JP7203534B2 - HYBRID VEHICLE CONTROL METHOD AND HYBRID VEHICLE CONTROL DEVICE - Google Patents

Description

The present invention relates to a hybrid vehicle control method and a hybrid vehicle control apparatus.

Patent Literature 1 discloses a technique for selecting a route with the highest charging efficiency among a plurality of routes.

JP 2013-177089 A

In Patent Literature 1, there is a problem that the engine is started when the cabin noise is low because of power generation, and the driver cannot enjoy quiet driving on a quiet road.
SUMMARY OF THE INVENTION It is an object of the present invention to provide a hybrid vehicle control method and a hybrid vehicle control apparatus that make it difficult for a driver to feel noise and vibration when the engine is started.

In the present invention, the road surface roughness of the current travel route is predicted, and based on the predicted road surface roughness , the engine is not started in the section where the road surface roughness is not rough before the section where the road surface roughness is rough . Priority is given to running by the drive motor of the

Therefore, since the engine can be started and charged in the section where the road surface is rough , the vehicle can be driven by the drive motor without the engine running in the section where the road surface is not rough in front of it, and the driver can quietly drive the vehicle. You can fully enjoy safe driving.

1 is a control system block diagram of a control device for a hybrid vehicle to which the present invention is applied; FIG. 4 is a flow chart showing the flow of control processing according to the first embodiment; 4 is a time chart showing an example of execution of control processing in the first embodiment; FIG. 10 is a flow chart showing the flow of control processing in the second embodiment; FIG. FIG. 11 is a time chart showing an example of execution of control processing in the second embodiment; FIG. 10 is a flow chart showing the flow of control processing in Example 3. FIG. FIG. 11 is a time chart showing an example of execution of control processing in the third embodiment; FIG.

[Example 1]
FIG. 1 is a control system block diagram of a hybrid vehicle control device to which the present invention is applied.

First, the configuration of the entire control system will be described with reference to FIG.
A system controller 1 for a series hybrid vehicle as a control device for a hybrid vehicle includes vehicle interior sound prediction means 1a and priority control means 1b, and transmits driving force to a pair of drive wheels 7 via an automatic transmission (not shown). an engine controller 2a that controls the engine 2, a generator controller 3a that controls the generator 3 driven by the engine 2 via a generator inverter 3b, a battery controller 4a that controls the battery 4, and a drive inverter 5b , and a drive motor controller 5a that controls a drive motor 5 that transmits drive force to a pair of drive wheels 7 via a speed reducer 6, and give instructions to each controller to control the series hybrid vehicle. .
Furthermore, the system controller 1 receives road surface information and map information from an external data center and other vehicles 11 via a navigation system 8 having a display device 9 and an in-vehicle communication device 10. etc.) 12, information from a displacement sensor 13 for detecting vertical vibration of the vehicle as a vibration sensor, and an acceleration sensor 14 for detecting vertical acceleration of the vehicle as a vibration sensor.

FIG. 2 is a flow chart showing the flow of control processing according to the first embodiment.
That is, it shows the flow of control processing of the system controller 1 having the vehicle interior sound prediction means 1a and the priority control means 1b.
This flowchart is repeatedly executed at a predetermined calculation cycle.

In step S1, the vehicle interior sound prediction means 1a receives the travel route from the current location to the destination from the navigation system 8, and further from the external data center and other vehicles 11 via the navigation system 8 and the in-vehicle communication device 10, the current Acquire the road surface information (road surface roughness) of the road along the travel route.
In addition, when the travel route from the current location to the destination is not set in the navigation system 8, the current travel route precedes the same travel route via the navigation system 8 and the vehicle-mounted communication device 10. When it is determined from the travel route information from the other vehicle 11 that the current travel route is a non-branching road, the road surface roughness of the current travel route before the branch is determined as the vehicle interior noise. It predicts a high coarse section and a non-coarse (smooth) section with low cabin noise.
This increases the chances of anticipation and allows the driver to enjoy quieter driving.
In step S2, the vehicle interior sound prediction means 1a sets a threshold for judging that the road surface is rough from the acquired road surface information (road surface roughness) of the current driving route. A rough section with high room sound and a non-rough (smooth) section with low room sound are predicted.
For example, the road surface conditions are divided into four stages, and the threshold is selected according to the road surface conditions of the travel route. Predict intervals.
In this way, by setting a threshold value for judging that the road surface is rough based on the road surface information of the driving route, the road surface roughness of the current driving route can be flexibly changed according to the road conditions. Intervals and non-coarse (smooth) intervals with low cabin noise can be predicted.
In step S3, the vehicle interior sound prediction means 1a acquires the distance to the section where the road surface roughness is rough.
In step S4, the vehicle interior sound prediction means 1a acquires the current state of charge (SOC) of the battery 4 and the gradient information (travel load) of the current travel route.
The state of charge (SOC) information of the battery 4 to be acquired is for predicting the distance traveled by the drive motor 5, and the gradient information is for predicting the travel load (the degree of decrease in the state of charge (SOC) of the battery 4).
In step S5, the vehicle interior sound prediction means 1a starts the engine 2 from the road surface information, the state of charge (SOC) of the battery 4, and the gradient information obtained up to the section where the road surface roughness is rough (the vehicle interior sound is high). It is determined whether or not it is possible to travel by the drive motor 5 in the off state.
If the drive motor 5 can run without starting the engine 2 up to a section where the road surface is rough (vehicle noise is loud), the process proceeds to step S6, where the road surface is rough (vehicle noise is loud). When it is not possible to run the vehicle by the driving motor 5 without starting the engine 2 until the section, the process returns to step S1.
In step S6, the priority control means 1b implements traveling by the drive motor 5 without starting the engine 2. FIG.
In step 7, the threshold for starting the engine 2 based on the required driving force (the amount of depression of the accelerator pedal by the driver) (threshold of the amount of depression of the accelerator pedal by the driver) is set high.
As a result, it is possible to prevent the engine 2 from being started even when the driver slightly depresses the accelerator pedal.

In step S8, whether or not the vehicle speed of the host vehicle is equal to or greater than a threshold value (eg, 40 km/h), and whether the required driving force (the amount of depression of the accelerator pedal by the driver) is equal to or greater than the engine start threshold value (eg, 1/4 opening). whether the current state of charge (SOC) of the battery 4 is equal to or less than a specified lower limit threshold; whether the current section is a section (prediction) with rough road surface (vehicle noise is high); determine whether or not
When the vehicle speed is a threshold value (for example, 40 km/h) or more, or when the required driving force (the amount of depression of the accelerator pedal by the driver) is an engine start threshold value (for example, 1/4 opening) or more, the current battery 4 When the state of charge (SOC) is equal to or lower than the lower limit threshold, or when the road surface is rough (vehicle noise is loud) in the current driving section (prediction), the process proceeds to step S9. Proceed, and if none of the conditions are satisfied, return to step S6.
When the vehicle speed is above a threshold value (for example, 40 km/h), wind noise increases, and when the required driving force (the amount of accelerator pedal depression by the driver) is above the engine start threshold value (for example, 1/4 opening), , it is necessary to generate electricity by starting the engine 2 in order to increase the driving force. This is because it is necessary to generate power by starting the engine, and as a result, it becomes a section where the cabin sound is high.
In step S9, the priority control means 1b starts the engine 2, drives the generator 3 to generate electricity, and starts charging the battery 4. FIG.
In step S10, it is determined whether or not the current state of charge (SOC) of the battery 4 is equal to or lower than the upper limit threshold.
When the current SOC of the battery 4 is equal to or less than the upper threshold, the process proceeds to step S11, and when the current state of charge (SOC) of the battery 4 is not equal to or less than the upper threshold, the process returns to step S1.
In step S11, it is determined whether or not the section in which the vehicle is currently traveling is a section (prediction) with rough road surface (vehicle noise is high).
If the current section is a section with rough road surface roughness (vehicle noise is high) (prediction), the process proceeds to step S12, and the road section with rough road surface is rough (vehicle noise is high). high) section (prediction), the process returns to step S1.
In step S12, it is determined whether or not the vehicle has arrived at the destination.
When the destination has been reached, the control ends, and when the destination has not been reached, the process returns to step S1.

FIG. 3 is a first time chart showing an example of execution of control processing according to the first embodiment.

The horizontal axis is time, the top is the predicted road surface condition, the actual road surface condition, the vehicle speed, the state of charge (SOC) of the battery 4 having upper and lower thresholds that are the usable range, and the engine. 2 state changes.
As for changes in the state of charge (SOC) of the battery 4 and the state of the engine 2, the solid line indicates the first embodiment, and the broken line indicates the comparative example.

In the first embodiment, the section from time t0 to time t2 is a smooth road surface (low vehicle interior noise), the section from time t2 to time t4 is a rough road surface (high vehicle interior noise), and time t4. It is predicted that the road surface is not rough and smooth (vehicle noise is low) from time t7 until arrival at the destination.
Note that the actual road surface condition matches the predicted road surface condition.
For this reason, in the first embodiment, the priority control means 1b judges that it is possible to run by the drive motor 5 without starting the engine 2 until the rough road surface (vehicle noise is high) starting from time t2. (Step S5 in FIG. 2), from time t0 to time t2, the vehicle is driven by the driving motor 5 without starting the engine 2 (Step S6 in FIG. 2).
Shortly before time t2 and from time t4 to time t5, the vehicle decelerates and the battery 4 is charged by regeneration, so the state of charge (SOC) of the battery 4 is increased.
In this way, when the deceleration timing of the host vehicle can be predicted, the stop timing of the engine 2 is determined in consideration of regenerative charging due to deceleration.
As a result, the time during which the engine 2 is started can be shortened, so that the driver can enjoy more quiet driving.
From time t2 to time t4, the road surface is rough (vehicle noise is high), so the priority control means 1b starts the engine 2, drives the generator 3 to generate electricity, and charges the battery 4. (step S9 in FIG. 2).
As a result, since this is a rough road section, the vehicle interior noise is high, and even if the engine 2 is started, the generator 3 is driven to generate electricity, and the battery 4 is charged, the engine noise is loud to the driver. can be suppressed.
Also, until time t4, the state of charge (SOC) of the battery 4 can be charged close to the upper threshold, and the engine 2 will not be started in the next section of the road surface that is not rough and smooth (vehicle noise is low). It is possible to travel by the drive motor 5 in this state.
From time t4 to time t7 when the vehicle arrives at the destination, it is predicted that the road surface is not rough and smooth (vehicle noise is low). (Step S6 in FIG. 2).
At time t7, the vehicle arrives at the destination, so control ends (step S12 in FIG. 2).

On the other hand, in the comparative example, although the road surface is not rough and smooth (vehicle noise is low), during the period from time t0 to time t1, from time t2 to time t3, and from time t5 to time t5, During t6, the host vehicle starts accelerating (the accelerator pedal is greatly depressed by the driver's operation), so the engine is started, the generator 3 is driven to generate electricity, and the battery 4 is charged.
For this reason, the engine is started even though the road surface is not rough and smooth (vehicle noise is low), and the engine noise becomes noise to the driver.

Next, functions and effects will be described.
The hybrid vehicle control method and the hybrid vehicle control apparatus of the first embodiment have the following effects.

(1) The vehicle interior sound prediction means 1a predicts the road surface roughness of the current travel route between a rough section with high vehicle interior sound and a non-rough (smooth) section with low vehicle interior sound, and predicts the predicted vehicle interior sound. Based on the level, the priority control means 1b gives priority to driving by the drive motor 5 in a state where the engine 2 is not started in a non-rough (smooth) section with a low cabin sound that precedes a rough section with a high cabin sound. and set it to run.
Therefore, on a road with low cabin noise, it is possible to run with the drive motor 5 in a state where the engine 2 is not started, and in the subsequent section where the cabin noise is high, the engine 2 is started and the generator 3 is driven. As a result, the driver is less likely to feel noise, vibration, etc., when the engine is started, and can fully enjoy quiet driving in sections where the vehicle interior noise is low. .

(2) The vehicle interior sound prediction means 1a receives information from the navigation system 8 about the current travel route from the current location to the destination, and also from the external data center and other vehicles 11 via the navigation system 8 and the on-board communication device 10. Acquired the road surface information (road surface roughness) of the route.
Therefore, it is possible to improve the accuracy of predicting the level of the vehicle interior sound.

(3) The vehicle interior sound prediction means 1a sets a threshold for judging that the road surface is rough from the obtained road surface information (road surface roughness) of the current driving route, and sets the road surface roughness of the current driving route as the threshold. Based on this, the rough section with high cabin noise and the non-coarse (smooth) section with low cabin noise are predicted.
Therefore, by setting a threshold for judging that the road surface is rough based on the road surface information of the driving route, the road surface roughness of the current driving route can be flexibly changed according to the conditions of the driving route. Intervals and non-coarse (smooth) intervals with low cabin noise can be predicted.

(4) When the travel route from the current location to the destination is not set in the navigation system 8, the vehicle interior sound prediction means 1a determines that the current travel route is the same travel route via the navigation system 8 and the in-vehicle communication device 10. When it is determined that the current travel route is a non-branching section from the information from the other vehicle 11 traveling ahead on the route, a threshold for determining that the road surface is rough on the travel route until the branch. is set, and the road surface roughness of the current driving route is predicted to be a rough section with high cabin noise and a non-rough (smooth) section with low cabin noise.
Therefore, by setting a threshold for judging that the road surface is rough based on the road surface information of the driving route, the road surface roughness of the current driving route can be flexibly changed according to the conditions of the driving route. It is possible to predict sections and non-rough (smooth) sections in which the vehicle interior noise is low, and increase the chances of prediction, so that the driver can enjoy quieter driving.

(5) When the deceleration timing of the own vehicle can be predicted, the stop timing of the engine 2 is determined in consideration of regenerative charging due to deceleration.
Therefore, the time during which the engine 2 is started can be shortened, so that the driver can enjoy more quiet driving.

FIG. 4 is a flow chart showing the flow of control processing according to the second embodiment.
That is, it shows the flow of control processing of the system controller 1 having the vehicle interior sound prediction means 1a and the priority control means 1b.
This flowchart is repeatedly executed at a predetermined calculation cycle.

Unlike the first embodiment, in step S8a, detection information (sensor values) from the vehicle interior sound sensor 12, the displacement sensor 13 for detecting vertical movement of the vehicle, and the acceleration sensor 14 for detecting vertical movement of the vehicle are Based on this, it is determined whether or not the vehicle is traveling on a section with rough road surface (vehicle noise is high).
In particular, when the actual vehicle vibration increases and the state of charge (SOC) of the battery is equal to or lower than the lower threshold, the engine is started, the generator 3 is driven to generate electricity, and the battery 4 is charged.
Since the actual vehicle vibration is large, it is difficult for the driver to feel the noise, vibration, etc. at the time of starting the engine.
Since other configurations are the same as those of the first embodiment, steps common to the first embodiment are denoted by the same reference numerals as those of the first embodiment, and description thereof is omitted.

FIG. 5 is a time chart showing an example of execution of control processing according to the second embodiment.

The horizontal axis is time, the top is the predicted road surface condition, the next is the actual road surface condition based on the detection information (sensor values) from the vehicle interior sound sensor 12, the displacement sensor 13, and the acceleration sensor 14, the vehicle speed, It shows changes in the state of charge (SOC) of the battery 4 and the state of the engine 2 having upper and lower thresholds that are the usable range.
As for changes in the state of charge (SOC) of the battery 4 and the state of the engine 2, the solid line indicates the second embodiment, and the dashed line indicates the first embodiment.

At time t1a, in the road surface condition predicted in the first embodiment, it is predicted that the vehicle interior sound is low and not rough (smooth), but the detection from the vehicle interior sound sensor 12, the displacement amount sensor 13, and the acceleration sensor 14 According to the information (sensor value), the vehicle is actually running in a rough section where the cabin noise is high. is driven to generate power, and the battery 4 is charged (step S9 in FIG. 4).
In this way, even if the prediction is wrong, it is possible to perform accurate control by detecting the actual state.
It should be noted that cases where the prediction is wrong include noise due to road construction, deterioration of the road surface, joints of expressways, road noise due to uneven roads, and the like.

Next, functions and effects will be described.
In addition to the effects of the first embodiment, the hybrid vehicle control method and the hybrid vehicle control apparatus of the second embodiment have the following effects.

(1) The vehicle interior sound sensor 12, the displacement sensor 13, and the acceleration sensor 14 are provided. It is determined whether or not the vehicle is traveling on a section with rough road surface (vehicle noise is high).
Therefore, even if the prediction is wrong, it is possible to perform accurate control by detecting the actual vehicle interior sound or the like.

(2) When the actual vehicle vibration increases and the state of charge (SOC) of the battery is below the lower limit threshold value, the detection information (sensor values) from the displacement amount sensor 13 (vibration sensor) and the acceleration sensor 14 (vibration sensor) increases. The engine is started, the generator 3 is driven to generate electricity, and the battery 4 is charged.
Therefore, since the actual vehicle vibration is large, it is difficult for the driver to perceive the noise, vibration, etc. at the time of starting the engine.

FIG. 6 is a flow chart showing the flow of control processing according to the third embodiment.
That is, it shows the flow of control processing of the system controller 1 having the vehicle interior sound prediction means 1a and the priority control means 1b.
This flowchart is repeatedly executed at a predetermined calculation cycle.

Unlike the first embodiment, steps S13 and S14 are added.
That is, in step S13, the road surface roughness is determined based on detection information (sensor values) from the vehicle interior sound sensor 12, the displacement sensor 13 for detecting vertical movement of the vehicle, and the acceleration sensor 14 for detecting vertical movement of the vehicle. It is determined whether or not the vehicle is traveling in a rough section (vehicle noise is high).
A displacement sensor 13 for detecting vertical movement of the vehicle as a vibration sensor and an acceleration sensor 14 for detecting vertical movement of the vehicle as a vibration sensor are used to detect the movement of the vehicle due to joints of highways, uneven roads, etc. Detect vertical movement.
When the vehicle is traveling on a section with rough road surface (cabin noise is loud), the process proceeds to step S9, and when not traveling on a section with rough road surface (cabin noise is high), the process proceeds to step S14.
In step S14, a timer (not shown) is used to determine whether or not the prediction and the detection information (sensor value) have deviated for a certain period of time or more.
When the prediction and the sensor value have diverged for a certain period of time or longer, the control is terminated.
That is, if the predicted cabin sound pitch interval deviates from the cabin sound pitch interval based on the information (sensor values) detected by the cabin sound sensor 12, the displacement sensor 13, and the acceleration sensor 14 for a certain period of time or longer, the prediction is made. Since the accuracy was poor, the control was returned to the normal control to improve the accuracy of the predictive control itself.
Since other configurations are the same as those of the first embodiment, steps common to the first embodiment are denoted by the same reference numerals as those of the first embodiment, and description thereof is omitted.

FIG. 7 is a time chart showing an example of execution of control processing according to the third embodiment.

The horizontal axis is time, and the top is the predicted road surface condition, and then the actual road surface condition, vehicle speed, and upper and lower threshold values that are the usable range based on information detected by the vehicle interior sound sensor 12 and the like. The change in the state of charge (SOC) of the battery 4 and the state of the engine 2 are shown.
As for changes in the state of charge (SOC) of the battery 4 and the state of the engine 2, the solid line indicates the third embodiment, and the dashed line indicates the first embodiment.

At time t2, the road surface condition predicted in the first embodiment is predicted to be a rough section with high cabin noise, but detection information (sensor value ), the vehicle is actually traveling in a section where the vehicle interior noise is low and not rough (smooth). Since the high-low section of the sound and the high-low section of the cabin sound based on the detection information (sensor value) deviate, the predictive control is terminated at time t3, and the engine 2 is stopped (step S14 in FIG. 6). .
In addition, at time t4, the road surface condition predicted in the first embodiment is predicted to be a non-rough (smooth) section with low cabin noise. According to the detection information (sensor value) of the vehicle, the vehicle is actually running in a rough section where the cabin noise is high. Therefore, in the third embodiment, the priority control means 1b predicts Since the high-low section of the cabin sound and the high-low section of the cabin sound based on the detection information (sensor value) deviate, at time t5, the predictive control is terminated and the engine 2 is started (step in FIG. 6). S14).
In this way, even if the predicted cabin sound pitch interval differs from the cabin sound pitch interval based on the detection information (sensor value), that is, even if the prediction is incorrect, accurate control is possible.

Next, functions and effects will be described.
In addition to the effects of the first embodiment, the hybrid vehicle control method and the hybrid vehicle control apparatus of the third embodiment have the following effects.
(1) The vehicle interior sound sensor 12, the displacement sensor 13, and the acceleration sensor 14 are provided, and based on the detection information (sensor values) from the vehicle interior sound sensor 12, the displacement sensor 13, and the acceleration sensor 14, prediction is performed for a certain period of time. Predictive control is terminated when there is a discrepancy between the high and low intervals of the cabin sound detected and the high and low intervals of the cabin sound based on the detection information (sensor value).
Therefore, even if the prediction is incorrect, accurate control can be achieved by detecting the actual vehicle interior sound and vertical movement of the own vehicle.

[Other embodiments]
Although the embodiments for carrying out the present invention have been described above, the specific configuration of the present invention is not limited to the configurations shown in the examples, and can be implemented without departing from the gist of the invention. Even if there is a design change, etc., it is included in the present invention.
For example, in the embodiment, a series hybrid vehicle has been described, but it goes without saying that the present invention can also be applied to other types of hybrid vehicles.
In addition, the present invention can be applied to both manually operated vehicles and automatically operated vehicles.

1 System controller (hybrid vehicle control device)
1a cabin sound prediction means 1b priority control means 2 engine 3 generator 4 battery 5 drive motor 8 navigation system 12 cabin sound sensor 13 displacement sensor (vibration sensor)
14 acceleration sensor (vibration sensor)

Claims (9)

a generator, an engine that drives the generator, a battery that is charged by the generator, and a driving motor that is driven by the battery for traveling;
In a hybrid vehicle control method for controlling traveling by the drive motor while the engine is not started on the current traveling route,
Predict the road surface roughness of the current driving route,
Based on the predicted road surface roughness, in a section where the road surface roughness is not rough prior to the section where the road surface roughness is rough, priority is given to driving by the drive motor in a state where the engine is not started;
setting a high threshold value for starting the engine based on the depression amount of the accelerator pedal in a section where the road surface roughness is not rough before the section where the road surface roughness is rough;
A hybrid vehicle control method characterized by: In the hybrid vehicle control method according to claim 1,
In the section where the road surface roughness is rough, the battery is charged by starting the engine and driving the generator.
A hybrid vehicle control method characterized by: In the hybrid vehicle control method according to claim 1,
In the prediction of the road surface roughness of the current driving route, the driving route information is obtained from the navigation system, and a threshold value for determining the road surface roughness of the current driving route is set.
A hybrid vehicle control method characterized by: In the hybrid vehicle control method according to claim 3 ,
When a travel route is not set in the navigation system and the vehicle is traveling along a non-branching travel route, the road surface roughness until branching is predicted based on the travel route information from the navigation system or another vehicle. ,
A hybrid vehicle control method characterized by: In the hybrid vehicle control method according to claim 4,
In the prediction of the road surface roughness of the travel route until the branching, the travel route information is obtained from the navigation system or the other vehicle, and a threshold is set for judging the road surface roughness of the travel route until the branch. do,
A hybrid vehicle control method characterized by: In the hybrid vehicle control method according to claim 1 ,
Acquire the actual vehicle sound information from the vehicle sound sensor,
When the actual cabin sound is high, the engine is started and the generator is driven to generate electricity;
A hybrid vehicle control method characterized by: In the hybrid vehicle control method according to claim 1,
Acquire the actual vehicle vibration information from the vibration sensor and the battery state of charge information,
When the actual vehicle vibration increases and the state of charge of the battery is lower than the specified value, the engine is started and the generator is driven to generate power.
A hybrid vehicle control method characterized by: In the hybrid vehicle control method according to claim 1,
Acquire sensor information from the vehicle interior sound sensor and vibration sensor,
Predictive control is terminated when the predicted road surface roughness and the high-low interval of the vehicle interior sound based on the sensor information deviate for a certain period of time.
A hybrid vehicle control method characterized by: a generator, an engine that drives the generator, a battery that is charged by the generator, and a driving motor that is driven by the battery for traveling;
A control device for a hybrid vehicle that controls travel by the drive motor while the engine is not started on the current travel route,
a road surface roughness prediction means for predicting the road surface roughness of the current travel route;
Based on the predicted road surface roughness, in a section where the road surface roughness is not rough prior to the section where the road surface roughness is rough, priority is given to driving by the drive motor in a state where the engine is not started, and the road surface roughness is increased . priority control means for setting a high threshold for starting the engine based on the amount of depression of the accelerator pedal in a section where the road surface roughness is not rough before the section where the road surface is rough;
A hybrid vehicle control device characterized by:

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