Health monitoring methods for early fault detection in high voltage battery packs used in electric vehicles

Patent metadata

Field	Value
Publication number	US-12202374-B2
Application number	US-202117516279-A
Country	US
Kind code	B2
Filing date	Nov 1, 2021
Priority date	Nov 1, 2021
Publication date	Jan 21, 2025
Grant date	Jan 21, 2025

Abstract

A system for monitoring a battery of a vehicle includes a processor and a memory storing instructions which when executed by the processor configure the processor to receive first features including statistics of internal resistances of a plurality of cell groups in a battery pack of the battery, compute second features for the battery pack based on the first features, determine whether the battery pack is faulty based on one or more of the second features, and determine, in response to the battery pack being faulty, whether one or more of the cell groups is faulty based on one or more of the first features.

First claim

What is claimed is:

1. A system for monitoring a battery of a vehicle, the system comprising:
a processor; and
a memory storing instructions which when executed by the processor configure the processor to:
receive first features including statistics of internal resistances of a plurality of cell groups in a battery pack of the battery, wherein the first features include at least maximum, minimum, and average internal resistance values for each of the cell groups;
compute second features for the battery pack using combinations of maximum, minimum, and average values of the first features, wherein the first features are adjusted based on one or more parameters of the battery before computing the second features based on the first features;
determine that the battery pack is faulty in response to the one or more of the second features deviating from respective normal values by respective thresholds (i) for one or more drive cycles of the vehicle or (ii) progressively during a plurality of drive cycles of the vehicle, wherein a drive cycle is a trip made by the vehicle;
determine, in response to the battery pack being faulty, whether one or more of the cell groups is faulty based on one or more of the first features;
perform a severity assessment to provide at least one of detection and prediction of a failure in battery pack;
proactively monitor failure progression and send a notification ahead of the failure to avoid a malfunction of the vehicle; and
control an operation of the vehicle in response to a detected fault.

2. The system of claim 1 wherein the instructions further configure the processor to identify one or more of the faulty cell groups that contributes maximally to the faulty battery pack based on one of the second features indicating that the battery pack is faulty and the one or more of the first features of the faulty cell groups.

3. The system of claim 1 wherein the instructions further configure the processor to determine a fault severity level in response to the battery pack and the one or more of the cell groups being faulty.

4. The system of claim 3 wherein the instructions further configure the processor to provide an indication regarding the battery pack and the one or more of the cell groups being faulty and the fault severity level.

5. The system of claim 1 wherein the internal resistances of the cell groups include at least one of charge and discharge resistances of the cell groups.

6. The system of claim 1 wherein the instructions further configure the processor to determine that the one or more of the cell groups is faulty in response to the one or more of the first features deviating from respective normal values by respective thresholds (i) for the one or more drive cycles of the vehicle or (ii) progressively during the plurality of drive cycles of the vehicle.

7. The system of claim 1 wherein the instructions further configure the processor to normalize the second features based on the one or more parameters of the battery before determining whether the battery pack is faulty based on one or more of the second features.

8. A method for monitoring a battery of a vehicle, the method comprising:
receiving first features including statistics of internal resistances of a plurality of cell groups in a battery pack of the battery, the statistics including at least maximum, minimum, and average internal resistance value for each of the cell groups;
computing second features for the battery pack using combinations of maximum, minimum, and average values of the first features;
adjusting the first features based on one or more parameters of the battery before computing the second features based on the first features;
determining that the battery pack is faulty in response to the one or more of the second features deviating from respective normal values by respective thresholds (i) for one or more drive cycles of the vehicle or (ii) progressively during a plurality of drive cycles of the vehicle;
determining, in response to the battery pack being faulty, whether one or more of the cell groups is faulty based on one or more of the first features;
performing a severity assessment to provide at least one of detection and prediction of a failure in battery pack;
proactively monitoring failure progression and sending a notification ahead of the failure to avoid a malfunction of the vehicle; and
controlling an operation of the vehicle in response to a detected fault.

9. The method of claim 8 further comprising identifying one or more of the faulty cell groups that contributes maximally to the faulty battery pack based on one of the second features indicating that the battery pack is faulty and the one or more of the first features of the faulty cell groups.

10. The method of claim 8 further comprising determining a fault severity level in response to the battery pack and the one or more of the cell groups being faulty.

11. The method of claim 10 further comprising providing an indication regarding the battery pack and the one or more of the cell groups being faulty and the fault severity level.

12. The method of claim 8 further comprising determining the internal resistances of the cell groups including at least one of charge and discharge resistances of the cell groups.

13. The method of claim 8 further comprising determining that the one or more of the cell groups is faulty in response to the one or more of the first features deviating from respective normal values by respective thresholds (i) for the one or more drive cycles of the vehicle or (ii) progressively during the plurality of drive cycles of the vehicle.

14. The method of claim 8 further comprising normalizing the second features based on the one or more parameters of the battery before determining whether the battery pack is faulty based on one or more of the second features.

Assignees

• Gm Global Tech Operations Llc

Inventors

• Sankavaram Chaitanya
• Wang Ning
• Zhang Yilu
• Spigno Ciro A

Classifications

• H02J7/84

  Control of state of health [SOH] · CPC title

• H02J7/50 Primary

  acting upon multiple batteries simultaneously or sequentially · CPC title

• G01R31/367

  Software therefor, e.g. for battery testing using modelling or look-up tables · CPC title

• G01R31/389

  Measuring internal impedance, internal conductance or related variables · CPC title

• G01R31/396

  Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery · CPC title