Drive device capable of diagnosing fault omen

Abstract

The purpose of the present invention is to achieve a drive device capable of diagnosing a fault sign of a power device, limiting the operation of the power device or performing load drive control by excluding the power device, and suppressing a short replacement cycle of the power device. A drive device (100) is provided with: power devices (1a-1f) for driving a load; a characteristic sensor (2a-2f) that detects a characteristic of the power device (1a-1f); a sensing result holding unit (3) that holds the detection results of the characteristic sensors (2a-2f) in time series; control signal changing units (4, 5) for detecting a fault indication of the power devices (1a-1f) on the basis of the detection result of the sensing result holding unit (3), and outputting a control changing signal; and a drive control unit (10) that controls the driving of the power devices (1a-1f). The control signal changing units (4, 5) detect a fault sign of the power devices (1a-1f) on the basis of the control threshold value, and when the fault sign of the power devices (1a-1f) is detected, control changing signals (20) are output to the drive control unit (10) so that the load (200) is driven by the power devices (1a-1f) other than the detected power devices (1a-1f).

Description

Technical Field

[0001] The present invention relates to a drive device represented by an inverter for driving a load such as a motor. Background Art

[0002] Generally, automotive semiconductor components require higher reliability than consumer products, and semiconductor suppliers conduct mass production based on reliability assurance for automobiles.

[0003] For example, a car is guaranteed to last for 10 years or to last for 200,000 kilometers. These guarantees include the unique ideas of each car manufacturer and assume that semiconductor components will only work for a few hours a day.

[0004] The automotive industry is actively developing autonomous driving technology and advanced driver assistance technology. If autonomous driving level 4 or higher is put into practical use, it is expected that the system installed in the vehicle will perform driving and all other operations without the need for driver operation.

[0005] In addition to technology development, the application of car sharing is expected to expand in the future in terms of services. In order to effectively utilize the idle time of a car, sharing it with multiple users is expected to become popular in the future.

[0006] In order to improve the reliability of semiconductor components under the above circumstances, technologies for predicting the life of semiconductor components and the time when failures will occur have been developed.

[0007] Patent document 1 describes a technique that calculates the difference between the last measurement value and the current measurement value of a sensor installed on a power converter, performs variable transformation on a plurality of past differences to obtain intermediate data, and calculates the damage level of the power converter based on the intermediate data. In the technique described in patent document 1, when the damage level exceeds a damage threshold, a warning signal indicating that a fault period is approaching is output.

[0008] Patent Document 2 describes a technique in which, when it is determined that a power conversion device has reached a specific operating state, a current value is acquired and a failure sign is determined based on the acquired current value. Prior art literature Patent Literature

[0009] Patent Document 1: Japanese Patent Application Publication No. 2020-141465 Patent Document 2: Japanese Patent No. 6184335 Summary of the invention Problem that the invention aims to solve

[0010] As mentioned above, the current reliability of automotive semiconductor components includes the assumption of daily operating hours. This is because people operate the car as drivers. In the future, when car sharing or fully autonomous driving are put into practical use, especially in extreme cases such as automatic delivery, the operating hours are assumed to be close to 24 hours a day.

[0011] Under such circumstances, the life of semiconductor components, that is, the time when they reach failure, will be relatively much faster than it is now, and is expected to be as short as about 1 or 2 years.

[0012] Even in current automotive semiconductor components, for example, the reliability is designed to withstand the use assumed as described above of 10 years and 200,000 kilometers, but it is unrealistic to provide reliability guarantee for 24-hour operation as described above in terms of feasibility and cost.

[0013] Furthermore, in autonomous driving, a functional failure due to a failure of a component may be fatal, so it is preferable to be able to grasp the situation before a failure occurs.

[0014] As mentioned above, in an era when autonomous driving and car sharing are expected to become more widespread, one option for operating a car is to maintain performance by replacing parts. On the other hand, replacing parts will increase costs.

[0015] Therefore, in order to suppress the cost of component replacement, either reducing the replacement frequency or reducing the cost of replacement components themselves may become a problem.

[0016] However, if car sharing becomes popular and autonomous driving is put into practical use, the daily operating hours of semiconductor components are expected to increase, power devices will deteriorate faster, and replacement cycles will become shorter. Therefore, it is necessary not only to detect signs of failure at an early stage, but also to consider control conditions to delay the progress of degradation and thus suppress the shortening of replacement cycles.

[0017] The object of the present invention is to realize a drive device capable of diagnosing the signs of failure, which diagnoses the signs of failure of power devices, limits the operation of the power device with signs of failure or eliminates the power device to perform load drive control, thereby suppressing the shortening of the replacement cycle of the power device. Technical means of solving problems

[0018] In order to achieve the above-mentioned object, the present invention is constructed as follows.

[0019] A drive device capable of diagnosing a sign of a fault comprises: a plurality of power devices for driving a load; a characteristic sensor for detecting the characteristics of each of the plurality of power devices; a sensing result holding unit for holding the detection results of the plurality of power devices by the characteristic sensor in a time series; a control signal changing unit for detecting the sign of a fault of each of the plurality of power devices based on the detection results held in a time series by the sensing result holding unit and outputting a control change signal; and a drive control unit for controlling the driving of the plurality of power devices, wherein the control signal changing unit detects the sign of a fault of the plurality of power devices based on a control threshold value, and when the sign of a fault of at least one of the plurality of power devices is detected, the control change signal is output to the drive control unit in a manner such that the load is driven by the power devices other than the power device for which the sign of a fault is detected. Effects of the Invention

[0020] According to the present invention, a drive device capable of diagnosing a sign of failure can be realized, which diagnoses the sign of failure of a power device, restricts the operation of the power device that has predicted a failure or eliminates the power device to perform load drive control, thereby suppressing the shortening of the replacement cycle of the power device. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a diagram showing an example of the configuration of the driving device of Example 1. Figure 2 This is a graph showing an example of characteristic variation of a power device. Figure 3 This is a flowchart of the detection of a failure sign and the output of a control change signal in the first embodiment. Figure 4 This is a flowchart of the detection of a failure sign and the output of an alarm signal in the first embodiment. Figure 5 A diagram showing a drive device for performing diagnosis on a characteristic sensor according to a modification of the first embodiment. Figure 6 This is a diagram showing an example of the structure of the driving device of Example 2. Figure 7 This is a diagram showing an example of a method for detecting a sign of a failure according to the second embodiment. Figure 8 This is a diagram showing an example of a method of correcting a life prediction model. Fig. 9 This is a flowchart for outputting a control change signal and an alarm signal according to the remaining life. Fig.10 This is a diagram showing a structure for notifying the remaining life as actual time based on the operation history. Fig.11This is a diagram showing an example of the configuration of a vehicle according to the third embodiment. Fig.12 This is a flowchart of the delay diagnosis method of the third embodiment. Fig.13 This is a flowchart of the delay diagnosis method of the third embodiment. DETAILED DESCRIPTION

[0022] Hereinafter, a mode for carrying out the present invention will be described with reference to the drawings.

[0023] In the embodiment described below, it is possible to detect changes in the initial characteristics of the functional part included in the semiconductor component mounted on the vehicle with high accuracy, and when the change in the characteristics becomes large, it is judged as a sign of failure, and an alarm is issued in the form of a component replacement notice, etc. Furthermore, by mounting a structure of a correction function part, the period until the component is replaced can be further extended, and the cost can also be reduced by reducing the number of replacements. Example

[0024] (Example 1) Figure 1 FIG. 1 is a diagram showing the structure of a driving device 100 according to the first embodiment of the present invention. Figure 1 In the embodiment, characteristics of the power devices 1a to 1f mounted on the drive device 100 are measured by the characteristic sensors 2a to 2f respectively arranged corresponding to the power devices 1a to 1f, and the measurement results are stored as time series data.

[0025] Then, based on the retained time series data, it is determined whether the characteristics of each power device 1a to 1f have signs of changing over time. Thus, the signs of failure of each power device 1a to 1f are detected, and the control of the drive device 100 is changed according to the detection status, thereby reducing the frequency of component replacement of the drive device 100 or the power devices 1a to 1f, and when the characteristics of each power device 1a to 1f change further than the time when the signs of failure are detected, an alarm is issued to urge the user to replace the components.

[0026] The drive device 100 of the first embodiment of the present invention is used to drive the motor 200 shown as an example of a load, converts a DC power supply into a three-phase AC signal, and drives it through vector control to convert it into a rotational force. The control method for driving the motor 200 as a load is already known, so a detailed description is omitted in this specification.

[0027] The driving device 100 of embodiment 1 of the present invention comprises: a plurality of power devices 1a~1f; a driving control unit 10, which sends a signal for controlling the electrical action of the plurality of power devices 1a~1f to each power device 1a~1f; a plurality of characteristic sensors 2a~2f, which are configured corresponding to each power device 1a~1f for the purpose of sensing (detecting) the characteristics of each power device 1a~1f; and a sensing result holding unit (detection result holding unit) 3, which is used to periodically or at a specified time obtain the characteristics of the power devices 1a~1f sensed by the characteristic sensors 2a~2f, and hold the detection results as time series data.

[0028] Furthermore, the drive device 100 includes a characteristic change diagnostic unit 4, which refers to the time series data of the characteristics of the power devices 1a~1f maintained in the sensing result maintenance unit 3, diagnoses the fact that the characteristics of the power devices 1a~1f change over time, sends a control change signal 20 to the drive control unit 10, and outputs an alarm signal 30.

[0029] Here, the plurality of power devices 1a to 1f and the plurality of characteristic sensors 2a to 2f are numbered by using a combination of numbers and lowercase letters, but in this specification, the power devices 1a to 1f and the characteristic sensors 2a to 2f having the same lowercase letters at the end are defined to correspond to each other when acquiring characteristics. That is, as an example, in this specification, the object monitored by the characteristic sensor 2a is the characteristic of the power device 1a.

[0030] The characteristics of the power devices 1a to 1f monitored by the characteristic sensors 2a to 2f include voltage, current, and frequency as electrical characteristics and temperature (temperature near the power devices 1a to 1f) as environmental factor characteristics, but other characteristics may also be mentioned.

[0031] Alternatively, the voltage, current, frequency, and temperature may be intermittently measured over a certain period of time to calculate their time change rates, and stored in the sensing result storage unit 3 in the same manner as the characteristics of each power device 1a to 1f. Furthermore, the characteristic acquisition of the characteristic sensors 2a to 2f may selectively implement all or part of the characteristics listed above.

[0032] The characteristics of the power devices 1a to 1f may vary according to the operating state such as the power supply voltage or temperature, the control content of the load drive, or the phase information in the drive control. Therefore, the characteristics of each power device 1a to 1f monitored by the characteristic monitors 2a to 2f are preferably corrected according to the above-mentioned operating state, and the characteristics after the correction of the sensed characteristics of each power device 1a to 1f are referred to as corrected characteristics in the present invention.

[0033] The corrected characteristics preferably exclude the changes caused by the above-mentioned action state and reflect the pure characteristics of the power devices 1a~1f. As an example, the error rate of the characteristics of the power devices 1a~1f in the action state at the moment of monitoring the characteristics from the expected value is preferably used, but it can also be a value calculated by other methods.

[0034] An example of a method of diagnosing characteristic variation of the power devices 1 a to 1 f will be described.

[0035] Figure 2 This is a graph in which the value of the characteristic after correction is plotted on the vertical axis and time is plotted on the horizontal axis for one of the power devices 1 a to 1 f.

[0036] exist Figure 2 In the figure, each data point arranged horizontally corresponds to the corrected characteristic maintained in time series. When diagnosing the characteristic change, two thresholds are set. The first is the control thresholds CTH1 and CTH2 for detecting the change of the corrected characteristic over time and providing feedback on the control content of the drive device 100. The other threshold is the alarm thresholds ATH1 and ATH2 for outputting an alarm to the drive device 100 to warn that replacement is required when the characteristic change further develops.

[0037] In the first embodiment, the control threshold CTH1 and the alarm threshold ATH1 are used as thresholds for detecting when the corrected characteristic increases, and the control threshold CTH2 and the alarm threshold ATH2 are used as thresholds for detecting when the corrected characteristic decreases.

[0038] The characteristic change diagnosis unit 4 reads the time series data of the corrected characteristics of each power device 1a~1f maintained in the sensing result maintenance unit 3, calculates the characteristic change amount through statistical methods or machine learning, and determines whether the corrected characteristics of each power device 1a~1f sensed (detected) by the characteristic sensors 2a~2f are within the range of the above-mentioned control threshold or alarm threshold, so as to detect fault signs.

[0039] The range below the control threshold CTH1 and above the control threshold CTH2 is defined as the control threshold range, and the range greater than the control threshold CTH1 and below the alarm threshold ATH1 and smaller than the control threshold CTH2 and above the alarm threshold ATH2 is defined as the alarm threshold range. The alarm threshold range is wider than the control threshold range.

[0040] Figure 3 1 is a diagram showing an example of a flowchart of a method of determining a characteristic variation of each of the power devices 1 a to 1 f based on the corrected characteristics and outputting a control change signal to the drive control unit 10 .

[0041] Figure 3The flowchart of FIG. 1 describes one of the power devices 1 a to 1 f , but the flowchart of FIG. 1 may also be applied to other power devices mounted on the drive device 100 .

[0042] First, after the determination process is started in step S110, in step S120, the characteristic change diagnosis unit 4 reads the last recorded data in the time series data of the corrected characteristics of each power device 1a to 1f stored in the sensing result storage unit 3. For this data, that is, the value of the latest corrected characteristic in the characteristics of the power devices 1a to 1f, in step S130, a comparison is performed with the control threshold CTH1 or the control threshold CTH2. When the value of the corrected characteristic is greater than the control threshold CTH1 or less than the control threshold CTH2, the process proceeds to step S140. In step 130, when the value of the corrected characteristic is less than the control threshold CTH1 and greater than the control threshold CTH2, the process proceeds to step S160 and the flowchart ends.

[0043] In step S140, with reference to the corrected characteristic data of the past N times (N is a natural number) starting from the most recent data, it is determined whether the data of the past N times all exceed the control threshold CTH1 or are all less than the control threshold CTH2 (the characteristic change amount reaches outside the control threshold range). When it is determined that the characteristic change amount reaches outside the control threshold range, it is determined that the characteristics of the power devices 1a~1f have changed, and a sign of failure is detected.

[0044] If a sign of failure is detected in step S140 , the process proceeds to step S150 , and a control change signal 20 , which is a signal for diagnosing a characteristic change and changing the control method of the drive device 100 , is output.

[0045] In step S140 , when data equal to or less than the control threshold CTH1 or data less than the control threshold CTH2 is present in the data of the past N times, the process proceeds to step S160 and the flowchart ends.

[0046] exist Figure 3 In the example shown, when the corrected characteristic data exceeds the control threshold CTH1 for N consecutive times or is less than the control threshold CTH2 for N consecutive times, it is judged as a characteristic change. However, there is no problem even with a judgment method that combines the number of consecutive times and the occurrence pattern and is optimized through machine learning, etc.

[0047] The determination method can be rewritten from the outside after the driving device 100 is started.

[0048] The method of determining the variation in the characteristics of the power devices 1 a to 1 f has been described above. When the corrected characteristics of the power devices 1 a to 1 f further vary due to the passage of the operating time of the drive device 100 , a determination is made to output the alarm signal 30 .

[0049] Figure 4 1 is a flowchart showing a method of determining a characteristic variation of each of the power devices 1 a to 1 f based on the corrected characteristics and outputting the alarm signal 30 .

[0050] Figure 3 The flowchart shown and Figure 4 The difference in the flowchart shown is that Figure 4 Step S230 (with Figure 3 Steps S130) and S240 (with Figure 3 The threshold values ​​in step S140 (corresponding to step S140) are used as the alarm threshold value ATH1 and the alarm threshold value ATH2, and the threshold values ​​in step S250 (corresponding to step S250) are used as the alarm threshold value ATH1 and the alarm threshold value ATH2. Figure 3 The signal output in step S150 corresponding to the step S150 is used as the alarm signal 30.

[0051] exist Figure 4 In the action description of the flowchart, Figure 3 The control threshold CTH1 in the above-described operation description in the flowchart may be replaced by the alarm threshold ATH1 , the control threshold CTH2 may be replaced by the alarm threshold ATH2 , and the control change signal 20 may be replaced by the alarm control signal 30 .

[0052] The alarm signal 30 is output to a display device 31 provided outside the driving device 100 , and a warning message is displayed on the display device 31 .

[0053] The control thresholds CTH1 and CTH2 and the alarm thresholds ATH1 and ATH2 may be preset before the operation of the drive device 100, or may be set by communicating with the outside of the drive device 100, performing machine learning in a server at the communication destination, and reading out optimized values.

[0054] In addition, regarding the judgment criteria when data of corrected characteristics that cross the control thresholds CTH1 and CTH2 and the alarm thresholds ATH1 and ATH2 appear, consideration may be given to situations where the data appear consecutively for a specified number of times, situations where the data appear more than a specified number of times in the most recent N times, whether continuous or discontinuous, etc.

[0055] This determination criterion may be set in advance like the setting of the threshold value described above, or may be read back from the outside later.

[0056] In addition, since the operation of accumulating and saving data in time series will lead to an increase in the amount of data, when the most recent data is used for determination in the above, it is also possible to consider averaging the past data that deviates from the determination object, or re-recording the value and frequency as a histogram, etc., to reduce the number of data points. In the sensing result storage unit 3 of this embodiment, the internal data storage method and management method can also be appropriately selected.

[0057] The corrected characteristics can also be stored in a storage device such as a server located at the destination to which the information is transmitted via wireless communication, and used as research data for machine learning or characteristic change determination algorithms. In this case, in order to optimize the control threshold or alarm threshold for characteristic change diagnosis of the power devices 1a to 1f in the drive device 100 based on the machine learning results on the server side, the characteristic change determination threshold related to the power devices 1a to 1f of the drive device is rewritten via wireless communication, thereby providing better operation.

[0058] Next, the content of control change of drive device 100 when it is determined that power devices 1a to 1f show a sign of failure, that is, a sign that the characteristics of power devices 1a to 1f vary from the viewpoint of time change, is described.

[0059] It is assumed that the characteristic variation of the power devices 1 a to 1 f that progresses due to the operation of the drive device 100 varies among the power devices 1 a to 1 f even within the same drive device 100 .

[0060] The period during which the drive device 100 as a whole can be used is equal to the period during which all the power devices 1a to 1f can be used. In the present invention, the operating rate of the power device that detects the sign of a fault in the power devices 1a to 1f can be reduced, and the control of the drive device 100 can be changed in such a way that the progress of the characteristic change of the power device that detects the sign of a fault is relatively delayed compared with other power devices, thereby extending the period during which the drive device 100 as a whole can be used.

[0061] The minimum power devices 1a to 1f in each phase of the three-phase AC are arranged in a configuration where one power device is arranged on the power supply side (upper arm) and one power device is arranged on the ground side (lower arm).

[0062] In the present invention, two of the three phases need to operate in order to drive the motor 200 described as a load. Therefore, the unit to be excluded from the control of the drive device 100 is two power devices consisting of an upper arm and a lower arm that bear the load drive.

[0063] When one power device is detected to have a sign of failure, the operation of the driving phase undertaken by the power device is stopped, and the load is driven by the remaining two phases. However, it is preferred that the stop period can be switched according to the torque required by the motor 200, that is, the current value required for load driving.

[0064] More specifically, under a load condition where the required torque becomes relatively small, the driving of the phase to which the power device belongs is stopped so that the stop period of the power device becomes relatively long.

[0065] When failure signs are detected for a plurality of power devices in a plurality of control phases, control is performed such that degradation of the plurality of power devices progresses evenly by changing the phases excluded from drive control in a time-division manner.

[0066] By using the drive device 100 described in the first embodiment, when the characteristics of the power device constituting the drive device 100 undergo a characteristic change that becomes a sign of failure, it is detected and a control change signal 20 is sent to the drive control unit 10, thereby changing the control method of the drive device 100.

[0067] Thus, compared with the case where the control method of the drive device 100 is not changed, the period until the alarm signal 30 is output can be further extended.

[0068] By displaying a warning on the display device 31, the user of the drive device 100 takes measures such as component replacement after recognizing that the alarm signal 30 has been output. However, by extending the period until the output of the alarm signal 30 through the present invention, the time interval for component replacement can be extended, that is, the replacement frequency can be reduced.

[0069] Below, refer to Figure 5 A modification of the first embodiment will be described.

[0070] Figure 5 FIG. 1 is a diagram showing the structure of a driving device 100 according to a modified example of the first embodiment. Figure 5 In addition to Figure 1 In addition to the configuration shown, a self-diagnosis control unit 40 for instructing self-diagnosis of the plurality of characteristic sensors 2a to 2f is provided.

[0071] The modification of the first embodiment is a driving device 100 that can detect the amount of the variation through self-diagnosis and diagnose a sign of failure of the characteristic sensors 2a to 2f themselves when the accuracy of the detection values ​​of the characteristic sensors 2a to 2f varies over time.

[0072] For example, in Figure 5The driving device 100 of the structure shown in the figure further includes a self-diagnosis control unit 40 for sending a signal for instructing the performance of self-diagnosis to the characteristic sensors 2a to 2f. The self-diagnosis control unit 40 is equipped with a circuit for generating a reference signal 41 having a predetermined voltage, current or frequency for use periodically or in the self-diagnosis of the characteristic sensors 2a to 2f. The reference signal 41 is output to each characteristic sensor 2a to 2f to diagnose the characteristic detection accuracy of each characteristic sensor 2a to 2f. The reference signal 41 is activated only when the self-diagnosis of the characteristic sensors 2a to 2f is performed, and stops in the case other than the self-diagnosis.

[0073] It is also possible to store the errors of the characteristic sensors 2a to 2f obtained by self-diagnosis in the sensing result storage unit 3 in advance, similarly to the characteristics of the power devices 1a to 1f, and perform a control method by adding the error amount of the characteristic sensors 2a to 2f to the characteristic sensing results of the power devices 1a to 1f. Alternatively, in the case where the errors of the characteristic sensors 2a to 2f show a tendency to change over time, similarly to the case of the power devices 1a to 1f, a fault sign can be detected by a threshold value, and a fault signal can be sent to the corresponding device. Figure 1 The display device 31 shown also issues an alarm to notify replacement of components.

[0074] Since the reference signal for self-diagnosis is output only during self-diagnosis, the activation rate of the reference signal is suppressed to be lower than that of other circuits or devices in the driving device 100. Therefore, the characteristic variation of the reference signal itself can be ignored for other circuits or devices.

[0075] As described above, according to the first embodiment, it is possible to diagnose the fault signs of the mounted power devices 1a to 1f, collect and optimize the data of the drive device 100 existing in the market, optimize the diagnostic threshold of the fault sign, and thus realize the drive device 100 that can reduce the frequency of component replacement. In addition, it is possible to reduce the frequency of component replacement, reduce the number of component replacements, and also reduce costs.

[0076] That is, according to the first embodiment of the present invention, a drive device 100 capable of diagnosing fault signs can be realized, which diagnoses the fault signs of power devices 1a~1f, limits the operation of power devices 1a~1f with fault signs, or eliminates the power devices 1a~1f to perform load drive control, thereby suppressing the shortening of the replacement cycle of power devices 1a~1f.

[0077] (Example 2) Next, Example 2 of the present invention will be described.

[0078] In Example 2 of the present invention, a plurality of characteristic sensors 2a to 2f respectively arranged corresponding to the power devices 1a to 1f are used to measure the characteristics related to the plurality of power devices 1a to 1f mounted in the drive device 100, and the stress amount represented by the product of the measurement result and the measurement time interval is accumulated as time series data, and it is determined based on the accumulated stress amount whether the remaining life of each power device 1a to 1f is lower than a specified threshold.

[0079] Thus, the drive device 100 can reduce the frequency of component replacement of the drive device 100 or the power devices 1a~1f by detecting the signs of failure of each power device 1a~1f and changing the control of the drive device 100 according to the detection status, and can issue an alarm to prompt the user to replace components when the remaining life of each power device 1a~1f further changes. The drive device 100 is described.

[0080] In the second embodiment, thermal stress is described as an example of stress amount, and the thermal stress is represented by the product of the temperature measured by the characteristic sensors 2a to 2f and the measurement time interval.

[0081] Figure 6 It is a diagram showing a driving device 100 according to a second embodiment of the present invention. Figure 1 The difference between the structure of the driving device 100 in the embodiment 1 of the present invention shown and the driving device 100 in the embodiment 2 is that a stress diagnosis unit 5 is provided instead of the characteristic change diagnosis unit 4 of the embodiment 1. The stress diagnosis unit 5 is used to calculate the accumulated stress on the power devices 1a~1f based on the accumulated value of the characteristics of the power devices 1a~1f obtained by the characteristic sensors 2a~2f and stored in the sensing result storage unit 3, and determine the remaining life.

[0082] An example of a method of performing stress diagnosis based on the accumulated stress of the power devices 1 a to 1 f will be described.

[0083] Figure 7 Schematically shows the relationship between the cumulative stress applied to the power devices 1 a to 1 f and the remaining life of the power devices 1 a to 1 f. Figure 7 The intercept of the vertical axis represents the remaining life when the drive device 100 starts to operate, and the intercept of the horizontal axis represents the accumulated stress at the time when the remaining life ends, that is, when the power devices 1a to 1f fail.

[0084] Typically, before the drive device 100 starts operating, reliability tests and durability tests are carried out during the development phase of the semiconductor elements that constitute the power devices 1a to 1f. Based on the test results, the life prediction of the power devices 1a to 1f is estimated, and the above-mentioned vertical axis intercept, horizontal axis intercept, and line segments connecting these intercepts are determined.

[0085] When the driving device 100 just starts to operate, the accumulated thermal stress of the power devices 1a to 1f can be regarded as zero, and the remaining life of the power devices 1a to 1f at this time is substantially equal to the initial state (initial life).

[0086] The temperature of the drive device 100 during operation is sensed by the characteristic sensors 2a to 2f for each of the power devices 1a to 1f, and the product of the temperature with time is accumulated in the sensing result storage unit 3 as thermal stress.

[0087] In the stress diagnosis unit 5, the numerical information is stored Figure 7 The relationship between the accumulated amount of thermal stress and the remaining life is shown, and the remaining life of each power device 1a to 1f is calculated based on the amount of thermal stress recorded in the sensing result storage unit 3. At this time, the two thresholds, the control threshold CTHS and the alarm threshold ATHS, are compared with the remaining life, and the following actions are performed when the remaining life is lower than the respective thresholds.

[0088] Figure 8 1 is a diagram showing a method of correcting the remaining lifetime prediction model of the power devices 1 a to 1 f.

[0089] Figure 8 The dotted line shown in (a) is a remaining life model determined based on the results of the above-mentioned reliability test and durability test.

[0090] Figure 8 The waveform shown in (b) is a frequency distribution obtained by accumulating the amount of thermal stress at the time when the power devices 1a to 1f are actually used until they fail, for example, in a plurality of drive devices 100 sold on the market.

[0091] When the initial remaining life prediction model is matched to the stress at the time of actual failure, the remaining life prediction model and the actual failure time may not be consistent. Therefore, the life prediction model is corrected based on the accumulated data. Specifically, the probability of actual failure is the highest for thermal stress.

[0092] That is, the life prediction model is corrected in such a way that the accumulated stress with the maximum actual number of failures becomes the new intercept on the horizontal axis. Figure 8 In the figure, the solid line represents the revised remaining life prediction model.

[0093] In addition, for the drive device 100 collected and replaced from the market, it can also be operated until the power devices 1a~1f actually fail, and data related to the relationship between the accumulated thermal stress and the remaining life of the power devices 1a~1f can be collected. In this case, it can be considered that it can help improve the accuracy of life prediction.

[0094] Next, a method is described for setting a control change threshold CTHS and an alarm threshold ATHS for the remaining life that decreases as the cumulative stress increases, and outputting a control change signal 20 for changing the control of the drive device 100 and a component replacement alarm 30 when the remaining life falls below the respective thresholds. Fig. 9 This is a flowchart of a method of outputting the control change signal 20 and the component replacement alarm 30 for changing the control of the drive device 100 .

[0095] First, after the determination flow is started in step S310 , in step S320 , the stress diagnosis unit 5 reads the cumulative stress value of each of the power devices 1 a to 1 f held in the sensing result holding unit 3 .

[0096] In step S330 , the remaining life corresponding to the read cumulative stress value is compared with a control threshold value CTHS.

[0097] When the remaining lifetime is less than the control threshold value CTHS, the process proceeds to step S340, and the control change signal 20 is output.

[0098] In step S330 , if the remaining life is greater than the control threshold CTHS, the process proceeds to step S350 to compare the remaining life with the alarm threshold ATHS. If the remaining life is less than the alarm threshold ATHS, the process proceeds to step S360 to output the alarm signal 30 .

[0099] Next, in step S350, when the remaining life is equal to or greater than the alarm threshold value ATHS, the process proceeds to step S370 and the flowchart ends.

[0100] The accumulation rate of thermal stress, i.e. Figure 8 The speed of the lateral direction of the middle part varies depending on the method of applying thermal stress. For example, even if two usage methods are assumed to have the same operating time, the amount of accumulated stress under each usage method is different when the ambient temperature is different.

[0101] Based on this, in order to judge the remaining life according to the accumulated stress and then perform replacement in real time, information related to the usage of the drive device 100 is used. This information is not only stored in the drive device 100, but can also be sent and managed by an external server through wireless communication, etc.

[0102] For example, by operating in the market, data related to the correspondence between the accumulated thermal stress and the remaining life of the power devices 1a to 1f in the drive device 100 are accumulated. Based on these data, the device life prediction model determined in the early stage based on the reliability test and the durability test is corrected, and the life prediction under conditions closer to the actual working conditions can be performed, which can improve the life prediction accuracy of the drive device 100. In addition, the control threshold CTHS and the alarm threshold ATHS are also reset by reading back and can be the optimal value.

[0103] The control change and alarm output based on the remaining life described in the second embodiment can be used in conjunction with the method based on the characteristic change described in the first embodiment, and issued at an earlier arrival time, or a signal can be output when the conditions of both methods are met.

[0104] Next, the content of the control change of the drive device 100 when the remaining life of the power devices 1a to 1f decreases and is determined as a sign of failure in the second embodiment is described. The idea and content of the control change are the same as those of the first embodiment of the present invention, and further detailed description is omitted due to repetition. The difference from the first embodiment of the present invention is that the basis for the diagnosis of the sign of failure is whether it is caused by the change in the time-dependent characteristics of the power devices 1a to 1f, or the reduction in the remaining life of the power devices 1a to 1f caused by the accumulated stress.

[0105] Next, use Fig.10 This paper describes a method for calculating the rate of increase of the accumulated thermal stress value, comparing it with the life prediction model and the remaining life, predicting the time when an alarm will occur, and notifying the user.

[0106] Fig.10 The drive device 100 is also provided with an operation history monitor 50 for inputting the operation information of the drive device 100 to the stress diagnosis unit 5 of the drive device 100. Examples of the input operation information to the drive device 100 include the operation time per unit time, control conditions, temperature changes, etc. If the purpose of the operation history monitor 50 is explained by way of example, it is to calculate the stress increase per unit time. Based on the relationship between the stress increase per unit time and the remaining life, the actual failure time can be predicted.

[0107] Similarly, the period when the remaining life reaches the control threshold CTHA or the alarm threshold ATHS can also be predicted. By sending these periods to the outside of the drive device 100, for example, the drive device 100 has Figure 1 The display device 31 shown can visually inform the user.

[0108] That is, the convenience is improved in that the user can know the approximate time before an alarm or a failure occurs.

[0109] According to the above, in Example 2 of the present invention, multiple characteristic sensors 2a~2f respectively configured corresponding to each power device 1a~1f are used to measure various characteristics related to the multiple power devices 1a~1f mounted in the drive device 100, and the stress amount represented by the product of the measurement result and the measurement time interval is accumulated as time series data, and it is determined based on the accumulated stress amount whether the remaining life of each power device 1a~1f is lower than a specified threshold.

[0110] In this way, it is possible to detect the signs of failure of each power device 1a~1f, change the control of the drive device 100 according to the detection status, thereby reducing the frequency of component replacement of the drive device 100 or the power devices 1a~1f, and when the remaining life of each power device 1a~1f further changes, the drive device 100 can issue an alarm to prompt the user to replace the components.

[0111] (Example 3) Next, Example 3 of the present invention will be described.

[0112] In embodiment 3 of the present invention, a vehicle equipped with a drive device 100 is described, which performs fault prediction detection on power devices 1a~1f mounted on the drive device 100 based on detection of characteristic changes, or calculates the remaining life of the power devices by calculating the cumulative stress, issues a notification of component replacement at an appropriate time, and can reduce the frequency of component replacement.

[0113] Fig.11 The structure of a vehicle 300 according to a third embodiment of the present invention is shown.

[0114] exist Fig.11 In the embodiment, the vehicle 300 includes a driving device 100, a motor 200, a wireless communication module 6, an antenna 7, and a display device 8. The driving device 100 may be the device described in the first embodiment or the device described in the second embodiment.

[0115] The wireless communication module 6 and the antenna 7 are responsible for controlling wireless communication between the drive device 100 and a server (not shown) disposed outside the vehicle 300. The server is equipped with a module for machine learning, which recursively performs calculations based on data sent from the drive device 100 and calculates data for resending to the drive device 100.

[0116] According to this specification, the data sent from the drive device 100 to the server may include, for example, control thresholds CTH1, CTH2 or CTHS, alarm thresholds ATH1, ATH2 or ATHS, accumulated thermal stress data of power devices 1a~1f reaching the actual failure moment, corrected characteristics accumulated in a time series in the sensing result retention unit 3 of the drive device 100, or statistical data related to the driving of the vehicle 300, etc.

[0117] Furthermore, the target of the server communication is not limited to a single drive device 100 , and may include drive devices 100 mounted on a plurality of other vehicles 300 operating in the same manner on the market.

[0118] The data sent from the server to the drive device 100 may include control thresholds CTH1, CTH2 or CTHS, alarm thresholds ATH1, ATH2 or ATHS, life prediction models of the power devices 1a to 1f, etc., which are recalculated based on the data sent from the drive device 100.

[0119] The characteristic change diagnosis unit 4 in Example 1 and the stress diagnosis unit 5 in Example 2 refer to the control threshold CTH1, CTH2 or CTHS, the alarm threshold ATH1, ATH2 or ATHS, and the life prediction model of the power devices 1a~1f received from the server, and correct the control threshold range and the remaining life.

[0120] By adopting this configuration, the thresholds and judgment criteria for content diagnosis and control described in Embodiments 1 and 2 of the present invention can be corrected and optimized based on the massive data on the market.

[0121] In addition, in the machine learning module in the server, for example, the working environment can be estimated based on the data obtained from the drive device 100, and the recalculated result corresponding to the working environment can be sent to the drive device 100 based on the data of other vehicles 300 working in a similar environment. In this way, the accuracy of the control change threshold CTH1, CTH2 or CTHS, the alarm threshold ATH1, ATH2 or ATHS, and the life prediction model of the drive device 100 in a similar working environment can be improved.

[0122] Next, the timing of executing the diagnosis in the drive device 100 mounted on the vehicle 300 will be described.

[0123] The characteristic acquisition timing described in the first and second embodiments is the timing when the driving device 100 is operating, and the acquired characteristic value needs to be corrected according to the operating conditions.

[0124] In Example 3, Fig.12 and Fig.131 and 2. In the flowchart, a procedure for performing delay diagnosis in an initial state after the system of the vehicle 300 is started and before the drive device 100 starts to operate is shown and described.

[0125] Fig.12 The figure shows a delayed diagnosis flow for detecting the presence or absence of characteristic variation of the power devices 1a to 1f mounted on the drive device 100 as a sign of failure after the system of the vehicle 300 is started and before the drive device 100 starts operating.

[0126] Likewise, Fig.13 This is a diagram showing a delay diagnosis flow for outputting a change in characteristics as an alarm for component replacement.

[0127] exist Fig.12 In the process, after the flow starts in step S410, the system of the vehicle 300 is started in step S420. Next, in step S430, the characteristics of each of the power devices 1a to 1f mounted on the drive device 100 are measured.

[0128] Afterwards, steps S440, S450 and S460 are the same as steps S130, S140 and S150 described in Example 1 ( Figure 3 ) are the same, and detailed description is omitted.

[0129] The characteristics of the power devices 1 a to 1 f mounted on the drive device 100 are measured, and a diagnosis of characteristic variation is performed in steps S440 and S450 to detect the presence or absence of a sign of a failure.

[0130] The delay diagnosis is completed before step S460, and in step S470, the drive device 100 starts the operation of load driving, etc. Then, the same diagnosis as that shown in the first embodiment is performed periodically or at a specific time.

[0131] By implementing delayed diagnosis, the drive device 100 can perform diagnosis under more diverse conditions before and after work starts, and send the diagnosis results to the server, thereby improving the accuracy of machine learning and further improving the accuracy of the diagnostic threshold and life prediction model fed back from the server.

[0132] As described above, according to Example 3, a vehicle equipped with a drive device 100 can be realized, which can detect the signs of failure of power devices 1a~1f mounted on the drive device 100 based on the detection of characteristic changes, or calculate the remaining life of power devices 1a~1f by calculating the cumulative stress, and can issue a notification of component replacement at an appropriate time, and can reduce the frequency of component replacement.

[0133] exist Fig.113 shows a case where the present invention is applied to a vehicle 300, but the present invention can also be applied to other than vehicles, such as aerial transportation means.

[0134] The present invention is not limited to the above-mentioned embodiments 1, 2 and 3, and includes various modifications. For example, the above-mentioned embodiments 1, 2 and 3 are described in detail to explain the present invention in an easy-to-understand manner, and are not necessarily limited to having all the described configurations. Furthermore, a part of the configuration of a certain embodiment may be replaced with the configuration of another embodiment, and the configuration of another embodiment may be added to the configuration of a certain embodiment. Furthermore, part of the configuration of each of Embodiments 1, 2, and 3 may be added, deleted, or replaced with another configuration.

[0135] In addition, the control lines and signal lines indicate the lines that are considered necessary for the description, and not all the control lines and signal lines are necessarily indicated on the product.

[0136] In addition, the characteristic change diagnosis unit 4 in the first embodiment and the stress diagnosis unit 5 in the second embodiment may be collectively referred to as a control change signal output unit. Explanation of symbols

[0137] 1a, 1b, 1c, 1d, 1e, 1f…power device, 2a, 2b, 2c, 2d, 2e, 2f…characteristic sensor, 3…sensing result holding unit, 4…characteristic change diagnosis unit (control signal change unit), 5…stress diagnosis unit (control signal change unit), 6…wireless communication module, 7…antenna, 8, 31…display device, 10…drive control unit, 20…control change signal, 30…alarm signal, 40…self-diagnosis control unit, 41…reference signal, 50…work history monitor, 100…drive device, 200…motor, 300…vehicle, CTH1, CTH2, CTHS…control threshold, ATH1, ATH2, ATHS…alarm threshold.

Claims

1. A driving device capable of diagnosing a fault sign, characterized in that: have: A plurality of power devices for driving a load; a characteristic sensor, used for detecting the characteristics of each of the plurality of power devices; a sensing result holding unit, configured to hold detection results of the characteristic sensor on the plurality of power devices in time series; a control signal changing unit that detects a failure sign of each of the plurality of power devices based on the detection result held in time series by the sensing result holding unit and outputs a control change signal; as well as a drive control unit that controls the driving of the plurality of power devices, The control signal changing unit detects the fault signs of the multiple power devices based on a control threshold value, and when the fault signs of more than one power device among the multiple power devices are detected, outputs a control change signal to the drive control unit in a manner that the load is driven by the power devices other than the power device for which the fault signs are detected.

2. The driving device according to claim 1, characterized in that: The control signal changing unit is a characteristic change diagnosing unit, which calculates the characteristic change amount of each of the multiple power devices based on the detection results maintained in a time series by the sensing result maintaining unit, and determines whether the characteristic change amount reaches outside the control threshold range determined by the control threshold to detect the fault signs of the multiple power devices.

3. The driving device according to claim 2, characterized in that: The characteristic change diagnosis unit determines whether the characteristic change amount is outside an alarm threshold range wider than the control threshold range determined by the control threshold, and outputs an alarm signal for warning when the characteristic change amount is outside the alarm threshold range.

4. The driving device according to claim 1, characterized in that: The control signal changing unit is a stress diagnosis unit, which calculates the remaining life as the characteristic variation amount of each of the multiple power devices based on the stress amount represented by the product of the detection result maintained in time series by the sensing result maintaining unit and the measurement time interval, and determines whether the remaining life of the multiple power devices is lower than the control threshold value to detect a fault sign.

5. The driving device according to claim 4, characterized in that: The stress diagnosis unit determines whether the remaining life has reached an alarm threshold value shorter than the control threshold value, and outputs an alarm signal for warning when the remaining life is shorter than the alarm threshold value.

6. The driving device according to claim 4, characterized in that: By referring to the failure data of other drive devices stored in the server of the destination communicated by wireless communication, A calculation method capable of correcting the remaining life of the power device.

7. The driving device according to claim 2, characterized in that: A self-diagnosis control unit is further provided for transmitting a reference signal for diagnosing the operation of the characteristic sensor to the characteristic sensor.

8. A vehicle, characterized in that: have: A drive device corresponding to any one of claims 1 to 7.

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