DESC:METHOD FOR MONITORING INSULATION STATE OF INVERTER DRIVEN MOTOR
CROSS REFERENCE TO RELATED APPLICATIONS
The present application claims priority from Indian Provisional Patent Application No. 202421022017 filed on 21/03/2024, the entirety of which is incorporated herein by a reference.
TECHNICAL FIELD
The present disclosure generally relates to an inverter driven motor. Particularly, the present disclosure relates to a method for monitoring insulation state of an inverter driven motor.
BACKGROUND
The electric vehicle (EV) market is rapidly expanding, driven by advancements in battery technology, government incentives, and increasing environmental concerns. The Auto-manufacturers re investing heavily in EV infrastructure, including fast-charging networks and improved energy efficiency. Additionally, the solid-state batteries and high-efficiency powertrains are emerging as key innovations for future EVs.
Recently, the motor drive system in electric vehicles has evolved with advancements in power electronics, control algorithms, and efficiency optimization. The modern electric and hybrid vehicles utilize high-efficiency inverters and advanced motor designs like PMSM and induction motors. Also, the emerging trends include SiC and GaN-based inverters for reduced losses and higher power density. However, with increasing usage of motor drive in vehicles, the insulation problems in the motor drive arises. The insulation problems in the motor drive occur due to factors such as electrical stress, thermal degradation, mechanical vibrations, and environmental conditions like moisture or contaminants. Over time, high-voltage stress may cause insulation breakdown, leading to leakage currents and reduced system efficiency. Also, excessive heat from prolonged operation accelerates material aging, weakening insulation properties. Furthermore, the mechanical shocks and continuous vibrations may create microcracks in insulating layers, increasing the risk of failure. Additionally, dust, humidity, and chemical exposure can degrade insulation surfaces, leading to unintended short circuits or safety hazards.
Traditionally, the isolation in the motor drives of electric vehicles traditionally monitored using resistance-based measurement techniques, voltage monitoring methods, and insulation resistance testers. These methods primarily relied on measuring the insulation resistance between the high-voltage (HV) system and the vehicle chassis to detect any potential faults or degradation in isolation. One of the common technique is resistance measurement method, where a high-value resistor is connected between the HV bus and the chassis ground. By applying a known voltage and measuring the leakage current, the insulation resistance is calculated. If the resistance dropped below a predefined threshold, an isolation fault is detected. However, the method has significant drawbacks. Firstly, these method required additional passive components that added to the system complexity and cost. Secondly, the method may not detect dynamic isolation failures, such as insulation breakdown occurring due to transient voltage spikes or mechanical stress over time. Moreover, during operation, insulation degradation is often gradual and not easily captured by periodic resistance measurements, leading to potential undetected faults. Another conventional approach involved voltage-based monitoring, where the voltage difference between the HV system and the chassis ground is continuously observed. Any unexpected fluctuations in the voltage difference may be indicate a loss of isolation. While the method is relatively straightforward, but the method suffered from low sensitivity to minor faults, making the method ineffective in detecting early-stage insulation degradation. Additionally, the method prone to false positives due to external noise, temperature variations, or minor fluctuations in the high-voltage system, leading to unnecessary warnings or system shutdowns. Moreover, a more manual method is often used which is the insulation resistance test using a megohmmeter, where a high DC voltage (e.g., 500V to 1000V) is applied to the motor drive circuit while the vehicle is off, and the resulting leakage current is measured to determine insulation integrity. This method is highly effective in detecting severe insulation breakdowns but not impractical for real-time monitoring, as the method required the vehicle to be taken offline for testing. Moreover, the method may be only detecting the insulation failures that had already occurred and is not effective in predicting insulation degradation over time.
Therefore, there is a need to provide an improved technique for isolation detection in a motor drive of an electric vehicle to overcome one or more problems associated as set forth above.
SUMMARY
An object of the present disclosure is to provide a method for monitoring insulation state of an inverter driven motor.
In accordance with an aspect of the present disclosure, there is provided a method for monitoring insulation state of an inverter driven motor. The method comprises detecting transient terminal voltage output of the motor, detecting motor oscillation current, acquiring a frequency response curve of a motor winding based on the detected voltage output and oscillation current and monitoring insulation state by utilizing a high-frequency sensitive characteristic component of the frequency response curve.
The present disclosure provides a method of isolation detection for a motor drive of an electric vehicle. The method as disclosed by present disclosure is advantageous in terms of enhanced high-frequency signal analysis techniques. Beneficially, the method enables real-time and precise insulation monitoring, thereby improves the early fault detection. Beneficially, the method provides high sensitivity to insulation degradation which captures the minor changes before the changes develop into critical failures. Additionally, the methods enhances the adaptability across different motor conditions, thereby enables the robust fault diagnosis. Furthermore, the method also facilitates predictive maintenance, thereby reducing the downtime. Also, the method significantly ensures that the insulation deterioration beyond a predetermined threshold is promptly flagged, thereby allows the timely corrective actions. Beneficially, the method provides a reliable assessment of insulation health which allows for implementation across various inverter-driven motors without major modifications. Furthermore, the method improves the system efficiency and safety by preventing catastrophic failures.
Additional aspects, advantages, features and objects of the present disclosure would be made apparent from the drawings and the detailed description of the illustrative embodiments constructed in conjunction with the appended claims that follow.
It will be appreciated that features of the present disclosure are susceptible to being combined in various combinations without departing from the scope of the present disclosure as defined by the appended claims.
BRIEF DESCRIPTION OF DRAWINGS
The summary above, as well as the following detailed description of illustrative embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the present disclosure, exemplary constructions of the disclosure are shown in the drawings. However, the present disclosure is not limited to specific methods and instrumentalities disclosed herein. Moreover, those in the art will understand that the drawings are not to scale. Wherever possible, like elements have been indicated by identical numbers.
Embodiments of the present disclosure will now be described, by way of example only, with reference to the following diagrams wherein:
FIG. 1 illustrates a flow chart of a method for monitoring insulation state of an inverter driven motor, in accordance with an aspect of the present disclosure.
In the accompanying drawings, an underlined number is employed to represent an item over which the underlined number is positioned or an item to which the underlined number is adjacent. A non-underlined number relates to an item identified by a line linking the non-underlined number to the item. When a number is non-underlined and accompanied by an associated arrow, the non-underlined number is used to identify a general item at which the arrow is pointing.
DETAILED DESCRIPTION
The following detailed description illustrates embodiments of the present disclosure and ways in which they can be implemented. Although some modes of carrying out the present disclosure have been disclosed, those skilled in the art would recognise that other embodiments for carrying out or practising the present disclosure are also possible.
The description set forth below in connection with the appended drawings is intended as a description of certain embodiments of a method for monitoring insulation state of an inverter driven motor and is not intended to represent the only forms that may be developed or utilised. The description sets forth the various structures and/or functions in connection with the illustrated embodiments; however, it is to be understood that the disclosed embodiments are merely exemplary of the disclosure that may be embodied in various and alternative forms. The figures are not necessarily to scale; some features may be exaggerated or minimised to show details of particular components. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a representative basis for teaching one skilled in the art to variously employ the present invention.
While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however, that it is not intended to limit the disclosure to the particular forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure.
The terms “comprise”, “comprises”, “comprising”, “include(s)”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, system that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or system. In other words, one or more elements in a system or apparatus preceded by “comprises... a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or apparatus.
In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings and which are shown by way of illustration specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.
The present disclosure will be described herein below with reference to the accompanying drawings. In the following description, well known functions or constructions are not described in detail since they would obscure the description with unnecessary detail.
As used herein, the terms “electric vehicle”, “EV”, and “EVs” are used interchangeably and refer to any vehicle having stored electrical energy, including the vehicle capable of being charged from an external electrical power source. This may include vehicles having batteries which are exclusively charged from an external power source, as well as hybrid-vehicles which may include batteries capable of being at least partially recharged via an external power source. Additionally, it is to be understood that the ‘electric vehicle’ as used herein includes electric two-wheeler, electric three-wheeler, electric four-wheeler, electric pickup trucks, electric trucks and so forth.
As used herein, the term “insulation state” refers to the condition or integrity of the electrical insulation within a system, particularly in components such as inverters, motors, or power electronics. The insulation state represents the ability of the insulation to prevent unintended current leakage, short circuits, or breakdowns under operating conditions. The insulation state can be quantitatively assessed using parameters such as insulation resistance, leakage current, dielectric strength, or capacitance variations. Changes in the insulation state may indicate degradation due to thermal stress, electrical stress, aging, contamination, or mechanical wear.
As used herein, the terms “inverter driven motor” and “motor” are used interchangeably and refer to an electric motor that operates with a power supply regulated by an inverter, which converts direct current (DC) or alternating current (AC) input into a variable frequency and voltage AC output. The inverter enables precise control of the motor's speed, torque, and overall performance by adjusting the output frequency and voltage according to the operational requirements. Such motors are commonly employed in applications demanding energy efficiency, dynamic response, and variable-speed operation, including industrial automation, electric vehicles, HVAC systems, and robotics.
As used herein, the term “transient terminal voltage output” refers to the voltage measured at the terminals of an electric motor that exhibits rapid variations in response to switching events of an associated inverter. The transient voltage arises due to the dynamic electrical interactions between the motor windings and the inverter switching signals, including pulse-width modulation (PWM) effects, parasitic capacitances, and inductive coupling within the motor circuit. The transient terminal voltage output captures high-frequency characteristics indicative of insulation conditions, electrical resonance, and potential degradation in motor windings.
As used herein, the term “motor oscillation current” refers to the transient or high-frequency current component that arises within the motor windings due to rapid changes in the applied voltage, particularly during inverter switching events. The motor oscillation current is primarily influenced by the motor's parasitic capacitances, inductances, and impedance characteristics, and exhibits oscillatory behaviour due to the interaction between the motor windings and the inverter-driven switching signals.
As used herein, the term “frequency response curve” refers to a graphical or analytical representation of a system response to varying input frequencies, illustrating how the system reacts to different frequency components of an applied signal. The frequency response curve is derived from the relationship between the transient terminal voltage output and the motor oscillation current across a range of frequencies. The frequency response curve characterizes the impedance behaviour of the motor windings and provides insights into resonance effects, insulation integrity, and deviations caused by insulation degradation.
As used herein, the term “high-frequency sensitive characteristic component” refers to a distinct feature or attribute in the frequency response of a motor winding that exhibits sensitivity to insulation state variations at high frequencies. The high-frequency sensitive characteristic component may include, but is not limited to, resonance peaks, attenuation characteristics, impedance variations, or phase shifts within a predefined high-frequency range.
As used herein, the term “switching event” refers to the transition of a power electronic switching device, such as an insulated-gate bipolar transistor (IGBT), metal-oxide-semiconductor field-effect transistor (MOSFET), or any other semiconductor switch, between its conducting (ON) state and non-conducting (OFF) state, or vice versa, within an inverter, converter, or motor drive system. This transition induces a change in the electrical conditions of the circuit, resulting in variations in voltage, current, and electromagnetic behaviour.
As used herein, the term “at least one current sensor” and “current sensor” are used interchangeably and refer to a device or system configured to detect, measure, and monitor an electric current flowing through a conductor, circuit, or electrical component. The current sensor generates the output signal corresponding to the magnitude and direction of the current, which can be further processed for control, monitoring, or protection purposes. The sensor may operate based on various principles, including but not limited to electromagnetic induction, Hall effect, resistive shunt measurement, fluxgate technology, or Rogowski coil-based sensing.
As used herein, the term “inverter” refers to an electrical device or circuit configured to convert direct current (DC) into alternating current (AC) at a desired voltage, frequency, and waveform. The inverter typically comprises power semiconductor switching elements, such as insulated-gate bipolar transistors (IGBTs) or metal-oxide-semiconductor field-effect transistors (MOSFETs), which are controlled by a switching algorithm to generate an AC output waveform. The inverter may include a control unit that regulates the output characteristics based on input parameters, load conditions, and feedback signals.
As used herein, the term “frequency domain transformation” refers to a mathematical process that converts a signal from its time-domain representation to a frequency-domain representation, facilitating the analysis of signal characteristics such as amplitude, phase, and frequency components. The frequency domain transformation enables the extraction of frequency-specific features from transient or oscillatory signals, which are critical for evaluating system behaviour. The transformation may be performed using techniques such as Fast Fourier Transform (FFT), Short-Time Fourier Transform (STFT), or wavelet transform, each offering unique advantages in detecting and isolating frequency-dependent anomalies in electrical signals.
As used herein, the term “at least one resonance peak” and “resonance peak” are used interchangeably and refer to a distinct frequency or multiple frequencies within the frequency response curve of a motor winding at which the impedance, voltage, or current exhibits a peak due to resonance effects. The resonance peak arises from the interaction between the motor winding’s inductive and capacitive characteristics, influenced by insulation integrity and electrical properties. The presence, amplitude, and shift of these resonance peaks serve as indicators of changes in the motor insulation state.
As used herein, the term “deviation metric” refers to a quantitative parameter representing the difference between a current high-frequency sensitive characteristic component of a motor’s frequency response curve and a reference frequency response curve. The deviation metric may be derived using statistical, mathematical, or signal-processing techniques, such as absolute difference, root mean square error (RMSE), correlation coefficients, or machine learning-based anomaly detection models. The deviation metric serves as an indicator of insulation state degradation, where a higher deviation value signifies greater insulation deterioration.
As used herein, the term “alert signal” refers to an electrical, visual, audible, or communication-based signal generated in response to a detected condition, such as an isolation fault, to notify a control system, operator, or external monitoring unit for initiating corrective action or further diagnosis.
As used herein, the term “predetermined threshold” refers to a predefined value, range, or condition set as a reference for evaluating a parameter or triggering a specific action. The predetermined threshold can be established based on empirical data, experimental results, industry standards, or system requirements and is used to determine when a certain response, such as generating an alert or adjusting system parameters, is necessary.
As used herein, the term “trend analysis” refers to a systematic evaluation of variations in a monitored parameter over a defined period to identify patterns, tendencies, or deviations indicative of a changing condition. Specifically, in the insulation monitoring of an inverter-driven motor, trend analysis involves continuously or periodically assessing variations in the high-frequency sensitive characteristic component of the frequency response curve. The trend analysis may involve statistical methods, data modelling, or machine learning algorithms to establish predictive insights and generate alerts when predefined deterioration thresholds are met.
Figure 1, describes a method 100 for monitoring insulation state of an inverter driven motor. The method 100 starts at step 102 and completes at step 108. At step 102, the method 100 comprises detecting transient terminal voltage output of the motor. At step 104, the method 100 comprises detecting motor oscillation current. At step 106, the method 100 comprises acquiring a frequency response curve of a motor winding based on the detected voltage output and oscillation current. At step 108, the method 100 comprises monitoring insulation state by utilizing a high-frequency sensitive characteristic component of the frequency response curve.
The present disclosure provides the method 100 of isolation detection for the motor drive of the electric vehicle. The method 100 as disclosed by present disclosure is advantageous in terms of providing an enhanced high-frequency signal analysis techniques. Beneficially, by analyzing the high-frequency components in the motor response, the method 100 enables real-time and precise insulation monitoring, thereby improving the early fault detection. Furthermore, the frequency response-based techniques significantly provide the high sensitivity to insulation degradation which captures the minor changes before develop into critical failures. Additionally, the use of frequency domain transformation methods, such as FFT, STFT, and wavelet transform, beneficially enhances the adaptability across different motor conditions, thereby enables the robust fault diagnosis. Furthermore, the method 100 also facilitates predictive maintenance by analyzing trends in insulation degradation and estimating the remaining useful life, thereby reducing downtime. Furthermore, the automated alerts ensure that the insulation deterioration beyond the predetermined threshold is promptly flagged which allows timely corrective actions. Beneficially, by comparing the frequency response curves against reference data, the method 100 provides a reliable assessment of insulation health. Additionally, the early detection of insulation issues improves the system efficiency and safety by preventing catastrophic failures.
In an embodiment, detecting the transient terminal voltage output comprises measuring voltage at the motor terminals during a switching event of the inverter. During operation, the inverter undergoes switching events that induce transient voltage fluctuations at the motor terminals. The voltage transients provide critical information regarding the electrical response of the motor windings. By capturing and analyzing these transient voltages, the method 100 enables the precise characterization of the motor frequency response, thereby facilitating the accurate assessment of the insulation degradation. Beneficially, the voltage measurement may be performed using a high-speed voltage sensors or probes capable of capturing rapid transients which ensure the reliable data acquisition for subsequent frequency domain transformation and insulation state evaluation.
In an embodiment, detecting the motor oscillation current comprises measuring current flow through motor windings using at least one current sensor. The current sensor may be positioned at a suitable location within the motor drive system to capture transient oscillation characteristics effectively. The sensor may be a Hall-effect sensor, a shunt resistor-based sensor, or a Rogowski coil, depending on the accuracy and bandwidth requirements of the monitoring system. By capturing oscillation currents, the method 100 significantly enables the precise determination of the motor electrical response to transient voltage fluctuations which facilitates the generation of a frequency response curve for insulation state monitoring. The acquired current data may be processed in conjunction with the detected transient terminal voltage output to derive relevant frequency-domain characteristics, aiding in the identification of insulation degradation trends.
In an embodiment, acquiring the frequency response curve comprises performing a frequency domain transformation on the detected transient terminal voltage output and the motor oscillation current. Furthermore, the frequency domain transformation comprises at least one of Fast Fourier Transform (FFT), Short-Time Fourier Transform (STFT), or wavelet transform. The frequency domain transformation converts the time-domain signals into the frequency domain, enables the identification of characteristic frequency components that indicate insulation degradation. The frequency domain transformation may be executed using the techniques such as Fast Fourier Transform (FFT), Short-Time Fourier Transform (STFT), or wavelet transform to extract relevant frequency-dependent characteristics. Beneficially, by analysing the transformed data, the method 100 identifies the variations in the electrical response of the motor, thereby allows for the precise monitoring of insulation health and early detection of potential faults.
In an embodiment, the high-frequency sensitive characteristic component comprises at least one resonance peak in the frequency response curve. The at least resonance peak may be identified by detecting the transient terminal voltage output and motor oscillation current, followed by performing the frequency domain transformation to derive the frequency response curve. The presence, shift, or attenuation of the resonance peak serves as an indicator of insulation deterioration which enables the accurate assessment of the motor’s insulation health. By continuously monitoring the resonance peaks and comparing with the reference data, the method 100 advantageously ensures the early detection of insulation faults, thereby facilitating the predictive maintenance and improving the overall motor reliability.
In an embodiment, the method 100 comprises comparing the acquired frequency response curve with a reference frequency response curve to detect changes in insulation state. The reference frequency response curve represents a baseline or predefined standard corresponding to a known insulation condition. The comparison may be performed by analysing the deviations in the characteristic components, such as the resonance peaks or amplitude variations in high-frequency regions, which may be sensitive to insulation deterioration. Beneficially, by identifying discrepancies between the acquired and reference frequency response curves, the method 100 enables the precise detection of insulation degradation, thereby allows for early fault diagnosis and predictive maintenance.
In an embodiment, the method 100 comprises quantifying the insulation state by calculating a deviation metric between current and reference high-frequency sensitive characteristic components. Furthermore, the method 100 comprises generating an alert signal when the monitored insulation state deteriorates beyond a predetermined threshold. The deviation metric may be derived by analyzing variations in the frequency response curve obtained from transient terminal voltage output and motor oscillation current. The method 100 involves comparing the real-time high-frequency sensitive characteristic component with the predefined reference dataset to detect deviations indicative of insulation degradation. The deviation metric may be computed using statistical measures, machine learning algorithms, or frequency domain transformations, such as Fast Fourier Transform (FFT), Short-Time Fourier Transform (STFT), or wavelet transformation. Based on the magnitude and trend of the deviation, the method significantly enables the predictive assessment of insulation health and facilitates proactive maintenance strategies to prevent potential motor failures. Additionally, when the monitored insulation state deteriorates beyond a predetermined threshold, the method 100 generates the alert signal. The alert signal may be an electrical, visual, audible, or communication-based signal generated in response to a detected condition.
In an embodiment, the method 100 comprises estimating remaining useful life of motor insulation based on trend analysis of changes in the high-frequency sensitive characteristic component over time. The method 100 involves continuously or periodically acquiring the frequency response curve of the motor winding and identifying deviations in high-frequency resonance peaks indicative of insulation degradation. By applying statistical modelling, machine learning algorithms, or historical data comparison, the method 100 establishes the degradation trend that enables predictive assessment of insulation failure. The estimation allows for proactive maintenance planning by determining the rate of deterioration and predicting the expected operational lifespan of the insulation. Additionally, threshold-based alerts may be generated if the observed degradation rate exceeds predefined limits, ensures timely intervention to prevent motor failure.
In an embodiment, the method 100 for monitoring insulation state of the inverter driven motor. The method 100 starts at step 102 and completes at step 108. At step 102, the method 100 comprises detecting transient terminal voltage output of the motor. At step 104, the method 100 comprises detecting motor oscillation current. At step 106, the method 100 comprises acquiring the frequency response curve of the motor winding based on the detected voltage output and oscillation current. At step 108, the method 100 comprises monitoring insulation state by utilizing the high-frequency sensitive characteristic component of the frequency response curve. Furthermore, detecting the transient terminal voltage output comprises measuring voltage at the motor terminals during the switching event of the inverter. Furthermore, detecting the motor oscillation current comprises measuring current flow through motor windings using the at least one current sensor. Furthermore, acquiring the frequency response curve comprises performing the frequency domain transformation on the detected transient terminal voltage output and the motor oscillation current. Furthermore, the frequency domain transformation comprises the at least one of Fast Fourier Transform (FFT), Short-Time Fourier Transform (STFT), or wavelet transform. Furthermore, the high-frequency sensitive characteristic component comprises the at least one resonance peak in the frequency response curve. Furthermore, the method 100 comprises comparing the acquired frequency response curve with the reference frequency response curve to detect changes in insulation state. Furthermore, the method 100 comprises quantifying the insulation state by calculating the deviation metric between current and reference high-frequency sensitive characteristic components. Furthermore, the method 100 comprises generating the alert signal when the monitored insulation state deteriorates beyond the predetermined threshold. Furthermore, the method 100 comprises estimating remaining useful life of motor insulation based on trend analysis of changes in the high-frequency sensitive characteristic component over time.
In the description of the present invention, it is also to be noted that, unless otherwise explicitly specified or limited, the terms “disposed,” “mounted,” and “connected” are to be construed broadly, and may for example be fixedly connected, detachably connected, or integrally connected, either mechanically or electrically. They may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Modifications to embodiments and combination of different embodiments of the present disclosure described in the foregoing are possible without departing from the scope of the present disclosure as defined by the accompanying claims. Expressions such as “including”, “comprising”, “incorporating”, “have”, “is” used to describe and claim the present disclosure are intended to be construed in a non- exclusive manner, namely allowing for items, components or elements not explicitly described also to be present. Reference to the singular is also to be construed to relate to the plural where appropriate.
Although embodiments have been described with reference to a number of illustrative embodiments thereof, it should be understood that numerous other modifications and embodiments can be devised by those skilled in the art that will fall within the spirit and scope of the principles of this disclosure. More particularly, various variations and modifications are possible in the component parts and/or arrangements of the subject combination arrangement within the scope of the present disclosure, the drawings and the appended claims. In addition to variations and modifications in the component parts and/or arrangements, alternative uses will also be apparent to those skilled in the art.
,CLAIMS:WE CLAIM:
1. A method (100) for monitoring insulation state of an inverter driven motor, wherein the method (100) comprises:
- detecting transient terminal voltage output of the motor;
- detecting motor oscillation current;
- acquiring a frequency response curve of a motor winding based on the detected voltage output and oscillation current; and
- monitoring insulation state by utilizing a high-frequency sensitive characteristic component of the frequency response curve.
2. The method (100) as claimed in claim 1, wherein detecting the transient terminal voltage output comprises measuring voltage at the motor terminals during a switching event of the inverter.
3. The method (100) as claimed in claim 1, wherein detecting the motor oscillation current comprises measuring current flow through motor windings using at least one current sensor.
4. The method (100) as claimed in claim 1, wherein acquiring the frequency response curve comprises performing a frequency domain transformation on the detected transient terminal voltage output and the motor oscillation current.
5. The method (100) as claimed in claim 4, wherein the frequency domain transformation comprises at least one of Fast Fourier Transform (FFT), Short-Time Fourier Transform (STFT), or wavelet transform.
6. The method (100) as claimed in claim 1, wherein the high-frequency sensitive characteristic component comprises at least one resonance peak in the frequency response curve.
7. The method (100) as claimed in claim 1, wherein the method (100) comprises comparing the acquired frequency response curve with a reference frequency response curve to detect changes in insulation state.
8. The method (100) as claimed in claim 1, wherein the method (100) comprises quantifying the insulation state by calculating a deviation metric between current and reference high-frequency sensitive characteristic components.
9. The method (100) as claimed in claim 1, wherein the method (100) comprises generating an alert signal when the monitored insulation state deteriorates beyond a predetermined threshold.
10. The method (100) as claimed in claim 1, wherein the method (100) comprises estimating remaining useful life of motor insulation based on trend analysis of changes in the high-frequency sensitive characteristic component over time.