TECHNICAL FIELD
The present disclosure relates to the field of batteries. More particularly, it relates to a system for predictive maintenance of a battery.

BACKGROUND
Background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0003] Electric vehicle is projected to be a $1.5 trillion industry by 2025. Accompanying this, would be the heavy production of battery packs or energy storage system, the most integral component of any electric vehicle. Battery packs are the power house of any electric vehicle and ensuring that it always remains in the healthiest state is important for ensuring range, feasibility and proper utility for any electric vehicle.
[0004] However, just like any non-conventional vehicle that requires maintenance for its engine, an electric vehicle too requires some maintenance for its battery pack/ battery, though the frequency of such maintenance in electric vehicles is significantly lower.
[0005] A battery comprise one or more sets of cells, a cell having an anode (-) and a cathode (+) and an electrolyte between the two. A separator to keep the anode and the cathode may also be used. The cathode and anode (the positive and negative sides at either end of a traditional battery) are hooked up to an electrical circuit which needs to be supplied with electricity.
[0006] The chemical reactions in the battery causes a build-up of electrons at the anode, resulting in an electrical difference between the anode and the cathode. Since electrons repel each other, they try to move to a place with fewer electrons. In a battery, such a place is the cathode. But the electrolyte keeps the electrons from going straight from the anode to the cathode within the battery. When the circuit is closed (a wire connects the cathode and the anode) the electrons will be able to get to the cathode via the circuit, thereby supplying electricity to the circuit.
[0007] However, these electrochemical processes change the chemicals in anode and cathode to make them stop supplying electrons finally and the battery is considered as ‘discharged’. So there is a limited amount of power available in a battery. If the battery is ‘rechargeable’ electric power can be supplied to the battery so as to cause the electrochemical processes to happen in reverse. Thereafter, the anode and cathode are restored to their original state and can again provide full power and the battery is said to be ‘recharged’.
[0008] A lithium-ion battery (LIB) or Li-ion battery is a type of rechargeable battery in which lithium ions move from the negative electrode to the positive electrode during discharge and back when charging. Li-ion batteries use an intercalated (layered) lithium compound as one electrode material, compared to the metallic lithium used in a non-rechargeable lithium battery. Lithium-ion batteries are common rechargeable batteries for portable electronics, with a high energy density, tiny memory effect and low self-discharge. LIBs are also growing in popularity for military, battery electric vehicle and aerospace applications.
[0009] As said, a battery usually comprises a number of cells. A cell is a basic electrochemical unit of the battery that contains the electrodes, separator, and electrolyte. Hence a battery or a battery pack is a collection of cells or cell assemblies, with housing, electrical connections, and possibly electronics for control and protection. For rechargeable cells (that constitute a rechargeable battery such as a lithium-ion battery), the term cathode designates the electrode where reduction is taking place during the discharge cycle. For lithium-ion cells the positive electrode ("cathode") is the lithium-based one.
[0010] Batteries are often used to supply main/standby electrical power to critical equipment. For example, computers rely upon batteries in event main power fails. Electrical substations include battery systems to provide direct current (DC) power to protection relays, circuit breaker control circuits, and other low-power control, monitoring and indication devices in the event of a power system fault or during circuit reconfiguration.
[0011] Hence it is important for such systems, that batteries are functional when required as their failure at a time when they are expected to function optimally can be catastrophic. For instance, if a battery stopped delivering power to an electric vehicle due to any technical issue, then the vehicle would come to a halt, thereby creating immediate customer dissatisfaction & inconvenience and may subsequently impact the brand image of the electric vehicle providers.
[0012] There is thus a need in the art for a system that enables predictive maintenance of a battery so that it functions optimally when it is expected to.
[0013] Patent application US 2009/0009183 A (System and method for predictive maintenance of a battery assembly using temporal signal processing) elaborates upon a method of monitoring a battery assembly by obtaining a number of a monitored parameter samples; generating a temporal sequence of monotonically increasing values of the monitored parameter samples; and analyzing the values for an indication of a trend in the monitored parameter toward one of an upper operational boundary or a lower operational boundary to predict a fault condition of the battery assembly.
[0014] The method however relies upon measurement of absolute parameters such as impedance that may be difficult to measure or may not reflect accurately upon the actual condition of a battery. Also, it does not indicate how to maintain or fix the battery once the need for predictive maintenance is identified.
[0015] Patent Application ES2338091 (A1) titled ‘Método de mantenimientopredictivo de baterías’ (Predictive maintenance method for batteries) elaborates upon establishing acceptance and rejection criteria for a battery and then using advanced statistical methods based on the values of the impedance of the battery to determine time expected for the battery to reach a rejection criteria to establish a predictive maintenance plan to ensure that the useful life of the battery is greater than the established inspection period.
[0016] The method relies upon complex statistical methods based upon impedance values of the battery. Further, it does not determine/mention steps to fix/maintain the battery after the needs for predictive maintenance identified.
[0017] Hence there is a need in the art for a method that can be used for all rechargeable batteries, relies upon simple measurements and analysis thereof to determine when predictive maintenance is needed, and also suggests steps to maintain or fix the battery after a need for predictive maintenance has been identified.

OBJECTS OF THE PRESENT DISCLOSURE
[0018] Some of the objects of the present disclosure, which at least one embodiment herein satisfies are as listed herein below.
[0019] It is an object of the present disclosure to provide a system to monitor a battery.
[0020] It is another object of the present disclosure to provide a system to determine loose connections of wire, SOH, SOC of the battery.
[0021] It is another object of the present disclosure to provide a system to facilitate predictive maintenance of a battery.
[0022] It is another object of the present disclosure to provide an accurate, fast, efficient, cost effective and simple system.
[0023] These and other objects of the present invention will become readily apparent from the following detailed description taken in conjunction with the accompanying drawings.

SUMMARY
[0024] The present disclosure relates to the field of batteries. More particularly, it relates to a system for predictive maintenance of a battery.
[0025] In an aspect, present disclosure elaborates upon a system that may enable early prediction of the required maintenance of batteries, especially, rechargeable batteries such as Lithium ion batteries. The system may use real-time monitoring of battery status and, further, leverage data collected to identify systematic divergence of one or more parameters of the battery to predict whether maintenance of battery is required and an approximate time horizon for the same.
[0026] In an aspect, the system may comprise a battery management unit / BMU (also referred to as battery management system (BMU)), a control unit, where the BMS may be configured to continuously receive, in real-time, battery data from the battery and, further, transmit the battery data to a control unit, where the control unit may comprise a data-logger and a server. The battery data may be transmitted to the data logger that may, in turn, transmit the battery data to the server using an appropriate communication unit/ communication means such as Internet or mobile data from a telecom network or BlueTooth or WiFi or any other communication module. As can be readily understood, the BMU may be coupled to the control unit through the communication means.
[0027] In an aspect, an initial battery component calibration may be performed. This may ensure proper balancing of the cells of the battery and calibration of various values (for instance voltage) for the battery to function properly.
[0028] In an aspect, once the data-logger transfers the battery data to the server, proposed system may utilize various data pre-processing techniques to sort and clean raw data, and for detailed data-analysis, to proactively determine any battery maintenance related issues.
[0029] In an aspect, the proposed system may focus on possible failure i.e. shut down of the battery / connected BMS. As can be understood, if the cells in the battery are fully balanced to start with, i.e. calibrated and their voltage and capacity trend under charging/discharging are within recommended/expected range, then a divergence in cells’ voltages can be due to loose electrical connections in one or more of the cells experiencing such divergence, or due to increase in roughness at surface of a cell’s electrodes, these symptoms being indicative of a potential maintenance issue. The proposed system uses this divergence data to determine if the battery needs maintenance.

BRIEF DESCRIPTION OF THE DRAWINGS
[0030] The accompanying drawings are included to provide a further understanding of the present disclosure, and are incorporated in and constitute a part of this specification. The drawings illustrate exemplary embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure.
[0031] The diagrams are for illustration only, which thus is not a limitation of the present disclosure, and wherein:
[0032] FIGs. 1A-1C illustrate exemplary block diagrams of the proposed system to elaborate its working in accordance with an exemplary embodiment of the present disclosure.
[0033] FIG. 2 illustrates exemplary functional units of control unit of the proposed system in accordance with an exemplary embodiment of the present disclosure
[0034] FIG. 3A-3G illustrate exemplary experimental results using the proposed system in accordance with an exemplary embodiment of the present disclosure
[0035] FIG. 4 illustrates empirical quantification of battery data generated to determine whether battery maintenance is needed in accordance with an exemplary embodiment of the present disclosure.
[0036] FIG. 5 illustrates a method for predictive maintenance of a battery in accordance with an exemplary embodiment of the present disclosure.

DETAILED DESCRIPTION
[0037] In the following description, numerous specific details are set forth in order to provide a thorough understanding of embodiments of the present invention. It will be apparent to one skilled in the art that embodiments of the present invention may be practiced without some of these specific details.
[0038] Embodiments of the present invention may be provided as a computer program product, which may include a machine-readable storage medium tangibly embodying thereon instructions, which may be used to program a computer (or other electronic devices) to perform a process. The machine-readable medium may include, but is not limited to, fixed (hard) drives, magnetic tape, floppy diskettes, optical disks, compact disc read-only memories (CD-ROMs), and magneto-optical disks, semiconductor memories, such as ROMs, PROMs, random access memories (RAMs), programmable read-only memories (PROMs), erasable PROMs (EPROMs), electrically erasable PROMs (EEPROMs), flash memory, magnetic or optical cards, or other type of media/machine-readable medium suitable for storing electronic instructions (e.g., computer programming code, such as software or firmware).
[0039] Various methods described herein may be practiced by combining one or more machine-readable storage media containing the code according to the present invention with appropriate standard computer hardware to execute the code contained therein. An apparatus for practicing various embodiments of the present invention may involve one or more computers (or one or more processors within a single computer) and storage systems containing or having network access to computer program(s) coded in accordance with various methods described herein, and the method steps of the invention could be accomplished by engine s, routines, subroutines, or subparts of a computer program product.
[0040] If the specification states a component or feature “may”, “can”, “could”, or “might” be included or have a characteristic, that particular component or feature is not required to be included or have the characteristic.
[0041] As used in the description herein and throughout the claims that follow, the meaning of “a,” “an,” and “the” includes plural reference unless the context clearly dictates otherwise. Also, as used in the description herein, the meaning of “in” includes “in” and “on” unless the context clearly dictates otherwise.
[0042] The recitation of ranges of values herein is merely intended to serve as a shorthand method of referring individually to each separate value falling within the range. Unless otherwise indicated herein, each individual value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g. “such as”) provided with respect to certain embodiments herein is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention otherwise claimed. No language in the specification should be construed as indicating any non-claimed element essential to the practice of the invention.
[0043] Groupings of alternative elements or embodiments of the invention disclosed herein are not to be construed as limitations. Each group member can be referred to and claimed individually or in any combination with other members of the group or other elements found herein. One or more members of a group can be included in, or deleted from, a group for reasons of convenience and/or patentability. When any such inclusion or deletion occurs, the specification is herein deemed to contain the group as modified thus fulfilling the written description of all groups used in the appended claims.
[0044] Exemplary embodiments will now be described more fully hereinafter with reference to the accompanying drawings, in which exemplary embodiments are shown. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. These embodiments are provided so that this disclosure will be thorough and complete and will fully convey the scope of the invention to those of ordinary skill in the art. Moreover, all statements herein reciting embodiments of the invention, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include both currently known equivalents as well as equivalents developed in the future (i.e., any elements developed that perform the same function, regardless of structure).
[0045] The present disclosure relates to the field of batteries. More particularly, it relates to a system for predictive maintenance of a battery.
[0046] According to an aspect the present disclosure pertains to asystem for predictive maintenance of a battery, wherein the system can include: a battery management unit (BMU) adapted to be operatively coupled to a battery comprising one or more cells, and configured to receive battery data from the battery, and correspondingly generate a first set of data packets; and a control unit operatively coupled to the battery management unit, and can be including one or more processors with a memory, the memory storing instructions executable by the one or more processors and configured to: receive the first set of data packets from the BMU; extract a second set of data packets from the received first set of data packets, wherein the second set of data packets are indicative of one or more parameters of the battery; determine divergence in at least one of the one or more parameters of the battery, based on a comparison of the second set of data packets with a first dataset, wherein the first dataset can include one or more set of data packets associated with pre-determined ranges of the one or more parameters of the battery; and determine, a time-duration, based on the determined divergence, and correspondingly generate a set of maintenance signals, wherein the set of maintenance signals can be indicative of one or more maintenance actions to be performed, after the determined time duration, on any or a combination of the battery and the BMU.
[0047] In an embodiment, the control unit can be configured to determine the divergence within a pre-determined time period.
[0048] In an embodiment, the one or more parameters can be any or a combination of voltage, current, temperature, charge capacity, state of charge, state of health and power of battery.
[0049] In an embodiment, the control unit can be configured to generate, when the divergence exceeds a threshold limit, a set of warning signals, wherein the set of warning signals can be indicative of one or more defects in any or a combination of the battery and the BMU.
[0050] In an embodiment, the one or more defects can include any or a combination of loose connection of wire, broken wire, a short-circuit condition, over-heating, a fault in at least one of the one or more cell, and a fault in battery management unit.
[0051] In an embodiment, the BMU can include one or more sensors to monitor the one or more parameter of the battery.
[0052] In an embodiment, the BMU can be communicatively coupled, through a communication unit, to the control unit.
[0053] In an embodiment, the communication unit can include any or a combination of a GSM module, data cable, Bluetooth, wired network, Li-Fi module, and Wi Fi module, Amazon AWS, and MongoDB.
[0054] In an embodiment, the system can be configured to monitor rate of flow of the first data packets from the BMU to the control unit, and correspondingly generate the set of warning signals when monitored rate of flow of the first data packets is less than a pre-determined rate.
[0055] In an embodiment, the battery can include any or a combination of Lithium-ion battery and rechargeable battery.
[0056] According to another aspect the present disclosure pertains to a method for predictive maintenance of a battery, wherein the method can include:receiving, at a battery management unit (BMU) adapted to be operatively coupled to the battery comprising one or more cells, battery data from the battery, and correspondingly generate a first set of data packets;receiving, at one or more processors of a control unit, the first set of data packets from the BMU; extracting, at the one or more processors, a second set of data packets from the received first set of data packets, wherein the second set of data packets can be indicative of one or more parameters of the battery; determining, at the one or more processors, divergence in at least one of the one or more parameters of the battery, based on a comparison of the second set of data packets with a first dataset, wherein the first dataset can include set of pre-determined ranges of the one or more parameters of the battery; and determining, at the one or more processors, a time-duration, based on the determined divergence, and correspondingly generate a set of maintenance signals, and wherein the set of maintenance signals can be indicative of one or more maintenance actions to be performed, after the determined time duration, on any or a combination of the battery and the BMU.
[0057] FIGs. 1A-1C illustrate exemplary block diagrams of the proposed system to elaborate its working in accordance with an exemplary embodiment of the present disclosure.
[0058] In an embodiment, FIG. 1A illustrates an exemplary overall architecture of the proposed system 100. In an embodiment, the proposed system 100 can include a battery management unit (also, referred to as BMU, battery management system, BMS) 104 and a control unit 110, where the BMU 104 can be adapted to be operatively coupled to a battery 102 that can be comprising one or more cells 112-1, 112-2… 112-N (also, collectively referred to as cells 112, and individually referred to as cell 112). In an illustrative embodiment, the battery 102 can be any or a combination of Lithium-ion battery and rechargeable battery. In an embodiment, the control unit 110 can include a data logger 106 and a server 108. In an illustrative embodiment, the BMU 104 can include one or more sensors to monitor battery 102. In another illustrative embodiment, the BMU 104 can act as a charger and, hence, can be utilized in charging of the battery 102. In yet another illustrative embodiment, the proposed system 100 can include a charger (not shown) distinct from the BMS 104, which can be utilized for charging the battery 102.
[0059] In an illustrative implementation, the BMS 104 can be any electronic system that can manage a rechargeable battery, such as, but not limited to, protecting the battery 102 from operating outside a safe operating area, monitoring state of the battery 102, calculating secondary data, reporting the data, controlling environment, such as, temperature inside/ around the battery 102, authenticating the battery 102 and / or balancing the cells 112 associated with the battery 102. Further, the BMS 104 can be capable of the following functionalities:
SOC Determination: State of charge (SoC) is the level of charge of an electric battery 102 relative to its capacity. In a battery electric vehicle (BEV), hybrid vehicle (HV), or plug-in hybrid electric vehicle (PHEV), SoC for the battery 102 is the equivalent of a fuel gauge.
SOH Determination: The State of Health (SOH) is a measure of a battery's capability to deliver its specified output.
In the proposed system 100, the BMS 104 used or built for accommodating the battery 102 should be capable of SOC determination and SOH determination.
[0060] In an embodiment, the BMU 104 can include one or more sense wires and can be communicatively coupled, through a communication unit, to the control unit 110, where the communication unit can include any or a combination of a GSM module, data cable, Bluetooth, wired network, Li-Fi module, and Wi Fi module.
[0061] In an illustrative embodiment, the battery 102 may provide its performance and health data (also, referred to as battery data, herein) to the BMS 104, where the BMS 104 can be configured to receive the battery data in real-time and provide same to the data-logger 106. The data-logger 106 can transmit the battery data to the server 108. In an embodiment, the proposed system 100 can include a control unit 110 configured at a server 108, or in a cloud remote from the data-logger 106 and can be configured to receive battery data using appropriate communication technologies such as GSM, GPRS, Wifi, BlueTooth, Internet etc., the data-logger 106 being likewise configured to transmit battery data using the technologies. In another embodiment, the proposed system 100 can include a data-logger 106 distinct from the control unit 110, and the control unit 110 can be configured to process the battery data transmitted from the data-logger 106.
[0062] In an illustrative implementation, the battery 102 of the vehicle can be integrated with the data logger 106 or any communication module 106 capable of receiving, storing and transmitting the battery data detected or analysed by the BMS 104, through a communication network. Some of the examples of the communication network include a GSM chip with a sim card integrated with the communication module to transmit the data stored to a server 108 through a cellular data network. The communication module 106 can, further, include a location tracking system capable of analyzing and tracking the real time geolocation and time information. In an embodiment, the communication module 106 can be a module capable of receiving feeds from Global Positioning System (GPS) or any navigation system. The data such as the SOC, SOH, GPS co-ordinates with time periods shall be sent to the server 108 via the communication module 106.
[0063] In an illustrative embodiment, the proposed system 100 can process the battery data and, further, generate any or a combination of a set of warning signals and a set of maintenance signals. In an embodiment, the maintenance signal can include information as to how soon maintenance of the battery 102 is required, as well as any other data that may aid in the proper maintenance of the battery 102.
[0064] In an embodiment, FIG. 1B illustrates battery data transmission in the proposed system 100.
[0065] In an embodiment, the BMU 104 can be configured to receive the battery data from the battery, and correspondingly generate a first set of data packets. In an embodiment, the battery data can include one or more parameters of the battery 102, and a time associated with receiving of the battery data. In an embodiment, the control unit 110 can be configured to receive the first set of data packets from the BMU 104. In another embodiment, the control unit 110 can be configured to extract a second set of data packets from the received first set of data packets, such that the second set of data packets can be indicative of one or more parameters of the battery 102, where the one or more parameters can be any or a combination of voltage, current, temperature, charge capacity, state of charge, state of health, power, and the likes.
[0066] In an embodiment, the control unit 110 can be configured to determine divergence in value of at least one of the one or more parameters, based on a comparison of the second set of data packets with a first dataset, where the first dataset can be including one or more set of data packets associated with pre-determined ranges of the one or more parameters. In another embodiment, the control unit 110 can be configured to generate a set of warning signals, when the divergence exceeds a threshold limit, such that the set of warning signals can be indicative of one or more defects in any or a combination of the battery 102 and the BMU 104, such as, but not limited to, any or a combination of loose connection of wire, broken wire, a short-circuit condition, over-heating, a fault in at least one of the one or more cell, and a fault in battery management unit.
[0067] In an exemplary embodiment, battery data of a LFP battery (Lithium Iron Phosphate cells based battery) 102 can be sensed through the one or more sensors and correspondingly transmitted, through the sense wire, to the BMS 104, and the BMS 104 can in turn use a communication wire to provide the battery data to the data-logger 106 that may in turn use a GSM network to provide the battery data to the server 108 that can be configured in a remote location.
[0068] In an embodiment, FIG. 1C illustrates real-time monitoring of the battery data through the proposed system 100.
[0069] As illustrated at FIG.1C, the battery data can be acquired in real-time through the BMS 104, the received battery data can be stored in the data logger 106 and further, can be communicated to the server 108 from the data-logger 106 via a communication means. In this manner, continuous and real-time data monitoring of the one or parameters of the battery can be done.
[0070] In an embodiment, the proposed system 100 can focus on possible failure i.e. shut down of the battery 102 / connected BMS 104. As can be understood, if the cells 112 in the battery 102 are fully balanced to start with, i.e. calibrated and their voltage and capacity trend under charging/discharging are within recommended/expected range, then a divergence in cells’ voltages can be due to loose electrical connections in one or more of the cells 112 experiencing such divergence, or due to increase in roughness at surface of a cell’s electrodes, these symptoms being indicative of a potential maintenance issue. The proposed system 100 can uses the divergence data to determine if the battery 102 needs maintenance.
[0071] Further, the proposed system 100 can be configured to maintain an operative communication in between the server 108 and an appropriate database such as Amazon AWS server and MongoDB database.
[0072] FIG. 2 illustrates exemplary functional units of control unit of the proposed system in accordance with an exemplary embodiment of the present disclosure
[0073] As illustrated, the control unit 110 can include one or more processor(s) 202. The one or more processor(s) 202 can be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that manipulate data based on operational instructions. Among other capabilities, the one or more processor(s) 202 are configured to fetch and execute computer-readable instructions stored in a memory 204 of the control unit 110. The memory 204 can store one or more computer-readable instructions or routines, which may be fetched and executed to create or share the data units over a network service. The memory 204 can include any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as EPROM, flash memory, and the like.
[0074] In an embodiment, the control unit 110 can also include an interface(s) 206. The interface(s) 206 may include a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, storage devices, and the like. The interface(s) 206 may facilitate communication of the control unit 110 with various nodes and devices coupled to the control unit 110. The interface(s) 206 may also provide a communication pathway for one or more components of the control unit 110. Examples of such components include, but are not limited to, processing engine(s) 208 and database 210.
[0075] In an embodiment, the processing engine(s) 208 can be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing engine(s) 208. In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing engine(s) 208 may be processor executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing engine(s) 208 may include a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing engine(s) 208. In such examples, the control unit 110 can include the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to control unit 110 and the processing resource. In other examples, the processing engine(s) 208 may be implemented by electronic circuitry. The database 210 can include data that is either stored or generated as a result of functionalities implemented by any of the components of the processing engine(s) 208.
[0076] In an embodiment, the processing engine(s) 208 can include a data receiving engine 212, a divergence determining engine 214, a maintenance signal generating engine 216, and other engine(s) 220. The other engine(s) 220 can implement functionalities that supplement applications or functions performed by the control unit 110 or the processing engine(s) 208.
Data Receiving Engine 212
[0077] In an aspect data receiving engine 212 can, based upon instructions stored in memory 204, enable the one or more processors 202 of the control unit 110 to receive raw real-time battery data (from a data-logger 106 or any other suitable device configured to perform same function) and can clean the raw battery data for further analysis, and provide the cleaned battery data to the divergence determining engine 214. In an exemplary embodiment, the data receiving engine 212 can provide the cleaned battery data to the divergence determining engine 214 using an appropriate communication network. In another embodiment, the data receiving engine 212 can store the cleaned battery data on a storage medium such as a secure digital (SD) card from which divergence determining engine 214 can retrieve same.
[0078] The raw battery data can include one or more parameters of the battery 102 and a time instant when the battery data is received by the BMS 104. The clean battery data may likewise include the value of one or more parameters of the battery 102 and corresponding time instants of their receipts by the BMS 104.
[0079] In an exemplary embodiment, to ensure that the data receiving engine 208 receives the correct battery data, cells 112 of the battery 102 can be properly calibrated and balanced in an initial step before staring the process of monitoring of the battery 102 by the BMS 104 and further processing as being described herein.
[0080] In an embodiment, the data receiving engine 212 can, based upon instructions stored in memory 206, enable the one or more processors 202 of the control unit 110 to perform different functions of the data receiving engine 212 as elaborated above. In an exemplary embodiment, the data receiving engine 212 can include one or more processors 202 dedicatedly used to perform functionalities of the data receiving engine 212 as elaborated.
Divergence Determining Engine 214
[0081] In an embodiment, the divergence determining engine 214 can, based upon instructions stored in memory 204, enable the one or more processors 202 of the control unit 110 to receive the cleaned battery data from the data logger 206 and, consequently determine divergence of at least one of the one or more parameters associated with the battery data received over a temporal sequence for a pre-determined time period, and likewise for the at least one of the one or more such parameters being monitored in real-time by the BMS 104. The pre-determined time period can be set in the database 210 and retrieved from there as required. The divergence can be calculated with respect to /from pre-determined ranges of the one or more parameters, when the the battery 102 is properly calibrated and the cells 112 are properly balanced.
[0082] In another aspect, the divergence determining engine 214 can retrieve, value of the at least one of the one or more parameters as well as a time instant when the at least one of the one or more such parameters is being received by the BMS 104, from the battery data to establish the temporal sequence of values of the at least one of the one or more parameters (and likewise, that of values of other parameters) received by the divergence determining engine 214.
[0083] In an embodiment, the divergence determining engine 214 can, based upon instructions stored in the memory 206, enable the one or more processors 202 of the control unit 110 to perform different functions of the divergence determining engine 214 as elaborated above. In an exemplary embodiment, the divergence determining engine 214 can include one or more processors 102 dedicatedly used to perform functionalities of the divergence determining engine 214 as elaborated.
Maintenance Signal Generating Engine 216
[0084] In an embodiment, the maintenance signal generating engine 216 can determine whether the divergence as determined above for at least one of the one or more parameters of the battery 102 exceeds a threshold limit. In an embodiment, the threshold limit can be stored in the database 210 and, further, can be retrieved the maintenance signal generating engine 216 as and when required, and the maintenance signal generating engine 216 can generate a set of maintenance signals accordingly. As can be readily understood the threshold limit can be a range of values, or an absolute value, as appropriate in accordance with the proposed system 100.
[0085] In an exemplary embodiment, for instance, the at least one of the one or more parameters can be voltage of the cells 112 configured in the battery 102, the pre-determined time period can be 30 seconds, and a pre-determined range of voltage can be 0.2 volts to 0.4 volts, which can be associated with voltage of cells 112. If, at any time during a segment of 30 seconds, the divergence of voltage of a cell 112 of the battery 102 having a plurality of such cells 112 is found to be more than 0.4 volts (from an initial value when the battery is calibrated and its cells balanced), the maintenance signal generating engine 216 can generate the set of maintenance signals asking for the immediate maintenance of the battery 102. The set of maintenance signals can include data associated with the determined divergence to enable a user to quickly determine the cell 112 that needs maintenance and any other relevant aspect.
[0086] In another embodiment, the maintenance signal generating engine 216 can determine when the divergence as determined exceeds for a combination of the one or more parameters exceed the threshold limit, and for such set/ combination of parameters, and generate the set of maintenance signals accordingly. The combination of such parameters and corresponding pre-determined ranges can be stored in the database 210, and can be retrieved by the maintenance signal generating engine 216.
[0087] In an exemplary embodiment, for instance, the at least one of the one or more parameters can be a combination of voltage of a cell 112 of the battery 102, and total current being delivered by the battery 102. In an embodiment, the pre-determined time period can be 30 seconds and the pre-determined range of voltage can be 0.2 volts to 0.4 volts which can be associated with voltage of cells 112 and 0.3 amperes to 0.6 amperes can be pre-defined range for the total current. If at any time during a segment of 30 seconds, the divergence of voltage of a cell 112 of the battery 102 having a plurality of such cells 112 is more than 0.4 volts, and during the same time segment the divergence of current is above 0.6 amperes, then the maintenance signal generating engine 216 can generate the set of maintenance signals asking for the battery 102 to be maintained immediately.
[0088] In an embodiment, likewise, an absolute threshold limit, as well as a range associated with the threshold limit, and continuous time which for which the threshold limit is exceeded can be stored in the database 210 and the maintenance signal generating engine 216 can generate maintenance signals accordingly. For instance, an absolute threshold limit can be total current falling below 3 Amperes for a continuous period of one minute. In the event such an incident occurs, a set of maintenance signals can be generated accordingly.
[0089] As can be readily appreciated, any or a combination of one or more parameters pertaining to the battery 102 and associated absolute values or divergence determined over a pre-determined time period as retrievable from the battery data can be used by the maintenance signal generating engine 216 to trigger the set of maintenance signals.
Other Engines 220
[0090] In an embodiment, the proposed system 100 can include other engines 220 that can implement functionalities that supplement applications or functions performed by the proposed system 100 as described here.
Database 210
[0091] In an aspect, the database 210 can include data that is either provided by users /administrators of the proposed system 100 or generated as a result of functionalities implemented by any of the components of the proposed system 100. For instance, various threshold limits, divergence ranges, pre-determined time periods can be stored in database 216 and later, can be retrieved by other engines 220 as required.
[0092] In an embodiment, the database 216 can as well store values of the one or more parameters when the battery 102 is fully calibrated and the cells 112 are balanced so as to determine the divergence accurately from such values. The user/administrator of the proposed system 100 can provide values, such as, but not limited to, divergence ranges, pre-determined time periods, and threshold limits using appropriate user interfaces.
[0093] Though functions of all the engines is associated with generation of the set of maintenance signals, but it can be appreciated by a person skilled in the art that the engines can work in a similar way for generating the set of warning signals.
[0094] Although the proposed system 100 has been elaborated as above to include all the main units and engines, it is completely possible that actual implementations can include only a part of the described engines/units or a combination of the described engines/units or a division of the described engines/units into sub-units in various combinations or sequences across multiple devices that can be operatively coupled with each other, including in the cloud or database and use appropriate communication channels. Further the engines/units can be configured in any sequence to achieve objectives elaborated. Also, it can be appreciated that proposed system 100 can be configured in a computing device (for instance a server) or across a plurality of computing devices operatively connected with each other, wherein the computing devices can be any of a computer, a laptop, a smart phone, an Internet enabled mobile device and the like. Therefore, all possible modifications, implementations and embodiments of where and how the proposed system 100 is configured are well within the scope of the present invention.
[0095] FIG. 3A-3G illustrate exemplary experimental results using the proposed system 100 in accordance with an exemplary embodiment of the present disclosure.
[0096] In an embodiment, various experiments are being carried out, associated with the proposed system 100, which is installed in a rechargeable or hybrid vehicle. In an illustrative implementation, battery installed in the vehicle is a Lithium-ion battery 102 including 16 Lithium Iron Phosphate (LFP) cells 112. Each cell 112 can have a capacity of 72 Ah and operating voltage range of 2.5 to 3.65 volt. Each cell 112 can be connected with a sense wire that can be, further, connected with the BMS 104. In an embodiment, the battery 102 can be operatively connected to the BMS 104 and the data-logger 106 for real-time battery health and performance data collection and monitoring.
[0097] Initially, the battery 102 can be fully calibrated and all the components of the proposed system 100 can be thoroughly checked to be fully functional. In an illustrative embodiment, all the 16 cells 112 of the battery 102 can be of same grading i.e. the cells 112 can have similar state of health (SOH) and similar energy storage capacity. All electrical connections from/to the battery 102 and electrical components the proposed system 100 can be checked. In any application where rechargeable batteries (lithium ion or any other batteries) are used, may require frequent calibration and maintenance based on the application and usage. Data analytics driven predictive maintenance is operationally efficient. In another illustrative embodiment, the battery 102 that has been graded with respect to the cells’ voltage and capacity will have similar voltage and internal resistance profile of all the cells 112.
[0098] In an embodiment, major connections in the proposed system 100 can be classified as: electrode’s connection, connections to BMS 104 using sense wires, BMS 104 to data-logger 106 connection, which can be connected using communication cable, GSM or network connectivity, and charger to battery 102 connections.
[0099] In case, the vehicle faces vibration then chance are that one or more connections will be loose if the sense wires are not spot welded to the electrodes of cells in the BMS 104. Therefore, leading to loose contacts in between cell’s electrodes and the wires or connector, which is also referred to as loose state of (electric) connections.
[00100] This definition could be further extended to BMS 104 and data-logger 106 electric connections. In an embodiment, sense-wire can be connected to the BMS 104 for enabling its functions, now, if the sense-wire is loosely connected to the cell 112, or a bolt is not connected well, then such connections can also be referred to as loose state of electric connection, as the contact is poor in between surfaces.
[00101] In another embodiment, if the BMS 104 to the data-logger 106 communication wire/port/pin(s) is/are broken or loosely connected or detached, it is also considered to be a loose state of connection.
[00102] In an embodiment, network connectivity is required to provide connectivity of the battery 102 with cloud, which can be provided through GSM. In case, the GSM antenna or GSM chip is malfunctioning or not working, it will also be considered to be a loose state of connection.In an embodiment, there can be only 2 cases when loose GSM connectivity can be observed – No network area, and GSM sim or antenna is malfunctioning or poorly connected.
[00103] In an embodiment, in case of GSM connectivity, two timestamps can be recorded with respect to the battery data – first one being actual time stamp when battery is being used, and second when being server/cloud timestamp when data is received by the server/cloud. In an implementation, loose GSM connectivity can lead to data-lag, which can be associated with a difference between the actual time stamp and the server/cloud time stamp. In an embodiment, the data-lag is defined as the late delivery of actual data to the server or cloud and the data-lag can be recovered once the GSM connectivity is restored or based-on the functions of the BMS 104 or the data-logger 106.
[00104] In an embodiment, there can be only 2 cases when loose GPS connectivity can be observed, which are either, no network area or enclosed space under GPS, or malfunctioning or loosely connected GPS chip or antenna Loose GPS connectivity. Loss of GPS connectivity can shut down location tracking and therefore, coordinates cannot be recorded. In an embodiment, once ‘loose GPS connectivity’ is identified, maintenance scheduled can be prepared to restore location tracking.
[00105] In an illustrative embodiment, the battery 102 can be charged using a charger of adequate specification. Be a slow charger or a fast charger, it should be connected through a connector/joint that can withstand the application and condition. When a connector is loosely connected then there are high chances of current/charge losses leading to relatively high time to charge. In some cases, loose connector may also result in short-circuiting of the BMS 104.
[00106] In an embodiment, as illustrated in FIG. 3A, in a first experiment, the battery data for multiple discharge-charge cycle can be received at the proposed system 100 using process and components, such as, the BMS 104 and the data-logger 106 as described above and the battery data showed expected and normal trends in term of voltages and capacity, hence, indicating all the cells 112 are adequately connected with sense wire, and the BMS 104 and the data-logger 106 are working fine.
[00107] In an embodiment, in a second experiment, electrical connections of the cell 112 fifteen (that is, the fifteenth cell 112 of the battery 102) can be loosened.
[00108] As can be seen from the table in FIG. 3B at 302, the fifteenth cell 112 (also referred to as cell 15, herein) with the loose connection at the electrodes showed significantly higher value of voltage in 30 seconds of monitoring under the experiment. In the beginning of the observation period, the cell 15 can be at a voltage of 3.38 Volts, and at the end of the observation period, the cell 15 can be at a voltage of 3.78 V, thereby indicating an overall variation of 0.4 volts over the observation period. Further, even variation between most sequential readings of the cell 15 are also observed to be high. For instance, at 304 the voltage is observed to be 3.58 V, just a second later, at 306 the voltage is observed to be 3.75 V and, at the next second, at 308 the voltage is observed to be 3.33 V. Other cells 112 exhibited a very steady voltage pattern with hardly any deviation over the same period.
[00109] Hence, due to loose contacts at electrodes of the cell 15, real-time voltage data of the cell 15 varied significantly over a temporal sequence during which such data is monitored.
[00110] In an embodiment, voltage values for the cell 15 (with loose connection) can be zero or outbound, if the cell 15 has completely lost contacts/ connections with the sense wire. In such a case, it can result in an impact to the nearest cells 112 as well, based on series or parallel connections.
[00111] In an embodiment, in a third experiment, electrical connections of the cell 112 thirteen (that is, the thirteenth cell 112 of the battery 102) can be loosened.
[00112] As can be seen from the table in FIG. 3C at 310, the thirteen cell 112 (also referred to as cell 13, herein) with the loose connection at the electrodes showed significantly lower value of voltage in 60 seconds of monitoring under the experiment. In the beginning of the observation period, the cell 13 can be at a voltage of 2.69 Volts, and at the end of the observation period, the cell 13 can be at a voltage of 2.54 Volts, thereby indicating an overall variation of 0.4 volts over the observation period. Further, even variation between most sequential readings of the cell 15 are also observed to be high. For instance, at 312 the voltage is observed to be 2.69 V, just a second later, at 314 the voltage is observed to be 3.03 V and, at the next second, at 316 the voltage is observed to be 2.69 V again. On the other hand, it can be observed that other cells 112 exhibited a very steady voltage pattern with hardly any deviation over the same period.
[00113] Hence, due to loose contacts at electrodes of the cell 13, real-time voltage data of the cell 13 varied significantly over a temporal sequence during which such data is monitored.
[00114] In an embodiment, in a fourth experiment, connections between the BMS 104 and the data logger 106 can be hampered.
[00115] As can be seen from the table in FIG. 3D at 320, values based on connections between the BMS 104 and the data logger 106 can be recorded. At 322, the battery data received from the BMS 104 can be recorded as zero values when the BMS 104 to the data logger 106 communication is broken, or the connections between the BMS 104 to the data logger 106 got loosened. At 324, when the BMS 104 to the data logger 106 connection is intact, values of the one or more parameters are recorded and found to be non-zero.
[00116] In an embodiment, in a fifth experiment, connections between the data logger 106 and GPS can be hampered.
[00117] As can be seen from the table in FIG. 3E at 330, values based on connections between the data logger 106 and GPS associated with the proposed system 100 are illustrated.In an embodiment, it can be observed that, at 330, values of coordinates, that is of latitudes and longitudes, are zero, even when rest of the data is coming.
[00118] In an embodiment, in a sixth experiment, values can be recorded in case of loose GSM connectivity.
[00119] As can be seen from the table in FIG. 3F, which shows the values recorded in case of loose GSM connectivity. In an embodiment, from 342 and 344, a large data-lag can be observed, which is approximated to be of 5 hours 20 minutes.
[00120] In an embodiment, in a seventh experiment, values can be recorded in case of loose charger to battery connection.
[00121] As can be seen from the table in FIG. 3G, at 352, as the value of current is zero, it can be observed that charging is stopped due to of loose connections between a charger (utilized for charging the battery 102) and the battery 102. At 354, it can be observed that as a charger of 15A is connected with the battery 102, a current of around 16A flows in the battery. At 356, it can be observed that, as the battery 102 gets fully charged, the voltages across the cell 112 stopped increasing, even when the charger is connected to the battery 102.At 358,it can be observed that the capacity of the cell 112 stopped increasing even when charger is still connected.
[00122] In an embodiment, once the loose state of connection is observed and identified via data analytics, a set of maintenance signals can be generated, which can be indicative of potential predictive maintenance steps needed to be taken. In an illustrative implementation, following tables provides predictive maintenance information for ‘state of loose connections’-

Connections of concern Context Analytical observations, if loose connections
Electrodes to BMS connection If the sense-wires are not or loosely connected to the cells’ electrodes Cells’ voltage for loosely connected cells will be outbound or uniquely different then the rest of cells.
BMS to Data-logger (DL) communication BMS to DL communication port or wire is loose or broken or not connected Zero entries will be recorded, if DL is working.
GPS connectivity If the GSM antenna or GSM chip is malfunctioning or enclosed space No coordinates will be recorded (i.e. zero latitude/longitude).
GSM connectivity If the GSM antenna or GSM chip is malfunctioning No data will be recorded
Possible data lag when network connectivity is recovered.
Charger to Battery connection Charging wire is broken or charger is incompatible. Cell voltages or capacity will not increase even though charger is connected.
Table 1

Connections of concern
Analytical observations, if loose connections
Schedule of predictive maintenance

1. Electrode’s to BMS connection
If the one or more cells’ voltages and capacity are recorded as zero, or one or more cells are out of the range for voltage Fix the sense-wire connection attached to both respective electrodes and BMS.

2. BMS to DL communication
If the battery usage data is recorded as zeros (when DL is functioning).
Or, the data is not being recorded (when Dl is off or malfunctioning).
BMS communication with DL is broken and mostly due to loose or disconnected communication cable
3. GSM connectivity
No data is coming however, battery is in use.
Or
data-lag is observed in the timestamps of use or server.
Collect the data from temporary storage such as SD card and fix the respective issue with the GSM antenna
4. GPS connectivity If the coordinates (latitude/longitude) values are not coming Real-time location tracking is stopped when GPS connectivity is disrupted, check the GPS antenna and connection as predictive maintenance

5. Charger to Battery connection
Battery is not getting charged even when charger is connected Understand the charger incompatibility, find out connection issues related to the charger and battery.

Table 2

[00123] FIG. 4 illustrates empirical quantification of battery data generated to determine whether battery maintenance is needed in accordance with an exemplary embodiment of the present disclosure.
[00124] As elaborated above, loose connections at electrodes of a cell 112 under observation can lead to a higher divergence over time of voltage being generated by the cell 112. In similar manner, based on observations with a battery 102, state of loose connections and corresponding need of maintenance can be empirically quantified, as shown in FIG.4. As can be readily understood, at a starting /initial stage, the battery 104 needs to be fully balanced/calibrated as mentioned above.
[00125] As illustrated in FIG. 4, if voltage variation of any cell 112 is up to 0.1 volts (with respect to a minimum cell voltage when cells 112 of the battery 102 are balanced) for about 30 seconds during the charging or discharging state of the battery 102 then that particular cell 112 may not need any maintenance, as shown at 402. Likewise, if variation is between 0.1 to 0.2 volts, no maintenance may be needed, as shown at 404. However, if voltage variation is between 0.2 to 0.4 volts, it indicates that the cell 112 is under loose state and electrical connections are loose, and so maintenance is needed soon, as shown at 406.
[00126] However, if voltage variation is more than 0.4 volt for about 30 seconds during the charging or discharging state of the battery then that particular cell is under loose state and electrical connections are very loose, leading to an immediate requirement of maintenance to avoid shutdown of the BMS 104 or the battery 102, as shown at 408.
[00127] For such variations to be used as being described herein to determine/predict maintenance requirement, the battery 102 should be fully-balanced and all the cells 112 should be of same grading. Further, the battery 102can operate either in charging or discharging mode.
[00128] In this manner, it can be tested and validated that if a cell’s voltage value diverges at a higher rate than the rest, it is an early sign of the loose state of connections at the electrodes of the particular cell 112 (i.e. one with higher divergence), starting with an initial stage of the cells 112 of the battery 102 being fully balanced.
[00129] In the example being described herein, time duration for monitoring cell voltages is 30 seconds. However, as can be readily appreciated, any pre-determined time duration can be used. Similarly, while herein the variation is clearly attributed to loose contact at electrodes of a cell 112, in other cases only a need for maintenance maybe generated and maintenance steps need further investigations.
[00130] As can be readily understood, similar tests can be done across various batteries and for each battery voltage variance thresholds as above can be found to determine whether a cell of the battery is in need of maintenance or not.
[00131] Further, while the above example uses voltage variation, it can be readily understood that variation in any other parameters of the battery or of its individual cells being monitored by the BMS 104 in real-time may similarly be used.
[00132] As known, a BMS 104 monitors state of a battery as represented by various parameters such as total voltage, voltages of individual cells, minimum and maximum cell voltage or voltage of periodic taps, average temperature, coolant intake temperature, coolant output temperature, or temperatures of individual cells, state of charge (SOC) or depth of discharge (DOD), to indicate the charge level of the battery, state of health (SOH), a measurement of the remaining capacity of the battery as % of the original capacity, temperature and other conditions.
[00133] Additionally, a BMS 104 can calculate values based on the above items, such as: maximum charge current as a charge current limit (CCL), maximum discharge current as a discharge current limit (DCL), charge [Ah] delivered or stored, total operating time since first use, and other parameters.
[00134] Any or a combination of above parameters can be monitored in real-time and a temporal sequence of their values generated and provided by the proposed system 100 with the help of the data-logger 106. In an embodiment, ranges of the one or more parameters and the threshold limits can be determined based upon experimental analysis as already elaborated and stored in the proposed system 100 (or be provided to it as required). The proposed system 100 can accordingly generate any or a combination of a set of warning signals and a set of maintenance signals that can in turn be provided to system operators as required. In case, maintenance is immediately required, a set of alarm signals may likewise be generated.
[00135] In this manner, the proposed system 100 can enable predictive maintenance of rechargeable batteries 102 so as to ensure their availability when required and with savings on resources and time. Battery failure can be minimized due to proactive maintenance and lifetime of the battery extended. The proposed system 100 can be well deployed in critical sectors where availability of power supply needs to be ensured.
[00136] FIG. 5 illustrates a method for predictive maintenance of a battery in accordance with an exemplary embodiment of the present disclosure.
[00137] As illustrated in FIG. 5, in an embodiment, the method for predictive maintenance of a battery 102 includes a step 502 of receiving, at a battery management unit (BMU) 104 adapted to be operatively coupled to the battery 102 comprising one or more cells 112, battery data from the battery 102, and correspondingly generate a first set of data packets.
[00138] In an embodiment, the method includes a step 504 of receiving,at one or more processors of a control unit 110, the first set of data packets from the BMU 104.
[00139] In an embodiment, the method includes a step 506 ofextracting, at the one or more processors, a second set of data packets from the received first set of data packets, where the second set of data packets can be indicative of one or more parameters of the battery 102.
[00140] In an embodiment, the method includes a step 508 ofdetermining, at the one or more processors, divergence in at least one of the one or more parameters of the battery 102, based on a comparison of the second set of data packets with a first dataset, wherein the first dataset can include set of pre-determined ranges of the one or more parameters of the battery 102.
[00141] In an embodiment, the method includes a step 510 ofdetermining, at the one or more processors, a time-duration, based on the determined divergence.
[00142] In an embodiment, the method includes a step 512 ofgenerating, at the one or more processors, a set of maintenance signals, where the set of maintenance signals can be indicative of one or more maintenance actions to be performed, after the determined time duration, on any or a combination of the battery and the BMU.
[00143] Though various embodiments of the disclosure are explained in terms of a battery, however, a person skilled in the art would appreciate that the proposed system 100 can also work equally efficiently when implemented with various energy storing and supplying elements such as, but not limited to, capacitor bank, fuel cell, solar cell/ panel, and all such implementations and embodiments are well within the scope of the present invention.
[00144] Thus, it will be appreciated by those of ordinary skill in the art that the diagrams, schematics, illustrations, and the like represent conceptual views or processes illustrating systems and methods embodying this invention. The functions of the various elements shown in the figures may be provided through the use of dedicated hardware as well as hardware capable of executing associated software. Similarly, any switches shown in the figures are conceptual only. Their function may be carried out through the operation of program logic, through dedicated logic, through the interaction of program control and dedicated logic, or even manually, the particular technique being selectable by the entity implementing this invention. Those of ordinary skill in the art further understand that the exemplary hardware, software, processes, methods, and/or operating systems described herein are for illustrative purposes and, thus, are not intended to be limited to any particular named.
[00145] While embodiments of the present invention have been illustrated and described, it will be clear that the invention is not limited to these embodiments only. Numerous modifications, changes, variations, substitutions, and equivalents will be apparent to those skilled in the art, without departing from the spirit and scope of the invention, as described in the claim.
[00146] In the foregoing description, numerous details are set forth. It will be apparent, however, to one of ordinary skill in the art having the benefit of this disclosure, that the present invention may be practiced without these specific details. In some instances, well-known structures and devices are shown in block diagram form, rather than in detail, to avoid obscuring the present invention.
[00147] As used herein, and unless the context dictates otherwise, the term "coupled to" is intended to include both direct coupling (in which two elements that are coupled to each other contact each other)and indirect coupling (in which at least one additional element is located between the two elements). Therefore, the terms "coupled to" and "coupled with" are used synonymously. Within the context of this document terms "coupled to" and "coupled with" are also used euphemistically to mean “communicatively coupled with” over a network, where two or more devices are able to exchange data with each other over the network, possibly via one or more intermediary device.
[00148] It should be apparent to those skilled in the art that many more modifications besides those already described are possible without departing from the inventive concepts herein. The inventive subject matter, therefore, is not to be restricted except in the spirit of the appended claims. Moreover, in interpreting both the specification and the claims, all terms should be interpreted in the broadest possible manner consistent with the context. In particular, the terms “comprises” and “comprising” should be interpreted as referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced. Where the specification claims refers to at least one of something selected from the group consisting of A, B, C …. N, the text should be interpreted as requiring only one element from the group, not A plus N, or B plus N, etc.
[00149] While the foregoing describes various embodiments of the invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof. The scope of the invention is determined by the claims that follow. The invention is not limited to the described embodiments, versions or examples, which are included to enable a person having ordinary skill in the art to make and use the invention when combined with information and knowledge available to the person having ordinary skill in the art.

ADVANTAGES OF THE PRESENT DISCLOSURE
[00150] The present disclosure provides a system to monitor a battery.
[00151] The present disclosure provides a system to determine loose connections of wire, SOH, SOC of the battery.
[00152] The present disclosure provides a system to facilitate predictive maintenance of a battery.
[00153] The present disclosure provides an accurate, fast, efficient, cost effective and simple network vulnerability assessment system.

We Claim:
1. A system for predictive maintenance of a battery, wherein the system comprises:
a battery management unit (BMU) adapted to be operatively coupled to the battery comprising one or more cells, and configured to receive battery data from the battery, and correspondingly generate a first set of data packets; and
a control unit operatively coupled to the battery management unit, and comprising one or more processors with a memory, the memory storing instructions executable by the one or more processors and configured to:
receive the first set of data packets from the BMU;
extract a second set of data packets from the received first set of data packets, wherein the second set of data packets are indicative of one or more parameters of the battery;
determine divergence in at least one of the one or more parameters of the battery, based on a comparison of the second set of data packets with a first dataset, wherein the first dataset comprises set of pre-determined ranges of the one or more parameters of the battery; and
determine a time-duration, based on the determined divergence, and correspondingly generate a set of maintenance signals, and wherein the set of maintenance signals is indicative of one or more maintenance actions to be performed, after the determined time duration, on any or a combination of the battery and the BMU.
2. The system as claimed in claim 1, wherein the control unit is configured to determine the divergence within a pre-determined time period.
3. The system as claimed in claim 1, wherein the one or more parameters are any or a combination of voltage, current, temperature, charge capacity, state of charge, state of health and power of battery.
4. The system as claimed in claim 1, wherein the control unit is configured to generate, when the divergence exceeds a threshold limit, a set of warning signals, wherein the set of warning signals is indicative of one or more defects in any or a combination of the battery and the BMU.
5. The system as claimed in claim 4, wherein the one or more defects comprise any or a combination of loose connection of wire, broken wire, a short-circuit condition, over-heating, a fault in at least one of the one or more cell, and a fault in battery management unit.
6. The system as claimed in claim 1, wherein the BMU comprises one or more sensors to sense the one or more parameter of the battery.
7. The system as claimed in claim 1, wherein the BMU is communicatively coupled, through a communication unit, to the control unit, wherein the communication unit comprises any or a combination of , a GSM module, data cable, Bluetooth, wired network, Li-Fi module, and Wi Fi module, Amazon AWS, and MongoDB.
8. The system as claimed in claim 7, wherein the system is configured to monitor rate of flow of the first data packets from the BMU to the control unit, and correspondingly generate the set of warning signals when monitored rate of flow of the first data packets is less than a pre-determined rate.
9. The system as claimed in claim 1, wherein the battery is any or a combination of Lithium-ion battery and rechargeable battery.
10. A method for predictive maintenance of a battery, wherein the method comprises:
receiving, at a battery management unit (BMU) adapted to be operatively coupled to the battery comprising one or more cells, battery data from the battery, and correspondingly generate a first set of data packets;
receiving, at one or more processors of a control unit, the first set of data packets from the BMU;
extracting, at the one or more processors, a second set of data packets from the received first set of data packets, wherein the second set of data packets are indicative of one or more parameters of the battery;
determining, at the one or more processors, divergence in at least one of the one or more parameters of the battery, based on a comparison of the second set of data packets with a first dataset, wherein the first dataset comprises set of pre-determined ranges of the one or more parameters of the battery; and
determining, at the one or more processors, a time-duration, based on the determined divergence, and correspondingly generate a set of maintenance signals, and wherein the set of maintenance signals is indicative of one or more maintenance actions to be performed, after the determined time duration, on any or a combination of the battery and the BMU.