Methods and systems for managing multi-cell batteries

1 . A method for measuring electrical quantities in an electrical system, comprising:

obtaining a first set of known electrical output values via an electrical quantity sensor, the first set of known electrical outputs being associated with a first temperature measured via a temperature sensor that is different than the electrical quantity sensor;

obtaining a second set of known electrical output values via the electrical quantity sensor, the second set of known electrical outputs being associated with a second temperature that is different from the first temperature, the second temperature being measure via the temperature sensor;

measuring an operational temperature of one or more locations in the electrical system;

computing a pair of reference electrical output values, corresponding to the measured operational temperature, in accordance with the first set of known electrical output values associated with the first temperature and the second set of known electrical output values associated with the second temperature; and

interpolating among the pair of computed reference electrical output values to determine a temperature-corrected electrical quantity based on the measured operational temperature and the reference electrical output values.

2 . The method of claim 1 , wherein:

the electrical system includes a battery management system having a multi-cell battery, and

the method further comprises:

providing a temperature threshold;

comparing the measured operational temperature to the temperature threshold; and

controlling a charge or discharge of cells in the battery based on comparing the measured operational temperature to the temperature threshold.

3 . The method of claim 1 , wherein the first and second temperatures include first and second known absolute temperatures, respectively.

4 . The method of claim 1 , the first and second temperatures include first and second relative temperatures that are not absolutely known.

5 . The method of claim 1 , further comprising determining a remaining charge in the battery system, via a machine learning model, based on the battery voltage, a current, and a current temperature.

6 . The method of claim 1 , wherein the first and second sets of known electrical output values are obtained during fabrication of a device including the electrical system.

7 . The method of claim 6 , further comprising storing the first and second sets of known electrical output values in nonvolatile memory.

8 . A method for measuring electrical quantities in an electrical system, comprising:

obtaining, at a first temperature, a set of electrical output values of via an electrical quantity sensor of the electrical system, the electrical quantity sensor being a linear sensor, the first temperature being measured via a temperature sensor that is different than the electrical quantity sensor; and

interpolating among the set of reference electrical output values to determine a temperature-corrected electrical value based on the first temperature and the set of reference electrical output values in accordance with a temperature coefficient being less than a temperature coefficient threshold.

9 . The method of claim 8 , wherein the electrical system includes a battery management system having a multi-cell battery.

10 . The method of claim 9 , further comprising:

measuring an operational temperature of the electrical system;

providing a temperature threshold;

comparing the measured operational temperature to the temperature threshold; and

controlling a charge or discharge of cells in the battery based on the comparison with regard to the threshold.

11 . The method of claim 10 , further comprising executing a machine learning model to predict a remaining charge in the multi-cell battery based on the measured operational temperature and the reference electrical output values.

12 . The method of claim 11 , further comprising training the machine learning model to predict the amount of charge remaining in the pack using charge and discharge cycles based on recent history.

13 . The method of claim 11 , further comprising training the machine learning model to predict an optimum strategy for charging, discharging and/or balancing the multi-cell battery system.

14 . The method of claim 8 , wherein the first temperature is a known temperature.

15 . The method of claim 8 , wherein the first temperature is a respective relative temperature.

16 . The method of claim 8 , wherein the set of electrical outputs are obtained during a manufacturing process of the electrical system.

17 . The method of claim 8 , further comprising storing the set of electrical outputs in a nonvolatile memory device.

18 . The method of claim 8 , wherein the temperature-corrected electrical value includes a temperature-compensated and interpolated voltage.

19 . The method of claim 18 , wherein the temperature-corrected electrical value includes a temperature-compensated and interpolated current.

20 . The method of claim 19 , wherein:

the electrical system includes a battery management system comprising a multi-cell battery; and

the method further comprising determining a state of charge of the multi-cell battery according to the temperature-compensated and interpolated voltage, the temperature-compensated and interpolated current, and an operational temperature.