Technique for estimation of internal battery temperature

A method for estimating an internal temperature of a battery from terminal impedance measurements of the battery, the method comprising:

• obtaining multiple terminal impedance measurements for the battery at a plurality of frequencies based on a plurality of periodic signals injected into the battery, wherein each of the periodic signals have a different frequency of the plurality of frequencies;
• deriving model parameters for a multivariable polynomial regression model, the deriving comprising:
• obtaining training data from a set of training batteries similar to the battery;
• and
• applying a linear least squares fit to the training data;
• and
• combining the multiple terminal impedance measurements using the multivariable polynomial regression model to produce an estimate of the internal temperature of the battery as an output of the multivariable polynomial regression model;
• wherein the plurality of frequencies span a range of frequencies selected to reduce dependence of the estimate of the internal temperature of the battery on a state of health (SOH) of the battery and a state of charge (SOC) of the battery.

A system for estimating an internal temperature of a battery from a plurality of terminal impedance measurements obtained for the battery, wherein the plurality of terminal impedance measurements are taken at a plurality of frequencies, the system comprising:

• at least one hardware processor;
• and
• at least one memory storing instructions that cause the at least one hardware processor to perform operations comprising:
• providing a multivariable polynomial regression model comprising a number of model parameters, the multivariable polynomial regression model configured to combine the plurality of terminal impedance measurements to generate an estimate the internal temperature of the battery;
• wherein the plurality of frequencies span a range of frequencies selected to reduce dependence of the estimate of the internal temperature of the battery on a state of health (SOH) of the battery and a state of charge (SOC) of the battery;
• obtaining the plurality of terminal impedance measurements for the battery based on a plurality of periodic signals injected into the battery, wherein each of the periodic signals have a different frequency of the plurality of frequencies;
• inputting the plurality of terminal impedance measurement into the multivariable polynomial regression model as a plurality of inputs;
• and
• applying the multivariable polynomial regression model to the plurality of terminal impedance measurements to estimate the internal temperature of the battery as an output of the multivariable polynomial regression model.