CN113391230B - Calculation method for reducing capacity loss rate in energy storage scene - Google Patents

Calculation method for reducing capacity loss rate in energy storage scene Download PDF

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CN113391230B
CN113391230B CN202110515858.1A CN202110515858A CN113391230B CN 113391230 B CN113391230 B CN 113391230B CN 202110515858 A CN202110515858 A CN 202110515858A CN 113391230 B CN113391230 B CN 113391230B
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祁建程
楼旸
董远云
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Wanke Energy Technology Co ltd
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Abstract

The invention provides a calculation method for reducing the loss tolerance rate in an energy storage scene, which can effectively reduce the loss tolerance rate and improve the service capacity of the whole battery by replacing the battery and recombining the battery. The method can rapidly calculate the capacity which is improved at most after determining the number of the replaced new batteries and exchanging the number of the battery modules, and provides an optimal solution, wherein the optimal solution comprises which battery modules are replaced by the new battery modules and which battery modules are exchanged, so that the capacity consistency of different battery packs is improved.

Description

Calculation method for reducing loss tolerance rate in energy storage scene
Technical Field
The invention belongs to the technical field of energy storage systems, and particularly relates to a calculation method for reducing a loss tolerance rate in an energy storage scene.
Background
In a large energy storage application scenario, as the characteristics of different batteries are not completely consistent, along with the increase of the battery operation time, the capacities, voltages, internal resistances and the like of the different batteries are inconsistent. Inconsistent batteries are used in series, and problems of capacity loss, service life loss, internal resistance loss and the like can occur.
Disclosure of Invention
The invention aims to solve the technical problems and provides a calculation method for reducing the loss tolerance rate in an energy storage scene.
The battery cell monomers form a battery pack, the capacity accords with the wooden barrel principle, and the capacity of the worst battery cell determines the capacity of the whole battery pack. To prevent the battery from being overcharged and overdischarged, the logic of the battery management system is set as follows: during discharging, when the lowest monomer voltage reaches a discharge cut-off voltage, the whole battery pack stops discharging; in the charging, when the highest cell voltage reaches the charge cut-off voltage, the charging is stopped. Example with two cells in series: one cell has a capacity of C, and the other has a capacity of only 0.9C. Due to the series relationship, both cells pass the same amount of current. During charging, the battery with small capacity is always fully charged first, so that the charging cut-off condition is reached, and the system does not continue to charge. During discharging, the battery with small capacity inevitably discharges all available energy, and the system stops discharging immediately. Therefore, the battery cell with small capacity is fully charged all the time, the battery cell with large capacity uses part of the capacity all the time, and one part of the capacity of the whole battery pack is in an idle state.
Assuming that the sum of the capacities of the battery cells is S1, and the full charge capacity of the battery pack is S2 due to the inconsistency, the loss tolerance R is S1/S2. Through setting up and changing new battery and change battery quantity, we can try to get fast, which battery module's needs are replaced, which battery module needs the change position, and what capacity is promoted to holistic energy unit, reduces what capacity loss rate.
The invention provides a calculation method for reducing the capacity loss rate in an energy storage scene, which comprises the following steps of inputting the number m of battery packs to be exchanged, solving which battery packs need to be exchanged and what the whole capacity of a battery pack is improved by:
step one, establishing a capacity matrix, a number matrix and a category vector of an energy unit:
battery pack capacity matrix
Figure GDA0003699681970000011
Each row is a battery pack, if two battery packs are connected in parallel and the end of charging and discharging is influenced by the same common short plate battery, the two battery packs are combined into one battery pack, c ij Is the actual capacity of the jth battery pack of the ith battery pack;
battery pack numbering matrix
Figure GDA0003699681970000021
a ij Is the number of the jth battery pack of the ith battery pack;
battery pack class vector PT ═ b 1 b 2 ... b k ];
b i E {0,1}, when b i 0, then is type A, b i When the compound is 1, the compound is B type;
step two, calculating the capacity of the reference battery pack:
selecting a reference battery pack p to find the minimum batteryCapacity Battery pack min (c) pj ) Calculating the battery capacity c p The minimum pack capacity multiplied by the number of packs:
c p =min(c pj )*k;
step three, calculating the capacity of the target battery pack:
selecting another target to exchange the battery pack q, and finding out the battery pack max (c) which is the same as the AB model of the battery pack with the minimum battery capacity of the battery pack p and has the maximum battery capacity pj ) Calculating the capacity variation Delta c of the battery pack q after the battery pack is replaced q
Δc q =min(c' qj )*k-min(c qj )*k;
Wherein c' qj The capacity of different battery packs of the new battery pack after the battery pack is exchanged;
step four, calculating the capacity variation of the reference battery pack:
calculating the capacity variation Delta c of the exchange battery pack of the battery pack p p
Δc p =min(c' pj )*k-min(c pj )*k;
Step five, calculating the capacity variation of the energy unit:
calculating the capacity variation Delta c of the whole energy unit after exchanging the battery pack pq
Δc pq =Δc p +Δc q
Step six, calculating the capacity improvement amount of all combinations:
traversing the combinations of all the reference battery packs and the target battery packs in sequence, calculating the capacity variation of the energy units of all the combinations, selecting the combination with the largest lifting amount for exchanging, and if the variation of a plurality of combinations is lifted to be the same, turning to the step seven;
step seven, the combination selection with the same capacity lifting amount:
if the variation of a plurality of combinations is improved the same, calculating the standard deviation reduction of each combination, and selecting the combination with the maximum reduction:
Δs pq =Δs p +Δs q =(s p -s' p )+(s q -s' q );
Figure GDA0003699681970000031
wherein s is p ,s q Is the capacity standard deviation, s 'of the battery packs p, q' p 、s' q For the capacity standard deviation, Δ s, of the transposed battery packs p, q pq The reduction amount of the standard deviation of the battery packs p and q after the battery packs are exchanged;
step eight, calculating the number of the exchanged battery packs:
comparing the position difference quantity of the battery packs of the exchanged battery monomer number matrix and the original number matrix, and stopping iteration if the difference quantity is greater than the quantity of the battery packs to be exchanged; if the number matrix of the exchanged single batteries is the same as that of the previous iteration, stopping the iteration; otherwise, the next iteration is continued.
After the technical scheme is adopted, the invention has the following advantages:
according to the calculation method for reducing the loss tolerance rate in the energy storage scene, the loss tolerance rate can be effectively reduced and the use capacity of the whole battery is improved by replacing the battery and recombining the battery. The method can rapidly calculate the capacity which is improved at most after determining the number of the replaced new batteries and exchanging the number of the battery modules, and provides an optimal solution, wherein the optimal solution comprises which battery modules are replaced by the new battery modules and which battery modules are exchanged, so that the capacity consistency of different battery packs is improved.
Detailed Description
The present invention will be described in further detail with reference to specific examples.
The battery cell monomers form a battery pack, the capacity accords with the wooden barrel principle, and the capacity of the worst battery cell determines the capacity of the whole battery pack. To prevent the battery from being overcharged and overdischarged, the logic of the battery management system is set as follows: during discharging, when the lowest monomer voltage reaches a discharge cut-off voltage, the whole battery pack stops discharging; in the charging, when the highest cell voltage reaches the charge cut-off voltage, the charging is stopped. Example with two cells in series: one cell has a capacity of C, and the other has a capacity of only 0.9C. Due to the series relationship, both cells pass the same amount of current. During charging, the battery with small capacity is always fully charged first, so that the charging cut-off condition is reached, and the system does not continue to charge. During discharging, the battery with small capacity inevitably discharges all available energy, and the system stops discharging immediately. Therefore, the battery cell with small capacity is fully charged all the time, the battery cell with large capacity uses part of the capacity all the time, and one part of the capacity of the whole battery pack is in an idle state.
Assuming that the sum of the capacities of the battery cells is S1, and the full charge capacity of the battery pack is S2 due to the inconsistency, the loss tolerance R is S1/S2. Through setting up and changing new battery and change battery quantity, we can try to get fast, which battery module's needs are replaced, which battery module needs the change position, and what capacity is promoted to holistic energy unit, reduces what capacity loss rate.
The invention provides a calculation method for reducing the capacity loss rate in an energy storage scene, which comprises the following steps of inputting the number m of battery packs to be exchanged, solving which battery packs need to be exchanged and what the whole capacity of a battery pack is improved by:
step one, establishing a capacity matrix, a number matrix and a category vector of an energy unit:
battery pack capacity matrix
Figure GDA0003699681970000041
Each row is a battery pack, and if two battery packs are connected in parallel and the end of charging and discharging is affected by the same common short plate battery, the two battery packs are combined into one battery pack, c ij Is the actual capacity of the jth battery pack of the ith battery pack;
battery pack numbering matrix
Figure GDA0003699681970000042
a ij Is the number of the jth battery pack of the ith battery pack;
battery pack class vector PT ═ b 1 b 2 ... b k ];
b i E {0,1}, when b i 0, then is type A, b i When the compound is 1, the compound is B type;
step two, calculating the capacity of the reference battery pack:
selecting a reference battery pack p to find a minimum battery capacity pack min (c) pj ) Calculating the battery capacity c p The minimum pack capacity multiplied by the number of packs:
c p =min(c pj )*k;
step three, calculating the capacity of the target battery pack:
selecting another target to exchange the battery pack q, and finding out the battery pack max (c) with the same AB type as the battery pack with the minimum battery capacity of the battery pack p and the maximum battery capacity pj ) Calculating the capacity variation Delta c of the battery pack q after the battery pack is replaced q
Δc q =min(c' qj )*k-min(c qj )*k;
Wherein c' qj The capacity of different battery packs of the new battery pack after the battery pack is exchanged;
step four, calculating the capacity variation of the reference battery pack:
calculating the capacity variation Delta c of the exchange battery pack of the battery pack p p
Δc p =min(c' pj )*k-min(c pj )*k;
Step five, calculating the capacity variation of the energy unit:
calculating the capacity variation Delta c of the whole energy unit after exchanging the battery pack pq
Δc pq =Δc p +Δc q
Step six, calculating the capacity improvement amount of all combinations:
traversing the combinations of all the reference battery packs and the target battery packs in sequence, calculating the capacity variation of the energy units of all the combinations, selecting the combination with the largest lifting amount for exchanging, and if the variation of a plurality of combinations is lifted to be the same, turning to the step seven;
step seven, the combination selection with the same capacity lifting amount:
if the variation of a plurality of combinations is improved the same, calculating the standard deviation reduction of each combination, and selecting the combination with the maximum reduction:
Δs pq =Δs p +Δs q =(s p -s' p )+(s q -s' q );
Figure GDA0003699681970000051
wherein s is p ,s q Is the capacity standard deviation, s 'of the battery packs p, q' p 、s' q For the capacity standard deviation, Δ s, of the transposed battery packs p, q pq The reduction amount of the standard deviation of the battery packs p and q after the battery packs are exchanged;
step eight, calculating the number of the exchanged battery packs:
comparing the position difference quantity of the battery packs of the exchanged battery monomer number matrix and the original number matrix, and stopping iteration if the difference quantity is greater than the quantity of the battery packs to be exchanged; if the number matrix of the exchanged single batteries is the same as that of the previous iteration, stopping the iteration; otherwise, the next iteration is continued.
The following are specific examples:
initial capacity matrix of each battery pack:
Figure GDA0003699681970000052
battery pack number matrix for each battery pack:
Figure GDA0003699681970000061
first round of traversal
1.1
Finding the highest capacity boost from both combinations
Battery pack No. 6 of battery pack 2 is exchanged with battery pack No. 5 of battery pack 1, and the capacity increase amount of battery pack 2:
Δc 2 =4*5-2*5=10;
capacity increase amount of battery 1:
Δc 1 =2*5-2*5=0;
the overall capacity improvement is as follows:
Δc 21 =Δc 2 -Δc 1 =10-0=10;
it was found that battery pack No. 11 of battery pack 3 was exchanged with battery pack No. 5 of battery pack 1, and the overall capacity boost was also 10.
1.2 calculate the amount of standard deviation reduction for both combinations
Reduction in standard deviation of battery packs 2 and 1:
Δs 21 =(s 2 -s' 2 )+(s 1 -s' 1 )=(1.28-0.88)+(1.2-1.04)=0.4+0.16=0.56;
reduction in standard deviation of battery packs 3 and 1:
Δs 31 =(s 3 -s' 3 )+(s 1 -s' 1 )=(1.04-0.64)+(1.2-0.88)=0.4+0.32=0.72;
1.3 Battery capacity and numbering after swapping
This combination is selected because the standard deviation improvement degree of the exchange of the battery packs 3 and 1 is high.
After the first round of traversal, the capacity of each battery pack:
Figure GDA0003699681970000062
battery pack number of each battery pack:
Figure GDA0003699681970000071
second round of traversal
Capacity improvement of No. 6 battery pack exchange of battery pack 2 and No. 4 battery pack exchange of battery pack 1:
Δc 21 =Δc 2 -Δc 1 =(4*5-2*5)+(2*5-2*5)=10-0=10;
battery capacity after exchange, capacity of each battery pack:
Figure GDA0003699681970000072
battery pack number of each battery pack:
Figure GDA0003699681970000073
the final result is: the overall capacity is increased by (2+4+5+3) × 5- (2+2+3+3) × 5 ═ 20.
The number of the exchanged battery packs is 4, and the battery packs are respectively No. 4, No. 5, No. 6 and No. 11.
Other embodiments of the present invention than the preferred embodiments described above will be apparent to those skilled in the art from the present invention, and various changes and modifications can be made therein without departing from the spirit of the present invention as defined in the appended claims.

Claims (3)

1. A calculation method for reducing the loss tolerance rate in an energy storage scene is characterized by comprising the following steps:
step one, establishing a capacity matrix, a number matrix and a category vector of an energy unit:
battery pack capacity matrix
Figure FDA0003699681960000011
Each row is a battery pack, and if two battery packs are connected in parallel and the end of charging and discharging is affected by the same common short plate battery, the two battery packs are combined into one battery pack, c ij Is the actual capacity of the jth battery pack of the ith battery pack;
battery pack numbering matrix
Figure FDA0003699681960000012
a ij Is the number of the jth battery pack of the ith battery pack;
step two, calculating the capacity of the reference battery pack:
selecting a reference battery pack p to find a minimum battery capacity pack min (c) pj ) Calculating the battery capacity c p The minimum pack capacity multiplied by the number of packs:
c p =min(c pj )*k;
step three, calculating the capacity of the target battery pack:
another target is selected to exchange the battery pack q, and the battery pack max (c) with the maximum battery capacity of the battery pack p is found out pj ) Calculating the capacity variation Delta c of the battery pack q after the replacement of the battery pack q
Δc q =min(c' qj )*k-min(c qj )*k;
Wherein c' qj The capacity of different battery packs of the new battery pack after the battery pack is exchanged;
step four, calculating the capacity variation of the reference battery pack:
calculating the capacity variation Delta c of the exchange battery pack of the battery pack p p
Δc p =min(c' pj )*k-min(c pj )*k;
Step five, calculating the capacity variation of the energy unit:
calculating the capacity variation Delta c of the whole energy unit after exchanging the battery pack pq
Δc pq =Δc p +Δc q
Step six, calculating the capacity improvement amount of all combinations:
traversing all combinations of the reference battery packs and the target battery packs in sequence, calculating the capacity variation of the energy units of all the combinations, selecting the combination with the largest lifting amount for exchanging, and turning to the seventh step if the variation of the combinations is lifted to be the same;
step seven, the combination selection with the same capacity lifting amount:
if the variation of a plurality of combinations is improved the same, calculating the standard deviation reduction of each combination, and selecting the combination with the maximum reduction:
Δs pq =Δs p +Δs q =(s p -s' p )+(s q -s' q );
Figure FDA0003699681960000021
wherein s is p ,s q Is the capacity standard deviation, s 'of the battery packs p, q' p 、s' q For the capacity standard deviation, Δ s, of the transposed battery packs p, q pq The reduction amount of the standard deviation of the battery packs p and q after the battery packs are exchanged;
step eight, calculating the number of the exchanged battery packs:
comparing the position difference quantity of the battery packs of the exchanged battery monomer number matrix and the original number matrix, and stopping iteration if the difference quantity is greater than the quantity of the battery packs to be exchanged; and if the number matrix of the exchanged single batteries is the same as that of the previous iteration, stopping the iteration, and otherwise, continuing the next iteration.
2. The method for calculating the loss tolerance reduction rate in the energy storage scene according to claim 1, wherein the charging and discharging method of the battery pack is as follows: during discharging, when the lowest monomer voltage reaches a discharge cut-off voltage, the whole battery pack stops discharging; in the charging, when the highest cell voltage reaches the charge cut-off voltage, the charging is stopped.
3. The method for calculating the reduction tolerance rate in the energy storage scene according to claim 1,
the first step further comprises the following steps: establishing a category vector of energy units:
battery pack class vector PT ═ b 1 b 2 ... b k ];
b i E {0,1}, when b i 0, then is type A,b i When the compound is 1, the compound is B type;
step three, battery pack max (c) pj ) The same as the AB model of the minimum cell capacity pack of battery pack p.
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