CN107234982A - A kind of power battery charging method counted based on big data - Google Patents
A kind of power battery charging method counted based on big data Download PDFInfo
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- CN107234982A CN107234982A CN201710692215.8A CN201710692215A CN107234982A CN 107234982 A CN107234982 A CN 107234982A CN 201710692215 A CN201710692215 A CN 201710692215A CN 107234982 A CN107234982 A CN 107234982A
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- charging
- big data
- power battery
- charge control
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
- B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
- B60L58/12—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries responding to state of charge [SoC]
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
- B60L53/60—Monitoring or controlling charging stations
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L2240/00—Control parameters of input or output; Target parameters
- B60L2240/40—Drive Train control parameters
- B60L2240/54—Drive Train control parameters related to batteries
- B60L2240/545—Temperature
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L2240/00—Control parameters of input or output; Target parameters
- B60L2240/40—Drive Train control parameters
- B60L2240/54—Drive Train control parameters related to batteries
- B60L2240/547—Voltage
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/12—Electric charging stations
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/16—Information or communication technologies improving the operation of electric vehicles
Abstract
The invention discloses a kind of power battery charging method counted based on big data, this method includes input signal processing, big data statistic algorithm, charge control parameter setting and four steps of charge control；The charging ability of electrokinetic cell is obtained after input signal processing through excessive data statistics algorithm, charge control parameter is set afterwards, charge control is carried out.The present invention is to be based on existing battery management system, by in battery complete lifecycle, statistics application is carried out in electrokinetic cell practical application charging process, one avoids the difference of different application scene charging, secondly inconsistent application caused by avoiding under different application scene.
Description
Technical field
The present invention relates to new-energy automobile field, more particularly to a kind of power battery charging side counted based on big data
Method.
Background technology
Current Vehicular dynamic battery charge control, mainly using single charge control method.And this method is not adapted to
Different application scene, and be applicable also and non-fully for different operating modes.For example for fixed its charging of operation client and traveling road
Line is fixed, and has the good charging interval, and on-fixed operation client has charging rate in certain period of time and needed faster
Ask.
Design method relatively good at present, can provide different software versions, this mode increases for different operation scenes
Complicated version management and matching and calibration work.
The content of the invention
Existing battery management system is based on it is an object of the invention to overcome the deficiencies of the prior art and provide one kind, is led to
Cross in battery complete lifecycle, the power battery charging side of statistics application is carried out in electrokinetic cell practical application charging process
Method.
The purpose of the present invention is achieved through the following technical solutions：A kind of electrokinetic cell counted based on big data is filled
Method for electrically, this method includes input signal processing, big data statistic algorithm, charge control parameter setting and four steps of charge control
Suddenly；The charging ability of electrokinetic cell is obtained after input signal processing through excessive data statistics algorithm, sets charge control to join afterwards
Number, carries out charge control.
It is preferred that, input signal processing：Required for processing big data statistics and charge control parameter setting most
Polymeric monomer voltage and maximum temperature, battery charge ability parameter.
It is preferred that, big data statistic algorithm includes：Count the charging times in certain time and charging interval.It is excellent
Selection of land, counts intraday charging times and charging interval.
It is preferred that, charge control parameter setting：Charge-current demands are set, charge cutoff monomer voltage is set.
It is preferred that, charge control includes：Charged in actual charging process according to charge-current demands, when monomer electricity
Pressure reaches that cut-off monomer voltage then stops charging.
It is preferred that, input signal processing includes step：Calculate maximum monomer voltage MaxCellU；Calculate maximum electricity
Pond temperature MatT；Tabled look-up by temperature and obtain power battery charging ability ChrgI；
Big data statistic algorithm includes step：Record daily charging times ChrgN；Record daily charging interval ChrgT
(h)；Be input to by ChrgN and ChrgT in big data algorithm, obtain big data count daily charging times trend parameter A and
Big data counts daily charging interval trend parameter B；
Charge control parameter setting method includes step：If parameter A>A (t-1) and parameter B>B (t-1) is set up simultaneously,
Then illustrate trend increase when the daily demand charging times of the user and charging, then (preferably, a takes phase ReqChrgI=ChrgI*a
1.2), increase charge requirement electric current ReqChrgI；Otherwise A is judged<A (t-1) and parameter B<B (t-1) is set up simultaneously, then explanation should
The daily demand charging times of user and charging interval trend are reduced, then (preferably, 0.8) b takes ReqChrgI=ChrgI*b, subtracts
Small charge requirement electric current ReqChrgI；If above two Rule of judgment are unsatisfactory for, ReqChrgI=ChrgI, charging is needed
Electric current ReqChrgI is asked to be charged according to electrokinetic cell ability；
Charge control method includes step：It is more than or equal to charging if voltage if maximum monomer voltage MaxCellU
Stop charging, otherwise charge normal.
It is preferred that, the table that temperature is tabled look-up is determined by electrokinetic cell characteristic.
It is preferred that, calculated and counted greatly according to daily charging times ChrgN and daily charging interval ChrgT (h)
Daily charging times trend parameter A and big data, which count daily charging interval trend parameter B, according to statistics is counted on cloud backstage
Calculate.
The beneficial effects of the invention are as follows：The present invention is to be based on existing battery management system, passes through the complete Life Cycle of battery
In phase, statistics application is carried out in electrokinetic cell practical application charging process, one avoids the charging of different application scene not
Together, secondly inconsistent application caused by avoiding under different application scene.
Brief description of the drawings
Fig. 1 is control method block schematic illustration in the present invention；
Fig. 2 is input signal processing schematic diagram in the present invention；
Fig. 3 is big data statistic algorithm schematic diagram in the present invention；
Fig. 4 is charge control parameter setting schematic diagram in the present invention；
Fig. 5 is charge control schematic diagram in the present invention.
Embodiment
Technical scheme is described in further detail below in conjunction with the accompanying drawings, but protection scope of the present invention is not limited to
It is as described below.
As shown in Fig. 1~Fig. 5, a kind of power battery charging method counted based on big data, this method is included input and believed
Number processing, big data statistic algorithm, charge control parameter setting and four steps of charge control；Through excessive after input signal processing
Data statistics algorithm obtains the charging ability of electrokinetic cell, and charge control parameter is set afterwards, carries out charge control.
It is preferred that, input signal processing：Required for processing big data statistics and charge control parameter setting most
Polymeric monomer voltage and maximum temperature, battery charge ability parameter.
It is preferred that, big data statistic algorithm includes：Count the charging times in certain time and charging interval.It is excellent
Selection of land, counts intraday charging times and charging interval.
It is preferred that, charge control parameter setting：Charge-current demands are set, charge cutoff monomer voltage is set.
It is preferred that, charge control includes：Charged in actual charging process according to charge-current demands, when monomer electricity
Pressure reaches that cut-off monomer voltage then stops charging.
It is preferred that, input signal processing includes step：Calculate maximum monomer voltage MaxCellU；Calculate maximum electricity
Pond temperature MatT；Tabled look-up by temperature and obtain power battery charging ability ChrgI；
Big data statistic algorithm includes step：Record daily charging times ChrgN；Record daily charging interval ChrgT
(h)；Be input to by ChrgN and ChrgT in big data algorithm, obtain big data count daily charging times trend parameter A and
Big data counts daily charging interval trend parameter B, and big data algorithm includes recurrence/cluster/decision tree etc.；
Charge control parameter setting method includes step：If parameter A>A (t-1) and parameter B>B (t-1) is set up simultaneously,
Then illustrate trend increase when the daily demand charging times of the user and charging, then (preferably, a takes phase ReqChrgI=ChrgI*a
1.2), increase charge requirement electric current ReqChrgI；Otherwise A is judged<A (t-1) and parameter B<B (t-1) is set up simultaneously, then explanation should
The daily demand charging times of user and charging interval trend are reduced, then (preferably, 0.8) b takes ReqChrgI=ChrgI*b, subtracts
Small charge requirement electric current ReqChrgI；If above two Rule of judgment are unsatisfactory for, ReqChrgI=ChrgI, charging is needed
Electric current ReqChrgI is asked to be charged according to electrokinetic cell ability；
Charge control method includes step：If maximum monomer voltage MaxCellU is more than or equal to charging by voltage
(different battery chargings are different by voltage, such as ternary lithium ion battery is 4.2V by voltage) then stop charging, otherwise just
Often charging.
It is preferred that, the table that temperature is tabled look-up is determined by electrokinetic cell characteristic, and different temperatures battery allows electric current different：
Such as 20 DEG C to 40 DEG C are 1C, and it is 0 that 0 DEG C, which is 0,65 DEG C,.
It is preferred that, calculated and counted greatly according to daily charging times ChrgN and daily charging interval ChrgT (h)
Daily charging times trend parameter A and big data, which count daily charging interval trend parameter B, according to statistics is counted on cloud backstage
Calculate.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, it is noted that all
Any modifications, equivalent substitutions and improvements made within the spirit and principles in the present invention etc., should be included in the guarantor of the present invention
Within the scope of shield.
Claims (10)
1. a kind of power battery charging method counted based on big data, it is characterised in that：This method include input signal processing,
Big data statistic algorithm, four steps of charge control parameter setting and charge control；United after input signal processing by big data
Calculating method obtains the charging ability of electrokinetic cell, and charge control parameter is set afterwards, carries out charge control.
2. a kind of power battery charging method counted based on big data according to claim 1, it is characterised in that input
Signal transacting：Handle the maximum monomer voltage and maximum temperature required for big data statistics and charge control parameter setting, battery
Charging current ability parameter.
3. a kind of power battery charging method counted based on big data according to claim 1 or 2, it is characterised in that
Big data statistic algorithm includes：Count the charging times in certain time and charging interval.
4. a kind of power battery charging method counted based on big data according to claim 3, it is characterised in that statistics
Intraday charging times and charging interval.
5. a kind of power battery charging method counted based on big data according to claim 1 or 4, it is characterised in that
Charge control parameter setting：Charge-current demands are set, charge cutoff monomer voltage is set.
6. a kind of power battery charging method counted based on big data according to claim 5, it is characterised in that charging
Control includes：Charged in actual charging process according to charge-current demands, when monomer voltage reaches that cut-off monomer voltage then stops
Charging.
7. a kind of power battery charging method counted based on big data according to claim 1, it is characterised in that：
Input signal processing includes step：Calculate maximum monomer voltage MaxCellU；Calculate largest battery temperature MatT；Pass through temperature
Degree, which is tabled look-up, obtains power battery charging ability ChrgI；
Big data statistic algorithm includes step：Record daily charging times ChrgN；Record daily charging interval ChrgT (h)；It is logical
Cross ChrgN and ChrgT to be input in big data algorithm, obtain big data and count daily charging times trend parameter A and big data
Count daily charging interval trend parameter B；
Charge control parameter setting method includes step：If parameter A>A (t-1) and parameter B>B (t-1) is set up simultaneously, then is said
Trend increase when the bright daily demand charging times of the user and charging, then phase ReqChrgI=ChrgI*a, increases charge requirement electricity
Flow ReqChrgI；Otherwise A is judged<A (t-1) and parameter B<B (t-1) is set up simultaneously, then illustrates the daily demand charging time of the user
Number and charging interval trend are reduced, then ReqChrgI=ChrgI*b, reduce charge requirement electric current ReqChrgI；If above two
Individual Rule of judgment is unsatisfactory for, then ReqChrgI=ChrgI, and charge requirement electric current ReqChrgI is carried out according to electrokinetic cell ability
Charging；
Charge control method includes step：It is more than or equal to charging if maximum monomer voltage MaxCellU if voltage to stop
Charging, is otherwise charged normal.
8. a kind of power battery charging method counted based on big data according to claim 7, it is characterised in that：Temperature
The table tabled look-up is determined by electrokinetic cell characteristic.
9. a kind of power battery charging method counted based on big data according to claim 7 or 8, it is characterised in that：
Calculated according to daily charging times ChrgN and daily charging interval ChrgT (h) and obtain the daily charging times trend of big data statistics
Parameter A and big data count daily charging interval trend parameter B and calculated on cloud backstage.
10. a kind of power battery charging method counted based on big data according to claim 7, it is characterised in that：A takes
1.2, b take 0.8.
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| CN201710692215.8A CN107234982B (en) | 2017-08-14 | 2017-08-14 | A kind of power battery charging method based on big data statistics |
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| CN201710692215.8A CN107234982B (en) | 2017-08-14 | 2017-08-14 | A kind of power battery charging method based on big data statistics |
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| CN107234982A true CN107234982A (en) | 2017-10-10 |
| CN107234982B CN107234982B (en) | 2019-05-07 |
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0711016A2 (en) * | 1994-11-04 | 1996-05-08 | Mitsubishi Denki Kabushiki Kaisha | Parameter measuring method, charge/discharge control method and apparatus and life predicting method for secondary batteries and power storage apparatus using the same |
| US20090243549A1 (en) * | 2008-03-31 | 2009-10-01 | Naoki Matsumura | Intelligent battery charging rate management |
| CN103872398A (en) * | 2012-12-13 | 2014-06-18 | 财团法人工业技术研究院 | Charging method of rechargeable battery and related charging structure |
| CN203660620U (en) * | 2014-01-28 | 2014-06-18 | 林家宏 | Charging control circuit for battery of mobile device |
| CN104852435A (en) * | 2015-05-22 | 2015-08-19 | 聊城大学 | Electric automobile serial lithium battery management system and a management method thereof |
| CN105826976A (en) * | 2016-03-30 | 2016-08-03 | 维沃移动通信有限公司 | Mobile terminal charging method and mobile terminal |
-
2017
- 2017-08-14 CN CN201710692215.8A patent/CN107234982B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0711016A2 (en) * | 1994-11-04 | 1996-05-08 | Mitsubishi Denki Kabushiki Kaisha | Parameter measuring method, charge/discharge control method and apparatus and life predicting method for secondary batteries and power storage apparatus using the same |
| US20090243549A1 (en) * | 2008-03-31 | 2009-10-01 | Naoki Matsumura | Intelligent battery charging rate management |
| CN103872398A (en) * | 2012-12-13 | 2014-06-18 | 财团法人工业技术研究院 | Charging method of rechargeable battery and related charging structure |
| CN203660620U (en) * | 2014-01-28 | 2014-06-18 | 林家宏 | Charging control circuit for battery of mobile device |
| CN104852435A (en) * | 2015-05-22 | 2015-08-19 | 聊城大学 | Electric automobile serial lithium battery management system and a management method thereof |
| CN105826976A (en) * | 2016-03-30 | 2016-08-03 | 维沃移动通信有限公司 | Mobile terminal charging method and mobile terminal |
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| CN107234982B (en) | 2019-05-07 |
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Effective date of registration: 20210427 Address after: 406, 4th floor, building 9, no.388, section 3, Chenglong Avenue, Chengdu Economic and Technological Development Zone (Longquanyi District), Sichuan 610000 Patentee after: Chengdu Yajun New Energy Technology Co.,Ltd. Address before: 610000 Sichuan city of Chengdu province Tianfu New Street Youfang village nine Group No. 300 emerging industrial park building B1 1-3 Patentee before: CHENGDU RAJA NEW ENERGY AUTOMOBILE SCIENCE AND TECHNOLOGY Co.,Ltd. |
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