Claims:1. A method for managing a battery pack (120 and 130), the method comprising:
monitoring, by a battery performance controller (102), a voltage associated with at least one cell (120a-120n and 130a-130n) of at least one battery pack (120 and 130) during at least one event;
detecting, by the battery performance controller (102), at least one charging weakness index associated with the at least one cell (120a-120n and 130a-130n) and at least one discharging weakness index associated with the at least one cell (120a-120n and 130a-130n) over a period of time based on the monitored voltage;
determining, by the battery performance controller (102), at least one of a cumulative charging weakness index based on the at least one charging weakness index and a cumulative discharging weakness index based on the at least one discharging weakness index;
comparing, by battery performance controller (102), at least one of the determined cumulative charging weakness index with a predefined value and the cumulative discharging weakness index with a predefined value;
identifying, by the battery performance controller (102), a category of at least one cell (120a-120n and 130a-130n) based on the comparison; and
performing, by the battery performance controller (102), at least one action based on the at least one identified category.

2. The method as claimed in claim 1, wherein identifying, by the battery performance controller (102), the category of at least one weak cell (120a-120n and 130a-130n) based on the comparison comprises:
performing, by the battery performance controller (102), at least one of:
determining, by the battery performance controller (102), at least one cell (120a-120n and 130a-130n) upon identifying a maximum charging weakness index is greater than a charge cycle and a maximum discharging weakness index is greater than a discharge cycle, when the at least one cell (120a-120n and 130a-130n) has the maximum charging weakness index and the maximum discharging weakness index;
determining, by the battery performance controller (102), at least one imbalanced battery pack upon identifying the cell maximum charging weakness index is greater than the charge cycle and the maximum discharging weakness index is greater than the discharge cycle, when the maximum charging weakness index and the maximum discharging weakness index are for different the at least one cell (120a-120n and 130a-130n); and
determining, by the battery performance controller (102), the cell (120a-120n and 130a-130n) as an optimal cell upon identifying the maximum charging weakness index is less than the charge cycle and the maximum discharging weakness index is less than the discharge cycle.

3. The method as claimed in claim 1, wherein monitoring, by the apparatus (100), the voltage associated with at least one cell (120a-120n and 130a-130n) of the at least one battery pack (120 and 130) comprises:
acquiring, by the battery performance controller (102), a predetermined upper cut off voltage for the charging event and a predetermined lower cut off voltage for the discharging event; and
monitoring, by the battery performance controller (102), the voltage associated with the at least one cell (120a-120n and 130a-130n) based on the predetermined upper cut off voltage for the charging event and the predetermined lower cut off voltage for the discharging event.

4. The method as claimed in claim 3, wherein the predetermined upper cut off voltage is determined based on a cell chemistry and an internal resistance value associated with the at least one cell (120a-120n and 130a-130n), and wherein the predetermined lower cut off voltage is determined based on the cell chemistry and the internal resistance value associated with the at least one cell (120a-120n and 130a-130n).
5. The method as claimed in claim 1, wherein detecting, by the apparatus (100), the at least one charging weakness index associated with the at least one cell (120a-120n and 130a-130n) and the at least one discharging weakness index associated with the at least one cell (120a-120n and 130a-130n) over the period of time comprises:
identifying, by the battery performance controller (102), a minimum voltage associated with at least one cell (120a-120n and 130a-130n) and a maximum voltage associated with the at least one cell (120a-120n and 130a-130n);
assigning, by the battery performance controller (102), a charging index value for the at least one cell (120a-120n and 130a-130n) based on the voltage difference of the minimum voltage and the maximum voltage within a threshold value over the period of time, wherein the charging index value for the at least one cell (120a-120n and 130a-130n) is assigned during a charge cycle and a discharge cycle;
assigning, by the battery performance controller (102), the discharging index value for the at least one cell (120a-120n and 130a-130n) based on the voltage difference of the minimum voltage and the maximum voltage within a threshold value over a period of time, wherein the index value for the at least one cell (120a-120n and 130a-130n) is assigned during the charge cycle and the discharge cycle; and
indexing, by the battery performance controller (102), the at least one charging weakness index associated with the at least one cell (120a-120n and 130a-130n) and the at least one discharging weakness index associated with the at least one cell (120a-120n and 130a-130n) based on the charging index value and the discharging index value.

6. The method as claimed in claim 1, wherein the at least one action is at least one of
ranking the at least one cell (120a-120n and 130a-130n) in the battery pack (120 and 130) based on a health of the at least one cell (120a-120n and 130a-130n);
notifying a user of the battery pack (120 and 130) about the weak cell;
notifying an imbalanced battery pack, notifying the rank of the at least one cell (120a-120n and 130a-130n) in the battery pack (120 and 130);
replacing the at least one weak cell in the battery pack (120 and 130); and
balancing the at least one battery pack to maintain the health of the battery pack (120 and 130).

7. The method as claimed in claim 1, wherein the at least one event comprises a charging event and a discharging event.

8. An apparatus (100) for managing a battery pack (120 and 130), the apparatus (100) comprising:
a memory (106);
a processor (108); and
a battery performance controller (102), coupled with the memory (106) and the processor (108), configured for:
monitoring a voltage associated with at least one cell (120a-120n and 130a-130n) of at least one battery pack (120 and 130) during at least one event,
detecting at least one charging weakness index associated with the at least one cell (120a-120n and 130a-130n) and at least one discharging weakness index associated with the at least one cell (120a-120n and 130a-130n) over a period of time based on the monitored voltage,
determining at least one of a cumulative charging weakness index based on the at least one charging weakness index and a cumulative discharging weakness index based on the at least one discharging weakness index,
comparing at least one of the determined cumulative charging weakness index with a predefined value and the cumulative discharging weakness index with a predefined value;
identifying a category of at least one cell (120a-120n and 130a-130n) based on the comparison; and
performing at least one action based on the at least one identified category.

9. The apparatus (100), as claimed in claim 8, wherein the battery performance controller (102) identifies the category of at least one weak cell (120a-120n and 130a-130n) based on the comparison by performing at least one of:
determining at least one cell (120a-120n and 130a-130n) upon identifying the maximum charging weakness index is greater than a charge cycle and the maximum discharging weakness index is greater than a discharge cycle, when the at least one cell (120a-120n and 130a-130n) has the maximum charging weakness index and the maximum discharging weakness index;
determining at least one imbalanced battery pack upon identifying the cell maximum charging weakness index is greater than the charge cycle and the maximum discharging weakness index is greater than the discharge cycle, when the maximum charging weakness index and the maximum discharging weakness index are for different the at least one cell (120a-120n and 130a-130n); and
determining the cell (120a-120n and 130a-130n) as an optimal cell upon identifying the maximum charging weakness index is less than the charge cycle and the maximum discharging weakness index is less than the discharge cycle.

10. The apparatus (100), as claimed in claim 8, wherein the battery performance controller (102) monitors the voltage associated with at least one cell (120a-120n and 130a-130n) of the at least one battery pack (120 and 130) by:
acquiring a predetermined upper cut off voltage for the charging event and a predetermined lower cut off voltage for the discharging event; and
monitoring the voltage associated with the at least one cell (120a-120n and 130a-130n) based on the predetermined upper cut off voltage for the charging event and the predetermined lower cut off voltage for the discharging event.

11. The apparatus (100), as claimed in claim 10, wherein the battery performance controller (102) determines the predetermined upper cut off voltage based on a cell chemistry and an internal resistance value associated with the at least one cell (120a-120n and 130a-130n), and wherein the predetermined lower cut off voltage is determined based on the cell chemistry and the internal resistance value associated with the at least one cell (120a-120n and 130a-130n).

12. The apparatus (100), as claimed in claim 8, wherein the battery performance controller (102) detects the at least one charging weakness index associated with the at least one cell (120a-120n and 130a-130n) and the at least one discharging weakness index associated with the at least one cell (120a-120n and 130a-130n) over the period of time by:
identifying a minimum voltage associated with at least one cell (120a-120n and 130a-130n) and a maximum voltage associated with the at least one cell (120a-120n and 130a-130n);
assigning a charging index value for the at least one cell (120a-120n and 130a-130n) based on the voltage difference of the minimum voltage and the maximum voltage within a threshold value over the period of time, wherein the charging index value for the at least one cell (120a-120n and 130a-130n) is assigned during a charge cycle and a discharge cycle;
assigning the discharging index value for the at least one cell (120a-120n and 130a-130n) based on the voltage difference of the minimum voltage and the maximum voltage within a threshold value over a period of time, wherein the index value for the at least one cell (120a-120n and 130a-130n) is assigned during the charge cycle and the discharge cycle; and
detecting the at least one charging weakness index associated with the at least one cell (120a-120n and 130a-130n) and the at least one discharging weakness index associated with the at least one cell (120a-120n and 130a-130n) based on the charging index value and the discharging index value.

13. The apparatus (100), as claimed in claim 8, wherein the action comprises at least one of
ranking the at least one cell (120a-120n and 130a-130n) in the battery pack (120 and 130) based on a health of the at least one cell (120a-120n and 130a-130n);
notifying a user of the battery pack (120 and 130) about the weak cell, notify an imbalanced battery pack;
notifying the rank of the at least one cell (120a-120n and 130a-130n) in the battery pack (120 and 130);
replacing the at least one weak cell in the battery pack (120 and 130); and
balancing the at least one battery pack to maintain the health of the battery pack (120 and 130).

14. The apparatus (100), as claimed in claim 8, wherein the at least one event comprises a charging event and a discharging event.

15. The apparatus (100), as claimed in claim 8, wherein the apparatus (100) further comprises at least one of a battery management system (100a) and a server (100b).
, Description:TECHNICAL FIELD
[001] Embodiments disclosed herein relate to a battery management system, and more particularly to related to methods and apparatuses for managing a battery pack.

BACKGROUND
[002] In general, diagnostics and prognostics play an important role in a battery pack of an electric vehicle (EV). Accurate monitoring of a battery cell (e.g., lithium-ion (Li–ion) cell or the like) in the battery pack is necessary to determine weak / imbalanced cells and take pre-emptive measures to replace/balance the battery pack. Full capacity of the battery pack cannot be utilized if there is a presence of a weak cell/module in the battery pack. Additionally, the weak cell discharges faster compared to other cells which may lead to the EV stopping unexpectedly due to the breach of lower cut-off voltage.
[003] Further, the pack imbalance occurs if the cells with different capacity are grouped together in the battery pack or if the user of the EV does not allow the cells enough time to balance during charging once 100% State of Charge (SOC) is reached. Although, the presence of the imbalanced pack comparatively poses a lesser risk than having a weak cell, the imbalance worsens further if the battery pack is not balanced eventually. The presence of the weak cell eventually leads to faster degradation of the battery capacity. Hence, it is necessary to monitor the cells periodically to check the presence of any weak/imbalanced cells in the battery pack.
[004] Currently, the presence of the weak/imbalanced cell is only determined when the user of the EV experiences sudden drop in the SOC and brings in the EV to a service station. Next, a floor charging is done to bring all the cells to same voltage level and a discharge test is done to determine whether there is any problem in the battery pack. Not only this process is time consuming but also there is human and cost involvement, which makes this process complex and expensive.
[005] Thus, it is desired to address the above mentioned disadvantages or other shortcomings or at least provide a useful alternative.

OBJECTS
[006] The principal object of embodiments herein is to disclose methods and apparatuses for managing a battery pack.
[007] Another object of embodiments herein is to monitor a voltage associated with one or more cell of one or more battery pack during an event.
[008] Another object of embodiments herein is to determine a cumulative charging weakness index based on one or more charging weakness index and a cumulative discharging weakness index based on one or more discharging weakness index.
[009] Another object of embodiments herein is to determine one or more weak cell upon identifying a maximum charging weakness index is greater than a charge cycle and a maximum discharging weakness index is greater than a discharge cycle, when the one or more cell has the maximum charging weakness index and the maximum discharging weakness index.
[0010] Another object of embodiments herein is to determine one or more imbalanced pack upon identifying the one or more cell maximum charging weakness index is greater than the charge cycle and the maximum discharging weakness index is greater than the discharge cycle, when the maximum charging weakness index and the maximum discharging weakness index are for different the one or more cell.
[0011] Another object of embodiments herein is to determine the cell as optimal cell upon identifying the maximum charging weakness index is less than the charge cycle and the maximum discharging weakness index is less than the discharge cycle.
[0012] Another object of embodiments herein is to compare the determined cumulative charging weakness index with a predefined value and the cumulative discharging weakness index with a predefined value to identify a category of the one or more cell based on the comparison.
[0013] Another object of embodiments herein is to rank the one or more cell in the battery pack based on a health of the one or more cell.
[0014] Another object of embodiments herein is to notify a user about the weak cell in the battery pack.
[0015] Another object of embodiments herein is to notify an imbalanced battery pack to the user.
[0016] Another object of embodiments herein is to replace the one or more weak cell in the battery pack and balance the one or more battery pack to maintain the health of the battery.
[0017] Another object of embodiments herein is to avoid unexpected failures of the battery pack.
[0018] Another object of embodiments herein is to real time determination of weak cell/module within a battery pack without bringing the EV to a service station. This results in saving time and cost but also providing a hassle free experience to the user of the EV.
[0019] Another object of embodiments herein is to provide that full capacity of the battery pack can be utilized and avoid unexpected EV stopping due to the breach of lower cut-off voltage.
[0020] These and other aspects of the embodiments herein will be better appreciated and understood when considered in conjunction with the following description and the accompanying drawings. It should be understood, however, that the following descriptions, while indicating at least one embodiment and numerous specific details thereof, are given by way of illustration and not of limitation. Many changes and modifications may be made within the scope of the embodiments herein without departing from the scope thereof, and the embodiments herein include all such modifications.

BRIEF DESCRIPTION OF FIGURES
[0021] Embodiments herein are illustrated in the accompanying drawings, through out which like reference letters indicate corresponding parts in the various figures. The embodiments herein will be better understood from the following description with reference to the drawings, in which:
[0022] FIG. 1 shows various hardware components of an apparatus for managing a battery pack, according to embodiments as disclosed herein;
[0023] FIG. 2 is an overview of a system for managing the battery pack, according to embodiments as disclosed herein;
[0024] FIG. 3 is a flow chart illustrating a method for managing the battery pack, according to embodiments as disclosed herein;
[0025] FIG. 4 is an example flow chart illustrating operations for indexing a cumulative discharging weakness index during discharging operations, according to embodiments as disclosed herein;
[0026] FIG. 5 is an example flow chart illustrating operations for indexing a cumulative charging weakness index during charging operations, according to embodiments as disclosed herein; and
[0027] FIG. 6 is an example illustration in which cell conditions are depicted, according to embodiments as disclosed herein.

DETAILED DESCRIPTION
[0028] The embodiments herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting embodiments that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
[0029] The embodiments herein achieve methods for managing a battery pack by an apparatus. The method includes monitoring voltage associated with one or more cell of one or more battery pack during an event. The method includes detecting a charging weakness index associated with the one or more cell and a discharging weakness index associated with the one or more cell. Further, the method includes determining a cumulative charging weakness index based on the charging weakness index and a cumulative discharging weakness index based on the discharging weakness index. Further, the method includes comparing the determined cumulative charging weakness index with a predefined value and the cumulative discharging weakness index with a predefined value. Further, the method includes identifying a category of the one or more cell based on the comparison. Further, the method includes performing an action based on the identified category.
[0030] Unlike conventional methods and systems, the proposed method can be used to real time determination of weak cell/module within the battery pack without bringing the vehicle to the service station. This results in saving time and cost but also providing hassle free experience to the user of the EV. In the proposed method, full capacity of the battery pack can be utilized and avoid unexpected vehicle stopping due to the breach of lower cut-off voltage. The method can be used to prolong the life of the battery without any manual intervention.
[0031] Based on the proposed method, early detection of weak/imbalanced cell in the battery pack to take pre-emptive measures (either to replace the cell or balance the pack) to maintain the health of the battery and avoid unexpected failures. The method can be used to prolong the life of the battery.
[0032] The proposed method can be used to real time determination of the weak cell/module within the battery pack in a simple and efficient manner. Early detection of imbalanced pack can be easily fixed by alerting the user to let the cells balance after doing a normal charge. The method can be used to maintain a healthy battery and get away from range anxiety.
[0033] In an example, the method can be used to monitor the cell voltages during specific segments of charging/discharging process and indexing/grading the weak cells based on their voltage values. The whole process can be done online through analyzing a telematics data. The cell chemistry utilized for the method is LiFePO4 (LFP). Based on the experimental data and upper cut off voltage/SOC for charging curve and lower voltage/SOC cut off for discharging curve is considered for the weak cell identification analysis. Further, whenever the cell/battery pack operated in the identified voltage/SOC window, the minimum and maximum voltages are recorded, and the cells are correspondingly assigned an index value depending upon the voltage difference within threshold value or beyond it. The process is repeated for every charge/discharge cycle where the criteria are met. Further, the index is summed every month to obtain charging and discharging weakness index. Finally, the presence of weak/imbalanced pack is determined by comparing the weakness index with predefined criteria. By this analysis not only one can identify the weak cells but also rank them according to their respective health in a simple and cost effective manner.
[0034] Referring now to the drawings, and more particularly to FIGS. 1 through 6, where similar reference characters denote corresponding features consistently throughout the figures, there are shown embodiments.
[0035] FIG. 1 shows various hardware components of an apparatus (100) for managing a battery pack (120 and 130), according to embodiments as disclosed herein. In an embodiment, the apparatus (100) is communicated with the one or more battery pack (120 and 130). The one or more battery pack (120 and 130) can be, for example, but not limited to, a Li-ion battery pack, a LiFePO4 (LFP) battery pack, Nickel, Manganese and Cobalt (NMC) battery pack, lead-acid batteries battery pack or the like. In an embodiment, the battery pack can be a primary battery pack. In another embodiment, the battery pack can be a secondary battery pack. The apparatus can be operated in a vehicle (as shown in the FIG. 2). The vehicle can be, for example, but not limited to an electrical vehicle (EV), a hybrid electric vehicle (HEV), a plug-in hybrid electric vehicles (PHEV), a battery based electric vehicle (BEV) or the like. The apparatus (100) can also be operated/used in an electronic device (e.g., smart phone, data center, laptop, immersive device, or the like).
[0036] In an embodiment, the apparatus (100) can be a battery management system (100a) (as shown in the FIG. 2). In another embodiment, the apparatus (100) can be a server (100b) (as shown in the FIG. 2). The server (100b) can be, for example, but not limited to a cloud server, an edge server, a third party server or the like. In an embodiment, the apparatus (100) includes a battery performance controller (102), a communicator (104), a memory (106), a processor (108), and a display (110). The processor (108) is coupled with the battery performance controller (102), the communicator (104), the memory (106) and the display (110).
[0037] The battery pack (120 and 1130) includes a plurality of battery cells (120a-120n and 130a-130n) connected in parallel/serial. In general, when the plurality of (120a-120n and 130a-130n) is used in series and/or in parallel, a voltage may be measured and monitored based on the connection arrangement.
[0038] Further, it is ideal for electrical characteristics such as voltage (SoC) and resistance of the battery cells (120a-120n and 130a-130n) to be uniform, but there may be a manufacturing dispersion, a difference in deterioration caused by using the battery, battery cell abnormality, etc., and thus there may be a difference in the voltage or the SoC between the battery cells (120a-120n and 130a-130n). Further, the battery pack (120 and 130) includes the plurality of battery cells (120a-120n and 130a-130n) that collectively dictate the capabilities of the battery pack (120 and 130). The number of cells per module and the number of modules per battery pack (120 and 130) may be varied based on the application at hand.
[0039] The battery performance controller (102) is configured to monitor a voltage associated with the one or more cell (120a-120n and 130a-130n) of the one or more battery pack (120 and 130) during an event. The event can be, for example, but not limited to a charging event and a discharging event. In an embodiment, the battery performance controller (102) is configured to acquire a predetermined upper cut off voltage for the charging event and a predetermined lower cut off voltage for the discharging event. In an example, upper cut off voltage/SOC (VH) (for example in case of LFP VH is around 95% SOC and Nickel, Manganese and Cobalt (NMC) it can be around 80% SOC) for the charging curve and a lower voltage/SOC (VL) (for example in case of LFP and the NMC it can be around 30% SOC) cut off for discharging curve is considered for the weak cell/ imbalance calculations.
[0040] Based on the predetermined upper cut off voltage for the charging event and the predetermined lower cut off voltage for the discharging event, the battery performance controller (102) is configured to monitor the voltage associated with the one or more cell (120a-120n and 130a-130n). The predetermined upper cut off voltage is determined based on a cell chemistry and an internal resistance value associated with the one or more cell (120a-120n and 130a-130n). The predetermined lower cut off voltage is determined based on the cell chemistry and the internal resistance value associated with the one or more cell (120a-120n and 130a-130n).
[0041] Further, the battery performance controller (102) is configured to detect a charging weakness index associated with the one or more cell (120a-120n and 130a-130n) and a discharging weakness index associated with the one or more cell (120a-120n and 130a-130n) over a period of time based on the monitored voltage. In an embodiment, the battery performance controller (102) is configured to identify a minimum voltage associated with the one or more cell (120a-120n and 130a-130n) and a maximum voltage associated with the one or more cell (120a-120n and 130a-130n). Further, the battery performance controller (102) is configured to assign a charging index value for the one or more cell (120a-120n and 130a-130n) based on the voltage difference of the minimum voltage and the maximum voltage within a threshold value over the period of time. In an embodiment, the threshold value is determined by the user of the battery pack (120 and 130). In another embodiment, the threshold value is determined by an original equipment manufacturer (OEM). The charging index value for the one or more cell (120a-120n and 130a-130n) is assigned during the charge cycle and the discharge cycle. Further, the battery performance controller (102) is configured to assign the discharging index value for the one or more cell (120a-120n and 130a-130n) based on the voltage difference of the minimum voltage and the maximum voltage within the threshold value over the period of time. The index value for the one or more cell (120a-120n and 130a-130n) is assigned during the charge cycle and the discharge cycle. Further, the battery performance controller (102) is configured to detect the charging weakness index associated with the cell (120a-120n and 130a-130n) and the discharging weakness index associated with the cell (120a-120n and 130a-130n) based on the charging index value and the discharging index value.
[0042] In an example, during charging/discharging the maximum cell to minimum cell voltage difference are calculated and based on the threshold deltaV values identified, the below indexing criteria is followed for Vmin cell during discharge and Vmax cell for charging.
deltV1 < Vmax- Vmin deltaV2 mV ..(2)
[0043] The deltaV1 and deltaV2 values are in the order of 100mV and 200 mV for LFP. For NMC it is in the order of 30 mV and 70 mV respectively. The detailed indexing sequences are explained in the FIG. 4 and FIG. 5. Further, every month weightage values are summed to get a charging weakness index and a discharging weakness index.
[0044] Further, the battery performance controller (102) is configured to determine a cumulative charging weakness index based on the charging weakness index and a cumulative discharging weakness index based on the discharging weakness index.
[0045] Further, the battery performance controller (102) is configured to compare the determined cumulative charging weakness index with a predefined value and the cumulative discharging weakness index with a predefined value. In an embodiment, the predefined value is determined by the user of the battery pack (120 and 130). In another embodiment, the predefined value is determined by the OEM. Further, the battery performance controller (102) is configured to identify the category of the one or more cell (120a-120n and 130a-130n) based on the comparison. In an embodiment, the battery performance controller (102) is configured to determine the one or more cell (120a-120n and 130a-130n) upon identifying the maximum charging weakness index is greater than a charge cycle (CC) and the maximum discharging weakness index is greater than a discharge cycle (DC), when the one or more cell (120a-120n and 130a-130n) has the maximum charging weakness index and the maximum discharging weakness index. In other words, if the same cell has MaxCWi and MaxDWi and if MaxCWi ≥ CC or MaxDWi ≥ DC then cell is to be considered as the weak cell. The MaxDWi is a maximum discharging weakness index, CC is a Charge Cycle, and DC is a Discharge Cycle
[0046] In another embodiment, the battery performance controller (102) is configured to determine the imbalanced battery pack upon identifying the cell maximum charging weakness index is greater than the charge cycle and the maximum discharging weakness index is greater than the discharge cycle, when the maximum charging weakness index and the maximum discharging weakness index are for different the one or more cell (120a-120n and 130a-130n). In other words, if MaxCWi and MaxDWi are for different cells and if MaxCWi ≥ CC or MaxDWi ≥ DC then battery pack is to be considered as imbalanced pack.
[0047] In another embodiment, the battery performance controller (102) is configured to determine the cell (120a-120n and 130a-130n) as an optimal cell upon identifying the maximum charging weakness index is less than the charge cycle and the maximum discharging weakness index is less than the discharge cycle. In other words, if MaxCWi < CC and MaxDWi < DC then the battery pack is considered as functioning satisfactory.
[0048] Further, the battery performance controller (102) is configured to perform an action based on the identified category. In an embodiment, the action can be, for example, but not limited to rank the one or more cell (120a-120n and 130a-130n) in the battery pack (120 and 130) based on a health of the one or more cell (120a-120n and 130a-130n), notify a user of the battery pack (120 and 130) about the weak cell, notify an imbalanced battery pack on the display (110), notify the rank of the one or more cell (120a-120n and 130a-130n) in the battery pack (120 and 130) on the display (110), replace the one weak cell in the battery pack (120 and 130), balance the battery pack (120 and 130) to maintain the health of the battery pack (120 and 130), and avoid unexpected failures of the battery pack (120 and 130).
[0049] In an example (600), cell conditions are depicted in the FIG. 6. As shown in the FIG. 6, the light gray color cell (120a and 120c) are in initial stage of weak cell/poor cell. The black color cell (130c) are in final stage of the weak cell/poor cell (e.g., priority to replace as soon as early). The other cell (120b, 120d, 130a, and 130b) are optimal cell in the battery pack (120 and 130).
[0050] In an example, the battery pack (120 and 130) is balanced by a passive balancing and an active balancing. The passive balancing may be performed by consuming energy of the cell (120a-120n and 130a-130n), having a high voltage or SoC. The passive balancing may include, for example, discharging cells through a resistor. The active balancing may be implemented to transfer energy of a cell with a high voltage or SoC to a cell with a low voltage or SoC to equalize the voltage or SoC between the two cells (120a-120n and 130a-130n). The method can be used to determine a high-impedance cell. The high-impedance cell is a cell having higher impedance or higher equivalent resistance than other cells due to, for example, connection problems between cells, deterioration differences, and cell anomalies.
[0051] The battery performance controller (102) is physically implemented by analog or digital circuits such as logic gates, integrated circuits, microprocessors, microcontrollers, memory circuits, passive electronic components, active electronic components, optical components, hardwired circuits, or the like, and may optionally be driven by firmware.
[0052] Further, the processor (108) is configured to execute instructions stored in the memory (106) and to perform various processes. The communicator (104) is configured for communicating internally between internal hardware components and with external devices via one or more networks. The memory (106) also stores instructions to be executed by the processor (108). The memory (106) may include non-volatile storage elements. Examples of such non-volatile storage elements may include magnetic hard discs, optical discs, floppy discs, flash memories, or forms of electrically programmable memories (EPROM) or electrically erasable and programmable (EEPROM) memories. In addition, the memory (106) may, in some examples, be considered a non-transitory storage medium. The term “non-transitory” may indicate that the storage medium is not embodied in a carrier wave or a propagated signal. However, the term “non-transitory” should not be interpreted that the memory (106) is non-movable. In certain examples, a non-transitory storage medium may store data that can, over time, change (e.g., in Random Access Memory (RAM) or cache).
[0053] Further, at least one of the plurality of modules/controller may be implemented through the AI model. A function associated with the AI model may be performed through the non-volatile memory, the volatile memory, and the processor (108). The processor (108) may include one or a plurality of processors. At this time, one or a plurality of processors may be a general purpose processor, such as a central processing unit (CPU), an application processor (AP), or the like, a graphics-only processing unit such as a graphics processing unit (GPU), a visual processing unit (VPU), and/or an AI-dedicated processor such as a neural processing unit (NPU).
[0054] The one or a plurality of processors control the processing of the input data in accordance with a predefined operating rule or AI model stored in the non-volatile memory and the volatile memory. The predefined operating rule or artificial intelligence model is provided through training or learning.
[0055] Here, being provided through learning means that a predefined operating rule or AI model of a desired characteristic is made by applying a learning algorithm to a plurality of learning data. The learning may be performed in a device itself in which AI according to an embodiment is performed, and/o may be implemented through a separate server/system.
[0056] The AI model may comprise of a plurality of neural network layers. Each layer has a plurality of weight values and performs a layer operation through calculation of a previous layer and an operation of a plurality of weights. Examples of neural networks include, but are not limited to, convolutional neural network (CNN), deep neural network (DNN), recurrent neural network (RNN), restricted Boltzmann Machine (RBM), deep belief network (DBN), bidirectional recurrent deep neural network (BRDNN), generative adversarial networks (GAN), and deep Q-networks.
[0057] The learning algorithm is a method for training a predetermined target device (for example, a robot) using a plurality of learning data to cause, allow, or control the target device to make a determination or prediction. Examples of learning algorithms include, but are not limited to, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning.
[0058] Although the FIG. 1 shows various hardware components of the apparatus (100) but it is to be understood that other embodiments are not limited thereon. In other embodiments, the apparatus (100) may include less or more number of components. Further, the labels or names of the components are used only for illustrative purpose and does not limit the scope of the invention. One or more components can be combined together to perform same or substantially similar function in the apparatus (100).
[0059] FIG. 2 is an overview of a system (1000) for managing the battery pack (120 and 130), according to embodiments as disclosed herein. In an embodiment, the apparatus (100) includes the battery management system (100a) and the server (100b). The operations and functions of the the battery management system (100a) and the server (100b) are already explained in connection with the FIG. 1. The battery management system (100a) and the server (100b) are communicated with each other over wired communication medium and a wireless communication medium.
[0060] FIG. 3 is a flow chart (300) illustrating a method for managing the battery pack (120 and 130), according to embodiments as disclosed herein. The operations (302-312) are performed by the battery performance controller (102).
[0061] At 302, the method includes monitoring the voltage associated with the one or more cell (120a-120n and 130a-130n) of the battery pack (120 and 130) during the event. At 304, the method includes indexing the charging weakness index associated with the one or more cell (120a-120n and 130a-130n) and the discharging weakness index associated with the one or more cell (120a-120n and 130a-130n) over the period of time based on the monitored voltage. At 306, the method includes determining the cumulative charging weakness index based on the charging weakness index and the cumulative discharging weakness index based on the discharging weakness index.
[0062] At 308, the method includes comparing the determined cumulative charging weakness index with the predefined value and the cumulative discharging weakness index with the predefined value. At 310, the method includes identifying the category of the one or more cell (120a-120n and 130a-130n) based on the comparison. At 312, the method includes performing the action based on the identified category. The action is already explained in the FIG.1.
[0063] Unlike conventional methods and systems, the proposed method can be used to real time determination of weak cell/module within the battery pack without bringing the vehicle to the service station. This results in saving time and cost but also providing hassle free experience to the user of the EV. In the proposed method, full capacity of the battery pack can be utilized and avoid unexpected vehicle stopping due to the breach of lower cut-off voltage. The method can be used to prolong the life of the battery without any manual intervention.
[0064] Based on the proposed method, the proper estimation of a state of health (SOH) can be made by ignoring the weak cell and considering the capacity of rest of the battery pack (120 and 130).
[0065] FIG. 4 is an example flow chart (400) illustrating operations for indexing the cumulative discharging weakness index during the discharging operations, according to embodiments as disclosed herein. The operations (402-416) are performed by the battery performance controller (102).
[0066] At 402, the method includes determining whether 20oC < Tamb< 45oC. If the step (402) does not meet the condition, the operations are disabled at 404. At 406, the method includes determining whether any cell voltage is equal to Vi? If any cell voltage is not equal to Vi then, the method performs the operation (402). If any cell voltage is equal to Vi then, at 408, the method includes reading minimum cell voltage (vmax- vmmin)>deltV1. At 410, the method includes identifying the cell number reached the vmax, I, if ΔV deltV1. At 510, the method includes identifying the cell number reached the vmax, I, if ΔV