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为什么使用状态方程预估得到的soc为SoC_real? #12
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状态方程表示了电池模型,这里的预设是模型可以(近似地)表示电池行为。所以仿真过程把模型的输出,即状态方程的输出,(近似)看做电池的实际输出。然后再将模型的输出加上噪声,作为实际观测值,输入到估计算法,这样来仿真不同算法的估计结果。 因此,这个仿真只是验证的是:默认电池模型近似能力满足要求的情况下,不同算法的有效性。 更严谨的做法是,使用实际的电池观测值,而不是模型仿真(加噪声)值作为算法输入。不过这是有两个问题需要考虑:
这也是我用模型输出作为电池输出的原因。这样的话过程噪声可以直接在模型里设定,卡尔曼算法中只需要与设定保持一致即可。而模型的soc仿真值就可以看做真实值提供参考。 |
how to identify process noise for a real battery sir |
作者的噪声可能是测量出来的吧,现在我在做的东西没有可以测量的途径,也还在想有什么其他的途径可以确定。 |
Short answer is I have no idea. I just preset the process noise in the model and use the same value during simulation. |
Thanks Alterwl I too took a similar approach then. But I it still is boggling my mind on how to do it. I tried taking some battery test in uni lab as my battery was a generic one and didn't have any data online, but it also didn't work. |
程序中貌似认定通过状态空间方程预估得到的soc为真实值,且在AH、EKF、UKF的Error计算中使用SoC_real作为基准值。
请问这一做法的依据是什么?
如果通过状态空间方程预估得到的soc为真实值,那么为什么需要AH、EKF、UKF一系列方法呢?
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