capacity estimation coupled with SOH estimation, Li-Ion cell

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irene giusti 2024-1-26

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评论： Athmane 2024-9-23

Goodmorning,

I'm trying to evaluate the state of health of a Li-Ion cell comparing the estimated results with the experimental data. In order to do this, I'm using the Capacity estimation block coupled with the SOH block (capacity based). I used the SOC estimation block as input for the capacity estimator and the parameters of the battery were set using Battery (table-based) block, in which I also set the capacity fade using the equation option already implemented in the block.

I'm not able to find reliable results because the capacity increases during the charging phase and decreases during the discharge, in such a way that the SOH oscillates from 1 to 0.6 or even to 0 after few cycles. Instead, using the SOH estimation based on the resistance increase I can obtain reliable results. I would like to compare the results using both methods.

I kindly ask what can be wrong in the estimation of the capacity or if the problem is in something else.

Thank You in advance,

Irene

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akshatsood 2024-2-5

The approach to estimate the State of Health (SOH) based on resistance increase is indeed viable when battery degradation primarily manifests as an increase in internal resistance. However, the challenge of scarce experimental data on resistance changes over the lifecycle makes this method less practical. Your strategy to construct a lookup table using capacity fade data is an alternative, as capacity metrics are more readily available.

The oscillation of the SOH from 1 to 0 due to the capacity estimation fluctuating between 1.5 and 8 suggests that there may be an issue with the setup or the model itself. Normally, you would expect the capacity to decrease gradually, not oscillate, as the battery degrades. The inclusion of a 'mean' block seems to be an attempt to smooth out these fluctuations, but it's crucial to consider whether this averaging has a physical basis or if it merely masks the underlying problem.

It is not typical for the estimated capacity to oscillate so widely, and it could indicate that the model or the input data is not accurately capturing the battery's behavior. This could be due to incorrect assumptions in the model, or other factors. This requires a more detailed investigation and I would share any updates I will have during the investigation.

akshatsood 2024-9-23

Hi @Athmane,

Please note that the "SOH Estimator" was introduced in the R2023b release, which is why you are encountering this issue in your current release, R2018b.

Athmane 2024-9-23

Hi @akshatsood,

Yes, I understand that. However, is it possible to create a model to estimate the SoH in version R2018b? If so, do you have a model you could suggest, or what alternatives or methods could be used?

Best regards,

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采纳的回答

akshatsood 2024-2-5

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2074641-capacity-estimation-coupled-with-soh-estimation-li-ion-cell#answer_1403031

编辑：akshatsood 2024-2-5

Hi @irene giusti,

I understand that you are observing a difference in the estimated data and experimental data. On investigating the files shared and understanding the requirements highlighted in the question, I put forward the following observations

The approach to estimate the State of Health (SOH) based on resistance increase is indeed viable when battery degradation primarily manifests as an increase in internal resistance. However, challenge of scarce experimental data on resistance changes over the lifecycle makes this method less practical. Your strategy to construct a lookup table using fade data is an alternative, as capacity metrics are more readily available.
The oscillation of the SOH from 1 to 0 due to the capacity estimation fluctuating between 1.5 and 8 suggests that there may be an issue with the setup or the model itself. Normally, you would expect capacity to decrease gradually, not oscillate, as the battery degrades. The inclusion of a 'mean' block seems to be an attempt to smooth out these fluctuations, but it is crucial to consider whether this averaging has a physical ground or if it merely masks the symptoms of an underlying problem that needs to be addressed.
It is not typical for the estimated capacity to oscillate so widely, and it could indicate that the model or the input data is not accurately capturing the battery behavior. This could be due to incorrect assumptions in the model. This requires a more detailed investigation and I would share any updates I will have.

Further, I would request you to go through the following MATLAB Answer, it seems to address a similar problem pertaining to SOH. Do let me know if it helps in resolving the problem.

https://www.mathworks.com/matlabcentral/answers/2051562-why-soh-decreases-in-few-cycles

I hope this helps.

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irene giusti 2024-2-6

Thank You for the answer, I will investigate in order to find the error in the battery model settings

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