CN110954335A - Health assessment method and system for industrial vehicle - Google Patents
Health assessment method and system for industrial vehicle Download PDFInfo
- Publication number
- CN110954335A CN110954335A CN201910850505.XA CN201910850505A CN110954335A CN 110954335 A CN110954335 A CN 110954335A CN 201910850505 A CN201910850505 A CN 201910850505A CN 110954335 A CN110954335 A CN 110954335A
- Authority
- CN
- China
- Prior art keywords
- industrial vehicle
- health
- cloud server
- intelligent terminal
- vehicle
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 14
- 239000000126 substance Substances 0.000 claims abstract description 13
- 238000012423 maintenance Methods 0.000 claims abstract description 9
- 238000004458 analytical method Methods 0.000 claims abstract description 7
- 238000011156 evaluation Methods 0.000 claims description 5
- 238000005457 optimization Methods 0.000 abstract 1
- 230000005802 health problem Effects 0.000 description 2
- 238000012216 screening Methods 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M17/00—Testing of vehicles
- G01M17/007—Wheeled or endless-tracked vehicles
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses an industrial vehicle health state assessment method and system. The method comprises the following steps: the cloud server carries out physical modeling on related components according to physical/chemical characteristics of actual industrial vehicle components, and uploads collected original data of the industrial vehicle operation to the cloud through a network by using the intelligent terminal; the cloud end screens original data of the operation of the vehicle based on the relation between physical/chemical characteristics of corresponding working parameters of related components and the health state of the components, and puts the screened key data into the physical model for analysis to obtain the health state of each component of the industrial vehicle; and integrating the health states of the components to evaluate the current health state of the industrial vehicle and predict the future health state. In addition, the cloud end also generates a health report and returns the health report to the user, and provides an optimization suggestion of vehicle use for the user, so that the user can maintain or overhaul the vehicle in advance, and the maintenance cost caused by damage/failure of related components is reduced.
Description
Technical Field
The invention provides a health assessment method and system for an industrial vehicle, relates to the field of vehicle assessment and maintenance management, and particularly relates to an automation scheme for real-time assessment and prediction of the health condition of the industrial vehicle.
Background
Industrial vehicles are used more and more widely as operation tools, the operation time is long, the operation intensity is high, the use environment is poor, and once the vehicles are damaged, professional technicians are required to maintain the vehicles, so that the shutdown is caused, and the production is influenced. Therefore, how to ensure the long-time fault-free operation or quick fault removal of the vehicle becomes an important performance index for measuring future industrial vehicles. The existing technical scheme for solving the problem comprises: 1. carrying out manual regular maintenance on the industry; 2. the vehicle running state is monitored through the Internet of vehicles platform in real time, when the vehicle breaks down, the system can prompt and display a fault point, the field personnel can be helped to remotely solve the problem, the temporary diagnosis and the investigation of professional engineers are not needed, and the time and the cost are saved. For the prior art scheme 1, once a vehicle is sold and is difficult to timely maintain by a worker at regular intervals, the vehicle is regularly maintained by a technician only when the vehicle breaks down, and the vehicle is often out of service for a long time. And prior art scheme 2 is the maintenance afterwards that breaks down, and the vehicle is not paid attention to when the fault, often the trouble is great when developing to shut down, even the vehicle subassembly loss needs whole change, and cost of maintenance is high.
Disclosure of Invention
The invention provides an evaluation method for the health state of an industrial vehicle, which can timely acquire the current health state of the relevant industrial vehicle, predict the possible future health problems, inform a user in advance and provide a rationalization suggestion, so that the industrial vehicle is maintained before the health problems are generated, and the maintenance cost is reduced. The invention provides an evaluation method of the health state of an industrial vehicle, which specifically comprises the following steps: a. the cloud server carries out physical modeling on the vehicle related components according to the physical/chemical characteristics of the actual industrial vehicle components; b. uploading the original data of the industrial vehicle operation collected in real time to a cloud server through an intelligent terminal; c. the cloud server screens the original data based on the relation between the physical/chemical characteristics of the corresponding working parameters of the related components and the health states of the components, and puts the obtained key data into the physical model for analysis to obtain the health states of the components of the industrial vehicle; d. the cloud server synthesizes the health states of the related components of the industrial vehicle, generates a health report of the industrial vehicle and pushes the health report to an intelligent terminal user.
Further, the key data screened from the raw data by the cloud server include: the running speed and the load weight of the vehicle; voltage, current, temperature at which the battery operates; voltage, current, temperature, etc. at which the motor controller operates. The critical data will be used to analyze the current operating state of the vehicle and predict future operating conditions. By evaluating the reconstructed model of the relevant components of the industrial vehicle through the key data, the past working state of the components can be summarized, and meanwhile, the future service life of the components can be predicted. For example, the voltage, current, and temperature at which the motor controller operates can be used to analyze the health and life of the core devices MOSFETs of the motor controller. And according to the analysis and prediction results of the components, the intelligent terminal user is pertinently given reasonable suggestions and fed back to the user in the form of a health report.
Correspondingly, the invention further provides a health state evaluation system of the industrial vehicle, and the system comprises a data acquisition module, an intelligent terminal and a cloud server of the distributed industrial vehicle. The data acquisition module is used for acquiring original data of industrial vehicle operation in real time and sending the original data to the intelligent terminal. The intelligent terminal uploads the collected original data of the operation of the industrial vehicle to the cloud server, and receives and displays the health report of the industrial vehicle fed back by the cloud server. The cloud server analyzes and predicts the current and future health states of each component of the industrial vehicle based on the physical/chemical rules between the corresponding working parameters and the health states of the relevant components and in combination with the model established for each component and the key data relevant to each component, generates a health report of the industrial vehicle and pushes the health report to an intelligent terminal user; the key data is obtained by screening from the original data.
Drawings
FIG. 1 is a flow chart of a method for health assessment of an industrial vehicle provided by the present invention;
FIG. 2 is a graph of battery life versus battery depth of discharge;
FIG. 3 is a graph of battery capacity versus battery operating temperature;
fig. 4 is a plot of MOSFET cycle life versus junction temperature.
Detailed Description
In order to make the technical problems, technical solutions and advantages solved by the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Fig. 1 is a flowchart of a method for evaluating a state of health of an industrial vehicle according to the present invention. As shown in fig. 1, the method comprises the steps of:
a. the cloud server carries out physical modeling on the vehicle related components according to the physical/chemical characteristics of the actual industrial vehicle components;
b. uploading the original data of the industrial vehicle operation collected in real time to a cloud server through an intelligent terminal;
c. the cloud server screens the original data based on the relation between the physical/chemical characteristics of the corresponding working parameters of the related components and the health states of the components, and puts the obtained key data into the physical model for analysis to obtain the health states of the components of the industrial vehicle;
d. the cloud server synthesizes the health states of the related components of the industrial vehicle, generates a health report of the industrial vehicle and pushes the health report to an intelligent terminal user.
Specifically, in step a, the cloud performs physical modeling on the relevant components of the industrial vehicle to realize model reconstruction of the actual vehicle. Important components of the vehicle are subjected to model reconstruction through physical modeling so as to quantitatively analyze the working state of the components. The relevant component model of an industrial vehicle can be built with actual components according to the specific vehicle and can also be a classical analysis model on relevant books. And evaluating the health state of each component of the industrial vehicle based on the physical/chemical rules between the corresponding working parameters and the health state of the relevant components and by combining the model established for each component and the key data relevant to each component. For example, model reconstruction of the power battery circuit can be achieved by referring to a battery classical analysis model in a related professional book. The discharging depth of the battery can be obtained by detecting key data such as current, residual capacity and working temperature when the battery works and combining the current and the residual capacity with a battery circuit model when the battery works. And then, according to the relationship between the service life of the battery and the discharge depth of the battery (shown in figure 2) and the relationship between the capacity of the battery and the working temperature of the battery (shown in figure 3), the current state of health of the battery is evaluated, and the future working state and the service life of the battery are predicted. As another example, the motor controller model reconstruction may be implemented with reference to a physical model of a power semiconductor device, a MOSFET. The MOSFET is used as a core device of the motor controller, and directly determines the health state and the service life of the motor controller. According to the relation between the cycle life of the MOSFET and the junction temperature (as shown in fig. 4), the current health state and the service life of the MOSFET can be evaluated in the model by monitoring the core key data such as the current, the temperature and the like when the motor controller works, and further the health state and the service life of the motor controller can be evaluated.
In the step b, the original data of the vehicle operation can be acquired in real time through a data acquisition module comprising a plurality of sensors and then summarized to the user intelligent terminal. For example, a current sensor, a voltage sensor and a temperature sensor can be adopted to respectively acquire the working current, voltage and temperature of the battery and the motor controller in real time; the load, the running speed and the like of the vehicle are acquired in real time by utilizing a gravity sensor and a speed sensor. The user intelligent terminal can upload the original data of the operation of the industrial vehicle to the cloud server in real time, and can also temporarily store the original data of the operation of the industrial vehicle at a local end, and upload the temporarily stored original data to the cloud server when the original data meet a preset opportunity.
In step c, the cloud server screens out key data related to important components of the industrial vehicle from the raw data, such as the driving speed and the loading weight of the vehicle, the working current of the motor controller, the temperature of the radiator, the working current of the battery, the residual capacity and the like. The critical data will be used to analyze the current state of health of the relevant components of the vehicle and to predict future operating conditions.
And d, the cloud server synthesizes the health states of the related components of the industrial vehicle, generates a health report of the industrial vehicle and pushes the health report to an intelligent terminal user. The cloud server can push the statement of health to the intelligent terminal user in real time and dynamically display the statement of health on the intelligent terminal, and can also respond to a user request to push the statement of health to the intelligent terminal. The key data can be subjected to quantitative analysis of the reconstructed model, so that the passing working state of the vehicle can be summarized, and the future service life of related components can be predicted. The summary and forecast will be pushed to the end user over the network in the form of a statement of health, giving the end user rationalized advice given for industrial vehicle maintenance. For example, the depth of discharge of the battery is controlled to extend the life, the operating temperature of the motor controller is controlled to extend the life of the motor controller, the actual load capacity of the vehicle is recommended to reduce mechanical fatigue, and the like.
Correspondingly, the invention provides a health state evaluation system of an industrial vehicle, which comprises a data acquisition module, an intelligent terminal and a cloud server of the distributed industrial vehicle. The data acquisition module is used for acquiring original data of industrial vehicle operation in real time and sending the original data to the intelligent terminal. The intelligent terminal uploads the collected original data of the industrial vehicle operation to the cloud server, and receives and displays the health report of the industrial vehicle fed back by the cloud server. The cloud server analyzes and predicts the current and future health states of each component of the industrial vehicle based on the physical/chemical rules between the corresponding working parameters and the health states of the relevant components and in combination with the model established for each component and the key data relevant to each component, generates a health report of the industrial vehicle and pushes the health report to an intelligent terminal user; the key data is obtained by screening from the original data.
By the method and the system provided by the invention, a user can know the health state of the relevant industrial vehicle in time, particularly the working state and the expected service life of the important components, and can also obtain the relevant maintenance suggestions in time, so that the user can maintain or overhaul the vehicle in advance, and the failure cost is reduced.
Claims (8)
1. A state of health assessment method of an industrial vehicle, the method comprising the steps of:
a. the cloud server carries out physical modeling on the vehicle related components according to the physical/chemical characteristics of the actual industrial vehicle components;
b. uploading the original data of the industrial vehicle operation collected in real time to a cloud server through an intelligent terminal;
c. the cloud server screens the original data based on the relation between the physical/chemical characteristics of the corresponding working parameters of the related components and the health states of the components, and puts the obtained key data into the physical model for analysis to obtain the health states of the components of the industrial vehicle;
d. the cloud server synthesizes the health states of the related components of the industrial vehicle, generates a health report of the industrial vehicle and pushes the health report to an intelligent terminal user.
2. The method of claim 1, wherein, in the step b, the intelligent terminal uploads the raw data of the operation of the industrial vehicle to the cloud server in real time, or temporarily stores the raw data of the operation of the industrial vehicle and uploads the temporarily stored raw data to the cloud server at a preset time interval.
3. The method of claim 2, wherein the critical data in step c comprises: the running speed, the load weight, the voltage, the current and the temperature of the battery operation, and the voltage, the current and the temperature of the motor controller operation of the vehicle.
4. The method according to claim 1 or 3, wherein the statement of health of the industrial vehicle generated by the cloud-side server in the step d further comprises a rationalization suggestion given for maintenance of the industrial vehicle; and the cloud server can push the statement of health to the intelligent terminal user in real time and dynamically display the statement of health on the intelligent terminal, and can also respond to the user request and push the statement of health to the intelligent terminal.
5. A health state evaluation system of an industrial vehicle comprises a data acquisition module, an intelligent terminal and a cloud server, wherein the data acquisition module is used for distributing the industrial vehicle; the data acquisition module comprises a plurality of sensors distributed on the industrial vehicle and is used for acquiring original data of the industrial vehicle in real time and sending the original data to the intelligent terminal; the intelligent terminal is used for uploading the collected original data of the industrial vehicle operation to the cloud server, and receiving and displaying a health report of the industrial vehicle fed back by the cloud server; the cloud server performs physical modeling on vehicle related components in advance according to physical/chemical characteristics of actual industrial vehicle components, analyzes and predicts current and future health states of each component of the industrial vehicle based on physical/chemical rules between working parameters and health states of the industrial vehicle related components and in combination with models established for each component and key data related to each component, generates a health report of the industrial vehicle and pushes the health report to an intelligent terminal user, wherein the key data are data screened from the original data and used for analyzing the current health state of the industrial vehicle and predicting the future health state of the industrial vehicle.
6. The system of claim 5, wherein the intelligent terminal can upload the raw data of the operation of the industrial vehicle to the cloud server in real time, or can temporarily store the raw data of the operation of the industrial vehicle and upload the temporarily stored raw data to the cloud server at a preset time interval.
7. The system of claim 6, wherein the critical data comprises: the running speed, the load weight, the voltage, the current and the temperature of the battery operation, and the voltage, the current and the temperature of the motor controller operation of the vehicle.
8. The system according to claim 4 or 7, wherein the statement of health of the industrial vehicle further comprises rationalization suggestions given for the state of health of the industrial vehicle; and the cloud server can push the statement of health to the intelligent terminal user in real time and dynamically display the statement of health on the intelligent terminal, and can also respond to the user request and push the statement of health to the intelligent terminal.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910850505.XA CN110954335A (en) | 2019-09-10 | 2019-09-10 | Health assessment method and system for industrial vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910850505.XA CN110954335A (en) | 2019-09-10 | 2019-09-10 | Health assessment method and system for industrial vehicle |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110954335A true CN110954335A (en) | 2020-04-03 |
Family
ID=69976229
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910850505.XA Pending CN110954335A (en) | 2019-09-10 | 2019-09-10 | Health assessment method and system for industrial vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110954335A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111709542A (en) * | 2020-06-12 | 2020-09-25 | 浪潮集团有限公司 | Vehicle prediction diagnosis method based on fog computing environment |
| CN112738214A (en) * | 2020-12-24 | 2021-04-30 | 郑州嘉晨电器有限公司 | Industrial vehicle environment reconstruction method and system |
| CN112989490A (en) * | 2021-03-29 | 2021-06-18 | 重庆长安新能源汽车科技有限公司 | Method for online real-time evaluation of health state of electric drive system of electric vehicle |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103149042A (en) * | 2013-01-30 | 2013-06-12 | 大连理工大学（徐州）工程机械研究中心 | Safety evaluation decision making system of construction crane and safety evaluation decision making method thereof |
| CN107544290A (en) * | 2017-10-26 | 2018-01-05 | 南京越博电驱动***有限公司 | A kind of new-energy automobile Performance Evaluation analysis and optimization system and method |
| CN108382332A (en) * | 2018-02-26 | 2018-08-10 | 杭州翼兔网络科技有限公司 | A kind of electric vehicle integrated control Cloud Server |
| JP2018170144A (en) * | 2017-03-29 | 2018-11-01 | 三菱自動車工業株式会社 | Battery temperature estimation device and method, and battery state estimation device |
| CN109948169A (en) * | 2017-12-20 | 2019-06-28 | 中国中车股份有限公司 | A kind of railway freight-car prognostic and health management system |
-
2019
- 2019-09-10 CN CN201910850505.XA patent/CN110954335A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103149042A (en) * | 2013-01-30 | 2013-06-12 | 大连理工大学（徐州）工程机械研究中心 | Safety evaluation decision making system of construction crane and safety evaluation decision making method thereof |
| JP2018170144A (en) * | 2017-03-29 | 2018-11-01 | 三菱自動車工業株式会社 | Battery temperature estimation device and method, and battery state estimation device |
| CN107544290A (en) * | 2017-10-26 | 2018-01-05 | 南京越博电驱动***有限公司 | A kind of new-energy automobile Performance Evaluation analysis and optimization system and method |
| CN109948169A (en) * | 2017-12-20 | 2019-06-28 | 中国中车股份有限公司 | A kind of railway freight-car prognostic and health management system |
| CN108382332A (en) * | 2018-02-26 | 2018-08-10 | 杭州翼兔网络科技有限公司 | A kind of electric vehicle integrated control Cloud Server |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111709542A (en) * | 2020-06-12 | 2020-09-25 | 浪潮集团有限公司 | Vehicle prediction diagnosis method based on fog computing environment |
| CN112738214A (en) * | 2020-12-24 | 2021-04-30 | 郑州嘉晨电器有限公司 | Industrial vehicle environment reconstruction method and system |
| CN112989490A (en) * | 2021-03-29 | 2021-06-18 | 重庆长安新能源汽车科技有限公司 | Method for online real-time evaluation of health state of electric drive system of electric vehicle |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110647133B (en) | Rail transit equipment state detection maintenance method and system | |
| CN111241154B (en) | Storage battery fault early warning method and system based on big data | |
| EP2697699B1 (en) | Dynamic assessment system for high-voltage electrical components | |
| Wang et al. | On the application of a model of condition-based maintenance | |
| CN110954335A (en) | Health assessment method and system for industrial vehicle | |
| CN105809255A (en) | IoT-based heat-engine plantrotary machine health management method and system | |
| EP2051086A2 (en) | Method and system for remotely predicting the remaining life of an AC motor system | |
| EP2051366A1 (en) | Method and system for determining the reliability of a DC motor system | |
| KR20140130538A (en) | Method and system for diagnostic rules for heavy duty gas turbines | |
| CN112727965B (en) | Fault monitoring method and device for brake of coal mining machine | |
| US10963797B2 (en) | System for analyzing machine data | |
| KR100564362B1 (en) | Prevention system and the method for maintenance of railway car using RAMS analysis | |
| Tichý et al. | Predictive diagnostics usage for telematic systems maintenance | |
| KR101278428B1 (en) | Real-time collaborated enterprise asset management system based on condition-based maintenance and method thereof | |
| CN107121943B (en) | Method and device for obtaining health prediction information of intelligent instrument | |
| JP7308717B2 (en) | Platform door diagnostic device, platform door system, and platform door diagnostic program | |
| CN117761444B (en) | Method and system for monitoring service life of surge protector | |
| CN110765633A (en) | Intelligent management method and device for power device | |
| KR20130065844A (en) | System and method for managing energy equipments efficiency in intelligent building | |
| CN115660640A (en) | Intelligent automobile part fault diagnosis modeling method, electronic equipment and program product | |
| CN116413627A (en) | Method for estimating battery state and battery monitoring system | |
| KR102411915B1 (en) | System and method for froviding real time monitering and ai diagnosing abnormality sign for facilities and equipments | |
| KR102351070B1 (en) | Method for managing air quality improvement device and air quality improvement device applied with the same | |
| CN114037098A (en) | Intelligent management system for operation safety and maintenance of electric vehicle | |
| KR20130049232A (en) | System and method for monitoring of engine |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200403 |
|
| RJ01 | Rejection of invention patent application after publication |