Method for estimating life consumption

Abstract

A method for estimating the life consumption of an electronic component used with an electric motor, the method comprising identifying the start of an operating drive cycle of the electric motor; measuring an operating parameter of the electronic component during the operating drive cycle, wherein a change in direction of the measured value of the operating parameter is identified during a time period of the operating drive cycle; identifying whether the change in direction of the measured value of the operating parameter corresponds to a maximum or a minimum value, wherein if the change in direction of the measured value of the operating parameter corresponds to a maximum value, the maximum value is placed in a first buffer, and if the measured value of the operating parameter corresponds to a minimum value, the minimum value is placed in a second buffer, wherein when each maximum or minimum value is identified, the corresponding value is compared with the previous maximum and / or minimum values stored in the first buffer and the second buffer respectively to identify a full load cycle or a half load cycle of the electronic component, wherein for each identified full load cycle and half load cycle, the stored maximum and / or minimum values used to identify the full load cycle and / or half load cycle are removed from the corresponding buffer, identifying the end of the operating drive cycle of the electric motor, wherein after identifying the end of the drive cycle, a final operating parameter value is determined, and any remaining full load cycles and / or half load cycles of the electronic component are identified in combination with the maximum and minimum values retained in the corresponding first buffer and second buffer; estimating a life consumption value of the electronic component associated with the operating drive cycle based on the full load cycles and half load cycles identified during the operating drive cycle and identified based on the determined final operating parameter value after the operating drive cycle has been completed.

Description

Technical Field

[0001] The present invention relates to a method for estimating lifetime consumption, in particular a method for estimating the lifetime consumption of semiconductor devices for vehicle applications. Background Art

[0002] With the increasing interest in environmentally friendly vehicles, there is a corresponding increase in the interest in using electric motors to provide drive torque for electric vehicles.

[0003] An electric motor operates based on the principle that a current-carrying wire will be subjected to a force when there is a magnetic field. When the current-carrying wire is placed perpendicular to the magnetic field, the force on the current-carrying wire is proportional to the flux density of the magnetic field. Generally, in an electric motor, the force on the current-carrying wire forms a rotational torque.

[0004] Examples of known types of electric motors include induction motors, brushless permanent magnet motors, switched reluctance motors, and synchronous slip-ring motors, which have a rotor and a stator, as is well known to those skilled in the art.

[0005] Generally, a power electronics system, which may include an inverter for example, is used to control the current within the electric motor, thereby controlling the drive torque generated by the electric motor. However, the operation of the electric motor can impose thermo-mechanical effects on the semiconductor devices within the power electronics system, where due to the differences in the thermal expansion coefficients and mechanical stiffnesses of the materials within the power electronics system, thermal deformations (i.e., thermal loads) that can cause fatigue and functional failures are generated.

[0006] However, as a result of the unpredictable operating environment and complex and irregular operating conditions of electric vehicles, the temperature distribution / load conditions of the semiconductor devices within the power electronics system are generally variable and unpredictable.

[0007] To effectively evaluate cumulative fatigue damage, different cycle counting algorithms have been used in applications subjected to random and complex load conditions, such as level crossing counting, simple range counting, peak counting, and rainflow counting, etc. These counting methods are particularly useful in data analysis because the spectrum of the varying load can be grouped into a set of simple uniform data histograms, which allows the application of Miner's rule for fatigue life assessment.

[0008] Based on the measured thermal data, the corresponding fatigue damage caused by the load distribution on the semiconductor devices within the power electronics system can be numerically evaluated to predict the remaining life of the power electronics system.

[0009] Among different cycle counting algorithms, the rainflow counting method developed by T. Endo and M. Matsuishi in 1968 has been widely used in reliability analysis, where the rainflow counting uses rules for pairing local minima and maxima to generate equivalent load cycles.

[0010] Typically, all heat-related data, such as ambient, coolant, and semiconductor junction temperatures, are continuously monitored throughout an entire cycle and recorded in a storage device. However, due to the need to pair local minima and maxima to produce an equivalent duty cycle, the identification of local minima and maxima is typically only performed at the end of the drive cycle of the electric motor. Therefore, the corresponding life consumption or remaining life can only be updated after the entire duty cycle.

[0011] However, the disadvantages of using this method are, first, a large-capacity data storage device is required to record the data for the entire drive cycle, and second, the life prediction can only be refreshed after each cycle is completed.

[0012] To address these issues, another technique has been proposed that utilizes a stack implementation where consecutive extreme values are compared with previous values through a recursive algorithm to identify equivalent full and half cycles of the load distribution on the semiconductor device caused by thermomechanical stress occurring during the drive cycle. This method can provide real-time life consumption estimation with smaller data storage requirements. However, due to uncounted maximum / minimum values resulting from incomplete data, this technique may lead to errors in life consumption estimation.

[0013] It is desirable to improve this situation. Summary of the Invention

[0014] According to one aspect of the present invention, there is provided a method and apparatus for estimating the life consumption of an electronic component used with an electric motor according to the appended claims.

[0015] The present invention provides the advantages of allowing continuous monitoring of the maximum / minimum temperature values of the semiconductor device to allow for the determination of in-cycle thermal damage and post-cycle damage in parallel, thereby allowing for higher accuracy with real-time monitoring capabilities. Additionally, the hardware storage device for storing measured thermal / load data can be reduced. Brief Description of the Drawings

[0016] The present invention will now be described by way of example with reference to the accompanying drawings, in which:

[0017] Figure 1 A decomposition view of a drive device from a first perspective according to an embodiment of the present invention is shown;

[0018] Figure 2 A decomposition view of a drive device from a second perspective according to an embodiment of the present invention is shown;

[0019] Figure 3 A control device according to an embodiment of the present invention is shown;

[0020] Figure 4 illustrates a life consumption estimation system according to an embodiment of the present invention;

[0021] Figure 5 illustrates a typical life consumption estimation performed by a life consumption estimation system according to an embodiment of the present invention. Detailed Description

[0022] The described embodiment of the present invention is a method for estimating the life consumption of an electronic component used with an electric motor. For the purposes of this embodiment, the electric motor is used in a wheel of a vehicle, wherein the electric motor includes an integrated power module having an inverter for controlling the current in the electric motor. Preferably, the motor is used to provide drive for the vehicle. However, the electric motor can be used for any purpose and can be located anywhere within the vehicle when located in the vehicle. The motor is of a type having a set of coils that are part of a stator for connection to the vehicle and a rotor carrying a set of magnets that radially surrounds the coils and is for connection to the wheel. To avoid doubt, the various aspects of the present invention are equally applicable to a generator having the same arrangement. Thus, the definition of an electric motor is intended to include a generator.

[0023] For the purposes of this embodiment, as Figure 1 shown, the in-wheel electric motor includes a stator 252, which includes a radiator 253, a plurality of coils 254, and an electronic module 255 mounted in the rear of the stator for driving the coils. The coils 254 are formed on a stator tooth lamination structure to form a coil winding, as described below. A stator cover 256 is mounted on the rear of the stator 252, surrounding the electronic module 255 to form the stator 252, which can then be fixed to the vehicle and does not rotate relative to the vehicle during use.

[0024] The electronic module 255 includes two control devices 400, where each control device 400 includes two inverters 410 and control logic 420, and in this embodiment, the control logic includes a processor for controlling the operation of the two inverters 410, as Figure 3 shown. Although in this embodiment, the electronic module 255 includes two control devices, equally, the electronic module 255 can include a single control device or more than two control devices.

[0025] The rotor 240 includes a front portion 220 and a cylindrical portion 221 forming a cover that substantially surrounds the stator 252. The rotor includes a plurality of permanent magnets 242 arranged on the inner side of the cylindrical portion 221. For the purposes of this embodiment, 32 magnet pairs are mounted on the inner side of the cylindrical portion 221. However, any number of magnet pairs can be used.

[0026] The magnet is very close to the coil winding on the stator 252 such that the magnetic field generated by the coil interacts with the magnet 242 disposed on the inner side of the cylindrical portion 221 of the rotor 240 to rotate the rotor 240. Since the permanent magnet 242 is used to generate the driving torque to drive the electric motor, the permanent magnet is generally referred to as the drive magnet.

[0027] The rotor 240 is attached to the stator 252 via a bearing housing 223. The bearing housing 223 can be a standard bearing housing as used in the vehicle in which the electric motor assembly will be installed. The bearing housing includes two parts, a first part fixed to the stator and a second part fixed to the rotor. The bearing housing is fixed to the central portion 253 of the wall of the stator 252 and is also fixed to the central portion 225 of the housing wall 220 of the rotor 240. The rotor 240 is thus rotatably fixed to the vehicle at the central portion 225 of the rotor 240, and the rotor will be used with the vehicle. This has the advantage that then a normal wheel bolt can be used at the central portion 225 to fix the rim and tire to the rotor 240 to fix the rim to the central portion of the rotor and thus firmly to the rotatable side of the bearing housing 223. The wheel bolt can be assembled through the central portion 225 of the rotor into the bearing housing itself. Since both the rotor 240 and the wheel are mounted on the bearing housing 223, there is a one-to-one correspondence between the rotational angles of the rotor and the wheel.

[0028] Figure 2 A perspective view of the same assembly, showing the stator 252 and the rotor, is presented. Figure 1 The rotor 240 includes an outer rotor wall 220 and a circumferential wall 221, and the magnets 242 are circumferentially disposed within the circumferential wall. As described above, the stator 252 is connected to the rotor 240 via the bearing housing at the central portions of the rotor wall and the stator wall.

[0029] A V-shaped seal is provided between the circumferential wall 221 of the rotor and the outer edge of the stator.

[0030] The rotor also includes a set of magnets 227 for position sensing, or commutation magnets, which in combination with sensors mounted on the stator allow the estimation of the rotor flux angle. The rotor flux angle defines the positional relationship between the drive magnet and the coil winding. Alternatively, instead of a set of separate magnets, the rotor can include a ring of magnetic material having a plurality of magnetic poles that act as a set of separate magnets.

[0031] To allow the commutation magnets to be used for calculating the rotor flux angle, preferably, each drive magnet has an associated commutation magnet, wherein the rotor flux angle is derived from the flux angles associated with the set of commutation magnets by calibrating the measured commutation magnet flux angles. To simplify the correlation between the commutation magnet flux angles and the rotor flux angle, preferably, the set of commutation magnets has the same number of magnets or pole pairs as the set of drive magnet pairs, wherein the commutation magnets and the associated drive magnets are substantially radially aligned with each other. Thus, for the purposes of the present embodiment, the set of commutation magnets has 32 magnet pairs, wherein each magnet pair is substantially radially aligned with a corresponding drive magnet pair.

[0032] In this embodiment, the sensors, which are Hall sensors, are mounted on the stator. The sensors are arranged such that as the rotor rotates, each of the individual commutation magnets forming the commutation magnet ring rotates past the sensors respectively.

[0033] As the rotor rotates relative to the stator, the commutation magnets rotate past the sensors accordingly, and the Hall sensors output an AC voltage signal, wherein the sensors output an entire voltage cycle of 360 electrical degrees for each magnet pair passing by the sensors.

[0034] For improved position detection, preferably, an associated second sensor is placed 90 electrical degrees shifted from the first sensor.

[0035] The electric motor 40 in this embodiment includes four coil groups 60, wherein each coil group 60 has three coil subgroups, which are coupled in a Y configuration to form a three-phase sub-electric motor, resulting in the motor having four three-phase sub-electric motors. A first control device is coupled to two coil groups, and a second control device is coupled to the other coil groups, wherein each inverter in the respective control devices is arranged to control the current in the respective coil groups. However, although this embodiment describes an electric motor having four coil groups 60 (i.e., four sub-electric motors), the electric motor can equally have two or more coil groups and associated control devices (i.e., two or more sub-electric motors). For example, in a preferred embodiment, the electric motor 40 includes eight coil groups 60, wherein each coil group 60 has three coil subgroups, which are coupled in a Y configuration to form a three-phase sub-electric motor, resulting in an electric motor having eight three-phase sub-electric motors.

[0036] Figure 3 The connection between the respective coil groups 60 and the control device 400 housed in the electronic module 255 is shown, wherein the respective coil groups 60 are connected to the respective three-phase inverters 410 included on the control device 400. As is well known to those skilled in the art, a three-phase inverter contains six switches, wherein a three-phase AC voltage can be generated by the controlled operation of the six switches.

[0037] As described above, the electronic module 255 includes two control devices 400, each control device 400 having two inverters 410 coupled to the coil group 60. Additionally, each control device 400 includes interface means, wherein in a first embodiment, the interface means on each control device 400 is arranged to allow communication between the respective control devices 400 housed in the electronic module 255 via a communication bus, and one of the control devices 400 is arranged to communicate with a vehicle controller mounted external to the electric motor. The processor 420 on each control device 400 is arranged to process the communication via the interface means.

[0038] The processor 420 on the respective control device 400 is arranged to control the two inverters 410 mounted in the respective control device 400 to allow each electric motor coil group 60 to be supplied with a three-phase voltage source, thereby allowing the respective coil subgroups to generate a rotating magnetic field. Although this embodiment describes each coil group 60 as having three coil subgroups, the present invention is not limited thereto, and it should be understood that each coil group 60 may have one or more coil subgroups.

[0039] Under the control of the respective processor 420, each three-phase bridge inverter 410 is arranged to provide pulse width modulation PWM voltage control on the respective coil subgroup, thereby generating a current in the respective coil subgroup for providing the required torque by the respective sub-electric motor.

[0040] As described above, PWM switching is used to apply an alternating voltage to the electric motor coil winding, wherein the amplitude of the voltage applied to the coil winding depends on the rotor speed. The torque applied to the rotor is generated by the phase current in the coil winding, wherein the electric motor torque is a function of the amplitude and phase angle of the phase current.

[0041] As described above, PWM control works by using the motor inductance to average the applied pulsed voltage to drive the required current into the motor coil. Using PWM control, the applied voltage is switched on the motor winding. During the period when the voltage is switched on the motor coil, the current rises in the motor coil at a rate determined by its inductance and the applied voltage. Before the current has increased beyond the required value, the PWM voltage control is cut off, thereby allowing precise control of the current to be achieved.

[0042] For a given coil group 60, the three-phase bridge inverter 410 switches are arranged to apply a single voltage phase on each coil subgroup.

[0043] The inverter switch may include a semiconductor device, such as a metal oxide semiconductor field effect transistor (MOSFET) or an insulated gate bipolar transistor (IGBT). In this example, the switch includes an IGBT. However, any suitable known switching circuit may be employed to control the current. A well-known example of such a switching circuit is a three-phase bridge circuit having six switches configured to drive a three-phase electric motor. The six switches are configured as three groups of two switches in parallel, where each pair of switches is placed in series and forms a branch of the three-phase bridge circuit.

[0044] Preferably, the vehicle controller is arranged to transmit a torque demand request to the control device 400 via a controller area network (CAN) bus 430. The torque demand request transmitted via the CAN bus 430 corresponds to the torque that the electric motor needs to generate based on driver input (e.g., based on a throttle demand generated within the vehicle).

[0045] To allow obtaining the temperature distribution of the corresponding semiconductor device within the control device, each control device includes means for measuring / estimating the temperature of the semiconductor device, such as the junction and / or core temperature of the semiconductor device. Examples of different means for measuring / estimating the temperature of the semiconductor device include thermistors, thermocouples, and resistive temperature detectors (RTDs), however, any means for measuring / estimating the temperature may be used.

[0046] Access to the temperature information allows performing an estimation of the lifetime consumption of the corresponding semiconductor device, as described below, where during each operation drive cycle of the electric motor, the system continuously monitors the maximum / minimum temperature values of the semiconductor device and the vehicle's surrounding environment. An online coding algorithm using a stack-based implementation and a recursive algorithm is used to identify full-load cycles and half-load cycles during the operation drive cycle.

[0047] The operation drive cycle of the electric motor will typically correspond to the operation cycle of the electric motor, e.g., the duration during which the electric motor is used to drive the vehicle from a first position to a second position. In other words, it corresponds to the duration during which the electric motor performs a specific operation.

[0048] Now reference will be made to Figure 4 an embodiment of a system for estimating lifetime consumption, where the lifetime consumption estimation system 500 includes an in-cycle damage assessment block 510, a stack management block 520, a post-cycle damage assessment block 530, and a lifetime consumption monitoring block 540. Preferably, a processor incorporated within one of the respective control devices 400 is used to perform the functions of the in-cycle damage assessment block 510, the stack management block 520, the post-cycle damage assessment block 530, and the lifetime consumption monitoring block 540. However, the functions for performing the lifetime consumption estimation may be performed remotely from the semiconductor device for which the lifetime consumption estimation is being performed. Similarly, the functions of the respective blocks may be combined.

[0049] During the period, the damage assessment block 510 is arranged to identify local maximum / minimum temperature values in real time, where the damage assessment block 510 during the period executes a counting algorithm, such as the rainflow algorithm developed by T. Endo and M. Matsuishi in 1968, to evaluate whether any whole or half heat cycle has been formed from the recorded thermal data.

[0050] To allow the damage assessment block 510 during the period to perform this task, when the life consumption estimation system 500 detects a new operation driving cycle, the initial condition of the vehicle is checked and recorded, which may include the remaining life of the system, coolant status, local time, weather conditions, etc. As described above, the temperature of each semiconductor device is monitored / estimated, such as the junction temperature of the semiconductor device, or the initial temperature from the IGBT temperature sensor.

[0051] Since the counting algorithm executed by the damage assessment block 510 during the period is executed in real time, it is impossible to pre-sort the recorded data. To overcome this problem, the damage assessment block 510 during the period is arranged to define two buffers with flexible sizes for processing the recorded maximum temperature values and minimum temperature values, where the recorded maximum temperature values are stored in one buffer and the recorded minimum temperature values are stored in the other buffer.

[0052] Whenever a new local maximum / minimum temperature value is identified, for example, using the 3-point counting rule, the damage assessment block 510 during the period stores the temperature value in the corresponding buffer and executes a counting algorithm, such as the rainflow algorithm, to evaluate whether any whole or half heat cycle has been identified from the recorded thermal data, also known as the full load cycle or half load cycle. Alternatively, the evaluation of whether any whole or half heat cycle has been identified can be performed before storing the new local maximum / minimum temperature value in the buffer, where, if appropriate, the new local maximum / minimum temperature value can be stored in the corresponding buffer after the evaluation has been completed.

[0053] The recursive algorithm uses the minimum and maximum temperature values stored in the corresponding stacks to identify the full load / temperature cycle and the half load / temperature cycle.

[0054] For illustrative purposes, an example of real-time identification of whole or half heat cycles using one buffer for storing maximum temperature values and a second buffer for storing minimum temperature values will be described.

[0055] For the detected maximum temperature, if the corresponding buffer already has an existing maximum temperature value stored, then, as described above, the new maximum temperature value is compared with the stored value, otherwise the new value becomes the first value in the buffer / stack.

[0056] If the new maximum temperature value is greater than the first maximum temperature value in the buffer / stack, then the buffer / stack for the minimum temperature value is checked for the saved values. If there is a minimum value, a half-load cycle is identified, where the temperature change over half a cycle will be the absolute value of the difference between that minimum value and the old maximum value.

[0057] The old maximum value is then removed from the maximum buffer / stack by replacing the old maximum value with the new temperature value.

[0058] Or, if there is more than one temperature value in the minimum buffer / stack, a full-load cycle is identified, where the temperature change over the full cycle will be the absolute value of the difference between the new minimum value and the old maximum value. In this case, the old maximum temperature value and the new minimum temperature value are removed from the respective buffer / stack.

[0059] In the case where the new maximum temperature value is less than the previously stored maximum temperature value, the new temperature value is saved in the maximum buffer / stack together with the previously stored maximum temperature value. If the maximum buffer / stack contains more than one temperature value, the whole operation will be recursively repeated.

[0060] Similarly, when a new minimum temperature value is identified, the new temperature value is compared with the first value in the minimum buffer / stack.

[0061] If the new minimum temperature value is less than the previously stored minimum temperature value, the maximum buffer / stack is checked for the saved values.

[0062] If there is only one maximum value, a half-cycle is identified, where the temperature change over the identified half-cycle is the absolute value of the difference between the maximum value and the previously stored minimum value.

[0063] The old minimum value is then removed from the minimum stack by replacing the old minimum value with the new temperature value.

[0064] If it is indicated that there is more than one value in the maximum buffer / stack, a full cycle is identified, where the absolute difference is the difference between the new maximum temperature value and the previously stored minimum temperature value.

[0065] In this case, the previously stored minimum temperature value and the new maximum temperature value are removed from their respective buffer / stack.

[0066] In the case of a new minimum temperature value that is greater than the previously stored temperature value, the new temperature value is stored side by side with the previously stored minimum temperature value in the minimum buffer / stack.

[0067] If the minimum stack contains more than one value, the whole operation will be recursively repeated.

[0068] Accordingly, the corresponding buffer size varies dynamically according to the recorded maximum and minimum temperature values. For example, a sequence of extreme values with decreasing absolute values will result in an increase in the buffer / stack size. Conversely, when an amplitude extreme value greater than the minimum value stored in the stack is encountered, the buffer / stack size decreases.

[0069] Once the operation drive cycle ends, any remaining maximum / minimum values that were not counted during the operation drive cycle are passed to the stack management block 520 and stored in the buffer / stack associated with the stack management block 520, as described below.

[0070] The initial condition of the corresponding buffer / stack can be defined in any suitable manner. For example, the buffer / stack can be initialized with the first two extreme values, a maximum value and a minimum value. Alternatively, the buffer / stack can be initialized with artificial values whose absolute values are greater than the highest expected maximum value or the lowest expected minimum value.

[0071] The full / half cycles identified by the cycle damage assessment block 510 within the period are provided to the life consumption monitoring block 540 to allow the life consumption monitoring block 540 to evaluate the corresponding damage caused during the recorded operation drive cycle and thus evaluate the life consumption of each semiconductor device, as described below.

[0072] The stack management block 520 is arranged to identify whole or half thermal cycles that were not identified by the cycle damage assessment block 510 during the operation drive cycle.

[0073] To allow the stack management block 520 to perform this task, when the life consumption estimation system 500 detects a new operation drive cycle, the stack management block 520 is arranged to record the initial ambient temperature of the vehicle, such as the initial junction temperature of the semiconductor device within the corresponding control device 400.

[0074] The initial ambient temperature value of the vehicle is saved as the first value in the maximum or minimum temperature value buffer associated with the stack management block 520. Preferably, the stack management block 520 buffer corresponds to the same buffer used by the cycle damage assessment block 510. However, the stack management block 520 can have separate maximum and minimum temperature value buffers.

[0075] In addition, the stack management block 520 is arranged to continuously monitor the ambient temperature of the vehicle during the operation drive cycle and store the value as the last value in one of the respective buffers associated with the stack management block 520.

[0076] In addition to the first and last ambient temperature values of the vehicle, the remaining maximum / minimum values that have not been counted by the in-cycle damage assessment block 510 are received by the stack management block 520 and stored in the buffer / stack of the stack management block 520 as described above. The stored temperature values (i.e., the first and last ambient temperatures and the remaining maximum / minimum values) are passed from the stack management block 520 to the post-cycle damage assessment block 530.

[0077] The post-cycle damage assessment block 530 is arranged to analyze the temperature values received from the stack management block 520 to identify any missing whole or half thermal cycles that were not identified by the in-cycle damage assessment block 510. For example, since the final ambient temperature value is only available after the operating duty cycle has been completed, the in-cycle damage assessment block 510 will typically not have access to this information, resulting in missing whole or half thermal cycles that are not identified by the in-cycle damage assessment block 510.

[0078] The life consumption monitoring block 540 receives the thermal cycle information from the in-cycle damage assessment block 510 and the post-cycle damage assessment block 530, and uses the identified thermal cycles received from both blocks to evaluate the corresponding life consumption.

[0079] Figure 5 A typical life consumption estimate performed by the life consumption estimation system 500 described above is shown. As described above, the life consumption estimation system continuously monitors the maximum / minimum temperature values around each semiconductor device and the vehicle, and processes the in-cycle thermal damage 600 performed in real time during the operating drive cycle 620 and the post-cycle damage 610 performed after the operating drive cycle 620 has been completed in a parallel manner, such that standard counting rules can be followed, which ensures high precision with real-time monitoring capabilities while reducing storage requirements.

Claims

1. A method for estimating the life consumption of an electronic component used with an electric motor, the method comprising identifying the start of an operating drive cycle of the electric motor; measuring an operating parameter of the electronic component during the operating drive cycle, wherein a direction change of a measured value of the operating parameter is identified during a time period of the operating drive cycle; identifying whether the direction change of the measured value of the operating parameter corresponds to a maximum value or a minimum value, wherein if the direction change of the measured value of the operating parameter corresponds to a maximum value, the maximum value is placed in a first buffer, and if the measured value of the operating parameter corresponds to a minimum value, the minimum value is placed in a second buffer, wherein when each maximum value or minimum value is identified, the corresponding value is compared with the previous maximum value and / or minimum value stored in the first buffer and the second buffer respectively to identify a full load cycle or a half load cycle of the electronic component, wherein for each identified full load cycle and half load cycle, the stored maximum value and / or minimum value used to identify the full load cycle and / or the half load cycle is removed from the corresponding buffer, identifying the end of the operating drive cycle of the electric motor, wherein after identifying the end of the drive cycle, a final operating parameter value is determined, and any remaining full load cycles and / or half load cycles of the electronic component are identified in combination with the maximum and minimum values retained in the respective first buffer and second buffer; estimating a life consumption value associated with the operating drive cycle of the electronic component based on the full load cycles and half load cycles identified during the operating drive cycle and identified based on the determined final operating parameter value after the operating drive cycle has been completed.

2. The method according to claim 1, wherein, The operating parameter is the temperature of the electronic component and / or the load condition of the electronic component.

3. The method according to claim 2, wherein The temperature of the electronic component is the junction temperature and / or the core temperature of the electronic component.

4. The method according to any one of the preceding claims, wherein, When the start of the operating drive cycle is identified, the condition associated with the electric motor is stored.

5. The method according to claim 4, wherein The stored condition includes the temperature of the electronic component and / or the local time of the electric motor.

6. The method according to claim 1, wherein The three-point rule is used to determine the direction change of the measured value of the operating parameter.

7. The method according to claim 1, wherein A counting algorithm is used to compare each identified maximum and / or minimum value with the previously stored maximum and / or minimum values stored in the first buffer and the second buffer respectively.

8. The method according to claim 7, wherein The counting algorithm is the rainflow algorithm.

9. The method according to claim 7 or 8, wherein The counting algorithm is arranged to identify full load cycles and / or half load cycles.

10. An apparatus for estimating the life consumption of an electronic component used with an electric motor, comprising means arranged to perform the method of any one of claims 1 to 9.

11. A vehicle, comprising an electric motor and the apparatus according to claim 10.

12. A computer storage medium, comprising computer-implemented instructions for performing the method of any one of claims 1 to 9.

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