JP2002092137A - Life time prediction system and life time predicting method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a life time prediction system capable of exactly predicting and presenting the life of automobile components. SOLUTION: The life prediction system 10 is provided with a measurement value input part 12 for receiving a plurality of measurement values measured in at least two or more measurements and the number of the measurements about physical quantities to influence the life of the automotive components; a storage part 14 for storing the plurality of inputted measurement values and the number of measurements; a life predicting part 16 to calculate a regression line, based on the plurality of measurement values and the number of measurements stored in the storage part 14 and to predict the life time of the automotive components, based on the regression line; and a prediction result output part 18 to output the life time of the automotive components predicted by the life predicting part 16 to a printer 104, a display 102, etc.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a life prediction system for predicting the life of automobile parts.

[0002]

2. Description of the Related Art Automobile parts such as batteries and tires often need to be replaced depending on their life. The user of an automobile can usually know the average life of the parts of the automobile from the average life presented by the manufacturer when purchasing the automobile or the parts of the automobile. Also, after a certain period of time from when the car user purchased the car or auto parts, by direct mail, etc.
A method of recommending the user of the vehicle to replace the vehicle part has been proposed.

[0003]

However, the average life expectancy provided by a manufacturer or the like is merely an average life expectancy of parts of the automobile, and how the automobile user uses the automobile (for example, , Drive long distances daily, spend only on weekends, etc.)
The life of the parts of the vehicle varies greatly. That is,
For example, there is a problem in that the average life cannot be accurately predicted from the viewpoint of each automobile.
As a result, the user of the vehicle regularly or irregularly measures a physical quantity (for example, the discharge voltage of the battery) that affects the life of parts of the vehicle at a gas station or the like, and replaces the battery based on the measured value. Life management had to be done.

Accordingly, an object of the present invention is to solve the above-mentioned problems and to provide a life prediction system capable of accurately predicting and presenting the life of parts of an automobile.

[0005]

In order to solve the above-mentioned problems, a life estimating system of the present invention is a life estimating system for estimating the life of an automobile part, which affects the life of the automobile part. Measurement value input means for inputting a plurality of measurement values measured in at least two or more measurements for a physical quantity; storage means for storing the plurality of measurement values input by the measurement value input means; A service life estimating means for estimating the life of the vehicle component based on the plurality of stored measurement values; and a prediction result output means for outputting the service life of the vehicle component predicted by the life estimating means. It is characterized by that.

A plurality of measured values of at least two or more measured physical quantities that affect the life of a vehicle component are input and stored, and the life of the vehicle component is determined based on the plurality of measured values. , It is possible to predict not the average life but the life inherent in the vehicle component in consideration of the actual change of the physical quantity in the vehicle component. In addition, by outputting the predicted life, the predicted life can be presented to the user of the automobile part or the like.

In the life prediction system of the present invention, the measured value input means further inputs the measurement time of each of the plurality of measured values, and the storage means stores the time inputted by the measured value input means. The measurement time of each of the plurality of measured values is further stored, and the life expectancy predicting means is configured to calculate the life of the vehicle based on the plurality of measured values stored in the storing means and the time of each of the plurality of measured values. It is preferable to predict the life of the battery.

[0008] A plurality of measured values of at least two or more measured physical quantities that affect the life of a component of an automobile and the measured times of the plurality of measured values are input and stored, and the plurality of measured values are stored. The life of a vehicle component based on the measured value of the plurality of measured values and the measurement time of each of the plurality of measured values. Can be predicted.

Further, in the life prediction system of the present invention, the life prediction means is configured to determine the physical quantity based on the plurality of measured values stored in the storage means and when each of the plurality of measured values is measured. It is preferable to calculate a regression curve representing a change with time of the vehicle and predict the life of the parts of the vehicle based on the regression curve.

[0010] By calculating a regression curve representing a change with time of the physical quantity and estimating the life of the parts of the vehicle based on the regression curve, the change with time of the physical quantity in the parts of the car is considered. The service life inherent in the parts of the vehicle can be easily predicted.

In the life prediction system according to the present invention, the prediction result output means includes a plurality of measurement values stored in the storage means together with a life of the vehicle component predicted by the life prediction means. Of these, it is preferable to output the measured value at the latest measurement and the latest measurement time.

By outputting the latest measured time and the measured value at the time of the measurement together with the predicted life, the predicted life and the latest measured value and the measured value at the time of the measurement are converted to the parts of the automobile. Can be presented to other users or the like.

In the life prediction system of the present invention, the measured value input means further inputs the mileage of the vehicle at the time of measuring each of the plurality of measured values, and the storage means stores the measured value input. The driving distance of the vehicle at the time of measuring each of the plurality of measurement values input by the means is further stored, and the life prediction means includes the plurality of measurement values and the plurality of measurement values stored in the storage means. It is preferable that the life of the parts of the vehicle is predicted based on the traveling distance of the vehicle at each measurement.

[0014] A plurality of measured values of at least two or more measured physical quantities that affect the life of the parts of the vehicle and the mileage of the vehicle at each of the plurality of measurements are input and stored. By estimating the life of a vehicle component based on the plurality of measured values and the travel distance of the vehicle at each of the plurality of measurements, the change of the physical quantity of the vehicle in the vehicle component in consideration of the change in the travel distance is considered. The life expectancy inherent to the part can be predicted.

Further, in the life expectancy prediction system of the present invention, the life expectancy means includes a plurality of the measured values stored in the storage means and a travel distance of the vehicle at the time of measuring each of the plurality of measured values. It is preferable that a regression curve representing a change in the physical quantity according to the traveling distance is calculated based on the regression curve, and the life of parts of the vehicle is predicted based on the regression curve.

A change in the physical quantity of the vehicle due to the travel distance is taken into account by calculating a regression curve representing a change in the physical quantity according to the travel distance and estimating the life of the vehicle component based on the regression curve. It is possible to easily predict the service life inherent to the vehicle component.

Further, in the life prediction system of the present invention, the prediction result output means includes a plurality of the measured values stored in the storage means together with a life of the vehicle component predicted by the life prediction means. It is preferable to output the measured value at the latest measurement and the travel distance of the vehicle at the latest measurement.

By outputting the measured value and the mileage at the latest measurement together with the predicted life, the measured value and the mileage at the latest measurement together with the predicted life are calculated by the user of the above-mentioned automobile part. Etc. can be presented.

In the life prediction system according to the present invention, it is preferable that the prediction result output means displays and outputs the life of the vehicle component predicted by the life prediction means.

By displaying and outputting the predicted life, the predicted life can be easily presented to the user of the above-mentioned automobile parts.

Further, in the life prediction system of the present invention, the prediction result output means displays and outputs the life of the vehicle component predicted by the life prediction means to a terminal device connected via a network. It is preferable to have a feature.

By displaying and outputting the predicted life to a terminal device connected via a network, the predicted life can be presented to a user of a remotely located automobile component or the like.

In the life prediction system of the present invention, it is preferable that the prediction result output means prints out the life of the vehicle component predicted by the life prediction means.

By printing out the predicted life, the predicted life can be easily presented to the user of the above-mentioned automobile parts.

Further, in the life expectancy prediction system of the present invention, the measured value input means inputs the measured value by receiving the measured value transmitted from a measuring device for measuring the physical quantity. It is preferred to do so.

By inputting the measured value by receiving the measured value transmitted from the measuring device for measuring the physical quantity, there is no need to input the measured value manually using a keyboard or the like.

According to another aspect of the present invention, there is provided a life estimation method for estimating the life of an automobile part, wherein at least two physical quantities that affect the life of the automobile part are used. A measurement value input step of inputting a plurality of measurement values measured at the time of the above measurement, a storage step of storing the plurality of measurement values input in the measurement value input step in a storage unit, and the storage step A life prediction step of predicting the life of the vehicle component based on the plurality of measurement values stored in the storage unit; and a prediction result output step of outputting the life of the vehicle component predicted in the life prediction step. It is characterized by having.

A plurality of measured values measured in at least two or more measurements of physical quantities that affect the life of the parts of the vehicle are input and stored, and the life of the parts of the vehicle is determined based on the plurality of measured values. , It is possible to predict not the average life but the life inherent in the vehicle component in consideration of the actual change of the physical quantity in the vehicle component. In addition, by outputting the predicted life, the predicted life can be presented to the user of the automobile part or the like.

[0029]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A life prediction system according to an embodiment of the present invention will be described with reference to the drawings, and a life prediction method according to an embodiment of the present invention will be described.
First, the configuration of the life estimation system according to the present embodiment will be described. FIG. 1 is a configuration diagram of a life estimation system according to the present embodiment. The life prediction system according to the present embodiment is a life prediction system that predicts the life of parts of an automobile, and is installed at, for example, a gas station. In addition, the life prediction system according to the present embodiment can predict the life of various automobile parts such as a timing belt, an air conditioner, a battery, and a tire.
Here, a case where the lives of the battery and the tire are predicted will be described as an example.

As shown in FIG. 1, the life prediction system 10 includes a measured value input unit 12 (measured value input means) and a storage unit 1.
4 (storage means) and life estimation section 16 (life estimation means)
And a prediction result output unit 18 (prediction result output means). Hereinafter, each component will be described in detail.

The measured value input unit 12 inputs a plurality of measured values of at least two or more measured physical quantities that affect the life of parts of a vehicle.

For example, for a battery, the discharge voltage at the 5th second, which is a physical quantity that affects the life, is measured by the voltage measuring device 1.
The measured value of the discharge voltage measured at least at the time of two or more at the time of 00 and measured at the time of the at least two or more is input from the measured value input unit 12. For an automobile part whose life depends greatly on time, such as a battery, the measured value of the physical quantity (discharge voltage at the 5th second) affecting the life and the measurement time of each measured value are input from the measured value input unit 12. Is done.

Similarly, with respect to the tire, the groove remaining amount, which is a physical quantity affecting the life, is measured by the groove remaining amount measuring device 101 at least at the time of measurement, and is measured at the time of the at least two measurements. The measured value of the groove remaining amount is input from the measured value input unit 12. For automobile parts whose life greatly depends on the mileage of the vehicle, such as tires, the measured value of the physical quantity (groove remaining amount) that affects the life and the mileage of the vehicle at the time of each of the measured values are measured. It is input from the value input unit 12.

Here, the measurement value input section 12 inputs the measurement value by receiving the measurement value transmitted from the measuring device for measuring the physical quantity. More specifically, the voltage measuring device 100, the groove remaining amount measuring device 101, and the life prediction system 10 are connected via a wired or wireless network, and are transmitted from the voltage measuring device 100 via the network. When the measured value of the fifth-second discharge voltage is received by the measured value input unit 12, the measured value of the fifth-second discharge voltage is input to the measured value input unit 12. When the measurement value input unit 12 receives the measurement value of the groove remaining amount transmitted by the measurement unit, the measurement value of the groove remaining amount is input to the measurement value input unit 12. Here, the measured values of the physical quantity such as the discharge voltage at 5th second and the remaining amount of the groove are sequentially input when the physical quantity is measured at the gas station. When the part is purchased, an initial measurement value (or an initial standard value) of a physical quantity measured by a manufacturer or the like is input as a measurement value of the physical quantity. Here, the initial measurement value (or the initial standard value) of the physical quantity is input in advance from the measurement value input unit 12 and stored in the storage unit 1.
4 may be stored. In this case, at the time of purchase of the automobile part, by inputting information (automobile part code or the like) for specifying the automobile part, the initial value of the physical quantity stored in the storage unit 14 is obtained. A measured value (or an initial standard value) is specified, and the specified initial measured value is used as a measured value of the physical quantity.

The storage unit 14 stores the plurality of measured values input by the measured value input unit 12, the time when each of the plurality of measured values is measured, and the mileage of the vehicle at the time when each of the plurality of measured values is measured. . More specifically, the storage unit 1
4, a measurement history database 20 is stored.
FIG. 2 is a configuration diagram of the measurement history database 20. As shown in FIG. 2, the measurement history database 20 includes customer information, purchase histories of automobile parts, and the life of each automobile part for each of a plurality of customers who use the life estimation system 10. Is stored. More specifically, the measurement history database 20 stores the customer number of the customer as the customer information. , Name, address, telephone number, car name and car number of the car to be used are stored. In addition, the measurement history database 20 stores the part name, the product name, and the purchase date of the automobile part purchased by the customer as the automobile part purchase history. Further, the measurement history database 20
For each automobile part, the measurement history of the physical quantity that affects the life of the automobile part is given as the measurement target name, the physical quantity that affects the life of the automobile part (measurement item), the measurement date of the physical quantity (measurement time). ), A measured value, a life value, a predicted life, a name of a measurer (or a person in charge code), a name of a measuring device (or a device code), and a comment by the measurer are stored. For automobile parts whose life depends greatly on the traveling distance of the vehicle, such as tires, the measured values of the physical quantities are stored together with the traveling distance of the vehicle at the time of measuring the measured values. Here, the life value is a value of the above physical quantity which is considered to be the life of the automobile part. Further, the predicted life is the life of the vehicle component predicted based on the plurality of measured values stored in the storage unit 14. The method of calculating the predicted life will be described later. In the column of expected life at the time of purchase of the part (at the time of the first measurement), an average life published by a manufacturer or the like is stored. Here, the measurement date, measurement value,
Regarding the name of the measurer, the name of the measuring device, the comment by the measurer, and the mileage, data on a plurality of measurement dates are stored.

Returning to FIG. 1, the life predicting section 16 predicts the life of the parts of the vehicle based on the plurality of measured values stored in the storage section 14. More specifically, the life prediction unit 16 calculates a plurality of physical quantities (fifth-second discharge voltage) stored in the measurement history database 20 of the storage unit 14 for an automobile part whose life greatly depends on time, such as a battery. Based on the measured value and the measurement time of each of the plurality of measured values of the physical quantity (discharge voltage at the 5th second), the physical quantity (5
A regression line representing a change with time of the second discharge voltage) is calculated, and the life of the automobile component is predicted based on the regression line.

On the other hand, the life predicting unit 16 calculates a plurality of physical quantities (remaining grooves) stored in the measurement history database 20 of the storage unit 14 for automobile parts whose life greatly depends on the traveling distance of the vehicle such as tires. Of the physical quantity (remaining groove) based on the measured value of the vehicle and the traveling distance of the vehicle at the time of measuring each of the plurality of measured values of the physical quantity (remaining groove).
, A regression line representing the change due to the travel distance is calculated, and the life of the automobile component is predicted based on the regression line. Less than,
A specific description will be given by taking data stored in the measurement history database 20 shown in FIG. 2 as an example.

In estimating the life of the battery, the life estimating unit 16 first calculates a plurality of pairs of the measurement time and the measured value of the discharge voltage at the fifth second already stored in the measurement history database 20 of the storage unit 14. It is read from the measurement history database 20 of the storage unit 14. That is, when estimating the life of the battery after October 1, 1998 and before April 1, 1999, a set of the already obtained fifth-second discharge voltage measurement value and the measured value (hereinafter, referred to as a “between”) is used. (At the time of measurement, measured value)
) Is (April 1, 1998, 10.20
V) and (October 1, 1998, 10.10 V)
Therefore, the life prediction unit 16 reads out the pair of the two measurement times and the measurement values from the measurement history database 20 of the storage unit 14. Subsequently, the life predicting unit 16 reads out the 2 from the measurement history database 20 of the storage unit 14.
A regression line indicating the relationship between the time and the discharge voltage at the 5th second as shown in FIG. 3 is calculated using a set of the two measurement times and the measured values. Subsequently, the life predicting unit 16 determines that the discharge voltage at the 5th second is the value (lifetime value) of the discharge voltage at the 5th second, which is considered to be the life of the battery, in the regression line calculated as described above.
Calculate the time to be 3V. This time is shown in FIG.
As shown in the figure, it is 54 months. Here, as shown in FIG. 2, since the battery was purchased on April 1, 1998, the life expectancy predicting unit 16 predicts October 2002, which has passed 54 months from April 1, 1998. Calculate as life.

Similarly, when predicting the life of the battery after April 1, 1999 and before April 1, 2000, the time between the measurement of the already obtained fifth-second discharge voltage and the measured value is assumed. The pairs are (April 1, 1998, 10.20 V), (October 1, 1998, 10.10 V) and (1999
(April 1, 1995, 9.95 V), the life prediction unit 16 reads the set of the three measurement times and the measured values from the measurement history database 20 of the storage unit 14, and A regression line indicating the relationship between the time and the discharge voltage at the 5th second as shown in FIG. 4 is calculated using a set of the two measurement times and the measured values, and the time at which the discharge voltage at the 5th second becomes 9.3 V is calculated. Is calculated. This time is 44 months, as shown in FIG. Here, since the battery was purchased on April 1, 1998, as shown in FIG.
6 is 200 months after 44 months from April 1, 1998
One year and 12 months are calculated as the predicted life.

Similarly, when estimating the life of the battery after April 1, 2000, the combination of the already obtained fifth-second discharge voltage measurement value and the measured value is (April 1, 1998)
Date, 10.20 V) and (October 1, 1998, 10.
10V), (April 1, 1999, 9.95V) and (2
(April 1, 000, 9.60V)
The life prediction unit 16 reads the set of the four measurement times and measured values from the measurement history database 20 of the storage unit 14 and uses the set of the four measurement times and measured values as shown in FIG. A regression line indicating the relationship between the time and the discharge voltage at the 5th second is calculated, and the time at which the discharge voltage at the 5th second becomes 9.3V is calculated. This time is 37 months, as shown in FIG. Here, as shown in FIG. 2, since the battery was purchased on April 1, 1998, the life expectancy predicting unit 16 predicts May 2001, which has passed 37 months from April 1, 1998. Calculate as life. As described above, when a new measured value is obtained, the life predicting unit 16 can calculate the predicted life in consideration of the new measured value. Therefore, each time a new measured value is obtained, the accuracy of the predicted life is improved.

When estimating the life of the tire, the life estimating unit 16 first determines the measured value of the groove remaining amount stored in the measurement history database 20 of the storage unit 14 and the vehicle value at the time of measuring the measured value. A plurality of pairs with the traveling distance are read from the measurement history database 20 of the storage unit 14.
That is, when the life of a tire is predicted after October 1, 1998, a set of a measured value of the remaining groove amount already obtained and a mileage of the vehicle at the time of measuring the measured value (hereinafter referred to as (mileage) , Measured value)) is (0 km,
8.0mm) and (30000km, 3.8mm)
Therefore, the life prediction unit 16 reads the pair of the two travel distances and the measured value from the measurement history database 20 of the storage unit 14. Subsequently, the life prediction unit 16 uses the pair of the two travel distances and the measured values read from the measurement history database 20 of the storage unit 14 to calculate the travel distance and the remaining groove amount as shown in FIG. A regression line indicating the relationship is calculated. Subsequently, the life predicting unit 16 calculates a traveling distance in the regression line calculated as described above such that the remaining groove length becomes 2.5 mm, which is the value (life value) of the remaining groove considered to be the life of the tire. The travel distance is defined as the predicted life of the tire. The running distance is 39000 as shown in FIG.
km.

The prediction result output section 18 outputs the life of the vehicle component predicted by the life prediction section 16. The prediction result output unit 18 also displays the measured values of the physical quantities stored in the storage unit 14 (including the measured values at the time of the latest measurement), the measured values of the measured values, The vehicle travel distance at the time of measurement is output. More specifically, the prediction result output unit 18 sets the predicted life, the measured value of the physical quantity, the measurement value of the measured value, and the mileage of the vehicle at the time of the measurement at the gas station according to an instruction from the user. Output to a display 102 connected to the life expectancy prediction system 10 or printed out to a printer 104 installed at a gas station and connected to the life prediction system 10 or a network 10 such as the Internet.
The display is output to a customer terminal device (a personal computer, a mobile phone, a car navigation terminal device having a communication function, or the like) connected to the life expectancy system 10 via the communication terminal 6. The prediction result output unit 18 also measures the predicted life and the physical quantity at arbitrary timing, such as when a new predicted life is calculated by the life prediction unit 16 or when an output instruction is input from the user. When the measurement value is measured, the mileage of the vehicle at the time of the measurement is output. The prediction result output unit 18 also outputs the life prediction unit 1
6 when the life expectancy calculated by Step 6 is a certain period before, or when the life expectancy is a certain distance before the life expectancy, or when the difference between the life and the physical quantity affecting the life of the automobile part is constant. When the value (or the ratio is a constant value), the predicted life, the measured value of the physical quantity, the measurement value of the measured value, and the travel distance of the vehicle at the time of the measurement may be output. By doing so, the customer can know that the service life of his / her automobile parts is near.
Note that whether or not the difference between the physical quantity that affects the life of the automobile component and the life value has become a constant value can be calculated from the above-described regression line.

More specifically, the prediction result output unit 18
For example, a service sheet 22 as shown in FIG. That is, the service sheet 22 includes the issue date of the service sheet 22, the name of the customer, the name of the part for managing the life, the product name of the part, the purchase date of the part, and the inspection date of the part (that is, the life of the part is affected). Are printed, the inspection items of the part (that is, the physical quantities that affect the life of the part), the mileage at the time of inspection, the expected life, and the like are printed. Further, on the service sheet 22, a comment on the state of each automobile part is printed.
In order to print such a comment, a plurality of comment sentences corresponding to the state of each automobile part are stored in the storage unit 14 in advance.
If any one of the plurality of comment statements is automatically selected based on the measured physical quantity value (or the predicted physical quantity value) and printed, Good. Further, the service sheet 22 prints the fuel efficiency of the vehicle during a specific period. In order to print the fuel efficiency of such a vehicle, when the vehicle refuels at a gas station,
The refueling amount and the travel distance at the time of refueling may be stored in the storage unit 14, and the fuel efficiency may be calculated based on the relationship between the refueling amount and the travel distance and printed.

Next, the operation and effect of the life prediction system according to the present embodiment will be described. The life expectancy prediction system 10 inputs a plurality of measured values of at least two or more measured physical quantities that affect the life of an automobile component from the measured value input unit 12 and stores them in the storage unit 20.
Is stored in the measurement history database 20, and the life predicting unit 16 predicts the life of the parts of the vehicle based on the plurality of measured values. Therefore, it is possible to predict not the average life but the life inherent in the vehicle component in consideration of the actual change of the physical quantity in the vehicle component. In addition, the life prediction system 10 outputs the life predicted by the life prediction unit 16 by the prediction result output unit 18. Therefore, the predicted life can be presented to the user of the above-mentioned automobile parts. As a result, it is possible to accurately predict and present the life of the parts of the vehicle.

The life expectancy prediction system 10 is a component of an automobile (for example, a battery) whose life greatly depends on time.
With respect to a physical quantity that affects the life of a component of an automobile, a plurality of measured values measured in at least two or more measurement times and the respective measurement times of the plurality of measured values are input from the measured value input unit 12 and stored. The life estimation unit 16 stores the measurement history in the measurement history database 20 and estimates the life of the parts of the vehicle based on the plurality of measured values and the measurement time of each of the plurality of measured values. Therefore, it is possible to predict the life span unique to the vehicle component in consideration of the change with time of the physical quantity in the vehicle component. As a result, it is possible to more accurately predict the life of an automobile component (for example, a battery) whose life depends greatly on time. Further, the life expectancy prediction system 10
The life prediction unit 16 calculates a regression line representing the change of the physical quantity with time, and predicts the life of the parts of the vehicle based on the regression line. It is possible to easily predict the service life inherent to the vehicle component.

The life expectancy prediction system 10 is used to measure at least two or more physical quantities that affect the life of an automobile component (for example, tires) of an automobile component whose life depends greatly on the mileage of the automobile. The plurality of measured values and the mileage of the vehicle at each of the plurality of measurements are input from the measured value input unit 12 and stored in the measurement history database 20 of the storage unit 14,
The life prediction unit 16 predicts the life of parts of the vehicle based on the plurality of measured values and the traveling distance of the vehicle at each of the plurality of measurements. Therefore, it is possible to predict the life span unique to the vehicle component in consideration of the change in the physical quantity of the vehicle component due to the traveling distance. As a result, it is possible to more accurately predict the life of an automobile component (for example, a tire) whose life depends greatly on the traveling distance. Furthermore, in the life prediction system 10, the life prediction unit 16 calculates a regression line representing a change in the physical quantity according to the traveling distance, and predicts the life of parts of the vehicle based on the regression line. It is possible to easily predict the service life inherent to the part of the vehicle in consideration of the change in the physical quantity of the part due to the traveling distance.

In the life expectancy prediction system 10,
The prediction result output unit 18 outputs the measured value of the physical quantity (particularly the measured value at the latest measurement), the measured value of the measured value, the mileage at the time of the measurement, and the like, together with the life predicted by the life predicting unit. Thus, these pieces of information can be presented to the user of the above-mentioned automobile parts. As a result, convenience is improved.

In the life expectancy prediction system 10, the prediction result output section 18 displays the life predicted by the life estimation section 16 on the display 102 installed in the gas station.
, It is possible to easily present the predicted life to the user of the parts of the automobile and the staff of the gas station.

In the life prediction system 10, the prediction result output unit 18 outputs the life predicted by the life prediction unit 16 to the terminal device 10 connected via the network 106.
8, the predicted life can be presented to a user or the like of the remotely located automobile part. As a result, the user can refer to the predicted life without going to a place where the life prediction system 10 is installed, such as a gas station,
Convenience is improved.

In the life prediction system 10, the prediction result output unit 18 prints out the life predicted by the life prediction unit 16 to the printer 104 installed in the gas station so that the predicted life is output. It can be easily presented to the user of the automobile parts and the staff of the gas station. In this case, the printed life can be sent to the user by direct mail or the like.

In addition, the life expectancy prediction system 10 is configured such that the measured value input unit 12 inputs the measured value by receiving the measured value transmitted from the measuring device for measuring the physical quantity, and the measured value input unit 12 manually inputs the measured value using a keyboard or the like. This eliminates the need to input the measurement value via the, and the convenience is improved.

Although the life expectancy prediction system 10 according to the above embodiment is installed in a gas station,
For example, as shown in FIG. 8, a service life prediction system 10 is installed at a management center or the like provided outside a gas station, and a voltage measuring device 100, a groove remaining amount measuring device 101, and a display 102 are arranged at the gas station. , A printer 104 or the like via a network 110 can be adopted. By employing such an embodiment, it is possible to collectively manage the measured values measured at a plurality of gas stations. In this case, in the management center, an initial measurement value (or an initial standard value) used as the first measurement value of the physical quantity may be collectively input for each of the plurality of automobile parts. In addition, by installing a printer or the like in the management center and printing and outputting, it is possible to send the predicted life to the user or the like by direct mail or the like. In this case, the sending of the direct mail and the sending of the bill for use may be combined.

The life expectancy prediction system 10 according to the above-described embodiment uses a regression line when calculating the life expectancy. However, this is based on a quadratic function, A regression curve such as a cubic function may be used.

Further, the life prediction system 10 according to the above embodiment predicts the life of an automobile component using all the physical quantities that have been measured and obtained. May be used to predict the life of an automobile component. When there are three or more physical quantities that have already been measured and obtained, the latest two physical quantities are used to predict the lifespan of the vehicle components, so that it is possible to get closer (regardless of the distant past usage of the automobile). Life prediction that strongly reflects the vehicle usage pattern.

The service life prediction system 10 according to the above embodiment predicts the service life of the battery from the measured value of the discharge voltage at the 5th second and the service life of the tire from the measured value of the remaining groove. In a similar manner, it is also possible to predict the life of other automobile parts from other physical quantities. For example, it is also possible to predict the life of lubricating oils such as engine oils and gear oils from measured values of physical quantities such as total acid value, viscosity, light transmittance, light reflectivity, and conductivity. Also, automatic transmission fluid (AT) can be obtained from measured values of physical quantities such as total acid value, viscosity, light transmittance, light reflectivity, and conductivity.
It is also possible to predict the lifetime of F). It is also possible to predict the life of the tire from the measured value of the degree of cure of the rubber. Further, it is also possible to predict the life of the battery from the specific gravity of the battery liquid.

Further, the life expectancy prediction system 10 according to the above-described embodiment includes a tire air pressure, an amount of battery fluid, a deflection amount of a timing belt and a V-belt, a temperature of an outlet of a car air conditioner, an air conditioner gas pressure (service for charging a refrigerant) Valves (pressure values by two gauge manifolds of high pressure and low pressure), CO gas, HC gas, NO in exhaust gas
The concentration or the like of each of the _X gases may be sequentially measured, and the measured values may be presented to the user. By presenting such measured values to the user, the user can know the state of his or her vehicle.

[0057]

According to the life prediction system and the life prediction method of the present invention, a plurality of measured values of at least two or more measured physical quantities that affect the life of an automobile component are inputted and stored. And predicting the life of the vehicle component based on the plurality of measured values. Therefore, it is possible to predict not the average life but the life inherent in the vehicle component in consideration of the actual change of the physical quantity in the vehicle component. In addition, the life expectancy prediction system of the present invention outputs the life expectancy. Therefore, the predicted life can be presented to the user of the above-mentioned automobile parts. As a result, it is possible to accurately predict and present the life of the parts of the vehicle.

Further, in the life expectancy predicting system of the present invention, a plurality of measured values of at least two or more measured physical quantities that affect the life of a component of an automobile and the time of measurement of each of the plurality of measured values. Is input and stored, and the life of the vehicle component is predicted based on the plurality of measured values and the measurement time of each of the plurality of measured values. In consideration of the above, it is possible to predict the life span unique to the vehicle component. As a result, the life can be more accurately predicted, especially for automotive parts whose life depends greatly on time.

Further, in the life prediction system of the present invention, a regression curve representing a change in the physical quantity with time is calculated, and the life of the parts of the vehicle is predicted based on the regression curve. It is possible to easily predict the service life inherent in the parts of the vehicle in consideration of the change with time of the physical quantity in the above.

Further, in the life expectancy predicting system of the present invention, by outputting the latest measurement time and the measured value at the time of the measurement together with the predicted life, the predicted life and the latest measurement time and the relevant value are output. The measured values at the time of measurement can be presented to the user of the above-mentioned automobile parts. As a result, convenience is improved.

Further, in the life expectancy prediction system of the present invention, a plurality of measured values of at least two or more measured physical quantities that affect the life of the parts of the automobile and the running of the automobile at each of the plurality of measurements are measured. The distance is input and stored, and the life of the vehicle component is predicted based on the plurality of measured values and the traveling distance of the vehicle at each of the plurality of measurements. It is possible to predict the service life inherent to the parts of the vehicle in consideration of the change due to the traveling distance of the vehicle. As a result, the life can be more accurately predicted, particularly for parts of an automobile whose life depends greatly on the mileage.

Further, in the life expectancy prediction system of the present invention, a regression curve representing a change in the physical quantity according to the traveling distance is calculated, and the life expectancy of the parts of the automobile is predicted based on the regression curve. It is possible to easily predict the service life inherent to the part of the vehicle in consideration of the change in the physical quantity of the part due to the traveling distance.

Further, in the life expectancy prediction system of the present invention, the predicted life and the measured value at the latest measurement and the traveling distance are output, so that the predicted life and the measured value at the latest measurement are output. And the traveling distance can be presented to the user of the above-mentioned automobile parts. As a result, convenience is improved.

Further, in the life prediction system of the present invention, the predicted life is displayed and output, so that the predicted life can be easily presented to the user of the parts of the automobile.

Also, in the life expectancy prediction system of the present invention, the predicted life is displayed and output on a terminal device connected via a network, so that the predicted life can be obtained from the parts of the vehicle located remotely. It can be presented to a user or the like. As a result, the user can refer to the predicted life without going to a place where the life prediction system is arranged, such as a gas station, and the convenience is improved.

Further, in the life expectancy prediction system of the present invention, by printing out the life expectancy, the life expectancy can be easily presented to the user of the above-mentioned automobile parts. In this case, the printed life can be sent to the user by direct mail or the like.

Further, in the life expectancy prediction system of the present invention, by inputting the measured value by receiving the measured value transmitted from the measuring device for measuring the physical quantity, the measured value is manually input using a keyboard or the like. There is no need to input measured values, and convenience is improved.

[Brief description of the drawings]

FIG. 1 is a configuration diagram of a life prediction system.

FIG. 2 is a configuration diagram of a measurement history database.

FIG. 3 is a diagram showing a relationship between time and a discharge voltage at the 5th second.

FIG. 4 is a diagram showing a relationship between time and a discharge voltage at the 5th second.

FIG. 5 is a diagram showing a relationship between time and a discharge voltage at the 5th second.

FIG. 6 is a diagram showing a relationship between a traveling distance and a groove remaining amount.

FIG. 7 is a configuration diagram of a service sheet.

FIG. 8 is a configuration diagram of a life estimation system.

[Explanation of symbols]

10: life expectancy prediction system, 12: measured value input unit, 14 ...
Storage unit, 16: Life prediction unit, 18: Prediction result output unit, 2
0: Measurement history database

Continuing on the front page (72) Inventor Seiichiro Takahashi 1-3-12 Nishi-Shimbashi, Minato-ku, Tokyo Business Planning Division, Nisseki Mitsubishi Co., Ltd. (72) Inventor Seiji Maeda 1-3-3 Nishi-Shimbashi, Minato-ku, Tokyo No. 12 Nishiishi Mitsubishi Co., Ltd. Technology Development Department F-term (reference) 3D026 BA21 BA28 5B049 CC00

Claims (12)

[Claims] 1. A life prediction system for predicting the life of a vehicle component, comprising: inputting a plurality of measured values of at least two or more measurements of a physical quantity affecting the life of the vehicle component. Value input means; storage means for storing the plurality of measurement values input by the measurement value input means; and estimating the life of the vehicle component based on the plurality of measurement values stored in the storage means. A life prediction system comprising: a life prediction unit that performs life prediction; and a prediction result output unit that outputs the life of the vehicle component predicted by the life prediction unit. 2. The measurement value input means further inputs a measurement time of each of the plurality of measurement values, and the storage means stores a measurement time of each of the plurality of measurement values input by the measurement value input means. Further, the life expectancy predicting means predicts the life of the vehicle component based on the plurality of measured values stored in the storing means and the time of measurement of each of the plurality of measured values. The life prediction system according to claim 1. 3. The method according to claim 1, wherein the life estimating unit calculates a regression curve representing a change with time of the physical quantity based on the plurality of measurement values stored in the storage unit and a measurement time of each of the plurality of measurement values. The life prediction system according to claim 2, wherein the life prediction is performed based on the regression curve. 4. The predictive result output means, together with the service life of the vehicle component predicted by the service life predicting means, the measured value at the latest measurement among the plurality of measured values stored in the storage means. 3. The life expectancy predicting system according to claim 2, wherein the system outputs the time and the latest measurement time. 5. The measurement value input unit further inputs a travel distance of the vehicle at the time of measuring each of the plurality of measurement values, and the storage unit stores the plurality of measurements input by the measurement value input unit. The driving distance of the vehicle at the time of measuring each of the values is further stored, and the life expectancy predicting unit is configured to drive the vehicle at the time of measuring each of the plurality of measured values and the plurality of measured values stored in the storing unit. The life prediction system according to claim 1, wherein the life prediction of the parts of the vehicle is predicted based on the distance. 6. The travel of the physical quantity based on the plurality of measured values stored in the storage unit and a travel distance of the vehicle at the time of measuring each of the plurality of measured values. The life prediction system according to claim 5, wherein a regression curve representing a change with distance is calculated, and the life of the vehicle component is predicted based on the regression curve. 7. The predicted result output means, together with the service life of the vehicle component predicted by the service life predicting means, the measured value at the time of the latest measurement among the plurality of measured values stored in the storage means. The life prediction system according to claim 5, wherein the system outputs the travel distance of the vehicle at the time of the latest measurement. 8. The life prediction system according to claim 1, wherein the prediction result output means displays and outputs the life of the parts of the vehicle predicted by the life prediction means. 9. The apparatus according to claim 8, wherein the prediction result output means displays and outputs the life of the vehicle component predicted by the life prediction means to a terminal device connected via a network. Life prediction system. 10. The life prediction system according to claim 1, wherein the prediction result output unit prints out the life of the vehicle component predicted by the life prediction unit. 11. The life estimation according to claim 1, wherein the measurement value input unit inputs the measurement value by receiving the measurement value transmitted from a measurement device that measures the physical quantity. system. 12. A life prediction method for predicting the life of a vehicle component, comprising: inputting a plurality of measured values of at least two or more measured physical quantities that affect the life of the vehicle component. A value input step; a storage step of storing the plurality of measurement values input in the measurement value input step in storage means; and the vehicle based on the plurality of measurement values stored in the storage means in the storage step. A life prediction step of predicting the life of the component, and a prediction result output step of outputting the life of the component of the vehicle predicted in the life prediction step.