A distributed energy storage battery optimizer SOC balancing control method and system

Abstract

The present invention discloses a distributed energy storage battery optimizer SOC balancing control method and system, which belongs to the field of battery energy storage system control. The present invention performs secondary voltage compensation on the output voltage of the battery optimizer to obtain a secondary voltage compensation amount; performs improved droop control on the value of the superposition of the secondary voltage compensation amount and the bus rated voltage to obtain a reference value of the battery optimizer output voltage; performs voltage closed-loop control on the reference value of the battery optimizer output voltage to obtain a frequency difference signal; superimposes the output frequency difference signal with the initial resonant frequency to obtain an actual switching frequency value; and performs pulse frequency modulation on the actual switching frequency value to obtain a driving signal for the battery optimizer power device. Therefore, the balancing control method proposed in the present invention can realize parallel control of multiple battery optimizers during charging and discharging, and can realize coordinated control of multiple battery optimizers when output power control is performed on multiple battery optimizers at the same time.

Description

Technical Field

[0001] The present invention belongs to the technical field of battery energy storage system control, and relates to a distributed energy storage battery optimizer SOC balancing control method and system. Background Art

[0002] In energy storage systems, batteries are typically connected to the DC bus through a bidirectional DC / DC converter to achieve peak shaving and valley filling of DC bus power. The bidirectional flow of energy is achieved by switching the charge and discharge modes of the bidirectional DC / DC converter. Therefore, a good performance of the bidirectional DC / DC converter is an important prerequisite for maintaining stable system operation.

[0003] In existing technologies, bidirectional DC / DC converter topologies often use non-isolated bidirectional DC-DC converters. For example, the published literature, "Distributed Energy Storage Bidirectional DC / DC Converter and SOC Balancing Control," and "Research on Coordinated Control Strategies Based on Improved Droop Methods in Independent DC Microgrids," respectively employ suspended interleaved parallel bidirectional DC / DC converters and bidirectional Buck / Boost converters. These converters have the advantages of simple structure, no transformer, and a small number of components. However, the non-isolated bidirectional DC / DC converter topologies used in these literatures are not suitable for high-voltage applications and operate in a hard-switching state, which limits their efficiency and power density.

[0004] Energy storage modules in energy storage systems are typically connected in parallel to the DC bus in a distributed manner. However, due to differences in components, it is difficult to maintain consistent parameters across the DC bus. Without effective control measures, the output currents of the modules can vary significantly. In severe cases, this can lead to circulating currents between modules, severely impacting the module's service life and even endangering the system's safety and reliability. To prevent overcharging or over-discharging of energy storage modules and ensure proper power distribution among them, an effective power allocation strategy is required to ensure that each module outputs or absorbs power based on its state of charge, thereby achieving power balance and efficient utilization of the energy storage units. Summary of the Invention

[0005] The purpose of the present invention is to solve the problem in the prior art that there are differences in components in energy storage systems, which makes it difficult to maintain consistent parameters of the energy storage modules connected in parallel on the DC bus, resulting in large differences in the output current of each module. A distributed energy storage battery optimizer SOC balancing control method and system are provided.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] The present invention proposes a distributed energy storage battery optimizer SOC balancing control method, comprising the following steps:

[0008] The secondary voltage compensation of the battery optimizer is obtained by subtracting the bus output voltage of the battery optimizer from the rated bus voltage of the battery optimizer through a PI controller;

[0009] Obtain the bus voltage after secondary voltage compensation according to the secondary voltage compensation amount of the battery optimizer and the bus rated voltage of the battery optimizer;

[0010] Obtaining a reference value of the battery optimizer output voltage according to the bus voltage after secondary voltage compensation, the dynamic droop coefficient, and the battery optimizer output current;

[0011] The reference value of the battery optimizer output voltage is subtracted from the bus output voltage of the battery optimizer, and then the frequency difference signal is obtained through the PI controller and limiter;

[0012] According to the frequency difference signal and the initial resonant frequency of the CLLC resonant converter, an actual switching frequency value is obtained, and pulse frequency modulation is performed on the actual switching frequency value to obtain a driving signal for the battery optimizer power device.

[0013] Preferably, the calculation method of the secondary voltage compensation amount δu of the battery optimizer is as follows:

[0014]

[0015] Among them, u oref For a given battery optimizer bus rated voltage, u o is the bus output voltage of the battery optimizer obtained by sampling, k p_b is the proportional control parameter of the voltage compensation PI controller, k i_b is the integral control parameter of the voltage compensation PI controller.

[0016] Preferably, the bus voltage u' after secondary voltage compensation oref The calculation method is as follows:

[0017] u' oref =u oref +δu

[0018] Among them, u oref is the bus rated voltage of a given battery optimizer, and δu is the secondary voltage compensation of the battery optimizer.

[0019] Preferably, the reference value u' of the battery optimizer output voltage orefi as follows:

[0020] u' orefi =u' oref -i oi R i

[0021] Among them, when the system reaches steady state, the output voltage of the battery optimizer satisfies u oi =u' orefi ,i oi is the output current of the i-th battery optimizer, R i is the dynamic droop coefficient;

[0022] The dynamic droop coefficient R is determined based on the state of charge parameters of each battery. i , so that during the charging process, the battery with a higher state of charge parameter absorbs less electrical energy, and the battery with a lower state of charge parameter absorbs more electrical energy; during the discharging process, the battery with a higher state of charge parameter releases more electrical energy, and the battery with a lower state of charge parameter releases less electrical energy.

[0023] Preferably, the battery optimizer output current i obtained by sampling oi The battery status is judged by the status;

[0024] Dynamic droop coefficient R in charging or discharging state i The calculation method is as follows:

[0025] When the battery optimizer output current i oi <0, the battery is in charging state, the dynamic droop coefficient R i The formula is:

[0026] When the battery optimizer output current i oi >0, the battery is in discharge state, the dynamic droop coefficient R i The formula is:

[0027] When the battery optimizer output current i oi =0, then the battery optimizer will exit;

[0028] Among them, R0 is the initial droop coefficient of the energy storage module, which is selected to meet Δu omax The maximum value of the allowable deviation of the bus output voltage obtained by sampling, Δu omin The minimum value of the allowable deviation of the bus output voltage obtained by sampling, i omax is the maximum output current of the battery optimizer, i omin is the minimum output current of the battery optimizer, n is the balancing speed adjustment factor of the energy storage module, SOC i is the state of charge of the battery connected to the i-th battery optimizer, A SOC is the average value of the state of charge of all batteries, α and β are both constants; the value of α is required to be when SOC i When the value of α|SOC is largei -A SOC |>10β, the value of β is required to be β<1.

[0029] Preferably, the frequency difference signal Δf is calculated as follows:

[0030]

[0031] Among them, k p_u is the proportional control parameter of the voltage loop PI controller, k i_u is the integral control parameter of the voltage loop PI controller, u o is the bus output voltage of the battery optimizer obtained by sampling, u' orefi The reference value of the battery optimizer output voltage;

[0032] The actual switching frequency value f of the driving signal of the battery optimizer power device s for:

[0033]

[0034] in, is the initial resonant frequency of the CLLC resonant converter, and Δf is the frequency difference signal.

[0035] Preferably, the actual switching frequency value is pulse frequency modulated to obtain a PFM wave at the actual switching frequency value;

[0036] Output current i for battery optimizer oi The battery status is detected to determine whether it is charging or discharging:

[0037] When the battery optimizer output current i oi <0, the PFM wave at the actual switching frequency drives the switch tubes S1-S4. When the battery optimizer output current i oi >0, the PFM wave at the actual switching frequency drives the switch tubes S5-S8. When the battery optimizer output current i oi When =0, no driving signal is input to the switch tube.

[0038] The present invention proposes a distributed energy storage battery optimizer SOC balancing control system, comprising:

[0039] A secondary voltage compensation amount acquisition module, which is used to obtain the secondary voltage compensation amount of the battery optimizer by subtracting the bus output voltage of the battery optimizer from the bus rated voltage of the battery optimizer through a PI controller;

[0040] A bus voltage acquisition module after secondary voltage compensation, wherein the bus voltage acquisition module after secondary voltage compensation is used to obtain the bus voltage after secondary voltage compensation based on the secondary voltage compensation amount of the battery optimizer and the bus rated voltage of the battery optimizer;

[0041] A reference value acquisition module for the output voltage of the battery optimizer, the reference value acquisition module for the output voltage of the battery optimizer being used to obtain a reference value of the output voltage of the battery optimizer based on the bus voltage after secondary voltage compensation, the dynamic droop coefficient, and the output current of the battery optimizer;

[0042] A frequency difference signal acquisition module, which is used to obtain a frequency difference signal by subtracting the reference value of the battery optimizer output voltage from the bus output voltage of the battery optimizer and then passing the difference through a PI controller and a limiter;

[0043] A drive signal acquisition module is used to obtain an actual switching frequency value based on the frequency difference signal and the initial resonant frequency of the CLLC resonant converter, and to perform pulse frequency modulation on the actual switching frequency value to obtain a drive signal for the battery optimizer power device.

[0044] A computer device includes a memory and a processor, wherein the memory stores a computer program and the processor implements the steps of a distributed energy storage battery optimizer SOC balancing control method when executing the computer program.

[0045] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a distributed energy storage battery optimizer SOC balancing control method.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] The present invention proposes a SOC balancing control method for a distributed energy storage battery optimizer. Compared to prior art bidirectional DC / DC converters, this method utilizes a CLLC resonant converter to obtain parameters, addressing the problem of non-isolated bidirectional DC / DC converter topologies being unable to adapt to high-voltage environments and operating in a hard-switching state. Secondary voltage compensation is performed for bus voltage drops, addressing the issue of droop control causing the bus voltage to deviate from a given value to a certain extent, thereby reducing the bus voltage fluctuation range. A dynamic droop coefficient, determined based on each battery's real-time SOC parameter, allows the output power of the energy storage module to be adjusted in real time based on the battery's real-time SOC parameter, achieving a reasonable distribution of bus power among the modules and improving the SOC balancing speed of each module. Simultaneous output power control of multiple battery optimizers enables coordinated control of the multiple battery optimizers. Therefore, the control method proposed in this invention addresses the prior art problem of component differences in energy storage systems, making it difficult to maintain consistent parameters among the energy storage modules connected in parallel on the DC bus, resulting in significant differences in output current among the modules.

[0048] Furthermore, a no-load startup strategy is combined to reduce the resonant current overshoot during the startup process; the discharge threshold and charging threshold are set to avoid the oscillation phenomenon of switching back and forth in the converter.

[0049] The present invention proposes a system for a distributed energy storage battery optimizer SOC balancing control method. By dividing the system into a secondary voltage compensation amount acquisition module, a bus voltage acquisition module after secondary voltage compensation, a battery optimizer output voltage reference value acquisition module, a frequency difference signal acquisition module, and a drive signal acquisition module, a modular concept is adopted to make each module independent of each other, facilitating unified management of each module. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0051] Figure 1 This is a flow chart of the SOC balancing control method of the distributed energy storage battery optimizer of the present invention.

[0052] Figure 2 This is a schematic diagram of the principle of the SOC balancing control method of the distributed energy storage battery optimizer of the present invention.

[0053] Figure 3 This is a structural diagram of the distributed energy storage battery optimizer system of the present invention.

[0054] Figure 4 This is the DC bus charging and discharging U / I control characteristic diagram of the present invention.

[0055] Figure 5 This is a control system diagram of the SOC balancing control method of the distributed energy storage battery optimizer of the present invention. DETAILED DESCRIPTION

[0056] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0057] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort shall fall within the scope of protection of the present invention.

[0058] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0059] In the description of the embodiments of the present invention, it should be noted that if the terms "upper," "lower," "horizontal," "inner," etc. appear, the orientation or positional relationship indicated is based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the inventive product is typically placed when in use. These terms are merely for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or component referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limitations on the present invention. In addition, the terms "first," "second," etc. are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0060] In addition, if the term "horizontal" appears, it does not mean that the component must be absolutely horizontal, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0061] In the description of the embodiments of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "disposed," "installed," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to internal connections between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0062] The present invention is described in further detail below with reference to the accompanying drawings:

[0063] The present invention proposes a distributed energy storage battery optimizer SOC balancing control method, such as Figure 1 As shown, the following steps are included:

[0064] S1. Subtract the bus output voltage of the battery optimizer from the rated bus voltage of the battery optimizer and then use the PI controller to obtain the secondary voltage compensation of the battery optimizer.

[0065] The calculation method of the secondary voltage compensation δu of the battery optimizer is as follows:

[0066]

[0067] Among them, u oref For a given battery optimizer bus rated voltage, u o is the bus output voltage of the battery optimizer obtained by sampling, k p_b is the proportional control parameter of the voltage compensation PI controller, k i_b is the integral control parameter of the voltage compensation PI controller.

[0068] S2. Obtaining the bus voltage after secondary voltage compensation based on the secondary voltage compensation amount of the battery optimizer and the bus rated voltage of the battery optimizer;

[0069] Bus voltage u' after secondary voltage compensation oref The calculation method is as follows:

[0070] u' oref =u oref +δu

[0071] Among them, u oref is the bus rated voltage of a given battery optimizer, and δu is the secondary voltage compensation of the battery optimizer.

[0072] S3. Obtaining a reference value of the battery optimizer output voltage based on the bus voltage after secondary voltage compensation, the dynamic droop coefficient, and the battery optimizer output current;

[0073] Reference value u' of the battery optimizer output voltage orefi as follows:

[0074] u' orefi =u' oref -i oi R i

[0075] Among them, when the system reaches steady state, the output voltage of the battery optimizer satisfies u oi =u' orefi ,i oi is the output current of the i-th battery optimizer, R i is the dynamic droop coefficient;

[0076] The dynamic droop coefficient R is determined based on the state of charge parameters of each battery. i , so that during the charging process, the battery with a higher state of charge parameter absorbs less electrical energy, and the battery with a lower state of charge parameter absorbs more electrical energy; during the discharging process, the battery with a higher state of charge parameter releases more electrical energy, and the battery with a lower state of charge parameter releases less electrical energy.

[0077] According to the sampled battery optimizer output current i oi The battery status is judged by the status;

[0078] Dynamic droop coefficient R in charging or discharging state i The calculation method is as follows:

[0079] When the battery optimizer output current i oi <0, the battery is in charging state, the dynamic droop coefficient R i The formula is:

[0080] When the battery optimizer output current i oi >0, the battery is in discharge state, the dynamic droop coefficient R i The formula is:

[0081] When the battery optimizer output current i oi =0, then the battery optimizer will exit;

[0082] Among them, R0 is the initial droop coefficient of the energy storage module, which is selected to meet Δu omax The maximum value of the allowable deviation of the bus output voltage obtained by sampling, Δu omin The minimum value of the allowable deviation of the bus output voltage obtained by sampling, i omax is the maximum output current of the battery optimizer, i ominis the minimum output current of the battery optimizer, n is the balancing speed adjustment factor of the energy storage module, SOC i is the state of charge of the battery connected to the i-th battery optimizer, A SOC is the average value of the state of charge of all batteries, α and β are both constants; the value of α is required to be when SOC i When the value of α|SOC is large i -A SOC |>10β, the value of β is required to be β<1.

[0083] S4. Subtract the reference value of the battery optimizer output voltage from the bus output voltage of the battery optimizer and pass it through a PI controller and a limiter to obtain a frequency difference signal;

[0084] The frequency difference signal Δf is calculated as follows:

[0085]

[0086] Among them, k p_u is the proportional control parameter of the voltage loop PI controller, k i_u is the integral control parameter of the voltage loop PI controller, u o is the bus output voltage of the battery optimizer obtained by sampling, u' orefi It is the reference value of the battery optimizer output voltage.

[0087] S5. Obtain an actual switching frequency value according to the frequency difference signal and the initial resonant frequency of the CLLC resonant converter, perform pulse frequency modulation on the actual switching frequency value, and obtain a driving signal for the battery optimizer power device.

[0088] The actual switching frequency value f of the driving signal of the battery optimizer power device s for:

[0089]

[0090] in, is the initial resonant frequency of the CLLC resonant converter, and Δf is the frequency difference signal.

[0091] Perform pulse frequency modulation on the actual switching frequency value to obtain the PFM wave at the actual switching frequency value;

[0092] Output current i for battery optimizer oi The battery status is detected to determine whether it is charging or discharging:

[0093] When the battery optimizer output current i oi <0, the PFM wave at the actual switching frequency drives the switch tubes S1-S4. When the battery optimizer output current i oi>0, the PFM wave at the actual switching frequency drives the switch tubes S5-S8. When the battery optimizer output current i oi When =0, no driving signal is input to the switch tube.

[0094] The present invention proposes a distributed energy storage battery optimizer SOC balancing control method, which can be implemented according to the following steps.

[0095] Step 1: The secondary voltage compensation unit performs secondary voltage compensation on the output voltage of the battery optimizer, making the bus output voltage different from the given bus rated voltage and then obtaining the secondary voltage compensation amount through the PI controller.

[0096] Step 2: Superimpose the secondary voltage compensation amount and the bus rated voltage to obtain the bus voltage after secondary voltage compensation.

[0097] Step 3: The droop control unit subtracts the product of the dynamic droop coefficient and the battery optimizer output current from the bus voltage after secondary voltage compensation to obtain a reference value of the battery optimizer output voltage.

[0098] Step 4: The voltage control unit compares the reference value of the battery optimizer output voltage with the sampled bus output voltage, obtains the frequency difference signal through the PI controller and limiter, and forms a voltage closed-loop control.

[0099] Step 5: Add a frequency modulation loop and superimpose the frequency difference signal with the initial resonant frequency of the CLLC resonant converter to obtain the actual switching frequency value.

[0100] The actual switching frequency value is pulse-frequency modulated to obtain a driving signal for the power device of the battery optimizer.

[0101] In this embodiment, the SOC balancing method based on the improved droop control is used to adjust the output current of the CLLC resonant converter to achieve coordinated control of multiple CLLC resonant converters. Figure 2 The figure is a schematic diagram of the principle of a distributed energy storage battery optimizer SOC balancing control method according to an embodiment of the present invention, combined with Figure 2 Steps 1 to 6 are explained.

[0102] The secondary voltage compensation of the CLLC resonant converter in step 1 can be implemented according to the following steps.

[0103] The secondary voltage compensation δu is shown as follows:

[0104]

[0105] Among them, u oref For a given busbar rated voltage, u ois the bus output voltage obtained by sampling, k p_b and k i_b are the proportional control parameter and the integral control parameter of the voltage compensation PI controller.

[0106] Because improved droop control compromises the accuracy of differential control and the effectiveness of current sharing, it can cause a drop in the DC bus voltage. To stabilize the bus voltage within the allowable range, the battery optimizer's bus voltage reference value is compensated to achieve this goal. The deviation between the bus voltage reference value and the bus output voltage is calculated using a proportional integral, and the resulting output is used as the voltage loop compensation.

[0107] Obtaining the bus voltage after secondary voltage compensation in step 2 can be implemented according to the following steps.

[0108] The bus voltage after secondary voltage compensation is the result of adding the secondary voltage compensation amount to the bus rated voltage. The bus voltage after secondary voltage compensation is shown in the following formula:

[0109] u' oref =u oref +δu

[0110] The improved droop control in step 3 can be implemented as follows.

[0111] The reference value of the battery optimizer output voltage is obtained by subtracting the product of the dynamic droop coefficient and the battery optimizer output current from the bus voltage after secondary voltage compensation:

[0112] u' orefi =u' oref -i oi R i

[0113] Among them, u' orefi is the reference value of the battery optimizer output voltage. When the system reaches a steady state, the output voltage of the battery optimizer satisfies u oi =u' orefi ,i oi is the output current of the i-th battery optimizer, R i is the dynamic droop coefficient.

[0114] Dynamic droop coefficient R i Select as follows:

[0115] Determine the dynamic droop coefficient R based on the real-time state of charge parameters of each battery iThe value of is chosen so that during the charging process, the battery with a higher state of charge parameter absorbs less energy, and the battery with a lower state of charge parameter absorbs more energy; during the discharging process, the battery with a higher state of charge parameter releases more energy, and the battery with a lower state of charge parameter releases less energy.

[0116] When the output current of the battery optimizer i oi <0, the battery is in charging state, the dynamic droop coefficient R i The formula is:

[0117] When the output current of the battery optimizer i oi >0, the battery is in discharge state, the dynamic droop coefficient R i The formula is:

[0118] When the output current of the battery optimizer i oi =0, the battery optimizer exits.

[0119] Among them, R0 is the initial droop coefficient of the energy storage module, which is selected to meet Δu omax and Δu omin The maximum and minimum values ​​of the sampled bus output voltage allowable deviation, i omax and i omin is the maximum and minimum output current of the battery optimizer; n is the balancing speed adjustment factor of the energy storage module; SOC i A is the state of charge of the battery connected to the i-th battery optimizer; SOC is the average value of the state of charge of all batteries; α and β are both constants, and the value of α is required to be when SOC i When the value of α|SOC is large i -A SOC |>10β, the value of β is required to be β<1.

[0120] like Figure 3 This is the system structure diagram of the distributed energy storage battery optimizer of the present invention. The main circuit of the battery optimizer is a CLLC resonant bidirectional DC-DC converter, including a high-voltage side capacitor C1, a primary side resonant capacitor C r1 , primary side resonant inductor L r1 , excitation inductance L m , transformer, secondary side resonant capacitor C r2 , secondary side resonant inductor L r2, switches S1 to S8, and low-voltage side capacitor C2. The battery optimizer is connected to the battery on one side and to the DC bus on the other. The battery and battery optimizer form an energy storage module. The DC bus can connect to any number of energy storage modules connected in parallel. The DC bus is connected to a current source load. The converter's charge and discharge mode depends on the requirements of the DC bus, specifically the direction of the current in the current source load.

[0121] In this embodiment, the operation of two energy storage modules connected in parallel on a DC bus is used as an example for explanation:

[0122] Multiple energy storage modules are connected in parallel on the DC bus, and the average state of charge of all batteries is A. SOC As the state of charge of each battery changes, A SOC The value of is between the maximum state of charge and the minimum state of charge. Assume that the state of charge SOC1 of the battery in energy storage module 1 is greater than A SOC , the state of charge SOC1 of the battery in energy storage module 2 SOC , the output current ratios of energy storage module 1 and energy storage module 2 in the charge and discharge modes are:

[0123] When the output current of the battery optimizer i oi <0, the battery is in charging state, and the output current ratio of energy storage module 1 and energy storage module 2 is

[0124] When the output current of the battery optimizer i oi >0, the battery is in discharge state, and the output current ratio of energy storage module 1 and energy storage module 2 is

[0125] Among them, α|SOC i -A SOC |>10β, ignoring the influence of β, the output current ratio of energy storage module 1 and energy storage module 2 in the charge and discharge mode is simplified to:

[0126] When the output current of the battery optimizer i oi <0, the battery is in charging state, and the output current ratio of energy storage module 1 and energy storage module 2 is

[0127] When the output current of the battery optimizer i oi >0, the battery is in discharge state, and the output current ratio of energy storage module 1 and energy storage module 2 is

[0128] From the output current ratio of energy storage module 1 and energy storage module 2, it can be seen that at this time, the output current ratio expression only contains a constant. Therefore, the output current distribution of each energy storage module is a constant value, and the output current distribution of the module with more energy storage is greater than that of the module with less energy storage.​

[0129] In step 4, the voltage closed-loop control is implemented according to the following steps.

[0130] The control method of voltage closed-loop control is as follows:

[0131] The reference value of the battery optimizer output voltage is compared with the sampled bus output voltage, and the frequency difference signal is obtained through the PI controller and limiter. The formula of the frequency difference signal is:

[0132]

[0133] Among them, k p_u Proportional control parameter of the voltage loop PI controller, k i_u is the integral control parameter of the voltage loop PI controller. The upper limit of the limiter is The lower limit of the limiter is f max and f min are the maximum frequency and minimum frequency that the system can withstand, so Δf satisfies

[0134] Adding the frequency modulation loop in step 5 can be implemented according to the following steps.

[0135] The control method of adding the frequency modulation loop is as follows: the initial resonant frequency of the CLLC resonant converter is set to Subtract the frequency difference signal Δf from the actual switching frequency value of the driving signal of the battery optimizer power device to obtain the actual switching frequency value. The formula for the actual switching frequency value is:

[0136]

[0137] The circuit of the battery optimizer in this embodiment may include the following structure.

[0138] The pulse frequency modulation in step 6 can be implemented according to the following steps.

[0139] Perform pulse frequency modulation on the actual switching frequency value to obtain the PFM wave under the actual switching frequency value. The specific process is to input the actual switching frequency value f s , the output frequency value is the actual switching frequency value f s , the duty cycle is 50%, two complementary square waves.

[0140] Output current i for battery optimizer oi The battery optimizer detects the status of the battery and determines whether it is in the charging or discharging state. oi<0, the PFM wave at the actual switching frequency value drives the switch tubes S1 to S4, wherein the drive signals of S1 and S4 and the drive signals of S2 and S3 are two complementary square waves; when the battery optimizer output current i oi >0, the PFM wave at the actual switching frequency value drives the switch tubes S5 to S8, wherein the drive signals of S5 and S8 are two complementary square waves with the drive signals of S5 and S6; when the battery optimizer output current i oi When =0, no driving signal is input to the switch tube.

[0141] like Figure 4 This is the U / I control characteristic of the DC bus charge and discharge of the present invention. The charge and discharge mode of the converter depends on the needs of the DC bus. The specific process is: if the system needs to charge the battery, the current source load will inject current into the DC bus to raise the DC bus voltage. When the DC bus voltage exceeds the charging threshold, the DC bus charges the energy storage module connected in parallel on the DC bus; when the system needs to discharge the battery, the current source load will draw current from the DC bus. When the DC bus voltage is lower than the discharge threshold, the energy storage module connected in parallel on the DC bus discharges to the DC bus. In order to avoid the converter switching back and forth between charge and discharge, the charging threshold and the discharge threshold are designed to be different to avoid the oscillation phenomenon of the CLLC resonant converter switching back and forth, where U1 and U2 are the discharge threshold and the charging threshold, and U L and U H is the bus voltage regulation range.

[0142] The no-load startup strategy is as follows: When starting with no-load, the DC bus voltage is lower than the discharge threshold, so the energy storage module discharges to the DC bus. The soft start strategy is used during startup, by setting the output initial value of the voltage loop PI controller in step 5. The actual switching frequency value f of the driving signal of the battery optimizer power device is s At the start-up time, the frequency is at its maximum value f s_max , and then gradually decreases to the initial resonant frequency When the DC bus voltage is equal to the discharge threshold, the battery optimizer exits operation and maintains the DC bus voltage near the discharge threshold. The load is then connected only after the DC bus voltage stabilizes.

[0143] The present invention proposes a control system for a distributed energy storage battery optimizer SOC balancing control method, such as Figure 5 Shown, including:

[0144] A secondary voltage compensation amount acquisition module, which is used to obtain the secondary voltage compensation amount of the battery optimizer by subtracting the bus output voltage of the battery optimizer from the bus rated voltage of the battery optimizer through a PI controller;

[0145] A bus voltage acquisition module after secondary voltage compensation, wherein the bus voltage acquisition module after secondary voltage compensation is used to obtain the bus voltage after secondary voltage compensation based on the secondary voltage compensation amount of the battery optimizer and the bus rated voltage of the battery optimizer;

[0146] A reference value acquisition module for the output voltage of the battery optimizer, the reference value acquisition module for the output voltage of the battery optimizer being used to obtain a reference value of the output voltage of the battery optimizer based on the bus voltage after secondary voltage compensation, the dynamic droop coefficient, and the output current of the battery optimizer;

[0147] A frequency difference signal acquisition module, which is used to obtain a frequency difference signal by subtracting the reference value of the battery optimizer output voltage from the bus output voltage of the battery optimizer and then passing the difference through a PI controller and a limiter;

[0148] A drive signal acquisition module is used to obtain an actual switching frequency value based on the frequency difference signal and the initial resonant frequency of the CLLC resonant converter, and to perform pulse frequency modulation on the actual switching frequency value to obtain a drive signal for the battery optimizer power device.

[0149] An embodiment of the present invention provides a terminal device, comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of each of the aforementioned method embodiments are implemented. Alternatively, when the processor executes the computer program, the functions of each module / unit in each of the aforementioned apparatus embodiments are implemented.

[0150] The computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to accomplish the present invention.

[0151] The terminal device may be a computing device such as a desktop computer, a notebook computer, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0152] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0153] The memory may be used to store the computer programs and / or modules, and the processor implements various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory.

[0154] If the module / unit integrated in the terminal device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0155] The present invention proposes a distributed energy storage battery optimizer SOC balancing control method and system, which has the following advantages: 1) The present invention performs secondary voltage compensation for the bus voltage drop caused by droop control, solves the problem that the bus voltage deviates from the given value to a certain extent due to droop control, and reduces the bus voltage fluctuation range. 2) In the prior art, the main circuit of the battery optimizer adopts a non-isolated bidirectional DC / DC converter topology, which cannot adapt to occasions with high voltage levels and operates in a hard switching state. The present invention adopts a CLLC resonant converter as a bidirectional DC / DC converter topology, which has a high voltage gain and natural soft switching characteristics, has the advantages of high power density and high efficiency, and can achieve electrical isolation between the input and output ends, thereby improving the safety performance of the converter. 3) The present invention proposes combining a no-load starting strategy to reduce the resonant current overshoot during the startup process; setting a discharge threshold and a charging threshold to avoid the oscillation phenomenon of the converter switching back and forth. 4) The droop coefficient in the prior art lacks the ability to adjust in real time based on the battery's state of charge. A single charging rate may cause overcharging of battery packs with high SOCs, while a single discharging rate may cause overdischarging of battery packs with low SOCs, and the power of the other battery packs cannot be fully utilized. The present invention adopts a control strategy that determines a dynamic droop coefficient based on the state of charge parameters of each battery. This allows the output power of the energy storage module to be adjusted in real time based on the battery's state of charge parameters, achieving a reasonable distribution of bus power among the energy storage modules and improving the state of charge balancing speed of each energy storage module. When multiple battery optimizers are simultaneously controlled for output power, coordinated control of multiple battery optimizers can be achieved.

[0156] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A distributed energy storage battery optimizer SOC balancing control method, characterized in that: The steps include: The secondary voltage compensation of the battery optimizer is obtained by subtracting the bus output voltage of the battery optimizer from the rated bus voltage of the battery optimizer through a PI controller; Obtain the bus voltage after secondary voltage compensation according to the secondary voltage compensation amount of the battery optimizer and the bus rated voltage of the battery optimizer; Obtaining a reference value of the battery optimizer output voltage according to the bus voltage after secondary voltage compensation, the dynamic droop coefficient, and the battery optimizer output current; The reference value of the battery optimizer output voltage is subtracted from the bus output voltage of the battery optimizer, and then the frequency difference signal is obtained through the PI controller and limiter; According to the frequency difference signal and the initial resonant frequency of the CLLC resonant converter, an actual switching frequency value is obtained, and pulse frequency modulation is performed on the actual switching frequency value to obtain a driving signal for the battery optimizer power device; Secondary voltage compensation of battery optimizer The calculation method is as follows: in, For a given battery optimizer's busbar rated voltage, is the bus output voltage of the battery optimizer obtained by sampling, is the proportional control parameter of the voltage-compensated PI controller, is the integral control parameter of the voltage compensation PI controller; Frequency difference signal The calculation method is as follows: in, is the proportional control parameter of the voltage loop PI controller, is the integral control parameter of the voltage loop PI controller, is the bus output voltage of the battery optimizer obtained by sampling, The reference value of the battery optimizer output voltage; The actual switching frequency value of the driving signal of the battery optimizer power device for: in, is the initial resonant frequency of the CLLC resonant converter, is the frequency difference signal.

2. The SOC balancing control method for a distributed energy storage battery optimizer according to claim 1, characterized in that: Bus voltage after secondary voltage compensation The calculation method is as follows: in, For a given battery optimizer's busbar rated voltage, It is the secondary voltage compensation amount of the battery optimizer.

3. The distributed energy storage battery optimizer SOC balancing control method according to claim 1, characterized in that: Reference value of battery optimizer output voltage as follows: Among them, when the system reaches steady state, the output voltage of the battery optimizer satisfies , For the The output current of the battery optimizer, is the dynamic droop coefficient; Dynamic droop coefficient determined by the state of charge parameters of each battery , so that during the charging process, the battery with a higher state of charge parameter absorbs less electrical energy, and the battery with a lower state of charge parameter absorbs more electrical energy; during the discharging process, the battery with a higher state of charge parameter releases more electrical energy, and the battery with a lower state of charge parameter releases less electrical energy.

4. The distributed energy storage battery optimizer SOC balancing control method according to claim 3, characterized in that: The battery optimizer output current is obtained based on the sampling The battery status is judged by the status; Dynamic droop coefficient in charging or discharging state The calculation method is as follows: When the battery optimizer output current , the battery is in charging state, dynamic droop coefficient The formula is: ； When the battery optimizer output current , the battery is in discharge state, dynamic droop coefficient The formula is: ； When the battery optimizer output current , at this time the battery optimizer exits; in, is the initial droop coefficient of the energy storage module, which should be selected to meet , is the maximum value of the allowable deviation of the bus output voltage obtained by sampling, is the minimum value of the allowable deviation of the bus output voltage obtained by sampling, is the maximum output current of the battery optimizer, is the minimum output current of the battery optimizer, is the equilibrium speed adjustment factor of the energy storage module, For the The state of charge of the battery to which the battery optimizer is connected, is the average state of charge of all batteries, and are all constants; The value requirement is when When the value of , The value requirement is .

5. The distributed energy storage battery optimizer SOC balancing control method according to claim 1, characterized in that: Perform pulse frequency modulation on the actual switching frequency value to obtain the PFM wave at the actual switching frequency value; Output current for battery optimizer The battery status is detected to determine whether it is charging or discharging: When the battery optimizer output current When the actual switching frequency value of the PFM wave drives the switch tube , when the battery optimizer output current When the actual switching frequency value of the PFM wave drives the switch tube , when the battery optimizer output current When , no driving signal is input to the switch tube.

6. A distributed energy storage battery optimizer SOC balancing control system, characterized in that: The distributed energy storage battery optimizer SOC balancing control method according to any one of claims 1 to 5 comprises: A secondary voltage compensation amount acquisition module, which is used to obtain the secondary voltage compensation amount of the battery optimizer by subtracting the bus output voltage of the battery optimizer from the bus rated voltage of the battery optimizer through a PI controller; A bus voltage acquisition module after secondary voltage compensation, wherein the bus voltage acquisition module after secondary voltage compensation is used to obtain the bus voltage after secondary voltage compensation based on the secondary voltage compensation amount of the battery optimizer and the bus rated voltage of the battery optimizer; A reference value acquisition module for the output voltage of the battery optimizer, the reference value acquisition module for the output voltage of the battery optimizer being used to obtain a reference value of the output voltage of the battery optimizer based on the bus voltage after secondary voltage compensation, the dynamic droop coefficient, and the output current of the battery optimizer; A frequency difference signal acquisition module, which is used to obtain a frequency difference signal by subtracting the reference value of the battery optimizer output voltage from the bus output voltage of the battery optimizer and then passing the difference through a PI controller and a limiter; A drive signal acquisition module is used to obtain an actual switching frequency value based on the frequency difference signal and the initial resonant frequency of the CLLC resonant converter, and to perform pulse frequency modulation on the actual switching frequency value to obtain a drive signal for the battery optimizer power device.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the distributed energy storage battery optimizer SOC balancing control method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the distributed energy storage battery optimizer SOC balancing control method according to any one of claims 1 to 5 are implemented.

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