CN115208026A

CN115208026A - Active energy balancing method for source-load separation between battery packs

Info

Publication number: CN115208026A
Application number: CN202210931644.7A
Authority: CN
Inventors: 张云; 魏逸航; 朱新山
Original assignee: Tianjin University
Current assignee: Tianjin University
Priority date: 2022-08-10
Filing date: 2022-08-10
Publication date: 2022-10-18

Abstract

The invention relates to an active energy balancing method for source-charge separation among battery packs, and belongs to the field of power electronics. In the prior art, most of the balancing topologies and balancing control methods can only balance adjacent batteries, and have the problems of fixed balancing current, low balancing speed, low efficiency and the like. The method of the invention connects the battery pack by the proposed balanced topology structure, and improves the effect of electric quantity balance by a source-load separation active energy balance method based on fuzzy control and optimized droop control. When the SOC difference between the battery packs reaches the set threshold value, the method can automatically judge the balance parameters such as the balance mode, the balance current and the like, so that the energy can be balanced between any two battery packs, and the magnitude of the balance current can be determined according to the state of the battery pack, thereby controlling the balance speed and greatly improving the flexibility, balance speed and efficiency of the SOC balance of the battery pack.

Description

Active energy balancing method for source-load separation among battery packs

Technical Field

The invention belongs to the technical field of power electronics, and particularly relates to an active energy balancing method for source-load separation among battery packs.

Background

With the rapid development of society, the demand for energy in social life and various industrial fields is also increasing. The storage battery is used as a portable, clean and pollution-free energy source and is widely applied to the fields of energy storage systems of smart power grids, direct current micro-grids (DC micro-grids), electric automobiles, new energy unmanned aerial vehicles and the like. The single storage battery has the problems of low voltage and small capacity, and a plurality of single batteries are required to be connected in series or in parallel to meet different requirements. However, in practical use, due to the difference between the batteries and various external factors, the battery pack has a problem of inconsistent state of charge (SOC), which further affects the performance of the energy system, and in other energy systems, the storage battery pack needs to maintain similar electric quantity or perform specific energy exchange. In the foregoing application of the storage battery pack, for example, in a power supply system of a new energy unmanned aerial vehicle, when a plurality of storage battery packs are used, if a certain battery pack is out of operation due to imbalance of the SOC, a load carried by the unmanned aerial vehicle and normal operation thereof are seriously affected. The SOC dynamic real-time balance among the battery packs plays a vital role in maintaining the stable operation of the whole energy system, so that the flexibility, the stability, the balance speed and the efficiency of the SOC balance control strategy of the battery pack are very necessary to be improved.

Yan Ma et al, based on the proposed intra-group and inter-group two-stage equalization topologies, obtain the equalization current between two adjacent modules or monomers by fuzzy control [ Yan Ma et al, equalization of lithium-ion battery based on fuzzy control in electric field. However, the method can only interact energy between two adjacent modules or single cells to achieve overall energy balance, and cannot enable the energy to directly interact between any two battery packs, so that the problem of low balance efficiency exists in some cases. Xianonan Lu et al adopts an SOC-based adaptive droop control method to perform energy interaction and power distribution in a distributed energy storage system [ Xianonan Lu et al. State-of-charge balance using adaptive droop control for distributed energy storage systems in DC micro-logical applications. IEEE Trans. Ind Electron, jun.2014,61 (6): 2804-2815]. Although the droop coefficient can be dynamically adjusted according to the SOC condition by the method, the droop coefficient is inversely proportional to the n-th order of the SOC, a proper n is selected to achieve a more ideal effect, and unreasonable droop coefficients are easily generated under certain conditions. Thomas Morstyn et al utilize a multi-agent sliding mode control for a state of charge between distributed DC microgrid battery energy storage systems [ Thomas Morstyn et al, multi-agent sliding mode control for a state of charge between distributed DC microgrid battery energy storage systems distributed between devices in DC microrid. IEEE transformations on Smart grid, sept.2018,9 (5): 4735-4743]. However, the method has the characteristic that the battery energy storage system is either completely charged or completely discharged, and has limitation. Khan Duc Hoang et al propose a virtual rated power concept, and realize accurate power distribution of distributed battery energy units in a direct current microgrid according to an SOC level and the virtual rated power, so as to realize battery pack SOC balance [ khan Duc Hoang et al. It does not focus on direct energy exchange between battery packs to achieve energy balance. In addition, many balancing topologies and methods based on bidirectional direct current converters (DC-DC bidirectional converters) are proposed in succession.

Although the aforementioned method has been verified through simulation or experiment, there are a series of disadvantages that energy can only interact between two adjacent modules or single units, equalization parameter adjustment is not easy, direct equalization cannot be performed in island mode, equalization mode is single, equalization efficiency is low, and practicability of the method is not considered. Therefore, the existing inter-battery-group energy balance control methods are less adopted in practice, which means that it is necessary to research the inter-battery-group energy balance control methods with more flexibility and higher efficiency.

Disclosure of Invention

Aiming at the defects in the prior art, the invention aims to provide an active energy balancing method for separating the source and the charge of battery packs, which can automatically judge parameters such as a balancing mode, balancing current and the like when the SOC of the battery packs has certain difference, dynamically control the energy balancing speed of any battery pack and improve the flexibility, the balancing speed and the efficiency of the SOC balance of a battery pack.

In order to achieve the above purposes, the invention adopts the technical scheme that: an active energy balancing method for source-load separation among battery packs. On the basis that a DC-DC bidirectional converter is used for balancing a topology hardware platform to be connected with a battery pack, active energy balancing between the battery packs is carried out; after source-load separation and equalization mode judgment are carried out according to the characteristics of the equalization topology, a load side (energy absorption side) equalization current and a source side (energy output side) droop coefficient are obtained by utilizing fuzzy control, and energy equalization is carried out by combining optimization droop control, and the method comprises the following steps of:

(1) Estimating the electric quantity of each phase of battery pack, dividing each phase of battery pack into a source side (output energy side) and a charge side (absorption energy side) by using a source-charge separation method, wherein the corresponding converters are a source side converter and a charge side converter respectively;

(2) Judging whether the battery packs of all phases are balanced or not by adopting a multi-valued balancing strategy;

(3) Adopting fuzzy control and optimizing droop control method, after starting equalization, calculating equalization current I of each load side by using fuzzy control _{equ_i} Determining the total load current on the bus, and calculating the Droop coefficient Droop of the source side by using fuzzy control _i Performing power distribution on each source side by combining with optimized droop control, so that the source side transmits energy to the load side to perform energy balance;

(4) In the process of battery equalization, the equalization mode and the load-side equalization current I are dynamically updated according to the battery state _{equ_i} And the source side Droop coefficient Droop _i 。

Further, the DC-DC bidirectional converter balancing topological structure is a structure with a high-voltage side sharing a direct current bus, any number of battery packs are respectively connected to the low-voltage sides of the same number of converters, the high-voltage sides of the converters are connected in parallel to establish an internal balancing bus, and no other load exists on the internal balancing bus.

Further, the source-load separation method comprises the following steps: utilizing the electric quantity SOC of each phase battery pack _i Calculating the average value SOC of all the battery packs _avg Maximum value SOC _max Minimum value SOC _min Delta SOC _max SOC of each-phase battery pack _i And SOC _avg Difference value Δ SOC of _i According to Δ SOC _i Positive and negative of (1) determines whether each phase battery pack is controlled to be on the source side or the load side, delta SOC _i The phase battery pack is a positive value and is controlled to be a source side; delta SOC _i In negative value, the phase battery pack is controlled to be on the charge side.

Further, the multi-valued equalization strategy is: for delta SOC _i Setting different opening and closing balance thresholds, and if the threshold conditions are met, opening or closing balance of the phase battery pack is realized; for delta SOC _max Set to open and closeAnd (4) balancing a threshold value, wherein if the threshold value condition is met, the maximum electric quantity and the minimum electric quantity of the battery pack are balanced in opening or closing.

Further, the fuzzy control and optimized droop control method comprises the following steps: after starting balance, the SOC is charged to the load side _i And Δ SOC _i As the input of a lotus-side fuzzy controller, the lotus-side equalizing current I is obtained according to the established lotus-side fuzzy rule _{equ_i} (ii) a To the source side, the SOC _i And Δ SOC _i The source side droop coefficient drooping is obtained as an input of the source side fuzzy controller according to a formulated source side fuzzy rule. A balanced internal bus voltage correction link is added in a source side droop control link, the input of the link is the difference value of a bus voltage given value and an actual value, proportional-integral control is adopted, the output is a bus voltage corrected value, and the bus voltage given value can be changed.

Further, in the balancing process, the state of the battery pack is updated in real time, and the balancing mode judgment and the load side balancing current I are carried out again according to the battery state at each time _{equ_i} Calculation and update of the source side droop coefficient droopin.

The invention has the following effects: by adopting the method, the energy balance between any two battery packs can be realized, and the balance flexibility is greatly enhanced; the charge side equalizing charge current and the source side droop coefficient are dynamically adjusted by fuzzy control so as to carry out reasonable power distribution, namely the equalizing current is controllable, and the overcharge and over-discharge of the battery are avoided; the balance speed and the energy transfer efficiency are greatly improved; the stability of an internal direct current bus is maintained through a bus correction link, and bus voltage fluctuation caused by droop control is eliminated; in conclusion, by adopting the method of the invention, when the SOC difference between the battery packs reaches the set threshold value, parameters such as the equalization mode, the equalization current and the like can be automatically judged, the energy equalization speed between any battery packs can be dynamically controlled, and the flexibility, the equalization speed and the efficiency of the SOC equalization between the battery packs are greatly improved.

Drawings

FIG. 1 is a flow chart of the overall control of source-to-charge separation active energy balance among battery packs;

FIG. 2 is a block diagram of a source-to-charge separation active energy balance control;

FIG. 3 is a block diagram of an inter-group equalization circuit topology based on a DC-DC bi-directional converter;

FIG. 4 is a block diagram of inter-group balanced charge-side fuzzy logic control;

FIG. 5 is a membership function of input and output at the load side;

FIG. 6 is a table of side-of-lotus fuzzy rules;

FIG. 7 is a block diagram of inter-group equalization source side fuzzy logic control;

FIG. 8 is a source side input-output membership function;

FIG. 9 is a source-side fuzzy rule table;

FIG. 10 is a setting variation diagram of the SOC state;

FIG. 11 is a graph of energy balance parameter variation using the present method;

FIG. 12 shows the results of an inter-group energy balance experiment using this method.

Detailed Description

The following description will explain embodiments of the present invention in further detail with reference to the accompanying drawings.

The invention designs an active energy balancing method for source-load separation among battery packs, which is characterized in that on the basis of connecting batteries by using the balanced topological structure, source-load separation and mode judgment are performed through more reasonable balanced control, the balanced mode parameters are determined according to the SOC change of the battery packs by utilizing fuzzy control and optimized droop control, a bus compensation link is added, and the flexibility, balanced speed and efficiency of SOC balance of the battery packs are improved. Fig. 1 is an overall control flow chart of the present invention, and fig. 2 is a control block diagram of the present invention.

The method comprises the following concrete implementation steps:

firstly, connecting 4 48V battery packs to the low-voltage side of a Buck/Boost bidirectional converter according to a balanced topology, and connecting the high-voltage side of the converter in parallel to a common internal balanced direct-current bus, as shown in FIG. 3. Obtaining the low-voltage side voltage U of each phase by sampling hardware of each phase _{Low_i} Low side current I _{Low_i} High side current I _{High_i} And a common internal bus voltage U _dc 。

And (4) performing SOC estimation of each-phase battery pack based on an OCV-AH method by using voltage and current data acquired by hardware circuit sampling. And (4) calculating important parameters, and separating the source and the load according to the important parameters, wherein the specific implementation details are as follows.

Acquiring the voltage U of the low-voltage side battery pack before the system does not start to balance _{Low_i} Before the system is not operated, the open-circuit voltage of the battery can be regarded as the open-circuit voltage of the battery, and therefore the initial value SOC of the battery pack electric quantity of each phase is determined through the OCV-SOC curve of the battery _{0_i} 。

After the initial value of the SOC is obtained, real-time ampere-hour integration is carried out, but the influence of factors such as temperature and charge-discharge efficiency on the estimation of the residual electric quantity is not considered in the traditional ampere-hour integration method, so that the accuracy of the SOC estimation is not high. The invention is optimized to a certain extent, compensates the temperature and the charge-discharge efficiency coefficient in the calculation, and can further improve the estimation precision of the SOC.

The charging and discharging conditions of the battery are different at different temperatures, so the influence of the temperature on the SOC estimation is not negligible. The temperature compensation formula commonly used at present is as follows.

η _T ＝1+0.008(T _N -T) (1)

Wherein, T _N Refers to a standard temperature of 20 deg.c and T refers to the current temperature value.

The current of the battery can be greatly changed under different working states, and the charging and discharging efficiency of the battery is influenced. If the influence of the charge-discharge efficiency of the battery is not considered, the accumulated error of the SOC is larger and larger, and the estimation result is inaccurate. The relationship between the available electric quantity and the discharge current is as follows.

Q＝A*I ^n-1 (2)

Where I represents the discharge current, n refers to the structural constant of the cell (typically 1.15-1.42), where 1.2 is taken and a is the cell constant associated with the active material. Under the condition of the same initial condition, the values of A and n are the same and are also 1.2, so that the charge-discharge efficiency can be obtained as the following formula.

Wherein, I _N At rated current, Q _N Is rated capacity.

The corrected SOC mathematical model is established through the analysis

Wherein, SOC _{0_i} The initial value of the electric quantity before the discharge of the ith battery pack is referred to; eta _T Represents a temperature compensation coefficient; eta _i The charge-discharge efficiency compensation coefficient of the ith battery pack is represented; I.C. A _{Low_i} (t) refers to the ith battery pack charge-discharge current as a function of time t; q _{0_i} The capacity before discharging the ith battery pack.

Calculating the average value, the maximum value, the minimum value, the range and the SOC of each phase of the electric quantity _i The difference from the average value (average deviation value) is as follows.

SOC _max ＝MAX{SOC ₁ ,SOC ₂ ,…SOC _i …,SOC _N } (6)

SOC _min ＝MIN{SOC ₁ ,SOC ₂ ,…SOC _i …,SOC _N } (7)

ΔSOC _max ＝SOC _max -SOC _min (8)

ΔSOC _i ＝SOC _i -SOC _avg (9)

Wherein N refers to the number of battery packs. And dynamically ranking the electric quantity of each battery pack, and dividing each battery pack into a source side and a load side by using a source-load separation method, wherein the detailed process is as follows.

The condition for judging the ith phase battery pack as the "charged" side is

ΔSOC _i ≤0 (10)

The condition for determining the i-th phase battery pack as the "source" side is

ΔSOC _i ＞0 (11)

Step two, adopting a multi-value equalization strategy of 'average deviation value + extreme value + multi-threshold' according to delta SOC _i And Δ SOC _max Whether each phase starts equalization is judged, and the detailed process is as follows.

After the load side and the source side are separated, the condition for starting equalization on the ith phase battery pack is that

|ΔSOC _i |≥λ ₁ (12)

Wherein λ is ₁ To turn on the equalization threshold, we take 3 here.

The condition for closing the equalization for the ith phase battery pack is

|ΔSOC _i |≤λ ₂ (13)

Wherein λ is ₂ To turn off the equalization threshold, 1 is taken here.

The balancing problem of the battery with the maximum electric quantity and the battery with the minimum electric quantity is additionally considered, namely the condition of judging to start balancing by extreme difference is

|ΔSOC _max |≥λ ₃ (14)

The condition for judging the balance to be closed by the range is

|ΔSOC _max |≤λ ₃ (15)

Wherein λ is ₃ The equalization thresholds for the very bad decision to turn on and off are taken to be 4 here. And if the conditions are met, correspondingly opening and closing the battery with the maximum electric quantity and the battery with the minimum electric quantity for balancing.

And step three, carrying out energy balance by combining fuzzy control with an optimized droop control method, wherein the specific implementation details are as follows.

For the load side, after the equalization is started, the SOC is set _i And Δ SOC _i As input of the charge-side fuzzy controller, the output is the phase equilibrium current I _{equ_i} As shown in fig. 4. The lotus side model paste controller converts the accurate input into a fuzzy variable, and the fuzzy variable is processed and pushed by a formulated lotus side model paste rule baseThe results of the processing engine are converted to accurate outputs by the deblurring unit, which is implemented in detail as follows.

Input quantity SOC _i And Δ SOC _i Are set to (0, 100%) and (0, 70%), respectively, the transformed fuzzy variables are divided into 5 fuzzy subsets: very Small (VS), small (S), medium (M), large (L), very Large (VL), output I _{equ_i} Is set to (0, 3) according to the reasonable current range, the fuzzy variable corresponding to the interval is also divided into five subintervals: very Small (VS), small (S), medium (M), large (L), very Large (VL).

The membership function selects a triangular fuzzy membership function, and the membership function of input and output quantities at the load side is shown in FIG. 5.

A charge-side fuzzy rule table is established according to the charge and discharge data and experience of the battery, as shown in fig. 6.

Obtaining the balance current I by a gravity center centroid deblurring method for fuzzy output _{equ_i} The expression is

Will equalize the current I _{equ_i} As a given current, the load side is controlled to be in a current source mode through single current loop control of the bidirectional DC-DC converter.

For the source side, after equalization is started, the SOC is set _i And Δ SOC _i As input of the source side fuzzy controller, the output is the Droop coefficient Droop _i As shown in fig. 7. The source side fuzzy controller converts the precise input into fuzzy variable, and uses the established source side fuzzy rule base to make processing, and the result of inference engine is converted into precise output by the defuzzifier, and its detailed implementing process is as follows.

Input quantity SOC _i And Δ SOC _i Are set to (0, 100%) and (0, 70%), respectively, the transformed fuzzy variables are divided into 5 fuzzy subsets: very Small (VS), small (S), medium (M), large (L), very Large (VL), output Droop _i Is set to (1.6, 3) according to the reasonable parameter range of the droop control, and the fuzzy variable corresponding to the intervalDivided into five subintervals: very Small (VS), small (S), medium (M), large (L), very Large (VL).

The membership function selects a triangular fuzzy membership function, and the source side input-output quantity membership function is shown in fig. 8.

The source-side fuzzy rule table is empirically established as shown in fig. 9.

Obtaining the balance current Droop by adopting a gravity center centroid deblurring method for fuzzy output _i The expression is

After the source side droop coefficient is obtained, a bus voltage correction ring is added, and the output of a correction link is a correction voltage U _xiuzheng The droop control circuit is added into a droop control voltage ring, the source side carries out optimized droop control through a bidirectional DC-DC converter, reasonable power distribution is carried out, and all load side required currents are borne.

Step four, dynamically acquiring the battery state in the battery balancing process to obtain the SOC _i 、SOC _avg 、SOC _max 、SOC _min 、ΔSOC _max 、ΔSOC _i And performing source-load separation, balance mode judgment and load-side balance current I again according to the parameters at each time interval _{equ_i} Calculating and Source side Droop coefficient Droop _i The energy balance condition is adjusted in real time until the balance is finished.

In order to show the remarkable effects of the present invention, the present example shows some experimental results obtained by using the examples. Under the condition that the internal equalizing bus voltage is given as 100V, for 4 48V battery packs, first, the SOC state of each current battery pack is manually set, and then, the change in SOC state is set, and the equalization parameter and the equalization state of each battery pack are observed, and the setting change in SOC state is as shown in fig. 10. Fig. 11 shows the automatic equalization parameter change according to the SOC change obtained by the present invention, and fig. 12 shows the experimental result. Fig. 12 shows the low-voltage side currents and the dc bus voltages of the battery packs 1, 2, and 3, and when the equalization threshold is satisfied, each battery pack is in the corresponding equalization mode, and when the SOC of each battery pack changes, the source charge condition changes accordingly, and the energy exchange condition changes from 1 (source) to 3 (charge) to 2 (source) to 2 (charge) and then to 3 (source) to 1 (charge). In addition, the power borne by each phase differs according to the source side droop coefficient, and for example, in the 2-to-2 stage, the output currents of the battery pack 1 and the battery pack 2 serving as sources are 3A and 2.2A respectively. The balance current on the charge side also dynamically changes, as in the case of 3 to 1, the balance current of the battery pack 4 as a charge is 2.59A, and in the case of 2 to 2, the balance current of the battery pack 4 as a charge is 2.09A. Meanwhile, through optimized droop control, the voltage of the internal equalization direct current bus is always maintained at about 100V of a given voltage. As can be seen from fig. 11 and 12, the source load condition, the equalization parameters, and the equalization state can be automatically determined according to the SOC change, and dynamic adjustment can be performed rapidly, so that the equalization between the battery packs is in a reasonable state, and a stable energy equalization state is maintained.

The experimental result obtained in this embodiment can show that when the SOC difference between the battery packs reaches the set threshold value, the method of the present invention can automatically determine parameters such as the equalization mode and the equalization current, and dynamically control the energy equalization speed between any battery packs, thereby greatly improving the flexibility, the equalization speed, and the efficiency of SOC equalization between the battery packs.

The present invention may be embodied in other specific forms without departing from its spirit or essential characteristics. The described embodiments are to be considered in all respects only as illustrative and not restrictive, for example:

1) The non-isolated bidirectional DC-DC topology used in the inter-group balancing topology is not limited to the configuration in the embodiment;

2) The parameters of the battery pack and other related charging and discharging data are not limited to those used in the embodiments;

3) The plurality of thresholds in the equalization mode determination are not limited to those used in the embodiments;

4) The domains, fuzzy subsets, fuzzy rule tables and the like in the fuzzy control are not limited to those used in the embodiment;

5) The equalization parameters such as equalization current, droop factor, etc. are not limited to those used in the embodiments. The scope of the invention is, therefore, indicated by the appended claims rather than by the foregoing description. All changes which come within the meaning and range of equivalency of the claims are to be embraced within their scope.

Claims

1. An active energy balancing method for separating the source and the load among battery packs is characterized in that,

the active energy balancing method is used for carrying out active energy balancing among battery packs on the basis that a DC-DC bidirectional converter is used for balancing a topological hardware platform to connect the battery packs;

the active energy balancing method comprises the following steps of after source-load separation and balancing mode judgment are carried out according to the characteristics of balanced topology, acquiring balanced current on a load side (energy absorption side) and droop coefficients on a source side (energy output side) by utilizing fuzzy control, and then carrying out energy balancing by combining optimized droop control, wherein the method comprises the following steps:

(2) Judging whether each phase of battery pack starts balancing or not by adopting a multi-value balancing strategy;

(3) The fuzzy control is combined with the optimized droop control method, and after the balance is started, the balance current I of each load side is calculated by utilizing the fuzzy control _{equ_i} Determining the total load current on the bus, and calculating the Droop coefficient Droop of each source side by using fuzzy control _i Power distribution is carried out on each source side by combining with optimized droop control, so that the source side transmits energy to the load side, and energy balance is carried out;

2. The active energy balancing method for source-load separation among battery packs according to claim 1, wherein the balancing topology structure of the DC-DC bidirectional converter is a high-voltage side common-direct-current bus structure, any number of battery packs are respectively connected to the low-voltage sides of the same number of converters, the high-voltage sides of the converters are connected in parallel to establish an internal balancing bus, and no other load is placed on the internal balancing bus.

3. The active energy balancing method for source-charge separation among battery packs according to claim 1, wherein the source-charge separation method comprises: utilizing the electric quantity SOC of each phase battery pack _i Calculating the average value SOC of all the battery packs _avg Maximum value SOC _max Minimum value SOC _min Delta SOC _max SOC of each-phase battery pack _i And SOC _avg Difference value Δ SOC of _i According to Δ SOC _i Positive and negative of (1) determines whether each phase battery pack is controlled to be on the source side or the load side, delta SOC _i The phase battery pack is a positive value and is controlled to be a source side; delta SOC _i In negative value, the phase battery pack is controlled to be on the charge side.

4. The active energy balancing method for source-to-charge separation between battery packs according to claim 1, wherein the multi-valued balancing policy is: for delta SOC _i Setting different opening and closing balance thresholds, and if the threshold conditions are met, opening or closing balance of the phase battery pack is realized; for delta SOC _max And setting a starting and closing balance threshold value, and if the threshold value condition is met, starting or closing the battery pack with the maximum electric quantity and the minimum electric quantity is balanced.

5. The active energy balancing method for source-to-charge separation between battery packs according to claim 1, wherein the fuzzy control combined with optimized droop control method comprises: after starting balance, the SOC is charged to the load side _i And Δ SOC _i As input of the charge side fuzzy controller, the charge side equalizing current I is obtained according to the established charge side fuzzy rule _{equ_i} (ii) a To the source side, the SOC _i And Δ SOC _i As the input of the source side fuzzy controller, the source side Droop coefficient Droop is obtained according to the established source side fuzzy rule _i . Adding a correction link for balancing internal bus voltage in a source side droop control link, wherein the input of the link is bus powerAnd the difference value of the pressure set value and the actual value is controlled by proportional integral, the output is a bus voltage correction value, and the bus voltage set value can be changed.

6. The active energy balancing method for source-charge separation between battery packs as claimed in claim 1, wherein during balancing, the battery pack state is updated in real time, and the balancing mode judgment and the load side balancing current I are carried out again according to the battery state after a period of time _{equ_i} Calculating and Source side Droop coefficient Droop _i The update of (2).