Predicting future battery safety threat events with causal models

A personal computing device, comprising:

• a battery;
• a processor;
• and
• memory storing a causal model and instructions that, in response to execution of the instructions by the processor, cause the processor to:
• obtain a plurality of data points indicative of a history of the battery;
• and
• use the plurality of data points as input for the causal model to generate a prediction of a future state of the battery;
• wherein the causal model comprises a plurality of nodes linked by edges, each node representing an event and each edge representing an observed cause-effect relationship between an event represented by one node of the causal model and another event represented by another node of the causal model, wherein a given node of the plurality of nodes represents the future state of the battery.

A non-transitory computer-readable medium comprising instructions that, in response to execution of the instructions by a processor, cause the processor to:

• obtain a plurality of data points associated with a battery;
• and
• apply the plurality of data points as input for a causal network to generate output, wherein the output predicts a future safety threat event of the battery;
• wherein the causal network encodes a plurality of events occurring over a lifetime of the battery and cause-effect relationships between the plurality of events, wherein a given event of the plurality of events comprises the future safety threat event of the battery.