Chengtao,CHEN Quanshi,WANG Junping,et al.Improved AH counting method for state of charge estimation of electric vehicle batteries[J].Journal ofTsinghuaUniversity(Scienceand Technology),2006,46(2):247-251.
[12]李哲,卢兰光,欧阳明高.提高安时积分法估算电池SOC精度的方法比较[J].清华大学学报(自然科学版),2010,50(8):1293-1296.LI Zhe, LULanguang, OUYANGMinggao.Comparison of methods for improving SOC estimation accuracythroughanampere-hourintegeration approach[J].Journal of Tsinghua University(Science and Technology),2010,50(8):1293-1296.
[13]鲍慧,于洋.基于安时积分法的电池SOC估算误差校正[J].计算机仿真,2013,30(11):148-151.BAO Hui,YU Yang.State of charge estimation calibration based on ampere-hour method[J].Computer Simulation,2013,30(11):148-151.
[14]马俊,龚国庆,陈勇,等.不同工况对锂离子电池SOC预估精度的影响[J].电源技术,2016,40(12):2335-2338.MA Jun,GONG Guoqing,CHEN Yong,et al.Influence of different driving cycle on precision of SOC estimation[J].Chinese Journal of Power Sources,2016,40(12):2335-2338.
[15] HE Yao,LIU Xingtao,ZHANG Chenbin.A new model for state of charge(SOC)estimation for highpower Li-ion batteries[J].Applied Energy,2013,101:808-810.
[2]孙继平.煤矿井下避难硐室与救生舱关键技术研究[J].煤炭学报,2011,36(5):713-717.SUN Jiping.The key technologies of the refuge chamber and rescue capsule in the underground coal mine[J].Journal of China Coal Society,2011,36(5):713-717.
[3]孙继平.煤矿井下紧急避险系统研究[J].煤炭科学技术,2011,39(1):69-71.SUN Jiping.Research on emergency refuge system in underground mine[J].Coal Science and Technology,2011,39(1):69-71.
[4]欧阳佳佳.储能电池管理系统研究[D].杭州:浙江大学,2016.
[5]童广浙.磷酸铁锂储能电池管理系统设计[D].南宁:广西大学,2013.
[6]华周发,李静.电动汽车动力电池SOC估算方法综述[J].电源技术,2013,37(9):1686-1689.HUA Zhoufa,LI Jing.Summary of methods for state of charge estimation of EV power batteries[J].Chinese Journal of Power Sources,2013,37(9):1686-1689.
[7] HE Hongwen,XIONG Rui,PENG Jiankun.Realtime estimation of battery state-of-charge with unscented Kalman filter and RTOSμCOS-II platfrom[J].Applied Energy,2016,162:1410-1418.
[8]张金龙,佟微,漆汉宏,等.平方根采样点卡尔曼滤波在磷酸铁锂电池组荷电状态估算中的应用[J].中国电机工程学报,2016,36(22):6246-6253.ZHANG Jinlong,TONG Wei,QI Hanhong,et al.Application of square root sigma point Kalman filter to SOC estimation of LiFePO4 battery pack[J].Proceedings of the CSEE,2016,36(22):6246-6253.
[9]尹安东,张万兴,赵韩,等.基于神经网络的磷酸铁锂电池SOC预测研究[J].电子测量与仪器学报,2011,25(5):433-437.YIN Andong,ZHANG Wanxing,ZHAO Han,et al.Research on estimation for SOC of LiFePO4 Li-ion battery based on neural network[J].Journal of Electronic Measurement and Instrument,2011,25(5):433-437.
[10]于海芳,逯仁贵,朱春波,等.基于安时法的镍氢电池SOC估计误差校正[J].电工技术学报,2012,27(6):12-18.YU Haifang,LU Rengui,ZHU Chunbo,et al.State of charge estimation calibration for Ni-MH battery based on ampere-hour method[J].Transactions of China Electrotechnical Society,2012,27(6):12-18.
[11]林成涛,陈全世,王军平,等.用改进的安时计量法估计电动汽车动力电池SOC[J].清华大学学报(自然科学版),2006,46(2):247-251.LIN Chengtao,CHEN Quanshi,WANG Junping,et al.Improved AH counting method for state of charge estimation of electric vehicle batteries[J].Journal ofTsinghuaUniversity(Scienceand Technology),2006,46(2):247-251.
[12]李哲,卢兰光,欧阳明高.提高安时积分法估算电池SOC精度的方法比较[J].清华大学学报(自然科学版),2010,50(8):1293-1296.LI Zhe, LULanguang, OUYANGMinggao.Comparison of methods for improving SOC estimation accuracythroughanampere-hourintegeration approach[J].Journal of Tsinghua University(Science and Technology),2010,50(8):1293-1296.
[13]鲍慧,于洋.基于安时积分法的电池SOC估算误差校正[J].计算机仿真,2013,30(11):148-151.BAO Hui,YU Yang.State of charge estimation calibration based on ampere-hour method[J].Computer Simulation,2013,30(11):148-151.
[14]马俊,龚国庆,陈勇,等.不同工况对锂离子电池SOC预估精度的影响[J].电源技术,2016,40(12):2335-2338.MA Jun,GONG Guoqing,CHEN Yong,et al.Influence of different driving cycle on precision of SOC estimation[J].Chinese Journal of Power Sources,2016,40(12):2335-2338.
[15] HE Yao,LIU Xingtao,ZHANG Chenbin.A new model for state of charge(SOC)estimation for highpower Li-ion batteries[J].Applied Energy,2013,101:808-810.