GB2618505A - Test method performed with design of experiment created by an artificial intelligence - Google Patents
Test method performed with design of experiment created by an artificial intelligence Download PDFInfo
- Publication number
- GB2618505A GB2618505A GB2313056.0A GB202313056A GB2618505A GB 2618505 A GB2618505 A GB 2618505A GB 202313056 A GB202313056 A GB 202313056A GB 2618505 A GB2618505 A GB 2618505A
- Authority
- GB
- United Kingdom
- Prior art keywords
- data
- artificial intelligence
- test method
- intelligence module
- design
- 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
- 238000013473 artificial intelligence Methods 0.000 title claims abstract 16
- 238000010998 test method Methods 0.000 title claims abstract 13
- 238000013400 design of experiment Methods 0.000 title claims abstract 11
- 238000012549 training Methods 0.000 claims abstract 10
- 238000004088 simulation Methods 0.000 claims abstract 8
- 238000012544 monitoring process Methods 0.000 claims abstract 5
- 238000000034 method Methods 0.000 claims abstract 2
- 238000013528 artificial neural network Methods 0.000 claims 2
- 238000005259 measurement Methods 0.000 claims 2
- 238000011156 evaluation Methods 0.000 claims 1
- 238000012360 testing method Methods 0.000 claims 1
Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/088—Non-supervised learning, e.g. competitive learning
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- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Biomedical Technology (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Health & Medical Sciences (AREA)
- Supply And Distribution Of Alternating Current (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to a computer implemented test method comprising creation of a battery model (20) generated by a virtual data generator (12) in a control unit (10) indicating the dynamics of the battery, collecting at least one piece of data and at least one second piece of data from the created battery model (20) by means of a data collector (14), converting the obtained first and second pieces of data into a training data by a controller (16), training an artificial intelligence module (30) using the training data to create an design of experiment for batteries. Test method further comprising the process steps of creation of an design of experiment by a processor (32) in the artificial intelligence module (30), determining the parameters to be tested with the design of experiment, creating a simulation environment (40) by a simulation generator (34) of the artificial intelligence module (30) with the determined parameters, monitoring the battery dynamics according to the changing parameters of the batteries with an monitoring unit (36) inside the artificial intelligence module (30).
Claims (1)
1- A computer implemented test method comprising, to create a battery model (20) generated by a virtual data generator (12) in a control unit (10) indicating the dynamics of the battery, collecting at least one piece of data and at least one second piece of data from the created battery model (20) by means of a data collector (14), converting the obtained first and second pieces of data into a training data by a controller (16), training an artificial intelligence module (30) using the training data to create an design of experiment for batteries characterized by comprising the process steps of creation of an design of experiment by a processor (32) in the artificial intelligence module (30), determining the parameters to be tested with the design of experiment, creating a simulation environment (40) by a simulation generator (34) of the artificial intelligence module (30) with the determined parameters, monitoring the battery dynamics according to the changing parameters of the batteries with an monitoring unit (36) inside the artificial intelligence module (30).
2- A test method according to claim 1 , wherein the parameters are selected from the group comprising the temperature, voltage and charge state.
3- A test method according to any one of the preceding claims, wherein a current of a predetermined value is applied to the battery in the simulation environment (40) by the processor (32) in the artificial intelligence module (30) in a way that corresponds to the changing parameters.
4- A test method according to any of the preceding claims, comprising the step of obtaining at least three pieces of data by means of the data collector (14) by matching the data at each measurement point by measuring the dynamics of the battery simultaneously and repeatedly in the battery model (20).
5- A test method according to Claim 4, comprising the step of obtaining a training data by merging the corresponding voltage, current and temperature change data of the first, second and third data pieces with the capacities of the batteries at the time of measurement by means of the controller (16).
6- A test method according to any of the preceding claims, wherein the design of experiment created with the artificial intelligence module (30) provides an input data and a variation range of input data variables.
7- A test method according to any of the preceding claims, comprising the steps of evaluation the battery dynamics according to the changing parameters using an actor neural network and a critic neural network and generate an output data.
8- A test method according to claim 7, wherein the output data is saved in a memory unit (16) located in the control unit (10).
9- A test method according to any of the preceding claims, wherein a reward mechanism is applied by the controller (16) such that reducing the test time of the artificial intelligence module (30) on the batteries.
10- A computer implemented test method comprising the steps of creation of a virtual model (70) by means of a virtual data generator (12) in a control unit (10) in a way that shows the dynamics of the dynamic system (60), collecting at least one piece of data and at least one second piece of data from the generated virtual model by means of a data collector (14), converting obtained first and second pieces of data into a training data by a controller (16), training an artificial intelligence module (30) using the training data to form an design of experiment profile characterized by, creating an design of experiment by a processor (32) in the artificial intelligence module (30), determining the parameters to be tested with the design of experiment, creating a simulation environment (40) by a simulation generator (34) in the artificial intelligence module (30) with the determined parameters, observing the dynamics of the dynamic system (60) according to the changing parameters in the simulation environment with a monitoring unit (36) in the artificial intelligence module (30).
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/TR2021/050090 WO2022164400A2 (en) | 2021-11-08 | 2021-11-08 | Test method performed with design of experiment created by an artificial intelligence |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| GB202313056D0 GB202313056D0 (en) | 2023-10-11 |
| GB2618505A true GB2618505A (en) | 2023-11-08 |
Family
ID=82654866
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| GB2313056.0A Pending GB2618505A (en) | 2021-11-08 | 2021-11-08 | Test method performed with design of experiment created by an artificial intelligence |
Country Status (2)
| Country | Link |
|---|---|
| GB (1) | GB2618505A (en) |
| WO (1) | WO2022164400A2 (en) |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20180037760A (en) * | 2016-10-05 | 2018-04-13 | 삼성전자주식회사 | Device and method to estimate state of battery |
| CN110210147B (en) * | 2019-06-05 | 2021-03-12 | 杭州华塑科技股份有限公司 | Simulation device and simulation method for estimating battery health state |
| AU2021101964A4 (en) * | 2021-04-16 | 2021-06-03 | Anoop Arya | Artificial intelligence based smart electric vehicle battery management system |
-
2021
- 2021-11-08 WO PCT/TR2021/050090 patent/WO2022164400A2/en unknown
- 2021-11-08 GB GB2313056.0A patent/GB2618505A/en active Pending
Non-Patent Citations (1)
| Title |
|---|
| NOT ADVISED * |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2022164400A2 (en) | 2022-08-04 |
| WO2022164400A8 (en) | 2023-09-21 |
| WO2022164400A3 (en) | 2023-12-07 |
| GB202313056D0 (en) | 2023-10-11 |
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