Description:TECHNICAL FIELD
Embodiments of the present disclosure generally relate to battery management systems, and more particularly relate to a battery regeneration system for optimizing de-sulfation of a lead-acid type storage battery and method thereof.

BACKGROUND
Generally, traditional lead-acid batteries may be a mainstay for various applications due to robustness and affordability of the lead-acid batteries. However, the lead-acid batteries may inherent limitations raise significant concerns for both economic and environmental sustainability. The lead-acid batteries may have a lifespan of approximately 36 months under ideal conditions. However, once the lifespan elapses, the lead-acid batteries may be discarded, generating a substantial waste stream, and contributing to environmental pollution. Frequent replacements incur a high cost of capital expenditure (CAPEX) for users, impacting overall financial viability. Further, the production of new lead-acid batteries may be an energy-intensive process, contributing to carbon footprint and depleting natural resources. The disposal of used batteries poses further environmental challenges. Toxic materials within the batteries can leach into the environment, causing significant harm if not handled responsibly. The limitations of traditional lead-acid batteries necessitate a paradigm shift towards sustainable battery management.
Conventionally, systems provide a battery optimization and restoration devices that uses a means of varying the regulator voltage as a function of time and discharge event timing and depth to establish a consistent power level for the charging of the capacitor. Another conventional system provides a device for removing membranous lead sulfate deposited on electrodes of a lead-acid battery by dissolving the lead sulfate into fine particles. Yet another conventional system provides a plurality of capacitive discharge channels selectively activatable by a control board to provide a pulse wave modulated de-sulfating current to a lead-acid battery.
However, in the conventional systems it is generally necessary to open a battery pack, perform repeated discharge and charge multiple times, and apply additional high-frequency pulse voltage to remove sulfur, so as to achieve the maintenance purpose of the battery, maintain the rated voltage, and prolong the battery life. Accordingly, the conventional systems mainly have the following defects: (1) The battery needs to be peeled off for the application scenario, and the working status of the battery pack cannot be monitored online in real time. In some remote or high-altitude mountains, this greatly increases the operating cost; (2) It requires relying on external desulfurization maintenance equipment also needs to rely on manual on-site operations. When the maintenance site cannot provide electricity for the maintenance equipment to work, the maintenance difficulty is greatly increased.
Consequently, there is a need in the art for an improved battery regeneration system and method thereof, to address at least the aforementioned issues in the prior arts.

SUMMARY
This summary is provided to introduce a selection of concepts, in a simple manner, which is further described in the detailed description of the disclosure. This summary is neither intended to identify key or essential inventive concepts of the subject matter nor to determine the scope of the disclosure.
An aspect of the present disclosure provides a battery regeneration system. The system includes one or more sensors, communicatively coupled to at least one lead-acid battery. The one or more sensors are configured to determine one or more battery parameters corresponding to the at least one lead-acid battery. The one or more battery parameters are determined during at least one of a charging cycle and a discharging cycle of the at least one lead-acid battery. Further, the system includes the processor and configure to receive the determined one or more battery parameters from the one or more sensors. Further, the system analyses the one or more battery parameters to determine at least one of a sulphation level corresponding to a severity of sulphation and a conductive medium level corresponding to an amount of conductive medium retained in the at least one lead-acid battery. Furthermore, the system determines, using one or more Artificial Intelligence (AI)-based techniques, an appropriate very high-frequency cross-pulsing technique for a de-sulfation of at least one lead-acid battery, based on the determined sulfation level. The very high-frequency cross-pulsing technique is in Kilohertz (KHz) range of frequencies.
Further, the system generates, using one or more pulse signals of the individually variable pulse signals comprises adjustable pulse frequency AI-based techniques, pulse sequence data corresponding to a sequential repetition of individually variable pulse signals, based on the determined appropriate very high-frequency cross pulsing technique. Each pulse signal of the individually variable pulse signals comprises an adjustable pulse frequency and an individually variable pulse amplitude. Furthermore, the system transmits, via a communication channel, the generated pulse sequence data to a control unit, for the de-sulfation of at least one lead-acid battery, and transmit the determined conductive medium level to a Battery Monitoring System (BMS), based on the amount of the conductive medium retained in the at least one lead-acid battery. Additionally, the system periodically modifies, the adjustable pulse frequency and the individually variable pulse amplitude in the pulse sequence data, for each pulse signal of the individually variable pulse signals. The adjustable pulse frequency and the individually variable pulse amplitude is within a pre-defined very high-frequency range and a pre-defined pulse amplitude range optimized for de-sulphation. Further, the system transmits the modified adjustable pulse frequency and the individually variable pulse amplitude in the pulse sequence data to the control unit.
Furthermore, the system includes the control unit communicatively coupled to the processor. The control unit receives at least one of the generated pulse sequence data, the modified adjustable pulse frequency, and the modified individually variable pulse amplitude from the processor via the communication channel. Furthermore, the control unit generates at least one of the sequential repetitions of individually variable pulse signals, the modified adjustable pulse frequency, and the modified individually variable pulse amplitude, based on the received data. Additionally, the control unit applies, via terminals of the at least one lead-acid battery, at least one of the generated sequential repetition of individually variable pulse signals, the modified adjustable pulse frequency, and the modified individually variable pulse amplitude, as a charging current to the at least one lead-acid battery for the de-sulphation and a regeneration. The at least one lead-acid battery is charged to original condition upon completion of the de-sulphation.
Another aspect of the present disclosure provides a battery regeneration method. The method includes receiving one or more battery parameters corresponding to at least one lead-acid battery from one or more sensors communicatively coupled to at least one lead-acid battery. The one or more battery parameters are determined during at least one of a charging cycle and a discharging cycle of the at least one lead-acid battery. Further, the method includes analyzing the one or more battery parameters to determine at least one of a sulphation level corresponding to a severity of sulphation and a conductive medium level corresponding to an amount of conductive medium retained in the at least one lead-acid battery. Furthermore, the method includes determining, using one or more Artificial Intelligence (AI)-based techniques, an appropriate very high-frequency cross pulsing technique for a de-sulfation of the at least one lead-acid battery, based on the determined sulfation level. The very high-frequency cross-pulsing technique is in Kilohertz (KHz) range of frequencies. Furthermore, the method includes generating, using the one or more AI-based techniques, pulse of individually sequence data corresponding to a sequential repetition variable pulse signal, based on the determined appropriate very high-frequency cross pulsing technique. Each pulse signal of the individually variable pulse signals comprises an adjustable pulse frequency and an individually variable pulse amplitude.
Further, the method includes transmitting, via a communication channel, the generated pulse sequence data to a control unit, for the de-sulfation of the at least one lead-acid battery, and transmitting the determined conductive medium level to a Battery Monitoring System (BMS), based on the amount of the conductive medium retained in the at least one lead-acid battery. Further, the method includes modifying periodically, the adjustable pulse frequency and the individually variable pulse amplitude in the pulse sequence data, for each pulse signal of the individually variable pulse signals. The adjustable pulse frequency and the individually variable pulse amplitude is within a pre-defined very high-frequency range and a pre-defined pulse amplitude range optimized for de-sulphation. Additionally, the method includes transmitting the modified adjustable pulse frequency and the individually variable pulse amplitude in the pulse sequence data to the control unit.
To further clarify the advantages and features of the present disclosure, a more particular description of the disclosure will follow by reference to specific embodiments thereof, which are illustrated in the appended figures. It is to be appreciated that these figures depict only typical embodiments of the disclosure and are therefore not to be considered limiting in scope. The disclosure will be described and explained with additional specificity and detail with the appended figures.

BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS
The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the description, serve to explain the disclosed principles. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the figures to reference like features and components. Some embodiments of system and/or methods in accordance with embodiments of the present subject matter are now described, by way of example only, and with reference to the accompanying figures, in which:
FIG. 1 illustrates a block diagram representation of a network architecture of a battery regeneration system for optimizing de-sulfation of a lead-acid type storage battery, in accordance with some embodiments of the present disclosure;
FIG. 2 illustrates a block diagram representation of a proposed system such as those shown in FIG. 1, capable of optimizing de-sulfation of a lead-acid type storage battery, in accordance with some embodiments of the present disclosure;
FIG. 3 illustrates a flow diagram representation of a detailed network architecture for a battery regeneration system, in accordance with some embodiments of the present disclosure;
FIG. 4A illustrates a graph diagram representation of a de-sulphation of at least one lead-acid battery, in accordance with some embodiments of the present disclosure;
FIG. 4B illustrate graph diagram representations of a pulse charging of at least one lead-acid battery, in accordance with some embodiments of the present disclosure; and
FIG. 5 illustrates a flow chart depicting a battery regeneration method for optimizing de-sulfation of a lead-acid type storage battery, in accordance with some embodiments of the present disclosure.
Further, those skilled in the art will appreciate that elements in the figures are illustrated for simplicity and may not have necessarily been drawn to scale. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the figures by conventional symbols, and the figures may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the figures with details that will be readily apparent to those skilled in the art having the benefit of the description herein.
DETAILED DESCRIPTION
For the purpose of promoting an understanding of the principles of the disclosure, reference will now be made to the embodiment illustrated in the figures and specific language will be used to describe them. It will nevertheless be understood that no limitation of the scope of the disclosure is thereby intended. Such alterations and further modifications in the illustrated system, and such further applications of the principles of the disclosure as would normally occur to those skilled in the art are to be construed as being within the scope of the present disclosure. It will be understood by those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the disclosure and are not intended to be restrictive thereof.
In the present document, the word “exemplary” is used herein to mean “serving as an example, instance, or illustration”. Any embodiment or implementation of the present subject matter described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.
While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however that it is not intended to limit the disclosure to the forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternative falling within the scope of the disclosure.
The terms “comprises”, “comprising”, “includes”, “including” or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, device or method that includes a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or device or method. In other words, one or more elements in a system or apparatus proceeded by “comprises… a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or method.
Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this disclosure belongs. The system, methods, and examples provided herein are only illustrative and not intended to be limiting.
In the following specification and the claims, reference will be made to a number of terms, which shall be defined to have the following meanings. The singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise.
A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary, a variety of optional components are described to illustrate the wide variety of possible embodiments of the invention. In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings that form a part hereof, and in which are shown by way of illustration specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.
Embodiments of the present disclosure provides a battery regeneration system for optimizing de-sulfation of a lead-acid type storage battery and method thereof. The system includes one or more sensors connected to a lead-acid battery. The sensors determine various battery parameters during charging or discharging cycles. The processor, part of the system, receives and analyzes the parameters, discerning the sulphation level and conductive medium amount within the lead-acid battery. Employing Artificial Intelligence (AI)-based techniques, the system identifies an optimal very high-frequency cross-pulsing technique for de-sulfation, operating in the Kilohertz (KHz) frequency range.
Furthermore, the system generates pulse sequence data using adjustable pulse frequency AI-based techniques, representing a sequential repetition of individually variable pulse signals based on the determined cross-pulsing technique. The data is transmitted to a control unit for de-sulfation. The system periodically adjusts pulse frequency and amplitude within predefined ranges optimized for de-sulphation, transmitting modifications to the control unit. The control unit, receiving data from the processor, applies generated pulse signals as a charging current through the terminals of the lead-acid battery, facilitating de-sulfation and regeneration to its original condition upon completion.
Referring now to the drawings, and more particularly to FIGs. 1 through FIG. 5 where similar reference characters denote corresponding features consistently throughout the figures, there are shown preferred embodiments, and these embodiments are described in the context of the following exemplary system and/or method.
FIG. 1 illustrates a block diagram representation of a network architecture of a battery regeneration system 100 for optimizing de-sulfation of a lead-acid type storage battery. in accordance with some embodiments of the present disclosure. According to FIG. 1, the network architecture includes one or more sensors 102, at least one lead-acid battery 104, a computing system 106, a control unit 114, a battery management unit 118, a server 120, and an electronic device 122. The electronic device 122 may be associated with one or more users, and communicatively coupled to the server 120 via a communication network (not shown in FIG. 1). In an embodiment the electronic device 122 may include, but is not limited to, a laptop computer, a desktop computer, a tablet computer, a smartphone, a wearable device, a digital camera, and the like. Further, the communication network may be a wired network or a wireless network. The server 120 may be at least one of, but is not limited to, a central server, a cloud server, a remote server, a rake server, an on-premises server, and the like. Further, the computing system 106 may be communicatively coupled to the database (not shown in FIG. 1), via the communication network. The database may include, but is not limited to, battery data, battery parameters data, battery characteristics data, State of Health (SoH) data, any other data, and combinations thereof. The database may be any kind of databases/repositories such as, but are not limited to, relational database, dedicated database, dynamic database, monetized database, scalable database, cloud database, distributed database, any other database, and combination thereof.
The at least one lead-acid battery 104 includes, but is not limited to, a Flooded Lead-Acid (FLA) battery, a Valve-Regulated Lead-Acid (VRLA) battery, a Gel Cell battery, an Absorbent Glass Mat (AGM) battery, a Deep Cycle battery, a Starting, Lighting, and Ignition (SLI) battery, a Lead-Carbon battery, an Enhanced Flooded Batteries (EFB), a Thin Plate Pure Lead (TPPL) battery, and the like. The one or more sensors 102 may include, but not limited to, a conductive medium sensing sensor, a level of sulphation sensing sensor, a capacitive type of sensor, a voltage measuring senor, a current measuring sensor, an ultrasonic level sensor, an internal resistance sensor, and the like.
Further, the electronic device 122 may be associated with, but not limited to, a user, an individual, an administrator, a vendor, a technician, a worker, a specialist, a healthcare worker, an instructor, a supervisor, a team, an entity, an organization, a company, a facility, a bot, any other user, and combination thereof. The entities, the organization, and the facility may include, but are not limited to, a hospital, a healthcare facility, an exercise facility, a laboratory facility, an e-commerce company, a merchant organization, an airline company, a hotel booking company, a company, an outlet, a manufacturing unit, an enterprise, an organization, an educational institution, a secured facility, a warehouse facility, a supply chain facility, any other facility and the like. The electronic device 122 may be used to provide input and/or receive output to/from the computing system 106, and/or to the database, respectively. The electronic device 122 may present to the user one or more user interfaces for the user to interact with the computing system 106 and/or to the database for battery regeneration need. The electronic device 122 may be at least one of, an electrical, an electronic, an electromechanical, and a computing device. The electronic device 122 may include, but is not limited to, a mobile device, a smartphone, a personal digital assistant (PDA), a tablet computer, a phablet computer, a wearable computing device, a virtual reality / augmented reality (VR/AR) device, Metaverse based devices, a laptop, a desktop, a server, and the like.
Further, the computing system 106 may be implemented by way of a single device or a combination of multiple devices that may be operatively connected or networked together. The computing system 106 may be implemented in hardware or a suitable combination of hardware and software. The computing system 106 includes one or more hardware processor(s) 108, and a memory 110. The memory 110 may include a plurality of modules 112. The computing system 106 may be a hardware device including the hardware processor 108 executing machine-readable program instructions for battery regeneration of a lead-acid type storage battery. Execution of the machine-readable program instructions by the hardware processor 108 may enable the computing system 106 to regenerate battery of a lead-acid type storage battery. The “hardware” may comprise a combination of discrete components, an integrated circuit, an application-specific integrated circuit, a field-programmable gate array, a digital signal processor, or other suitable hardware. The “software” may comprise one or more objects, agents, threads, lines of code, subroutines, separate software applications, two or more lines of code, or other suitable software structures operating in one or more software applications or on one or more processors.
The one or more hardware processors 108 may include, for example, microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuits, and/or any devices that manipulate data or signals based on operational instructions. Among other capabilities, hardware processor 108 may fetch and execute computer-readable instructions in the memory 110 operationally coupled with the computing system 106 for performing tasks such as data processing, input/output processing, and/or any other functions. Any reference to a task in the present disclosure may refer to an operation being or that may be performed on data.
Though few components and subsystems are disclosed in FIG. 1, there may be additional components and subsystems which is not shown, such as, but not limited to, ports, routers, repeaters, firewall devices, network devices, databases, network attached storage devices, servers, assets, machinery, instruments, facility equipment, emergency management devices, image capturing devices, sensors, any other devices, and combination thereof. The person skilled in the art should not be limiting the components/subsystems shown in FIG. 1. Although FIG. 1 illustrates the computing system 106, and the electronic device 122 connected to the database, server, BMS, control unit, one skilled in the art can envision that the computing system 106, and the electronic device 122 can be connected to several user devices located at various locations and several databases via the communication network.
Those of ordinary skilled in the art will appreciate that the hardware depicted in FIG. 1 may vary for particular implementations. For example, other peripheral devices such as an optical disk drive and the like, local area network (LAN), wide area network (WAN), wireless (e.g., wireless-fidelity (Wi-Fi)) adapter, graphics adapter, disk controller, input/output (I/O) adapter also may be used in addition or place of the hardware depicted. The depicted example is provided for explanation only and is not meant to imply architectural limitations concerning the present disclosure.
Those skilled in the art will recognize that, for simplicity and clarity, the full structure and operation of all data processing systems suitable for use with the present disclosure are not being depicted or described herein. Instead, only so much of the computing system 106 as is unique to the present disclosure or necessary for an understanding of the present disclosure is depicted and described. The remainder of the construction and operation of the computing system 106 may conform to any of the various current implementations and practices that were known in the art.
In an embodiment, the battery regeneration system 100 includes the one or more sensors 102, communicatively coupled to at least one lead-acid battery 104, configured to determine one or more battery parameters corresponding to the at least one lead-acid battery. The one or more battery parameters may be determined during at least one of a charging cycle and a discharging cycle of the at least one lead-acid battery 104. Further, the one or more battery parameters include, but not limited to, a voltage value, a current value, a temperature value, an impedance value, an internal resistance value, a capacitance value, and the like.
Furthermore, the computing system 106 may receive the determined one or more battery parameters from the one or more sensors 102. Furthermore, the computing system 106 may analyse the one or more battery parameters to determine at least one of a sulphation level corresponding to a severity of sulphation and a conductive medium level corresponding to an amount of conductive medium retained in the at least one lead-acid battery. The conductive medium may include, but is not limited to, a electrolyte (liquid electrolyte), a gel electrolyte, a solid electrolyte, a polymer electrolyte, a saltwater electrolyte, a molten salt, an air (air electrode), and the like. Additionally, the computing system 106 may determine, using one or more Artificial Intelligence (AI)-based techniques, an appropriate very high-frequency cross-pulsing technique for a de-sulfation of at least one lead-acid battery, based on the determined sulfation level. In an example, the AI-based techniques may include, but are not limited to, random forest technique, and the like. Further, the AI-based techniques may include, but are not limited to, Support Vector Machines (SVMs), neural networks, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Reinforcement Learning (RL), Explainable AI (XAI), and the like. Further, in another example, the very high-frequency cross-pulsing technique may be in Kilohertz (KHz) range of frequencies of for example, but not limited to, 0-20Khz, and the like. The very high-frequency cross pulsing technique utilises a cross-pulse technique or a Direct Current (DC) pulse technique for a controlled and a targeted approach for the de-sulfation of the at least one battery. The very high-frequency cross pulsing technique may maintain temperature within a pre-defined temperature in the at least one lead-acid battery during de-sulphation.
In an embodiment, the appropriate very high-frequency cross-pulsing technique is determined, based on a random historical problems tree techniques. The AI-based techniques may choose a best random historical problems tree techniques and predict a best solution from the random historical problems tree techniques for the de-sulfation. The AI-based techniques may include appropriate functions to change the frequency as required by the predicted solution, that may involve interfacing with frequency control devices or modules connected to the Pulse Width Modulation (PWM) section consisting of the regeneration. Further, the one or more sensors 102 may collect all the detailed basic inputs of accumulated sulphate on the surface of the battery grid during the regeneration based on voltage, current, temperature and impedance. The AI-based techniques or machine learning algorithms search for the best features among random decision trees and predict the best stable and accurate prediction. The PWMs use an Analogue to Digital Converter (ADC) to convert analogue signals to digital or use the PWM to convert digital signals to analogue. The output may be high pulse frequency and amplitudes on a Cathode-Ray Oscilloscope (CRO).
For example, the AI-based techniques may be used to analyse one or more complex patterns and diverse data sets. The data sets may be received from the one or more sensors 102 in form of real time voltage, current, temperature, Depth of Discharge (DoD), State of Health (SoH), and other battery parameters associated with a battery degradation. The battery regeneration system 100 may enhance precision to generate the appropriate pulse for the regeneration technique on real time.
In an embodiment, the computing system 106 may generate, using one or more pulse signals of the individually variable pulse signals comprises adjustable pulse frequency AI-based techniques, pulse sequence data corresponding to a sequential repetition of individually variable pulse signals, based on the determined appropriate very high-frequency cross pulsing technique. Each pulse signal of the individually variable pulse signals comprises an adjustable pulse frequency and an individually variable pulse amplitude.
In an embodiment, the computing system 106 may transmit, via a communication channel, the generated pulse sequence data to the control unit 114, for the de-sulfation of at least one lead-acid battery 104. Further, the computing system 106 may transmit the determined conductive medium level to the Battery Monitoring System (BMS) 118, based on the amount of the conductive medium retained in the at least one lead-acid battery.
In an embodiment, the computing system 106 may periodically modify, the adjustable pulse frequency and the individually variable pulse amplitude in the pulse sequence data, for each pulse signal of the individually variable pulse signals. The adjustable pulse frequency and the individually variable pulse amplitude may be within a pre-defined very high-frequency range and a pre-defined pulse amplitude range optimized for de-sulphation. The de-sulphation comprises initially breaking sulphate deposits and subsequently dissolving the broken sulphation by creating a plurality of minute bubbles at a grid of the at least one lead-acid battery. In the pulse frequency optimization, the adjustable pulse frequency may be set within a pre-defined very high-frequency range. this means that the frequency at which the pulses are applied to the battery is carefully selected to be within a specific range that has been found to be most beneficial for the de-sulphation process. high-frequency pulses are often more effective in breaking down sulphate deposits. In the pulse amplitude optimization, the individually variable pulse amplitude is set within a pre-defined pulse amplitude range. this involves adjusting the strength or intensity of each pulse within a specific range that has been determined to be optimal for de-sulphation. the amplitude of the pulses is a crucial factor in ensuring effective battery regeneration without causing harm to the terminals.
In an embodiment, the computing system 106 may transmit the modified adjustable pulse frequency and the individually variable pulse amplitude in the pulse sequence data to the control unit 114.
In an embodiment, the control unit 114 may be communicatively coupled to the processor 108. The control unit 114 may receive at least one of the generated pulse sequence data, the modified adjustable pulse frequency, and the modified individually variable pulse amplitude from the processor 108 via the communication channel.
In an embodiment, the control unit 114 may generate at least one of the sequential repetition of individually variable pulse signals, the modified adjustable pulse frequency, and the modified individually variable pulse amplitude, based on the received data.
In an embodiment, the control unit 114 may apply, via terminals of the at least one lead-acid battery 104, at least one of the generated sequential repetition of individually variable pulse signals, the modified adjustable pulse frequency, and the modified individually variable pulse amplitude, as a charging current to the at least one lead-acid battery for the de-sulphation and a regeneration. The at least one lead-acid battery 104 may be charged to original condition upon completion of the de-sulphation. During the charging cycle, an effect of the very high-frequency cross pulsing technique creates a plurality of minute bubbles in a moisture content of the conductive medium to dissolve the broken sulphate back in a sulfuric acid for regaining a specific gravity of the conductive medium. The plurality of minute bubbles may be formed based on a result of electrochemical processes due to continuous a very high-frequency pulse charge and pulse discharge on a grid of the at least one lead-acid battery.
In an embodiment, the battery regeneration system 100 may include the BMS 118. The BMS 118 may periodically monitor, via the one or more sensors 102, the one or more battery parameters corresponding to the at least one lead-acid battery, during the charging cycle and discharging cycle. Further, the battery regeneration system 100 may transmit the monitored one or more battery parameters to the server 120 associated with the BMS 118.
In an embodiment, the BMS 118 may receive the determined conductive medium level from the processor 108, based on the amount of the conductive medium retained in the at least one lead-acid battery 104. Further, the BMS 118 may determine the amount of conductive medium required to be filled in the at least one lead-acid battery 104. Furthermore, the BMS 118 may generate, via the server 120, an alert to the electronic device, based on the determined amount of conductive medium required to be filled in the at least one lead-acid battery. For example, a data analytics and predictive modelling of AI technique may be used to process the large data from the at least one lead-acid battery 104. The large data may include, but not limited to, voltage, current temperature of individual battery cells, DOD, SOH, historical data, and the like. The data analytics and predictive modelling of AI technique may predict the battery performance and predicts the requirement of battery regeneration.
In an embodiment, the control unit 114 may monitor, in real-time, via a feedback loop connected to the one or more sensors 102, a response of the at least one lead-acid battery 104 to the applied at least one of the generated sequential repetition of individually variable pulse signals, the modified adjustable pulse frequency, and the modified individually variable pulse amplitude. Furthermore, the control unit 114 may transmit the response of the at least one lead-acid battery to the processor 108. In an embodiment, the control unit 114 may receive the modified adjustable pulse frequency and the modified individually variable pulse amplitude from the processor 108 via the communication channel, based on the transmitted response.
In an embodiment, the control unit 114 may generate the modified adjustable pulse frequency and the modified individually variable pulse amplitude, based on the received data. Further, the control unit 114 may apply, via the terminals of the at least one lead-acid battery 104, the modified adjustable pulse frequency, and the modified individually variable pulse amplitude, to the at least one lead-acid battery for the de-sulphation.
In an embodiment, the control unit 114 may include a pulse generation unit 116. The pulse generation unit may generate at least one of pulse width modulated signals and asymmetrical pulse width modulated signals based on the determined appropriate very high-frequency cross pulsing technique for the de-sulfation.
In an embodiment, the server 120 may receive the monitored one or more battery parameters from the BMS 118. The server 120 may generate a statistical data corresponding to monitored one or more battery parameters. The statistical data comprises a State of Health (SoH) of the at least one lead-acid battery. Further, the server 120 may display, via a user interface associated with the electronic device 122, the generated statistical data as one or more Network Operations Centre (NOC) services. The NOC services may include, but not limited to, monitoring, alerts and notifications, incident management, performance optimization, reporting, remote diagnostics, and the like.
FIG. 2 illustrates a block diagram representation of a proposed system such as those shown in FIG. 1, capable of optimizing de-sulfation of a lead-acid type storage battery, in accordance with some embodiments of the present disclosure. The computing system 106 may also function as a computer-implemented system (hereinafter referred to as the system 106). The system 106 comprises the one or more hardware processors 108, the memory 110, and a storage unit 204. The one or more hardware processors 108, the memory 110, and the storage unit 204 are communicatively coupled through a system bus 202 or any similar mechanism. The memory 108 comprises a plurality of modules 112 in the form of programmable instructions executable by the one or more hardware processors 108.
In an embodiment, the plurality of modules 112 may include a parametric data receiving module 206, a parameter analysing module 208, a frequency determining module 210, a pulse generating module 212, a pulse transmitting module 214, a pulse frequency and pulse transmitting module 216, a pulse sequence data transmitting module 218.
The one or more hardware processors 108, as used herein, means any type of computational circuit, such as, but not limited to, a microprocessor unit, microcontroller, complex instruction set computing exceptionally long processor unit, reduced instruction set computing microprocessor unit, very long instruction word microprocessor unit, explicitly parallel instruction computing microprocessor unit, graphics processing unit, digital signal processing unit, or any other type of processing circuit. The one or more hardware processors 108 may also include embedded controllers, such as generic or programmable logic devices or arrays, application-specific integrated circuits, single-chip computers, and the like.
The memory 110 may be a non-transitory volatile memory and a non-volatile memory. The memory 110 may be coupled to communicate with the one or more hardware processors 108, such as being a computer-readable storage medium. The one or more hardware processors 108 may execute machine-readable instructions and/or source code stored in the memory 110. A variety of machine-readable instructions may be stored in and accessed from the memory 110. The memory 110 may include any suitable elements for storing data and machine-readable instructions, such as read-only memory, random access memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, a hard drive, a removable media drive for handling compact disks, digital video disks, diskettes, magnetic tape cartridges, memory cards, and the like. In the present embodiment, the memory 110 includes the plurality of modules 112 stored in the form of machine-readable instructions on any of the above-mentioned storage media and may be in communication with and executed by the one or more hardware processors 108.
The storage unit 204 may be a cloud storage or a repository such as those shown in FIG. 1. The storage unit 204 may store, but is not limited to, battery data, battery parameters data, battery characteristics data, State of Health (SoH) data, any other data, and combinations thereof. The storage unit 204 may be any kind of databases/repositories such as, but are not limited to, relational database, dedicated database, dynamic database, monetized database, scalable database, cloud database, distributed database, any other database, and combination thereof.
In an embodiment, the parametric data receiving module 206 may receive the determined one or more battery parameters from the one or more sensors 102. Furthermore, the parameter analysing module 208 may analyse the one or more battery parameters to determine at least one of a sulphation level corresponding to a severity of sulphation and a conductive medium level corresponding to an amount of conductive medium retained in the at least one lead-acid battery. Additionally, the frequency determining module 210 may determine, using one or more Artificial Intelligence (AI)-based techniques, an appropriate very high-frequency cross-pulsing technique for a de-sulfation of at least one lead-acid battery, based on the determined sulfation level. For example, the very high-frequency cross-pulsing technique may be in Kilohertz (KHz) range of frequencies. The very high-frequency cross pulsing technique utilises a cross-pulse technique or a Direct Current (DC) pulse technique for a controlled and a targeted approach for the de-sulfation of the at least one battery. The very high-frequency cross pulsing technique may maintain temperature within a pre-defined temperature in the at least one lead-acid battery during de-sulphation. In an embodiment, for determining the conductive medium level corresponding to an amount of conductive medium retained in the at least one lead-acid battery, the parameter analysing module 208 may analyse varying capacitance conductive medium retained in the at least one lead-acid battery 104.
For example, the AI-based techniques may be used to analyse one or more complex patterns and diverse data sets. The data sets may be received from the one or more sensors 102 in form of real time voltage, current, temperature, Depth of Discharge (DoD), State of Health (SoH), and other battery parameters associated with a battery degradation. The battery regeneration system 100 may enhance precision to generate the appropriate pulse for the regeneration technique on real time.
In an embodiment, the pulse generating module 212 may generate, using one or more pulse signals of the individually variable pulse signals comprises adjustable pulse frequency AI-based techniques, pulse sequence data corresponding to a sequential repetition of individually variable pulse signals, based on the determined appropriate very high-frequency cross pulsing technique. Each pulse signal of the individually variable pulse signals comprises an adjustable pulse frequency and an individually variable pulse amplitude.
In an embodiment, the pulse transmitting module 214 may transmit, via a communication channel, the generated pulse sequence data to the control unit 114, for the de-sulfation of at least one lead-acid battery 104. Further, the pulse transmitting module 214 may transmit the determined conductive medium level to the Battery Monitoring System (BMS) 118, based on the amount of the conductive medium retained in the at least one lead-acid battery.
In an embodiment, the pulse frequency and pulse amplitude modifying module 216 may periodically modify, the adjustable pulse frequency and the individually variable pulse amplitude in the pulse sequence data, for each pulse signal of the individually variable pulse signals. The adjustable pulse frequency and the individually variable pulse amplitude may be within a pre-defined very high-frequency range and a pre-defined pulse amplitude range optimized for de-sulphation. The de-sulphation comprises initially breaking sulphate deposits and subsequently dissolving the broken sulphation by creating a plurality of minute bubbles at a grid of the at least one lead-acid battery.
In an embodiment, the pulse sequence data transmitting module 218 may transmit the modified adjustable pulse frequency and the individually variable pulse amplitude in the pulse sequence data to the control unit 114. The control unit apply, via terminals of the at least one lead-acid battery, at least one of the sequential repetition of individually variable pulse signals, the modified adjustable pulse frequency, and the modified individually variable pulse amplitude, as a charging current to the at least one lead-acid battery for the de-sulphation and a regeneration, wherein the at least one lead-acid battery 104 may be charged to original condition upon completion of the de-sulphation.
In an embodiment, the processor 108 may determine a stage of sulphation in the at least one lead-acid battery based on at least one a low voltage, a high impedance, a high rate of rise in temperature, and changes in temperature patterns within the at least one lead-acid battery 104.
In an embodiment, for analysing the one or more battery parameters, the processor 108 may identify changes in at least one of a voltage profile, a current profile, an impedance profile, and a temperature profile of at least one lead-acid battery, indicative of the severity of sulphation. Further, the processor 108 determine at least one of an amplitude, a frequency and a pulse duration for each pulse required to be applied for de-sulphation. De-sulphation comprises initially breaking sulphate deposits and subsequently dissolving the broken sulphation by creating a plurality of minute bubbles at a grid of the at least one lead-acid battery 104.
FIG. 3 illustrates a flow diagram representation of a detailed network architecture 300 for a battery regeneration system 100, in accordance with some embodiments of the present disclosure. The network architecture 300 may include input power supply, for example, an Alternating Current (AC) input voltage of 220V. This voltage passes through several stages of filtering and conditioning to remove noise and ensure a clean power supply for the rest of the battery regeneration system 100. RC filter circuits may eliminate high-frequency noise and unwanted transients from the incoming AC. Another filter stage specifically targets electromagnetic and radio frequency interference (EMI/RFI) using dedicated circuit. This ensures clean power that may not disrupt sensitive electronic components later in the process. The conditioned AC then reaches a 220VAC filter circuit for further noise removal before proceeding to the next stage.
Further, the network architecture 300 may include an over/under voltage protection circuit for safeguarding the battery regeneration system 100 from damage caused by fluctuations in the input voltage. If the voltage goes too high or too low, the over/under voltage protection circuit may cut off the power supply to protect the other components. Further, the BMS 118 may constantly track the voltage, current, and temperature of the connected batteries. This information is used to optimize the regeneration process and prevent damage to the batteries.
Further, Switched-mode power supplies (SMPS) may convert the filtered AC input voltage to various DC voltages required by different parts of the battery regeneration system 100. The DC voltages may be used to power the control circuits, charge the batteries, or drive the MOSFET switching circuits. Additionally, regeneration pulse circuits generate the specific electrical pulses needed to revive the sulfated plates within the batteries. The pulses are carefully controlled in terms of amplitude, frequency, and duration to ensure effective regeneration without damaging the batteries. Furthermore, Metal-oxide-semiconductor field-effect transistors (MOSFETs) act as electronic switches that control the flow of current to the batteries during the regeneration process. The gate driver circuits provide the necessary signals to turn the MOSFETs on and off at the appropriate times. After the regeneration process, the battery voltage is rectified from DC to AC and then filtered to remove any remaining electrical noise. The filtered AC voltage can then be used to power external devices or fed back into the grid.
The network architecture 300 may also include several other components. For example, a PWM control and feedback synchronization circuit may regulate the pulse width modulation (PWM) of the regeneration pulses and ensures proper synchronization with the AC power line. Safety circuits may protect the system from overcurrent, overheating, and other potential hazards. Additionally, communication interfaces such as RS-232 or Bluetooth to allow for data logging, monitoring, and control from a remote device.
For example, applying a high frequency pulse may be more effective in battery de-sulphation. However, in some cases applying the high frequency pulse may increase battery impedance which may affect the current characteristics of the battery. The feedback loop of a Programmable Logic Controller (PLC) (e.g., microcontroller) may continuously computes the rise in battery impedance and temperature and varies the frequency of the pulse accordingly. The process works in a closed-loop system and adjusting the frequency-response is performed by using transient-response characteristics for the battery regeneration system 100.
FIG. 4A illustrates a graph diagram 400A representation of a de-sulphation of at least one lead-acid battery, in accordance with some embodiments of the present disclosure. The computing system 106 may calculate the amplitude, frequency and pulse duration required to be applied to de-sulphated the terminal and internal grid of battery as shown in the graph 400A. The computing system 106 may perform stage wise de-sulphation by first breaking the sulphation and then dissolving the same by creating bubbles at the grid of battery.
FIG. 4B illustrate graph diagram representations 400B of a pulse charging of at least one lead-acid battery 104, in accordance with some embodiments of the present disclosure. The pulse charging may be a process in which the charging current is applied to the battery for a short period then removed for some time and then applied again and so on. The form of pulse charging used for an experiment also had a discharge pulse as part of the charger’s output waveform. The graph diagram representations 400B depicts plots of a charge and discharge pulses of a charger and a response of a battery to the charge and discharge pulses.
Exemplary scenarios:
In an exemplary scenario, the battery regeneration system 100 incorporates advanced sensors, including voltage/current sensors, internal resistance sensors, and temperature sensors. precise monitoring of voltage and current characteristics during charging and discharging cycles provides valuable insights into battery health. Changes in voltage and temperature profiles can indicate the presence of sulfation.
Utilizing highly sensitive temperature sensors with a 32-bit Analog to Digital Converter (ADC), the system 100 monitors temperature variations indicative of sulfation. The system 100 uses intelligent sensors, capable of computing and making decisions without manual intervention, rather than non-of intelligent sensors, which require manual intervention. The operational workflow of the intelligent sensors involves data collection, processing, analysis, decision-making, and communication. Lead-acid batteries, known for reliability, face challenges such as sulfation and declining electrolyte levels. The present disclosure provides a digital regeneration system with built-in intelligent sensors to address these challenges and extend battery life.
Intelligent sensors compute critical battery parameters and apply a high-frequency cross pulse to the battery. The system 100 dynamically adjusts pulse voltage and frequency to keep the charging current within specified limits. The intelligent sensors assess the level of sulfation and adapt the regeneration behavior in real-time, utilizing individually variable pulse signals for efficient de-sulfation.
The present disclosure also monitors electrolyte levels in real-time using capacitive sensors, enabling timely top-ups to prevent damage. High-frequency pulses aid in de-sulfation, preventing temperature rise and improving battery health. Variable ripple application enhances Direct Current Accumulator (DCA) performance by improving current distribution. AC pulse and cross-pulse DC pulse technologies effectively reduce sulfation, providing a controlled and targeted approach to de-sulfation. High-frequency pulse charging disrupts and breaks down lead sulfate crystals, preventing hardening. The system 100 aims to achieve over 90% capacity revival in the battery regeneration process.
Further, the technology also involves moisture generation during the charge cycle, creating tiny bubbles in the electrolyte to dissolve broken sulfate back into sulfuric acid. Continuous monitoring captures critical battery parameters, providing insights into State of Charge (SOC), State of Health (SOH), and other statistics. Proactive updates about battery health help predict premature degradation and facilitate timely interventions. The total impedance (Z) of the battery may calculated as the vector sum of its ohmic resistance and reactance, represented as shown in equation 1 below:
Z=v(R^2+X^2 )…. Equation 1
In the above equation the variable ‘Z’ may be a total impedance of the battery, ‘R’ may be an ohmic resistance, and ‘X’ may be a reactance.
R (Ohmic Resistance): This component accounts for the resistive part of the impedance, representing the opposition to the flow of alternating current (AC) caused by the inherent resistance of the battery materials, conductors, and other factors. X (Reactance): This component represents the reactive part of the impedance, capturing the opposition to the flow of AC resulting from inductive or capacitive effects in the battery. Reactance can be further categorized into inductive reactance (XL) and capacitive reactance (XC). The equation combines both the resistive and reactive components to calculate the total impedance of the battery. The reactance (XX) term includes both inductive and capacitive reactance contributions. The square root of the sum of the squares of R and X gives the magnitude of the impedance (Z).
FIG. 5 illustrates a flow chart depicting a battery regeneration method 500 for optimizing de-sulfation of a lead-acid type storage battery 104, in accordance with some embodiments of the present disclosure.
At step 502, the method 500 includes receiving, by a processor 108 associated with a battery regeneration system 100, one or more battery parameters corresponding to at least one lead-acid battery 104 from one or more sensors 102, communicatively coupled to at least one lead-acid battery 104. The one or more battery parameters may be determined during at least one of a charging cycle and a discharging cycle of the at least one lead-acid battery 104.;
At step 504, the method 500 includes analysing, by the processor 108, the one or more battery parameters to determine at least one of a sulphation level corresponding to a severity of sulphation and a conductive medium level corresponding to an amount of conductive medium retained in the at least one lead-acid battery 104.
At step 506, the method 500 includes determining, by the processor 108, using one or more Artificial Intelligence (AI)-based techniques, an appropriate very high-frequency cross pulsing technique for a de-sulfation of the at least one lead-acid battery 104, based on the determined sulfation level. The very high-frequency cross-pulsing technique is in Kilohertz (KHz) range of frequencies.
At step 508, the method 500 includes generating, by the processor 108, using the one or more AI-based techniques, pulse of individually sequence data corresponding to a sequential repetition variable pulse signals, based on the determined appropriate very high-frequency cross pulsing technique. Each pulse signal of the individually variable pulse signals includes an adjustable pulse frequency and an individually variable pulse amplitude.
At step 510, the method 500 includes transmitting, by the processor 108, via a communication channel, the generated pulse sequence data to a control unit 114, for the de-sulfation of the at least one lead-acid battery 104, and transmit the determined conductive medium level to a Battery Monitoring System (BMS) 118, based on the amount of the conductive medium retained in the at least one lead-acid battery 104.
At step 512, the method 500 includes modifying, by the processor 108, periodically, the adjustable pulse frequency and the individually variable pulse amplitude in the pulse sequence data, for each pulse signal of the individually variable pulse signals. The adjustable pulse frequency and the individually variable pulse amplitude is within a pre-defined very high-frequency range and a pre-defined pulse amplitude range optimised for de-sulphation.
At step 514, the method 500 includes transmitting, by the processor 108, the modified adjustable pulse frequency and the individually variable pulse amplitude in the pulse sequence data to the control unit 114. The control unit 114 apply, via terminals of the at least one lead-acid battery 104, at least one of the sequential repetition of individually variable pulse signals, the modified adjustable pulse frequency, and the modified individually variable pulse amplitude, as a charging current to the at least one lead-acid battery 104 for the de-sulphation and a regeneration. The at least one lead-acid battery 104 may be charged to original condition upon completion of the de-sulphation.
The order in which the method 500 is described is not intended to be construed as a limitation, and any number of the described method blocks may be combined or otherwise performed in any order to implement the method 500 or an alternate method. Additionally, individual blocks may be deleted from the method 500 without departing from the spirit and scope of the ongoing description. Furthermore, the method 500 may be implemented in any suitable hardware, software, firmware, or a combination thereof, that exists in the related art or that is later developed. The method 500 describes, without limitation, the implementation of the computing system 106. A person of skill in the art will understand that method 500 may be modified appropriately for implementation in various manners without departing from the scope and spirit of the ongoing description.
Various embodiments of the present disclosure provide a battery regeneration system for optimizing de-sulfation of a lead-acid type storage battery and method thereof. The present disclosure enables reusing end-of-life lead-acid batteries, contributing to a reduction in the procurement of new batteries. This not only conserves natural resources but also minimizes the energy-intensive manufacturing process. Environmental concerns is addressed by significantly reducing hazardous emissions during battery disposal through smelting. This proactive step towards sustainability underscores our commitment to preserving the environment. The present disclosure provides substantial cost savings by eliminating the need for periodic replacements of end-of-life batteries, thereby reducing capital expenditures. The capability of the technology may include to assess sulphation on battery terminals and grids without requiring battery opening sets it apart from conventional methods that necessitate invasive procedures. The present disclosure provides system and method to accurately predicts the amount of gel/acid required for battery regeneration without the need for battery disassembly, streamlining the maintenance process.
Unlike conventional methods that employ high direct current and voltage, the present disclosure uses variable low voltages and currents, ensuring effective sulphate removal without risking damage to the battery terminals. The present disclosure employ high-frequency cross-pulsing technology, in contrast to the low-frequency approach of conventional methods. This prevents excessive temperature rise within the batteries, safeguarding them from permanent damage. The present disclosure introduces moisture on the terminal surfaces, offering protection against impacts and aiding in the dissolution of sulphate back into the electrolyte. Conventional methods typically lack this moisture-generation feature. Unlike traditional approaches that involve adding acids/gels/distilled water before charging, the present disclosure follows a 3-in-1 process. The system breaks down sulphate, dissolves it back into the electrolyte, and charges the battery to its original condition, all without introducing external elements. Real-time communication of all battery cell parameters to a central depository (NOC) through a Battery Monitoring System (BMS) underscores enables efficient and data-driven battery management.
The written description describes the subject matter herein to enable any person skilled in the art to make and use the embodiments. The scope of the subject matter embodiments is defined by the claims and may include other modifications that occur to those skilled in the art. Such other modifications are intended to be within the scope of the claims if they have similar elements that do not differ from the literal language of the claims or if they include equivalent elements with insubstantial differences from the literal language of the claims.
A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary, a variety of optional components are described to illustrate the wide variety of possible embodiments of the invention. When a single device or article is described herein, it will be apparent that more than one device/article (whether they cooperate) may be used in place of a single device/article. Similarly, where more than one device or article is described herein (whether or not they cooperate), it will be apparent that a single device/article may be used in place of the more than one device or article, or a different number of devices/articles may be used instead of the shown number of devices or programs. The functionality and/or the features of a device may be alternatively embodied by one or more other devices which are not explicitly described as having such functionality/features. Thus, other embodiments of the invention need not include the device itself.
The illustrated steps are set out to explain the exemplary embodiments shown, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope and spirit of the disclosed embodiments. Also, the words “comprising”, “having”, “containing”, and “including”, and other similar forms are intended to be equivalent in meaning and be open-ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items, or meant to be limited to only the listed item or items. It must also be noted that as used herein and in the appended claims, the singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise.
Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the invention be limited not by this detailed description, but rather by any claims that issue on an application based here on. Accordingly, the embodiments of the present invention are intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims. , Claims:CLAIMS
We claim:
1. A battery regeneration system (100) comprising:
one or more sensors (102), communicatively coupled to at least one lead-acid battery (104), configured to determine one or more battery parameters corresponding to the at least one lead-acid battery (104), wherein the one or more battery parameters are determined during at least one of a charging cycle and a discharging cycle of the at least one lead-acid battery (104);
a processor (108) communicatively coupled to one or more sensors (102);
a memory (110) coupled to the processor (108), wherein the memory (110) comprises processor (108)-executable instructions, which on execution, cause the processor (108) to:
receive the determined one or more battery parameters from the one or more sensors (102);
analyse the one or more battery parameters to determine at least one of a sulphation level corresponding to a severity of sulphation and a conductive medium level corresponding to an amount of conductive medium retained in the at least one lead-acid battery (104);
determine, using one or more Artificial Intelligence (AI)-based techniques, an appropriate very high-frequency cross-pulsing technique for a de-sulfation of at least one lead-acid battery (104), based on the determined sulfation level, wherein the very high-frequency cross-pulsing technique is in Kilohertz (KHz) range of frequencies;
generate, using one or more pulse signals of the individually variable pulse signals comprises adjustable pulse frequency AI-based techniques, pulse sequence data corresponding to a sequential repetition of individually variable pulse signals, based on the determined appropriate very high-frequency cross pulsing technique, wherein each pulse signal of the individually variable pulse signals comprises an adjustable pulse frequency and an individually variable pulse amplitude;
transmit, via a communication channel, the generated pulse sequence data to a control unit (114), for the de-sulfation of at least one lead-acid battery (104), and transmit the determined conductive medium level to a Battery Monitoring System (BMS) (118), based on the amount of the conductive medium retained in the at least one lead-acid battery (104);
modify periodically, the adjustable pulse frequency and the individually variable pulse amplitude in the pulse sequence data, for each pulse signal of the individually variable pulse signals, wherein the adjustable pulse frequency and the individually variable pulse amplitude is within a pre-defined very high-frequency range and a pre-defined pulse amplitude range optimised for de-sulphation; and
transmit the modified adjustable pulse frequency and the individually variable pulse amplitude in the pulse sequence data to the control unit (114); and
the control unit (114) communicatively coupled to the processor (108) is configured to:
receive at least one of the generated pulse sequence data, the modified adjustable pulse frequency and the modified individually variable pulse amplitude from the processor (108) via the communication channel;
generate at least one of the sequential repetition of individually variable pulse signals, the modified adjustable pulse frequency, and the modified individually variable pulse amplitude, based on the received data; and
apply, via terminals of the at least one lead-acid battery (104), at least one of the generated sequential repetition of individually variable pulse signals, the modified adjustable pulse frequency, and the modified individually variable pulse amplitude, as a charging current to the at least one lead-acid battery (104) for the de-sulphation and a regeneration, wherein the at least one lead-acid battery (104) is charged to original condition upon completion of the de-sulphation.

2. The battery regeneration system (100) as claimed in claim 1, further comprises:
the BMS (118) configured to:
monitor periodically, via the one or more sensors (102), the one or more battery parameters corresponding to the at least one lead-acid battery (104), during the charging cycle and discharging cycle; and
transmit the monitored one or more battery parameters to a server (120) associated with the BMS (118); and
the server (120) configured to:
receive the monitored one or more battery parameters from the BMS (118);
generate a statistical data corresponding to monitored one or more battery parameters, wherein the statistical data comprises a State of Health (SoH) of the at least one lead-acid battery (104); and
display, via a user interface associated with an electronic device (122), the generated statistical data as one or more Network Operations Centre (NOC) services.

3. The battery regeneration system (100) as claimed in claim 2, wherein the BMS (118) is further configured to:
receive the determined conductive medium level from the processor (108), based on the amount of the conductive medium retained in the at least one lead-acid battery (104);
determine the amount of conductive medium required to be filled in the at least one lead-acid battery (104);
generate, via the server (120), an alert to the electronic device (122), based on the determined amount of conductive medium required to be filled in the at least one lead-acid battery (104)

4. The battery regeneration system (100) as claimed in claim 1, wherein the control unit (114) is further configured to:
monitor, in real-time, via a feedback loop connected to the one or more sensors (102), a response of the at least one lead-acid battery (104) to the applied at least one of the generated sequential repetition of individually variable pulse signals, the modified adjustable pulse frequency, and the modified individually variable pulse amplitude;
transmit the response of the at least one lead-acid battery (104) to the processor (108);
receive the modified adjustable pulse frequency and the modified individually variable pulse amplitude from the processor (108) via the communication channel, based on the transmitted response;
generate the modified adjustable pulse frequency and the modified individually variable pulse amplitude, based on the received data; and
apply, via the terminals of the at least one lead-acid battery (104), the modified adjustable pulse frequency, and the modified individually variable pulse amplitude, to the at least one lead-acid battery (104) for the de-sulphation.

5. The battery regeneration system (100) as claimed in claim 1, wherein the control unit (114) further comprises:
a pulse generation unit (116) configured to:
generate at least one of pulse width modulated signals and asymmetrical pulse width modulated signals based on the determined appropriate very high-frequency cross pulsing technique for the de-sulfation.

6. The battery regeneration system (100) as claimed in claim 1, wherein the processor (108) is further configured to:
determine a stage of sulphation in the at least one lead-acid battery (104) based on at least one a low voltage, a high impedance, a high rate of rise in temperature, and changes in temperature patterns within the at least one lead-acid battery (104).

7. The battery regeneration system (100) as claimed in claim 1, wherein for analysing the one or more battery parameters, the processor (108) is further configured to:
identify changes in at least one of a voltage profile, a current profile, an impedance profile, and a temperature profile of at least one lead-acid battery (104), indicative of the severity of sulphation; and
determine at least one of an amplitude, a frequency and a pulse duration for each pulse required to be applied for de-sulphation.

8. The battery regeneration system (100) as claimed in claim 1, wherein de-sulphation comprises initially breaking sulphate deposits and subsequently dissolving the broken sulphation by creating a plurality of minute bubbles at a grid of the at least one lead-acid battery (104).

9. The battery regeneration system (100) as claimed in claim 1, wherein for determining the conductive medium level corresponding to an amount of conductive medium retained in the at least one lead-acid battery (104), the processor (108) is further configured to analyse varying capacitance conductive medium retained in the at least one lead-acid battery (104).

10. The battery regeneration system (100) as claimed in claim 1, wherein the one or more sensors (102) comprises at least one of a conductive medium sensing sensor, a level of sulphation sensing sensor, a capacitive type of sensor, a voltage measuring senor, a current measuring sensor, an ultrasonic level sensor, and an internal resistance sensor.

11. The battery regeneration system (100) as claimed in claim 1, wherein the one or more battery parameters comprises at least one of a voltage value, a current value, a temperature value, an impedance value, an internal resistance value, and a capacitance value.

12. The battery regeneration system (100) as claimed in claim 1, wherein the very high-frequency cross pulsing technique utilises at least one of a cross-pulse technique and a Direct Current (DC) pulse technique for a controlled and a targeted approach for the de-sulfation of the at least one battery, wherein the very high-frequency cross pulsing technique maintains temperature within a pre-defined temperature in the at least one lead-acid battery (104) during de-sulphation.

13. The battery regeneration system (100) as claimed in claim 1, wherein during the charging cycle, an effect of the very high-frequency cross pulsing technique creates a plurality of minute bubbles in a moisture content of the conductive medium to dissolve the broken sulphate back in a sulphuric acid for regaining a specific gravity of the conductive medium, wherein the plurality of minute bubbles are formed based on a result of electrochemical processes due to continuous a very high-frequency pulse charge and pulse discharge on a grid of the at least one lead-acid battery (104).

14. A battery regeneration method comprising:
receiving, by a processor (108) associated with a battery regeneration system (100), one or more battery parameters corresponding to at least one lead-acid battery (104) from one or more sensors (102) communicatively coupled to at least one lead-acid battery (104), wherein the one or more battery parameters are determined during at least one of a charging cycle and a discharging cycle of the at least one lead-acid battery (104);
analysing, by the processor (108), the one or more battery parameters to determine at least one of a sulphation level corresponding to a severity of sulphation and a conductive medium level corresponding to an amount of conductive medium retained in the at least one lead-acid battery (104);
determining, by the processor (108), using one or more Artificial Intelligence (AI)-based techniques, an appropriate very high-frequency cross pulsing technique for a de-sulfation of the at least one lead-acid battery (104), based on the determined sulfation level, wherein the very high-frequency cross-pulsing technique is in Kilohertz (KHz) range of frequencies;
generating, by the processor (108), using the one or more AI-based techniques, pulse of individually sequence data corresponding to a sequential repetition variable pulse signals, based on the determined appropriate very high-frequency cross pulsing technique, wherein each pulse signal of the individually variable pulse signals comprises an adjustable pulse frequency and an individually variable pulse amplitude;
transmitting, by the processor (108), via a communication channel, the generated pulse sequence data to a control unit (114), for the de-sulfation of the at least one lead-acid battery (104), and transmit the determined conductive medium level to a Battery Monitoring System (BMS) (118), based on the amount of the conductive medium retained in the at least one lead-acid battery (104);
modifying, by the processor (108), periodically, the adjustable pulse frequency and the individually variable pulse amplitude in the pulse sequence data, for each pulse signal of the individually variable pulse signals, wherein the adjustable pulse frequency and the individually variable pulse amplitude is within a pre-defined very high-frequency range and a pre-defined pulse amplitude range optimised for de-sulphation; and
transmitting, by the processor (108), the modified adjustable pulse frequency and the individually variable pulse amplitude in the pulse sequence data to the control unit (114), wherein the control unit (114) apply, via terminals of the at least one lead-acid battery (104), at least one of the sequential repetition of individually variable pulse signals, the modified adjustable pulse frequency, and the modified individually variable pulse amplitude, as a charging current to the at least one lead-acid battery (104) for the de-sulphation and a regeneration, wherein the at least one lead-acid battery (104) is charged to original condition upon completion of the de-sulphation.

15. The battery regeneration method as claimed in claim 14 further comprising:
receiving, by the control unit (114) communicatively coupled to the processor (108), at least one of the generated pulse sequence data, the modified adjustable pulse frequency and the modified individually variable pulse amplitude from the processor (108) via the communication channel;
generating, by the control unit (114), at least one of the sequential repetition of individually variable pulse signals, the modified adjustable pulse frequency, and the modified individually variable pulse amplitude, based on the received data; and
applying, by the control unit (114), via terminals of the at least one lead-acid battery (104), at least one of the generated sequential repetition of individually variable pulse signals, the modified adjustable pulse frequency, and the modified individually variable pulse amplitude, as a charging current to the at least one lead-acid battery (104) for the de-sulphation and a regeneration, wherein the at least one lead-acid battery (104) is charged to original condition upon completion of the de-sulphation.

16. The battery regeneration method as claimed in claim 14 further comprising:
monitoring periodically, by the BMS (118), via the one or more sensors (102), the one or more battery parameters corresponding to the at least one lead-acid battery (104), during the charging cycle and discharging cycle;
transmitting, by the BMS (118), the monitored one or more battery parameters to a server (120) associated with the BMS (118);
receiving, by the server (120), the monitored one or more battery parameters from the BMS (118);
generating, by the server (120), a statistical data corresponding to monitored one or more battery parameters, wherein the statistical data comprises a State of Health (SoH) of the at least one lead-acid battery (104); and
displaying, by the server (120), via a user interface associated with an electronic device (122), the generated statistical data as one or more Network Operations Centre (NOC) services.

17. The battery regeneration method as claimed in claim 16 further comprising:
receiving, by the BMS (118), the determined conductive medium level from the processor (108), based on the amount of the conductive medium retained in the at least one lead-acid battery (104);
determining, by the BMS (118), the amount of conductive medium required to be filled in the at least one lead-acid battery (104);
generating, by the BMS (118), via the server (120), an alert to the electronic device (122), based on the determined amount of conductive medium required to be filled in the at least one lead-acid battery (104)

18. The battery regeneration method as claimed in claim 15 further comprising:
monitoring, by the control unit (114), in real-time, via a feedback loop connected to the one or more sensors (102), a response of the at least one lead-acid battery (104) to the applied at least one of the generated sequential repetition of individually variable pulse signals, the modified adjustable pulse frequency, and the modified individually variable pulse amplitude;
transmitting, by the control unit (114), the response of the at least one lead-acid battery (104) to the processor (108);
receiving, by the control unit (114), the modified adjustable pulse frequency and the modified individually variable pulse amplitude from the processor (108) via the communication channel, based on the transmitted response;
generating, by the control unit (114), the modified adjustable pulse frequency and the modified individually variable pulse amplitude, based on the received data; and
applying, by the control unit (114), via the terminals of the at least one lead-acid battery (104), the modified adjustable pulse frequency, and the modified individually variable pulse amplitude, to the at least one lead-acid battery (104) for the de-sulphation.

19. The battery regeneration method as claimed in claim 14 further comprising:
generating, by the control unit (114), via a pulse generation unit (116), at least one of pulse width modulated signals and asymmetrical pulses width modulated signals based on the determined appropriate very high-frequency cross pulsing technique for the de-sulfation.

20. The battery regeneration method as claimed in claim 14 further comprising:
determining, by the processor (108), a stage of sulphation in the at least one lead-acid battery (104) based on at least one a low voltage, a high impedance, a high rate of rise in temperature, and changes in temperature patterns within the at least one lead-acid battery (104).

21. The battery regeneration method as claimed in claim 14, wherein analysing the one or more battery parameters further comprises:
identifying, by the processor (108), changes in at least one of a voltage profile, a current profile, an impedance profile, and a temperature profile of the at least one lead-acid battery (104), indicative of the severity of sulphation; and
determining, by the processor (108), at least one of an amplitude, a frequency and a pulse duration for each pulse required to be applied for de-sulphation.

22. The battery regeneration method as claimed in claim 14, wherein de-sulphation comprises initially breaking sulphate deposits and subsequently dissolving the broken sulphation by creating a plurality of minute bubbles at a grid of the at least one lead-acid battery (104).

23. The battery regeneration method as claimed in claim 14, wherein determining the conductive medium level corresponding to an amount of conductive medium retained in the at least one lead-acid battery (104), further comprises analysing, by the processor (108), varying capacitance conductive medium retained in the at least one lead-acid battery (104).

24. The battery regeneration method as claimed in claim 14, wherein the one or more battery parameters comprises at least one of a voltage value, a current value, a temperature value, an impedance value, an internal resistance value, and a capacitance value.

25. The battery regeneration method as claimed in claim 14, wherein the very high-frequency cross pulsing technique utilises at least one of a cross-pulse technique and a Direct Current (DC) pulse technique for a controlled and a targeted approach for the de-sulfation of the at least one battery, wherein the very high-frequency cross pulsing technique maintains temperature within a pre-defined temperature in the at least one lead-acid battery (104) during de-sulphation.

26. The battery regeneration method as claimed in claim 14, wherein during the charging cycle, an effect of the very high-frequency cross pulsing technique creates a plurality of minute bubbles in a moisture content of the conductive medium to dissolve the broken sulphate back in a sulphuric acid for regaining a specific gravity of the conductive medium, wherein the bubble plurality of minute bubbles is formed based on a result of electrochemical processes due to continuous a very high-frequency pulse charge and pulse discharge on a grid of the at least one lead-acid battery (104).