Systems and methods for battery performance prediction

A method of predicting battery cell performance, the method comprising:

• performing at least two battery tests to generate, for each cycle of at least a first cycle and a second cycle of a battery cell, data of a charge-voltage curve for the cycle in a corresponding battery test, each of the at least two battery tests comprising:
• applying a plurality of pulses to the battery cell during cycling the battery cell between a first voltage and a second voltage in the cycle, and measuring a respective charge-voltage curve portion for each of the plurality of pulses, the charge-voltage curve for the cycle comprising the respective charge-voltage curve portion for each of the plurality of pulses;
• calculating, using the data from the charge-voltage curves for the first cycle and the second cycle, features describing a difference of at least one battery cell property between the charge-voltage curves for the first cycle and for the second cycle;
• providing the features of the battery cell as input to a machine learning system to predict cell performance of the battery cell, wherein the machine learning system comprises a machine learning model that has been trained using training data including battery test data of battery cells that reached respective end of life (EOL) cycles, and, in response,
• automatically generating a prediction result for the battery cell by the machine learning model, the prediction result indicating an EOL cycle of the battery cell;
• and
• taking an action based on the prediction result for the battery cell,
• wherein calculating the features describing the difference between the charge-voltage curves for the first cycle and for the second cycle comprise:
• for each of the plurality of pulses, determining differences of the at least one battery cell property based on corresponding data points between the respective charge-voltage curve portions for the first cycle and the second cycle, and calculating one or more characteristics of the differences of the at least one battery cell property for the pulse, wherein the features comprise each of the calculated one or more characteristics for the pulse of the plurality of pulses.

A system comprising:

• one or more computers;
• and
• one or more storage devices on which are stored instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations for predicting battery cell performance, the operations comprising:
• performing at least two battery tests to generate battery test data of a battery cell, the battery test data comprising data of at least one battery cell property of the at least two battery tests, each of the at least two battery tests comprising applying a plurality of pulses on the battery cell during a corresponding battery cycle and measuring a charge-voltage curve for the corresponding battery cycle, the charge-voltage curve comprising a respective charge-voltage curve portion for each of the plurality of pulses;
• providing the battery test data of the battery cell as input to a machine learning system to predict cell performance of the battery cell, wherein the machine learning system comprises a machine learning model that has been trained using training data including battery test data of battery cells that reached respective end of life (EOL) cycles, and, in response,
• automatically generating a prediction result for the battery cell by the machine learning model, the prediction result indicating an EOL cycle of the battery cell;
• and
• taking an action based on the prediction result for the battery cell,
• wherein the battery test data of the battery cell comprises features describing a difference of the at least one battery cell property for at least two battery cycles of the at least two battery tests, and wherein the features comprise, for each of the plurality of pulses, one or more characteristics of the at least one battery cell property based on corresponding data points between the respective charge-voltage curve portions for the at least two battery cycles.