图7蓄电池等效内阻
Fig.7Battery equivalent resistance
图8为蓄电池有效容量估计结果。由图可知,在此放电过程中,电池有效容量变化不大,只在放电末期略微减小;经过多次充放电循环后,电池容量会大大降低,表明此时电池健康状态(SOH)受到较大的影响。
图8蓄电池有效容量
Fig.8Battery available capacity
4 结论
本文运用双扩展卡尔曼滤波方法对VRLA蓄电池的SOC及部分参数进行估计,仿真结果表明该方法能够处理Ah-OCV方法难以解决的问题,即在较短时间内实现SOC的准确估计,并且有效抑制噪声干扰。在线估计的电池内阻和有效容量还能够实时判断蓄电池的健康状态,提高了蓄电池的可监控性,为混合动力汽车能量的合理分配和再生利用提供准确的蓄电池状态信息。
参考文献
[1] 陈清泉,孙逢春,祝嘉光.现代电动汽车技术[M].北京理工大学出版社,2002:238–245
[2] G. Plett, Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs, Part 1, Background[J]. Journal of Power Sources. 134 (2) (2004) :252–261.
[3] G. Plett, Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs, Part 2, Modeling and identification[J]. Journal of Power Sources, 134 (2) (2004) : 262–276.
[4] G. Plett, Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs, Part 3, State and parameter estimation[J]. Journal of Power Sources,134 (2) (2004) : 277–292.
[5] 夏超英,张术,孙宏涛.基于推广卡尔曼滤波算法的SOC估算策略[J].电源技术,2007,5(131):
414–417
[6] Seongjun Lee, Jonghoon Kim, Jaemoon Lee, etc. State-of-charge and capacity estimation of lithium-ion batteryusing a new open-circuit voltage versus state-of-charge[J]. Journal of Power Sources ,185 (2008):1367–1373
[7] Jaehyun Hana, Dongchul Kima, Myoungho Sunwoob. State-of-charge estimation of lead-acid batteries using anadaptive extended Kalman filter [J]. Journal of Power Sources ,188 (2009) : 606–612
[8] 赵彦玲,吴淑红. MATLAB与SIMULINK工程应用[M].电子工业出版社,2001:55–70