KR102184590B1 - Apparatus and method of providing vehicle preventive maintenance service - Google Patents

Abstract

The vehicle preventive maintenance service providing device receives at least one vibration signal from the vehicle and collects vehicle information from the electronic control unit (ECU) of the vehicle to indicate vehicle diagnosis information and the current state of the vehicle that are diagnosed in real time while the vehicle is driving. A vehicle information generation unit that generates vehicle status information, a vehicle failure prediction unit that generates vehicle parts status based on the vehicle diagnosis information and vehicle status information to determine the urgency of preventive maintenance and predicts the occurrence of a vehicle failure, the at least A vehicle repair shop recommendation unit that recommends a vehicle repair shop based on price or distance based on the preventive maintenance urgency in one vehicle part condition, and detects whether or not a maintenance service is performed on the vehicle part condition according to the preventive maintenance urgency. It includes a preventive maintenance service compensation department that provides compensation for preventive maintenance services. Therefore, the vehicle preventive maintenance service providing apparatus and method generates vehicle status information through the vehicle information generation unit, analyzes vehicle status information to predict vehicle failure, recommends a vehicle repair shop based on the urgency of preventive maintenance, and whether or not to perform maintenance. Provides service compensation according to.

Description

Device and method for providing vehicle preventive maintenance service {APPARATUS AND METHOD OF PROVIDING VEHICLE PREVENTIVE MAINTENANCE SERVICE}

The present invention relates to a vehicle preventive maintenance service provision, and more particularly, to a vehicle preventive maintenance service providing apparatus and method for preventing and maintaining vehicle parts by generating and utilizing diagnostic information of a vehicle.

Vehicles and machines, including automobiles, constantly operate parts and reduce durability in the driving process for a role. Accordingly, parts constituting a vehicle and a machine have different degrees of wear according to their type and role, and must be replaced and repaired as necessary.

However, since what parts are damaged due to deterioration of durability varies depending on the environment of the vehicle and machine, replacement and repair are performed by collectively setting the mileage or time.

However, because the driving environment of the vehicle and the machine is different, the indifference of the user who did not know the status of the parts damage or the status of the parts damaged before the collective replacement period and did not recognize the importance of the replacement caused the failure, resulting in accidents including personal and material damage. And cause great social losses.

As a method of preventing such damage, research and development are underway to increase driver satisfaction by maintaining durability and driving stability by replacing consumables and parts at an appropriate time to prevent damage to parts.

Korean Patent Registration No. 10-1127625 relates to a vehicle customized preventive maintenance guidance system, and stores a preventive maintenance list according to vehicle characteristics in the server 330, and according to the user's request, the user's vehicle type, year, and In the vehicle customized preventive maintenance guidance system that provides a preventive maintenance list according to the mileage, it is installed at a maintenance company that has joined as a member, and receives the vehicle type, year, and maintenance details of the vehicle maintained by the maintenance company and receives the server 330 An input terminal 300 for transmitting to ); A maintenance history database 400 which is linked to the server 330 and stores maintenance details for each vehicle type and year input through the input terminal 300; It is installed in the server 330 and statistically processes maintenance details for each vehicle type and year from the information stored in the maintenance history database 400 to generate and store a preventive maintenance list according to vehicle age or mileage for each vehicle type and year. Statistics module 500; characterized in that it includes.

Korean Patent Registration No. 10-1053722 is a vehicle self-diagnosis system and its method using a telematics device. A vehicle self-diagnosis system using a telematics device receives detection signals from various sensors and detects abnormalities in each vehicle device based on this. The plurality of electronic control units (ECUs) for generating diagnostic codes corresponding thereto; A self-diagnosis interface device that stores data on whether or not an item to be diagnosed is abnormal, transmitted through the electronic control unit (ECU); And a telematics device that is connected to the self-diagnosis interface device through a predetermined communication line and displays diagnostic information according to received data to a driver in real time. According to the present invention, the driver can check the state of the vehicle in real time while the vehicle is running, so that it is easy to prepare for an accident in advance. In addition, even for beginners in driving, the condition of the vehicle can be easily grasped through a monitor, and the vehicle condition can be grasped in real time, thereby eliminating the burden of frequent maintenance at a repair shop.

Korean Patent Registration No. 10-1127625 (registered on March 9, 2012) Korean Patent Registration No. 10-1053722 (registered on July 27, 2011)

An embodiment of the present invention is to provide an apparatus and method for providing a vehicle preventive maintenance service for predicting a failure of a vehicle by generating current state of a vehicle and vehicle state information and grasping the state of vehicle parts.

An embodiment of the present invention is to provide an apparatus and method for providing a vehicle preventive maintenance service that recommends a vehicle repair shop based on a preventive maintenance urgency according to the state of a vehicle part.

An embodiment of the present invention is to provide a vehicle preventive maintenance service providing apparatus and method that provides a preventive maintenance bonus according to whether or not vehicle maintenance is performed at a vehicle repair shop based on the urgency of preventive maintenance according to the state of vehicle parts.

Among the embodiments, the vehicle preventive maintenance service providing apparatus receives at least one vibration signal from the vehicle and collects vehicle information from the electronic control unit (ECU) of the vehicle, and the vehicle diagnosis information and vehicle are diagnosed in real time while the vehicle is driving. Vehicle information generation unit that generates vehicle status information indicating the current status of the vehicle, and vehicle breakdown that determines the urgency of preventive maintenance by generating vehicle parts status based on the vehicle diagnosis information and vehicle status information and predicts the occurrence of vehicle failure. Prediction unit, a vehicle repair shop recommendation unit that recommends a vehicle repair shop based on price or distance based on the preventive maintenance urgency in the condition of the at least one vehicle part, and a maintenance service regarding the condition of the vehicle parts according to the preventive maintenance urgency. Includes a preventive maintenance service compensation unit that detects whether or not it is performed and provides compensation for preventive maintenance services, wherein the vehicle failure prediction unit integrates the vehicle diagnosis information and vehicle condition information to analyze the driving distance and driving environment to calculate the severity of the vehicle. And determine the degree of aging of the vehicle part based on the severity, and the urgency of preventive maintenance based on the degree of aging compared to the life cycle of the vehicle part, but determine the specific gravity and contribution condition for each severe condition, and at least one corresponding severity Under the conditions, the severity of the vehicle when the vehicle is driven under the corresponding severe condition can be calculated by reflecting the driving distance of the vehicle for each driving section, the specific gravity constant of the driving section, and the contribution of the driving section.

The vehicle information generation unit generates vehicle diagnosis information based on a composite vibration signal incorporating vibration signals detected by a plurality of vibration detectors installed in the vehicle, and based on vehicle information of the ECU collected through the OBD II connector. Vehicle status information can be generated.

The vehicle information generator includes the vibration detectors based on a frequency band of the composite vibration signal including at least a vibration detection signal of the vehicle engine and an engine timing belt, a wheel vibration detection signal of the vehicle, and a vibration detection signal of the vehicle body. The vehicle component may be diagnosed by specifying one of at least one associated vehicle component, and the vehicle diagnosis information may be generated.

The vehicle failure prediction unit preferentially detects an abnormality of the vehicle part from the vehicle state information, and if the abnormality of the vehicle part is not detected, estimates the state of the vehicle part from the vehicle diagnosis information to increase the urgency of the preventive maintenance. You can decide.

The vehicle failure prediction unit may compare the vehicle complex vibration signal and the normal complex vibration signal based on the vehicle diagnosis information to determine the preventive maintenance urgency according to the degree of abnormality for the part specified as abnormal.

The vehicle failure prediction unit may calculate the driving distance of the vehicle through the following equation.

[Equation]

Here, M is the running distance is, M _j is the vehicle of the j heavy conditions traveling in J of heavy conditions mileage, M driving section _ji is dark M _j divided by the I region in the heavy conditions j of the vehicle It is the i-th mileage the vehicle has driven.

The vehicle component state is generated based on the cumulative amount of the driving severity of the vehicle, and the aging degree of parts and consumables is determined through the vehicle component state, and preventive maintenance urgency including replacement consumables and maintenance necessary parts is generated. Vehicle failure prediction can be provided to vehicles and user terminals.

Among embodiments, the vehicle preventive maintenance service providing method includes vehicle diagnostic information and vehicle diagnostic information that are diagnosed in real time while the vehicle is driving by receiving at least one vibration signal from a vehicle and collecting vehicle information from an electronic control unit (ECU) of the vehicle. Vehicle information generation step of generating vehicle status information indicating the current state of the vehicle, vehicle failure occurrence that determines preventive maintenance urgency by generating vehicle parts status based on the vehicle diagnosis information and vehicle status information and predicts the occurrence of vehicle failure Prediction step, a vehicle repair shop recommendation step of recommending a vehicle repair shop based on price or distance based on the preventive maintenance urgency in the state of the at least one vehicle part, and a maintenance service related to the state of the vehicle parts according to the preventive maintenance urgency. It includes a preventive maintenance service compensation step of providing compensation for preventive maintenance service by detecting whether it has been performed, wherein the vehicle failure prediction step determines the weight and contribution condition for each severe condition, and integrates the vehicle diagnosis information and vehicle condition information. By analyzing the mileage and driving environment and reflecting the mileage of the vehicle for each driving section, the specific gravity constant of the driving section, and the contribution of the driving section under at least one applicable severe condition, the severity of the vehicle when the vehicle is driven under the corresponding severe condition And determining an aging degree of the vehicle component based on the calculated severity, and determining the preventive maintenance urgency based on an aging degree compared to a life cycle of the vehicle component.

The disclosed technology can have the following effects. However, since it does not mean that a specific embodiment should include all of the following effects or only the following effects, it should not be understood that the scope of the rights of the disclosed technology is limited thereby.

The apparatus for providing a vehicle preventive maintenance service according to an embodiment of the present invention may predict a vehicle failure by generating current state of the vehicle and vehicle state information and grasping the state of vehicle parts.

The apparatus for providing a vehicle preventive maintenance service according to an embodiment of the present invention may recommend a vehicle repair shop based on the urgency of preventive maintenance according to the state of vehicle parts.

The apparatus for providing a vehicle preventive maintenance service according to an embodiment of the present invention may provide a preventive maintenance bonus according to whether vehicle maintenance is performed in a vehicle repair shop based on the urgency of preventive maintenance according to the state of vehicle parts.

1 is a diagram showing a vehicle preventive maintenance service providing system according to an embodiment of the present invention.
FIG. 2 is a diagram illustrating a system for providing a vehicle preventive maintenance service in FIG. 1.
FIG. 3 is a diagram illustrating an apparatus for providing a vehicle preventive maintenance service in FIG. 1.
4 is a flowchart illustrating a process of providing a vehicle preventive maintenance service performed in the vehicle preventive maintenance service providing system of FIG. 1.
5 is a view showing a process of performing part diagnosis through a complex vibration signal in the process of predicting the occurrence of a vehicle failure of FIG. 4.
6 is a diagram showing an analysis of a constant velocity joint composite vibration signal in a process of predicting the occurrence of a vehicle failure of FIG. 4.
7 is a view showing a process of performing part diagnosis using a wheel bearing, brake judder, and wheel balance complex vibration signal in the process of predicting the occurrence of a vehicle failure of FIG. 4.
FIG. 8 is a diagram illustrating a severe condition in which a vehicle failure prediction unit measures an aging degree of a component in the process of predicting the occurrence of a vehicle failure of FIG. 4.
9 is a diagram illustrating an example of a severe condition in which a vehicle failure prediction unit measures an aging degree of a component in the process of predicting the occurrence of a vehicle failure of FIG. 4.
FIG. 10 is a diagram illustrating an example of a manual replacement time of a target product item in order to compare the aging degree and the life of the parts by the vehicle failure prediction unit in the process of predicting the occurrence of the vehicle failure of FIG. 4.

Since the description of the present invention is merely an embodiment for structural or functional description, the scope of the present invention should not be construed as being limited by the embodiments described in the text. That is, since the embodiments can be variously changed and have various forms, the scope of the present invention should be understood to include equivalents capable of realizing the technical idea. In addition, since the object or effect presented in the present invention does not mean that a specific embodiment should include all of them or only those effects, the scope of the present invention should not be understood as being limited thereto.

Meanwhile, the meaning of terms described in the present application should be understood as follows.

Terms such as "first" and "second" are used to distinguish one component from other components, and the scope of rights is not limited by these terms. For example, a first component may be referred to as a second component, and similarly, a second component may be referred to as a first component.

Singular expressions are to be understood as including plural expressions unless the context clearly indicates otherwise, and terms such as “comprise” or “have” refer to implemented features, numbers, steps, actions, components, parts, or It is to be understood that it is intended to designate that a combination exists and does not preclude the presence or addition of one or more other features or numbers, steps, actions, components, parts, or combinations thereof.

As used herein, "vehicle", "vehicular" or other similar terms are automobiles, passenger automobiles, buses generally including sport utility vehicles (SUV). , Trucks, various commercial vehicles, ships including various boats and ships, airplanes, etc., and hybrid vehicles, electric vehicles, hybrid electric vehicles, hydrogen powered vehicles and other alternative fuels (e.g., petroleum Fuels derived from resources that are not) are understood to include vehicles. As mentioned herein, an electric vehicle (EV) is a rechargeable energy storage device (e.g., one or more rechargeable electrochemical cells or other types of batteries) as part of its locomotion capabilities. It is a vehicle that contains the electric power obtained from. The EV is not limited to automobiles and may include motorcycles, carts, scooters, and the like. In addition, a hybrid vehicle is a vehicle having two or more power sources, for example gasoline-based power and electricity-based power (eg, hybrid electric vehicle (HEV)).

All terms used herein have the same meaning as commonly understood by one of ordinary skill in the field to which the present invention belongs, unless otherwise defined. Terms defined in commonly used dictionaries should be construed as having meanings in the context of related technologies, and cannot be construed as having an ideal or excessive formal meaning unless explicitly defined in the present application.

1 is a diagram showing a vehicle preventive maintenance service providing system according to an embodiment of the present invention.

Referring to FIG. 1, the vehicle preventive maintenance service providing system 100 may include a user vehicle 110, a user terminal 120, a vehicle preventive maintenance service providing device 130, and a vehicle information database 140.

The user terminal 120 corresponds to a computing device that can receive and use the vehicle preventive maintenance service provided by the vehicle preventive maintenance service providing device 130, and may be implemented as a smartphone, a laptop, or a computer, but is not limited thereto. Instead, it can be implemented in various devices such as a tablet PC. The user vehicle 110 may be connected to the vehicle preventive maintenance service providing device 130 through a network, and a plurality of user vehicles 110 may be connected to the user terminal 120 at the same time.

The vehicle preventive maintenance service providing apparatus 130 may be implemented as a computer or a server corresponding to a program through which the user vehicle 110 can provide a vehicle preventive maintenance service for a vehicle for which the vehicle preventive maintenance service is selected. The user terminal 120 may be wirelessly connected to the user vehicle 110 through Bluetooth, WiFi, and the like, and may exchange data with the user vehicle 110 through a network.

The vehicle preventive maintenance service providing apparatus 130 may be implemented including the vehicle information database 140, and may be implemented independently of the vehicle information database 140. When implemented independently of the vehicle information database 140, the vehicle preventive maintenance service providing device 130 may be connected to the vehicle information database 140 by wire or wirelessly to exchange data.

The vehicle information database 140 may store various pieces of information necessary for providing a vehicle preventive maintenance service. For example, the vehicle information database 140 stores normal vehicle diagnosis information according to the type of vehicle, a normal complex vibration signal according to the vehicle type, vehicle diagnosis information received from the user vehicle 110 and information on vehicle condition information, etc. It may be stored, but is not limited thereto, and information processed in various forms related to the provision of vehicle preventive maintenance service may be stored.

FIG. 2 is a diagram illustrating a system for providing a vehicle preventive maintenance service in FIG. 1.

Referring to FIG. 2, the user vehicle 110 includes vibration signals detected by the engine vibration detector 210, the knuckle vibration detector 220, and the vehicle body vibration detector 230.

In one embodiment, the composite vibration signal may include a vibration detection signal of the engine vibration detector 210, the knuckle vibration detector 220, and the vehicle body vibration detector 230. The engine vibration sensor 210 may be attached to the engine of the user's vehicle 110 and transmit a vibration detection signal to the vehicle preventive maintenance service providing apparatus 130 by sensing vibrations of the vehicle engine and the engine timing belt.

The knuckle vibration detector 220 may be mounted on a plurality of steering knuckles of the user vehicle 110. The knuckle vibration detector 220 may include a multi-axis wheel acceleration sensor. The knuckle vibration sensor 220 may detect wheel vibration and transmit a vibration detection signal to the vehicle preventive maintenance service providing device 130.

One or more vehicle body vibration detectors 230 may be attached to the vehicle body of the user vehicle 110. The vehicle body vibration sensor 230 may include a multi-axis vehicle body acceleration sensor, a multi-axis rotation angle sensor, a multi-axis inclination sensor, and a GPS sensor. The vehicle body vibration sensor 230 may sense vibration of the vehicle body and transmit a vibration signal to the vehicle preventive maintenance service providing apparatus 130.

FIG. 3 is a diagram illustrating an apparatus for providing a vehicle preventive maintenance service in FIG. 1.

3, the vehicle preventive maintenance service providing device 130 includes a vehicle information generation unit 310, a vehicle failure prediction unit 320, a vehicle repair shop recommendation unit 330, and a preventive maintenance service compensation unit 340. Include.

The vehicle information generation unit 310 integrates the engine vibration signal, the knuckle vibration signal, and the vehicle body vibration signal received from the user vehicle 110 into a composite vibration signal and converts the vehicle information provided by the ECU (Electronic Control Unit) 240 into OBD II. Vehicle diagnostic information is generated using vehicle information collected through the connector. Vehicle diagnosis information includes diagnosis information on each part of the vehicle. The vehicle information generation unit 310 may collect vehicle information provided by the vehicle ECU through an OBD II connector, and generate vehicle condition information necessary for vehicle preventive maintenance service.

In an embodiment, the vehicle failure prediction unit 320 may receive vehicle diagnosis information and vehicle status information. The vehicle failure prediction unit 320 generates the vehicle component status of the user vehicle 110 by integrating vehicle diagnosis information and vehicle status information, and then analyzes the degree of vibration abnormality of individual components to detect abnormalities, determine and prevent aging. Maintenance urgency can be determined.

The vehicle failure prediction unit 320 uses the normal complex vibration signal diagnosis information, and uses the complex vibration signal diagnosis information of the user vehicle 110 currently running and the normal diagnosis information of the vehicle information database 410 based on the frequency band. It includes a parts diagnosis algorithm to compare and an aging degree prediction algorithm that predicts the aging degree of parts.

In an embodiment, the vehicle failure prediction unit 320 may specify a component corresponding to a frequency domain in which an abnormal diagnosis result according to the vehicle component state is generated. The vehicle failure prediction unit 320 may determine the urgency of preventive maintenance according to the degree of abnormality with respect to the specified component for which the abnormal diagnosis result is displayed.

In an embodiment, the aging degree prediction algorithm may calculate the driving severity of the user vehicle 110 by analyzing a driving distance and a driving environment by integrating vehicle diagnosis information and vehicle condition information, and generate a driving pattern of the severity. The aging degree prediction algorithm predicts the degree of aging based on the accumulated amount of severity calculated from the severe driving pattern, generates the condition of vehicle parts, and then determines the degree of aging compared to the life cycle of products and consumables to predict the remaining life.

The vehicle failure prediction unit 320 may determine the urgency of preventive maintenance, which means the need for replacement and maintenance, by analyzing the aging and life results of specific parts and consumables according to the state of the vehicle parts.

The vehicle repair shop recommendation unit 330 receives the urgency of preventive maintenance of parts according to the vehicle failure prediction unit 320. The vehicle repair shop recommendation unit 330 includes a repair shop recommendation function that recommends a repair shop to a user through the user vehicle 110 and the user terminal 120 when a specific part requiring maintenance is present according to the urgency of preventive maintenance.

The service shop recommendation function is the location of the user's vehicle 110 through the GPS device according to the urgency of preventive maintenance, the location of the registered workshop, the possibility of servicing specific parts of the registered workshop, the expertise of servicing specific parts of the registered workshop, the maintenance fee of the registered workshop, and the registered workshop. It is possible to recommend a repair shop to the user by synthesizing the evaluation contents of

The preventive maintenance service compensation unit 340 receives the urgency of preventive maintenance of a specific part according to the vehicle failure prediction unit 320. The preventive maintenance service compensation unit 340 detects whether the maintenance service of a specific part is performed according to the preventive maintenance urgency, and provides a service compensation to the user through the user vehicle 110 and the user terminal 120.

In one embodiment, the preventive maintenance service compensation unit 340 increases the durability of the vehicle through maintenance of specific parts according to the urgency of preventive maintenance, secures driving stability, and provides service compensation by reducing the risk of accidents through preventive maintenance. It can be used to provide discounts on insurance payments for users.

In one embodiment, the vehicle preventive maintenance service providing device 130 includes vehicle diagnosis information, vehicle state information, vehicle component state, severe driving driving pattern, component diagnosis result, component aging degree, component preventive maintenance urgency, vehicle Information on failure prediction, repair shop recommendation, and service provision may be provided through the user vehicle 110 and the user terminal 120.

4 is a flowchart illustrating a process of providing a vehicle preventive maintenance service performed in the vehicle preventive maintenance service providing system of FIG. 1.

Referring to FIG. 4, the vehicle information generation unit 310 integrates vibration information that appears while the vehicle is running through the engine vibration sensor 210, the knuckle vibration sensor 220, and the vehicle body vibration sensor 230 of the user vehicle 110. By receiving one complex vibration information, vehicle diagnosis information may be generated, and vehicle information provided by the ECU 240 of the user vehicle 110 may be received through an OBD II connector to generate vehicle condition information.

The vehicle failure prediction unit 320 may generate vehicle component states each composed of preventive maintenance urgency and vehicle components through a component diagnosis algorithm and an aging degree prediction algorithm based on vehicle information. Vehicle failure prediction unit 320 is a vehicle failure prediction service to the user through the user vehicle 110 and the user terminal 120 by detecting a component abnormality, determining a component aging degree, and determining the maintenance urgency using the vehicle component status. Can provide.

Vehicle repair shop recommendation unit 330 is based on the preventive maintenance urgency in at least one vehicle part status, according to the preventive maintenance urgency, the location of the vehicle through the GPS device, the location of the registered repair shop, the expertise of maintenance of specific parts of the registered repair shop, and A vehicle repair shop recommendation service may be provided to a user through the user vehicle 110 and the user terminal 120 on the basis of the aggregated data of the maintenance fee of the registered repair shop.

The preventive maintenance service compensation unit 340 may detect whether or not a maintenance service is performed on the state of a corresponding vehicle part according to the preventive maintenance urgency. The preventive maintenance service compensation unit 340 is a service compensation by increasing the durability of the vehicle through maintenance of specific parts according to the urgency of preventive maintenance, securing driving stability, and reducing the risk of accidents through preventive maintenance. A discount service may be provided to a user through the user vehicle 110 and the user terminal 120.

In one embodiment, the vehicle preventive maintenance service providing device 130 includes vehicle diagnosis information, vehicle state information, vehicle component state, severe driving driving pattern, component diagnosis result, component aging degree, component preventive maintenance urgency, vehicle Information on failure prediction, repair shop recommendation, and service provision may be provided to the user through the user vehicle 110 and the user terminal 120.

5 is a view showing a process of performing part diagnosis through a complex vibration signal in the process of predicting the occurrence of a vehicle failure of FIG. 4.

The vehicle failure prediction unit 320 may perform parts diagnosis through a parts diagnosis algorithm, and the parts diagnosis algorithm consists of a first step for low-frequency analysis and a second step for high-frequency analysis to determine the degree of vibration abnormality. May contain component specific diagnostic logic.

The specific component diagnosis logic converts the complex vibration signal including the acceleration signal and vibration signal of vibration detectors into a frequency response function using Fast Fourier Transform (FFT) to analyze the component's inherent system mathematically and vehicle information. It may include a diagnosis process of determining whether or not it is normal by comparing it with normal diagnosis information of the database 140.

Finally, the parts diagnosis algorithm diagnoses the abnormality of the parts based on the complex vibration signal diagnosis information of the user vehicle 110 currently running and the frequency band of the frequency response function using the normal complex vibration signal unique system, and a failure occurs. I can predict.

6 is a view showing an analysis of a constant velocity joint composite vibration signal in the process of predicting the occurrence of a vehicle failure of FIG. 4, and FIG. 7 is a wheel bearing, brake judder, and wheel balance complex vibration signal in the process of predicting the occurrence of a vehicle failure of FIG. It is a diagram showing the process of performing part diagnosis using.

In FIG. 6, the vehicle failure prediction unit 320 analyzes the composite vibration signal with a component diagnosis algorithm to identify vibration generated by a brake judder in the user vehicle 110. Vibration caused by the brake judder may have an abnormal frequency range indicating vibration abnormality in the range of 18 ~ 24Hz.

In FIG. 7, the vehicle failure prediction unit 320 performs normal information of the vehicle information database 140 and a comparison diagnosis logic based on a frequency band in the composite vibration signal diagnosis information using a parts diagnosis algorithm. The vehicle failure prediction unit 320 may generate a vehicle component state by classifying and specifying a component corresponding to a frequency region in which a diagnostic logic execution result and an abnormal diagnosis result are displayed.

In one embodiment, the parts diagnosis algorithm is when an abnormal diagnosis result is obtained from vehicle diagnosis information including a composite vibration signal in which vibration signals related to various parts such as wheel bearings, brake judder, and wheel balance are integrated. It may include a diagnostic logic that classifies and specifies parts corresponding to each acceleration, vehicle driving state, vehicle driving environment, vehicle driving slope, and frequency domain.

The parts diagnosis algorithm analyzes the complex vibration signal including at least one symptom among tire inflation pressure abnormality, wheel balance abnormality, wheel alignment abnormality, wheel bearing flaking, constant velocity joint flaking, damper leak, ball joint overcap, and brake judder. After creating the state of the vehicle parts, it is possible to diagnose whether the parts are abnormal and to identify and classify the abnormal parts.

In one embodiment, the vehicle failure prediction unit 320 may predict the occurrence of a failure for a specific part for which an abnormal diagnosis result is displayed through the state of the vehicle part, and may determine the urgency of preventive maintenance according to the degree of abnormality. The vehicle failure prediction unit 320 may generate a preventive maintenance urgency and provide a vehicle failure prediction through the user vehicle 110 and the user terminal 120.

FIG. 8 is a diagram illustrating a severe condition in which a vehicle failure prediction unit measures an aging degree of a component in the process of predicting the occurrence of a vehicle failure of FIG. 4.

Referring to FIG. 8, the vehicle failure prediction unit 320 determines the severity of the vehicle diagnosis information and the vehicle condition information, the analysis sensor type, the specific gravity, the mileage, the driving time and the contribution through the aging degree prediction algorithm. 110) can be determined, and the degree of aging of vehicle parts can be predicted based on the severity. The aging degree prediction algorithm includes the following equation.

Here, M corresponds to the mileage of the vehicle. M _j corresponds to the mileage the vehicle has traveled among j severe conditions under severe conditions of different J types. M _ji corresponds to the i-th mileage the vehicle has traveled among the driving intervals where M _j is divided into I sections under j severe conditions.

Here, S corresponds to the severity of the vehicle. S _j corresponds to the severity of the vehicle when the vehicle is driven under the j severe condition among the severe conditions of different J types. M _ji corresponds to the i-th mileage the vehicle has traveled among the driving intervals where M _j is divided into I sections under j severe conditions. W _ji corresponds to the specific gravity constant of the i-th running section among the running sections divided into I sections under j severe conditions. C _ji corresponds to the contribution of the i-th driving segment among the driving segments divided into I segments under j severe conditions.

Thus, the total severity of the vehicle S _T can be expressed as the sum of S _j .

Here, S _T is the sum of S _j from the J severe conditions to the j severe condition, and corresponds to the total severity.

In one embodiment, the vehicle failure prediction unit 320 uses the aging degree prediction algorithm, by using the severity condition analyzed from vehicle diagnosis information and vehicle condition information, analysis sensor type, specific gravity, mileage, driving time, and contribution. You can calculate the severity of the vehicle. The vehicle failure prediction unit 320 may generate a severe driving pattern of the vehicle using the calculated severity.

9 is a diagram illustrating an example of a severe condition in which a vehicle failure prediction unit predicting occurrence of a vehicle failure of FIG. 4 measures an aging degree of a component.

In FIG. 9, the vehicle failure prediction unit 320 may calculate the severity of the user vehicle 110 by determining the weight and contribution condition for each J severe condition through an aging degree prediction algorithm, and the severity due to the severe driving pattern The degree of aging of vehicle parts can be predicted based on the accumulated amount.

In one embodiment, the vehicle failure prediction unit 320 may determine different weight and contribution conditions for each severe condition according to FIG. 9 through an aging degree prediction algorithm. "1-DP" described in the contribution condition means that the contribution corresponds to a one-dimensional parameter, and "2-DP" means that the contribution corresponds to a two-dimensional parameter. The vehicle failure prediction unit 320 may calculate the severity of the vehicle by determining the weight and contribution conditions for each of the J severe conditions, and generate the vehicle part status of the user vehicle 110 based on the accumulated severity. I can. For example, the severe condition “when the frequency of high-speed driving is high” corresponds to a one-dimensional parameter (ie, vehicle speed). In addition, the contribution condition of the severe condition is defined in advance as 100% if the vehicle speed is 200 km/h or more and 0% if the vehicle speed is less than 80 km/h. If the vehicle traveled at a speed of 220 km/h, the contribution is 100%, and if the vehicle traveled at a speed of 50 km/h, the contribution is 0%. The vehicle failure prediction unit 320 may provide a vehicle part condition and a severe driving pattern using an aging degree prediction algorithm to a user through the user vehicle 110 and the user terminal 120.

FIG. 10 is a diagram illustrating an example of a manual replacement time of a target product item in order to compare the aging degree and the life of the parts by the vehicle failure prediction unit in the process of predicting the occurrence of the vehicle failure of FIG. 4.

In FIG. 10, the vehicle failure prediction unit 320 predicts the aging degree of vehicle parts and consumables based on the accumulated severity calculated by the aging degree prediction algorithm, and then, the vehicle part life of the vehicle information database 140 The status of vehicle parts is created by comparing the replacement cycle and consumable replacement timing data.

In one embodiment, M _S and T _S are the driving distance and driving time of the vehicle under severe conditions, and M _N and T _N are the driving distance and driving time of the vehicle under normal conditions. The vehicle failure prediction unit 320 may predict the occurrence of a vehicle failure by determining the degree of aging of the part through the state of the vehicle part and generating a preventive maintenance urgency. Vehicle parts are engine oil and oil filter, air cleaner filter, spark plug, brake disc, brake pad, lower arm ball joint cleaning, drive shaft and boot, air filter for air conditioner, rear differential oil, transfer case and automatic transmission oil. It may include the state of the same parts and parts of consumables.

In one embodiment, the vehicle failure prediction unit 320 determines the degree of aging of parts and consumables through the state of the vehicle parts, and generates preventive maintenance urgency including consumables requiring replacement and parts requiring maintenance, and A vehicle failure prediction may be provided through the user terminal 120.

As a result, the vehicle preventive maintenance service providing system 330 receives the complex vibration signal and ECU 240 information from the user vehicle 110. The vehicle information generation unit 310 generates vehicle status information and vehicle diagnosis information by using the received composite vibration signal and ECU 240 information. The failure occurrence predicting unit 320 generates a vehicle vehicle component status through the generated vehicle status information and vehicle diagnosis information, determines the vehicle component status, and predicts the occurrence of a vehicle failure based on the urgency of preventive maintenance. The vehicle repair shop recommendation unit 330 provides a service for recommending a vehicle repair shop to a user through prediction of a vehicle failure based on the urgency of preventive maintenance. The preventive maintenance service compensation unit 340 may provide a compensation service to a user who has performed preventive maintenance through the preventive maintenance service compensation unit 340. The vehicle preventive maintenance service providing system 330 may provide various types of information through the user vehicle 110 and the user terminal 120.

Although the above has been described with reference to preferred embodiments of the present invention, those skilled in the art will variously modify and change the present invention within the scope not departing from the spirit and scope of the present invention described in the following claims. You will understand that you can do it.

100: vehicle preventive maintenance service provision system
110: user vehicle 120: user terminal
130: vehicle preventive maintenance service providing device
140: vehicle information database
210: engine vibration sensor 220: knuckle vibration sensor
230: vehicle-made vibration sensor 240: ECU
310: vehicle information generation unit 320: vehicle failure prediction unit
330: vehicle repair shop recommendation department 340: preventive maintenance service compensation department

Claims (8)

A vehicle that receives at least one vibration signal from a vehicle and collects vehicle information from an electronic control unit (ECU) of the vehicle to generate vehicle diagnostic information that is diagnosed in real time while the vehicle is driving and vehicle status information indicating the current state of the vehicle Information generation unit;
A vehicle failure prediction unit for determining a preventive maintenance urgency by generating a vehicle part condition based on the vehicle diagnosis information and the vehicle condition information, and predicting the occurrence of a vehicle failure;
A vehicle repair shop recommendation unit for recommending a price or distance-based vehicle repair shop based on the urgency of preventive maintenance in the state of the at least one vehicle part; And
Including a preventive maintenance service compensation unit for providing a preventive maintenance service compensation by detecting whether a maintenance service is performed on the condition of the vehicle part according to the preventive maintenance urgency,
The vehicle failure prediction unit
The vehicle diagnostic information and vehicle condition information are integrated to analyze the driving distance and the driving environment to calculate the severity of the vehicle, determine the aging degree of the vehicle component based on the severity, and determine the aging degree of the vehicle component compared to the life cycle of the vehicle component. Determine the urgency of the preventive maintenance,
Vehicles when the vehicle is driven under the severe conditions by determining the specific gravity and contribution conditions for each severe condition and reflecting the mileage of the vehicle for each driving section, the specific gravity constant of the driving section, and the contribution of the driving section under at least one applicable severe condition. Vehicle preventive maintenance service providing device, characterized in that calculating the severity of.
The method of claim 1, wherein the vehicle information generation unit
Vehicle diagnosis information is generated based on a composite vibration signal incorporating vibration signals detected by a plurality of vibration detectors installed in the vehicle, and vehicle status information is generated based on vehicle information of the ECU collected through the OBD II connector. Vehicle preventive maintenance service providing device, characterized in that.
The method of claim 2, wherein the vehicle information generation unit
At least one association associated with the vibration detectors based on a frequency band of the composite vibration signal including at least a vibration detection signal of the vehicle engine and an engine timing belt, a wheel vibration detection signal of the vehicle, and a vibration detection signal of a vehicle body A vehicle preventive maintenance service providing apparatus, characterized in that the vehicle component is diagnosed by specifying one of the vehicle components and the vehicle diagnostic information is generated.
The method of claim 1, wherein the vehicle failure prediction unit
And determining the urgency of the preventive maintenance by estimating the state of the vehicle component from the vehicle diagnosis information when an abnormality of the vehicle component is detected preferentially in the vehicle state information, and if an abnormality in the vehicle component is not detected. Vehicle preventive maintenance service provision device.
The method of claim 4, wherein the vehicle failure prediction unit
The vehicle preventive maintenance service providing apparatus, characterized in that the predictive maintenance urgency is determined according to the degree of abnormality for a part specified as abnormal by comparing the complex vibration signal of the vehicle with the normal complex vibration signal based on the vehicle diagnosis information.
The method of claim 1, wherein the vehicle failure prediction unit
Vehicle preventive maintenance service providing apparatus, characterized in that calculating the mileage of the vehicle through the following equation.
[Equation]

Here, M is the running distance is, M _j is the vehicle of the j heavy conditions traveling in J of heavy conditions mileage, M driving section _ji is dark M _j divided by the I region in the heavy conditions j of the vehicle It is the i-th mileage the vehicle has driven.
The method of claim 6, wherein the vehicle failure prediction unit
The vehicle component state is generated based on the cumulative amount of the driving severity of the vehicle, and the aging degree of parts and consumables is determined through the vehicle component state, and preventive maintenance urgency including replacement consumables and maintenance necessary parts is generated. Vehicle preventive maintenance service providing apparatus, characterized in that providing a prediction of vehicle failure to the vehicle and the user terminal.
Vehicle status indicating vehicle diagnosis information and the current state of the vehicle by receiving at least one vibration signal from the vehicle in the vehicle information generation unit and collecting vehicle information from the electronic control unit (ECU) of the vehicle. Vehicle information generation step of generating information;
A vehicle failure prediction step of generating a vehicle part condition based on the vehicle diagnosis information and the vehicle condition information in the vehicle failure occurrence predicting unit to determine the urgency of preventive maintenance and predicting the occurrence of a vehicle failure;
A vehicle repair shop recommendation step of recommending a price or distance-based vehicle repair shop based on the urgency of preventive maintenance in the state of the at least one vehicle part, by the vehicle repair shop recommendation unit; And
Including a preventive maintenance service compensation step of providing a preventive maintenance service compensation by detecting whether a maintenance service has been performed on the condition of the vehicle part according to the preventive maintenance urgency in the preventive maintenance service compensation unit,
The vehicle failure prediction step
The weight and contribution conditions for each severe condition are determined, and the vehicle diagnosis information and vehicle condition information are integrated to analyze the mileage and the driving environment, and the mileage of the vehicle for each driving section and the specific gravity constant of the driving section under at least one corresponding severe condition Calculating the severity of the vehicle when the vehicle is driven under the corresponding severe condition by reflecting the contribution of the driving section; And
And determining the degree of aging of the vehicle component based on the calculated severity and determining the urgency of preventive maintenance based on the degree of aging compared to the life cycle of the vehicle component.

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