CN106649962A - Modeling method for participation of electric automobile power battery in power system frequency modulation based on consideration of battery life - Google Patents

Modeling method for participation of electric automobile power battery in power system frequency modulation based on consideration of battery life Download PDF

Info

Publication number
CN106649962A
CN106649962A CN201610895474.6A CN201610895474A CN106649962A CN 106649962 A CN106649962 A CN 106649962A CN 201610895474 A CN201610895474 A CN 201610895474A CN 106649962 A CN106649962 A CN 106649962A
Authority
CN
China
Prior art keywords
frequency modulation
electric automobile
power
battery
power system
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.)
Granted
Application number
CN201610895474.6A
Other languages
Chinese (zh)
Other versions
CN106649962B (en
Inventor
郭钰锋
张冬蕊
姜伊
王�琦
陈润欣
马欣彤
张童童
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Harbin Yingyan Technology Co.,Ltd.
Original Assignee
Harbin Institute of Technology
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Harbin Institute of Technology filed Critical Harbin Institute of Technology
Priority to CN201610895474.6A priority Critical patent/CN106649962B/en
Publication of CN106649962A publication Critical patent/CN106649962A/en
Application granted granted Critical
Publication of CN106649962B publication Critical patent/CN106649962B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/20Design optimisation, verification or simulation

Abstract

The invention discloses a modeling method for participation of an electric automobile power battery in power system frequency modulation based on consideration of the battery life, relates to a modeling method for participation of the electric automobile power battery in the power system frequency modulation, and aims to solve the problem that the influence of the cyclic life of the electric automobile battery and the travel state of an electric automobile on the participation of the battery of the electric automobile in the power system frequency modulation in the prior art. The modeling method comprises the following steps: 1, constructing a power system frequency modulation model containing an electric automobile power battery module, and outputting a power curve of the electric automobile power battery; 2, determining a networking proportion of the electric automobile; 3, determining a per unit extreme value of the power of a secondary frequency modulation channel of the power system frequency modulation model in the step 1 according to the step 2; and 4, constructing a life loss model of the electric automobile power battery, and calculating the capacity loss and the maximum energy shift of the electric automobile power battery which participates in the frequency modulation. The modeling method is applied to the field of power electrics.

Description

A kind of electric automobile power battery for considering battery life participates in power system frequency modulation and builds Mould method
Technical field
The present invention relates to electric automobile power battery participates in power system frequency modulation modeling method.
Background technology
Electric automobile is with electrical network interaction technique (V2G technologies) as the important step of intelligent grid, and its technological subject is electronic Automobile is because quick response and charge and discharge mode and the characteristic deposited, the effect is significant in power system frequency is adjusted.And participate in adjusting It is taken in small doses at short intervals during business, frequently discharge and recharge can cause irreversible infringement to the physical arrangement of electric automobile power battery, and then Reduce its service life.Battery life is the principal element for restricting Development of Electric Vehicles.Therefore, battery is being considered Under the premise of, to set up electric automobile power battery and participate in power system frequency modulation model, analysis electric automobile power battery participates in electric power System frequency modulation effect and the impact to its battery life, the development to promoting ev industry is significant.
Existing battery loss model does not account for influence factor and the rule of batteries of electric automobile cycle life, it is impossible to complete Face describes battery in the different phase for participating in power system frequency modulation, the infringement suffered by battery life;Existing frequency modulation model is only Comprising conventional power units such as steam turbine, the hydraulic turbines, do not consider under the overall situation of V2G technologies development, electric powered motor electricity Pond participates in the effect of power system frequency modulation.
The content of the invention
The present invention is not account for the impact of batteries of electric automobile cycle life and electronic vapour to solve prior art Car trip state it is participated in power system frequency modulation impact problem, and propose a kind of consideration battery life electric automobile Electrokinetic cell participates in power system frequency modulation modeling method.
A kind of electric automobile power battery for considering battery life participates in power system frequency modulation modeling method according to the following steps Realize:
Step one:The power system frequency modulation model containing electric automobile power battery module is set up, electric powered motor is exported Battery power curve;
Step 2:Determine electric automobile networking ratio;
Step 3:The frequency modulation frequency modulation channel power perunit pole of power system frequency modulation model in step one is determined according to step 2 Limit value;
Step 4:Electric automobile power battery life consumption model is set up, and calculates electric automobile power battery and participate in adjusting Capacitance loss and ceiling capacity skew after frequency.
Invention effect:
The present invention considers electric automobile trip state and participates in power system frequency modulation effect to electric automobile power battery Affect, and participate in impact of the power system frequency modulation to the electric automobile power battery life-span, establish the electricity for considering battery life Electrical automobile electrokinetic cell participates in power system frequency modulation model, and power system frequency modulation is participated in electric automobile from system end and battery-end Effect is estimated.Power system chirping strategies are participated in by modeling method of the present invention to electric automobile to select, can be with Battery capacity loss is dropped to into 0.0113% by 0.0158%, i.e. most senior general's battery capacity loss reduces by 28.5%.
Description of the drawings
Fig. 1 is single regional power system frequency modulation illustraton of model;
Fig. 2 is electric automobile power battery frequency modulation frequency modulation channel pattern figure;
Fig. 3 is private car trip proportion moment scattergram;
Fig. 4 is private car trip distance ratio scattergram;
Fig. 5 is private car trip average speed moment scattergram;
Fig. 6 is electric automobile trip proportion overview logic diagram;
Fig. 7 is electric automobile networking ratio scattergram;
Fig. 8 is electric automobile frequency modulation frequency modulation channel power ultimate value curve chart;
Fig. 9 is actual daily load curve figure certain electrical network one day;
Figure 10 predicts daily load curve figure one day for certain electrical network;
Figure 11 is electric automobile power battery primary frequency modulation strategy implementation method figure;
Figure 12 is the energy curves figure of power battery module group 1;
Figure 13 is the energy curves figure of power battery module group 2;
Figure 14 is system frequency deviation curve chart;
Figure 15 is electric automobile power battery frequency modulation frequency modulation passage limit value figure;
Figure 16 is that electrokinetic cell participates in frequency modulation frequency modulation system frequency difference curve chart;
Figure 17 is electrokinetic cell energy excursion curve chart.
Specific embodiment
Specific embodiment one:A kind of electric automobile power battery for considering battery life participates in the modeling of power system frequency modulation Method is comprised the following steps:
Step one:The power system frequency modulation model containing electric automobile power battery module is set up, electric powered motor is exported Battery power curve;
Step 2:Determine electric automobile networking ratio;
Step 3:The frequency modulation frequency modulation channel power perunit pole of power system frequency modulation model in step one is determined according to step 2 Limit value;
Step 4:Electric automobile power battery life consumption model is set up, and calculates electric automobile power battery and participate in adjusting Capacitance loss and ceiling capacity skew after frequency.
Specific embodiment two:Present embodiment from unlike specific embodiment one:Set up in the step one and contain The detailed process of the power system frequency modulation model of electric automobile power battery module is:
Step is one by one:Frequency modulation frequency modulation principle is unified based on power train, single regional power system frequency modulation model, such as Fig. 1 is set up It is shown;
Containing primary frequency modulation passage and frequency modulation frequency modulation passage in power system, the transmission function of primary frequency modulation passage isGiS () is the transmission function of each unit, aiFor each power of the assembling unit share coefficient, δiFor each unit difference coefficient;Two The transmission function of secondary FM channel is K (s), and K (s) is PI control functions;System is output as the frequency departure △ of current system f;RiTo participate in the power partition coefficient of the unit of frequency modulation frequency modulation, Ta∑For regional power grid equivalent time constant, βFor regional power grid Equivalent self-balancing coefficient, τ is zero-order holder time delay.
Step one two:Electric automobile power battery module is added into single regional power system frequency modulation model;
Power battery module is described using first order inertial loop, and its transmission function is:
Wherein described KEVFor electric automobile work(frequency characteristic coefficient, TEVFor power battery module time constant, s is La Pula This operator, GEVS () is the transmission function of power battery module;
It is a that electric automobile power battery participates in the transmission function of primary frequency modulation passage during power system frequency modulation modelEVGEV (s), aEVThe power fraction coefficient shared by power battery module;Frequency modulation frequency modulation passage is secondary in single regional power system frequency modulation model Power perunit ultimate value is increased on the basis of FM channel.Electric automobile power battery participates in power system frequency modulation frequency modulation passage Logic diagram is as shown in Figure 2.
Other steps and parameter are identical with specific embodiment one.
Specific embodiment three:Present embodiment from unlike specific embodiment one or two:In the step 2 really The detailed process for determining electric automobile networking ratio is:
The present invention considers the trip feature of electric automobile cluster determining electric automobile power battery frequency modulation frequency modulation passage Perunit limit value.Private car trip proportion moment, distance and velocity distribution curve are obtained according to statistical result.In the five rings of Beijing The statistical result of floating vehicle data survey is respectively as shown in Fig. 3, Fig. 4, Fig. 5.
For a certain moment t, automobile user trip proportion is designated as P (t).Any time, electric automobile trip Range distribution is as shown in Figure 4.When electric automobile trip distance is longer, restricted by travel speed, it is impossible in a hour Complete corresponding mileage.Therefore, at subsequent time (t+1), it is still in transport condition, it is impossible to be connected with electrical network.But just when (t+1) For quarter, its operating range changes.And still moment t subsequent time run electric automobile in trip distance, OK After sailing the renewal of the states such as speed, will be superimposed with the electric automobile at (t+1) moment trip state and ratio, it is electronic so as to obtain The overview that automobile continuously runs.Specific procedure logic diagram is as shown in Figure 6.
Wherein s (t) refers to (1h) in unit interval, and at a time under average speed, electric automobile can be travelled Ultimate range.And according to Fig. 4, d (t) refers to that electric automobile inscribes the row drawn up row distance and draw up this distance of row at this Car ratio.For example, when electric automobile is when being 40km at moment t maximum displacements s (t), electricity of d (t) the middle rolling cars distance less than 40km Electrical automobile is believed that within this period can switch to halted state by transport condition, network operation in parallel participates in system frequency modulation.And go Electric automobile of the car distance more than 40km will be continued to run with subsequent time, and it is also needed in the distance for travelling and shared automobile group Ratio will be updated in the state parameter of subsequent time.
On the basis of the above, by the way that to whole day 24 hours, electric automobile group use state carried out rolling renewal, you can obtain Whole day not in the same time under, access electrical network electric automobile ratio change curve, as shown in Figure 7.
Step 2 one, setting initial time value t=1, according to electric automobile trip speed v (t), trip proportion P of statistics T the statistical result of () and trip distance d (t) obtains the speed in electric automobile 1 hour;
Step 2 two, speed of service v (t) for obtaining electric automobile;
Step 2 three, maximum displacement s (t) calculated in electric automobile 1 hour;
Step 2 four, as t=1 electric automobile operation ratio be P (t);When t is more than 1, the operating ratio of electric automobile Example is P (t)+Pa.sum. (t);
Step 2 five, two to the step 2 four of iteration execution step 2, until t terminates to obtain electric automobile operation when being more than 24 Proportional curve figure, networking ratio=1-operation ratio.
Other steps and parameter are identical with specific embodiment one or two.
Specific embodiment four:Unlike one of present embodiment and specific embodiment one to three:The step 2 The process of asking for of Pa.sum. (t) is specially in four:
Ratio Ps.d. (t) of step (1), trip distance d (t) of counting statistics data acquisition more than s (t);
Driving ratio Pa.d. (t+1) outside step (2), counting statistics data, Pa.d. (t+1)=P (t) Ps.d. (t);
Step (3), renewal d (t+1) are d (t)-s (t);D (t+1) is brought in step (1) again, iteration execution step (1) and step (2), Pa.d. (t+2) is obtained;Until d (t+m) terminates less than s (t+m);
Step (4), t hours, total driving ratio is outside statistical data
Other steps and parameter are identical with one of specific embodiment one to three.
Specific embodiment five:Unlike one of present embodiment and specific embodiment one to four:The step 3 The middle frequency modulation frequency modulation channel power perunit ultimate value for determining power system frequency modulation model in step one is specially:
Due to electric automobile power battery itself capacity limit, there is maximum output limit in it to the frequency modulation power that electrical network is provided Value, according to the electric automobile networking ratio distribution curve obtained in step 2, with reference to battery types and electric automobile scale, The output limit that electrokinetic cell is reached in electrical network provided auxiliary frequency modulation service can be calculated, as shown in Figure 8.
The mark of frequency modulation frequency modulation channel power perunit ultimate value=electric automobile networking ratio × batteries of electric automobile total capacity One value.
Other steps and parameter are identical with one of specific embodiment one to four.
Specific embodiment six:Unlike one of present embodiment and specific embodiment one to five:The step 4 It is middle set up electric automobile power battery life consumption model detailed process be:
By taking lithium iron phosphate dynamic battery as an example, for cycle-index, ambient temperature, charge-discharge magnification and discharge and recharge depth The factor of four aspects of degree is analyzed, and battery capacity is lost as the Main Basiss for weighing battery life decay, sets up and uses In the battery module of electric vehicle Cycle life prediction model of frequency modulation service;
If the parameter of energy variation is A in cyclic processh
Ah=DOD × n × Cap (2)
Cap is the capacity (AH) of set of cells in formula, and DOD is the depth of discharge (%) of set of cells, and n is electrokinetic cell circulation time Number;
Based on Arrhenius formula, obtain battery capacity and lose with the relation of each electric stress factor:
In formula B be the preceding paragraph factor, EaFor reaction activity, its value is 31500Jmol-1, T is set of cells place environment Thermodynamic temperature (K), R is gas constant, and its value is 8.314J (mol × K)-1, z is energy equation factor, and value is 0.55- 0.56;
When at set of cells place, thermodynamic temperature T of environment is 298K, preceding paragraph factor B is between discharge-rate C_Rate Relational expression:
Other steps and parameter are identical with one of specific embodiment one to five.
Specific embodiment seven:Unlike one of present embodiment and specific embodiment one to six:The step 4 The middle capacitance loss calculated after electric automobile power battery participation frequency modulation and the detailed process of ceiling capacity skew are:
The electric automobile power battery power curve obtained in step one is integrated through integrator, electronic vapour is obtained Car electrokinetic cell energy curves, according to energy curves ceiling capacity skew is obtained;Energy curves are input to Battery life loss model, calculates electric automobile power battery and participates in after power system frequency modulation according to formula (2) to formula (4) Capacitance loss.
Other steps and parameter are identical with one of specific embodiment one to six.
Embodiment one:
Emulated with the service data that certain electrical network is actual a day, load data is as shown in Figure 9 and Figure 10.With model As a example by the electric automobile parameter of " Roewe E50 ", its parameter is as shown in table 1.
The Roewe E50 vehicle relevant parameters of table 1
Step 1:The power system frequency modulation model that module containing electric automobile power battery is participated in is set up, wherein battery module is passed Delivery function is:
Step 2:Determine that electric automobile participates in power system chirping strategies.
In the present embodiment, electric automobile power battery is only involved in power system primary frequency modulation.Electric automobile participates in power train Unified time chirping strategies are as follows:Electric automobile power battery module is divided into two groups, and group 1 is participating in system primary frequency modulation process In, first in charged state, group 2 is in discharge condition.Often through 60 minutes, two groups of charging and discharging states are exchanged.
In Matlab/Simulink emulation platforms, by measure battery module of electric vehicle is divided into into two groups, sets arteries and veins The cycle for rushing generator is 3600s, when pulse signal is more than zero, to the electrokinetic cell of group 1 positive signal is input into, and now organizes 1 Electrokinetic cell be in charged state, to the negative signal of the electrokinetic cell input of group 2, now the electrokinetic cell of group 2 is in electric discharge State;Conversely, when pulse signal is less than zero, group 1 is in discharge condition, and input signal is negative value, group 2 is in charged state, Input signal be on the occasion of.With comparator determination frequency deviation signal whether zero passage.When frequency departure signal is for just and set of cells is defeated The set of cells for entering signal for timing in charged state is started to charge up, when frequency departure signal is less than zero and is input into the letter of set of cells Number for it is negative when, the set of cells in discharge condition is started working, and the conversion of two Battery pack charging and discharging states is realized with this, only with Pulse signal is illustrated in case of being more than zero to model, and concrete steps are as shown in figure 11.
Step 3:Set up electric automobile power battery life consumption model.By taking lithium iron phosphate dynamic battery as an example, for following Ring number of times, ambient temperature, the factor of four aspects of charge-discharge magnification and depth of discharge are analyzed, and battery capacity is damaged Lose as the Main Basiss for weighing battery life decay, set up pre- for the battery module of electric vehicle cycle life of frequency modulation service Survey model;
Being introduced into can reflect the parameter A of energy variation in cyclic processh, provide definition:
Ah=DOD × n × Cap (2)
Cap is the capacity (AH) of set of cells in formula, and DOD is the depth of discharge (%) of set of cells, and n is electrokinetic cell circulation time Number;
It is to provide battery capacity to lose with the relation of each electric stress factor with Arrhenius formula:
In formula B be the preceding paragraph factor, EaFor reaction activity, its value is 31500Jmol-1, T is set of cells place environment Thermodynamic temperature (K), R is gas constant, and its value is 8.314J (mol × K)-1, z is energy equation factor, and value is 0.55- 0.56;
When ambient temperature T is 298K, preceding paragraph factor B is with the relational expression between discharge-rate C_Rate
Emulated on Matlab/Simulink platforms, as a result as shown in Figure 12, Figure 13 and Figure 14.
Under calculating the strategy, the loss of electric automobile power battery module capacity is 0.0119%, and ceiling capacity skew is 1.85%.
Embodiment two:
Emulated with the service data that certain electrical network is actual a day, load data is as shown in Figure 9 and Figure 10.With model As a example by the electric automobile parameter of " Roewe E50 ", its parameter is as shown in table 1.
The Roewe E50 vehicle relevant parameters of table 1
Step 1:The power system frequency modulation model that module containing electric automobile power battery is participated in is set up, wherein battery module is passed Delivery function is:
Step 2:Determine that electric automobile participates in power system chirping strategies.
Electric automobile participation power system frequency modulation frequency modulation strategy is as follows in this strategy:System frequency deviation signal, first via PID control link, generates corresponding power control signal.When power control signal exceedes setting signal marginal value, electronic vapour In the presence of power control signal, the frequency modulation power needed for output system reaches power system frequency modulation to car power battery module Purpose.
Wherein battery capacity share is 0.02, and zero-order holder time delay is set to 15s, electric automobile power battery PID channel parameters are set to 0.15/0.6/0, and PID signal response marginal value is set to 0.002, the electricity according to determined by step 3 Electrical automobile electrokinetic cell frequency modulation frequency modulation limit value is as shown in figure 15.
Step 3:Set up electric automobile power battery life consumption model.By taking lithium iron phosphate dynamic battery as an example, for following Ring number of times, ambient temperature, the factor of four aspects of charge-discharge magnification and depth of discharge are analyzed, and battery capacity is damaged Lose as the Main Basiss for weighing battery life decay, set up pre- for the battery module of electric vehicle cycle life of frequency modulation service Survey model;
Being introduced into can reflect the parameter A of energy variation in cyclic processh, provide definition:
Ah=DOD × n × Cap (2)
Cap is the capacity (AH) of set of cells in formula, and DOD is the depth of discharge (%) of set of cells, and n is electrokinetic cell circulation time Number;
It is to provide battery capacity to lose with the relation of each electric stress factor with Arrhenius formula:
In formula B be the preceding paragraph factor, EaFor reaction activity, its value is 31500Jmol-1, T is set of cells place environment Thermodynamic temperature (K), R is gas constant, and its value is 8.314J (mol × K)-1, z is energy equation factor, and value is 0.55- 0.56;
When ambient temperature T is 298K, preceding paragraph factor B is with the relational expression between discharge-rate C_Rate
Emulated on Matlab/Simulink platforms, as a result as shown in Figure 16 and Figure 17.
Through calculating, electrical automobile power battery module life loss is 0.0215% under the strategy, and ceiling capacity skew is 14.62%.
Embodiment three:
Emulated with the service data that certain electrical network is actual a day, load data is as shown in Figure 9 and Figure 10.With model As a example by the electric automobile parameter of " Roewe E50 ", its parameter is as shown in table 1.
The Roewe E50 vehicle relevant parameters of table 1
In the present embodiment, there are four kinds of discharge and recharge strategies:
Strategy 1:During system primary frequency modulation is participated in, power battery module can freely turn between charge and discharge state Change;
Strategy 2:Electric automobile power battery module is divided into three groups, and group 1 is first during system primary frequency modulation is participated in In charged state, when energy content of battery change exceedes gross energy 1.85%, switch to discharge condition.Group 2 is similar to group 1, but first In discharge condition.Group 3 will participate in system frequency modulation when will be in identical charging and discharging state with group 2 organizing 1.Wherein, group 1 and group 2 Battery capacity is the 40% of electrokinetic cell total capacity, organizes 3 capacity for the 20% of electrokinetic cell total capacity;
Strategy 3:Electric automobile power battery module is divided into two groups, and group 1 is first during system primary frequency modulation is participated in In charged state, group 2 is in discharge condition.Often through 60 minutes, two groups of charging and discharging states are exchanged;
Strategy 4:Electric automobile power battery module is divided into two groups, organizes 1 during system primary frequency modulation is participated in, only It is charged, group 2 is only discharged.
Step 1:The power system frequency modulation model that module containing electric automobile power battery is participated in is set up, wherein battery module is passed Delivery function is:
Step 2:Set up electric automobile power battery life consumption model.By taking lithium iron phosphate dynamic battery as an example, for following Ring number of times, ambient temperature, the factor of four aspects of charge-discharge magnification and depth of discharge are analyzed, and battery capacity is damaged Lose as the Main Basiss for weighing battery life decay, set up pre- for the battery module of electric vehicle cycle life of frequency modulation service Survey model;
Being introduced into can reflect the parameter A of energy variation in cyclic processh, provide definition:
Ah=DOD × n × Cap (2)
Cap is the capacity (AH) of set of cells in formula, and DOD is the depth of discharge (%) of set of cells, and n is electrokinetic cell circulation time Number;
It is to provide battery capacity to lose with the relation of each electric stress factor with Arrhenius formula:
In formula B be the preceding paragraph factor, EaFor reaction activity, its value is 31500Jmol-1, T is set of cells place environment Thermodynamic temperature (K), R is gas constant, and its value is 8.314J (mol × K)-1, z is energy equation factor, and value is 0.55- 0.56;
When ambient temperature T is 298K, preceding paragraph factor B is with the relational expression between discharge-rate C_Rate
Power battery module capacity and energy variation numerical value are as shown in table 2 under through calculating Different Strategies.
Power battery module capacity and energy variation under the Different Strategies of table 2
Analyze by the method for the invention, pay the utmost attention to the capacitance loss of battery, selection strategy 2 is used as electric powered motor Battery participates in power system chirping strategies, battery capacity loss can be dropped to into 0.0113% by 0.0158%, i.e. most senior general Battery capacity loss reduces by 28.5%.

Claims (7)

1. a kind of electric automobile power battery for considering battery life participates in power system frequency modulation modeling method, it is characterised in that The electric automobile power battery participates in power system frequency modulation modeling method and comprises the following steps:
Step one:The power system frequency modulation model containing electric automobile power battery module is set up, electric automobile power battery is exported Power curve;
Step 2:Determine electric automobile networking ratio;
Step 3:The frequency modulation frequency modulation channel power perunit limit of power system frequency modulation model in step one is determined according to step 2 Value;
Step 4:Electric automobile power battery life consumption model is set up, and calculates electric automobile power battery and participated in after frequency modulation Capacitance loss and ceiling capacity skew.
2. a kind of electric automobile power battery participation power system frequency modulation for considering battery life according to claim 1 is built Mould method, it is characterised in that the power system frequency modulation model containing electric automobile power battery module is set up in the step one Detailed process is:
Step is one by one:Frequency modulation frequency modulation principle is unified based on power train, single regional power system frequency modulation model is set up;
Containing primary frequency modulation passage and frequency modulation frequency modulation passage in power system, the transmission function of primary frequency modulation passage isGiS () is the transmission function of each unit, aiFor each power of the assembling unit share coefficient, δiFor each unit difference coefficient;Two The transmission function of secondary FM channel is K (s);System is output as the frequency departure △ f of current system;
Step one two:Electric automobile power battery module is added into single regional power system frequency modulation model;
Power battery module is described using first order inertial loop, and its transmission function is:
G E V ( s ) = K E V 1 + T E V s - - - ( 1 )
Wherein described KEVFor electric automobile work(frequency characteristic coefficient, TEVFor power battery module time constant, s is that Laplce calculates Son, GEVS () is the transmission function of power battery module;
It is a that electric automobile power battery participates in the transmission function of primary frequency modulation passage during power system frequency modulationEVGEV(s), aEVFor electricity Power fraction coefficient shared by electrical automobile power battery module;Frequency modulation frequency modulation passage is in the secondary tune of single regional power system frequency modulation model Power perunit ultimate value is increased on the basis of frequency passage.
3. a kind of electric automobile power battery participation power system frequency modulation for considering battery life according to claim 2 is built Mould method, it is characterised in that the detailed process of determination electric automobile networking ratio is in the step 2:
Step 2 one, arrange initial time value t=1, according to statistical result obtain 24 hours in electric automobile trip speed v (t), Trip proportion P (t) and trip distance d (t);
Step 2 two, speed of service v (t) obtained in 1 hour of electric automobile;
Step 2 three, maximum displacement s (t) calculated in electric automobile 1 hour;
Step 2 four, as t=1 electric automobile operation ratio be P (t);When t is more than 1, the operation ratio of electric automobile is P(t)+Pa.sum.(t);
Step 2 five, two to the step 2 four of iteration execution step 2, until t terminates when being more than 24, obtain electric automobile operating ratio Example curve chart, networking ratio=1-operation ratio.
4. a kind of electric automobile power battery participation power system frequency modulation for considering battery life according to claim 3 is built Mould method, it is characterised in that the process of asking for of Pa.sum. (t) is specially in the step 2 four:
Step (1), calculate 1 hour in statistical data obtain trip distance d (t) more than s (t) ratio Ps.d. (t);
Driving ratio Pa.d. (t+1) outside step (2), counting statistics data, Pa.d. (t+1)=P (t) Ps.d. (t);
Step (3), renewal d (t+1) are d (t)-s (t);D (t+1) is brought in step (1) again, iteration execution step (1) and Step (2), obtains Pa.d. (t+2);Until d (t+m) terminates less than s (t+m);
Step (4), t hours, total driving ratio is outside statistical data
5. a kind of electric automobile power battery participation power system frequency modulation for considering battery life according to claim 4 is built Mould method, it is characterised in that the frequency modulation frequency modulation channel power of power system frequency modulation model in step one is determined in the step 3 Perunit ultimate value is specially:
The perunit value of frequency modulation frequency modulation channel power perunit ultimate value=electric automobile networking ratio × batteries of electric automobile total capacity.
6. a kind of electric automobile power battery participation power system frequency modulation for considering battery life according to claim 5 is built Mould method, it is characterised in that the detailed process that electric automobile power battery life consumption model is set up in the step 4 is:
If the parameter of energy variation is A in cyclic processh
Ah=DOD × n × Cap (2)
Cap is the capacity of set of cells wherein in formula, and DOD is the depth of discharge of set of cells, and n is battery charging and discharging cycle-index;
Based on Arrhenius formula, obtain battery capacity and lose with the relation of each electric stress factor:
Q L o s s = B × exp ( - E a R T ) ( A h ) z - - - ( 3 )
In formula B be the preceding paragraph factor, EaFor reaction activity, T for set of cells place environment thermodynamic temperature, R is gas constant, z For energy equation factor;
When at set of cells place, thermodynamic temperature T of environment is 298K, preceding paragraph factor B is with the relation between discharge-rate C_Rate Expression formula:
B = - 22000 3 C _ R a t e + 101900 3 - - - ( 4 ) .
7. a kind of electric automobile power battery participation power system frequency modulation for considering battery life according to claim 6 is built Mould method, it is characterised in that electric automobile power battery is calculated in the step 4 and participates in the capacitance loss and most after frequency modulation The detailed process of big energy excursion is:
The electric automobile power battery power curve obtained in step one is integrated through integrator, electric automobile is obtained and is moved Power energy content of battery change curve, according to energy curves ceiling capacity skew is obtained;Energy curves are input to into battery Life consumption model, calculates electric automobile power battery and participates in the appearance after power system frequency modulation according to formula (2) to formula (4) Amount loss.
CN201610895474.6A 2016-10-13 2016-10-13 A kind of electric automobile power battery participation electric system frequency modulation modeling method considering battery life Active CN106649962B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201610895474.6A CN106649962B (en) 2016-10-13 2016-10-13 A kind of electric automobile power battery participation electric system frequency modulation modeling method considering battery life

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201610895474.6A CN106649962B (en) 2016-10-13 2016-10-13 A kind of electric automobile power battery participation electric system frequency modulation modeling method considering battery life

Publications (2)

Publication Number Publication Date
CN106649962A true CN106649962A (en) 2017-05-10
CN106649962B CN106649962B (en) 2019-11-05

Family

ID=58855939

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201610895474.6A Active CN106649962B (en) 2016-10-13 2016-10-13 A kind of electric automobile power battery participation electric system frequency modulation modeling method considering battery life

Country Status (1)

Country Link
CN (1) CN106649962B (en)

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107480848A (en) * 2017-06-26 2017-12-15 清华大学 A kind of scale electric automobile converges the appraisal procedure of equivalent energy storage capacity
CN108879734A (en) * 2018-08-20 2018-11-23 哈尔滨工业大学 A kind of electric automobile super capacitor, battery energy source frequency-division section participate in power grid frequency modulation method
CN109713696A (en) * 2018-11-09 2019-05-03 杭州电子科技大学 Consider the electric car photovoltaic charge station Optimization Scheduling of user behavior
CN111965547A (en) * 2020-09-27 2020-11-20 哈尔滨工业大学(威海) Battery system sensor fault diagnosis method based on parameter identification method
CN111993914A (en) * 2019-05-10 2020-11-27 通用汽车环球科技运作有限责任公司 Intelligent motor vehicle, charging system and control logic for managing vehicle grid integrated operation
CN112014736A (en) * 2020-08-21 2020-12-01 中国第一汽车股份有限公司 Battery life prediction method, device, equipment and storage medium
WO2021143482A1 (en) * 2020-01-16 2021-07-22 郑州宇通客车股份有限公司 Soh test method and apparatus

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103065199A (en) * 2012-12-18 2013-04-24 广东电网公司电力科学研究院 Electric vehicle charging station load forecasting method
CN103954913A (en) * 2014-05-05 2014-07-30 哈尔滨工业大学深圳研究生院 Predication method of electric vehicle power battery service life
CN105356459A (en) * 2015-11-23 2016-02-24 东南大学 A control method for allowing electric automobiles to participate in power system frequency modulation in a scattered grid-access manner
CN105826934A (en) * 2016-04-27 2016-08-03 中国电力科学研究院 Method for controlling auxiliary frequency modulation of electric vehicle based on feasible region
US20160233679A1 (en) * 2013-10-18 2016-08-11 State Grid Corporation Of China A method and system for control of smoothing the energy storage in wind phtovolatic power fluctuation based on changing rate

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103065199A (en) * 2012-12-18 2013-04-24 广东电网公司电力科学研究院 Electric vehicle charging station load forecasting method
US20160233679A1 (en) * 2013-10-18 2016-08-11 State Grid Corporation Of China A method and system for control of smoothing the energy storage in wind phtovolatic power fluctuation based on changing rate
CN103954913A (en) * 2014-05-05 2014-07-30 哈尔滨工业大学深圳研究生院 Predication method of electric vehicle power battery service life
CN105356459A (en) * 2015-11-23 2016-02-24 东南大学 A control method for allowing electric automobiles to participate in power system frequency modulation in a scattered grid-access manner
CN105826934A (en) * 2016-04-27 2016-08-03 中国电力科学研究院 Method for controlling auxiliary frequency modulation of electric vehicle based on feasible region

Cited By (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107480848A (en) * 2017-06-26 2017-12-15 清华大学 A kind of scale electric automobile converges the appraisal procedure of equivalent energy storage capacity
CN108879734A (en) * 2018-08-20 2018-11-23 哈尔滨工业大学 A kind of electric automobile super capacitor, battery energy source frequency-division section participate in power grid frequency modulation method
CN108879734B (en) * 2018-08-20 2021-07-13 哈尔滨工业大学 Frequency modulation method for electric vehicle super capacitor and battery energy source frequency division participation power grid
CN109713696A (en) * 2018-11-09 2019-05-03 杭州电子科技大学 Consider the electric car photovoltaic charge station Optimization Scheduling of user behavior
CN109713696B (en) * 2018-11-09 2020-09-01 杭州电子科技大学 Electric vehicle photovoltaic charging station optimal scheduling method considering user behaviors
CN111993914A (en) * 2019-05-10 2020-11-27 通用汽车环球科技运作有限责任公司 Intelligent motor vehicle, charging system and control logic for managing vehicle grid integrated operation
CN111993914B (en) * 2019-05-10 2023-11-28 通用汽车环球科技运作有限责任公司 Intelligent motor vehicle, charging system and control logic for managing vehicle grid integrated operation
WO2021143482A1 (en) * 2020-01-16 2021-07-22 郑州宇通客车股份有限公司 Soh test method and apparatus
CN112014736A (en) * 2020-08-21 2020-12-01 中国第一汽车股份有限公司 Battery life prediction method, device, equipment and storage medium
CN111965547A (en) * 2020-09-27 2020-11-20 哈尔滨工业大学(威海) Battery system sensor fault diagnosis method based on parameter identification method
CN111965547B (en) * 2020-09-27 2022-05-13 哈尔滨工业大学(威海) Battery system sensor fault diagnosis method based on parameter identification method

Also Published As

Publication number Publication date
CN106649962B (en) 2019-11-05

Similar Documents

Publication Publication Date Title
CN106649962B (en) A kind of electric automobile power battery participation electric system frequency modulation modeling method considering battery life
Zhang et al. A real-time energy management and speed controller for an electric vehicle powered by a hybrid energy storage system
You et al. Optimal charging schedule for a battery switching station serving electric buses
Ebbesen et al. Battery state-of-health perceptive energy management for hybrid electric vehicles
CN105095611B (en) A kind of electric automobile on highway quick charge station queuing strategy
CN103903090B (en) Electric car charging load distribution method based on user will and out-going rule
Hajimiri et al. A fuzzy energy management strategy for series hybrid electric vehicle with predictive control and durability extension of the battery
CN103213504A (en) Driving range estimation method of electric car
CN103065199A (en) Electric vehicle charging station load forecasting method
CN102331314A (en) Dynamic estimation of cell core temperature by simple external measurements
CN104590247A (en) Hybrid electric vehicle energy conservation predictive control method based on traffic signal lamp information
CN106355290A (en) Electric vehicle charge load prediction method and system based on Markov chain
CN103810539A (en) Optimal capacity configuration method considering availability of power conversion service for electric automobile converter station
CN108016303A (en) Control the apparatus and method of the charging of the battery of hybrid vehicle
Zhang et al. A novel learning-based model predictive control strategy for plug-in hybrid electric vehicle
CN105631163A (en) Electric vehicle power battery energy consumption hardware online simulation method and device
Moura Techniques for battery health conscious power management via electrochemical modeling and optimal control
Farag et al. A comparative study of Li-ion battery models and nonlinear dual estimation strategies
Sheikhan et al. State of charge neural computational models for high energy density batteries in electric vehicles
CN109710882A (en) A kind of orderly charge and discharge load modeling of off-network type micro-capacitance sensor electric car and method for solving based on optimization operation
CN105207243A (en) Battery energy capacity management method for real-time power prediction and correction of wind power plant
Chatterjee et al. Electric Vehicle Modeling in MATLAB and Simulink with SoC &SoE Estimation of a Lithium-ion Battery
CN106407726A (en) Method for selecting electrical access point of electric automobile charging station by considering influence on tidal flow
CN108599267A (en) A kind of Unit Combination dispatching method considering electric vehicle trip correlation
CN114039372B (en) Electric vehicle scheduling method and system participating in power grid partition peak clipping and valley filling

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
TR01 Transfer of patent right

Effective date of registration: 20210115

Address after: Building 9, accelerator, 14955 Zhongyuan Avenue, Songbei District, Harbin City, Heilongjiang Province

Patentee after: INDUSTRIAL TECHNOLOGY Research Institute OF HEILONGJIANG PROVINCE

Address before: 150001 No. 92 West straight street, Nangang District, Heilongjiang, Harbin

Patentee before: HARBIN INSTITUTE OF TECHNOLOGY

TR01 Transfer of patent right
TR01 Transfer of patent right

Effective date of registration: 20211223

Address after: 150000 room 100-40, building 20, innovation and entrepreneurship Plaza, science and technology innovation city, high tech Industrial Development Zone, Harbin, Heilongjiang Province (No. 178, Xiuyue Street)

Patentee after: Harbin Yingyan Technology Co.,Ltd.

Address before: Building 9, accelerator, 14955 Zhongyuan Avenue, Songbei District, Harbin City, Heilongjiang Province

Patentee before: INDUSTRIAL TECHNOLOGY Research Institute OF HEILONGJIANG PROVINCE

TR01 Transfer of patent right