基于健康因子的锂电池电量估算
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摘要
锂电池电量的准确估算是延长电池寿命,安全使用锂电池的关键。传统估计算法过度依赖于准确的电池模型,忽略了电池老化程度和环境温度的影响,使估算偏差越来越大。为此,在安时积分法的基础上,考虑老化程度及环境温度的影响,提出了一种基于健康因子的电池电量估算方法。对一款磷酸铁锂电池进行数百次的充放电实验,实时记录其内阻和电压变化。实验数据和MATLAB仿真结果表明,该估算方法具有很高的估算精度,其估算值最大绝对误差小于2.5%,结果验证了该方法的有效性。
It is extremely important to accurately estimate the battery remaining capacity, which is the key to the lifetime and safe use of the battery. Conventional estimation methods rely on accurate battery model overly and ignore the influence of the battery aging degree and the environment temperature, thus the estimation bias is more and more larger. Therefore, based on amp-hour integral method and considering the influence of battery aging degree and environment temperature, a new method with health factors to estimate the remaining capacity of battery was proposed. Hundreds of times of charge and discharge were carried out for a lithium-iron phosphate battery. The changes of internal resistance and real-time voltage were recorded. The experimental data and MATLAB simulation results show that the proposed method has high estimation accuracy,and the maximum absolute error of estimation value is under 2.5%. The results demonstrate that the method is very effective.
It is extremely important to accurately estimate the battery remaining capacity, which is the key to the lifetime and safe use of the battery. Conventional estimation methods rely on accurate battery model overly and ignore the influence of the battery aging degree and the environment temperature, thus the estimation bias is more and more larger. Therefore, based on amp-hour integral method and considering the influence of battery aging degree and environment temperature, a new method with health factors to estimate the remaining capacity of battery was proposed. Hundreds of times of charge and discharge were carried out for a lithium-iron phosphate battery. The changes of internal resistance and real-time voltage were recorded. The experimental data and MATLAB simulation results show that the proposed method has high estimation accuracy,and the maximum absolute error of estimation value is under 2.5%. The results demonstrate that the method is very effective.
引文
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[7]鲁照权,吴巨峰,鲁博翰.一种光电互补供电系统蓄电池剩余电量的准确估算方法:中国,201510040644.8[P].2015-10-04.
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[10]刘泽元,王友仁,陈则王,等.基于改进EKF的飞机蓄电池在线SOC估计方法[J].电子测量技术,2015,38(7):119-123.
[2]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.
[3] AUNG H,LOW K S,GOH S T. State-of-charge estimation of lithium-ion battery using square root spherical unscented Kalman filter(Sqrt-UKFST)in nanosatellite[J]. IEEE Transactions on Power Electronics,2014,30(9):4774-4783.
[4]项宇,刘春光,苏建强,等.基于BP神经网络的动力电池SOC预测模型与优化[J].电源技术,2013,37(6):963-965.
[5] XU J,MI CH T,CAO B G,et al. The state of charge estimation of lithium-ion batteries based on a proportional-integral observer[J].IEEE Transactions on Vehicular Technology,2014,63(4):1614-1621.
[6] TANG X P,WANG Y J,CHEN Z H. A method for state-of-charge estimation of LiFePO4batteries based on a dual-circuit state observer[J]. Journal of Power Sources,2015,296:23-29.
[7]鲁照权,吴巨峰,鲁博翰.一种光电互补供电系统蓄电池剩余电量的准确估算方法:中国,201510040644.8[P].2015-10-04.
[8]林春景,李斌,常国峰,等.不同温度下磷酸铁锂电池内阻特性实验研究[J].电源技术,2015,39(1):22-25.
[9] WATRIN N,BLUNIER B,MIRAOUI A.Review of adaptive systems for lithium batteries state-of-charge and state-of-health estimation[C]//Proceedings of 2012 IEEE Transportation Electrification Conference and Expo(ITEC). Dearborn, MI, USA:IEEE, 2012:1-6.
[10]刘泽元,王友仁,陈则王,等.基于改进EKF的飞机蓄电池在线SOC估计方法[J].电子测量技术,2015,38(7):119-123.