CN102520366B - Electric car cell safety and health assessment system and method thereof - Google Patents
Electric car cell safety and health assessment system and method thereof Download PDFInfo
- Publication number
- CN102520366B CN102520366B CN201110441125.4A CN201110441125A CN102520366B CN 102520366 B CN102520366 B CN 102520366B CN 201110441125 A CN201110441125 A CN 201110441125A CN 102520366 B CN102520366 B CN 102520366B
- Authority
- CN
- China
- Prior art keywords
- battery
- value
- driving
- information
- voltage
- 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.)
- Expired - Fee Related
Links
Landscapes
- Electric Propulsion And Braking For Vehicles (AREA)
- Secondary Cells (AREA)
Abstract
The invention discloses an electric car cell safety and health assessment system and a method thereof. The system comprises a charging control module, a driving cell lossless rapid test module, a driving cell safety assessment module, a driving cell health state assessment module, a driving cell residual electric quantity assessment module, a driving cell information storage module and a cell information display module. According to the system and the method of the invention, through a lossless cell rapid detection method, a driving cell is subjected to a rapid charge and discharge test, simultaneously, corresponding current, voltage and cell temperature information of the driving cell are acquired, response data of the driving cell to the charge and discharge test is inputted to a related algorithm model, thus dynamic performance of the driving cell is analyzed, and corresponding safety state information, health state information and residual electric quantity assessment information are obtained. The system can be arranged at sites of a charging station and the like, operation is simple, accuracy is high, and a response speed is fast.
Description
Technical field
The present invention relates to a kind of battery evaluating system and method thereof, relate in particular to a kind of safety and Health evaluating system and method thereof of the battery for electric motor car.
Background technology
In recent years, along with rechargeable battery technology is fast-developing, and the attention degree that various countries pollute harmful gas and carbon emission constantly increases, and electric motor car has progressed into people's the visual field, and becomes the automobile industry developing direction in future.Wherein, electric motor car includes pure electric vehicle (EV), hybrid-power electric vehicle (HEV) and plug-in hybrid electric vehicle (PHEV).
No matter be the electric motor car of which kind of type, battery is the primary key of its development.The battery that is applied to electric motor car should meet this four large requirement that cost is low, capacity is large, the life-span is long and security is good.Yet, because current electrochemical energy storage technology is still immature, the unexpected pyrophoricity accident that the battery produced the is accidental and quality of production is uneven causes the development of electric motor car to be stagnated to some extent.Therefore, a lot of research and development at present concentrate on the aspect of stability of material and the fabrication reliability of battery.Detection assessment for battery is also confined to these aspects of battery dump energy and battery mostly, and does not relate to for the safety and Health aspect of battery.
Summary of the invention
Because the above-mentioned defect of prior art, technical matters to be solved by this invention is to provide a kind of battery of electric vehicle safety and Health evaluating system and method thereof, it can carry out real-time assessment and demonstration to the security of battery of electric vehicle and health degree, with the very first time current state of electrolytic cell, guarantee the use of its safety and Health.
For achieving the above object, the invention provides a kind of battery of electric vehicle safety and Health evaluating system, it comprises:
Charge control module, thus it is connected driving battery to discharge and recharge operation with driving battery module, obtains the battery information of described driving battery;
Drive the harmless quick test module of battery, it is sent to described charge control module by predefined charge/discharge setting value sequence, and from described charge control module, obtains the battery information of described driving battery;
Drive cell safety evaluation module, it produces the safety state information of described driving battery;
Drive cell health state evaluation module, it produces the health status information of described driving battery;
The assessment of driving battery dump energy, it produces the dump energy appreciation information of described driving battery;
Drive battery information memory module, it stores battery information, safety state information, health status information and the dump energy appreciation information of described driving battery;
And battery information display module, it shows battery information, safety state information, health status information and the dump energy appreciation information of described driving battery;
Wherein, described charge control module, electric motor car drive the harmless quick test module of battery, driving cell safety evaluation module, drive cell health state evaluation module, drive battery dump energy assessment, drive battery information memory module to be connected successively with battery information display module, and described display module is connected with described charge control module.
Above-mentioned battery of electric vehicle safety and Health evaluating system, wherein, the battery information of described driving battery comprises voltage, electric current, the battery temperature that drives battery.
Above-mentioned battery of electric vehicle safety and Health evaluating system, wherein, described battery information display module is arranged on smart mobile phone or panel computer.
In addition, the present invention also provides a kind of battery of electric vehicle safety and Health appraisal procedure, and it comprises the following steps:
To driving battery to discharge and recharge operation, gather the battery information of described driving battery simultaneously;
Assess the safe condition of described driving battery, obtain the safety state information of described driving battery;
Assess the health status of described driving battery, obtain the health status information of described driving battery;
Assess the dump energy assessment of described driving battery, obtain the dump energy appreciation information of described driving battery;
Store battery information, safety state information, health status information and the dump energy appreciation information of described driving battery;
The battery information, safety state information, health status information and the dump energy appreciation information that show described driving battery.
Above-mentioned battery of electric vehicle safety and Health appraisal procedure, wherein, the battery information of described driving battery comprises voltage, electric current, the battery temperature that drives battery.
Above-mentioned battery of electric vehicle safety and Health appraisal procedure, wherein, discharges and recharges operation according to predefined charge/discharge setting value sequence to described driving battery.
Above-mentioned battery of electric vehicle safety and Health appraisal procedure, wherein, assesses the safe condition of described driving battery in the following way: CV
saf=R[f (I), g (V), h (T)], wherein, CV
safrepresent confidence in security value, I is for driving the current value of battery, V is for driving the magnitude of voltage of battery, T is for driving the temperature of battery, the current characteristic that f (I) calculates through special algorithm for current value, the current characteristic that g (V) calculates through special algorithm for magnitude of voltage, the temperature profile that h (T) calculates through special algorithm for battery temperature value, R[f (I), g (V), h (T)] be that current characteristic, voltage characteristic and temperature profile calculate safety assessment confidence value through special algorithm; Wherein, for calculating the special algorithm of described current characteristic, voltage characteristic and temperature profile, be: with Wavelet Packet Algorithm to adopt the time series of current value, magnitude of voltage and temperature value decompose and calculate the energy of wavelet decomposition Shu Shangge branch, local peak-to-peak value, local maximum, local minimum, crest factor, the degree of bias; Algorithm based on described current characteristic, voltage characteristic and temperature profile computationally secure assessment confidence value comprises: Artificial Neural Network, Self-organizing Maps method and regression algorithm, the current characteristic of described description battery status, voltage characteristic and temperature profile DUAL PROBLEMS OF VECTOR MAPPING are arrived to unified safe probability space, and to user, show 0 to 1 safe probability value, wherein: 0 represents that battery had lost efficacy and extremely danger; 1 represents that battery operation is in good condition and does not have potential safety hazard completely; Value between 0 to 1 represents the cell safety state between two kinds of extremities above.
Above-mentioned battery of electric vehicle safety and Health appraisal procedure, wherein, assesses the health status of described driving battery in the following way: CV
health=U[f (I), g (V), h (T)], wherein, CV
healthrepresent healthy confidence value, I is for driving the current value of battery, V is for driving the magnitude of voltage of battery, T is for driving the temperature of battery, the current characteristic that f (I) calculates through special algorithm for current value, the current characteristic that g (V) calculates through special algorithm for magnitude of voltage, the temperature profile that h (T) calculates through special algorithm for battery temperature value, U[f (I), g (V), h (T)] be current characteristic, voltage characteristic and temperature profile calculate health status assessment confidence value through special algorithm, wherein, be used for calculating described current characteristic, the special algorithm of voltage characteristic and temperature profile is: with Wavelet Packet Algorithm to adopt current value, the energy of wavelet decomposition Shu Shangge branch is decomposed and calculated to the time series of magnitude of voltage and temperature value, local peak-to-peak value, local maximum, local minimum, crest factor, the degree of bias, the algorithm that calculates health status assessment confidence value based on described current characteristic, voltage characteristic and temperature profile comprises: Artificial Neural Network, Self-organizing Maps method and regression algorithm, the current characteristic of described description battery status, voltage characteristic and temperature profile DUAL PROBLEMS OF VECTOR MAPPING are arrived to unified safe probability space, and to user, show 0 to 1 safe probability value, wherein: 0 represents that battery had lost efficacy and extremely danger, 1 represents that battery operation is in good condition and does not have potential safety hazard completely, value between 0 to 1 represents the cell safety state between two kinds of extremities above.Above-mentioned battery of electric vehicle safety and Health appraisal procedure, wherein, assess the dump energy assessment of described driving battery in the following way: SOC=C[f (I), g (V), h (T)], wherein, SOC is for driving the residual electric quantity of battery, I is for driving the current value of battery, V is for driving the magnitude of voltage of battery, T is for driving the temperature of battery, the current characteristic that f (I) calculates through special algorithm for current value, the current characteristic that g (V) calculates through special algorithm for magnitude of voltage, the temperature profile that h (T) calculates through special algorithm for battery temperature value, C[f (I), g (V), h (T)] be current characteristic, voltage characteristic and temperature profile calculate dump energy assessed value through special algorithm, wherein, be used for calculating described current characteristic, the special algorithm of voltage characteristic and temperature profile is: with Wavelet Packet Algorithm to adopt current value, the energy of wavelet decomposition Shu Shangge branch is decomposed and calculated to the time series of magnitude of voltage and temperature value, local peak-to-peak value, local maximum, local minimum, crest factor, the degree of bias, the algorithm that calculates dump energy assessed value based on described current characteristic, voltage characteristic and temperature profile is: by the current characteristic of described battery, voltage characteristic and temperature profile vector are estimated to dump energy with the model of dump energy, the model of assessment dump energy can be realized by Artificial Neural Network, Self-organizing Maps method or linearity or non-linear interpolation algorithm.
Above-mentioned battery of electric vehicle safety and Health appraisal procedure, wherein, adopts cloud computing to carry out the assessment of safe condition, health status and the dump energy of described driving battery.
Therefore, battery of electric vehicle safety and Health evaluating system of the present invention and method thereof are carried out fast charging and discharging test by a kind of harmless battery method for quick to driving battery, gather the corresponding electric current that drives battery simultaneously, voltage and battery temperature information, and will drive battery to be input in related algorithm model the response data of charge-discharge test, thereby the dynamic property of analysis-driven battery, obtain corresponding safety state information, health status information and dump energy appreciation information, it can be arranged on the ground such as charging station, simple to operate, accuracy is high, fast response time.
Accompanying drawing explanation
Fig. 1 is the structural representation of a kind of battery of electric vehicle safety and Health evaluating system of the present invention.
Embodiment
Below with reference to accompanying drawing, the technique effect of design of the present invention, concrete structure and generation is described further, to understand fully object of the present invention, feature and effect.
As shown in Figure 1, electric motor car of the present invention drives cell safety and health evaluation system to include charge control module 102, electric motor car drives the harmless quick test module 103 of battery, drives cell safety evaluation module 104, drives cell health state evaluation module 105, drives battery dump energy evaluation module 106, drives battery information memory module 107 and battery information display module 108, above-mentioned module is connected successively, and last battery information display module 108 is connected with charge control module 102.This electric motor car drives cell safety and health evaluation system can be arranged on charging station.When electric motor car is during in charging station charging or rest, can drive easily the safety and Health state estimation of battery.
When driving battery is discharged and recharged to operation according to predefined charge/discharge setting value sequence, drive electric current, voltage and the battery temperature of battery can produce corresponding variation.According to the variation of above-mentioned electric current, voltage and battery temperature, can analyze and obtain driving cell safety and health and fitness information.
Particularly, first drive battery module 101 to be connected charge control module 102 and electric motor car.Drive after the predefined charge/discharge setting value sequence that the harmless quick test module 103 of battery sends receiving electric motor car, 102 pairs of charge control module drive batteries to carry out and discharge and recharge operation, gather corresponding battery information simultaneously.Wherein, battery information comprises voltage, electric current and the battery temperature that drives battery while discharging and recharging; Then, charge control module 102 will obtain above-mentioned battery information and be sent to electric motor car and drive in the harmless quick test module 103 of battery; Electric motor car drives the harmless quick test module 103 of battery more above-mentioned battery information to be sent to and drives in cell safety evaluation module 104, and obtains driving the safety state information of battery; Then, battery information before and safety state information are together sent in driving cell health state evaluation module 105, to obtain driving the health status information of battery; Again this health status information is together sent to and is driven in battery dump energy evaluation module 106, to obtain driving the dump energy appreciation information of battery together with battery information before and safety state information; The battery information obtaining, safety state information, health status information and residual circuit appreciation information are together stored into and driven in battery information memory module 107; Finally in driving battery information display module 108, demonstrate above-mentioned battery information, safety state information, health status information and residual circuit appreciation information, for user's real time inspection.Wherein, drive the health status information of battery also to comprise the rechargeable use residual life information that drives battery.
In driving cell safety evaluation module 104, by adopting mode below to assess the safe condition that drives battery, thereby obtain driving the safety state information of battery: CV
saf=R[f (I), g (V), h (T)], wherein, CV
safrepresent confidence in security value, I is for driving the current value of battery, V is for driving the magnitude of voltage of battery, T is for driving the temperature of battery, the current characteristic that f (I) calculates through special algorithm for current value, the current characteristic that g (V) calculates through special algorithm for magnitude of voltage, the temperature profile that h (T) calculates through special algorithm for battery temperature value, R[f (I), g (V), h (T)] be that current characteristic, voltage characteristic and temperature profile calculate safety assessment confidence value through special algorithm.Wherein, for calculating the special algorithm of current characteristic, voltage characteristic and temperature profile, be: with Wavelet Packet Algorithm to adopt the time series of current value, magnitude of voltage and temperature value decompose and calculate the energy of wavelet decomposition Shu Shangge branch, local peak-to-peak value, local maximum, local minimum, crest factor, the degree of bias; Algorithm based on current characteristic, voltage characteristic and temperature profile computationally secure assessment confidence value comprises: Artificial Neural Network, Self-organizing Maps method and regression algorithm, the current characteristic of described description battery status, voltage characteristic and temperature profile DUAL PROBLEMS OF VECTOR MAPPING are arrived to unified safe probability space, and to user, show 0 to 1 safe probability value, wherein: 0 represents that battery had lost efficacy and extremely danger; 1 represents that battery operation is in good condition and does not have potential safety hazard completely; Value between 0 to 1 represents the cell safety state between two kinds of extremities above.In driving cell health state evaluation module 105, by adopting mode below to assess the health status that drives battery, thereby obtain driving the health status information of battery: CV
health=U[f (I), g (V), h (T)], wherein, CV
healthrepresent healthy confidence value, I is for driving the current value of battery, V is for driving the magnitude of voltage of battery, T is for driving the temperature of battery, the current characteristic that f (I) calculates through special algorithm for current value, the current characteristic that g (V) calculates through special algorithm for magnitude of voltage, the temperature profile that h (T) calculates through special algorithm for battery temperature value, U[f (I), g (V), h (T)] for calculating health status through special algorithm, current characteristic, voltage characteristic and temperature profile assess confidence value.Wherein, for calculating the special algorithm of described current characteristic, voltage characteristic and temperature profile, be: with Wavelet Packet Algorithm to adopt the time series of current value, magnitude of voltage and temperature value decompose and calculate the energy of wavelet decomposition Shu Shangge branch, local peak-to-peak value, local maximum, local minimum, crest factor, the degree of bias, based on described current characteristic, the algorithm that voltage characteristic and temperature profile calculate health status assessment confidence value comprises: Artificial Neural Network, Self-organizing Maps method, and regression algorithm, by the current characteristic of described description battery status, voltage characteristic and temperature profile DUAL PROBLEMS OF VECTOR MAPPING are to unified safe probability space, and to user, show 0 to 1 safe probability value, wherein: 0 represents that battery had lost efficacy and extremely danger, 1 represents that battery operation is in good condition and does not have potential safety hazard completely, value between 0 to 1 represents the cell safety state between two kinds of extremities above.
In driving battery dump energy evaluation module 106, by adopting mode below, assess the dump energy that drives battery, thereby obtain driving the dump energy appreciation information of battery: SOC=C[f (I), g (V), h (T)], wherein, SOC is for driving the residual electric quantity of battery, I is for driving the current value of battery, V is for driving the magnitude of voltage of battery, T is for driving the temperature of battery, the current characteristic that f (I) calculates through special algorithm for current value, the current characteristic that g (V) calculates through special algorithm for magnitude of voltage, the temperature profile that h (T) calculates through special algorithm for battery temperature value, C[f (I), g (V), h (T)] be current characteristic, voltage characteristic and temperature profile calculate dump energy assessed value through special algorithm.Wherein, for calculating the special algorithm of described current characteristic, voltage characteristic and temperature profile, be: with Wavelet Packet Algorithm to adopt the time series of current value, magnitude of voltage and temperature value decompose and calculate the energy of wavelet decomposition Shu Shangge branch, local peak-to-peak value, local maximum, local minimum, crest factor, the degree of bias; The algorithm that calculates dump energy assessed value based on described current characteristic, voltage characteristic and temperature profile is: by the current characteristic of described battery, voltage characteristic and temperature profile vector are estimated to dump energy with the model of dump energy, the model of assessment dump energy can be realized by Artificial Neural Network, Self-organizing Maps method or linearity or non-linear interpolation algorithm.
In the present invention, can adopt cloud computing technology that electric motor car is driven to cell safety evaluation module 104, drives cell health state evaluation module 105 and drives battery dump energy evaluation module 106 to be arranged on charging station and remote data center, thereby in the scale of the charging of charging station and assessment wait queue, adjust computational resource according to electric motor car, thereby realize the telescopic real-time calculating of high-performance, scale that electric motor car is driven to battery group, effectively improve resource utilization.
In addition, drive battery information display module 108 can be arranged on smart mobile phone or panel computer, so that real-time the reading of user drives the relevant information of battery, guarantee to drive cell safety effectively to use.
More than describe preferred embodiment of the present invention in detail.The ordinary skill that should be appreciated that this area just can design according to the present invention be made many modifications and variations without creative work.Therefore, all technician in the art, all should be in the determined protection domain by claims under this invention's idea on the basis of existing technology by the available technical scheme of logical analysis, reasoning, or a limited experiment.
Claims (9)
1. a battery of electric vehicle safety and Health evaluating system, is characterized in that, comprises
Charge control module, thus it is connected driving battery to discharge and recharge operation with driving battery module, obtains the battery information of described driving battery;
Drive the harmless quick test module of battery, it is sent to described charge control module by predefined charge/discharge setting value sequence, and from described charge control module, obtains the battery information of described driving battery;
Drive cell safety evaluation module, it produces the safety state information of described driving battery, and the safe condition of described driving battery is assessed in the following way: CV
saf=R[f (I), g (V), h (T)], wherein, CV
safrepresent confidence in security value, I is for driving the current value of battery, V is for driving the magnitude of voltage of battery, T is for driving the temperature of battery, the current characteristic that f (I) calculates through special algorithm for current value, the voltage characteristic that g (V) calculates through special algorithm for magnitude of voltage, the temperature profile that h (T) calculates through special algorithm for battery temperature value, R[f (I), g (V), h (T)] be that current characteristic, voltage characteristic and temperature profile calculate safety assessment confidence value through special algorithm; Wherein, for calculating the special algorithm of described current characteristic, voltage characteristic and temperature profile, be: with Wavelet Packet Algorithm to adopt the time series of current value, magnitude of voltage and temperature value decompose and calculate the energy of wavelet decomposition Shu Shangge branch, local peak-to-peak value, local maximum, local minimum, crest factor, the degree of bias; Algorithm based on described current characteristic, voltage characteristic and temperature profile computationally secure assessment confidence value comprises: Artificial Neural Network, Self-organizing Maps method and regression algorithm, described current characteristic, voltage characteristic and the temperature profile DUAL PROBLEMS OF VECTOR MAPPING of describing battery status are arrived to unified safe probability space, and to user, show 0 to 1 safe probability value, wherein: 0 represents that battery had lost efficacy and extremely danger; 1 represents that battery operation is in good condition and does not have potential safety hazard completely; Value between 0 to 1 represents the cell safety state between two kinds of extremities above;
Drive cell health state evaluation module, it produces the health status information of described driving battery;
The assessment of driving battery dump energy, it produces the dump energy appreciation information of described driving battery;
Drive battery information memory module, it stores battery information, safety state information, health status information and the dump energy appreciation information of described driving battery;
And battery information display module, it shows battery information, safety state information, health status information and the dump energy appreciation information of described driving battery;
Wherein, described charge control module, the harmless quick test module of driving battery, driving cell safety evaluation module, driving cell health state evaluation module, the assessment of driving battery dump energy, driving battery information memory module are connected successively with battery information display module, and described battery information display module is connected with described charge control module.
2. battery of electric vehicle safety and Health evaluating system as claimed in claim 1, is characterized in that, the battery information of described driving battery comprises voltage, electric current, the battery temperature that drives battery.
3. battery of electric vehicle safety and Health evaluating system as claimed in claim 1, is characterized in that, described battery information display module is arranged on smart mobile phone or panel computer.
4. a battery of electric vehicle safety and Health appraisal procedure, is characterized in that, comprises the following steps:
To driving battery to discharge and recharge operation, gather the battery information of described driving battery simultaneously;
Assess the safe condition of described driving battery, obtain the safety state information of described driving battery, the safe condition of described driving battery is assessed in the following way: CV
saf=R[f (I), g (V), h (T)], wherein, CV
safrepresent confidence in security value, I is for driving the current value of battery, V is for driving the magnitude of voltage of battery, T is for driving the temperature of battery, the current characteristic that f (I) calculates through special algorithm for current value, the voltage characteristic that g (V) calculates through special algorithm for magnitude of voltage, the temperature profile that h (T) calculates through special algorithm for battery temperature value, R[f (I), g (V), h (T)] be that current characteristic, voltage characteristic and temperature profile calculate safety assessment confidence value through special algorithm; Wherein, for calculating the special algorithm of described current characteristic, voltage characteristic and temperature profile, be: with Wavelet Packet Algorithm to adopt the time series of current value, magnitude of voltage and temperature value decompose and calculate the energy of wavelet decomposition Shu Shangge branch, local peak-to-peak value, local maximum, local minimum, crest factor, the degree of bias; Algorithm based on described current characteristic, voltage characteristic and temperature profile computationally secure assessment confidence value comprises: Artificial Neural Network, Self-organizing Maps method and regression algorithm, described current characteristic, voltage characteristic and the temperature profile DUAL PROBLEMS OF VECTOR MAPPING of describing battery status are arrived to unified safe probability space, and to user, show 0 to 1 safe probability value, wherein: 0 represents that battery had lost efficacy and extremely danger; 1 represents that battery operation is in good condition and does not have potential safety hazard completely; Value between 0 to 1 represents the cell safety state between two kinds of extremities above;
Assess the health status of described driving battery, obtain the health status information of described driving battery;
Assess the dump energy assessment of described driving battery, obtain the dump energy appreciation information of described driving battery;
Store battery information, safety state information, health status information and the dump energy appreciation information of described driving battery;
The battery information, safety state information, health status information and the dump energy appreciation information that show described driving battery.
5. battery of electric vehicle safety and Health appraisal procedure as claimed in claim 4, is characterized in that, the battery information of described driving battery comprises voltage, electric current, the battery temperature that drives battery.
6. battery of electric vehicle safety and Health appraisal procedure as claimed in claim 4, is characterized in that, according to predefined charge/discharge setting value sequence, described driving battery is discharged and recharged to operation.
7. battery of electric vehicle safety and Health appraisal procedure as claimed in claim 4, is characterized in that, assesses the health status of described driving battery in the following way: CV
health=U[f (I), g (V), h (T)], wherein, CV
healthrepresent healthy confidence value, I is for driving the current value of battery, V is for driving the magnitude of voltage of battery, T is for driving the temperature of battery, the current characteristic that f (I) calculates through special algorithm for current value, the voltage characteristic that g (V) calculates through special algorithm for magnitude of voltage, the temperature profile that h (T) calculates through special algorithm for battery temperature value, U[f (I), g (V), h (T)] be current characteristic, voltage characteristic and temperature profile calculate health status assessment confidence value through special algorithm, wherein, be used for calculating described current characteristic, the special algorithm of voltage characteristic and temperature profile is: with Wavelet Packet Algorithm to adopt current value, the energy of wavelet decomposition Shu Shangge branch is decomposed and calculated to the time series of magnitude of voltage and temperature value, local peak-to-peak value, local maximum, local minimum, crest factor, the degree of bias, the algorithm that calculates health status assessment confidence value based on described current characteristic, voltage characteristic and temperature profile comprises: Artificial Neural Network, Self-organizing Maps method and regression algorithm, described current characteristic, voltage characteristic and the temperature profile DUAL PROBLEMS OF VECTOR MAPPING of describing battery status are arrived to unified safe probability space, and to user, show 0 to 1 safe probability value, wherein: 0 represents that battery had lost efficacy and extremely danger, 1 represents that battery operation is in good condition and does not have potential safety hazard completely, value between 0 to 1 represents the cell safety state between two kinds of extremities above.
8. battery of electric vehicle safety and Health appraisal procedure as claimed in claim 4, it is characterized in that, assess the dump energy assessment of described driving battery in the following way: SOC=C[f (I), g (V), h (T)], wherein, SOC is for driving the residual electric quantity of battery, I is for driving the current value of battery, V is for driving the magnitude of voltage of battery, T is for driving the temperature of battery, the current characteristic that f (I) calculates through special algorithm for current value, the voltage characteristic that g (V) calculates through special algorithm for magnitude of voltage, the temperature profile that h (T) calculates through special algorithm for battery temperature value, C[f (I), g (V), h (T)] be current characteristic, voltage characteristic and temperature profile calculate dump energy assessed value through special algorithm, wherein, be used for calculating described current characteristic, the special algorithm of voltage characteristic and temperature profile is: with Wavelet Packet Algorithm to adopt current value, the energy of wavelet decomposition Shu Shangge branch is decomposed and calculated to the time series of magnitude of voltage and temperature value, local peak-to-peak value, local maximum, local minimum, crest factor, the degree of bias, the algorithm that calculates dump energy assessed value based on described current characteristic, voltage characteristic and temperature profile is: by the current characteristic of described battery, voltage characteristic and temperature profile vector are estimated to dump energy with the model of dump energy, the model of assessment dump energy can be realized by Artificial Neural Network, Self-organizing Maps method or linearity or non-linear interpolation algorithm.
9. battery of electric vehicle safety and Health appraisal procedure as claimed in claim 4, is characterized in that, adopts cloud computing to carry out the assessment of safe condition, health status and the dump energy of described driving battery.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201110441125.4A CN102520366B (en) | 2011-12-23 | 2011-12-23 | Electric car cell safety and health assessment system and method thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201110441125.4A CN102520366B (en) | 2011-12-23 | 2011-12-23 | Electric car cell safety and health assessment system and method thereof |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102520366A CN102520366A (en) | 2012-06-27 |
| CN102520366B true CN102520366B (en) | 2014-11-12 |
Family
ID=46291351
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201110441125.4A Expired - Fee Related CN102520366B (en) | 2011-12-23 | 2011-12-23 | Electric car cell safety and health assessment system and method thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102520366B (en) |
Families Citing this family (31)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103018681B (en) * | 2012-12-19 | 2015-04-15 | 上海交通大学 | Electric vehicle battery life decline and safe state detection technology based on deformation of battery cell in any shape |
| CN103344921B (en) * | 2013-07-08 | 2015-11-11 | 华南师范大学 | Lithium-ion-power cell health state evaluation system and method |
| CN103605078B (en) * | 2013-11-12 | 2016-02-10 | 清华大学 | The performance test methods of hybrid vehicle electrokinetic cell or electric battery |
| CN103605079B (en) * | 2013-11-20 | 2015-10-07 | 浙江工业大学 | Public Electric Vehicles and echelon thereof utilize the V2G active volume appraisal procedure of battery cluster |
| CN103941191B (en) * | 2014-03-26 | 2016-05-04 | 海博瑞恩电子科技无锡有限公司 | A kind of method of energy storage device integrated management and energy storage device |
| US9594121B2 (en) * | 2014-04-04 | 2017-03-14 | GM Global Technology Operations LLC | Systems and methods for estimating battery pack capacity |
| CN104393647B (en) * | 2014-11-28 | 2017-06-13 | 上海交通大学 | A kind of charging pile system for electric automobile |
| CN104459552B (en) * | 2014-11-28 | 2017-10-17 | 上海交通大学 | The method for assessing influence of the charging behavior to batteries of electric automobile health status |
| CN104569840A (en) * | 2014-12-26 | 2015-04-29 | 国家电网公司 | Aging detection method and device for individual battery |
| CN104569841A (en) * | 2014-12-26 | 2015-04-29 | 国家电网公司 | Aging detection method and device for battery pack |
| CN106033113B (en) * | 2015-03-19 | 2019-03-08 | 国家电网公司 | A kind of energy-storage battery group health state evaluation method |
| US9586579B1 (en) * | 2016-02-29 | 2017-03-07 | GM Global Technology Operations LLC | System and method for monitoring battery degradation |
| CN107329088B (en) * | 2016-04-29 | 2021-05-14 | 株式会社日立制作所 | Battery state of health diagnostic device and method |
| CN106154170B (en) * | 2016-05-31 | 2018-12-07 | 陈嘉贤 | The evaluation method and system of battery remaining power |
| CN106199450A (en) * | 2016-08-16 | 2016-12-07 | 成都市和平科技有限责任公司 | A kind of battery health evaluation system and method |
| CN106707176A (en) * | 2016-11-29 | 2017-05-24 | 芜湖市吉安汽车电子销售有限公司 | Real-time charge detection monitoring system for battery pack |
| CN107132489B (en) * | 2017-06-30 | 2021-01-05 | 浙江绿源电动车有限公司 | Battery capacity detection method, vehicle state judgment method, battery pack and electric vehicle |
| CN108226788B (en) * | 2017-11-20 | 2020-09-08 | 蔚来汽车有限公司 | Method, device and system for calculating SOC of battery based on charging state of charging side |
| TWI663413B (en) * | 2018-04-24 | 2019-06-21 | 聯華聚能科技股份有限公司 | Dual self-learning battery estimation system and method |
| EP3591414B1 (en) * | 2018-07-03 | 2022-01-19 | Electricité de France | Method for evaluating an electric battery state of health |
| CN109633450B (en) * | 2018-11-23 | 2021-05-14 | 成都大超科技有限公司 | Lithium battery charging detection system based on neural network |
| CN109738802A (en) * | 2018-12-06 | 2019-05-10 | 中车工业研究院有限公司 | A kind of the joint supervisory systems and method of vehicle-mounted energy-storage system |
| CN111145381B (en) * | 2019-05-17 | 2020-11-10 | 深圳市德塔防爆电动汽车有限公司 | Safety state evaluation method of electric vehicle and electric vehicle |
| CN111983467B (en) * | 2020-08-24 | 2023-02-03 | 哈尔滨理工大学 | Battery safety degree estimation method and estimation device based on second-order RC equivalent circuit model |
| CN111983466A (en) * | 2020-08-24 | 2020-11-24 | 哈尔滨市新量能电气技术有限公司 | Lithium battery safety degree estimation method and device based on voltage and temperature characteristics |
| CN111929588B (en) * | 2020-09-01 | 2021-01-01 | 杭州颉码能源科技有限公司 | Charging safety monitoring method, device and system based on extreme learning machine |
| CN111966111B (en) * | 2020-10-23 | 2021-06-08 | 北京国新智电新能源科技有限责任公司 | Automatic power distribution based mobile charging equipment formation control method, system and device |
| CN113608136B (en) * | 2021-07-27 | 2024-04-26 | 中北大学 | Method for predicting health state of multi-scale lithium ion battery |
| CN113872306B (en) * | 2021-11-08 | 2023-04-18 | 东华理工大学 | Online health condition evaluation method for photovoltaic energy storage battery |
| CN115389958B (en) * | 2022-10-28 | 2023-03-24 | 江苏海铂德能源科技有限公司 | Lithium ion battery operation safety evaluation method and system |
| CN116754976A (en) * | 2023-05-25 | 2023-09-15 | 盐城工学院 | Intelligent battery residual electric quantity estimation system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5672951A (en) * | 1994-11-04 | 1997-09-30 | Mitsubishi Denki Kabushiki Kaisha | Determination and control of battery state |
| CN101312260A (en) * | 2007-05-23 | 2008-11-26 | 佳能株式会社 | Battery pack, charging device, control method thereof, electronic device and control method thereof |
| CN101316048A (en) * | 2007-05-29 | 2008-12-03 | 扬州福德电池有限公司 | Intelligent charge control method for Ni-MH power accumulator set |
| CN101354432A (en) * | 2007-07-23 | 2009-01-28 | 黄永升 | Battery performance monitor |
| CN102024999A (en) * | 2010-11-16 | 2011-04-20 | 上海交通大学 | Electric car running power management system |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101960691B (en) * | 2008-02-29 | 2013-04-24 | 核心技术国际有限公司 | Charging device and quality judging device of pack cell |
-
2011
- 2011-12-23 CN CN201110441125.4A patent/CN102520366B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5672951A (en) * | 1994-11-04 | 1997-09-30 | Mitsubishi Denki Kabushiki Kaisha | Determination and control of battery state |
| CN101312260A (en) * | 2007-05-23 | 2008-11-26 | 佳能株式会社 | Battery pack, charging device, control method thereof, electronic device and control method thereof |
| CN101316048A (en) * | 2007-05-29 | 2008-12-03 | 扬州福德电池有限公司 | Intelligent charge control method for Ni-MH power accumulator set |
| CN101354432A (en) * | 2007-07-23 | 2009-01-28 | 黄永升 | Battery performance monitor |
| CN102024999A (en) * | 2010-11-16 | 2011-04-20 | 上海交通大学 | Electric car running power management system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102520366A (en) | 2012-06-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102520366B (en) | Electric car cell safety and health assessment system and method thereof | |
| Zhang et al. | Comprehensive dynamic battery modeling for PHEV applications | |
| CN102937704B (en) | Method for identifying RC (resistor-capacitor) equivalent model of power battery | |
| CN101133514B (en) | Method of estimating maximum output of battery for hybrid electric vehicle | |
| CN107003357B (en) | Battery management system based on wireless network | |
| CN106329021A (en) | Method and device for estimating remaining available energy of power battery | |
| TW202127052A (en) | Method and system for evaluating soundness of battery | |
| CN104931889A (en) | Systems and methods for determining battery system performance degradation | |
| CN103293485A (en) | Model-based storage battery SOC (state of charge) estimating method | |
| CN106569143A (en) | Method and system for on-line calculation of electrical core capacity and state of health (SOH), and electric vehicle | |
| CN102303538A (en) | Method and device for displaying residual driving range of electromobile | |
| CN104773083A (en) | Hybrid powertrain system and vehicle | |
| CN103267953B (en) | The evaluation method of a kind of lithium iron phosphate dynamic battery SOC | |
| CN203786271U (en) | Device for testing state of charge (SOC) of electric automobile battery pack | |
| CN109941148A (en) | Method, apparatus, the electronic equipment, storage medium of residual power percentage are provided | |
| CN103576026B (en) | Detection device for vehicle-mounted charger | |
| Klass et al. | Evaluating real-life performance of lithium-ion battery packs in electric vehicles | |
| CN105445665A (en) | Method for estimating state of charge of battery through Kalman filtering | |
| CN109143098A (en) | A kind of lithium ion battery life estimation method and device | |
| JP6577990B2 (en) | Internal state estimation device | |
| JP6911747B2 (en) | Battery information processing device, battery manufacturing support device, assembled battery, battery information processing method, and assembled battery manufacturing method | |
| CN115427256A (en) | Method for monitoring battery cell aging | |
| CN104977541A (en) | Systems and methods for estimating battery pack capacity | |
| CN102565718B (en) | Based on the lithium battery SOC determination methods that open-circuit voltage rise declines | |
| CN203798989U (en) | SOC detection device for power battery pack of electromobile |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20141112 Termination date: 20211223 |