Description:BACKGROUND
Technical Field
[001] The present disclosure relates to one or more battery packs, and more specifically relates to a system for estimating state of health of one or more battery packs and a method for the same.

Description of the Related Art
[002] State of Health (SOH) is a measure of a battery pack’s overall condition and performance compared to its original (new) state. Objective of measuring the SOH is to (i) predict lifespan, (ii) Assess Battery Degradation, (iii) ensure safety and reliability, (iv) help with maintenance and replacement decisions, (vii) and (vi) optimize battery performance of the battery pack/one or more battery packs.
[003] In a conventional approach, SOH is measured by tracking charge input and output, to estimate capacity, but minor measurement errors accumulate over multiple cycles. The conventional approach works best when the battery is fully charged and discharged regularly, but in real-world applications (e.g., EVs, energy storage), batteries rarely undergo full cycles, making the SOH estimate unreliable. SOH is affected by factors like chemical degradation, lithium plating, and electrode wear, which the conventional approach does not directly measure. Further, the conventional approach does not consider parameters like temperature variations, and self-discharge which makes the conventional approach inaccurate. In addition to that, the conventional approach is not suitable for large battery packs with multiple cells.
[004] In another conventional approach, SOH estimation and charging optimization are carried out on the vehicle side, adding an extra burden to the control unit (e.g., VCU, ECU, BMS) due to the need to handle a large volume of datasets which makes the existing approach slower, and complicated.
[005] In another conventional approach, one or more environmental conditions, or one or more rider behaviours are not considered while performing SOH estimation and charging optimization which makes the existing approach inaccurate. So that conventional approaches are inefficient in solving above mentioned problems.
[006] Accordingly, there remains a need for an improved system and method for estimating state of health of one or more battery packs in the vehicle and therefore addressing the aforementioned issues.

SUMMARY
[007] In view of the foregoing, an aspect herein provides a system for estimating State of Health (SOH) of one or more battery packs in a vehicle. The system includes a vehicle and a cloud. The vehicle includes one or more battery packs, a data collection module, and an aggression index module. The data collection module is configured to collect one or more vehicle riding data from the vehicle. The data collection module is further configured to collect at least one of battery energy capacity data or impedance data from the one or more battery packs. The aggression index (AI) identifying module is configured to identify an aggression index (AI) from the one or more vehicle riding data. The cloud includes a receiving module, a storage module, an estimation module, a degradation ratio identification module, an analysing module, and a regulation module. The receiving module is configured to receive (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of battery energy capacity data or impedance data from the data collection module. The storage module is operable by one or more processors and configured to store (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of energy capacity data or impedance data. The storage module includes a reference SOH of the one or more battery packs. The estimation module is operable by one or more processors and configured to estimate the SOH of the one or more battery packs during charging using (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of energy capacity data or impedance data. The degradation ratio identification module is operable by one or more processors and configured to identify a degradation ratio of the one or more battery packs by comparing an estimated SOH estimated by the estimation module with the reference SOH of the one or more battery packs. The degradation ratio is related to charge-discharge cycles of the one or more battery packs. The analysing module is operable by one or more processors and configured to analyse whether the degradation ratio is slower than a threshold degradation ratio or faster than the threshold degradation ratio. The regulation module is operable by one or more processors and configured to reduce constant current (CC) phase to slow down degradation when the degradation ratio is higher than the threshold degradation ratio. The regulation module is operable by one or more processors and configured to increase the CC phase to reduce charging time when the degradation is slower than the threshold degradation ratio.
[008] In some embodiments, the one or more vehicle riding data comprises at least one of usage patterns of the one or more battery packs, temperature of the one or more battery packs, charge cycles of the one or more battery packs, one or more environmental conditions, or one or more rider behaviours.
[009] In some embodiments, the data collection module is disposed on a control unit of the vehicle.
[0010] In some embodiments, the one or more battery packs include an Equivalent Circuit Model (ECM) with Direct Current Internal Resistance (DCIR) and resistance and capacitance values for calculating battery impedance data and monitoring degradation.
[0011] In some embodiments, the regulation module regulates the constant current (CC) phase based on state of charge SoC of the one or more battery packs, temperature of the one or more battery packs, SOH of the one or more battery packs, and impedance data of the one or more battery packs, and the one or more environmental conditions.
[0012] In another aspect, a method for estimating State of Health (SOH) of one or more battery packs in a vehicle is provided. The method includes (a) collecting, by a data collection module, one or more vehicle riding data from the vehicle; (b) collecting, by the data collection module, at least one of battery energy capacity data or impedance data from the one or more battery packs; (c) identifying, by an aggression index (AI) identifying module, an aggression index (AI) from the one or more vehicle riding data; (d) receiving, by a receiving module, (i) the one or more vehicle riding data with the aggression index (AI), and (ii) the at least one of battery energy capacity data or impedance data from the data collection module; (e) storing, by a storage module, (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of energy capacity data or impedance data; (f) estimating, by an estimation module, the SOH of the one or more battery packs during charging using (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of energy capacity data or impedance data; (g) identifying, by a degradation ratio identification module, a degradation ratio of the one or more battery packs that relates to related to charge-discharge cycles by comparing an estimated SOH estimated by the estimation module with the reference SOH of the one or more battery packs; (h) analysing, by an analysing module, whether the degradation ratio is slower than a threshold degradation ratio or faster than the threshold degradation ratio; (i) reducing, by a regulation module, constant current (CC) phase to slow down degradation when the degradation ratio is higher than the threshold degradation ratio; and (j) increasing, by the regulation module the constant current (CC) phase to reduce charging time when the degradation is slower than the threshold degradation ratio.
[0013] In some embodiments, the one or more vehicle riding data comprises at least one of usage patterns of the one or more battery packs, temperature of the one or more battery packs, charge cycles of the one or more battery packs, one or more environmental conditions, or one or more rider behaviours.
[0014] In some embodiments, the data collection module is disposed on a control unit of the vehicle.
[0015] In some embodiments, the one or more battery packs include an Equivalent Circuit Model (ECM) with Direct Current Internal Resistance (DCIR) and resistance and capacitance values for calculating battery impedance data and monitoring degradation.
[0016] In some embodiments, the regulation module regulates the constant current (CC) phase based on state of charge SoC of the one or more battery packs, temperature of the one or more battery packs, SOH of the one or more battery packs, and impedance data of the one or more battery packs, and the one or more environmental conditions.
[0017] 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 preferred embodiments 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, and the embodiments herein include all such modifications.

BRIEF DESCRIPTION OF DRAWINGS
[0018] These and other features, aspects, and advantages of the present invention are illustrated in the accompanying drawings, throughout 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:
[0019] FIG. 1 illustrates a system for estimating state of health (SOH) of one or more battery packs in a vehicle according to embodiments as disclosed herein;
[0020] FIG. 2 is a block diagram of a cloud according to embodiments as disclosed herein; and
[0021] FIG. 3A and 3B illustrate a flow diagram of a method for estimating the state of health (SOH) of the one or more battery packs in the vehicle, according to the embodiments as disclosed herein.
[0022] It may be noted that to the extent possible, like reference numerals have been used to represent like elements in the drawing. Further, those of ordinary skill in the art will appreciate that elements in the drawing are illustrated for simplicity and may not have been necessarily drawn to scale. For example, the dimension of some of the elements in the drawing may be exaggerated relative to other elements to help to improve the understanding of aspects of the invention. Furthermore, the elements may have been represented in the drawing by conventional symbols, and the drawings may show only those specific details that are pertinent to the understanding of the embodiments of the invention so as not to obscure the drawing with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein.

DETAILED DESCRIPTION OF DRAWINGS
[0023] In the following description, for the purposes of explanation, various specific details are set forth in order to provide a thorough understanding of embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features. An individual feature may not address all of the problems discussed above or might address only some of the problems discussed above. Some of the problems discussed above might not be fully addressed by any of the features described herein.
[0024] The ensuing description provides exemplary embodiments only and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the disclosure as set forth.
[0025] The word “exemplary” and/or “demonstrative” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and/or “demonstrative” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, such terms are intended to be inclusive—in a manner similar to the term “comprising” as an open transition word—without precluding any additional or other elements.
[0026] Reference throughout this specification to “one embodiment” or “an embodiment” or “an instance” or “one instance” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
[0027] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed items.
[0028] The accompanying drawings are used to help easily understand various technical features and it should be understood that the embodiments presented herein are not limited by the accompanying drawings. As such, the present disclosure should be construed to extend to any alterations, equivalents, and substitutes in addition to those which are particularly set out in the accompanying drawings. Although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are generally only used to distinguish one element from another.
[0029] In view of the foregoing, an aspect herein provides a system for estimating State of Health (SOH) of one or more battery packs in a vehicle. The system includes a vehicle and a cloud. The vehicle includes one or more battery packs, a data collection module, and an aggression index module. The data collection module is configured to collect one or more vehicle riding data from the vehicle. The data collection module is further configured to collect at least one of battery energy capacity data or impedance data from the one or more battery packs. The aggression index (AI) identifying module is configured to identify an aggression index (AI) from the one or more vehicle riding data. The cloud includes a receiving module, a storage module, an estimation module, a degradation ratio identification module, an analysing module, and a regulation module. The receiving module is configured to receive (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of battery energy capacity data or impedance data from the data collection module. The storage module is operable by one or more processors and configured to store (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of energy capacity data or impedance data. The storage module includes a reference SOH of the one or more battery packs. The estimation module is operable by one or more processors and configured to estimate the SOH of the one or more battery packs during charging using (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of energy capacity data or impedance data. The degradation ratio identification module is operable by one or more processors and configured to identify a degradation ratio of the one or more battery packs by comparing an estimated SOH estimated by the estimation module with the reference SOH of the one or more battery packs. The degradation ratio is related to charge-discharge cycles of the one or more battery packs. The analysing module is operable by one or more processors and configured to analyse whether the degradation ratio is slower than a threshold degradation ratio or faster than the threshold degradation ratio. The regulation module is operable by one or more processors and configured to reduce constant current (CC) phase to slow down degradation when the degradation ratio is higher than the threshold degradation ratio. The regulation module is operable by one or more processors and configured to increase the CC phase to reduce charging time when the degradation is slower than the threshold degradation ratio.
[0030] Accordingly, there remains a need for an improved system and method for estimating state of health of one or more battery packs in the vehicle. Referring now to the drawings, and more particularly to FIGS. 1 to 3 where similar reference characters denote corresponding features consistently throughout the figures, there are shown preferred embodiments.
[0031] FIG. 1 illustrates a system 100 for estimating state of health (SOH) of one or more battery packs 104 in a vehicle 102 according to embodiments as disclosed herein. The system 100 for estimating state of health (SOH) of the one or more battery packs 104 includes the vehicle 102, and a cloud 110. As used herein, the SOH of the one or more battery packs 104 is defined as a measurement that indicates the level of degradation and remaining capacity of the one or more battery packs 104.
[0032] The vehicle 102 the one or more battery packs 104, a data collection module 106, and an aggression index (AI) identifying module 108. The vehicle 102 includes, but not limited to, an electric vehicle. In another embodiment, the electric vehicle includes, but not limited to, Battery Electric Vehicles (BEVs), Hybrid Electric Vehicles (HEVs), Plug-in Hybrid Electric Vehicles (PHEVs), and Fuel Cell Electric Vehicles (FCEVs).
[0033] In one embodiment, the one or more battery packs 104 include, but not limited to, a primary battery pack, and a secondary battery pack. In another embodiment, the primary battery pack and the secondary battery pack include, but not limited to, lithium-ion batteries, nickel-cadmium batteries, lead-acid batteries, alkaline batteries, and zinc-carbon batteries. In one embodiment, the the one or more battery packs 104 include an Equivalent Circuit Model (ECM) with Direct Current Internal Resistance (DCIR) and resistance & capacitance values for calculating battery impedance data and monitoring degradation.
[0034] The data collection module 106 is configured to collect one or more vehicle riding data from the vehicle 102. In one embodiment, the one or more vehicle riding data includes at least one of usage patterns of the one or more battery packs 104, temperature of the one or more battery packs 104, charge cycles of the one or more battery packs 104, one or more environmental conditions, or one or more rider behaviours.
[0035] The data collection module 106 is further configured to collect at least one of battery energy capacity data or impedance data from the one or more battery packs 104. In one embodiment, Battery energy capacity data of the one or more battery packs refer to information on the total amount of energy the one or more battery packs 104 can store and deliver. In another embodiment, Battery energy capacity data of the one or more battery packs 104 refer to information on the total amount of energy can store and deliver by the one or more battery packs 104 that helps to assess performance, efficiency, and potential degradation over time of the one or more battery packs 104.
[0036] The data collection module 106 and the aggression index (AI) identifying module 108 disposed on the vehicle 102. In one embodiment, the data collection module 106 and the aggression index (AI) identifying module 108 are disposed on a control unit of the vehicle 102. In one embodiment, the control unit may include, but not limited to, Battery Management System (BMS), Electronic control unit (ECU) and Vehicle Control Unit (VCU).
[0037] The cloud 110 is operable by one or more processors. The cloud 110 includes a receiving module 112, a storage module 114, an estimation module 116, a degradation ratio identification module 118, an analysing module 120, and a regulation module 122. The receiving module 112 is configured to receive (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of battery energy capacity data or impedance data from the data collection module 106. The cloud 110 performs data cleaning to remove noise or inaccuracies caused by environmental factors or sensor errors, ensuring reliable analysis.
[0038] In one embodiment, the receiving module 112 is configured to receive (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of battery energy capacity data or impedance data from the data collection module 106 via a wireless communication. In another embodiment, the wireless communication may include, but not limited to, cellular communication, satellite communication, infra-red communication, microwave communication, wireless fidelity (Wi-Fi), Bluetooth, ZigBee, General Packet Radio Service (GPRS), and Near Field Communication (NFC).
[0039] The storage module 114 operable by one or more processors and configured to store (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of energy capacity data or impedance data. The storage module 114 includes a reference SOH of the one or more battery packs 104. In one embodiment, the reference SOH of the one or more battery packs 104 is the data collected during the battery's development.
[0040] The estimation module 116 is operable by one or more processors and configured to estimate the SOH of the one or more battery packs 104 during charging using (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of energy capacity data or impedance data.
[0041] The degradation ratio identification module 118 operable by one or more processors and configured to identify a degradation ratio of the one or more battery packs 104 by comparing an estimated SOH estimated by the estimation module 116 with the reference SOH of the one or more battery packs 104. The degradation ratio is related to charge-discharge cycles of the one or more battery packs 104.
[0042] The analysing module 120 operable by one or more processors and configured to analyse whether the degradation ratio is slower than a threshold degradation ratio or faster than the threshold degradation ratio. In one embodiment, the threshold degradation ratio may be varied based on one or more parameters of the one or more battery packs 104. In one embodiment, the one or more parameters of the one or more battery packs 104 may include but not limited to, battery chemistry, capacity, time, and current.
[0043] The regulation module 122 is operable by one or more processors and configured to reduce constant current (CC) phase to slow down degradation when the degradation ratio is higher than the threshold degradation ratio. The regulation module 122 is operable by one or more processors and configured to increase the CC phase to reduce charging time when the degradation is slower than the threshold degradation ratio. The regulation module 122 regulates the constant current (CC) phase based on state of charge SoC of the one or more battery packs 104, temperature of the one or more battery packs 104, SOH of the one or more battery packs 104, and impedance data of the one or more battery packs 104, and the one or more environmental conditions.
[0044] The SOH estimation and the constant current phase regulation are implemented on the cloud 110, as the slow dynamics of capacity and impedance changes eliminate the need for real-time on-vehicle computation, and the cloud 110 efficiently handle large datasets across multiple vehicles, reducing the computational burden on the control unit of the vehicle 102.
[0045] FIG. 2 is a block diagram of a cloud 110 according to embodiments as disclosed herein. The cloud 110 includes processor(s) 206, and memory 202 coupled to the processor(s) 206. The processor(s) 206, as used herein, means any type of computational circuit, such as, but not limited to, a microprocessor, a microcontroller, a complex instruction set computing microprocessor, a reduced instruction set computing microprocessor, a very long instruction word microprocessor, an explicitly parallel instruction computing microprocessor, a digital signal processor, or any other type of processing circuit, or a combination thereof.
[0046] The memory 202 includes a plurality of modules stored in the form of executable program which instructs the processor 206 to perform the method steps illustrated in Fig 1. The memory 202 has following modules: the receiving module 112, the storage module 114, the estimation module 116, the degradation ratio identification module 118, the analysing module 120, and the regulation module 122.
[0047] The receiving module 112 is configured to receive (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of battery energy capacity data or impedance data from the data collection module 106. The storage module 114 is configured to store (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of energy capacity data or impedance data. The estimation module 116 is configured to estimate the SOH of the one or more battery packs 104 during charging using (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of energy capacity data or impedance data. The degradation ratio identification module 118 is configured to identify a degradation ratio of the one or more battery packs 104 by comparing an estimated SOH estimated by the estimation module 116 with the reference SOH of the one or more battery packs 104. The analysing module 120 is configured to analyse whether the degradation ratio is slower than a threshold degradation ratio or faster than the threshold degradation ratio. The regulation module 122 is configured to reduce constant current (CC) phase to slow down degradation when the degradation ratio is higher than the threshold degradation ratio. The regulation module 122 is configured to increase the CC phase to reduce charging time when the degradation is slower than the threshold degradation ratio.
[0048] Computer memory elements may include any suitable memory device(s) for storing data and executable program, such as read only memory, random access memory, erasable programmable read only memory, electrically erasable programmable read only memory, hard drive, removable media drive for handling memory cards and the like. Embodiments of the present subject matter may be implemented in conjunction with program modules, including functions, procedures, data structures, and application programs, for performing tasks, or defining abstract data types or low-level hardware contexts. Executable program stored on any of the above-mentioned storage media may be executable by the processor(s) 206.
[0049] FIG. 3A and 3B illustrate a flow diagram of a method 300 for estimating the state of health (SOH) of the one or more battery packs in the vehicle, according to the embodiments as disclosed herein. In step 302, the method 300 includes collecting one or more vehicle riding data from the vehicle 102. In one specific embodiment of the present disclosure, the one or more vehicle riding data are collected from the vehicle 102 by a data collection module 106.
[0050] In step 304, the method 300 includes collecting at least one of battery energy capacity data or impedance data from the one or more battery packs 104. In one specific embodiment of the present disclosure, the at least one of battery energy capacity data or impedance data collected from the one or more battery packs 104 by the data collection module 106.
[0051] In step 306, the method 300 includes identifying an aggression index (AI) from the one or more vehicle riding data. In one specific embodiment of the present disclosure, the aggression index (AI) is identified from the one or more vehicle riding data by an aggression index (AI) identifying module 108.
[0052] In step 308, the method 300 includes receiving (i) the one or more vehicle riding data with the aggression index (AI), and (ii) the at least one of battery energy capacity data or impedance data from the data collection module 106. In one specific embodiment of the present disclosure, (i) the one or more vehicle riding data with the aggression index (AI), and (ii) the at least one of battery energy capacity data or impedance data received from the data collection module 106 by a receiving module 112.
[0053] In step 310, the method 300 includes storing (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of energy capacity data or impedance data. The storage module 114 includes a reference SOH of the one or more battery packs 104. In one specific embodiment of the present disclosure, (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of energy capacity data or impedance data stored by a storage module 114.
[0054] In step 312, the method 300 includes estimating the SOH of the one or more battery packs (104) during charging using (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of energy capacity data or impedance data. In one specific embodiment of the present disclosure, the SOH of the one or more battery packs 104 is estimated during charging using (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of energy capacity data or impedance data by an estimation module 116.
[0055] In step 314, the method 300 includes identifying a degradation ratio of the one or more battery packs 104 by comparing an estimated SOH estimated by the estimation module 116 with the reference SOH of the one or more battery packs 104. The degradation ratio is related to charge-discharge cycles of the one or more battery packs 104. In one specific embodiment of the present disclosure, the degradation ratio of the one or more battery packs (104) is identified by comparing the estimated SOH estimated by the estimation module 116 with the reference SOH of the one or more battery packs 104 by a degradation ratio identification module 118.
[0056] In step 316, the method 300 includes analysing whether the degradation ratio is slower than a threshold degradation ratio or faster than the threshold degradation ratio. In one specific embodiment of the present disclosure, the degradation ratio is analyzed whether slower than the threshold degradation ratio or faster than the threshold degradation ratio by an analysing module 120.
[0057] In step 318, the method 300 includes reducing constant current (CC) phase to slow down degradation when the degradation ratio is higher than the threshold degradation ratio. In one specific embodiment of the present disclosure, the constant current (CC) phase is reduced to slow down degradation when the degradation ratio is higher than the threshold degradation ratio by a regulation module 122.
[0058] In step 320, the method 300 includes increasing the constant current (CC) phase to reduce charging time when the degradation is slower than the threshold degradation ratio. In one specific embodiment of the present disclosure, the constant current (CC) phase is increased to reduce charging time when the degradation is slower than the threshold degradation ratio by the regulation module 122.
[0059] The system 100 provides a solution for safeguarding the one or more battery packs 104 by monitoring the rider's charging habits. If the rider consistently travels during the day and charges the vehicle overnight, the system 100 recognizes the available charging duration and automatically selects optimized charging to protect the one or more battery packs 104. In cases where the rider needs to make a trip at night, the system 100 provides the rider with an option to override optimized charging and switch to normal charging as needed to reduce the charging time.
[0060] In the system 100, provides a more accurate and reliable State of Health (SOH) estimation by adapting to real-world charging and discharging patterns rather than relying on full charge-discharge cycles. The system 100 considers the one or more environmental conditions, temperature, self-discharge, and the one or more rider behaviours while performing SOH estimation and charging optimization which makes the system 100 accurate. Furthermore, SOH estimation and charging optimization are carried out on the cloud 110 to reduce burden on the control unit (e.g., VCU, ECU, BMS) of the vehicle 102 which makes the system 100 faster, and simpler.
[0061] The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the appended claims. Improvements and modifications may be incorporated herein without deviating from the scope of the invention. 
LIST OF REFERENCE NUMERALS
System 100.
Vehicle 102.
One or more battery packs 104.
Data collection module 106.
aggression index (AI) identifying module 108.
Cloud 110.
Receiving module 112.
Storage module 114.
Estimation module 116.
Degradation ratio identification module 118.
Analysing module 120.
Regulation module 122.
Memory 202.
Bus 204.
Processor 206.
, Claims:CLAIMS
I/We claim:
1. A system (100) for estimating State of Health (SOH) of one or more battery packs (104) in a vehicle (102), comprising:
the vehicle (102) comprises:
the one or more battery packs (104);
a data collection module (106) is configured to:
collect one or more vehicle riding data from the vehicle (102); and
collect at least one of battery energy capacity data or impedance data from the one or more battery packs (104); and
an aggression index (AI) identifying module (108) is configured to identify an aggression index (AI) from the one or more vehicle riding data; and
a cloud (110) operable by one or more processors and comprises:
a receiving module (112) is configured to receive (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of battery energy capacity data or impedance data from the data collection module (106);
a storage module (114) operable by one or more processors and configured to store (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of energy capacity data or impedance data, wherein the storage module (114) comprises a reference SOH of the one or more battery packs (104);
an estimation module (116) operable by one or more processors and configured to estimate the SOH of the one or more battery packs (104) during charging using (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of energy capacity data or impedance data;
a degradation ratio identification module (118) operable by one or more processors and configured to identify a degradation ratio of the one or more battery packs (104) by comparing an estimated SOH estimated by the estimation module (116) with the reference SOH of the one or more battery packs (104), wherein the degradation ratio is related to charge-discharge cycles of the one or more battery packs (104);
an analysing module (120) operable by one or more processors and configured to analyse whether the degradation ratio is slower than a threshold degradation ratio or faster than the threshold degradation ratio; and
a regulation module (122) operable by one or more processors and configured to reduce constant current (CC) phase to slow down degradation when the degradation ratio is higher than the threshold degradation ratio, wherein the regulation module (122) operable by one or more processors and configured to increase the CC phase to reduce charging time when the degradation is slower than the threshold degradation ratio.

2. The system (100) as claimed in claim 1, wherein the one or more vehicle riding data comprises at least one of usage patterns of the one or more battery packs (104), temperature of the one or more battery packs (104), charge cycles of the one or more battery packs (104), one or more environmental conditions, or one or more rider behaviours.

3. The system (100) as claimed in claim 1, wherein the data collection module (106) is disposed on a control unit of the vehicle (102).

4. The system (100) as claimed in claim 1, wherein the one or more battery packs (104) comprise an Equivalent Circuit Model (ECM) with Direct Current Internal Resistance (DCIR) and resistance & capacitance values for calculating battery impedance data and monitoring degradation.

5. The system (100) as claimed in claim 1, wherein the regulation module (122) regulates the constant current (CC) phase based on state of charge SoC of the one or more battery packs (104), temperature of the one or more battery packs (104), SOH of the one or more battery packs (104), and impedance data of the one or more battery packs (104), and the one or more environmental conditions.

6. A method (300) for estimating State of Health (SOH) of one or more battery packs (104) in a vehicle (102), comprising:
collecting, by a data collection module (106), one or more vehicle riding data from the vehicle (102);
collecting, by the data collection module (106), at least one of battery energy capacity data or impedance data from the one or more battery packs (104);
identifying, by an aggression index (AI) identifying module (108), an aggression index (AI) from the one or more vehicle riding data;
receiving, by a receiving module (112), (i) the one or more vehicle riding data with the aggression index (AI), and (ii) the at least one of battery energy capacity data or impedance data from the data collection module (106);
storing, by a storage module (114), (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of energy capacity data or impedance data, wherein the storage module (114) comprises a reference SOH of the one or more battery packs (104);
estimating, by an estimation module (116), the SOH of the one or more battery packs (104) during charging using (i) the one or more vehicle riding data with the aggression index (AI) and (ii) the at least one of energy capacity data or impedance data;
identifying, by a degradation ratio identification module (118), a degradation ratio of the one or more battery packs (104) by comparing an estimated SOH estimated by the estimation module (116) with the reference SOH of the one or more battery packs (104), wherein the degradation ratio is related to charge-discharge cycles of the one or more battery packs (104);
analysing, by an analysing module (120), whether the degradation ratio is slower than a threshold degradation ratio or faster than the threshold degradation ratio; and
reducing, by a regulation module (122), constant current (CC) phase to slow down degradation when the degradation ratio is higher than the threshold degradation ratio; and
increasing, by the regulation module (122) the constant current (CC) phase to reduce charging time when the degradation is slower than the threshold degradation ratio.

7. The method (300) as claimed in claim 6, wherein the one or more vehicle riding data comprises at least one of usage patterns of the one or more battery packs (104), temperature of the one or more battery packs (104), charge cycles of the one or more battery packs (104), one or more environmental conditions, or one or more rider behaviours.

8. The method (300) as claimed in claim 6, wherein the data collection module (106) is disposed on a control unit of the vehicle (102).

9. The method (300) as claimed in claim 6, wherein the one or more battery packs (104) comprise an Equivalent Circuit Model (ECM) with Direct Current Internal Resistance (DCIR) and resistance and capacitance values for calculating battery impedance data and monitoring degradation.

10. The method (300) as claimed in claim 6, wherein the regulation module (122) regulates the constant current (CC) phase based on state of charge SoC of the one or more battery packs (104), temperature of the one or more battery packs (104), SOH of the one or more battery packs (104), and impedance data of the one or more battery packs (104), and the one or more environmental conditions.