Drive system capable of predictive fault diagnosis
The drive system predicts power device failures in automotive components by monitoring characteristics and adjusting operation, extending lifespan and reducing replacement frequency and costs in autonomous driving scenarios.
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Patents
- Current Assignee / Owner
- ASTEMO LTD
- Filing Date
- 2022-10-14
- Publication Date
- 2026-07-22
Smart Images
Figure 0007893885000001 
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Abstract
Description
Technical Field
[0001] The present invention relates to a drive device including an inverter for driving a load such as a motor.
Background Art
[0002] For automotive semiconductor components, generally, a stricter reliability is required than for consumer products, and each semiconductor supplier mass-produces after ensuring reliability for automotive use.
[0003] For example, it is guaranteed that the automobile can be used for 10 years or driven for 200,000 kilometers. These guarantees include the unique ideas of each automobile manufacturer and assume that the operating time of the semiconductor components per day is several hours.
[0004] In the automotive industry, the development of autonomous driving technology and advanced driver assistance technology is actively underway. When the autonomous driving level 4 or higher is commercialized, it is expected that the operation by the driver will be unnecessary and all operations such as driving will be performed by the system mounted on the vehicle.
[0005] In addition to technology development, in terms of services, it is considered that car sharing will be further applied in the future, and an operation mode in which a single automobile is shared by multiple users to effectively utilize the idle time of the automobile will also become popular in the future.
[0006] In the above-described situation, in order to improve the reliability of semiconductor components, technologies for predicting the life and failure time of semiconductor components have been developed.
[0007] Patent Document 1 describes a technique in which the difference between the previous measurement value and the current measurement value of a sensor attached to a power converter is calculated, intermediate data is obtained by varying a plurality of past differences, and the damage level of the power converter is calculated based on the intermediate data. In the technique described in Patent Document 1, when the damage level exceeds the damage threshold, a warning signal indicating that the failure time is approaching is output.
[0008] Patent Document 2 describes a technique for determining fault indicators based on the acquired current value when it is determined that a power converter has reached a specific operating state. [Prior art documents] [Patent Documents]
[0009] [Patent Document 1] Japanese Patent Publication No. 2020-141465 [Patent Document 2] Patent No. 6184335 [Overview of the project] [Problems that the invention aims to solve]
[0010] As mentioned earlier, current reliability considerations for automotive semiconductor components include the assumption of daily operating hours. This stems from the fact that humans operate the vehicles as drivers. In the future, when car sharing and fully autonomous driving become practical, it is expected that operating hours will approach 24 hours a day, especially in extreme cases such as automated delivery.
[0011] In such cases, the lifespan of semiconductor components, i.e., the time it takes for them to fail, will be considerably shorter than it is currently, and it is possible that it could be as short as one or two years.
[0012] Even current automotive semiconductor components are designed to withstand use such as the aforementioned 10-year, 200,000-kilometer driving scenario, but providing reliability guarantees for 24-hour operation as described above is not realistic in terms of both feasibility and cost.
[0013] Furthermore, in autonomous driving, a failure of a component can be fatal, so it is desirable to be able to detect failures before they occur.
[0014] As described above, in an era where autonomous driving and car sharing are expected to become widespread, maintaining performance through parts replacement can be considered as one option for operating a vehicle. On the other hand, parts replacement will add to the cost.
[0015] Therefore, the challenge may be to either reduce the frequency of replacements to lower the cost of parts replacement, or to lower the cost of the replacement parts themselves.
[0016] However, as car-sharing services become more widespread and autonomous driving becomes practical, the daily operating time of semiconductor components will increase, leading to faster degradation of power devices and shorter replacement cycles. Therefore, it is necessary not only to predict failures early but also to consider control conditions to slow down the progression of degradation and suppress the shortening of replacement cycles.
[0017] The objective of the present invention is to realize a drive device capable of predicting power device failures by diagnosing signs of failure, restricting the operation of power devices that are predicted to fail or excluding them from load drive control, and thereby suppressing the shortening of the power device replacement cycle. [Means for solving the problem]
[0018] To achieve the above objective, the present invention is configured as follows.
[0019] A drive system capable of predicting failures includes: 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 sense result holding unit for storing the detection results of the plurality of power devices by the characteristic sensor in a time series; a control signal changing unit that detects signs of failure in each of the plurality of power devices from the detection results stored in a time series by the sense result holding unit and outputs a control change signal; and a drive control unit that controls the driving of the plurality of power devices. A self-diagnostic control unit transmits a reference signal to the characteristic sensor for diagnosing the operation of the characteristic sensor,comprising, the control signal changing unit detects a sign of failure of the plurality of power devices based on a control threshold, and when detecting the sign of failure of one or more power devices among the plurality of power devices, outputs a control change signal to the drive control unit so as to drive the load with the power devices other than the power device in which the sign of failure is detected The system then calculates the characteristic variation amount for each of the multiple power devices from the detection results stored chronologically in the sense result holding unit, and detects a failure indication for the multiple power devices by determining whether the characteristic variation amount has reached outside the control threshold range defined by the control threshold. Furthermore, the drive device capable of predicting failures includes a plurality of power devices for driving a load, and characteristic sensors for detecting the characteristics of each of the plurality of power devices. A sense result holding unit for storing the detection results of the plurality of power devices by the characteristic sensor in a time series; a control signal modification unit for detecting signs of failure in each of the plurality of power devices from the detection results stored in a time series by the sense result holding unit and outputting a control change signal; and a drive control unit for controlling the driving of the plurality of power devices. The control signal modification unit detects signs of failure in the plurality of power devices based on a control threshold, and if it detects signs of failure in one or more of the plurality of power devices, it outputs a control modification signal to the drive control unit to drive the load with the remaining power devices excluding the power device in which the signs of failure were detected. The sense result holding unit calculates the remaining lifespan, which is the characteristic variation amount of each of the plurality of power devices, from the stress amount, which is expressed as the product of the detection result and the measurement time interval, and determines whether the remaining lifespan of the plurality of power devices is below the control threshold to detect signs of failure. The drive device can modify the calculation method of the remaining lifespan of the power devices by referring to failure data of other drive devices stored in a server to which communication has been made via wireless communication.
Advantages of the Invention
[0020] According to the present invention, it is possible to realize a drive device capable of diagnosing a sign of failure of a power device, restricting the operation of the power device in which a failure is predicted or excluding the power device, performing load drive control, and suppressing shortening of the replacement cycle of the power device
Brief Description of the Drawings
[0021] [Figure 1] It is a diagram showing an example of the configuration of a drive device according to Embodiment 1 [Figure 2] It is a graph showing an example of variation in characteristics of a power device [Figure 3] It is a flowchart of detection of a sign of failure and output of a control change signal in Embodiment 1 [Figure 4] It is a flowchart of detection of a sign of failure and output of an alarm signal in Embodiment 1 [Figure 5] It is a diagram showing a drive device for performing diagnosis on a characteristic sensor according to a modification of Embodiment 1 [Figure 6] It is a diagram showing an example of the configuration of a drive device according to Embodiment 2 [Figure 7] It is a diagram showing an example of a method for detecting a sign of failure according to Embodiment 2 [Figure 8] It is a diagram showing an example of a method for modifying a life prediction model [Figure 9]This flowchart shows how to output control change signals and alarm signals based on remaining lifespan. [Figure 10] This diagram shows a configuration for notifying remaining lifespan as real time based on operating history. [Figure 11] This figure shows an example of the vehicle configuration according to Example 3. [Figure 12] This is a flowchart of the latency diagnostic method according to Example 3. [Figure 13] This is a flowchart of the latency diagnostic method according to Example 3. [Modes for carrying out the invention]
[0022] Hereinafter, embodiments for carrying out the present invention will be described with reference to the attached drawings.
[0023] In the embodiment described below, it becomes possible to accurately detect deviations from the initial characteristics of a functional part included in a semiconductor component mounted in a vehicle, determine that a large deviation in characteristics indicates a potential failure, and issue an alarm in the form of a notification to replace the part. Furthermore, by incorporating a mechanism to correct the functional part, the period until part replacement can be extended even further, and costs can be reduced by reducing the number of replacements. [Examples]
[0024] (Example 1) Figure 1 shows the configuration of a drive unit 100 according to Embodiment 1 of the present invention. In Figure 1, various characteristics of multiple power devices 1a to 1f mounted on the drive unit 100 are measured by multiple characteristic sensors 2a to 2f, each of which is positioned to correspond to each power device 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 or not there are signs of the characteristics of each power device 1a to 1f changing over time. This allows for the detection of signs of failure in each power device 1a to 1f, and by changing the control of the drive unit 100 according to the detection status, the frequency of replacement of parts in the drive unit 100 or power devices 1a to 1f is reduced. Furthermore, if the characteristics of each power device 1a to 1f change further than at the time when signs of failure were detected, an alarm is issued to prompt the user to replace the parts.
[0026] The drive device 100 according to Embodiment 1 of the present invention is used to drive a motor 200, which is shown as an example load. It converts a DC power supply into a three-phase AC signal and drives it using vector control to convert it into rotational force. Since the control method for driving the motor 200, which is the load, is already widely known, details are omitted in this specification.
[0027] The drive device 100 according to Embodiment 1 of the present invention comprises a plurality of power devices 1a to 1f, a drive control unit 10 that transmits signals to each power device 1a to 1f for controlling the electrical operation of the plurality of power devices 1a to 1f, a plurality of characteristic sensors 2a to 2f arranged in correspondence with each power device 1a to 1f for the purpose of sensing (detecting) the characteristics of each power device 1a to 1f, and a sense result holding unit (detection result holding unit) 3 that periodically or at predetermined timings acquires the characteristics of the power devices 1a to 1f sensed by the characteristic sensors 2a to 2f and holds the detection results as time-series data.
[0028] Furthermore, the drive unit 100 includes a characteristic change diagnosis unit 4 that refers to time-series data of the characteristics of power devices 1a to 1f held in the sense result holding unit 3, diagnoses that the characteristics of power devices 1a to 1f are changing over time, transmits a control change signal 20 to the drive control unit 10, and outputs an alarm signal 30.
[0029] Here, the power devices 1a to 1f and the characteristic sensors 2a to 2f are described using a combination of numbers and lowercase English letters. In this specification, power devices 1a to 1f and characteristic sensors 2a to 2f that share the same lowercase English letter at the end are defined as corresponding to each other when acquiring characteristics. For example, in this specification, the characteristic sensor 2a monitors the characteristics of power device 1a.
[0030] The characteristics of power devices 1a to 1f monitored by characteristic sensors 2a to 2f include electrical characteristics such as voltage, current, and frequency, and environmental characteristics such as temperature (temperature near power devices 1a to 1f), but other characteristics can also be mentioned.
[0031] Alternatively, the rate of change over time of voltage, current, frequency, and temperature may be calculated by intermittently measuring them over a certain period, and these results may be stored in the sense result holding unit 3, similar to the characteristics of each power device 1a to 1f. Furthermore, the characteristic acquisition by characteristic sensors 2a to 2f may selectively perform on all or some of the characteristics mentioned above.
[0032] The characteristics of power devices 1a to 1f can vary depending on operating conditions such as power supply voltage, temperature, load drive control content, and phase information in drive control. Therefore, it is desirable to correct the characteristics of each power device 1a to 1f monitored by characteristic monitors 2a to 2f based on the aforementioned operating conditions, and in this invention, the corrected characteristics of each power device 1a to 1f are referred to as corrected characteristics.
[0033] The corrected characteristics preferably reflect the pure characteristics of the power devices 1a to 1f, with the aforementioned fluctuations due to operating conditions eliminated. For example, the error rate from the expected value of the characteristics of the power devices 1a to 1f in the operating condition at the time the characteristics are monitored is preferred, but values calculated by other methods may also be used.
[0034] This section describes an example of a method for diagnosing characteristic variations in power devices 1a to 1f.
[0035] Figure 2 plots the corrected characteristic values for one of the power devices 1a to 1f, with time on the vertical axis and time on the horizontal axis.
[0036] In Figure 2, each data point arranged horizontally corresponds to the corrected characteristics that are stored in a time series. Two thresholds are provided for diagnosing characteristic fluctuations. The first is the control threshold CTH1 and CTH2, which detect changes in the corrected characteristics over time and provide feedback to the control content of the drive unit 100. The second threshold is the alarm threshold ATH1 and ATH2, which output a warning alarm to inform the user that the drive unit 100 needs to be replaced if the characteristic fluctuations progress further.
[0037] In this embodiment 1, the control threshold CTH1 and alarm threshold ATH1 are thresholds for detecting when the corrected characteristics increase, and the control threshold CTH2 and alarm threshold ATH2 are thresholds for detecting when the corrected characteristics decrease.
[0038] The characteristic variation diagnostic unit 4 reads the time-series data of the corrected characteristics of each power device 1a to 1f held in the sense result holding unit 3, calculates the amount of characteristic variation using statistical methods or machine learning, and determines whether the corrected characteristics of each power device 1a to 1f sensed (detected) by the characteristic sensors 2a to 2f are within the range of the aforementioned control threshold or alarm threshold, thereby detecting signs of failure.
[0039] The control threshold range is defined as the range between control threshold CTH1 and control threshold CTH2, and the alarm threshold range is defined as the range between control threshold CTH1 and alarm threshold ATH1 and control threshold CTH2 and alarm threshold ATH2. The alarm threshold range is wider than the control threshold range.
[0040] Figure 3 shows an example flowchart of a method for determining the characteristic variations of each power device 1a to 1f based on the corrected characteristics and outputting a control change signal to the drive control unit 10.
[0041] The flowchart in Figure 3 is shown for one of the power devices 1a to 1f, but it can also be applied to other power devices mounted on the drive unit 100.
[0042] First, after the judgment flow is started in step S110, in step S120 the characteristic variation diagnosis unit 4 reads the last recorded data from the time-series data of the corrected characteristics of each power device 1a to 1f held in the sense result holding unit 3. In step S130, a comparison is performed between this data, i.e., the latest corrected characteristic value of the characteristics of power devices 1a to 1f, and the control threshold CTH1 or control threshold CTH2. If 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, if the value of the corrected characteristic is less than or equal to the control threshold CTH1 and greater than or equal to the control threshold CTH2, the process proceeds to step S160 and the flowchart ends.
[0043] In step S140, the corrected characteristic data for the past N times (where N is a natural number) starting from the most recent data is referenced, and it is determined whether all of the past N data exceeded the control threshold CTH1 or whether all of them were below the control threshold CTH2 (i.e., the characteristic fluctuation amount reached outside the control threshold range). If it is determined that the characteristic fluctuation amount reached outside the control threshold range, it is determined that the characteristics of power devices 1a to 1f have changed, and a fault precursor is detected.
[0044] If a fault indicator is detected in step S140, the process proceeds to step S150, where a control change signal 20 is output, which is a signal for diagnosing characteristic fluctuations and changing the control method of the drive unit 100.
[0045] In step S140, if there is data from the past N data points that is less than or equal to the control threshold CTH1 or less than the control threshold CTH2, the process proceeds to step S160 and the flowchart ends.
[0046] In the example shown in Figure 3, characteristic variation is determined when all corrected characteristic data exceeds the control threshold CTH1 for N consecutive times, or when all data falls below the control threshold CTH2. However, a determination method that combines the number of consecutive occurrences and the occurrence pattern, optimized using machine learning, is also acceptable.
[0047] The determination method can be rewritten externally after the drive unit 100 starts operating.
[0048] The method for determining characteristic fluctuations of each power device 1a to 1f has been described above. If the corrected characteristics of each power device 1a to 1f change further due to the elapsed operating time of the drive unit 100, a determination is made to output an alarm signal 30.
[0049] Figure 4 is a flowchart illustrating a method for determining the characteristic variations of each power device 1a to 1f based on the corrected characteristics and outputting an alarm signal 30.
[0050] The difference between the flowchart shown in Figure 3 and the flowchart shown in Figure 4 is that the thresholds in steps S230 (corresponding to step S130 in Figure 3) and S240 (corresponding to step S140 in Figure 3) in Figure 4 are alarm threshold ATH1 and alarm threshold ATH2, and the signal output in step S250 (corresponding to step S150 in Figure 3) is alarm signal 30.
[0051] The operation explanation in the flowchart of Figure 4 can be obtained by replacing the control threshold CTH1 with the alarm threshold ATH1, the control threshold CTH2 with the alarm threshold ATH2, and the control change signal 20 with the alarm control signal 30 in the operation explanation in the flowchart of Figure 3.
[0052] The alarm signal 30 is output to a display device 31 installed outside the drive unit 100, and a warning is displayed on the display device 31.
[0053] The control thresholds CTH1 and CTH2 and the alarm thresholds ATH1 and ATH2 may be set in advance prior to the operation of the drive unit 100, or they may be set by communicating with an external party, performing machine learning on a server at the communication destination, and reading back the optimized values.
[0054] Furthermore, regarding the criteria for determining when corrected characteristic data appears that crosses control thresholds CTH1 and CTH2 or alarm thresholds ATH1 and ATH2, possible criteria include when it appears a predetermined number of times consecutively, or when it appears a predetermined number of times or more in the most recent N times, regardless of whether it is consecutive or discontinuous.
[0055] Regarding these criteria, they can be set in advance, similar to the threshold settings mentioned earlier, or they can be retrieved later from an external source.
[0056] Furthermore, since the operation of accumulating and saving data chronologically leads to an increase in the amount of data, when making a judgment using the most recent data as described above, it is conceivable to reduce the number of data points by averaging past data that is excluded from the judgment, or by re-recording it as a histogram with values and frequencies. In the sense result holding unit 3 in this embodiment, the data holding method and management method within it can also be appropriately selected.
[0057] The corrected characteristics can be stored in a storage device such as a server at the destination of the information transmitted via wireless communication, and can be used as data for examining machine learning and characteristic variation detection algorithms. In this case, the machine learning results on the server side can be used to optimize the control thresholds and alarm thresholds for characteristic variation diagnosis of power devices 1a to 1f in the drive unit 100 by rewriting the characteristic variation detection thresholds for power devices 1a to 1f via wireless communication, thereby enabling more optimal operation.
[0058] Next, we will explain the changes to the control of the drive unit 100 when power devices 1a to 1f show signs of failure, that is, when it is determined that the characteristics of power devices 1a to 1f show signs of fluctuation over time.
[0059] The characteristic changes of power devices 1a to 1f that occur as a result of the operation of the drive unit 100 are expected to vary among the power devices 1a to 1f, even within the same drive unit 100.
[0060] The usable period of the drive unit 100 as a whole is equal to the usable period of all power devices 1a to 1f. In the present invention, the operating rate of power devices 1a to 1f that show signs of failure is reduced, and the control of the drive unit 100 is modified to relatively slow down the progression of characteristic changes of the power devices that show signs of failure compared to other power devices, thereby extending the usable period of the drive unit 100 as a whole.
[0061] The minimum power devices for each phase of the three-phase AC system, power devices 1a to 1f, are arranged with one on the power supply side (upper arm) and one on the ground side (lower arm).
[0062] In this invention, in order to drive the motor 200 described as a load, two of the three phases must be operating. Therefore, the unit to be excluded from the control of the drive device 100 is the two power devices consisting of an upper arm and a lower arm that are responsible for driving the load.
[0063] If a power device is detected showing signs of failure, the operation of the drive phase handled by that power device is stopped, and the load drive is switched to the remaining two phases. However, it is desirable that the duration of the stoppage be switchable according to the torque required for the motor 200, i.e., the current value required for load drive.
[0064] More specifically, under load conditions where the required torque is relatively small, the drive of the phase to which the power device belongs is stopped so that the stop period of the power device becomes relatively longer.
[0065] If signs of failure are detected in multiple power devices across multiple control phases, the phases excluded from drive control are changed via time-division multiplexing to ensure that the degradation of the multiple power devices progresses evenly.
[0066] By using the drive unit 100 described in this embodiment 1, if a characteristic fluctuation that indicates a failure occurs in the characteristics of the power devices constituting the drive unit 100, this is detected and a control change signal 20 is transmitted to the drive control unit 10 to change the control method of the drive unit 100.
[0067] This makes it possible to extend the period until the alarm signal 30 is output compared to the case where the control method of the drive unit 100 is not changed.
[0068] The user of the drive unit 100 will take action such as replacing parts after recognizing that an alarm signal 30 has been output when a warning is displayed on the display device 31. However, because the period until the output of the alarm signal 30 is extended by the present invention, the time interval for replacing parts is widened, and thus the frequency of replacement can be reduced.
[0069] Next, a modified example of Example 1 will be described with reference to Figure 5.
[0070] Figure 5 shows the configuration of the drive device 100 according to a modified example of Embodiment 1. In Figure 5, in addition to the configuration shown in Figure 1, the drive circuit 100 has a self-diagnosis control unit 40 that instructs self-diagnosis for a plurality of characteristic sensors 2a to 2f.
[0071] A modified version of this embodiment 1 is a drive device 100 that can detect fluctuations in the accuracy of the characteristic sensors 2a to 2f themselves over time through self-diagnosis, and diagnose signs of failure in the characteristic sensors 2a to 2f themselves.
[0072] For example, the drive unit 100 with the configuration shown in Figure 5 further includes a self-diagnosis control unit 40 for transmitting signals to characteristic sensors 2a to 2f to instruct them to perform self-diagnosis. The self-diagnosis control unit 40 is equipped with a circuit that generates a reference signal 41 having a predetermined voltage, current, or frequency for periodic use or for self-diagnosis of 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 aforementioned reference signal 41 is configured to operate only when self-diagnosis is performed on the characteristic sensors 2a to 2f, and stops operating at other times.
[0073] One possible approach is to store the errors of the characteristic sensors 2a to 2f obtained through self-diagnosis in the sense result holding unit 3, similar to the characteristics of the power devices 1a to 1f, and to incorporate the errors of the characteristic sensors 2a to 2f into the characteristic sense results of the power devices 1a to 1f. Alternatively, if the errors of the characteristic sensors 2a to 2f tend to fluctuate over time, a threshold can be used to detect a potential failure, similar to the case of the power devices 1a to 1f, and an alarm can be triggered on a device similar to the display device 31 shown in Figure 1 to notify the user of the need to replace the part.
[0074] Since the self-diagnostic reference signal is output only during self-diagnosis, the activation rate of the reference signal is kept lower than that of other circuits and devices within the drive unit 100. Therefore, characteristic variations of the reference signal itself can be ignored compared to other circuits and devices.
[0075] As described above, according to this embodiment 1, it is possible to diagnose the signs of failure of the power devices 1a to 1f mounted on the device, collect and optimize data from existing drive units 100 on the market, and optimize the diagnostic threshold for signs of failure, thereby realizing a drive unit 100 that can reduce the frequency of parts replacement. Furthermore, by reducing the frequency of parts replacement, the number of parts replacements is reduced, and costs can also be reduced.
[0076] In other words, according to Embodiment 1 of the present invention, it is possible to realize a drive device 100 capable of predicting failures, which can diagnose signs of failure in power devices 1a to 1f, restrict the operation of power devices 1a to 1f that are predicted to fail, or exclude power devices 1a to 1f from load drive control, thereby suppressing the shortening of the replacement cycle of power devices 1a to 1f.
[0077] (Example 2) Next, Example 2 of the present invention will be described.
[0078] In Embodiment 2 of the present invention, various characteristics of a plurality of power devices 1a to 1f mounted on the drive unit 100 are measured by a plurality of characteristic sensors 2a to 2f, each of which is positioned to correspond to each power device 1a to 1f. The stress amount, which is expressed as the product of the measurement result and the measurement time interval, is accumulated as time-series data, and based on the accumulated stress amount, it is determined whether or not the remaining lifespan of each power device 1a to 1f falls below a predetermined threshold.
[0079] This describes a drive unit 100 that can detect signs of failure in each power device 1a to 1f, and by changing the control of the drive unit 100 according to the detected state, it can reduce the frequency of component replacement of the drive unit 100 or power devices 1a to 1f, and can also issue an alarm to prompt the user to replace components if the remaining lifespan of each power device 1a to 1f changes further.
[0080] In this embodiment 2, thermal stress is described as an example of stress amount, and thermal stress is expressed as the product of temperature measured by characteristic sensors 2a to 2f and the measurement time interval.
[0081] Figure 6 shows a drive device 100 according to Embodiment 2 of the present invention. The difference between the drive device 100 in Embodiment 1 of the present invention shown in Figure 1 and the drive device 100 in Embodiment 2 is that, instead of the characteristic fluctuation diagnosis unit 4 in Embodiment 1, there is a stress diagnosis unit 5 that calculates the cumulative stress on the power devices 1a to 1f based on the cumulative values of the characteristics of the power devices 1a to 1f acquired by characteristic sensors 2a to 2f and held in the sense result holding unit 3, and determines the remaining lifespan.
[0082] This section describes an example of a method for conducting a stress diagnosis based on the cumulative stress of power devices 1a to 1f.
[0083] Figure 7 schematically shows the relationship between the cumulative stress applied to power devices 1a to 1f and the remaining lifespan of power devices 1a to 1f. The vertical intercept of Figure 7 represents the remaining lifespan at the start of operation of the drive unit 100, and the horizontal intercept represents the cumulative stress amount at the time when the remaining lifespan is exhausted, i.e., when power devices 1a to 1f fail.
[0084] Typically, before the drive unit 100 starts operation, reliability tests and durability tests are conducted during the development phase of the semiconductor elements that make up the power devices 1a to 1f. Based on the results of these tests, the lifespan of the power devices 1a to 1f is estimated, and the aforementioned vertical and horizontal intercepts, as well as the line segments connecting these intercepts, are determined.
[0085] Immediately after the drive unit 100 starts operating, the cumulative thermal stress of the power devices 1a to 1f can be considered zero, and the remaining lifespan of the power devices 1a to 1f at this time is approximately equal to that of the initial state (initial lifespan).
[0086] The temperature during operation of the drive unit 100 is sensed for each power device 1a to 1f by characteristic sensors 2a to 2f, and the product of this temperature and time is stored as thermal stress in the sense result holding unit 3.
[0087] The stress diagnosis unit 5 stores the relationship between the amount of accumulated thermal stress and the remaining life as numerical information, as shown in Figure 7, and calculates the remaining life of each power device 1a to 1f based on the amount of thermal stress recorded in the sense result holding unit 3. At that time, it compares the remaining life with two types of thresholds, the control threshold CTHS and the alarm threshold ATHS, and performs the following actions if the remaining life falls below the respective thresholds.
[0088] Figure 8 shows a method for correcting the remaining life prediction model for power devices 1a to 1f.
[0089] The dashed line shown in Figure 8(a) represents the remaining life model determined from the results of the reliability and durability tests described above.
[0090] The waveform shown in Figure 8(b) represents the frequency distribution of cumulative thermal stress at the point when power devices 1a to 1f actually failed, for example, multiple drive units 100 available on the market.
[0091] When the initial remaining life prediction model is matched with the stress level at the time of actual failure, the remaining life prediction model and the actual failure timing do not always match. Therefore, the life prediction model is modified based on accumulated data. Specifically, thermal stress has the highest probability of causing actual failure.
[0092] In other words, the lifetime prediction model is modified so that the cumulative stress amount that results in the maximum number of actual failures becomes the new horizontal intercept. In Figure 8, the modified remaining lifetime prediction model is shown as a solid line.
[0093] Furthermore, the drive unit 100 that has been recalled from the market and replaced may be operated until an actual failure occurs in the power devices 1a to 1f, and data on the relationship between the cumulative thermal stress of the power devices 1a to 1f and their remaining lifespan may be collected. In this case, it is thought that this could contribute to improving the accuracy of lifespan prediction.
[0094] Next, we will explain a method for setting a control change threshold CTHS and an alarm threshold ATHS for the remaining lifespan, which decreases with increasing cumulative stress, and outputting a control change signal 20 to change the control of the drive unit 100 and a parts replacement alarm 30 when the remaining lifespan falls below these thresholds. Figure 9 is a flowchart showing a method for outputting a control change signal 20 for changing the control of the drive unit 100 and a parts replacement alarm 30.
[0095] First, in step S310, the judgment flow is initiated, and then in step S320, the stress diagnosis unit 5 reads the cumulative stress values of each power device 1a to 1f held in the sense result holding unit 3.
[0096] In step S330, the remaining lifespan corresponding to the read cumulative stress value is compared with the control threshold CTHS.
[0097] If the remaining lifespan is less than the control threshold CTHS, the process proceeds to step S340 and a 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, where the remaining life is compared with the alarm threshold ATHS. If the remaining life is less than the alarm threshold ATHS, the process proceeds to step S360, where an alarm signal 30 is output.
[0099] Next, in step S350, if the remaining lifespan is greater than or equal to the alarm threshold ATHS, the process proceeds to step S370, and the flowchart ends.
[0100] The rate at which thermal stress accumulates, that is, the rate at which it progresses along the horizontal axis in Figure 8, differs depending on how the thermal stress is applied. For example, even if we consider two usage scenarios with the same operating time, the amount of accumulated stress will differ in each scenario if the ambient temperature is different.
[0101] Based on this, in order to determine the remaining lifespan based on cumulative stress and further translate this into real time, information regarding how the drive unit 100 is used may be utilized. This information may not only be stored within the drive unit 100, but may also be transmitted and managed by an external server via wireless communication or the like.
[0102] For example, by operating in the market, data on the relationship between the cumulative thermal stress and remaining lifespan of the power devices 1a to 1f in the drive unit 100 is accumulated. Based on this data, the device life prediction model, which was initially determined by reliability tests and durability tests, can be modified to enable life prediction under conditions closer to actual operation, thereby improving the accuracy of life prediction in the drive unit 100. Similarly, the control threshold CTHS and alarm threshold ATHS can also be read back and reset to their optimal values.
[0103] The control changes and alarm outputs based on remaining life described in this embodiment 2 may be used in conjunction with the method based on characteristic fluctuations described in embodiment 1, and may be issued when the condition is reached early, or a signal may be output when the conditions are met by both methods.
[0104] Next, we will explain the details of the control changes to the drive unit 100 when the remaining lifespan of power devices 1a to 1f decreases in this embodiment 2 and this is determined to be a sign of impending failure. The concept and content of the control changes are the same as in embodiment 1 of the present invention, and further detailed explanations will be omitted to avoid repetition. The difference from embodiment 1 of the present invention is whether the basis for the failure prediction diagnosis is due to the temporal characteristic changes of power devices 1a to 1f or to the decrease in the remaining lifespan of power devices 1a to 1f due to cumulative stress.
[0105] Next, Figure 10 illustrates how to predict when an alarm will be triggered and notify the user by calculating the rate of increase in cumulative thermal stress values and comparing it with a life prediction model and remaining lifespan.
[0106] Figure 10 further includes an operation history monitor 50 for inputting operational information of the drive unit 100 to the stress diagnosis unit 5 of the drive unit 100. Examples of operational information to be input to the drive unit 100 include operating time per unit time, control conditions, and temperature changes. The purpose of the operation history monitor 50, using an example, is to calculate the stress increase per unit time. The relationship between the stress increase per unit time and the remaining lifespan allows for the prediction of the actual failure time.
[0107] Similarly, the time when the remaining lifespan reaches the control threshold CTHA or alarm threshold ATHS can also be predicted. By transmitting these timings to an external source of the drive unit 100, for example, the drive unit 100 can be equipped with the display device 31 shown in Figure 1 to visually notify the user.
[0108] In other words, convenience is improved because users can know roughly when an alarm or malfunction will occur before it happens.
[0109] As described above, in Embodiment 2 of the present invention, various characteristics of a plurality of power devices 1a to 1f mounted on the drive unit 100 are measured by a plurality of characteristic sensors 2a to 2f, each of which is positioned to correspond to each power device 1a to 1f. The stress amount, which is expressed as the product of the measurement result and the measurement time interval, is accumulated as time-series data, and it is determined whether the remaining lifespan of each power device 1a to 1f falls below a predetermined threshold based on the accumulated stress amount.
[0110] This makes it possible to realize a drive unit 100 that can detect signs of failure in each power device 1a to 1f, and by changing the control of the drive unit 100 according to the detected state, the frequency of replacement of parts in the drive unit 100 or power devices 1a to 1f can be reduced, and an alarm can be issued to prompt the user to replace parts if the remaining lifespan of each power device 1a to 1f changes further.
[0111] (Example 3) Next, Example 3 of the present invention will be described.
[0112] Embodiment 3 of the present invention describes a vehicle equipped with a drive unit 100 that can detect signs of failure by detecting characteristic fluctuations in power devices 1a to 1f mounted on the drive unit 100, calculate the remaining lifespan of the power devices by calculating cumulative stress, issue notifications for component replacement at an appropriate time, and reduce the frequency of component replacement.
[0113] Figure 11 shows the configuration of vehicle 300 according to Embodiment 3 of the present invention.
[0114] In Figure 11, the vehicle 300 includes a drive unit 100, a motor 200, a wireless communication module 6, an antenna 7, and a display device 8. The drive unit 100 may be the one shown in Example 1 or the one shown in Example 2.
[0115] The wireless communication module 6 and antenna 7 are responsible for controlling wireless communication between the drive unit 100 and a server (not shown) located outside the vehicle 300. The server is equipped with a machine learning module that recursively calculates data based on the data transmitted from the drive unit 100 and retransmits it back to the drive unit 100.
[0116] The data transmitted from the drive unit 100 to the server, in accordance with this specification, may include, for example, control thresholds CTH1, CTH2 or CTHS, alarm thresholds ATH1, ATH2 or ATHS, cumulative thermal stress data at the time when power devices 1a to 1f actually failed, corrected characteristics accumulated in a time series in the sense result holding unit 3 of the drive unit 100, or statistical data related to the driving of the vehicle 300.
[0117] Furthermore, the server's communication targets may not be limited to a single drive unit 100, but may also include drive units 100 installed in multiple other vehicles 300 operating similarly in the market.
[0118] The data transmitted from the server to the drive unit 100 may include control thresholds CTH1, CTH2, or CTHS recalculated based on the data transmitted from the drive unit 100, alarm thresholds ATH1, ATH2, or ATHS, and lifetime prediction models for power devices 1a to 1f.
[0119] The characteristic variation diagnostic unit 4 in Example 1 and the stress diagnostic unit 5 in Example 2 can modify the control threshold range and remaining life by referring to the control thresholds CTH1, CTH2 or CTHS, alarm thresholds ATH1, ATH2 or ATHS, and life prediction models of power devices 1a to 1f received from the server.
[0120] By adopting this configuration, it becomes possible to correct and optimize the thresholds and judgment criteria for diagnosis and control of the contents described in Examples 1 and 2 of the present invention based on mass data from the market.
[0121] Furthermore, the machine learning module within the server can, for example, estimate the operating environment from data obtained from the drive unit 100, and then individually send recalculation results tailored to the operating environment to the drive unit 100 based on data from other vehicles 300 operating in similar environments. This makes it possible to improve the accuracy of the control change thresholds CTH1, CTH2 or CTHS, alarm thresholds ATH1, ATH2 or ATHS, and life prediction models for the drive unit 100 in similar operating environments.
[0122] Next, we will explain the timing of the diagnostic procedure performed on the drive unit 100 installed in the vehicle 300.
[0123] The characteristic acquisition timing described in Examples 1 and 2 was when the drive unit 100 was in operation, and correction of the acquired characteristic values was necessary depending on the operating conditions.
[0124] In Example 3, the sequence for performing latency diagnosis in the initial state after starting the vehicle 300 system but before the drive unit 100 starts operating is shown in flowcharts in Figures 12 and 13, and will be explained.
[0125] Figure 12 shows a latent diagnostic flow for detecting the presence or absence of characteristic fluctuations in power devices 1a to 1f mounted on the drive unit 100 as a sign of failure, after the vehicle 300 system has started up but before the drive unit 100 begins operation.
[0126] Similarly, Figure 13 shows a latency diagnostic flow for outputting characteristic variations as component replacement alarms.
[0127] In Figure 12, after the flow starts in step S410, the vehicle 300 system is started in step S420. Next, in step S430, the characteristics of each power device 1a to 1f mounted on the drive unit 100 are measured.
[0128] Subsequently, steps S440, S450 and S460 are the same as steps S130, S140 and S150 (Figure 3) described in Example 1, and a detailed explanation is omitted.
[0129] The characteristics of each power device 1a to 1f mounted on the drive unit 100 are measured, and in steps S440 and S450, characteristic fluctuations are diagnosed to detect whether or not there are signs of failure.
[0130] Latent diagnosis is completed by step S460, and in step S470, the drive unit 100 starts operations such as load driving. Thereafter, the same diagnosis as shown in Example 1 is performed periodically or at specific timings.
[0131] By performing latency diagnostics, the drive unit 100 can be diagnosed in a wider variety of situations, both before and after it starts operating. Sending the diagnostic results to the server improves the accuracy of machine learning, and consequently, the accuracy of the diagnostic thresholds and life prediction models fed back from the server can be improved.
[0132] As described above, according to Embodiment 3, it is possible to realize a vehicle equipped with a drive unit 100 that can detect signs of failure by detecting characteristic fluctuations in the power devices 1a to 1f mounted on the drive unit 100, calculate the remaining lifespan of the power devices 1a to 1f by calculating cumulative stress, issue notifications for part replacement at an appropriate time, and reduce the frequency of part replacement.
[0133] Figure 11 shows the application of the present invention to a vehicle 300, but the present invention can also be applied to other devices besides vehicles, such as air mobility devices.
[0134] It should be noted that the present invention is not limited to the above-described examples 1, 2, and 3, and includes various modifications. For example, the above-described examples 1, 2, and 3 are described in detail to make the present invention easier to understand, and are not necessarily limited to those having all the configurations described. Furthermore, it is possible to replace parts of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to add, delete, or replace some of the components of each of the embodiments 1, 2, and 3.
[0135] Furthermore, the control lines and signal lines shown are those deemed necessary for explanatory purposes and do not necessarily represent all control lines and signal lines in the actual product.
[0136] Furthermore, the characteristic variation diagnostic unit 4 in Example 1 and the stress diagnostic unit 5 in Example 2 can be collectively referred to as the control change signal output unit. [Explanation of symbols]
[0137] 1a, 1b, 1c, 1d, 1e, 1f... Power devices, 2a, 2b, 2c, 2d, 2e, 2f... Characteristic sensors, 3... Sense result holding unit, 4... Characteristic fluctuation diagnosis unit (control signal modification unit), 5... Stress diagnosis unit (control signal modification unit), 6... Wireless communication module, 7... Antenna, 8, 31... Display devices, 10... Drive control unit, 20... Control change signal, 30... Alarm signal, 40... Self-diagnosis control unit, 41... Reference signal, 50... Operation history monitor, 100... Drive unit, 200... Motor, 300... Vehicle, CTH1, CTH2, CTHS... Control threshold, ATH1, ATH2, ATHS... Alarm threshold
Claims
1. Multiple power devices for driving the load, A characteristic sensor for detecting the characteristics of each of the aforementioned multiple power devices, A sense result holding unit for storing the detection results of the plurality of power devices by the characteristic sensor in a time series, A control signal modification unit detects signs of failure in each of the multiple power devices from the detection results stored chronologically in the sense result holding unit and outputs a control change signal. A drive control unit that controls the operation of the plurality of power devices, A self-diagnostic control unit transmits a reference signal to the characteristic sensor for diagnosing the operation of the characteristic sensor, Equipped with, The control signal modification unit is, The system detects signs of failure in the plurality of power devices based on a control threshold, and if signs of failure are detected in one or more of the plurality of power devices, it outputs a control change signal to the drive control unit to drive the load with the remaining power devices, excluding the power device in which the signs of failure were detected. A drive device capable of diagnosing signs of failure, characterized in that it is a characteristic variation diagnostic unit that calculates the amount of characteristic variation for each of the multiple power devices from the detection results stored in a time series by the sense result holding unit, and detects signs of failure for the multiple power devices by determining whether the amount of characteristic variation has reached outside the control threshold range defined by the control threshold.
2. In a drive device capable of predicting failures, Multiple power devices for driving the load, A characteristic sensor for detecting the characteristics of each of the aforementioned multiple power devices, A sense result holding unit for storing the detection results of the plurality of power devices by the characteristic sensor in a time series, A control signal modification unit detects signs of failure in each of the multiple power devices from the detection results stored chronologically in the sense result holding unit and outputs a control change signal. A drive control unit that controls the operation of the plurality of power devices, Equipped with, The control signal modification unit is, The failure indicators of the aforementioned multiple power devices are detected based on control thresholds. If the failure indicator is detected in one or more of the aforementioned power devices, A control change signal is output to the drive control unit to drive the load using the power devices other than the power device from which the aforementioned failure indicator was detected. A stress diagnosis unit that detects signs of failure by calculating the remaining lifespan, which is the characteristic variation amount of each of the multiple power devices, from the stress amount expressed as the product of the detection results and the measurement time interval, which are stored in a time series by the sense result holding unit, and determining whether the remaining lifespan of the multiple power devices falls below the control threshold. The drive device is By referring to fault data from other drive units stored on a server that has been communicated to via wireless communication, A drive device capable of predicting failures, characterized in that the method for calculating the remaining lifespan of the power device can be modified.
3. A vehicle characterized by comprising the drive system described in claim 1 or 2.
4. In the drive device capable of predicting failure signs according to claim 1, The characteristic variation diagnostic unit is, A drive device characterized by determining whether the characteristic fluctuation amount has reached an alarm threshold range wider than the control threshold range determined by the control threshold, and outputting a warning alarm signal if it has reached an alarm threshold range.
5. In the drive device according to claim 2, The aforementioned stress diagnosis unit, A drive device characterized by determining whether the remaining lifespan has reached an alarm threshold shorter than the control threshold, and outputting a warning alarm signal if it is shorter than the alarm threshold.