Description:TECHNICAL FIELD

The present disclosure generally relates to a field of electric vehicles, and more specifically, relates to a system and a method for determining internal resistance of a battery unit associated with an electric vehicle (EV) in order to facilitate accurate determination of State of Health (SOH) of the battery unit and actual range of the EV.

BACKGROUND

Battery units, such as rechargeable batteries, have been widely used due to the advantages of high energy density, high operating voltage, extended service life, and minimal self-discharge. However, with the increasing popularity of electric vehicles (EVs), higher requirements are imposed on the energy density and fast charging performance of the rechargeable batteries. The State of Health (SOH) of the battery unit is typically assessed in terms of a capacity fade and a power fade. Capacity fade refers to an absolute energy storage capacity change of each cell associated with the battery unit. Conversely, the power fade involves a shift in the usable capacity of each cell, in that, a percentage of the usable capacity is lost as heat. The percentage changes throughout the lifespan of each cell associated with the battery unit.

EV battery units are subjected to diverse riding and environmental conditions. The variable conditions contribute to changes in the internal resistance of battery cells over time, consequently influencing the overall performance of the battery unit. Characterizing the usable capacity lost over time is crucial for accurately estimating the characteristics associated with battery applications such as SOH, State of Charge (SOC), actual range, etc. Failing to accurately consider the usable capacity lost over time may lead to inaccurate determination of SOC and actual range of the EV, and the like. For example, the usable capacity of the battery unit may be overestimated, potentially causing the battery unit to be discharged completely before utilizing the estimated capacity.

In battery units, the internal resistance plays a crucial role in determining the efficiency and health of the battery unit. The battery unit may be affected by factors such as temperature, charge-discharge cycles, and overall usage patterns. As the battery unit undergoes variable operational conditions, the internal resistance may change leading to a potential impact on the performance and capacity of the battery unit. For instance, internal resistance of the battery unit may increase over time which may reduce the usable capacity of the battery unit.

There exist various methods to measure the internal resistance of batteries, however, conventional methods measure the laboratory-level internal resistance of the batteries. Conventional methods do not consider the change in internal resistance during usage of the batteries, rather, the laboratory-level internal resistance is considered to determine battery characteristics thereby leading to inaccurate determination of battery characteristics. Further, conventionally known methods lack real-time measurement of the internal resistance of batteries in on-field products. Moreover, there does not exist any method to estimate internal resistance of batteries in both charge and discharge states of the batteries without adversely affecting the performance of the batteries.

Therefore, in view of the above-mentioned problems, it is desirable to provide a system and a method to efficiently and accurately determine internal resistance of each cell in a battery unit and consequently facilitate accurate determination of SOH, SOC, actual range, and other parameters associated with the battery unit.

SUMMARY

This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention. This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.

According to an embodiment of the present disclosure, disclosed herein is a method for determining internal resistance of a battery unit associated with an electric vehicle (EV). The method comprises, for each State of Charge (SOC) value amongst a pre-defined set of SOC values associated with the battery unit, detecting, at a first time instance, a first terminal voltage value for each cell associated with the battery unit. Further, the method comprises triggering a control action to cause a change in a current flowing through the battery unit upon detecting the first terminal voltage value. Furthermore, the method comprises detecting, at a second time instance upon triggering the control action, a second terminal voltage value for each cell associated with the battery unit. In addition, the method comprises determining the internal resistance of the battery unit based on a change in the second terminal voltage value with respect to the first terminal voltage value a current value indicative of the current flowing through the battery unit at one of the first time instance or the second time instance, and a state of the EV. The internal resistance is indicative of a State of Health (SOH) of the battery unit.

According to another embodiment of the present disclosure, disclosed herein is a system for determining internal resistance of a battery unit associated with an electric vehicle (EV). The system is associated with a Battery Management System (BMS) of the EV. The system comprises a memory and at least one processor in communication with the memory. The at least one processor is configured to, for each State of Charge (SOC) value amongst a pre-defined set of SOC values associated with the battery unit, detect, at a first time instance, a first terminal voltage value for each cell associated with the battery unit. Further, the at least one processor is configured to trigger a control action to cause a change in a current flowing through the battery unit upon detecting the first terminal voltage value. Further, the at least one processor is configured to detect, at a second time instance upon triggering the control action, a second terminal voltage value for each cell associated with the battery unit. Furthermore, the at least one processor is configured to determine the internal resistance of the battery unit based on a change in the first terminal voltage value with respect to the second terminal voltage value, a current value indicative of the current flowing through the battery unit at one of the first time instance or the second time instance, and a state of the EV, wherein the internal resistance is indicative of a State of Health (SOH) of the battery unit.

The present invention provides the system and the method to address limitations by focusing on the power fade of SOH. SOH may be a critical parameter representing the health of the battery unit. The system involves determining the internal resistance of the cell over time, allowing for the calculation of corresponding change in the power loss of the battery unit throughout the lifespan of the battery unit. The system coordinates with the electric motor to induce the voltage drop, thereby enabling the determination of internal resistance. Unlike existing solutions, the system allows for the measurement of internal resistance in both charge and standby (discharging) states, providing more comprehensive understanding of the health of the battery unit.

To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features, aspects, and advantages of the present invention will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein:

Figure 1A illustrates a block diagram depicting an embodiment of an Electronic Control Unit (ECU) of a vehicle, in accordance with an embodiment of the present disclosure;

Figure 1B illustrates a block diagram depicting a system for determining an internal resistance of a battery unit associated with an electric vehicle (EV), in accordance with an embodiment of the present disclosure;

Figure 2 illustrates a block diagram depicting a system for determining internal resistance of the battery unit, in accordance with an embodiment of the present disclosure;

Figure 3 illustrates a block diagram depicting modules associated with the system for determining the internal resistance of the battery unit, in accordance with an embodiment of the present disclosure;

Figure 4 illustrates a process flow depicting a process for determining internal resistance in charging and standby states, in accordance with an embodiment of the present disclosure;

Figure 5 illustrates a process flow depicting a method for determining the internal resistance of the battery unit associated with the electric vehicle, according to an embodiment of the present disclosure;

Figure 6A illustrates an exemplary graph depicting determination of internal resistance during a charging state of the EV, according to an embodiment of the present disclosure; and

Figure 6B illustrates an exemplary graph depicting determination of internal resistance during a standby state of the EV, according to an embodiment of the present disclosure.

Further, skilled artisans will appreciate that elements in the drawings 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 drawings by conventional symbols, and the drawings may show only those specific details that are pertinent to understanding the embodiments of the present invention so as not to obscure the drawings with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein.

DETAILED DESCRIPTION OF FIGURES

For the purpose of promoting an understanding of the principles of the present disclosure, reference will now be made to the various embodiments and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of the present disclosure is thereby intended, such alterations and further modifications in the illustrated system, and such further applications of the principles of the present disclosure as illustrated therein being contemplated as would normally occur to one skilled in the art to which the present disclosure relates.

It will be understood by those skilled in the art that the foregoing general description and the following detailed description are explanatory of the present disclosure and are not intended to be restrictive thereof.

Whether or not a certain feature or element was limited to being used only once, it may still be referred to as “one or more features” or “one or more elements” or “at least one feature” or “at least one element.” Furthermore, the use of the terms “one or more” or “at least one” feature or element do not preclude there being none of that feature or element, unless otherwise specified by limiting language including, but not limited to, “there needs to be one or more…” or “one or more elements is required.”

Reference is made herein to some “embodiments.” It should be understood that an embodiment is an example of a possible implementation of any features and/or elements of the present disclosure. Some embodiments have been described for the purpose of explaining one or more of the potential ways in which the specific features and/or elements of the proposed disclosure fulfil the requirements of uniqueness, utility, and non-obviousness.

Use of the phrases and/or terms including, but not limited to, “a first embodiment,” “a further embodiment,” “an alternate embodiment,” “one embodiment,” “an embodiment,” “multiple embodiments,” “some embodiments,” “other embodiments,” “further embodiment”, “furthermore embodiment”, “additional embodiment” or other variants thereof do not necessarily refer to the same embodiments. Unless otherwise specified, one or more particular features and/or elements described in connection with one or more embodiments may be found in one embodiment, or may be found in more than one embodiment, or may be found in all embodiments, or may be found in no embodiments. Although one or more features and/or elements may be described herein in the context of only a single embodiment, or in the context of more than one embodiment, or in the context of all embodiments, the features and/or elements may instead be provided separately or in any appropriate combination or not at all. Conversely, any features and/or elements described in the context of separate embodiments may alternatively be realized as existing together in the context of a single embodiment.

Any particular and all details set forth herein are used in the context of some embodiments and therefore should not necessarily be taken as limiting factors to the proposed disclosure.

The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such process or method. Similarly, one or more devices or sub-systems or elements or structures or components proceeded by “comprises... a” does not, without more constraints, preclude the existence of other devices or other sub-systems or other elements or other structures or other components or additional devices or additional sub-systems or additional elements or additional structures or additional components.

Embodiments of the present disclosure will be described below in detail with reference to the accompanying drawings.

For the sake of clarity, the first digit of a reference numeral of each component of the present disclosure is indicative of the Figure number, in which the corresponding component is shown. For example, reference numerals starting with digit “1” are shown at least in Figure 1. Similarly, reference numerals starting with digit “2” are shown at least in Figure 2.

An Electric Vehicle (EV) or a battery powered vehicle including, but not limited to, two-wheelers, such as scooters, mopeds, and motorbikes/motorcycles; three-wheelers, such as auto-rickshaws, four-wheelers, such as cars, and other Light Commercial Vehicles (LCVs) and Heavy Commercial Vehicles (HCVs) primarily work on the principle of driving an electric motor using the power from the batteries provided in the EV. Further, the electric vehicle may have at least one wheel which is electrically powered to traverse such a vehicle. The term ‘wheel’ may be referred to any ground-engaging member which allows traversal of the electric vehicle over a path. The types of EVs include Battery Electric Vehicles (BEVs), Hybrid Electric Vehicles (HEVs), and Range Extended Electric Vehicles. However, the subsequent paragraphs pertain to the different elements of a Battery Electric Vehicle (BEV).

In construction, an EV typically includes hardware components, such as a battery or battery pack enclosed within a battery casing and includes a Battery Management System (BMS), an on-board charger, a Motor Controller Unit (MCU), an electric motor, and an electric transmission system. In addition to the hardware components/elements, the EV may be supported with software modules including intelligent features including and not limited to navigation assistance, hill assistance, cloud connectivity, Over-The-Air (OTA) updates, adaptive display techniques and so on. The firmware of the EV may also include Artificial Intelligence (AI) & Machine Learning (ML) driven modules which enable the prediction of a plurality of parameters such as and not limited to driver/rider behaviour, road condition, charging infrastructures/charging grids in the vicinity and so on. The data pertaining to the intelligent features may be displayed through a display unit present in the dashboard of the vehicle. In one embodiment, the display unit may contain a Liquid Crystal Display (LCD) screen of a predefined dimension. In another embodiment, the display unit may contain a Light-Emitting Diode (LED) screen of a predefined dimension. The display unit may be a water-resistant display supporting one or more User-Interface (UI) designs. The EV may support multiple frequency bands such as 2G, 3G, 4G, 5G and so on. Additionally, the EV may also be equipped with wireless infrastructure such as, and not limited to Bluetooth, Wi-Fi and so on to facilitate wireless communication with other EVs or the cloud.

The ECU of the EV, depicted in Figure 1A, is responsible for managing all the operations of the EV, wherein the key elements of the ECU (10) typically includes (i) a microcontroller core (or processor unit) (12); (ii) a memory unit (14); (iii) a plurality of input (16) and output modules (18) and (iv) communication protocols including, but not limited to CAN protocol, Serial Communication Interface (SCI) protocol and so on. The sequence of programmed instructions and data associated therewith can be stored in a non-transitory computer-readable medium such as memory unit or storage device which may be any suitable memory apparatus such as, but not limited to read-only memory (ROM), programmable read-only memory (PROM), electrically erasable programmable read-only memory (EEPROM), random-access memory (RAM), flash memory, disk drive and the like. In one or more embodiments of the disclosed subject matter, non-transitory computer-readable storage media can be embodied with a sequence of programmed instructions for monitoring and controlling the operation of different components of the EV.

The processor may include any computing system which includes, but is not limited to, Central Processing Unit (CPU), an Application Processor (AP), a Graphics Processing Unit (GPU), a Visual Processing Unit (VPU), and/or an AI-dedicated processor such as a Neural Processing Unit (NPU). In an embodiment, the processor can be a single processing unit or several units, all of which could include multiple computing units. The processor may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Among other capabilities, the processor is configured to fetch and execute computer-readable instructions and data stored in the memory. The instructions can be compiled from source code instructions provided in accordance with a programming language such as Java, C++, C#.net or the like. The instructions can also comprise code and data objects provided in accordance with, for example, the Visual Basic™ language, LabVIEW, or another structured or object-oriented programming language. The one or a plurality of processors control the processing of the input data in accordance with a predefined operating rule or artificial intelligence (AI) model stored in the non-volatile memory and the volatile memory. The predefined operating rule or artificial intelligence model is provided through training or learning algorithms which include, but are not limited to, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning.

Furthermore, the modules, processes, systems, and devices can be implemented as a single processor or as a distributed processor. Also, the processes, modules, and sub-modules described in the various figures of and for embodiments herein may be distributed across multiple computers or systems or may be co-located in a single processor or system. Further, the modules can be implemented in hardware, instructions executed by a processing unit, or by a combination thereof. The processing unit can comprise a computer, a processor, such as the processor, a state machine, a logic array, or any other suitable devices capable of processing instructions. The processing unit can be a general-purpose processor which executes instructions to cause the general-purpose processor to perform the required tasks or, the processing unit can be dedicated to performing the required functions. In another embodiment of the present disclosure, the modules may be machine-readable instructions (software) which, when executed by a processor/processing unit, perform any of the described functionalities. In an embodiment, the modules may include a receiving module, a generating module, a comparing module, a pairing module, and a transmitting module. The receiving module, the generating module, the comparing module, the pairing module, and the transmitting module may be in communication with each other. The data serves, amongst other things, as a repository for storing data processed, received, and generated by one or more of the modules. Exemplary structural embodiment alternatives suitable for implementing the modules, sections, systems, means, or processes described herein are provided below.

Figure 1B illustrates a block diagram depicting a system (100) for determining an internal resistance of a battery unit (110) associated with an electric vehicle (EV) (102).

Further, in construction, the EV (102) may comprise hardware components such as a battery unit (110) or a battery module enclosed within a battery casing to form a battery pack, a Battery Management System (BMS) (104), a Motor Controller Unit (MCU) (106), and an electric motor (108). The EV (102) may further include an on-board battery charger and an electric transmission system. The primary function of the above-mentioned elements is detailed in the subsequent paragraphs: The battery unit (110) of the EV (102) (also known as Electric Vehicle Battery (EVB) or traction battery) is re-chargeable in nature and is the primary source of energy required for the operation of the EV (102). The battery unit (110) is typically charged using the electric current taken from the grid through a charging infrastructure. The battery unit (110) may be charged using an Alternating Current (AC) or a Direct Current (DC). In the case of AC input, the on-board battery charger converts the AC signal to DC signal after which the DC signal is transmitted to the battery unit (110) via the BMS (104). However, in case of DC charging, the on-board battery charger is bypassed, and the current is transmitted directly to the battery unit (110) via the BMS. In an embodiment, the on-board battery charger may be interchangeably referred as a battery charger, without departing from the scope of the present disclosure.

The battery unit (110) may include a plurality of cells (112) which are grouped into a plurality of modules in a manner in which the temperature difference between the cells (112) does not exceed a predetermined value, such as, 5 degrees Celsius. The terms “battery”, “cell”, and “battery cell” may be used interchangeably and may refer to any of a variety of different rechargeable cell compositions and configurations including, but not limited to, lithium-ion (e.g., lithium iron phosphate, lithium cobalt oxide, other lithium metal oxides, etc.), lithium-ion polymer, nickel metal hydride, nickel cadmium, nickel hydrogen, nickel-zinc, silver zinc, or any other battery type/configuration. The term “battery pack” or “battery unit” as used herein may be referred to multiple individual batteries enclosed within a single structure or multi-piece structure. The individual batteries may be electrically interconnected to achieve a desired voltage and capacity for a desired application.

The BMS (104) may be an electronic system configured to control the operation of the battery unit (110) and ensure that the battery unit (110) is operating safely and efficiently. The BMS (104) may be configured to continuously monitor different parameters of the battery unit (110) such as temperature, voltage, current, and so on, and communicates the monitored parameters to a control unit and the Motor Controller Unit (MCU) (106) in the EV (102) using a plurality of protocols including and not limited to Controller Area Network (CAN) bus protocol which facilitates the communication between the ECU/MCU and other peripheral elements of the EV (102) without the requirement of a host computer. A switch (114) may be associated with the battery unit (110) to enable charging of the battery unit (110) by establishing a closed electrical path for the flow of current into the battery unit (110). In an embodiment, the switch (114) may be controlled by the BMS (104).

The EV (102) may further be associated with the system (100) configured to determine an internal resistance of the battery unit (110). In an embodiment, the system (100) may be associated with the BMS (104). In an embodiment, the system (100) may be integrated within the BMS (104). In some embodiments, the system (100) may be connected to the battery management system (104) via a communication network. The communication network may include, without limitation, a direct interconnection, Local Area Network (LAN), Wide Area Network (WAN), wireless network (e.g., using Wireless Application Protocol (WAP)), the Internet, etc.

In an embodiment, the system (100) may be implemented in a cloud-based architecture or on a physical server (not shown). The system (100) may be configured to determine the internal resistance of the battery unit (110), as will be described in detail further below.

Referring to Figure 2, a block diagram of the system (100) is illustrated, in accordance with an embodiment of the present disclosure. The system (100) comprises a processor (210), a memory (220), and an Input/Output (I/O) interface (230). The system (100) further comprises a set of modules (240). The set of modules (240) may be configured to perform their designated functions in conjunction with the memory (220) and the processor (210).

In some embodiments, the memory (220) may be communicatively coupled to the processor (210) and the I/O interface (230). In some embodiments, the set of modules (240) may be included within the memory (220). The memory (220) may be configured to store data and instructions executable by the processor (210). The memory (220) may include a database (250) configured to store data.

The processor (210) may be disposed in communication with one or more input/output (I/O) devices via the respective I/O interface (230). The I/O interface (230) may employ communication code-division multiple access (CDMA), high-speed packet access (HSPA+), global system for mobile communications (GSM), long-term evolution (LTE), WiMax, or the like, etc.

Using the I/O interface (230), the system (100) may communicate with one or more I/O devices, specifically, the user devices associated with the human-to-human conversation. For example, the input device may be an antenna, microphone, touch screen, touchpad, storage device, transceiver, video device/source, etc. The output devices may be a video display (e.g., cathode ray tube (CRT), liquid crystal display (LCD), light-emitting diode (LED), plasma, Plasma Display Panel (PDP), Organic light-emitting diode display (OLED) or the like), audio speaker, etc.

In some embodiments, the set of modules (240) may include a set of instructions that may be executed to cause the system (100) to perform any one or more of the methods disclosed herein. The set of modules (240) may be configured to perform the steps of the present disclosure using the data stored in the memory (220), as discussed throughout this disclosure. In an embodiment, each of the set of modules (240) may be hardware units that may be outside the memory (220). Further, the memory (220) may include an operating system (251) for performing one or more tasks of the system (100).

The memory (220) may be operable to store instructions executable by the processor (210). The functions, acts, or tasks illustrated in the figures or described may be performed by the processor (210), in conjunction with the set of modules, for executing the instructions stored in the memory (220). The functions, acts, or tasks are independent of the particular type of instruction set, storage media, processor, or processing strategy and may be performed by software, hardware, integrated circuits, firmware, micro-code, and the like, operating alone or in combination. Likewise, processing strategies may include multiprocessing, multitasking, parallel processing, and the like.

For the sake of brevity, the architecture and standard operations of the memory (220) and the processor (210) are not discussed in detail. In one embodiment, the memory (220) may be configured to store the information as required by the set of modules (240) and/or the processor (210) to perform one or more functions to determine the internal resistance of the battery unit (110) associated with the EV (102).

In some embodiments, the database (250) may be configured to store information and parameters associated with the battery unit (110), such as, but not limited to, first terminal voltage value(s) (252), second terminal voltage value(s) (254), a current value (256), a voltage drop (258), and internal resistance array(s) (260).

In some embodiments, the memory (220) may communicate via a bus within the system (100). The memory (220) may include, but is not limited to, a non-transitory computer-readable storage media, such as various types of volatile and non-volatile storage media including, but not limited to, random access memory, read-only memory, programmable read-only memory, electrically programmable read-only memory, electrically erasable read-only memory, flash memory, magnetic tape or disk, optical media and the like. In one example, the memory (220) may include a cache or random-access memory for the processor. In alternative examples, the memory (220) is separate from the processor, such as a cache memory of a processor, the system memory, or other memory.

In one embodiment, the processor (210) may include specialized processing units such as integrated system (bus) controllers, memory management control units, floating point units, graphics processing units, digital signal processing units, etc. In one embodiment, the processor (210) may include a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), or both. The processor (210) may be one or more general processors, digital signal processors, application-specific integrated circuits, field-programmable gate arrays, servers, networks, digital circuits, analog circuits, combinations thereof, or other now-known or later developed devices for analysing and processing data. In some embodiments, the processor (210) may include one or a plurality of processors. The one or the plurality of processors may be a general-purpose processor, such as a central processing unit (CPU), an application processor (AP), or the like, a graphics-only processing unit such as a graphics processing unit (GPU), a visual processing unit (VPU), and/or an AI-dedicated processor such as a neural processing unit (NPU). The processor (210) may implement a software program, such as code generated manually (i.e., programmed).

Figure 3 illustrates a block diagram depicting the modules (240) of the system (100), in accordance with an embodiment of the present disclosure. The modules (240) comprise a detecting module (302), a triggering module (304), a determining module (306), and an updating module (308). Referring to Figures 1B, 2, and 3 together, the system (100) may be in communication with a user device associated with a user of EV (102). A web-based application may be provided on the user device and the user may provide a user input indicative of a request to determine the internal resistance of the battery unit (110) via the web-based application.

In an embodiment, the system (100) may be configured to determine the internal resistance of the battery unit (110) at a pre-defined State of Charge (SOC) value amongst a pre-defined set of SOC values associated with the battery unit (110). The pre-defined set of SOC values may refer to SOC values at which the internal resistance is to be determined. At each of the pre-defined set of SOC values, the system (100) may be configured to determine the internal resistance of the battery unit (110). As a non-limiting example, the pre-defined set of SOC values may include 25% SOC, 50% SOC, and 75% SOC and the system (100) may be configured to determine the internal resistance of the battery unit (110) when the SOC of the battery unit (110) is at 25% SOC, 50% SOC, and 75% SOC.

It is appreciated that the details regarding the determination of internal resistance will be described with respect to a particular SOC value from among the pre-defined set of SOC values, however, the details are equally applicable for each SOC value amongst the pre-defined set of SOC values. The system (100) may be configured to initiate determination of the internal resistance of the battery unit (110) when the battery unit (110) is at the particular SOC value, for instance, based on control signals from the BMS (104).

The detecting module (302), in conjunction with the processor (210), may be configured to detect, at a first time instance, the first terminal voltage value (252) for each cell (112) associated with the battery unit (110). In some embodiments, the first time instance may refer to a time instance when the particular SOC value amongst the pre-defined set of SOC values has been attained. In some embodiments, the first terminal voltage value (252) may be stored in the database (250).

Further, upon detecting the first terminal voltage value (252), the triggering module (304) in conjunction with the processor (210) may be configured to trigger a control action to cause a change in a current flowing through the battery unit (110). The control action may be triggered based on a state of the EV (102). The state of the EV (102) may include a charging state or a standby state. The charging state may refer to a state when the battery unit (110) is being charged via an external supply, i.e., a state where current is flowing into the battery unit (110). The standby state may refer to a state when current is flowing out of the battery unit (110) however the EV (102) is not being driven. The standby state as used in the present disclosure may thus be a type of discharging state where the current is flowing out of the battery unit (110), however, the EV (102) is not in movement.

In an embodiment, when the state of the EV (102) is detected as the charging state, the triggering module (304) may be configured to trigger the control action that includes ceasing a flow of the current to the battery unit (110) by deactivating the switch (114) associated with the battery unit (110). In other words, while the battery unit (110) is being charged, the flow of current into the battery unit (110) is ceased upon triggering the control action.

In an embodiment, when the state of the EV (102) is detected as the standby state, the triggering module (304) may be configured to trigger the control action that includes causing a flow of current to be drawn out of the battery unit (110). In particular, the triggering module (304) may send a request to the motor controller unit (106) associated with the EV (102) to receive a pre-defined amount of current from the battery unit (110). The motor controller unit (106) may receive the pre-defined amount of current from the battery unit (110), however, as the EV (102) is not being driven, the pre-defined amount of current is dissipated in the electric motor (108) associated with the EV (102). In an embodiment, the pre-defined amount of current is dissipated in motor windings of the electric motor (108) such that no torque is transferred to the wheels of the EV (102). The EV (102) can thus remain in the standby state while the pre-defined amount of current is drawn from the battery unit (110).

Further, once the control action is triggered, the detecting module (302), may further be configured to detect, at a second time instance, the second terminal voltage value (254) for each cell (112) associated with the battery unit (110). The second time instance refers to a time instance after the control action has been triggered. The detecting module (302) is thus configured to detect terminal voltage values associated with the battery unit (110) prior to the control action (i.e., the first terminal voltage value) and after the control action (i.e., the second terminal voltage value). In an embodiment, the detected first terminal voltage value (252) and the second terminal voltage value (254) are stored in the database (250).

Further, the determining module (306) may be configured to, in conjunction with the processor (210), determine the internal resistance of the battery unit (110) based on a change in the second terminal voltage value (254) with respect to the first terminal voltage value (252). The determining module (306) may further be configured to determine the internal resistance based on a current value (256) indicative of the current flowing through the battery unit (110) at one of the first time instance or the second time instance and the state of the EV (102).

In an embodiment, at a same SOC of the battery unit (110), the internal resistance value of each cell (112) of the battery unit (110) may vary in the charging state and the discharging state (standby state) due to an internal construction of the cells (112) of the battery unit (110) and electrochemical reactions within the cells (112) during the charging and discharging of the battery unit (110). The determining module (306) may be configured to determine the internal resistance value of the cell (112) when the EV (102) is in the charging state as well as when the EV (102) is in the standby state. In an embodiment, the battery unit (110) may include multiple cells (112) and the internal resistance in each state of the EV (102) may be determined for each of the multiple cells (112). In an alternate embodiment, the internal resistance in each state of the EV (102) may be determined for one or more of the multiple cells (112) and the determined internal resistance is considered for the remaining multiple cells (112).

It is appreciated that the details regarding the determination of the internal resistance may be detailed for a particular cell (112) of the battery unit (110) and the details are equally applicable for each of the multiple cells of the battery unit (110).

In an embodiment, the determining module (306) may be configured to determine the internal resistance for a cell (112) of the battery unit (110) during the charging state.

In the charging state, the determining module (306) may be configured to determine a voltage drop (258) associated with the battery unit based on the change in the second terminal voltage value (254) with respect to the first terminal voltage value (252). As mentioned above, the triggering module (304) is configured to deactivate the switch (114) and cease the flow of current into the battery unit (110). In particular, the triggering module (304) may cause the BMS (104) to open (deactivate) the switch (114) resulting in the current flowing through the battery unit (110) to suddenly drop to 0. The real time terminal voltages of the cell (112) before deactivation of the switch (at the first time instance) and after deactivation of the switch (at the second time instance) are determined. The sudden drop to 0 in the current value (256) results in the terminal voltage drop (258) between the measured first and second terminal voltages of the cell (112). The determining module (306) may be configured to determine the voltage drop (258) caused due to the sudden drop to 0 in the current value (256).

The determining module (306) may be configured to measure the current value (256) at the first time instance prior to the triggering of the control action, i.e., deactivation of the switch. Based on the determined voltage drop (258) and the measured current value (256) at the first time instance, the determining module (306) may be configured to determine the internal resistance.

In an embodiment, the voltage drop (258) may be determined based on the equation (1) below:
V_(t(k+?t))=V_tk- I*R_0 ………….(1)
where:
V_tk represents terminal voltage of the cell measured at time step k (first time instance),
V_(t(k+?t)) represents terminal voltage of the cell measured at time step k+?t (second time instance),
I represents current flowing through the cell at time step k, and
R_0 represents internal resistance of the cell at ?SOC?_k,i.e., SOC at time step k.

Further, the internal resistance may be determined based on the equation (2) below:

R_0 (?SOC?_k )=(V_tk-V_t(k+?t) )/I………….(2)

In the standby state, the determining module (306) may be configured to determine the voltage drop (258) associated with the battery unit based on the change in the second terminal voltage value (254) with respect to the first terminal voltage value (252). As mentioned above, the triggering module (304) is configured to send a request to the motor controller unit (106) to receive the pre-defined amount of current from the battery unit (110). The motor controller unit (106) receives the pre-defined amount of current from the battery unit (110) and dissipates the received amount of current in the electric motor (108) associated with the EV (102). The pre-defined amount of current drawn out of the battery unit (110) results in the voltage drop (258) in the terminal voltage of the battery unit (110), which may be determined based on the equation (1) above. That is, the real-time terminal voltages of the cell (112) before the motor controller unit receives the pre-defined amount of current (at the first time instance) and after the motor controller unit receives the pre-defined amount of current (at the second time instance) are determined. As a non-limiting example, in the standby state of the EV (102), at the first time instance, the triggering module (304) in conjunction with the BMS (104) may send a 0A current command to the motor controller unit (106) and at the second time instance, the triggering module (304) in conjunction with the BMS (104) may send a non-zero current command to the motor controller unit (106). In an embodiment, after the second time instance, the triggering module (304) in conjunction with the BMS (104) may again send a 0A current command to the motor controller unit (106).

Further, the pre-defined amount of current may be taken into account to determine the internal resistance. The determining module (306) may be configured to measure the current value (256) at the second time instance after triggering of the control action, i.e., sending the request to receive the pre-defined amount of current from the battery unit (110). Based on the determined voltage drop (258) and the measured current value (256) at the second time instance, the determining module (306) may be configured to determine the internal resistance using the equation (2) above.

It is appreciated that the details provided above with respect to equations (1) and (2) may be repeated at every SOC value amongst the pre-defined set of SOC values. Accordingly, the internal resistance of the battery unit (110) may be determined at multiple SOC values in both the charging and standby states of the EV (102). In an embodiment, the database (250) includes an internal resistance array (260) associated with the charging state of the EV (102) and an internal resistance array (260) associated with the standby state of the EV (102). The determined internal resistance may be stored in the respective internal resistance arrays (260). Thus, each of the internal resistance array (260) comprises a plurality of internal resistance values corresponding to the pre-defined set of SOC values.

Further, the updating module (308) in conjunction with the processor (210) may be configured to update the corresponding internal resistance arrays (260) associated with each of the charging state and the standby state of the EV (102). The corresponding internal resistance arrays (260) may be updated based on the determined internal resistance at each SOC value amongst the pre-defined set of SOC values.

In an embodiment, the determining module (306) may be configured to determine a new set of SOC values based on the internal resistance array (260) associated with the charging state and/or the internal resistance array (260) associated with the standby state. Further, the updating module (308) may be configured to update the pre-defined set of SOC values based on the new set of SOC values. Once the new set of SOC values are determined, the internal resistance may be determined for each SOC value amongst the new set of SOC values in a cyclic manner. As a result, the determination of the internal resistance in the charging state and/or the standby state may be performed at regular intervals during the lifetime of the battery unit (110).

In an embodiment, the internal resistance is indicative of a State of Health (SOH) of the battery unit (110), the SOH being related to condition of the battery unit (110) with respect to an ideal condition of the battery unit (110). In an embodiment, the updating module (308) in conjunction with the processor (210) may be configured to update the SOH of the battery unit (110) based on the updated internal resistance arrays (260) associated with the charging state and the standby state.

The updated internal resistance arrays (260) associated with the charging state and the standby state may be utilized by the BMS (104) to update a battery model of the battery unit (110). The battery model may refer to a representation or a simulation of operation of the battery unit (110) under different operating conditions. The battery model enables predicting various battery-related parameters and estimating performance of the battery unit (110). The update in the battery model may lead to an increase in the accuracy of the SOC determination. Further, the updated internal resistance arrays (260) may enable accurate prediction of the SOH of the battery unit (110), consequently leading to better prediction of end of life of the battery unit (110).

In an embodiment, as mentioned previously, the system (100) may be implemented on a cloud-based server and the determination of internal resistance of the battery unit (110) may be performed at the cloud server based on data associated with the EV (102). In an embodiment, based on the determined internal resistance of the battery unit (110), the system (100) may enable the detection of improper connections in the battery unit (110) which may occur due to rough operations of the EV (102) during use. The improper connections may include, but are not limited to, internal improper connections to the cells in the battery unit (110) and external improper connections to the cells in the battery unit (110).

Figure 4 illustrates a process flow depicting a process (400) for determining the internal resistance of the battery unit (110) at the charging and standby states of the EV (102), in accordance with an embodiment of the present disclosure. In one embodiment, the steps of the process (400) may be performed by the system (100), as discussed above.

Initially, at step (401), a magnitude of SOC of each cell (SOCn) may be determined. It is appreciated that while the process is described with reference to the SOC of each cell (SOCn), the process may be equally applicable for SOC of the battery unit (110).

At step (402), the SOCn at the given time (n) may be compared with a previous SOC value, i.e., SOCn-1. Further, a determination is made as to whether the SOCn is different from the SOCn-1 by a predetermined value. In a non-limiting example, the predetermined value may be 1 SOC unit, in that, a determination may be made as to whether the SOCn >= 1+ SOCn-1. In case the SOCn is not different from the SOCn-1 by the predetermined value, then the process (400) continues at step (401). In case the SOCn is different from the SOCn-1 by the predetermined value, then the process (400) continues at step (403).

At step (403), a state of the EV (102) is determined as one of the charging state or the discharging state. In case the state of the EV (102) is determined as a state different from the charging state or the discharging state, the process (400) moves to step (401). Upon determining the state of the EV (102) to be the charging state, the process (400) continues to step (404). At step (404), the current (In) flowing through the battery unit (110) at a first time instance is measured and recorded.

At step (405), the first terminal voltage (Vt(k-1)) of each cell at the first time instance (t(k-1)) is determined. At step (406), the control action is triggered and the switch (114) is deactivated. At step (407), after deactivating the switch (114), the second terminal voltage (Vt(k)) of each cell at the second time instance (t(k)) is determined.

At step (408), the voltage drop is determined based on the first terminal voltage and the second terminal voltage. Further, at step (409), the internal resistance R0n is determined based on the equation (3) below:

R_0n=(V_(t(k-1))-V_t(k) )/I_n ………(3)

At step (410), the internal resistance array associated with the charging state is updated based on the determined internal resistance R0n for the SOCn at the given time (n). After step (410), the process continues to step (401).

Further, at step (403), upon determining the state of the EV (102) to be the standby state, the process (400) continues to step (411). At step (411), the first terminal voltage (Vt(k-1)) of each cell at the first time instance (t(k-1)) is determined.

At step (412), the control action is triggered and a request may be sent to the motor controller unit (106) to receive a pre-defined amount of current from the battery unit (110). At step (413), the motor controller unit (106) may receive the pre-defined amount of current from the battery unit (110) and dissipate the received current in the electric motor (108).

At step (414), the current (In) flowing through the battery unit (110) at the second time instance is measured and recorded. At step (415), after receiving the pre-defined amount of current from the battery unit (110), the second terminal voltage (Vt(k)) of each cell at the second time instance (t(k)) is determined. At step (416), the internal resistance R0n is determined based on the equation (4) below:

R_0n=(V_(t(k))-V_t(k-1) )/I_n ………(4)

At step (417), the internal resistance array associated with the standby state is updated based on the determined internal resistance R0n for the SOCn at the given time (n). After step (417), the process continues to step (401).

It is appreciated that the process (400) may be repeated at regular intervals for multiple SOC values.

Figure 5 illustrates a process flow depicting a method (500) for determining the internal resistance of the battery unit (110) associated with the EV (102), according to an embodiment of the present disclosure. In one embodiment, the steps of the method (500) may be performed by the system (100), as discussed above.

At step (502), the method (500) comprises for each (SOC) value amongst the pre-defined set of SOC values associated with the battery unit (110), detecting, at a first time instance, a first terminal voltage value (252) for each cell (112) associated with the battery unit (110).

At step (504), the method (500) comprises triggering a control action to cause a change in a current flowing through the battery unit (110) upon detecting the first terminal voltage value (252).

At step (506), the method (500) comprises detecting, at a second time instance upon triggering the control action, a second terminal voltage value (254) for each cell (112) associated with the battery unit (110).

At step (508), the method (500) comprises determining an internal resistance of the battery unit (110) based on a change in the second terminal voltage value (254) with respect to the first terminal voltage value (252), a current value (256) indicative of the current flowing through the battery unit (110) at one of the first time instance or the second time instance, and the state of the EV. In an embodiment, the internal resistance is indicative of a State of Health (SOH) of the battery unit (110).

While the above-discussed steps in Figures 4-5 are shown and described in a particular sequence, the steps may occur in variations to the sequence in accordance with various embodiments. Further, a detailed description related to the various steps of Figures 4-5 is already covered in the description related to Figures 1-3 and is omitted herein for the sake of brevity.

Figure 6A illustrates an exemplary graph (600a) depicting determination of internal resistance during the charging state of the EV (102), according to an embodiment of the present disclosure. As described with respect to Figures 1B-4, when the switch (114) is deactivated, the current in the battery unit (110) drops to 0A and a voltage drop occurs. The exemplary graph (600a) depicts a voltage drop curve (602), and a current drop curve (604). The voltage drop curve (602) depicts the change in voltage across the battery unit (110) over time during the charging process. Further, the voltage drop curve (602) may represent fluctuations in voltage as the battery charges. Simultaneously, the current drop curve (604) depicts the changes in the charging current during the charging state and indicates the change in the charging current over time. In the illustrated example, the internal resistance for the battery unit (110) may be determined based on the equation (2) above, as:

R0 = (48.64 - 48.39)/ 11.8 = 22mO

Figure 6B illustrates an exemplary graph (600b) depicting determination of the internal resistance during standby state of the EV (102), according to an embodiment of the present disclosure. As described with respect to Figures 1B-4, the electric motor (108) receives the pre-defined amount of current from the battery unit (110). The exemplary graph (600b) includes a representation of the voltage drop in the voltage curve (612) and a representation of pulse current curve (614). The drop in the voltage may be utilized in determining the internal resistance R0. The representation of the pulse current curve (614) may provide a representation of the current from the battery unit (110) being dissipated in the electric motor (108). In the illustrated example, the internal resistance for the battery unit (110) may be determined based on the equation (2) above, as:

R0 = (53.45 - 52.95)/25= 20mO

In an exemplary use case, the system for determining the internal resistance of the battery unit (110) may be applied in various use case scenarios to assess and monitor the State of Health (SOH) of the battery. The system allows continuous monitoring of the internal resistance at different State of Charge (SOC) values. The SOC values may be utilized to assess the overall health of the battery unit (110) over time. The system may be employed to optimize the charging and discharging states of the battery unit (110) based on the determined internal resistance. By adjusting the current flow through the battery unit, the system (100) may enable optimization of the charging and discharging processes to enhance the battery performance. Early detection of changes in the internal resistance may be indicative of potential problems within the battery unit (110). The system may allow for timely indication of issues, enabling maintenance or replacement before significantly impacting the performance of EV. By regularly assessing the internal resistance at different SOC values, the system facilitates predictive maintenance strategies. Predicting potential issues before reaching critical conditions allows for scheduled maintenance, thereby reducing the risk of unexpected failures. The system may determine the remaining useful life of the battery unit, by correlating internal resistance with SOH, and further, provide parameters for predicting the longevity of the battery and planning for eventual replacements.

As described above, the present invention provides the system and the method to address limitations by focusing on the power fade of SOH. SOH may be a critical parameter representing the health of the battery unit. The system involves determining the internal resistance of the cell over time, allowing for the calculation of corresponding change in the power loss of the battery unit throughout the lifespan of the battery unit. The system coordinates with the electric motor to induce the voltage drop, thereby enabling the determination of internal resistance. Unlike existing solutions, the system allows for the measurement of internal resistance in both charge and standby (discharging) states, providing more comprehensive understanding of the health of the battery unit.

Accurate estimation of internal resistance is crucial for enhancing the SOC accuracy for each cell within the battery unit. SOC represents the amount of charge present at a particular time in the battery unit. Therefore, the system not only addresses current weaknesses in internal resistance measurement but also provides optimizing the overall performance of the battery and extends the reliability of electric vehicles.

While specific language has been used to describe the present disclosure, any limitations arising on account thereto, are not intended. As would be apparent to a person in the art, various working modifications may be made to the method in order to implement the inventive concept as taught herein. The drawings and the foregoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment.

It will be appreciated that the modules, processes, systems, and devices described above can be implemented in hardware, hardware programmed by software, software instruction stored on a non-transitory computer readable medium or a combination of the above. Embodiments of the methods, processes, modules, devices, and systems (or their sub-components or modules), may be implemented on a general-purpose computer, a special-purpose computer, a programmed microprocessor or microcontroller and peripheral integrated circuit element, an ASIC or other integrated circuit, a digital signal processor, a hardwired electronic or logic circuit such as a discrete element circuit, a programmed logic circuit such as a programmable logic device (PLD), programmable logic array (PLA), field-programmable gate array (FPGA), programmable array logic (PAL) device, or the like. In general, any process capable of implementing the functions or steps described herein can be used to implement embodiments of the methods, systems, or computer program products (software program stored on a non-transitory computer readable medium).

Furthermore, embodiments of the disclosed methods, processes, modules, devices, systems, and computer program product may be readily implemented, fully or partially, in software using, for example, object or object-oriented software development environments that provide portable source code that can be used on a variety of computer platforms. Alternatively, embodiments of the disclosed methods, processes, modules, devices, systems, and computer program product can be implemented partially or fully in hardware using, for example, standard logic circuits or a very-large-scale integration (VLSI) design. Other hardware or software can be used to implement embodiments depending on the speed and/or efficiency requirements of the systems, the particular function, and/or particular software or hardware system, microprocessor, or microcomputer being utilized.

In this application, unless specifically stated otherwise, the use of the singular includes the plural and the use of “or” means “and/or.” Furthermore, use of the terms “including” or “having” is not limiting. Any range described herein will be understood to include the endpoints and all values between the endpoints. Features of the disclosed embodiments may be combined, rearranged, omitted, etc., within the scope of the invention to produce additional embodiments. Furthermore, certain features may sometimes be used to advantage without a corresponding use of other features.

Reference numbers:

Components Reference Numbers
ECU 10
Processor unit 12
Memory unit 14
Input unit 16
Output unit 18
Environment 101
System 100
Electric vehicle (EV) 102
Battery management system (BMS) 104
Motor controller unit 106
Electric motor 108
Battery unit 110
Cells 112
Switch 114
Processor 210
Memory 220
I/O interface 230
Set of Modules 240
Database 250
Operating System 251
First Terminal Voltage Value 252
Second Terminal Voltage Value 254
Current Value 256
Voltage Drop 258
Internal Resistance Array 260
Detecting Module 302
Triggering Module 304
Determining Module 306
Updating Module 308 , Claims:1. A method (500) for determining internal resistance of a battery unit (110) associated with an electric vehicle (EV) (102), the method (500) comprising:
for each State of Charge (SOC) value amongst a pre-defined set of SOC values associated with the battery unit (110):
detecting (502), at a first time instance, a first terminal voltage value (252) for each cell (112) associated with the battery unit (110);
triggering (504) a control action to cause a change in a current flowing through the battery unit (110) upon detecting the first terminal voltage value (252);
detecting (506), at a second time instance upon triggering the control action, a second terminal voltage value (254) for each cell (112) associated with the battery unit (110); and
determining (508) an internal resistance of the battery unit (110) based on a change in the second terminal voltage value (254) with respect to the first terminal voltage value (252), a current value (256) indicative of the current flowing through the battery unit (110) at one of the first time instance or the second time instance, and a state of the EV (102), wherein the internal resistance is indicative of a State of Health (SOH) of the battery unit (110).

2. The method (500) as claimed in claim 1, comprising:
detecting the state of the EV (102) to be one of a charging state or a standby state; and
triggering the control action to cause a change in the current flowing through the battery unit (110) based on the detected state.

3. The method (500) as claimed in claim 2, wherein when the state of the EV (102) is detected as the charging state, triggering the control action comprises ceasing a flow of the current to the battery unit (110) by deactivating a switch (114) associated with the battery unit (110).

4. The method (500) as claimed in claim 2, wherein when the state of the EV (102) is detected as the charging state, determining the internal resistance of the battery unit (110) comprises:
determining a voltage drop (258) associated with the battery unit (110) based on the change in the second terminal voltage value (254) with respect to the first terminal voltage value (252);
measuring, at the first time instance prior to triggering the control action, the current value (256) indicative of the current flowing through the battery unit (110); and
calculating the internal resistance of the battery unit (110) based on the determined voltage drop (258) and the measured current value (256) at the first time instance.

5. The method (500) as claimed in claim 2, wherein when the state of the EV is detected as the standby state, triggering the control action comprises sending, to a motor controller unit (106) associated with the EV (102), a request to receive a pre-defined amount of current from the battery unit (110), wherein the pre-defined amount of current is dissipated in an electric motor (108) associated with the EV (102).

6. The method (500) as claimed in claim 2, wherein when the state of the EV (102) is detected as the standby state, determining the internal resistance of the battery unit (110) comprises:
determining a voltage drop (258) associated with the battery unit (110) based on the change in the second terminal voltage value (254) with respect to the first terminal voltage value (252);
measuring, at the second time instance after triggering the control action, the current value (256) indicative of the current flowing through the battery unit (110); and
calculating the internal resistance of the battery unit (110) based on the determined voltage drop (258) and the measured current value (256) at the second time instance.

7. The method (500) as claimed in claim 1, comprising:
updating an internal resistance array (260) associated with a charging state of the EV (102) and the internal resistance array (260) associated with a standby state of the EV (102) based on the determined internal resistance, wherein each of the internal resistance array (260) comprises a plurality of internal resistance values corresponding to the pre-defined set of SOC values.

8. The method (500) as claimed in claim 7, comprising:
determining a new set of SOC values based on one or more of the updated internal resistance array (260) associated with the charging state and the standby state; and
updating the pre-defined set of SOC values based on the new set of SOC values.

9. The method (500) as claimed in claim 8, comprising:
updating the SOH of the battery unit (110) based on the updated internal resistance array (260) associated with the charging state and the standby state.

10. A system (100) for determining internal resistance of a battery unit (110) associated with an electric vehicle (EV) (102), the system (100) being associated with a Battery Management System (BMS) (104) of the EV (102), the system (100) comprising:
a memory (220);
at least one processor (210) in communication with the memory (220), the at least one processor (210) being configured to, for each State of Charge (SOC) value amongst a pre-defined set of SOC values associated with the battery unit (110):
detect, at a first time instance, a first terminal voltage value (252) for each cell (112) associated with the battery unit (110);
trigger a control action to cause a change in a current flowing through the battery unit (110) upon detecting the first terminal voltage value (252);
detect, at a second time instance upon triggering the control action, a second terminal voltage value (254) for each cell (112) associated with the battery unit (110); and
determine an internal resistance of the battery unit (110) based on a change in the first terminal voltage value (252) with respect to the second terminal voltage value (254), a current value (256) indicative of the current flowing through the battery unit (110) at one of the first time instance or the second time instance, and a state of the EV (102), wherein the internal resistance is indicative of a State of Health (SOH) of the battery unit (110).

11. The system (100) as claimed in claim 10, wherein the at least one processor (210) is configured to:
detect the state of the EV (102) to be one of a charging state or a standby state; and
trigger the control action to cause a change in the current flowing through the battery unit (110) based on the detected state.

12. The system (100) as claimed in claim 11, wherein when the state of the EV (102) is detected as the charging state, to trigger the control action, the at least one processor (210) is configured to cease a flow of the current to the battery unit (110) by deactivating a switch (114) associated with the battery unit (110).

13. The system (100) as claimed in claim 11, wherein when the state of the EV (102) is detected as the charging state, to determine the internal resistance of the battery unit (110), the at least one processor (210) is configured to:
determine a voltage drop (258) associated with the battery unit (110) based on the change in the second terminal voltage value (254) with respect to the first terminal voltage value (252);
measure, at the first time instance prior to triggering the control action, the current value (256) indicative of the current flowing through the battery unit (110); and
calculate the internal resistance of the battery unit (110) based on the determined voltage drop (258) and the measured current value (256) at the first time instance.

14. The system (100) as claimed in claim 11, wherein when the state of the EV (102) is detected as the standby state, to trigger the control action, the at least one processor (210) is configured to send, to a motor controller unit (106) associated with the EV (102), a request to receive a pre-defined amount of current from the battery unit (110), wherein the pre-defined amount of current is dissipated in an electric motor (108) associated with the EV (102).

15. The system (100) as claimed in claim 11, wherein when the state of the EV (102) is detected as the standby state, to determine the internal resistance of the battery unit (110), the at least one processor (210) is configured to:
determine the voltage drop (258) associated with the battery unit (110) based on the change in the second terminal voltage value (254) with respect to the first terminal voltage value (252);
measure, at the second time instance after triggering the control action, the current value (256) indicative of the current flowing through the battery unit (110); and
calculate the internal resistance of the battery unit (110) based on the determined voltage drop (258) and the measured current value (256) at the second time instance.

16. The system (100) as claimed in claim 10, wherein the at least one processor (210) is configured to:
updating an internal resistance array (260) associated with a charging state of the EV (102) and the internal resistance array (260) associated with a standby state of the EV (102) based on the determined internal resistance, wherein each of the internal resistance array (260) comprises a plurality of internal resistance values corresponding to the pre-defined set of SOC values.

17. The system (100) as claimed in claim 16, wherein the at least one processor (210) is configured to:
determine a new set of SOC values based on one or more of the updated internal resistance array (260) associated with the charging state and the standby state; and
update the pre-defined set of SOC values based on the new set of SOC values.

18. The system (100) as claimed in claim 17, wherein the at least one processor (210) is configured to:
update the SOH of the battery unit (110) based on the updated internal resistance array (260) associated with the charging state and the standby state.