Techniques for efficient compression of sensor data are described herein. In an example, metrology data is received from a metrology device, the metrology data comprising one or more of: voltage (V) data; current (A) data; resistive power (W) data; and volt-amps reactive power (VAR) data. The metrology data is processed, wherein the processing comprises: performing peak-detection on the metrology data, to create data-signals comprising: a timestamped peak-values data-signal; and a peak-removed data-signal. Median-filtering is performed on the peak-removed data-signal, wherein a median-filtered data-signal is created. Level-shift detection is performed on the median-filtered data-signal, wherein a timestamped level-shift data-signal is created. The data is sent to a server. The data may include the timestamped peak-values data-signal and the timestamped level-shift data-signal.

Techniques for efficient compression of sensor data are described herein. In an example, metrology data is received from a metrology device, the metrology data comprising one or more of: voltage (V) data; current (A) data; resistive power (W) data; and volt-amps reactive power (VAR) data. The metrology data is processed, wherein the processing comprises: performing peak-detection on the metrology data, to create data-signals comprising: a timestamped peak-values data-signal; and a peak-removed data-signal. Median-filtering is performed on the peak-removed data-signal, wherein a median-filtered data-signal is created. Level-shift detection is performed on the median-filtered data-signal, wherein a timestamped level-shift data-signal is created. The data is sent to a server. The data may include the timestamped peak-values data-signal and the timestamped level-shift data-signal.

Techniques for efficient compression of sensor data are described herein. In an example, metrology data is received from a metrology device, the metrology data comprising one or more of: voltage (V) data; current (A) data; resistive power (W) data; and volt-amps reactive power (VAR) data. The metrology data is processed, wherein the processing comprises: performing peak-detection on the metrology data, to create data-signals comprising: a timestamped peak-values data-signal; and a peak-removed data-signal. Median-filtering is performed on the peak-removed data-signal, wherein a median-filtered data-signal is created. Level-shift detection is performed on the median-filtered data-signal, wherein a timestamped level-shift data-signal is created. The data is sent to a server. The data may include the timestamped peak-values data-signal and the timestamped level-shift data-signal.

Techniques for efficient compression of sensor data are described herein. In an example, metrology data is received from a metrology device, the metrology data comprising one or more of: voltage (V) data; current (A) data; resistive power (W) data; and volt-amps reactive power (VAR) data. The metrology data is processed, wherein the processing comprises: performing peak-detection on the metrology data, to create data-signals comprising: a timestamped peak-values data-signal; and a peak-removed data-signal. Median-filtering is performed on the peak-removed data-signal, wherein a median-filtered data-signal is created. Level-shift detection is performed on the median-filtered data-signal, wherein a timestamped level-shift data-signal is created. The data is sent to a server. The data may include the timestamped peak-values data-signal and the timestamped level-shift data-signal.

A vehicle, system and method for monitoring an occurrence of thermal runaway in a battery pack of the vehicle. The system includes a plurality of voltage sensors and a processor. The plurality of voltage sensors obtains a plurality of voltage measurements at each of a plurality of battery cells of the battery pack. The processor is configured to determine a mean value based on the plurality of voltage measurements, compare a voltage measurement obtained from a selected battery cell to the mean value, and generate a notification signal when a difference between the voltage measurement from the selected battery cell and the mean value is greater than or equal to a prognostic threshold.

A high-frequency QRS waveform curve analysis method comprises: acquiring a high-frequency QRS waveform curve; selecting the high-frequency QRS waveform curve in a preset time period as a reference waveform curve; selecting a point with the minimum root-mean-square voltage on the reference waveform curve as a first reference point; selecting a second reference point meeting a first selection condition and a third reference point meeting a second selection condition, wherein the time of the first reference point is later than that of the second reference point and earlier than the third reference point; based on the first reference point and the second reference point, determining an amplitude falling relative value; based on the first reference point and the third reference point, determining an amplitude rising relative value. If the amplitude falling rising relative values meet a preset condition, determining reference information according to the high-frequency QRS waveform curve.

A high-frequency QRS waveform curve analysis method comprises: acquiring a high-frequency QRS waveform curve; selecting the high-frequency QRS waveform curve in a preset time period as a reference waveform curve; selecting a point with the minimum root-mean-square voltage on the reference waveform curve as a first reference point; selecting a second reference point meeting a first selection condition and a third reference point meeting a second selection condition, wherein the time of the first reference point is later than that of the second reference point and earlier than the third reference point; based on the first reference point and the second reference point, determining an amplitude falling relative value; based on the first reference point and the third reference point, determining an amplitude rising relative value. If the amplitude falling rising relative values meet a preset condition, determining reference information according to the high-frequency QRS waveform curve.

A high-frequency QRS waveform curve analysis method comprises: acquiring a high-frequency QRS waveform curve; selecting the high-frequency QRS waveform curve in a preset time period as a reference waveform curve; selecting a point with the minimum root-mean-square voltage on the reference waveform curve as a first reference point; selecting a second reference point meeting a first selection condition and a third reference point meeting a second selection condition, wherein the time of the first reference point is later than that of the second reference point and earlier than the third reference point; based on the first reference point and the second reference point, determining an amplitude falling relative value; based on the first reference point and the third reference point, determining an amplitude rising relative value. If the amplitude falling rising relative values meet a preset condition, determining reference information according to the high-frequency QRS waveform curve.

A high-frequency QRS waveform curve analysis method comprises: acquiring a high-frequency QRS waveform curve; selecting the high-frequency QRS waveform curve in a preset time period as a reference waveform curve; selecting a point with the minimum root-mean-square voltage on the reference waveform curve as a first reference point; selecting a second reference point meeting a first selection condition and a third reference point meeting a second selection condition, wherein the time of the first reference point is later than that of the second reference point and earlier than the third reference point; based on the first reference point and the second reference point, determining an amplitude falling relative value; based on the first reference point and the third reference point, determining an amplitude rising relative value. If the amplitude falling rising relative values meet a preset condition, determining reference information according to the high-frequency QRS waveform curve.