stefferber
The best quick charging experience at INOITY 380kW charging station [INONITY-Himmelkron](https://www.goingelectric.de/stromtankstellen/Deutschland/Himmelkron/IONITY-Euro-Rastpark-Bayreuther-Strasse-1-3/33229/) with a short interruption  [INONITY-Hohenwarsleben](https://www.goingelectric.de/stromtankstellen/Deutschland/Hohenwarsleben/IONITY-Euro-Rastpark-Zum-Raukler-1/33434/)  [INONITY-Lippetal](https://www.goingelectric.de/stromtankstellen/Deutschland/Lippetal/IONITY-Euro-Rastpark-Straengenbach-1/37655/) 
And a typical charging at my home with Mennekes 22kW here only max 7.2kW 
Added GPS logging, did some more bug fixing, and a bit more robustness. A sample time series is also included. Still this is very much happy path engineering... Ready for...
While empirical scanning through the data I found the battery energy in kWh ;-) ``` EV_RANGE_VSC_INITIAL_HV_BATT_ENERGYx100 EV_RANGE_VSC_REVISED_HV_BATT_ENERGYx100 ``` Which correlates nicely with `EV_STATE_OF_CHARGE` as you can see in the attached...
Now there is only one more mystery left: How to calculate the real charging power in kW from `EV_CHARGING_RATE_SOC_PER_HOUR` in %.
I can only guess the difference between `INITAL` and `REVISED`. Maybe it is model the ageing of the battery? If you look at the chart above there is hardly a...
Do you want me to do a formal correlation analysis for `EV_STATE_OF_CHARGE` and `EV_RANGE_VSC_INITIAL_HV_BATT_ENERGYx100`. Shouldn't be that difficult with python...
SaaS = Statistics-as-a-Service ;-) ``` print(timeseries['EV_STATE_OF_CHARGE'].corr(timeseries['EV_RANGE_VSC_INITIAL_HV_BATT_ENERGYx100'])) print(timeseries['EV_STATE_OF_CHARGE'].corr(timeseries['EV_RANGE_VSC_REVISED_HV_BATT_ENERGYx100'])) print(timeseries['EV_RANGE_VSC_INITIAL_HV_BATT_ENERGYx100'].corr(timeseries['EV_RANGE_VSC_REVISED_HV_BATT_ENERGYx100'])) ``` results in ``` 0.9955738575736692 0.995446940831017 0.9999284070411001 ``` no doubt - the data is highly correlated
... which leads to the idea of a correlation map like this https://medium.com/@sebastiannorena/finding-correlation-between-many-variables-multidimensional-dataset-with-python-5deb3f39ffb3 ... next week. Will be in the mountains the next 3 days ;-)
Correlation map is ready. Needs you and other eyes to gather insights  White spots are due to "NaN" correlation. This datasets have Zero variance and therefore correlation is not...