Vehicle load estimation device

Abstract

The present invention provides a vehicle load estimation device that can accurately estimate the load on a component due to temperature changes. [Solution] Extreme values ​​in the temperature change of a component are extracted, and the temperature change amplitude corresponding to the starting temperature of the temperature change is extracted. For each temperature range with different starting temperatures to which the extracted temperature change amplitude applies, the frequency in a predetermined amplitude category is increased. Then, the total load of the component is estimated based on the frequency in the amplitude category. As a result, by organizing the temperature change amplitude for each starting temperature of the temperature change, it is possible to record substitute load characteristics for components with different loads in each temperature range. Therefore, it becomes possible to estimate the total load according to the differences in characteristics for each material property of the component. Thus, the load on the component due to temperature changes can be estimated with high accuracy.

Description

Technical Field

[0001] The present invention relates to a vehicle load estimation device.

Background Art

[0002] A load estimation device for a vehicle equipped with a component that receives a load due to temperature change is well known. For example, a prediction detection device in an electric vehicle described in Patent Document 1 is such a device. In this Patent Document 1, among the temperature changes of the electric motor mounted on the vehicle, the temperature difference between adjacent maximum values and minimum values is divided into a plurality of sections according to the magnitude, and the number of occurrences of the temperature difference is counted for each of the plurality of sections to obtain a cumulative value. Further, Patent Document 1 discloses calculating the ratio of the cumulative value to a predetermined upper limit value for each of the plurality of sections, and outputting an alarm signal when the sum value of these ratios exceeds a threshold value.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] By the way, even if the temperature difference in the temperature change of a component is the same, the magnitude of the load received may differ depending on which temperature range the temperature difference is in. For example, the temperature range in which the received load increases may differ for each component. Then, there is a possibility that the load due to the temperature change received by the component cannot be accurately estimated.

[0005] The present invention has been made in view of the above circumstances, and an object thereof is to provide a vehicle load estimation device capable of accurately estimating the load due to the temperature change received by a component.

Means for Solving the Problems

[0006] The gist of the first invention is (a) a load estimation device for a vehicle equipped with a component that is subjected to a load due to temperature changes, (b) a load estimation unit that estimates the total load which is the sum of the loads received by the component, (c) the load estimation unit extracts extreme values ​​including the maximum and minimum values ​​in the temperature change of the component, extracts the temperature change amplitude which is the difference between adjacent maximum and minimum values ​​corresponding to the starting temperature of the temperature change, increases the frequency in the amplitude category which is divided into different magnitudes of the temperature change amplitude predetermined for each temperature range of different starting temperatures to which the extracted temperature change amplitude applies, and (d) the load estimation unit estimates the total load based on the frequency in the amplitude category. [Effects of the Invention]

[0007] According to the first invention, extreme values ​​in the temperature change of a component are extracted, the temperature change amplitude corresponding to the starting temperature of the temperature change is extracted, and the frequency in a predetermined amplitude category for each temperature range with different starting temperatures to which the extracted temperature change amplitude applies is increased. Then, the total load of the component is estimated based on the frequency in the amplitude category. As a result, by organizing the temperature change amplitude for each starting temperature of the temperature change, it is possible to record substitute load characteristics for components with different loads in each temperature range. Therefore, it becomes possible to estimate the total load according to the differences in characteristics for each material property of the component. Thus, the load on the component due to temperature changes can be estimated with high accuracy. [Brief explanation of the drawing]

[0008] [Figure 1] This diagram illustrates the schematic configuration of a vehicle to which the present invention is applied, and further illustrates the main parts of the control functions and control systems for various control functions in the vehicle. [Figure 2] This diagram illustrates the extraction of temperature change amplitudes corresponding to the starting temperature. (a) is a diagram illustrating the extraction of extreme values. (b) is a diagram illustrating the extraction of temperature change amplitudes. (c) is a diagram illustrating the extraction of only the downward temperature change amplitudes corresponding to the starting temperature. [Figure 3] This figure illustrates the downward temperature change amplitude of an electric motor, extracted using the rainflow method. (a) shows an example of the temperature drop range corresponding to the temperature at which the temperature drops begin. (b) shows an example of the amplitude divisions for each temperature range of the temperature at which the temperature drops begin. [Figure 4] This diagram illustrates the essential parts of the control operation of an electronic control device. (a) is a flowchart illustrating the essential parts of the control operation of an electronic control device, and is a flowchart illustrating the control operation for accurately estimating the load on the motor due to temperature changes. (b) is a diagram illustrating the flow when the flowchart shown in (a) is executed repeatedly. [Figure 5] This flowchart explains the control operation for creating a temperature time series dataset, and is the subroutine corresponding to step S10 in the flowchart in Figure 4(a). [Figure 6] This flowchart explains the control operation for extracting the temperature change amplitude, and is the subroutine corresponding to step S20 in the flowchart of Figure 4(a). [Modes for carrying out the invention]

[0009] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. [Examples]

[0010] Figure 1 is a diagram illustrating the schematic configuration of a vehicle 10 to which the present invention is applied, and illustrates the main parts of the control functions and control systems for various controls in the vehicle 10. In Figure 1, the vehicle 10 includes wheels WH including front wheels 12 and rear wheels 14, a front wheel drive unit 20 that drives the front wheels 12, and a rear wheel drive unit 30 that drives the rear wheels 14. The vehicle 10 also includes a battery 40, which is a rechargeable DC power source.

[0011] Vehicle 10 is a four-wheel drive vehicle in which the torque distribution between the front wheels 12 and the rear wheels 14 can be adjusted. All-wheel drive (AWD) and four-wheel drive (4WD) are synonymous.

[0012] The front wheel drive system 20 includes an engine 22, a first electric motor MG1, a second electric motor MG2, a power split mechanism 24, a front wheel transmission mechanism 26, a front wheel power control device 28, and the like.

[0013] Engine 22 is a known internal combustion engine. The engine torque Te of engine 22 is controlled by an electronic control device 50, which will be described later. The first electric motor MG1 and the second electric motor MG2 are each known rotating electric machines, so-called motor generators. The first electric motor MG1's torque, Tmg1, is controlled by the front wheel power control device 28 controlled by the electronic control device 50. The second electric motor MG2's torque, Tmg2, is controlled by the front wheel power control device 28 controlled by the electronic control device 50. Engine 22 and the second electric motor MG2 function as power sources for driving.

[0014] The power split mechanism 24 is, for example, a known single-pinion type planetary gear system. The power split mechanism 24 mechanically splits the power of the engine 22 input to the carrier, for example, to a sun gear and a ring gear. A first electric motor MG1 is power-transmittingly connected to the sun gear. In the power split mechanism 24, the reaction force of the engine torque Te is borne by the first electric motor torque Tmg1, thereby directly transmitting torque to the ring gear. The ring gear is the output rotating member of the power split mechanism 24, and a second electric motor MG2 is power-transmittingly connected to it. The second electric motor MG2 is driven by the power generated by the first electric motor MG1 and / or power from the battery 40. By controlling the operating state of the first electric motor MG1, the differential state of the power split mechanism 24 is controlled, thereby configuring a known electric continuously variable transmission.

[0015] The front wheel transmission mechanism 26 includes, for example, a reduction gear mechanism including a differential gear, a drive shaft, etc., and transmits power output from the power split mechanism 24 and power output from the second electric motor MG2 to the front wheels 12.

[0016] The battery 40 is a high-voltage battery for driving. The battery 40 is electrically connected to the front-wheel power control device 28. The front-wheel power control device 28 includes, for example, an inverter. The front-wheel power control device 28 is electrically connected to each of the first electric motor MG1 and the second electric motor MG2. The front-wheel power control device 28 is a power control unit (PCU (Power Control Unit)) that controls the power transmitted between the battery 40 and each of the first electric motor MG1 and the second electric motor MG2. The front-wheel power control device 28 converts the DC power from the battery 40 into AC power for driving the first electric motor MG1 and the second electric motor MG2. The front-wheel power control device 28 converts the AC power generated by each of the first electric motor MG1 and the second electric motor MG2 into DC power and supplies it to the battery 40.

[0017] The rear-wheel drive device 30 includes a rear-wheel electric motor MGR, a rear-wheel transmission mechanism 32, a rear-wheel power control device 34, and the like.

[0018] The rear-wheel electric motor MGR is a known rotary electric machine and is a so-called motor generator. The rear-wheel electric motor MGR is controlled by the rear-wheel power control device 34 by the electronic control device 50, and the rear-wheel electric motor torque Tmgr, which is the torque of the rear-wheel electric motor MGR, is controlled. The rear-wheel electric motor MGR functions as a power source for traveling.

[0019] The rear-wheel transmission mechanism 32 includes, for example, a reduction gear mechanism including a differential gear, a drive shaft, and the like, and transmits the power output from the rear-wheel electric motor MGR to the rear wheels 14.

[0020] The battery 40 is electrically connected to the rear-wheel power control device 34. The rear-wheel power control device 34 includes, for example, an inverter. The rear-wheel power control device 34 is electrically connected to the rear-wheel motor MGR. The rear-wheel power control device 34 is a PCU that controls the power transmitted between the battery 40 and the rear-wheel motor MGR. The rear-wheel power control device 34 converts the DC power from the battery 40 into AC power for driving the rear-wheel motor MGR. The rear-wheel power control device 34 converts the AC power generated by the rear-wheel motor MGR into DC power and supplies it to the battery 40.

[0021] The vehicle 10 includes an electronic control unit 50 as a controller including the control unit of the vehicle 10. The electronic control unit 50 is configured to include a so-called microcomputer including, for example, a CPU, a RAM, a ROM, an input / output interface, and the like. The CPU executes various controls of the vehicle 10 by performing signal processing according to a program stored in the ROM in advance while using the temporary storage function of the RAM, for example.

[0022] Various signals based on detection values by various sensors and the like provided in the vehicle 10 are respectively supplied to the electronic control unit 50. The various sensors and the like are, for example, an engine speed sensor 60, a first motor speed sensor 62, a second motor speed sensor 64, a rear-wheel motor speed sensor 66, an accelerator opening sensor 68, a first motor temperature sensor 70, a second motor temperature sensor 72, a rear-wheel motor temperature sensor 74, an outside air temperature sensor 76, and the like. The various signals are, for example, an engine speed Ne, a first motor speed Nmg1, a second motor speed Nmg2, a rear-wheel motor speed Nmgr, an accelerator opening θacc, a first motor temperature THmg1, a second motor temperature THmg2, a rear-wheel motor temperature THmgr, an outside air temperature THair, and the like.

[0023] The first motor temperature THmg1 is the temperature of the first motor MG1. The second motor temperature THmg2 is the temperature of the second motor MG2. The rear-wheel motor temperature THmgr is the temperature of the rear-wheel motor MGR. The outside air temperature THair is the temperature outside the vehicle 10, that is, the temperature around the vehicle 10.

[0024] The electronic control unit 50 outputs various command signals to each device installed in the vehicle 10. These devices include, for example, the engine 22, the front wheel power control device 28, and the rear wheel power control device 34. The various command signals include, for example, the engine control command signal Se, the first motor control command signal Smg1, the second motor control command signal Smg2, and the rear wheel motor control command signal Smgr.

[0025] The electronic control unit 50 includes a drive control unit 52 to implement various controls in the vehicle 10.

[0026] The drive control unit 52 calculates the required drive torque Twdem for the vehicle 10 by applying the accelerator opening θacc and vehicle speed V to a predetermined drive request map, for example. The required drive torque Twdem is the required value of the drive torque Tw, which is the torque at the wheels WH. The drive torque Tw is the sum of the front wheel torque Twf, which is the torque at the front wheels 12, and the rear wheel torque Twr, which is the torque at the rear wheels 14. Note that unless otherwise specified, torque and force (driving force) are synonymous.

[0027] The drive control unit 52 sets the torque distribution ratio between the front and rear wheels based on multiple driving force-related values, such as accelerator opening θacc, vehicle speed, longitudinal acceleration, and yaw rate. Based on the requested drive torque Twdem and the torque distribution ratio, the drive control unit 52 calculates the requested front wheel torque Twfdem and the requested rear wheel torque Twrdem. The requested front wheel torque Twfdem is the requested value for the front wheel torque Twf. The requested rear wheel torque Twrdem is the requested value for the rear wheel torque Twr. The drive control unit 52 outputs an engine control command signal Se, a first motor control command signal Smg1, and a second motor control command signal Smg2 to control the front wheel drive unit 20 to achieve the requested front wheel torque Twfdem. The drive control unit 52 outputs a rear wheel motor control command signal Smgr to control the rear wheel drive unit 30, i.e., the rear wheel motor MGR, to achieve the requested rear wheel torque Twrdem.

[0028] Here, the motors MG of the first motor MG1, the second motor MG2, and the rear wheel motor MGR generate heat when in operation, causing the motor temperature THmg (THmg1, THmg2, THmgr) to fluctuate. Fluctuations in the motor temperature THmg impart a load B to the motors MG, which may reduce the durability of the motors MG. For example, the resin such as the insulator in the coil portion used in the motors MG may be subjected to load B due to fluctuations in the motor temperature THmg, which may reduce its durability. The motors MG are components that are subjected to load B due to fluctuations in the motor temperature THmg, i.e., temperature changes.

[0029] The load B of an electric motor (MG) due to temperature changes increases with larger temperature changes. Furthermore, the total load B increases with higher frequency of temperature changes. Therefore, it is conceivable to estimate the total load Btotal, which is the sum of the load B experienced by the electric motor (MG), by detecting the temperature difference during temperature changes and the frequency of each temperature difference. However, even if the temperature difference during a temperature change in the electric motor (MG) is the same, the magnitude of the load B may differ depending on the temperature range in which that temperature difference occurs. For example, different resin materials may have different glass transition points, and the temperature range in which the load B increases, corresponding to the temperature change passing through the glass transition point, may differ for each resin material. In such cases, it may be difficult to accurately estimate the load B.

[0030] In response to the aforementioned problems, the present invention estimates the total load Btotal by focusing on the temperature range in which the temperature difference in the temperature change of the electric motor MG lies. The electronic control device 50 further comprises a load estimation unit 54 that estimates the total load Btotal. The electronic control device 50 functions as a load estimation device according to the present invention.

[0031] The load estimation unit 54 estimates the total load Btotal for each of the following: the first motor MG1, the second motor MG2, and the rear wheel motor MGR. The total load Btotal for the motor MG represents one of the total load Btotal for each of the first motor MG1, the second motor MG2, and the rear wheel motor MGR. Furthermore, "MG#temperature" shown in Figures 2, 4, and 5, which will be described later, is the motor temperature THmg, and represents one of the first motor temperature THmg1, the second motor temperature THmg2, and the rear wheel motor temperature THmgr.

[0032] The load estimation unit 54 extracts extreme values, including the maximum and minimum values, in the temperature change of the electric motor MG. The load estimation unit 54 extracts the temperature change amplitude ΔT, which is associated with the starting temperature Ths of the electric motor MG's temperature change. The temperature change amplitude ΔT is the temperature amplitude component as the difference between adjacent maximum and minimum values. The temperature amplitude component is used as a substitute for the stress amplitude component. The "stress" in the stress amplitude component represents, for example, the change due to temperature of a resin material, and temperature is used as a substitute characteristic. The load estimation unit 54 increases the frequency H in a predetermined amplitude category DIVa for each different temperature range RNGt of the starting temperature Ths to which the extracted temperature change amplitude ΔT applies. The amplitude category DIVa is an interval of temperature change amplitude ΔT divided by different magnitudes of temperature change amplitude ΔT. The load estimation unit 54 estimates the total load Btotal based on the frequency H in the amplitude category DIVa for each temperature range RNGt. This total load Btotal is the total load Btotal of each individual motor (MG).

[0033] Figure 2 illustrates the extraction of the temperature change amplitude ΔT associated with the starting temperature Ths. Figure 2(a) illustrates the extraction of extreme values. Figure 2(b) illustrates the extraction of the temperature change amplitude ΔT. Figure 2(c) illustrates the extraction of only the downward temperature change amplitude ΔT associated with the starting temperature Ths.

[0034] The waveform in Figure 2(a) shows the peaks and troughs extracted from time-series data of the temperature change of the electric motor MG. The peaks in the time-series data represent local maximums. The troughs in the time-series data represent local minimums. The load estimation unit 54 temporarily stores the extracted extreme values ​​as temperature time-series data, which is time-series information of the temperature change. In this embodiment, the set of temperature time-series data is referred to as a temperature time-series dataset (see Figure 2(a)). The load estimation unit 54 has, for example, a storage unit 56, which stores the temperature time-series data, etc.

[0035] An example of creating a temperature time series dataset is shown below. The load estimation unit 54 acquires the motor temperature THmg. The load estimation unit 54 determines whether the acquired motor temperature THmg is an extreme value. If the load estimation unit 54 determines that the acquired motor temperature THmg is an extreme value, it determines whether the difference between the acquired motor temperature THmg and the latest data is greater than a predetermined extreme value difference. The latest data is the latest extreme value of the temperature time series data. If the load estimation unit 54 determines that the difference between the acquired motor temperature THmg and the latest data is greater than a predetermined extreme value difference, it adds the acquired motor temperature THmg to the temperature time series dataset. If the load estimation unit 54 determines that the difference between the acquired motor temperature THmg and the latest data is less than or equal to the predetermined extreme value difference, it does not add the acquired motor temperature THmg to the temperature time series dataset. In other words, when the load estimation unit 54 stores temperature time series data, if the difference between the extracted extreme value and the extreme value previously stored as temperature time series data is less than or equal to a predetermined extreme value difference, the extracted extreme value is not stored as temperature time series data. This reduces the area occupied by temporary storage by omitting data processing that has little impact on load B. The predetermined extreme value difference is, for example, a predetermined threshold used to determine whether the addition of an extreme value has little impact on load B. Between the extracted extreme value and the previously stored extreme value, one is a local maximum and the other is a local minimum.

[0036] The load estimation unit 54 terminates the storage of extreme values ​​in the currently being stored temperature time series data and starts storing extreme values ​​in new temperature time series data when a predetermined condition CDf is met. The predetermined condition CDf is, for example, condition CDa, when the latest motor temperature THmg stored in the temperature time series dataset is within a predetermined temperature difference from the ambient temperature THair. The predetermined temperature difference is, for example, a predetermined threshold for determining that the motor MG has cooled down and the motor temperature THmg has dropped to near the ambient temperature THair. This suppresses the length of data to be temporarily stored. Alternatively, the predetermined condition CDf is, for example, condition CDb, when the number of points, i.e., the number of extreme values, in the temperature time series dataset reaches a predetermined number. The predetermined number is, for example, a predetermined threshold for determining that the amount of temperature time series data to be temporarily stored has become an appropriate amount as a single temperature time series dataset. This suppresses the length of data to be temporarily stored. The load estimation unit 54 terminates the storage of extreme values ​​in the currently being stored temperature time series dataset and starts storing extreme values ​​in new temperature time series data when either condition CDa or condition CDb is met. This minimizes the length of data to be temporarily stored. The load estimation unit 54 determines whether the temperature difference between the motor temperature THmg and the ambient temperature THair, which has been added to the temperature time series dataset, is greater than a predetermined temperature difference. The load estimation unit 54 determines whether the number of points in the temperature time series dataset is less than a predetermined number. If the load estimation unit 54 determines that the temperature difference between the motor temperature THmg and the ambient temperature THair is within the predetermined temperature difference, it terminates the storage of extreme values ​​in the current temperature time series dataset and starts storing extreme values ​​in the new temperature time series dataset. Alternatively, if the load estimation unit 54 determines that the number of points in the temperature time series dataset has reached a predetermined number, it terminates the storage of extreme values ​​in the current temperature time series dataset and starts storing extreme values ​​in the new temperature time series dataset.

[0037] When the load estimation unit 54 finds that a predetermined condition CDf has been met, it starts storing extreme values ​​in a new temperature time series dataset. In doing so, it uses the data of the last extreme value in the previously stored temperature time series dataset as the data of the first extreme value in the new temperature time series dataset. This allows for the accurate extraction of the temperature change amplitude ΔT in the new temperature time series dataset.

[0038] The load estimation unit 54, in parallel with storing the extreme values ​​in the newly started temperature time series data, extracts the temperature change amplitude ΔT using the temperature time series data that has finished being stored, and increases the frequency H in the amplitude category DIVa for each temperature range RNGt to which the temperature change amplitude ΔT applies.

[0039] The transition to the temperature amplitude counting operation, which extracts the temperature change amplitude ΔT using the temperature time series data whose memory has ended, is performed when a predetermined condition CDf is met for each of the first motor temperature THmg1, the second motor temperature THmg2, and the rear wheel motor temperature THmgr. This allows the temperature amplitude counting operation to be performed under the same conditions for each of the first motor temperature THmg1, the second motor temperature THmg2, and the rear wheel motor temperature THmgr.

[0040] When the processing load becomes large, the temperature amplitude counting operation is performed in separate processing cycles. For example, the temperature amplitude counting operations for the first motor temperature THmg1, the second motor temperature THmg2, and the rear wheel motor temperature THmgr are performed in separate processing cycles. Alternatively, the creation of the temperature time series dataset and the temperature amplitude counting operation may be performed in separate processing cycles. This allows the necessary processing to be performed without placing an excessive load on the electronic control unit 50.

[0041] As described above, the load estimation unit 54 temporarily stores the extracted extreme values ​​as temperature time series data, and then extracts multiple temperature change amplitudes ΔT using the stored temperature time series data. For example, as shown in Figure 2(b), the load estimation unit 54 extracts temperature change amplitudes ΔT using the known rainflow method. In Figure 2(b), the solid line Th1-Th2-Th4 shows one of the rising temperature change amplitudes ΔT. The dashed line Th4-Th5-Th8 shows one of the falling temperature change amplitudes ΔT. Other temperature change amplitudes ΔT are extracted similarly. In this way, the load estimation unit 54 extracts multiple temperature change amplitudes ΔT from a temperature time series dataset, for example. Furthermore, because the rainflow method is used, it is considered a method that reflects how the motor MG is damaged, so a more accurate count of the load B can be obtained.

[0042] The load estimation unit 54 extracts the temperature change amplitude ΔT of either the rising or falling side of the temperature change of the electric motor MG. For example, as shown in Figure 2(c), the load estimation unit 54 extracts only the temperature change amplitude ΔT of the falling side of the temperature change of the electric motor MG from the temperature change amplitude ΔT extracted by the rainflow method. Although the extraction of only the falling side of the temperature change amplitude ΔT is shown here as an example, it is also possible to extract only the temperature change amplitude ΔT of the rising side of the temperature change of the electric motor MG from the temperature change amplitude ΔT extracted by the rainflow method.

[0043] The load estimation unit 54 may delete the temperature time series dataset after extracting the temperature change amplitude ΔT from it. However, if there is no problem, it may overwrite the temperature time series dataset from which the temperature change amplitude ΔT was extracted with new temperature time series data.

[0044] Figure 3 illustrates the downward temperature change amplitude ΔT of the electric motor MG, extracted using the rainflow method. Figure 3(a) shows an example of the temperature drop range as the temperature change amplitude ΔT, corresponding to the starting temperature Ths. Figure 3(b) shows an example of the amplitude division DIVa for each temperature range RNGt of the starting temperature.

[0045] Figure 3(a) shows the temperature drop, which is the downward temperature change amplitude ΔT of the temperature change amplitude ΔT shown in Figure 2(c), and the temperature at which the temperature drop begins. In Figure 3(b), the amplitude division DIVa for each temperature range RNGt is assigned each of the temperature drop divisions corresponding to the temperature drop start temperature, and the frequency H is increased. For example, if the temperature drop start temperature Th2 is between "T1~T2" in the temperature range RNGt, and the temperature drop division "Th2-Th3" is between "ΔT2~ΔT3" in the amplitude division DIVa, then the frequency H in the division "T1~T2" and "ΔT2~ΔT3" is increased by one. In Figure 3(b), the magnitude of the temperature range RNGt and the magnitude of the amplitude division DIVa may be equal, or they may not be equal, taking into consideration the impact on the damage to the electric motor MG.

[0046] For each of the predetermined amplitude divisions DIVa for each temperature range RNGt of the starting temperature Ths (see each division shown in Figure 3(b)), the load weighting of the load received by the motor MG is predetermined. The load estimation unit 54 estimates the total load Btotal based on the weighted load Bxy and the frequency Hxy in the amplitude division DIVa. For example, the load estimation unit 54 calculates the total load Btotal as the sum of the product values ​​of the load Bxy and frequency Hxy in each division (= Bxy × Hxy).

[0047] If the load estimation unit 54 determines that the temperature signal of the motor temperature THmg from the motor temperature sensors (70, 72, 74) is unreliable, it will not temporarily store the temperature time series data set. This prevents the incorrect recording of the motor load B of the motor MG.

[0048] Figure 4 is a diagram illustrating the main part of the control operation of the electronic control device 50. Figure 4(a) is a flowchart illustrating the main part of the control operation of the electronic control device 50, and is a flowchart illustrating the control operation for accurately estimating the load B due to temperature changes experienced by the electric motor MG, and is executed repeatedly, for example. Figure 4(b) is a diagram illustrating the flow when the flowchart shown in Figure 4(a) is executed repeatedly. Figure 5 is a flowchart illustrating the control operation for creating a temperature time series dataset, and is a subroutine corresponding to step S10 in the flowchart of Figure 4(a). Figure 6 is a flowchart illustrating the control operation for extracting the temperature change amplitude ΔT, and is a subroutine corresponding to step S20 in the flowchart of Figure 4(a).

[0049] In Figure 4(a), each step in the flowchart corresponds to a function of the load estimation unit 54. First, in step S10 (the step will be omitted hereafter), a temperature time series dataset is created by extracting the peaks (maximum values) and troughs (minimum values) of the motor temperature THmg, and in S20, the temperature change amplitude ΔT is extracted as a stress amplitude component.

[0050] In Figure 5, the temperature time series dataset is created in S10. First, in S110, the motor temperature THmg is acquired. Next, in S120, it is determined whether the acquired motor temperature THmg is an extreme value (maximum or minimum value). If the determination in S120 is negative, this routine is terminated. If the determination in S120 is positive, in S130, it is determined whether the difference between the acquired motor temperature THmg and the latest data is greater than a predetermined extreme value difference. If the determination in S130 is negative, this routine is terminated. If the determination in S130 is positive, in S140, the acquired motor temperature THmg is added to the temperature time series dataset. Next, in S150, it is determined whether the temperature difference between the motor temperature THmg added to the temperature time series dataset and the ambient temperature THair is greater than a predetermined temperature difference. If the judgment in S150 is affirmative, then in S160, it is determined whether the number of points in the temperature time series dataset is less than a predetermined number. If the judgment in S160 is affirmative, this routine is terminated. If the judgment in S150 is negative, or if the judgment in S160 is negative, then in S170, the process transitions from S10 to S20, and this routine is terminated.

[0051] In Figure 6, the temperature change amplitude ΔT is extracted in S20. First, in S210, the temperature change amplitude ΔT is extracted from a set of temperature time series datasets. Next, in S220, the set of temperature time series datasets is deleted. Then, in S230, the data of the last extreme value in the deleted set of temperature time series datasets is saved as the data of the first extreme value in the new temperature time series dataset that is being created, and this routine is terminated.

[0052] Returning to Figure 4(a), following S10 and S20, in S30, the downward (or cooling) temperature change amplitude ΔT is extracted from the extracted temperature change amplitude ΔT. Then, in S40, the frequency of the pre-set interval (or division) between the temperature drop start temperature and the temperature drop range, i.e., the amplitude division DIVa for each temperature range RNGt, to which each extracted cooling-side temperature change amplitude ΔT belongs, is increased, and this routine is terminated.

[0053] In Figure 4(b), if the conditions for transitioning to S20 are met in S10, S10 is started anew. S20 to S40 are executed in parallel with the execution of the new S10 (see S170 in Figure 5). These control operations are executed repeatedly. The timing for transitioning to S20 is when the conditions for transitioning to S20 are met for each of the first motor temperature THmg1, the second motor temperature THmg2, and the rear wheel motor temperature THmgr. If the processing load becomes heavy when processing S20 to S40 within one processing cycle, it may be separated from the processing of S10, for example. If the motor temperature THmg signal acquired in S110 is unreliable, the processing from S120 onward for the motor temperature THmg will not be performed.

[0054] As described above, according to this embodiment, extreme values ​​in the temperature change of the electric motor MG are extracted, the temperature change amplitude ΔT corresponding to the starting temperature Ths is extracted, and the frequency H in the amplitude category DIVa for each temperature range RNGt to which the extracted temperature change amplitude ΔT applies is increased. Then, the total load Btotal is estimated based on the frequency H in the amplitude category DIVa for each temperature range RNGt. As a result, by organizing the temperature change amplitude ΔT for each starting temperature Ths, it is possible to record the substitute load characteristics of the components of the electric motor MG, where the load B differs for each temperature range. Therefore, it becomes possible to estimate the total load Btotal according to the differences in characteristics for each material property of the components of the electric motor MG. Thus, the load B due to temperature changes experienced by the electric motor MG can be estimated with high accuracy.

[0055] Furthermore, according to this embodiment, the temperature change amplitude ΔT of only one of the rising or falling sides of the temperature change of the electric motor MG is extracted. By narrowing the focus to either the rising or falling side of the temperature change, the storage capacity of the storage unit 56 can be saved.

[0056] Furthermore, according to this embodiment, after the extracted multiple extreme values ​​are temporarily stored as temperature time series data, the stored temperature time series data is used to extract multiple temperature change amplitudes ΔT. This makes it possible to conveniently select the timing for extracting the temperature change amplitudes ΔT from the temperature time series dataset. In addition, since the extraction of temperature change amplitudes ΔT is not performed each time an extreme value is extracted, the normal load on the electronic control device 50 can be reduced.

[0057] Furthermore, according to this embodiment, when a predetermined condition CDf is met, the storage of extreme values ​​in the currently running temperature time series data is terminated, and the storage of extreme values ​​in new temperature time series data is started. In addition, in parallel with the storage of extreme values ​​in the newly started temperature time series data, the temperature change amplitude ΔT is extracted using the temperature time series data whose storage has been terminated. Furthermore, the frequency H in the amplitude category DIVa for each temperature range RNGt to which the extracted temperature change amplitude ΔT applies is increased. As a result, even if driving continues, the storage of extreme values ​​in the temperature time series data is not stopped, and the size of the temperature time series dataset can be kept within the limited temporary storage area.

[0058] Furthermore, according to this embodiment, the load on the motor MG is weighted in advance for each of the predetermined amplitude divisions DIVa for each temperature range RNGt of the starting temperature Ths. The total load Btotal is estimated based on the weighted load Bxy and the frequency Hxy in the amplitude division DIVa. This allows the degree of damage to the target component to be indicated, leading to appropriate countermeasures.

[0059] Although embodiments of the present invention have been described in detail above with reference to the drawings, the present invention is also applicable to other embodiments.

[0060] For example, in the above-described embodiment, the first motor MG1, the second motor MG2, and the rear wheel motor MGR were exemplified as components for which the load B due to temperature change is counted, but the invention is not limited to this embodiment. For example, the component for which the load B due to temperature change is counted may be at least one of the first motor MG1, the second motor MG2, and the rear wheel motor MGR. Alternatively, the component for which the load B due to temperature change is counted may be a component located near the motor MG. In short, the present invention can be applied to any vehicle equipped with components that are subjected to loads due to temperature changes.

[0061] Furthermore, in the above-described embodiment, AI-based estimation, such as a machine learning model, may be used for estimating the total load Btotal and the degree of damage to the components. For example, a weighted load Bxy may be pre-learned for each component, and the component name, the temperature change amplitude ΔT associated with the starting temperature Ths, etc., may be input to output an estimate of the total load Btotal. Alternatively, the measured temperature of the component may be input to a learning model having the function of the load estimation unit 54 to output an estimate of the total load Btotal.

[0062] It should be noted that the above-described embodiment is merely one example, and the present invention can be implemented in various modified and improved forms based on the knowledge of those skilled in the art. [Explanation of Symbols]

[0063] 10: Vehicle 50: Electronic control unit (load estimation device) 54: Load estimation unit MG: Electric motor (component subjected to load due to temperature changes)

Claims

1. A load estimation device for a vehicle equipped with components that are subjected to loads due to temperature changes, The system includes a load estimation unit that estimates the total load, which is the sum of the loads received by the aforementioned components. The load estimation unit extracts extreme values ​​including the maximum and minimum values ​​in the temperature change of the component, extracts the temperature change amplitude which is the difference between adjacent maximum and minimum values ​​and is associated with the starting temperature of the temperature change, and increases the frequency of the amplitude divisions, which are predetermined to be divided into different magnitudes of the temperature change amplitude for each temperature range of different starting temperatures to which the extracted temperature change amplitude applies. The load estimation device for a vehicle is characterized in that the load estimation unit estimates the total load based on the frequency in the amplitude category.

2. The load estimation device for a vehicle according to claim 1, characterized in that the load estimation unit extracts the temperature change amplitude of only one of the rising or falling sides of the temperature change.

3. The load estimation device for a vehicle according to claim 1, characterized in that the load estimation unit temporarily stores the extracted multiple extreme values ​​as temperature time series data, which is time series information of the temperature change, and then extracts multiple temperature change amplitudes using the stored temperature time series data.

4. When a predetermined condition is met, the load estimation unit terminates the storage of the extreme values ​​in the currently being stored temperature time series data and begins storing the extreme values ​​in new temperature time series data. The load estimation unit is characterized in that, in parallel with storing the extreme values ​​in the newly started temperature time series data, it extracts the temperature change amplitude using the temperature time series data whose storage has ended and increases the frequency in the amplitude category, as described in claim 3.

5. In each of the predetermined amplitude segments for each temperature range of the starting temperature, the weighting of the load received by the component is predetermined. The load estimation device for a vehicle according to any one of claims 1 to 4, characterized in that the load estimation unit estimates the total load based on the weighted load and the frequency in the amplitude category.

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