一种无人机锂电池剩余电量估计方法
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摘要
为了准确得到多旋翼无人机锂聚合物电池在不同的工作状态下的剩余电量,以电流模拟积分法为电量统计基础,将电池温度、充放电电流等因素对锂聚合物电池电量的影响等效为电池内阻的变化,利用卡尔曼滤波估计法对锂聚合物电池的剩余电量进行估计。实验发现这种方法可自适应电池老化引起的电量衰减,并能有效地补偿充放电过程电流积分误差的累积,通过选择合理的参数可得到不同工作状态下电池较为真实的剩余电量。从而为全自主控制多旋翼无人机系统提供可靠的剩余电量参考。
To accurately get the remaining capacity of the multi-rotor unmanned aerial vehicle lithium polymer battery under different working conditions, based on current analog integration for power statistics, the effect of battery temperature and current on the remaining capacity of lithium polymer battery was equaled for battery internal resistance change. The remaining capacity of lithium polymer battery was estimated by using the Kalman filter method. It's found that this method can be adaptive for power attenuation caused by aging, and can effectively compensate current integral error accumulation. Choosing reasonable parameters can get more real remaining capacity under different working conditions. This method can provide more reliable remaining capacity reference for autonomous control multi-rotor unmanned aerial vehicle system.
To accurately get the remaining capacity of the multi-rotor unmanned aerial vehicle lithium polymer battery under different working conditions, based on current analog integration for power statistics, the effect of battery temperature and current on the remaining capacity of lithium polymer battery was equaled for battery internal resistance change. The remaining capacity of lithium polymer battery was estimated by using the Kalman filter method. It's found that this method can be adaptive for power attenuation caused by aging, and can effectively compensate current integral error accumulation. Choosing reasonable parameters can get more real remaining capacity under different working conditions. This method can provide more reliable remaining capacity reference for autonomous control multi-rotor unmanned aerial vehicle system.
引文
[1]谢朝香,任杰伟,杨凯伦,等.无人机用锂离子蓄电池组性能测试与分析[J].上海航天,2014,31(6):67-72.
[2]曹金亮,张春光,陈修强,等.锂聚合物电池的发展、应用及前景[J].电源技术,2014,38(1):168-169.
[3]程艳青,高明煜.基于卡尔曼滤波的电动汽车剩余电量估计[J].杭州电子科技大学学报,2009,29(3):4-7.
[4]陈岚,刘皓喆,张谦,等.修正参数的安时法估算锂离子电池剩余电量[J].上海应用技术学院学报,2014,14(4):310-314.
[5]冯飞,逯仁贵,朱春波.一种锂离子电池低温SOC估计算法[J].电工技术学报,2014,29(7):53-58.
[6]戴海峰,孙泽昌,魏学哲.利用双卡尔曼滤波算法估计电动汽车用锂离子动力电池的内部状态[J].机械工程学报,2009,45(6):95-101.
[7]柏庆文.基于无味卡尔曼滤波的电动汽车动力电池SOC估计[D].长春:吉林大学,2013.
[2]曹金亮,张春光,陈修强,等.锂聚合物电池的发展、应用及前景[J].电源技术,2014,38(1):168-169.
[3]程艳青,高明煜.基于卡尔曼滤波的电动汽车剩余电量估计[J].杭州电子科技大学学报,2009,29(3):4-7.
[4]陈岚,刘皓喆,张谦,等.修正参数的安时法估算锂离子电池剩余电量[J].上海应用技术学院学报,2014,14(4):310-314.
[5]冯飞,逯仁贵,朱春波.一种锂离子电池低温SOC估计算法[J].电工技术学报,2014,29(7):53-58.
[6]戴海峰,孙泽昌,魏学哲.利用双卡尔曼滤波算法估计电动汽车用锂离子动力电池的内部状态[J].机械工程学报,2009,45(6):95-101.
[7]柏庆文.基于无味卡尔曼滤波的电动汽车动力电池SOC估计[D].长春:吉林大学,2013.