CN102195101A - Power battery management system and method thereof - Google Patents
Power battery management system and method thereof Download PDFInfo
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- CN102195101A CN102195101A CN2010102195716A CN201010219571A CN102195101A CN 102195101 A CN102195101 A CN 102195101A CN 2010102195716 A CN2010102195716 A CN 2010102195716A CN 201010219571 A CN201010219571 A CN 201010219571A CN 102195101 A CN102195101 A CN 102195101A
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Abstract
The invention relates to an electrical design field and discloses a power battery management system and a method thereof. Estimation algorithm of cell state of charge (SOC), a heat management technology, a safety management and other new technologies are researched and implemented. The system in the invention comprises a safety management subsystem, a heat management subsystem, an optimization subsystem and the like. The safety management subsystem is used for monitoring charged states of cell monomers; determining whether the cell monomers are in discharge end states according to charged states of cell monomers and terminating cell discharges if the cell monomers are in discharge end states. The heat management subsystem is used for detecting temperatures of cell monomer surfaces; determining upper limits of temperature ranges in cell monomers according to temperature history information of cell monomer surfaces; determining temperature distribution information of a cell box consisting of all cell monomers; controlling an operating temperature of the battery according to temperature distribution information so that the operating temperature is in a range of preset temperatures. The optimization subsystem is respectively connected with the safety management subsystem and the heat management subsystem, and is used for controlling working states of the safety management subsystem and the heat management subsystem. In the invention, the safety management, the heat management and the like are applied in a management field of a power battery, which can improve safety performance, prolong service life, raise usage efficiency, give fully play to cell potential and guarantee the safety of using.
Description
Technical field
The present invention relates to electrical design field, relate in particular to a kind of power battery group management system and method.
Background technology
Along with highlighting of energy problem, electric automobile becomes a kind of new environment-friendly type power tool.And power battery pack is a key components and parts of electric automobile, and the quality of its performance directly affects the dynamic property and the economy of car load.Battery management system is the contact bridge between electrokinetic cell and the car load, and the setting battery management system can improve the Performance And Reliability of electrokinetic cell.
The battery management technology is the requisite technical guarantee of electric automobile power battery use, to guaranteeing that battery is safe in utilization, give full play to performance, life-saving, the raising service efficiency of existing battery, thereby satisfy electric automobile safe and efficient work and significant to promoting the electric vehicle industrialization process.Battery management system is handled the problems such as measurement, prediction, state demonstration and comprehensive management of accumulator of electric car.
Battery management system is an important subsystem of EMS, and it handles the problems such as measurement, prediction, state demonstration and comprehensive management of accumulator of electric car.The battery management technology is the requisite technical guarantee of electric automobile power battery use, to guaranteeing that battery is safe in utilization, give full play to performance, life-saving, the raising service efficiency of existing battery, thereby satisfy electric automobile safe and efficient work and significant to promoting the electric vehicle industrialization process.The battery management technology is a platform technology, and as military field, aviation field etc., all there is battery set management The Application of Technology space in the field of every working power battery pack.So battery set management The Application of Technology space is boundless, economic benefit and social agency's highly significant.
In battery management system, the dump energy of battery (characterizing SOC:Stateof Charge with state-of-charge SOC) estimates it is one of key technology.Because battery SOC is subjected to the influence of factors such as ambient temperature, self discharge, periodic duty number of times, battery pack inconsistency, accurately the difficulty of estimating is very big, and to carry out the accuracy of SOC estimation not high so use prior art, can not effectively manage system.
Summary of the invention
The present invention's first purpose is to provide a kind of power battery group management system, its to management of automobile batteries group more effectively, reliable.
The present invention's second purpose is to provide a kind of power battery group management method, and its management to the automobile batteries group is effective more, reliable.
A kind of power battery group management system that the embodiment of the invention provides, comprise: security management subsystem, be used to monitor the state-of-charge of each battery cell, determine according to the state-of-charge of described each battery cell whether described each battery cell is in the discharge off state, if then stop described battery discharge;
Thermal management subsystem, be used to survey the temperature on described each battery cell surface, temperature history information according to described each battery cell surface, determine described each battery cell temperature inside upper limit, determine the temperature distribution information of the battery case that constitutes by all described battery cells, control the working temperature of described battery pack according to described temperature distribution information, make described working temperature be in the range of set temperature;
Optimize the subsystem subsystem, be electrically connected with described security management subsystem, thermal management subsystem respectively, be used to control the work of described thermal management subsystem, security management subsystem.
Alternatively, described security management subsystem comprises:
Initialization module is used for initialization and determines the state-of-charge initial value SOC0 of described each battery cell, predicated error covariance matrix initial value P
0, measuring noise square difference Q, filtering multiplication factor α;
Sampling module is used for for k=1, and Nietzsche's sample load voltage signal v of each battery cell is constantly obtained in each sampling instant of 2...
k, current signal I
k
The state-of-charge estimation block of battery is electrically connected with described initialization module, sampling module respectively, is used for determining the state-of-charge of described each battery cell:
The state-of-charge equation of battery: make x
k=SOC
k, wherein said k is a natural number,
Determine the load voltage amount y (k) of described each battery cell according to following formula:
Y (k)=f (I
k, x
k)+v
k=K
0-RI
k-k
1/ x
k-K
2x
k+ K
3Ln (x
k)+K
4Ln (1-x
k)+v
k, wherein, v
kBe measurement noise, described v
kVariance be Q,
Order measures battle array
Then the Kalman filter equation of the state-of-charge of described each battery cell prediction is:
The state-of-charge prediction of described each battery cell:
Calculate described measurement battle array: C
k=K
1/ (x
k)
2-K
2+ K
3/ x
3-K
4/ (1-x
k),
Determine filter gain:
Determine prediction mean square deviation: P
K/k-1=P
K-1/k-1,
Determine to estimate mean square deviation: P
K/k=(I-K
KC
K) P
K/k-1,
Obtain the estimated value of the state-of-charge of described each battery cell: x
K/k=x
K/k-1+ aK
k[y
k-f (I
k, x
K/k-1)];
Discharge is electrically connected with the state-of-charge estimation block of described each battery cell by module, is used for making described battery by discharge according to the estimated value of the state-of-charge of described each battery cell.
Alternatively, described thermal management subsystem comprises: temperature sensor, be arranged in the battery case that is used for ccontaining described each battery cell, and be used to survey the temperature on described each battery cell surface;
Memory module is electrically connected with described temperature sensor, is used to store the temperature history information on described each battery cell surface;
Monomer internal temperature upper limit determination module is electrically connected respectively with described temperature sensor and memory module, is used for current temperature and temperature history information according to described each battery cell, determines described each battery cell temperature inside upper limit;
The Temperature Distribution analysis module is electrically connected with described monomer internal temperature upper limit determination module, is used for according to described each battery cell temperature inside upper limit, determines the temperature distribution information of the battery case that is made of all described battery cells;
Temperature control modules is electrically connected with described Temperature Distribution analysis module, is used for the work according to the heat dissipation equipment of described each battery case of described temperature distribution information control, make described each battery cell respectively working temperature be in the range of set temperature;
Heat dissipation equipment is arranged in described each battery case.
Alternatively, described heat dissipation equipment is a blower fan.
Alternatively, described temperature control modules also is electrically connected with a display unit,
Described display unit is used to show control information and the interior warm distributed intelligence of each battery case on the described temperature control modules.
Alternatively, described optimization subsystem adopts embedded system development to form.
A kind of power battery group management method that the embodiment of the invention provides comprises:
Initial value SOC0, the predicated error covariance matrix initial value P of the state-of-charge of each battery cell determined in initialization
0, measuring noise square difference Q, filtering multiplication factor α;
For k=1, Nietzsche's sample load voltage signal v of each battery cell is constantly obtained in each sampling instant such as 2...
k, current signal I
k
Make x
k=SOC
k, according to the state-of-charge equation of each battery cell:
Determine the state-of-charge of described each battery cell, wherein said k is a natural number,
According to formula:
Y (k)=f (I
k, x
k)+v
k=K
0-RI
k-k
1/ x
k-K
2x
k+ K
3Ln (x
k)+K
4Ln (1-x
k)+v
k, determine the load voltage amount y (k) of described each battery cell, wherein, v
kBe measurement noise, described v
kVariance be Q,
Order measures battle array C
k:
According to Kalman filter equation:
Calculate described measurement battle array: C
k=K
1/ (x
k)
2-K
2+ K
3/ x
3-K
4/ (1-x
k);
Determine filter gain:
Determine prediction mean square deviation: P
K/k-1=P
K-1/k-1
Determine to estimate mean square deviation: P
K/k=(I-K
KC
K) P
K/k-1
Determine the estimated value of the state-of-charge of described each battery cell: x
K/k=x
K/k-1+ aK
k[y
k-f (I
k, x
K/k-1)];
According to the estimated value of the state-of-charge of described each battery cell, make described each battery cell by discharge.
Alternatively,, make described each battery cell, may further comprise the steps by discharge according to the estimated value of the state-of-charge of described each battery cell:
1) initialization: the fixedly final voltage threshold value V of given each battery cell
0
The threshold value WT of given load voltage signal extreme point after the clivia conversion
Valve
2), obtain the load voltage signal V (t) of each battery cell according to the estimated value of the state-of-charge of described each battery cell;
3) judge to exhale V (t) whether to be lower than threshold value V
0, as V (t)＜V
0The time execution in step 4 then), otherwise return step 2);
4) V (t) is carried out wavelet transformation by following formula:
Wherein R is a limit of integration, for beginning to carry out the initial moment of wavelet analysis to the zone between the current sampling instant;
Following formula is abbreviated as: WT
aX (t)=x (t) * Ψ
a(t), wherein x (t)=V (t) a is a scale factor, a=2
j, j is a natural number, its scope is 2～5,
θ (t) is Gauss's lowpass function,
5) obtain the extreme point of figure signal: WT
Max
6) judge WT
MaxWhether surpass threshold value WT
Valve, WT
ValveSpan be outer 2～0 arbitrarily, work as WT
Max＞WT
ValveThe time, then described battery cell stops discharge, otherwise returns step 2).Therefore, the technical program is by the battery SOC algorithm for estimating, state-of-charge according to each battery cell is controlled the discharge of each battery cell, prevent that discharge excessively, pass through battery cell surface temperature and historical information simultaneously and the inner maximum temperature of estimating battery, analyze the characteristic distributions in temperature field in the battery case, help optimizing the quantity and the position of battery case inner sensor, and the work of heat dissipation equipment of control electrokinetic cell so that each battery cell respectively working temperature be in the preference temperature scope of setting.Pass through optimal module, thermal management technology and safety management technology optimisation technique are combined, help solving better power battery pack security performance, life-saving, raising service efficiency, reach the target of giving full play to battery potential and ensuring safety and use.
Description of drawings
Accompanying drawing described herein is used to provide further understanding of the present invention, constitutes the application's a part, does not constitute to improper qualification of the present invention, in the accompanying drawings:
A kind of power battery group management system configuration schematic diagram that Fig. 1 provides for the embodiment of the invention 1;
The structural representation of the security management subsystem 0 that Fig. 2 provides for the embodiment of the invention 1;
The structural representation of a kind of power battery pack thermal management subsystem 1 in the power battery group management system that Fig. 3 provides for the embodiment of the invention 1;
The enforcement structural representation of a kind of power battery group management system in power vehicle that Fig. 4 provides for the embodiment of the invention 1;
The structural representation that the air-cooled serial heat radiation of battery pack in a kind of power battery pack thermal management subsystem 1 in the power battery group management system that Fig. 5 provides for inventive embodiments 1 is provided with;
The structural representation that the air-cooled parallel heat radiation of battery pack in a kind of power battery pack thermal management subsystem 1 in the power battery group management system that Fig. 6 provides for inventive embodiments 1 is provided with;
The method of estimation schematic flow sheet of a kind of electric power storage electrical automobile battery SOC based on improved EKF that Fig. 7 provides for inventive embodiments 1;
Current signal I (t) the waveform schematic diagram of gained in the method for estimation implementation process of a kind of electric power storage electrical automobile battery SOC based on improved EKF that Fig. 8 provides for inventive embodiments 1;
Voltage signal V (t) the waveform schematic diagram of gained in the method for estimation implementation process of a kind of electric power storage electrical automobile battery SOC based on improved EKF that Fig. 9 provides for inventive embodiments 1;
Gained SOC estimated result waveform schematic diagram in when there is initial error in SOC in the method for estimation implementation process of a kind of electric power storage electrical automobile battery SOC based on improved EKF that Figure 10 provides for inventive embodiments 1;
The SOC estimated result waveform schematic diagram that discharges naturally that the implementation process hypothesis exists in the method for estimation of a kind of electric power storage electrical automobile battery SOC based on improved EKF that Figure 11 provides for inventive embodiments 1;
The decision method schematic flow sheet of a kind of battery of electric vehicle discharge off state based on wavelet transformation that Figure 12 provides for inventive embodiments 1;
In the decision method implementation process of a kind of battery of electric vehicle discharge off state based on wavelet transformation that Figure 13 provides for inventive embodiments 1 when discharging current is 80A discharge voltage signal V (t) waveform schematic diagram;
Wavelet transformation result (yardstick a=8) the waveform schematic diagram of discharge voltage signal V (t) when discharging current is 80A in the decision method implementation process of a kind of battery of electric vehicle discharge off state based on wavelet transformation that Figure 14 provides for inventive embodiments 1;
Figure 15 is the battery management system frame diagram of method shown in Figure 13 in implementation process;
A kind of thermal management technology design cycle schematic diagram that Figure 16 provides for inventive embodiments 1.
Embodiment
Describe the present invention in detail below in conjunction with accompanying drawing and specific embodiment, be used for explaining the present invention in this illustrative examples of the present invention and explanation, but not as a limitation of the invention.
Embodiment 1:
The structural representation of a kind of power battery group management system that Fig. 1 provides for present embodiment, referring to diagram, this system comprises: security management subsystem 0, thermal management subsystem 1, optimize subsystem 2.Its operation principle is as follows:
Thereby whether the electric current and voltage that is used to monitor battery if then stop described battery discharge, prevents battery over-discharge above restriction.Prevent arbitrary battery over-discharge in the battery pack again in order to make full use of the energy content of battery, must be in good time and accurately to the judgement of discharging ending status of battery.Therefore prevent that battery over-discharge from being core technology, the decision method of discharge off state then is the key of this research.
Therefore, native system is in conjunction with security management subsystem 0 and thermal management subsystem 1, technology such as safety management and heat management are applied to the management domain of electrokinetic cell, help solving better power battery pack security performance, life-saving, raising service efficiency, reach the target of giving full play to battery potential and ensuring safety and use.
The structural representation of the security management subsystem 0 in a kind of power battery group management system that Fig. 2 provides for present embodiment, referring to diagram, this system comprises: the state-of-charge estimation block 003 of initialization module 000, sampling module 001, battery, discharge are by module 004.Wherein,
Initialization module 000, sampling module 001 are electrically connected with the state-of-charge estimation block 003 of battery respectively, as the parameter input that the state-of-charge estimation block 003 of each battery cell is estimated, discharge is connected with the state-of-charge estimation block 003 of battery by module 004.Its operation principle is as follows:
Initial value SOC0, the predicated error covariance matrix initial value P of the state-of-charge (SOC) of each battery cell determined in initialization module 000 initialization
0, measuring noise square difference Q, filtering multiplication factor α.Sampling module 001 is for k=1, and Nietzsche's sample load voltage signal v of battery is constantly obtained in each sampling instant of 2...
k, current signal I
kThe state-of-charge estimation block 003 of battery is used for the estimated value of the state-of-charge of definite each battery cell.Discharge is used for making each battery cell by discharge according to the estimated value of the state-of-charge of each battery cell by module 004.
The state-of-charge estimation block 003 of battery is determined to adopt following method to estimate the state-of-charge value of each battery cell:
The state-of-charge equation of battery: make x
k=SOC
k, wherein said k is a natural number,
Determine the load voltage amount y (k) of each battery cell according to following formula:
Y (k)=f (I
k, x
k)+v
k=K
0-RI
k-k
1/ x
k-K
2x
k+ K
3Ln (x
k)+K
4Ln (1-x
k)+v
k, wherein, v
kBe measurement noise, described v
kVariance be Q,
Order measures battle array
Then the Kalman filter equation of the state-of-charge of each battery list prediction is:
The state-of-charge prediction of each battery cell:
Calculate described measurement battle array: C
k=K
1/ (x
k)
2-K
2+ K
3/ x
3-K
4/ (1-x
k),
Determine filter gain:
Determine prediction mean square deviation: P
K/k-1=P
K-1/k-1,
Determine to estimate mean square deviation: P
K/k=(I-K
KC
K) P
K/k-1,
Obtain the estimated value of the state-of-charge of each battery cell: x
K/k=x
K/k-1+ aK
k[y
k-f (I
k, x
K/k-1)].
Fig. 3 has implemented the structural representation of a kind of thermal management subsystem 1 of providing for this, as seen, this thermal management subsystem 1 mainly comprises with lower member: temperature sensor 301, memory module 302, monomer internal temperature upper limit determination module 303, Temperature Distribution analysis module 304, temperature control modules 305, heat dissipation equipment 306.Annexation is as follows:
Temperature sensor 301 is arranged in the battery case that is used for ccontaining each battery cell, memory module 302 is electrically connected with temperature sensor 301, monomer internal temperature upper limit determination module 303 is electrically connected respectively with temperature sensor 301 and memory module 302, Temperature Distribution analysis module 304 is electrically connected with monomer internal temperature upper limit determination module 303, and temperature control modules 305 is electrically connected with Temperature Distribution analysis module 304.Its operation principle is as follows:
Be arranged on the temperature on temperature sensor 301 each the battery cell surface of detection in the battery case, and temperature is stored in the memory module 302, so in memory module 302, store the temperature history information on each battery cell surface, the current temperature of monomer internal temperature upper limit determination module 303 bases, and the temperature history information on each battery cell surface of storage is determined each battery cell temperature inside upper limit (being maximum temperature value) in the memory module 302, Temperature Distribution analysis module 304 is according to described each battery cell temperature inside upper limit, determine the temperature distribution information of the battery case that constitutes by all battery cells, temperature control modules 305 is according to the work of the heat dissipation equipment 306 of described each battery case of temperature distribution information control, make each battery cell respectively working temperature be in the range of set temperature.Wherein this heat dissipation equipment 306 can but be not limited to blower fan.
Temperature control modules 305 according to the work of the heat dissipation equipment 306 of described each battery case of temperature distribution information control mainly is:
A: under the battery low-temperature condition, the accurate measurement and the monitoring of battery temperature;
B: effectively loose wind and ventilation when battery pack temperature is too high;
C: the Fast Heating under the cryogenic conditions, battery pack can operate as normal;
D: the available ventilation when pernicious gas produces;
E: guarantee the even distribution of battery pack temperature field.
In the present embodiment, consider that temperature sensor might lose efficacy, the quantity of the corresponding temperature sensor of each battery cell can not be at least two again very little.
Monitoring for the ease of the user, can also on temperature control modules 305, connect a display unit 307, control information and the temperature in each battery case that display unit 307 can be used on the displays temperature control module 305 distribute, so that user monitoring improves user's use experience.
In addition, people optimize the quantity and the position of battery case inner sensor in the temperature distribution information of carrying out the battery case that power battery pack when design can also constitute according to all battery cells, thereby the heat management function and the management system optimisation technique of battery management system are combined, make when design, to make that the Temperature Distribution of electrokinetic cell is more even, further help guaranteeing the work and the safe handling of power battery pack.
The enforcement structural representation of a kind of power battery group management system in power vehicle that Fig. 4 provides for present embodiment.
Referring to shown in Figure 4, the whole power battery group management system is three layers of pyramid structure, be data acquisition daughter board, data acquisition motherboard and CPU CPU by separate CPU layering, piecemeal control, adopt secondary CAN field bus technique realize mutual information communication and with the information communication of car load turn-key system.System is by making up distributed frame, and bottom adopts the low side microprocessor and host computer selects for use the high-end microprocessor of 16 bit or DSP to solve, thereby guarantees the system-computed ability, to evade the potential problem of the system of exempting from.
The exploitation of this power battery group management system is preferably based on the submersible system, and submersible systematically analyzes the strategy of SOC value estimation, has provided voltage acquisition and and data such as temperature control.
Therefore, in power vehicle, this power battery group management system is installed in the power vehicle according to mode shown in Figure 4, when realizing, whole system is three layers of pyramid structure, the bottom is a detecting element, the intermediate layer is each bottom CPU 102 and battery pack bottom monitoring unit 105, and the intermediate layer is connected with the upper data processing equipment 106 of top layer by CAN-Bus109.In the thermal control of battery pack, realize the mode of layering, piecemeal control, realize modularization, blocking control, make that the heat management of battery pack is not random in order, guarantee the validity of heat management and the convenience of safeguarding.
In addition, in the present embodiment, adopt secondary CAN field bus technique realize each bottom CPU 102 in intermediate layer and battery pack bottom monitoring unit 105 and upper data processing equipment 106 mutual information communication and with the information communication of car load turn-key system, guarantee its high speed information transmission, and made message transmission have high noise immunity.
In addition, monitoring for the ease of the user, can also connect a display unit 111 on upper data processing equipment 106, display unit 111 can be used to show the temperature conditions and the voltage output situation of control information on the upper data processing equipment 106 and each battery pack.Be convenient to user monitoring, improve user's use experience.
Further, for operability and the man-machine interaction performance that improves native system, can also on upper data processing equipment 106, connect a PC110, this PC110 can be connected with upper data processing equipment 106 by the RS232 interface, and this PC110 is used for being provided with, monitoring for the user work of described upper data processing equipment 106.Improve the man-machine interaction of native system, be convenient to user management.
In the present embodiment, this heat dissipation equipment 306 can be existing various heat dissipation equipments 306, such as air cooling, liquid cooling and 3 kinds of modes of phase-change material cooling.Air cooling is plain mode, only need allow air flow through battery surface.Liquid cools is divided into direct contact and the non-dual mode that directly contacts.Mineral oil can be used as the direct contact heat transfer medium, and water or anti-icing fluid can be used as typical non-direct contact heat transfer medium.Liquid cooling must could be cooled off battery by heat exchange facilities such as water jackets, and this has reduced heat exchange efficiency to a certain extent.Heat transfer rate between battery wall and the fluid media (medium) is relevant with the factors such as form, flow velocity, fluid density and thermal conductivity that fluid flows.
The major advantage of air cooling mode has: (1) is simple in structure, and weight is less relatively; (2) possibility of leakage does not take place; Energy available ventilation when (3) pernicious gas produces; (4) cost is lower.Shortcoming is that heat exchange coefficient is low between itself and the battery wall, and cooling, firing rate are slow.
The major advantage of liquid cooling mode has: heat exchange coefficient height between (1) and the battery wall, and cooling, firing rate is fast; (2) volume is less.Major defect has: the possibility that has leakage; Weight is relatively large; Maintenance and maintenance are complicated; Need parts such as water jacket, heat exchanger, the structure relative complex.
The battery pack of parallel type hybrid dynamic electric motor car is as auxiliary power component, and service conditions is not very abominable, adopts the air cooling mode just may reach instructions for use; For pure electric automobile and serial type hybrid automobile, battery pack is as main power component, and living heat is very big, seek out reasonable thermal management effect, can consider to adopt the mode of liquid cooling.
Temperature contrast in the battery case 107 between the different battery modules, the inconsistency that can aggravate the internal resistance of cell and capacity if long time integration can cause part battery overcharge or overdischarge, and then influences the life-span and the performance of battery, and causes potential safety hazard.The temperature contrast and the battery pack of battery module are furnished with much relations in the battery case 107, and generally speaking, the battery in centre position accumulates heat easily, and the battery radiating condition at edge is quite a lot of.So when carrying out battery pack structure layout and heat dissipation design, guarantee the uniformity of battery pack heat radiation as far as possible.
With the air cooling heat radiation is that example is come, and draft type generally has serial and walks abreast two kinds, as shown in Figure 5 and Figure 6.
Under the serial draft type shown in Figure 5, cold air blows the people from the left side and blows out from the right side.Air constantly is heated in flow process, so the cooling effect on right side is poorer than the left side among the figure, battery pack temperature from left to right raises successively in the battery case 107, has the uneven temperature defective.
Shown in Figure 6, the air inlet of described blower fan is arranged on an end of each battery that is arranged side by side, the air outlet of blower fan is arranged on the other end of described each battery that is arranged side by side, and air inlet is the inlet channel 401 of wedge shape, and inlet channel 401 progressively narrows down along the air intake direction; Air outlet is the exhaust passage 402 of wedge shape, exhaust passage, described place 402 progressively broadens along air-out direction, the inlet channel 401 of this wedge shape, exhaust passage 402 make that slit pressure differential up and down is consistent substantially between different battery modules, have guaranteed to blow over different battery moulds and have adopted parallel draft type shown in Figure 5 to make air mass flow distribute more equably between battery module.
In battery management system, the dump energy of battery (characterizing SOC:Stateof Charge with state-of-charge SOC) estimates it is one of key technology.Because battery SOC is subjected to the influence of factors such as ambient temperature, self discharge, periodic duty number of times, battery pack inconsistency, accurately the difficulty of estimating is very big.
The advanced person's who is developed at present batteries management system is by Research on New and enforcements such as battery SOC algorithm for estimating, thermal management technology and safety managements, the parameter of bringing for cell degradation changes, the two filtering algorithms of research, when estimating SOC, battery capacity is estimated, and carried out the health status forecasting procedure research of battery in conjunction with change in voltage.The inventor proposes to judge and the management system optimisation technique based on the discharging ending status of battery that wavelet transformation and SOC technology combine, can judge the discharge off state adaptively for different environments for use and different types of battery, improve the discharge fail safe and give full play to the energy content of battery again, unhealthy battery early prediction technology.
The inventor studies in conjunction with the battery thermal model by practice, propose to pass through battery cell surface temperature and historical information and the algorithm of the inner maximum temperature of estimating battery, analyze the characteristic distributions in temperature field in the battery case, optimize the quantity and the position of battery case inner sensor, thereby the heat management function and the management system optimisation technique of battery management system combined.
1,1 native system has been set safety management function:
The function of safety management comprises that whether the electric current and voltage of monitoring battery surpasses restriction, prevents battery over-discharge etc.Prevent arbitrary battery over-discharge in the battery pack again in order to make full use of the energy content of battery, must be in good time and accurately to the judgement of discharging ending status of battery.
The method of the judgement discharge off state that the current driving force battery uses mainly contains: fixedly final voltage method, discharge curve slope method and capacity accumulative.
Wherein, though fixedly the final voltage method is simple, final discharging voltage difference under different discharging currents, the standard that neither one is unified, and the discharging current of actual electrokinetic cell is a change at random, does not have certain rule.If set unified final discharging voltage, for preventing battery overdischarge under any operating mode, this voltage must be tending towards conservative (higher), can influence making full use of of the energy content of battery.
When being the constant-current discharge test, discharge curve slope method uses maximum a kind of methods.From the battery discharge curve, can see in the battery discharge later stage, the slope catastrophe point (be commonly called as and be " flex point ") that obviously has a discharge curve, the capacity that battery can be emitted after this flex point seldom, and this discharge and use in future for battery is also very uneconomical, can be decided to be this flex point the terminating point of battery discharge.Generally flex point is decided to be its slope equals the point that 10 times of voltage-time curve plateau slopes are located now.Battery is when low discharging current, and the slope of the plateau that its voltage descends is very little, and slope is the obviously local and actual discharge off point wide apart of 10 times of plateaus in the discharge curve.And during heavy-current discharge, the slope of the plateau that its voltage descends is bigger, and slope is plateau 10 times place in the discharge curve, and voltage descends very fastly, has surpassed the stop value of actual discharge.It is very big that The noise is measured in the calculating of discharge curve slope simultaneously.
The capacity accumulative promptly writes down the electric weight that battery charges into and emits, and when in a charge and discharge cycles, both equate, think that battery discharge stops.This method constantly writes down discharging and recharging the historical data of battery except that need, also will carry out corrections such as discharging current, cell degradation, self discharge to capacity, and the process complexity is generally seldom used.
This inventor has proposed a kind of decision method of the discharging ending status of battery based on wavelet transformation, can judge the discharge off state adaptively for different environments for use and different types of battery, has adaptivity, can on the basis that guarantees fail safe, give full play to battery efficiency, thereby the SOC that obtains is an overall target, help further improving the reliability of this method, this method and SOC can be combined and carry out the discharge off condition judgement.
1, technology such as 2 heat managements
Battery pack will be given full play to good performance, and its working temperature must be limited to a smaller scope.For the battery that uses under high power discharge and the hot conditions, the heat management of battery is particularly necessary.The research of thermal management subsystem 1 mainly improves three aspects by battery thermal model, 1 design of battery pack thermal management subsystem and battery heat dispersion and forms.Wherein the battery thermal model is the research core, for thermal management subsystem 1 design and the improvement of battery heat dispersion provide theoretical foundation.About the battery thermal model, foreign study mechanism has carried out more research, and domestic research work is in the starting stage.1979, U.S. Argonne National Laboratory set up two-dimentional thermal model for the first time; Battery was divided into kernel in 86 years and two three-dimensional thermal models in zone of shell are studied; The University of Texas is considering that the inside battery material is reaching the two-dimentional thermal model of having set up lithium battery under the dynamic industrial and mineral under the anisotropic condition aspect the heat conduction.Research about thermal model is gradually improved, and the design of carrying out thermal management subsystem 1 for this project lays the foundation.But also exist battery is divided into kernel and two zones of shell, does not consider the existence of inner other parts such as collector etc.; Most models all adopts Bernardi to give birth to hot speed, because the difference of battery variety and model needs the applicability of the living hot speed of research Bernardi etc.Therefore need study in conjunction with thermal model, battery case interior flow field and battery are given birth to hot analysis of heat transfer, research is by the method for battery cell surface temperature in the battery pack and the inner maximum temperature of historical information estimating battery group, grasp the characteristic distributions in temperature field in the battery case, optimize the quantity and the position of temperature sensor in the battery case, improve the heat management level of battery management system.
Battery pack thermal management subsystem 1 of the present invention is from user's angle, is used for guaranteeing that battery pack is operated in the whole system of preference temperature scope, comprises parts such as battery case, heat transfer medium, monitoring equipment.The characteristics of battery pack thermal management subsystem 1 and major function:
Under a, the battery low-temperature condition, the accurate measurement and the monitoring of battery temperature;
B, effectively loose wind and ventilation when battery pack temperature is too high;
Fast Heating under c, the cryogenic conditions, battery pack can operate as normal; D, the available ventilation when pernicious gas produces;
The even distribution of e, assurance battery pack temperature field.
Adopt the good battery pack thermal management subsystem 1 of systematized method for designing design performance, the design of native system, on the research basis in early stage, sum up the achievement of repeatedly systematization design, take all factors into consideration temperature to the influence in battery performance and useful life with the selection of determining the optimum operating temperature range of battery, the prediction of battery thermal field accounting temperature, heat transfer medium, the key technologies such as selection of thermal management subsystem 1 heat radiation consequence devised, blower fan and point for measuring temperature.
In addition, the management system software and hardware is optimized, improves module voltage, the accuracy of current measurement, real-time, for the SOC algorithm for estimating and the correlated performance research of battery provides accurate test environment; Employing improves the maintainability of system in the application programming technology, is convenient to the through engineering approaches and the industrialization of system.
Therefore native system is attached most importance to the strong tracking Kalman filtering method based on neural network model, and its major technique innovative point is as follows:
(1), under the inhomogeneous condition of monomer characteristic, battery pack SOC estimates and based on the SOC algorithm for estimating of strong tracking card Kalman Filtering;
(2), battery discharge is proposed by condition judging method, raising discharge fail safe;
(3), battery system is given birth to heat analysis and management system optimisation technique.
The commercialization design of native system: through engineering approaches design, standard interface design, ray machine electricity converter ic plate and the power stability compensating circuit feedback integrated circuit (IC) design etc. that comprise product.Make native system possess following characteristics:
(1) communication and control interconnection;
(2) embedded μ C/OS and driving exploitation;
(3) location (RTLS) algorithm utilizes Kalman filtering to carry out the SOC estimation of battery pack in real time;
(4) data-storage system adopts the method that embedded database and JAVAAapplet technology combine;
(5) miniaturization.
(6) low power dissipation design etc.
Native system is based on the result of study of battery cell, estimate and based on the SOC algorithm for estimating of strong tracking card Kalman Filtering based on battery pack SOC under the inhomogeneous condition of monomer characteristic, utilize Kalman filter to realize the Minimum Mean Square Error estimation of SOC, realized estimation to battery charge state, and the error of initial value there is very strong correcting action, noise there is very strong inhibitory action, can improve the reliability of SOC algorithm, make algorithm for estimating have stronger mutation status follow-up control, the cell health state forecast is provided, be applicable to that electric current changes violent actual condition, thereby it is, significant when satisfying electric automobile work to promoting the electric vehicle industrialization process to battery security and the requirement of giving full play to the battery effective utilization.
In order further to be convenient to the public system of the present invention there is further connection, below the estimation technique and the implementation method of the storage battery state-of-charge (SOC) of explanation native system:
From ability and two angles of raising fail safe of giving full play to battery, the accurate estimation of SOC is the key factor that realizes the battery-efficient management; The estimated accuracy of SOC also is the basis of carrying out the energy strategy study simultaneously, is one of key technology of electric automobile.This method is based on the cell row electricity condition equation of ampere-hour measurement Law, and the state space equation of the battery that measurement equation constituted of cell load voltage, obtains the state-of-charge of battery again with improved EKF Equation for Calculating.Fig. 7 is based on the method for estimation flow chart of the electric power storage electrical automobile battery SOC of improved EKF, and referring to shown in Figure 7, this method may further comprise the steps:
Step 501: initialization: the initial value SOC of the SOC of given battery
0(be following x
0);
Given predicated error covariance matrix initial value P
0
Given measuring noise square difference Q:
Given filtering multiplication factor α;
For k=1,2... waits each sampling instant, carries out following calculating respectively:
Step 502: obtain Nietzsche's sample load voltage signal v of battery constantly
k, current signal I
k
Step 503: determine battery model: battery model is made up of following state-of-charge equation and load voltage measurement equation:
The state-of-charge equation of battery: make x
k=SOC
k
The load voltage measurement equation of battery:
y(k)＝f(I
k，x
k)+v
k＝K
0-RI
k-k
1/x
k-K
2x
k+K
3ln(x
k)+K
4ln(1-x
k)+v
k
Wherein, v
kBe measurement noise, its variance is Q.
Order measures battle array
Then Kalman filter equation is a status predication:
Calculate and measure battle array: C
k=K
1/ (x
k)
2-K
2+ K
3/ x
3-K
4/ (1-x
k);
Filter gain:
Prediction mean square deviation: P
K/k-1=P
K-1/k-1
Estimate mean square deviation: P
K/k=(I-K
KC
K) P
K/k-1
State estimation: x
K/k=x
K/k-1+ aK
k[y
k-f (I
k, x
K/k-1)];
For k=1,2... waits each sampling instant, and the computational process of circulation 2～3 can obtain each SOC estimated value of battery constantly.
Wherein, in the current signal I of experiment measuring gained in the implementation process (t), voltage signal V (t) are when there is initial error in SOC gained SOC estimated result, suppose that the waveform schematic diagram of the SOC estimated result that discharges naturally that exists is respectively shown in Fig. 8-11.
By above experimental results show that, method proposed by the invention has very strong adaptivity, can estimate the SOC of battery more exactly for different environments for use and this method of different types of battery, importantly insensitive for the initial value error, can partly correct the error that discharge brings.Reached its intended purposes.
(3) safety management technology (based on the decision method of the discharging ending status of battery of wavelet transformation).
Referring to Figure 12, safety management technology is that battery discharge is studied by condition judging method, improves the discharge fail safe, in conjunction with the SOC technology, and the discharging ending status of battery decision method that research is merged mutually based on wavelet transformation and SOC technology.The parameter of bringing for cell degradation changes, and the two filtering algorithms of research are estimated battery capacity when estimating SOC, and carried out the health status forecasting procedure research of battery in conjunction with change in voltage.The discharging ending status of battery decision method that proposition is merged mutually based on wavelet transformation and SOC technology can be judged the discharge off state adaptively for different environments for use and different types of battery, improves the discharge fail safe and gives full play to the energy content of battery again., unhealthy battery early prediction technology
Decision method based on the battery of electric vehicle discharge off state of wavelet transformation relates to electric automobile intelligent information processing technology field.The discharge off judgement is carried out in its comprehensive utilization fixedly final voltage method and discharge curve slope method, when being lower than fixedly final voltage, load voltage starts the wavelet analysis module, utilize wavelet transformation that the load voltage information of battery is analyzed, term extracts the slope catastrophe point through level and smooth back voltage signal, just stops discharge when the slope catastrophe point occurring.This method has very strong adaptability, for different environments for use and dissimilar batteries, all can adaptive judgement discharge off state, and can effectively overcome the influence of measurement noise simultaneously.
Referring to Figure 12, contain following steps by the control of the central processing unit in battery management system operation based on the decision method of the battery of electric vehicle discharge off state of wavelet transformation:
Step 601: initialization: the fixedly final voltage threshold value V of given battery
0
The threshold value WT of given load voltage signal extreme point after the clivia conversion
Valve
Step 602: the load voltage signal V (t) that obtains battery cell;
Step 603: whether the load voltage signal V (t) that judges battery cell is lower than preset threshold V
0, as V (t)＜V
0Shi Ze carries out wavelet transformation, otherwise continues step 602;
Step 604: V (t) is carried out wavelet transformation by following formula:
Wherein R is a limit of integration, for beginning to carry out the initial moment of wavelet analysis to the zone between the current sampling instant;
Following formula is abbreviated as: WT
aX (t)=x (t) * Ψ
a(t);
X (t)=V (t) a is a scale factor, a=2
j, j is a natural number, its scope is 2～5;
Wherein:
Wherein, θ (t) is Gauss's lowpass function,
Step 605: the extreme point that obtains figure signal: WT
Max
Step 606: judge extreme point WT
MaxWhether surpass the extreme point threshold value WT that sets
Valve, WT
ValveScope be outer 2～0 arbitrarily, work as WT
Max＞know WT
ValveAs the time execution in step 607 then: battery stops discharge, otherwise continues step 602.
Step 607: battery stops discharge.
Discharging current be 80A when wavelet transformation result (yardstick a=8) the waveform schematic diagram of discharge voltage signal V (t), discharge voltage signal V (t) of the decision method that Figure 13,14 is respectively above-mentioned battery of electric vehicle discharge off state based on wavelet transformation in implementation process.
Figure 15 is the battery management system frame diagram of method shown in Figure 12 in implementation process.
The function of safety management comprises that whether the electric current and voltage of monitoring battery surpasses restriction, prevents battery over-discharge etc.Prevent arbitrary battery over-discharge in the battery pack again in order to make full use of the energy content of battery, in good time and accurate to the judgement of discharging ending status of battery.
Therefore, adopt the discharging ending status of battery decision method based on wavelet transformation of present embodiment, can judge the discharge off state adaptively for different environments for use and different types of battery, on the basis that guarantees the discharge fail safe, give full play to the energy content of battery.
(4) function of heat management and design cycle:
Figure 16 is the thermal management technology design flow diagram in this power battery group management system.This battery pack thermal management subsystem 1 is used for guaranteeing that from user's angle battery pack is operated in the whole system of preference temperature scope, comprises parts such as battery case, heat transfer medium, monitoring equipment.The characteristics of battery pack thermal management subsystem 1 and major function:
Under a, the battery low-temperature condition, the accurate measurement and the monitoring of battery temperature;
B, effectively loose wind and ventilation when battery pack temperature is too high;
Fast Heating under c, the cryogenic conditions, battery pack can operate as normal;
D, the available ventilation when pernicious gas produces;
The even distribution of e, assurance battery pack temperature field.
The function of battery pack thermal management subsystem 1, the battery pack thermal management subsystem 1 that design performance is good, be to need to adopt systematized method for designing, the design of native system, on the research basis in early stage, sum up the achievement of repeatedly systematization design, take all factors into consideration temperature to the influence in battery performance and useful life with the selection of determining the optimum operating temperature range of battery, the prediction of battery thermal field accounting temperature, heat transfer medium, the key technologies such as selection of thermal management subsystem 1 heat radiation consequence devised, blower fan and point for measuring temperature.
To sum up, estimate and based on the SOC algorithm for estimating of strong tracking card Kalman Filtering based on battery pack SOC under the inhomogeneous condition of monomer characteristic, utilize Kalman filter to realize the Minimum Mean Square Error estimation of SOC, realized estimation to battery charge state, and the error of initial value there is very strong correcting action, noise there is very strong inhibitory action, can improve the reliability of SOC algorithm, make algorithm for estimating have stronger mutation status follow-up control, the cell health state forecast is provided, be applicable to that electric current changes violent actual condition, thereby it is, significant when satisfying electric automobile work to promoting the electric vehicle industrialization process to battery security and the requirement of giving full play to the battery effective utilization.
More than the technical scheme that the embodiment of the invention provided is described in detail, used specific case herein the principle and the execution mode of the embodiment of the invention are set forth, the explanation of above embodiment only is applicable to the principle that helps to understand the embodiment of the invention; Simultaneously, for one of ordinary skill in the art, according to the embodiment of the invention, the part that on embodiment and range of application, all can change, in sum, this description should not be construed as limitation of the present invention.
Claims (8)
1. a power battery group management system is characterized in that, comprising:
Security management subsystem is used to monitor the state-of-charge of each battery cell, determines according to the state-of-charge of described each battery cell whether described each battery cell is in the discharge off state, if then stop described battery discharge;
Thermal management subsystem, be used to survey the temperature on described each battery cell surface, temperature history information according to described each battery cell surface, determine described each battery cell temperature inside upper limit, determine the temperature distribution information of the battery case that constitutes by all described battery cells, control the working temperature of described battery pack according to described temperature distribution information, make described working temperature be in the range of set temperature;
Optimize the subsystem subsystem, be electrically connected with described security management subsystem, thermal management subsystem respectively, be used to control the work of described thermal management subsystem, security management subsystem.
2. power battery group management according to claim 1 system is characterized in that.
3. power battery group management according to claim 1 system is characterized in that described thermal management subsystem comprises: temperature sensor, be arranged in the battery case that is used for ccontaining described each battery cell, and be used to survey the temperature on described each battery cell surface;
Memory module is electrically connected with described temperature sensor, is used to store the temperature history information on described each battery cell surface;
Monomer internal temperature upper limit determination module is electrically connected respectively with described temperature sensor and memory module, is used for current temperature and temperature history information according to described each battery cell, determines described each battery cell temperature inside upper limit;
The Temperature Distribution analysis module is electrically connected with described monomer internal temperature upper limit determination module, is used for according to described each battery cell temperature inside upper limit, determines the temperature distribution information of the battery case that is made of all described battery cells;
Temperature control modules is electrically connected with described Temperature Distribution analysis module, is used for the work according to the heat dissipation equipment of described each battery case of described temperature distribution information control, make described each battery cell respectively working temperature be in the range of set temperature;
Heat dissipation equipment is arranged in described each battery case.
4. power battery group management according to claim 3 system is characterized in that,
Described heat dissipation equipment is a blower fan.
5. moving power battery group management according to claim 3 system is characterized in that,
Described temperature control modules also is electrically connected with a display unit,
Described display unit is used to show control information and the interior warm distributed intelligence of each battery case on the described temperature control modules.
6. power battery group management according to claim 1 system is characterized in that,
Described optimization subsystem adopts embedded system development to form.
7. a power battery group management method is characterized in that, comprising:
Initial value SOC0, the predicated error covariance matrix initial value P of the state-of-charge of each battery cell determined in initialization
0, measuring noise square difference Q, filtering multiplication factor α;
For k=1, Nietzsche's sample load voltage signal v of each battery cell is constantly obtained in each sampling instant such as 2...
k, current signal I
k
Make x
k=SOC
k, according to the state-of-charge equation of each battery cell:
Determine the state-of-charge of described each battery cell, wherein said k is a natural number,
According to formula:
Y (k)=f (I
k, x
k)+v
k=K
0-RI
k-k
1/ x
k-K
2x
k+ K
3Ln (X
K)+k
4Ln (1-x
k)+v
k, determine the load voltage amount y (k) of described each battery cell, wherein, v
kBe measurement noise, described v
kVariance be Q,
Order measures battle array
According to Kalman filter equation:
Calculate described measurement battle array: C
k=K
1/ (x
k)
2-K
2+ K
3/ x
3-K
4/ (1-x
k);
Determine filter gain:
Determine prediction mean square deviation: P
K/k-1=P
K-1/k-1
Determine to estimate mean square deviation: P
K/k=(I-K
KC
K) P
K/k-1
Determine the estimated value of the state-of-charge of described each battery cell: x
K/k=x
K/k-1+ aK
k[y
k-f (I
k, x
K/k-1)];
According to the estimated value of the state-of-charge of described each battery cell, make described each battery cell by discharge.
8. power battery group management method according to claim 7 is characterized in that,
According to the estimated value of the state-of-charge of described each battery cell, make described each battery cell by discharge, may further comprise the steps:
1) initialization: the fixedly final voltage threshold value V of given each battery cell
0
The threshold value WT of given load voltage signal extreme point after the clivia conversion
Valve
2), obtain the load voltage signal V (t) of each battery cell according to the estimated value of the state-of-charge of described each battery cell;
3) judge to exhale V (t) whether to be lower than threshold value V
0, as V (t)＜V
0The time execution in step 4 then), otherwise return step 2);
4) V (t) is carried out wavelet transformation by following formula:
Wherein R is a limit of integration, for beginning to carry out the initial moment of wavelet analysis to the zone between the current sampling instant;
Following formula is abbreviated as: WT
aX (t)=x (t) * Ψ
a(t), wherein x (t)=V (t) a is a scale factor, a=2
j, j is a natural number, its scope is 2～5,
θ (t) is Gauss's lowpass function,
5) obtain the extreme point of figure signal: WT
Max
6) judge WT
MaxWhether surpass threshold value WT
Valve, WT
ValveSpan be outer 2～0 arbitrarily, work as WT
Max＞WT
ValveThe time, then described battery cell stops discharge, otherwise returns step 2).
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