Samsung INR21700 30T 3Ah Li-ion Battery Data
Bibliographic record
Abstract
The included tests were performed at McMaster University in Hamilton, Ontario, Canada by Dr. Phillip Kollmeyer (phillip.kollmeyer@gmail.com). If this data is utilized for any purpose, it should be appropriately referenced. See the Readme file for more details. A new 3Ah Samsung 3.0T cell was tested in an 8 cu.ft. thermal chamber with a 75amp, 5 volt Digatron Firing Circuits Universal Battery Tester channel with a voltage and current accuracy of 0.1% of full scale. /*************************************************/ A series of tests were performed at six different temperatures, and the battery was charged after each test at 1C rate to 4.2V, 10mA cut off charge current, at battery temperature of 25degC The tests were performed as follows: 1. Four pulse discharge HPPC test (1, 2, 6, and 12C discharge and 0.5, 1, 2, and 4C charge, with reduced values at lower temperatures) performed at 100, 95, 90, 80, 70..., 20, 15, 10, 5, 2.5 % SOC. ("..._HPPC.mat") 2. C/20 Discharge and Charge test. ("..._C20DisCh.mat") 3.0.5C ("..._Dis_0p5C.mat"), 2C ("..._Dis_2C.mat"), and two 1C ("..._Cap_1C.mat") discharge tests. The first 1C discharge test is performed before the UDDS cycle, and the second is performed before the Mix3 cycle. 4.Series of four drive cycles performed, in following order: UDDS(..._UDDS.mat), HWFET(..._HWFET.mat), LA92 (..._LA92.mat), US06 (..._US06.mat). 5. A series of eight drive cycles (mix 1-8) (..._Mixed#.mat) consist of random mix of UDDS, HWFET, LA92, US06. The drive cycle power profile is calculated for a single Turnigy cell in a compact electric vehicle. 6. The previous tests are repeated for ambient temperatures of 40degC, 25degC, 10degC, 0degC, -10degC, and -20degC, in that order. For tests with ambient temperature below 10degC, a reduced regen current limit is set to prevent premature aging of the cells. The drive cycle power profiles are repeated until 95% of the 1C discharge capacity at the respective temperature has been discharged from the cell 7. A series of 16 charges (charge 1-16) (..._Charge##.mat) store the cell charging before and after every drive cycle starting with an inital top up before doing the Cap_1C test /*************************************************/ Matlab (.mat) file naming convention: The file names begin with the date the test started, and are followed by the time the test started and a descriptive name, such as in the following example: "11-07-19_10.49 557_Cap_1C_40degC_IN21700_30T.mat? Date: "11-07-19" (November 7th, 2019) Time: "10.49" (10:49 am) Descriptor: "40degC_IN21700_30T" The naming convention allows for sorting by date and test time when all the files are placed in one folder. This may be useful when trying to determine which charge is associated with which drive cycle, for example, or when looking at aging.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.282 | 0.123 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".