Arc fault detection in a vehicle

Abstract

Approaches for detecting arc faults in a vehicle are described. In one example, an oscillating signal may be obtained from a vehicle. In an example, a frequency transform may be applied to the oscillating signal for obtaining a frequency domain signal. Thereafter, a first segment and a second segment may be extracted from the frequency domain signal. The first segment may be representative of a first harmonic of the frequency domain signal. Similarly, the second segment may be representative of one of a second harmonic and a third harmonic of the frequency domain signal. Further, a ratio of the first harmonic and one of the second harmonic and third harmonic may be computed and compared to a predefined threshold. When it may be determined that the ratio is less than the predefined threshold, an indication may be generated, signifying that an arc fault has occurred in the vehicle.

Description

ARC FAULT DETECTION IN A VEHICLEBACKGROUND

[0001] Vehicles, whether powered by an internal combustion engine or an electric motor, are complex machines subject to a wide array of defects and faults arising during vehicles’ operational lifetime. For example, defects and faults in engines, motors, braking systems, accelerators, steering components, fuel system, and more, may arise in a vehicle. Such defects and faults may generally arise from manufacturing sources, wear and tear from regular usage, environmental factors, or due to improper maintenance. Electrical faults are increasingly prevalent, especially in modern vehicles with sophisticated electronic systems, and may range from battery problems to complex issues with engine control units or advanced driver assistance systems. Over the past few decades, electric vehicles have gained significant importance in the automotive industry due to reduced environmental impacts and improved energy efficiency. As the adoption of electric vehicles rises rapidly, ensuring safety, reliability, and longevity of the vehicle is of pivotal importance.BRIEF DESCRIPTION OF FIGURES

[0002] Systems and / or methods, in accordance with examples of the present subject matter are now described and with reference to the accompanying figures, in which:

[0003] FIG. 1 illustrates a vehicle having a control unit and component(s) for detection of arc faults in the vehicle, as per an example of the present subject matter;

[0004] FIG. 2 illustrates a block diagram depicting various components of a control unit for detection of arc faults in the vehicle, as per an example of the present subject matter;

[0005] FIGs. 3(A) and 3(B) illustrates experimental results pertaining to detecting arc faults in a vehicle, as per an example of the present subject matter.

[0006] FIGs. 4(A) to 4(D) illustrates experimental results pertaining to detecting arc faults in a vehicle, as per an example of the present subject matter;

[0007] FIG. 5 illustrates a method for detecting arc faults in a vehicle, as per an example of the present subject matter;

[0008] It may be noted that throughout the drawings, identical reference numbers designate similar, but not necessarily identical, elements. The figures are not necessarily to scale, and the size of some parts may be exaggerated to more clearly illustrate the example shown. Moreover, the drawings provide examples and / or implementations consistent with the description; however, the description is not limited to the examples and / or implementations provided in the drawings.DETAILED DESCRIPTION

[0009] As may be understood, vehicles have become complex and technologically advanced, necessitating sophisticated diagnosis, repair and maintenance. A vehicle is prone to defects and faults which may put a risk to rider’s safety and life. While modem day vehicles are designed with advanced safety features, defects and faults may still occur, posing significant challenges in the automotive industry. For example, defects and faults such as arc faults may arise in vehicles. Such arc faults are electrical malfunctions characterized by intermittent, high-temperature electrical discharges occurring due to breakdown or discontinuity in an electrical path. In the context of vehicles, particularly, electric vehicles, arc faults may occur due to various reasons such as loose connections, damaged insulation, corroded contacts, or due to mechanical stress or vibrations on the electrical components.

[0010] Generally, an electric arc may be introduced when two electrical contacts initially driven by a current are separated, causing arc faults. The conduction may then be maintained by an electric discharge that begins in the space between the electrical contacts. Arc faults are, thus, an electricalanomaly occurring due to unintended electrical discharges across an insulating medium, mainly due to degraded insulation or loose connections. For instance, in a vehicle, a break at the electrical connection may cause electric arcs that may be maintained because of direct current (DC) flowing into a battery management system of the vehicle. These arcs may cause heating and even thermal runaway in the battery which may lead to short circuits, malfunctions, or catastrophic incidents such as fires.

[0011] As EVs are becoming paramount in daily lives, it is important to detect such arc faults for the safety of human lives and property. In EVs, wherein high-voltage systems operate at 600 Volts to 800 Volts, potential for arc faults may increase. Arc faults in vehicles may also arise due to vibrations, thermal cycling, corrosion, or mechanical stress on electrical components. Therefore, based on a range of factors such as material ageing, loose connections, or other external factors such as vibrations and impact, the electrical connections inside the vehicle may be damaged or broken, resulting in arc faults. Particularly, critical areas such as motor windings, power inventor connections, battery pack interconnects, and current carrying cables may generally be prone to arc faults.

[0012] Continuing further, detecting arc faults in the vehicle may pose certain challenges due to dynamic nature of the automotive electrical systems. The intermittent nature of these faults, combined with rapid loads changes during normal vehicle operations and may make them difficult to identify arc faults. Moreover, electrical noise generated by motor controllers and power electronics may mask the signatures of developing arc faults.

[0013] T raditional approaches for determining arc faults typically include standard thermal breakers and arc fault circuit breakers comprising temperature monitoring sensors, voltage monitoring sensors, or overcurrent protection devices. Such approaches for identifying arc faults may lack the sensitivity and precision required for an early-stage detection of the arc faults. Further, traditional approaches for determining arc faults generally rely on a periodic offline testing for measuring overheating and electricalfluctuations in the vehicle. In the case of periodic offline testing, real-time fault detection may not be implemented during vehicle operation. Although visual inspections may be relied on to detect signs of wear, damage, or loose connections, the same may be limited depending on the frequency and thoroughness of the inspections.

[0014] Some other traditional approaches may also include vibration analysis for detecting mechanical faults and further to detect loose connection which may potentially lead to an arc fault. Such approaches may not be entirely useful for detecting electrical issues arising in the vehicles. Also, such traditional approaches may often suffer from dynamic conditions inherent in vehicle operations, posing a challenge to differentiate between normal and faulty conditions. Thus, traditional approaches may be lacking based on the complex dynamics, especially in the modern-day EVs having high-voltage systems and rapidly changing conditions.

[0015] Approaches for detecting arc faults in a vehicle are described. In one example, an oscillating signal may be obtained from a vehicle. The oscillating signal may be indicative of a phase current flowing through a component of the vehicle when the vehicle may be under variable operating conditions. For example, the vehicle may be moving on a road. In an example, a frequency transform may be applied to the oscillating signal for obtaining a frequency domain signal. Thereafter, a first segment and a second segment may be extracted from the frequency domain signal. In one example, the first segment may be representative of a first harmonic of the frequency domain signal. Similarly, the second segment may be representative of one of a second harmonic and a third harmonic of the frequency domain signal. A first magnitude and a second magnitude may be associated with the first harmonic and one of the second harmonic and the third harmonic, respectively. The first magnitude and the second magnitude may be indicative of a complex magnitude of the frequency transform of the oscillating signal.

[0016] Further, a ratio of the first harmonic and one of the second harmonic and third harmonic may be computed. The ratio may be compared to a predefined threshold. In one example, when it may be determined that the ratio is less than the predefined threshold, an indication may be generated. The indication may signify that an arc fault has occurred in the vehicle.

[0017] The present approaches provide numerous technical advantages. For example, arc faults may be detected in real-time due to continuous monitoring vehicle operations. The real-time monitoring may instantly alert the rider regarding an arc fault arisen in the vehicle, for the rider to take a necessary action for repair and maintenance. Based on detecting subtle changes in frequency components of the oscillating signal, the present approaches may identify arc faults at an early stage, before the same may develop into a serious issue. Such an early detection of the arc fault improves safety and reliability of the vehicle, and may help build customer confidence.

[0018] The manner in which the example computing systems are implemented is explained in detail with respect to FIGS. 1 -5. While aspects of the described systems and / or units may be implemented in any number of different electric devices, environments, and / or implementations, the examples are described in the context of the following example device(s). It may be noted that drawings of the present subject matter shown here are for illustrative purposes and are not to be construed as limiting the scope of the claimed subject matter.

[0019] FIG. 1 illustrates a vehicle, for example, vehicle 100 moving along a path on a road. The vehicle 100 may be an electric vehicle (EV) comprising one or more components, such as component(s) 104. Examples of such vehicles 100 include, but may not be limited to, electric two-wheeler, electric car, electric bus, etc. Examples of component(s) 104 include, but may not be limited to a motor, a battery management system, a braking system, a battery pack, etc. Vehicle 100 may include vehicle hardware, suchas a control unit 102 which may be responsible for managing and / or controlling the input parameters for detecting arc faults in a component of the vehicle 100. In an example, the control unit 102 of the vehicle 100 may include hardware or software-based application that is used to control the vehicle 100 through real-world environments based on the sensor(s), data, one or more machine learning, neural network-based learning model, or deep learning models, etc.

[0020] While moving along the path of the road, the control unit 102 may constantly receive data from one or more sensors of the vehicle 100. The data may pertain to variable operating conditions of the vehicle 100. The variable operating conditions may include, but are not limited to, variable speed, variable load, or variable environmental conditions such as rough terrains, etc. For example, the vehicle 100 may be moving along a terrain with variable throttle. In such instances, the vehicle 100 may experience vibrations and jerks which may cause an arc fault in the vehicle. Also, a loose electrical connection in any component 104 may also lead to an arc fault in the vehicle 100. During occurrence of an arc fault in the vehicle 100, the control unit 102 may generate an indication and / or an alert signifying that an arc fault 102 has been detected in the vehicle 100. The functioning of the control unit 102 for detecting arc faults in the vehicle 100 are explained in conjunction with FIGs. 2-5.

[0021] FIG. 2 illustrates a block diagram 200 depicting various components of a control unit, such as a control unit 102 installed in a vehicle, such as a vehicle 100. In an example, the vehicle 100 may include plurality of components and sensors placed at specific locations to monitor and generate data to be used while driving the vehicle 100. In an example, the control unit 102 may comprise processor(s) 202, memory(s) 204, interface(s) 206, a fault detection engine 208. The fault detection engine 208 may obtain data from one or more sensors installed in the vehicle 100. For example, the fault detection engine 208 may obtain vehicle current data 210 from a current sensor, vehicle load data 212 from a load sensor, vehiclespeed data 214 from a speed sensor, and other data 216 from sensor(s) of the vehicle 100. The instructions are fetched from the memory 204 and executed by a processor 202 included within the control unit 102.

[0022] The control unit 102 may be deployed within the vehicle 100. For example, the control unit 102 may be implemented by way of electronic circuitry which may enable the MCU 202 to perform a variety of functions, such as power control and conversion, and also generating control signals for controlling the operation of the vehicle 100. When implemented as electronic circuitry, the control unit 102 may include multiple electronic or electrical components, such as MOSFETs, and the like. In another example, the control unit 102 may either be implemented or may include one or more processing elements within specifically programmed one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, micro-controllers, micro-processors, electronic devices, other electronic units designed to perform the functions described herein, or a combination thereof. For a firmware and / or software implementation, the methodologies may be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described herein.

[0023] The fault detection engine 208 may be implemented as a combination of hardware and programming, for example, programmable instructions to implement a variety of functionalities. In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the fault detection engine 208 may be executable instructions. Such instructions may be stored on a non-transitory machine-readable storage medium which may be coupled either directly with control unit 102 or indirectly (for example, through networked means). In an example, the fault detection engine 208 may include a processing resource, for example, either a single processor or a combination of multiple processors, to executesuch instructions. In the present examples, the non-transitory machine- readable storage medium may store instructions that when executed by the processing resource, implement fault detection engine 208. In other examples, the fault detection engine 208 may be implemented as electronic circuitry.

[0024] In an example, the control unit 102, and in turn the fault detection engine 208 may be coupled to the component(s) of the vehicle 100 through a plurality of phase cables. While moving along the path on the road, the fault detection engine 208 of the vehicle 100 may obtain an oscillating signal. The oscillating signal may be indicative of a phase current flowing through the component(s) 104 of the vehicle when the vehicle 100 may be under variable operating conditions. For example, the vehicle may be moving on a road. In such instance, the vehicle current data 1 14, vehicle load data 212, and vehicle speed data 214 may constantly be updated and fed to the fault detection engine 208 through the one or more sensors of the vehicle 100. The oscillating signal may be a sinusoidal waveform obtained from the vehicle 100, depictive of a magnitude of current (in Amperes) obtained for a time interval of at least 10 milliseconds during the vehicle operating conditions.

[0025] In an example, the fault detection engine 208 may apply a frequency transform, for example, a Fast Fourier Transform (FFT) to the oscillating signal for obtaining a frequency domain signal. Thereafter, the fault detection engine 208 may extract a first segment and a second segment from the frequency domain signal. The first segment may be representative of a first harmonic of the frequency domain signal. The first harmonic of the frequency domain signal is the fundamental frequency of the frequency domain signal. The fundamental frequency has the highest magnitude. The fundamental frequency (or the first harmonic) may be obtained by applying Fast Fourier Transform (FFT) on a conditioned signal, which may be applying a Hamming Window factor to the oscillating signal, as is conventionally known. The conditional signal may be based on signalconditioning, wherein a signal is manipulated in such a way to prepare it for the next stage of processing. For example, in signal processing, a window function, for example, a Hamming window function, is a mathematical function that is zero-valued outside of a chosen interval (in the present case, the chosen interval is at least 10 milliseconds). Typically, window functions are symmetric around the middle of the interval, approach a maximum in the middle, and taper away from the middle.

[0026] Similarly, the second segment may be representative of one of a second harmonic and a third harmonic of the frequency domain signal. A first magnitude and a second magnitude may be associated with the first harmonic and one of the second harmonic and the third harmonic, respectively. The first magnitude and the second magnitude may be indicative of a complex magnitude of the frequency transform of the oscillating signal.

[0027] Further, the fault detection engine 208 may compute a ratio of the first harmonic and one of the second harmonic and third harmonic, and compare the ratio to a predefined threshold. In one example, the fault detection engine 208 may determine that the ratio is less than the predefined threshold and generate an indication. The indication may signify that an arc fault has occurred in the vehicle 100.

[0028] It may be noted that the ratio of the fundamental or the first harmonic to one of the second harmonic and the third harmonic may vary when the arc fault is presence in the vehicle 100, in contrary to the ideal conditions with the fundamental frequency of the first harmonic possessing the highest magnitude. Since, this ratio changes during the variable operating conditions of the vehicle 100, and in turn during the presence of the arc fault in the vehicle 100, it may be determined that an arc fault has occurred in the vehicle 100, without having the need for a manual check-up with a mechanic. Further, such a determination of the arc fault in the vehicle occurs in real-time and instantly, according to which necessary actions may be undertaken by the rider riding the vehicle 100.

[0029] FIGs. 3(A) and 3(B) illustrates experimental results 300 pertaining to detecting arc faults in a vehicle, as per an example of the present subject matter. The experimental results in FIGs. 3(A) and 3(B) shows an oscillating signal 302, for example, a sinusoidal waveform of current T (in Amperes) flowing through a component, such as component 104 of the vehicle 100, observed for ‘N’ number of samples. Under normal operating conditions of the vehicle 100, for example, without a loose electrical connection in the component(s) 104, and / or any other circumstance instigating an arc fault, a purely sinusoidal waveform may be observed, as shown in FIG. 3(A). However, under faulty conditions, for example, when a loose electrical connection may be present in one or more phase cables connecting the different component(s) 104 of the vehicle 100, an arc fault may arise. Whenever an arc fault arises in the component(s) 104 of the vehicle, a distorted oscillating signal 304 may be observed, as shown in FIG. 3(B). It may be noted that a spike can be observed in FIG. 3(B) (304, marked as dotted circle). The spike in the distorted oscillating signal may be due to an arc fault arising in the component(s) 104 of the vehicle 100, during variable operating conditions of the vehicle 100. Examples of variable operating conditions include, but are not limited to, a change in one of a throttle, load, speed, environmental conditions, and combinations thereof, of the vehicle 100.

[0030] FIGs. 4(A) to 4(D) illustrates experimental results 400 pertaining to detecting arc faults in a vehicle, as per an example of the present subject matter. The experimental results in FIG. 4(A) shows an oscillating signal 402, for example, a sinusoidal waveform of current T (in Amperes) flowing through a component, such as component 104 of the vehicle 100, observed for ‘N’ number of samples, under normal conditions of the vehicle 100. FIG. 4(B) shows a distorted oscillating signal 404 under faulty conditions of the vehicle 100. As explained previously, under normal operating conditions of the vehicle 100, for example, without a loose electrical connection in thecomponent(s) 104, and / or any other circumstance instigating an arc fault, a purely sinusoidal waveform may be observed, as shown in FIG. 4(A).

[0031] However, under faulty conditions, for example, when a loose electrical connection may be present in one or more phase cables connecting the different component(s) 104 of the vehicle 100, an arc fault may arise. Whenever an arc fault arises in the component(s) 104 of the vehicle, the distorted oscillating signal 404 may be observed, as shown in FIG. 4(B). It may be noted that a spike can be observed in FIG. 4(B) (402, marked as dotted circle). A spike 404 in the distorted oscillating signal may be due to an arc fault arising in the component(s) 104 of the vehicle 100, during variable operating conditions of the vehicle 100. Further, FIG. 4(C) shows a Fast Fourier Transform (FFT), or the frequency domain signal 406 of the oscillating signal 402. Similarly, FIG. 4(D) shows FFT of the frequency domain signal 408 of the distorted oscillating signal 404. It may be noted that the frequency domain signal 406 of FIG. 4(A) depicts a fundamental frequency or the first harmonic of the oscillating signal 402, while FIG. 4D depicts the first harmonics, second harmonic, third harmonic, and so on, (shown as dotted circle) of the distorted oscillating signal 404. Herein, a ratio of the first harmonic and one of the second harmonic and third harmonic may be computed, and compared to a predefined threshold. Upon determination that the ratio is less than the predefined threshold, an indication may be generated. The indication may signify that an arc fault has occurred in the vehicle 100.

[0032] FIG. 5 illustrates a method for detecting arc faults in a vehicle, as per an example of the present subject matter. The order in which the above- mentioned methods are described is not intended to be construed as a limitation, and some of the described method blocks may be combined in a different order to implement the methods, or alternative methods. During operation, the fault detection engine 208, amongst other functions, may extract a plurality of input vehicle characteristic(s) associated with a vehicle, for example, a vehicle 100. Further, the above-mentioned methods may beimplemented in a suitable hardware, computer-readable instructions, or combination thereof. The steps of such methods may be performed by either a system under the instruction of machine executable instructions stored on a non-transitory computer readable medium or by dedicated hardware circuits, microcontrollers, or logic circuits.

[0033] In an implementation, the method 500 may be performed under an “as a service” delivery model, where the fault detection engine 208, operated by a provider, receives programmable code. Herein, some examples are also intended to cover non-transitory computer readable medium, for example, digital data storage media, which are computer readable and encode computer-executable instructions, where said instructions perform some or all the steps of the above-mentioned method.

[0034] At block 502, an oscillating signal may be obtained may be obtained. In one example, while moving along a path of the road, the control unit 102 may constantly receive data from one or more sensors of the vehicle 100. The data may pertain to variable operating conditions of the vehicle 100. The variable operating conditions may include, but are not limited to, variable speed, variable load, or variable environmental conditions such as rough terrains, etc. For example, the vehicle 100 may be moving along a terrain with variable throttle. In such instances, the vehicle 100 may experience vibrations and jerks which may cause an arc fault in the vehicle.

[0035] For determining the presence of an arc fault in the vehicle 100, the control unit 102 obtains the oscillating signal which may be indicative of a phase current flowing through the component(s) 104 of the vehicle when the vehicle 100 may be under the variable operating conditions. The oscillating signal may be a sinusoidal waveform obtained from the vehicle 100, depictive of a magnitude of current (in Amperes) obtained for a time interval of at least 10 milliseconds during the vehicle operating conditions.

[0036] At block 504, a Fourier Transform may be applied on the oscillating signal. For example, the control unit 102 may apply a frequencytransform, for example, a Fast Fourier Transform (FFT) to the oscillating signal for obtaining a frequency domain signal.

[0037] At block 506, a first segment and a second segment may be extracted. For example, the control unit 102 may extract a first segment and a second segment from the frequency domain signal. The first segment may be representative of a first harmonic of the frequency domain signal. The first harmonic of the frequency domain signal is the fundamental frequency of the frequency domain signal. The fundamental frequency has the highest magnitude. The fundamental frequency (or the first harmonic) may be obtained by a Fast Fourier Transform (FFT) on a conditioned signal, which may be applying a Hamming Window factor to the oscillating signal. For example, in signal processing, a window function, for example, a Hamming window function, is a mathematical function that is zero-valued outside of a chosen interval (in the present case, the chosen interval is at least 10 milliseconds). Typically, window functions are symmetric around the middle of the interval, approach a maximum in the middle, and taper away from the middle.

[0038] Similarly, the second segment may be representative of one of a second harmonic and a third harmonic of the frequency domain signal. A first magnitude and a second magnitude may be associated with the first harmonic and one of the second harmonic and the third harmonic, respectively. The first magnitude and the second magnitude may be indicative of a complex magnitude of the frequency transform of the oscillating signal.

[0039] At block 508, a ratio may be computed. For example, the control unit 102 may compute a ratio of the first harmonic and one of the second harmonic and third harmonic, and compare the ratio to a predefined threshold. In one example, the ratio of the fundamental or the first harmonic to one of the second harmonic and the third harmonic may vary when the arc fault is presence in the vehicle 100, in contrary to the ideal conditions with the fundamental frequency of the first harmonic possessing the highestmagnitude. Since, this ratio changes during the variable operating conditions of the vehicle 100, and in turn during the presence of the arc fault in the vehicle 100, it may be determined that an arc fault has occurred in the vehicle 100, without having the need for a manual check-up with a mechanic. Further, such a determination of the arc fault in the vehicle occurs in real-time and instantly, according to which necessary actions may be undertaken by the rider riding the vehicle 100.

[0040] At block 510, an indication may be generated. For example, the control unit 102 may determine that the ratio is less than the predefined threshold and generate an indication. The indication may signify that an arc fault has occurred in the vehicle 100.

[0041] Although examples for the present disclosure have been described in language specific to structural features and / or methods, it is to be understood that the appended claims are not necessarily limited to the specific features or methods described. Rather, the specific features and methods are disclosed and explained as examples of the present disclosure.

Claims

l / We Claim:1 . A control unit to: obtain an oscillating signal from one or more sensors of a vehicle, the oscillating signal is indicative of a phase current through a component of the vehicle when the vehicle is in motion under variable operating conditions; apply a frequency transform to the oscillating signal to obtain a frequency domain signal; extract a first segment and second segment of the frequency domain signal, wherein the first segment is representative of a first harmonic of the frequency domain signal and the second segment is representative of one of a second harmonic and a third harmonic of the frequency domain signal; compute a ratio of the first harmonic to one of the second and the third harmonic; compare the ratio with a predefined threshold; and upon determination that the ratio is less than the predefined threshold, generate an indication signifying an arc fault in the component of the vehicle.

2. The control unit as claimed in claim 1 , wherein the frequency transform is a Fast Fourier Transform (FFT) applied on the oscillating signal.

3. The control unit as claimed in claim 1 , wherein the first harmonic corresponds to a fundamental frequency of the oscillating signal.

4. The control unit as claimed in claim 3, wherein to obtain the fundamental frequency, the control unit is to: apply a Hamming window factor to the oscillating signal to obtain a conditional signal; andapply a Fast Fourier Transform (FFT) on the conditioned signal to obtain the fundamental frequency.

5. The control unit as claimed in claim 1 , wherein the component of the vehicle is one of a motor, a battery management system, a braking system, a battery pack, and combinations thereof, of the vehicle.

6. The control unit as claimed in claim 1 , wherein the first segment and the second segment of the oscillating signal is obtained at a time interval of at least 10 milliseconds.

7. The control unit as claimed in claim 1 , wherein the variable operating conditions corresponds to a change in one of a throttle, load, speed, environmental conditions, and combinations thereof, of the vehicle.

8. A method for detecting arc fault in a vehicle comprising: obtaining an oscillating signal from one or more sensors of a vehicle, the oscillating signal is indicative of a phase current through a component of the vehicle when the vehicle is in motion under variable operating conditions; applying a frequency transform to the oscillating signal to obtain a frequency domain signal; extracting a first segment and second segment of the frequency domain signal, wherein the first segment is representative of a first harmonic of the frequency domain signal and the second segment is representative of one of a second harmonic and a third harmonic of the frequency domain signal; computing a ratio of the first harmonic to one of the second and the third harmonic; comparing the ratio with a predefined threshold; andupon determination that the ratio is less than the predefined threshold, generating an indication signifying an arc fault in the component of the vehicle.

9. The method as claimed in claim 8, wherein the frequency transform is a Fast Fourier Transform (FFT) applied on the oscillating signal.

10. The method as claimed in claim 8, wherein the first harmonic corresponds to a fundamental frequency of the oscillating signal.1 1 . The method as claimed in claim 10, wherein to obtain the fundamental frequency, the method comprises: applying a Hamming window factor to the oscillating signal to obtain a conditioned signal; and applying a Fast Fourier Transform (FFT) on the conditioned signal to obtain the fundamental frequency.

12. The method as claimed in claim 8, wherein the component of the vehicle is one of a motor, a battery management system, a braking system, a battery pack, and combinations thereof, of the vehicle.13 The method as claimed in claim 8, wherein the first segment and the second segment of the oscillating signal is obtained at a time interval of at least 10 milliseconds.

14. The method as claimed in claim 8, wherein the variable operating conditions correspond to a change in one of a throttle, load, speed, environmental conditions, and combinations thereof, of the vehicle.

15. A vehicle comprising: a component;one or more sensors; a control unit coupled to the component, wherein the control unit is to: obtain an oscillating signal from one or more sensors of a vehicle, the oscillating signal is indicative of a phase current through a component of the vehicle when the vehicle is in motion under variable operating conditions; apply a frequency transform to the oscillating signal to obtain a frequency domain signal; extract a first segment and second segment of the frequency domain signal, wherein the first segment is representative of a first harmonic of the frequency domain signal and the second segment is representative of one of a second harmonic and a third harmonic of the frequency domain signal; compute a ratio of the first harmonic to one of the second and the third harmonic; compare the ratio with a predefined threshold; and upon determination that the ratio is less than the predefined threshold, generate an indication signifying an arc fault in the component of the vehicle.

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