CN204030697U - Based on the battery management system of dynamic SOC estimating system - Google Patents
Based on the battery management system of dynamic SOC estimating system Download PDFInfo
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- CN204030697U CN204030697U CN201420524788.1U CN201420524788U CN204030697U CN 204030697 U CN204030697 U CN 204030697U CN 201420524788 U CN201420524788 U CN 201420524788U CN 204030697 U CN204030697 U CN 204030697U
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Abstract
The utility model relates to a kind of battery management system based on dynamic SOC estimating system, this system comprises main control unit, from control unit and host computer, main control unit, between control unit and host computer by CAN bus communication, described main control unit comprises battery testing system and SOC estimating system, battery balanced strategy and control system, the parameter that described SOC estimating system gathers each battery in battery pack by current sensor and voltage sensor is carried out SOC estimation.Realize dynamic SOC evaluation method based on the model dynamic estimation to state-of-charge SOC, its estimation result shows dynamic SOC evaluation method to system model noise and measures noise all have stronger inhibitory action, not only the initial value error of system model is had to stronger correcting action, also the identification result of model parameter is had to certain robustness simultaneously.
Description
Technical field
The utility model relates to power safety technique field, relates in particular to a kind of battery management system of estimating system based on dynamic SOC.
Background technology
Battery management system should have following function: the detection of battery pack external parameter, the estimation of battery condition judgement and dump energy, battery pack discharge and recharge control, battery electric quantity balanced management, battery pack heat management, provides with the function of external device communication etc.Oneself is tending towards ripe the detection technique of current battery external parameter, the emphasis of lithium ion battery management system research is now the balanced management of battery dump energy estimation and battery pack, SOC refers to the ratio of dump energy and battery total capacity, conventionally state of charge battery under uniform temperature being charged to can not absorb energy again time is defined as SOC=100%, and the state of charge that battery can not be emitted electric weight is again defined as to SOC=0%.SOC evaluation method mainly contains the method for ampere-hour method, open circuit voltage method, internal resistance method, Kalman filtering method, neural net and fuzzy reasoning.The ampere-hour method adopting is at present that the electric weight when the charging and discharging carrys out the SOC of estimating battery by battery, and according to the temperature of battery and discharge rate, SOC is compensated.This method is simple and easy to, algorithm stable, but along with the accumulation of time, error can be increasing.Open circuit voltage method is according to the corresponding relation between the open circuit voltage of battery and the depth of discharge of battery, estimates SOC by the open circuit voltage of measuring battery.The advantage of the method: the SOC that load method can real-time estimation battery pack in the time of constant-current discharge, and electric current is big ups and downs in practice, so adopt separately load method effect unsatisfactory.When practical application, open circuit voltage method is often combined with ampere-hour method, for the SOC estimation in charging initial stage and latter stage.Load method is rarely used in reality, but is commonly used to the criterion as battery charging and discharging cut-off.Internal resistance measurement method is the relation of utilizing between internal resistance and SOC, estimates SOC by measuring internal resistance.Under actual condition, the variation of electric current is very fast, and therefore the calculating of internal resistance is very complicated.Be applicable to the to discharge SOC estimation in later stage of internal resistance method, can be used in combination with ampere-hour method.Due to method complexity, the calculating of internal resistance is off-line case substantially, and amount of calculation is large, is therefore rarely used in reality.
Summary of the invention
For correlative technology field document and above the deficiencies in the prior art, in a large amount of existing literature research and long-term on the basis of association area Development Practice, the utility model proposes " based on the battery management system of dynamic SOC estimating system ", overcome in prior art technical barriers such as " ampere-hour method are along with the accumulation of time; error can be increasing ", realized the beneficial effect of " improving SOC estimation precision ".
For achieving the above object, the utility model is achieved through the following technical solutions: a kind of battery management system based on dynamic SOC estimating system, this system comprises main control unit, from control unit and host computer, main control unit, between control unit and host computer by CAN bus communication, described main control unit comprises battery testing system and SOC estimating system, battery balanced strategy and control system, described SOC estimating system gathers the parameter of each battery in battery pack by current sensor and voltage sensor.Described from control unit comprise cell detection system, described cell detection system comprises for gathering monomer battery voltage data acquisition unit, temperature data samwpling unit.Described host computer comprises, data presentation system, car load CAN network, PC connection data display system, and data presentation system connects LCD screen, and car load CAN network is made an excuse and is connected to data presentation system by CAN.Described battery testing system comprises voltage data collecting unit, temperature data samwpling unit, thermal management unit, the power brick current data collecting unit for gathering total battery pack data, high-tension electricity parameter online acquisition unit.Described thermal management unit comprises battery case cooling system, and thermal management unit is according to the temperature data management battery case cooling system work gathering.Described dynamic SOC estimating system is estimated by following steps: step 1, system is carried out to initialization, battery management system is to battery parameter identification; Step 2, discharge and recharge the starting stage, selecting open circuit voltage method, determining the value of state SOC0; In the inviolent stage of inside battery reaction, calculate the value of SOC by ampere-hour method; React the violent stage at inside battery, calculate the value of SOC1 by Kalman filtering method, and value is fed back to battery management system, and show on PC computer; Step 3, battery management system are received value of feedback and are deposited into two-dimensional data table, and after one-period T, battery management system judges next round SOC evaluation method according to the data of two-dimensional data table, carry out next round to battery parameter identification, execution step two.Step 4, battery management system system are sent halt instruction, and whole process finishes.Described step 1 initialization procedure comprises sets battery capacity, open circuit voltage, and conversion coulomb efficiency, BMS sampling time, built-up pattern parameter, setting Kalman filtering are calculated initial value.Described two-dimensional data table comprises battery parameter Identification Data and SOC Value Data.
The beneficial effects of the utility model are: realized dynamic SOC evaluation method based on the model dynamic estimation to state-of-charge SOC, its estimation result shows dynamic SOC evaluation method to system model noise and measures noise all have stronger inhibitory action, not only the initial value error of system model is had to stronger correcting action, also the identification result of model parameter is had to certain robustness simultaneously.
Brief description of the drawings
Fig. 1 is the battery management system structured flowchart of the utility model specific embodiment;
Fig. 2 is the dynamic SOC estimating system structure chart of the utility model specific embodiment;
Embodiment
Contrast accompanying drawing below, by the description to embodiment, to embodiment of the present utility model as related control system, mutual annexation, and implementation method, be described in further detail, to help those skilled in the art to have more complete, accurate and deep understanding to inventive concept of the present utility model, technical scheme.
Battery management system refers to parameter information that can Real-Time Monitoring electrokinetic cell, state-of-charge (the State of Charge of estimating battery, SOC), effectively battery capacity managed and distribute, possessing a set of complete system of the functions such as perfect fault detect, warning, data processing and transmission.Battery management system should have following function: the detection of battery pack external parameter, the estimation of battery condition judgement and dump energy, battery pack discharge and recharge control, battery electric quantity balanced management, battery pack heat management, provides with the function of external device communication etc.Oneself is tending towards ripe the detection technique of current battery external parameter, and the emphasis of lithium ion battery management system research is now the balanced management of battery dump energy estimation and battery pack.
As shown in Figure 1, a kind of battery management system based on dynamic SOC estimating system, this system comprises main control unit, from control unit and host computer, main control unit, between control unit and host computer by CAN bus communication, described main control unit comprises battery testing system and SOC estimating system, battery balanced strategy and control system, described SOC estimating system gathers the parameter of each battery in battery pack by current sensor and voltage sensor.Described from control unit comprise cell detection system, described cell detection system comprises for gathering monomer battery voltage data acquisition unit, temperature data samwpling unit.Described host computer comprises, data presentation system, car load CAN network, PC connection data display system, and data presentation system connects LCD screen, and car load CAN network is made an excuse and is connected to data presentation system by CAN.Described battery testing system comprises voltage data collecting unit, temperature data samwpling unit, thermal management unit, the power brick current data collecting unit for gathering total battery pack data, high-tension electricity parameter online acquisition unit.Described thermal management unit comprises battery case cooling system, and thermal management unit is according to the temperature data management battery case cooling system work gathering.
BMS generally forms topological structure by main control unit with from control unit, is responsible for communication by CAN bus.Main control unit function major function comprises total voltage sampling and power brick current sample, monitoring temperature and heat management, the contour piezoelectric parameter on-line measurement of insulation resistance, realize high-voltage safety control, battery pack and the diagnosis of high-tension system failure predication, the estimation of the state parameters such as SOC and active volume and available horsepower etc., total internal resistance measurement and calculating, the balance policy of integral battery door system and control, with the CAN communication of the each sub-control of bottom unit, with extraneous high-speed CAN communication etc.Mainly comprise voltage, electric current and the temperature sampling of each cell from control Elementary Function, support levels join supervision and the not communication altogether of high pressure (BMS internal communication) of more piece battery core, based on balanced decision-making and the control of cell, calculate the state parameter of each monomer, with communication of main control unit etc.
Main control unit comprises battery testing system, and battery testing system comprises voltage data collecting unit, temperature data samwpling unit, thermal management unit.
Voltage data gathers voltage collection circuit and selects successively tested battery by linear optical coupling switch, after sampling hold circuit, gathers voltage data through A/D.Through experimental test, the module voltage Acquisition Error of battery monitoring system is ± 0.05V.
Temperature data acquisition battery monitoring system uses digital temperature sensor collecting temperature data, and data transmission interface is 1-wire bus.Consider thermometric Stability and veracity, in each battery case, respectively have 4 points for measuring temperature, be evenly distributed on battery cell as in the reserved pit of temperature sensor.The polling period of temperature data is 500ms, and acquisition precision is 0.5 DEG C.
According to the battery temperature of temperature sensor measurement, comprise battery case temperature and battery module temperature, battery management system is by the work of Control battery case air cooling system.Air cooling system adopts cooling uniformity parallel draft type preferably.
The accurate estimation of battery charge state (State of Charge, SOC) is the important evidence that electrokinetic cell discharges and recharges control and energy source optimization management, directly affects the useful life of battery.Visible, the Measurement accuracy of battery dump energy is very crucial problem.But battery SOC can not directly be measured, can only estimate its size by parameters such as battery terminal voltage, charging and discharging currents and internal resistances.And these parameters also can be subject to the impact of the multiple uncertain factors such as cell degradation, variation of ambient temperature and motoring condition, therefore SOC estimation has accurately become problem demanding prompt solution in electric battery management system.Kalman filtering method is an optimization autoregression data processing algorithm, and its core concept is that the state of dynamical system is made to the maximum likelihood estimation in minimum variance meaning.During for initial SOC estimation, Kalman filtering method is described as battery by state equation and measures the system that equation forms, and SOC is an internal state of system.The object of Kalman filtering is the information of utilizing observation data to provide in carrying out Recursive Filtering, constantly revises state estimation, reduces estimation error, is applicable to steadily and non-stationary process, and has recursion.It only need remember the estimation result of back, has greatly reduced thus the use amount of memory, is easy to realize on algorithm, only need in storage battery uses first, demarcate SOC, and according to open circuit voltage prediction storage battery initial capacity, complete initial work.The precision of the method depends on the accuracy of battery model, and setting up model is accurately the key of algorithm, however battery in use each parameter also can be subject to the impact of life-span and variations in temperature, so the on-line identification of parameter is necessary.Kalman filtering method can not only provide SOC estimated value, and estimation error value can be provided; So there is quite high precision.But, the modeling of this method and all more complicated of the algorithm of implementation model, Capability Requirement is high.This method, applicable to the battery of any type, is especially applicable to the estimation of the more violent hybrid-power battery SOC of current fluctuation; There are very strong operability and practicality.The utility model in conjunction with proposing a kind of composite S OC estimation, for the advantage of three kinds of methods, under different conditions, adopts different evaluation methods to estimate at battery Kalman filtering, open circuit voltage method and ampere-hour method, thereby improves estimation precision.
Dynamically SOC estimating system is estimated by following steps as shown in Figure 2: step 1, system is carried out to initialization, battery management system is to battery parameter identification; Step 2, discharge and recharge the starting stage, selecting open circuit voltage method, determining the value of state SOC0; In the inviolent stage of inside battery reaction, calculate the value of SOC by ampere-hour method; React the violent stage at inside battery, calculate the value of SOC1 by Kalman filtering method, and value is fed back to battery management system, and show on PC computer; Step 3, battery management system are received value of feedback and are deposited into two-dimensional data table, and after one-period T, battery management system judges next round SOC evaluation method according to the data of two-dimensional data table, carry out next round to battery parameter identification, execution step two.Step 4, battery management system system are sent halt instruction, and whole process finishes.Described step 1 initialization procedure comprises sets battery capacity, open circuit voltage, and conversion coulomb efficiency, BMS sampling time, built-up pattern parameter, setting Kalman filtering are calculated initial value.Described two-dimensional data table comprises battery parameter Identification Data and SOC Value Data, finally output is two kinds of results that method weighting obtains, and w is the weighted factor of Kalman filtering method SOC, and 1-w is the weighted factor of ampere-hour method SOC, w meets SOC (k), 0≤w≤1.
Professional can also further recognize, the execution step of describing in conjunction with embodiment disclosed herein, can realize with electronic hardware, computer software or the combination of the two, these functions are carried out with hardware or software mode actually, depend on application-specific and the design constraint of technical scheme.Professional and technical personnel can realize described function with distinct methods to each specifically should being used for, but this realization should not thought and exceeds scope of the present utility model.The utility model is not limited to above-mentioned specific embodiment; do not departing under the utility model spirit and real situation thereof; those of ordinary skill in the art can make various corresponding changes and distortion according to the utility model; these are tackled mutually the amendment that the utility model carries out or are equal to replacement, and it all should be encompassed in the middle of the scope of claim protection of the present utility model.
Claims (5)
1. the battery management system based on dynamic SOC estimating system, it is characterized in that: this system comprises main control unit, from control unit and host computer, main control unit, between control unit and host computer by CAN bus communication, described main control unit comprises battery testing system and SOC estimating system, battery balanced strategy and control system, the parameter that described SOC estimating system gathers each battery in battery pack by current sensor and voltage sensor is carried out SOC estimation.
2. battery management system according to claim 1, it is characterized in that: described from control unit comprise cell detection system and SOC estimating system, described cell detection system comprises for gathering monomer battery voltage data acquisition, temperature data acquisition.
3. battery management system according to claim 1, it is characterized in that: described host computer comprises data presentation system, car load CAN network, PC connection data display system, data presentation system connects LCD screen, and car load CAN network is made an excuse and is connected to data presentation system by CAN.
4. battery management system according to claim 1, it is characterized in that: described battery testing system comprises voltage data collecting unit, temperature data samwpling unit, thermal management unit, the power brick current data collecting unit for gathering total battery pack data, high-tension electricity parameter online acquisition unit.
5. battery management system according to claim 4, is characterized in that: described thermal management unit comprises battery case cooling system, and thermal management unit is according to the temperature data management battery case cooling system work gathering.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104242393A (en) * | 2014-09-12 | 2014-12-24 | 安徽启光能源科技研究院有限公司 | Battery management system based on dynamic SOC estimation system |
| CN107590617A (en) * | 2017-09-27 | 2018-01-16 | 合肥工业大学 | A battery pack equalization method based on credibility reasoning model |
| EP3579006A1 (en) * | 2018-06-07 | 2019-12-11 | Samsung SDI Co., Ltd. | Validation of a temperature sensor of a battery cell |
| US11073884B2 (en) | 2017-11-15 | 2021-07-27 | International Business Machines Corporation | On-chip supply noise voltage reduction or mitigation using local detection loops |
| US11846678B2 (en) | 2018-06-07 | 2023-12-19 | Samsung Sdi Co., Ltd. | Method and system for validating a temperature sensor in a battery cell |
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2014
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104242393A (en) * | 2014-09-12 | 2014-12-24 | 安徽启光能源科技研究院有限公司 | Battery management system based on dynamic SOC estimation system |
| CN107590617A (en) * | 2017-09-27 | 2018-01-16 | 合肥工业大学 | A battery pack equalization method based on credibility reasoning model |
| US11073884B2 (en) | 2017-11-15 | 2021-07-27 | International Business Machines Corporation | On-chip supply noise voltage reduction or mitigation using local detection loops |
| US11561595B2 (en) | 2017-11-15 | 2023-01-24 | International Business Machines Corporation | On-chip supply noise voltage reduction or mitigation using local detection loops |
| EP3579006A1 (en) * | 2018-06-07 | 2019-12-11 | Samsung SDI Co., Ltd. | Validation of a temperature sensor of a battery cell |
| US11846678B2 (en) | 2018-06-07 | 2023-12-19 | Samsung Sdi Co., Ltd. | Method and system for validating a temperature sensor in a battery cell |
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Effective date of registration: 20190912 Address after: Room A-1288, Building 188 Changyi Road, Baoshan District, Shanghai, 2004 Patentee after: Shanghai Titanium Cheng Technology Co.,Ltd. Address before: 241200, No. 17, Zhanghe Road, national hi tech Industrial Development Zone, Yijiang District, Anhui, Wuhu Patentee before: ANHUI LIGHT ENERGY TECHNOLOGY RESEARCH INSTITUTE Co.,Ltd. |
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