Battery pack energy balancing method and system of layered buck-boost circuit

Abstract

The embodiment of the invention provides a battery pack energy balancing method and system of a layered buck-boost circuit, and the method comprises the steps: dividing a battery pack into a plurality of sub-modules, each sub-module comprises at least two single batteries connected in series, and configuring an intra-pack balancing channel and an inter-pack balancing channel; real-time working condition signals of all the single batteries are collected in real time, and the charge state mean value of the battery pack, the inter-pack range and the difference value between the adjacent single batteries are estimated; based on a fuzzy control algorithm, equalization current signals are generated, and the equalization current signals comprise intra-group equalization control signals and inter-group equalization control signals; and energy transfer and cross-level energy scheduling between adjacent single batteries are realized through intra-group equalization control signals and intra-group equalization channels, so that battery energy equalization is realized in a layered manner. According to the embodiment of the invention, the effects of improving the battery pack energy balancing efficiency, optimizing the dynamic response speed of the battery pack and reducing the energy loss can be achieved.

Description

Technical Field

[0001] The present application belongs to the technical field of battery management systems, and specifically relates to a battery pack energy balancing method and system for a layered buck-boost circuit. Background Art

[0002] In electric vehicles and energy storage systems, lithium-ion battery packs typically consist of multiple cells connected in series. Due to differences in production processes and operating environments, there are inconsistencies between the cells, manifesting as imbalances in the state of charge (SOC). This imbalance can reduce the overall performance and lifespan of the battery pack. Therefore, achieving high-precision cell balancing places extremely high demands on battery management systems. Current technologies face three core challenges: First, the balancing circuit topology design has inherent limitations. Existing single-layer buck-boost balancing circuits typically only transfer energy between adjacent cells. For long battery packs, energy must undergo multiple conversions before reaching the target cell, which not only increases energy loss but also significantly reduces balancing speed. Furthermore, the dynamic variation of battery internal resistance leads to significant discrepancies between theoretical models and actual circuits, affecting balancing accuracy. Second, the operating environment is subject to significant uncertainty. Battery packs face complex operating conditions in actual operation, including rapid switching between charge and discharge states, parameter changes caused by temperature gradients, and characteristic changes caused by battery aging. These factors together constitute a complex source of disturbances, and traditional control methods often struggle to effectively address these multi-timescale disturbances. Furthermore, existing control strategies lack adaptability. Fixed-parameter controllers struggle to adapt to the balancing requirements of battery packs at different states of charge. This is particularly true within the system-on-chip (SoC) platform, where voltage variations are less pronounced, which can easily lead to balancing misjudgments. Polarization effects at both ends of the SoC require specialized control strategies. This rigid control approach not only compromises balancing effectiveness but also poses potential safety risks.

[0003] Current battery balancing technology has significant shortcomings: Passive balancing, while simple in structure, suffers from low energy efficiency; active balancing suffers from slow capacitor balancing, electromagnetic interference issues with inductor balancing, and bulky transformer balancing. These limitations make it difficult for existing systems to simultaneously meet the requirements for balancing accuracy and efficiency. Voltage-based balancing strategies are particularly prone to malfunctions for battery types with distinct voltage plateaus, further increasing the difficulty of balancing. Summary of the Invention

[0004] The present application proposes a battery pack energy balancing method and system using a layered buck-boost circuit to address the above-mentioned deficiencies in the prior art.

[0005] According to a first aspect of an embodiment of the present application, a battery pack energy balancing method for a layered buck-boost circuit is provided, comprising: A battery pack energy balancing method for a layered buck-boost circuit, comprising: Divide the battery pack into a plurality of submodules, each submodule comprising at least two single cells connected in series, configure an active balancing circuit connected in parallel to each submodule as an intra-group balancing channel, and configure a bidirectional energy transfer circuit for connecting adjacent submodules as an inter-group balancing channel; Collecting real-time operating condition signals of each of the single cells in real time, and estimating the state of charge mean, inter-group range, and difference between adjacent single cells of the battery pack; Based on a fuzzy control algorithm, a balancing current signal is generated according to the state of charge mean of the battery group, the inter-group range, and the difference between the adjacent single batteries. The balancing current signal includes an intra-group balancing control signal and an inter-group balancing control signal. Energy transfer between adjacent single cells is achieved through the intra-group balancing control signal and the intra-group balancing channel, and cross-level energy scheduling between the multiple sub-modules is achieved through the inter-group balancing control signal and the cross-group inductor module of the inter-group balancing channel, so as to achieve hierarchical battery energy balancing.

[0006] In some embodiments, generating the intra-group balancing control signal and the inter-group balancing control signal includes: The state of charge mean of the battery pack and the difference between the adjacent single cells are input into the intra-group balancing controller, the state of charge mean of the battery pack and the inter-group range difference are input into the inter-group balancing controller, and the pulse width modulation duty cycle is dynamically adjusted through the fuzzy control algorithm to generate the intra-group balancing control signal and the inter-group balancing control signal.

[0007] In some embodiments, the layered implementation of battery energy balancing includes: When the battery pack is in a static state, the intra-group balancing channel and the inter-group balancing channel work in coordination; When the battery pack is in a charging state, the first stage of controlling the battery energy balancing is switched to the state of charge balancing control stage, and the second stage of controlling the battery energy balancing is switched to the voltage balancing control stage; When the battery pack is in a discharging state, when the range difference is greater than 2%, the battery energy balancing is controlled to trigger a high current balancing mode; when the range difference is less than 0.5%, the battery energy balancing is controlled to switch to a maintenance mode.

[0008] In some embodiments, the domains of the state of charge mean of the battery group and the difference between the adjacent single cells input to the intra-group balancing controller are [0, 20%] and [0, 60%] respectively; The domains of the state of charge mean of the battery group and the inter-group range input to the inter-group balancing controller are [0, 1] and [0, 10%] respectively; The pulse width modulation duty cycle range is [47%, 53%], and the balancing current of the balancing current signal is (0, 2)A.

[0009] In some embodiments, the balancing current signal is generated based on the fuzzy control algorithm using the state of charge mean of the battery pack, the inter-pack range, and the difference between adjacent single cells, including: Based on the state of charge mean of the battery pack, the inter-group range and the difference between adjacent single cells, a pulse width modulation signal driving a switching device is generated by a fuzzy control algorithm. The pulse width modulation signal includes a first control signal for adjusting the charge and discharge time of the inductor within the group and a second control signal for controlling the on and off of the inter-group balancing channel; The defuzzification of the fuzzy control algorithm is performed using the center of gravity method.

[0010] In some embodiments, the step-by-step balancing strategy under the charging state includes: When the battery pack is in a charging state, an adaptive attenuation mechanism for balancing current is introduced in the second stage to automatically reduce the balancing current intensity when the cell voltage approaches a threshold voltage, thereby avoiding overcharging damage through the adaptive attenuation mechanism.

[0011] In some embodiments, the intra-group balancing channel uses a single-inductor buck-boost circuit to achieve energy transfer between adjacent single cells; The inter-group balancing channel performs cross-level energy scheduling among the multiple sub-modules through the cross-group inductor module.

[0012] In some embodiments, dynamically adjusting the pulse width modulation duty cycle by the fuzzy control algorithm includes: Dividing the input state of charge mean of the battery pack, the inter-group range, and the difference between the adjacent single cells into five fuzzy subsets (VS, S, M, L, VL) through a membership function; The output pulse width modulation duty cycle is calculated by the center of gravity method, and the formula is: I = (∫xf(x)) / (∫f(x)) Wherein, I is the pulse width modulation duty cycle, x is the output variable domain, and f(x) is the membership function.

[0013] According to a second aspect of an embodiment of the present application, a battery pack energy balancing system with a layered buck-boost circuit is provided, comprising: A structural building module for dividing the battery pack into multiple submodules, each submodule comprising at least two single cells connected in series, an active balancing circuit connected in parallel to each submodule as an intra-group balancing channel, and a bidirectional energy transfer circuit for connecting adjacent submodules as an inter-group balancing channel; A battery status monitoring module is used to collect real-time operating condition signals of each of the single cells and estimate the mean state of charge of the battery pack, the range between groups, and the difference between adjacent single cells; a control signal generating module, configured to generate a balancing current signal based on a fuzzy control algorithm and the state of charge mean of the battery pack, the inter-pack range, and the difference between adjacent single cells, wherein the balancing current signal includes an intra-pack balancing control signal and an inter-pack balancing control signal; An energy transfer module is configured to implement energy transfer between adjacent single cells through the intra-group balancing control signal and the intra-group balancing channel, and implement cross-level energy scheduling between the multiple sub-modules through the inter-group balancing control signal and the cross-group inductance module of the inter-group balancing channel, so as to achieve hierarchical battery energy balancing.

[0014] According to a third aspect of an embodiment of the present application, an electric vehicle is provided, which is equipped with a battery pack energy balancing system with a hierarchical buck-boost circuit. The system is configured to execute the above-mentioned battery pack energy balancing method with the hierarchical buck-boost circuit.

[0015] The beneficial effects of the battery pack energy balancing method and system of the layered buck-boost circuit according to the embodiment of the present application include at least: This embodiment realizes decentralized management of the physical layer of the battery pack by decomposing the battery pack into several independent sub-modules, each of which is configured as an autonomous control unit. At the same time, through the innovatively designed buck-boost dual-channel topology, a three-dimensional energy scheduling network from intra-group voltage balancing to inter-group power is established, realizing efficient redistribution of energy between single cells, sub-modules and system layers. Combined with the dynamic fuzzy control algorithm, the accuracy of intra-group voltage balancing, inter-group power balancing and dynamic threshold adaptation are improved, realizing multi-dimensional, high-precision battery pack energy balancing management, and achieving the effects of improving battery energy balancing efficiency, optimizing dynamic response speed and reducing battery energy loss. Through the above-mentioned collaborative control, the present application achieves multi-dimensional energy balancing and high-precision control of millisecond-level response of battery packs, reducing the capacity attenuation rate of the battery pack by 42% and increasing the charge and discharge cycle life by 37%. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a flow chart of an embodiment of a battery pack energy balancing method for a layered buck-boost circuit according to an embodiment of the present application; Figure 2Figures 2(a), 2(c), and 2(e) show the state of charge changes of each single cell in the energy balancing process of a conventional buck-boost battery pack under the three states of rest, charge, and discharge, respectively. Figure 2 (b), 2(d) and 2(f) are diagrams showing the change in state of charge of each single cell during the energy balancing process of the layered buck-boost battery pack in the embodiment of the present application under the three states of rest, charge and discharge respectively; Figure 3 A circuit diagram of a battery pack energy balancing method using a layered buck-boost circuit according to an embodiment of the present application; Figure 4 A flowchart of another embodiment of a battery pack energy balancing method for a layered buck-boost circuit according to an embodiment of the present application; Figure 5 FIG. 1 is a structural diagram of a battery pack energy balancing system with a layered buck-boost circuit according to an embodiment of the present application. DETAILED DESCRIPTION

[0017] In order to enable those skilled in the art to better understand the technical solution of the present application, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0018] The following detailed description of the embodiments of the present application is provided in conjunction with the accompanying drawings and examples. The following detailed description of the embodiments and the accompanying drawings are used to illustrate the principles of the present application, but are not intended to limit the scope of the present application, i.e., the present application is not limited to the described embodiments.

[0019] Refer to the attached Figure 1 As shown, the present embodiment discloses a method for battery pack energy balancing using a layered buck-boost circuit. This embodiment can be implemented based on a system built using a visual simulation and model design tool (e.g., the Simulink simulation platform). Specifically, it includes steps 110-140.

[0020] Step 110 : Divide the battery pack into multiple submodules, and configure intra-group balancing channels and inter-group balancing channels.

[0021] Each submodule includes at least two single cells connected in series.

[0022] In some embodiments, an active balancing circuit connected in parallel to each submodule is configured as an intra-group balancing channel, and a bidirectional energy transfer circuit for connecting adjacent submodules is configured as an inter-group balancing channel.

[0023] For example, refer to the attached Figure 3As shown in the figure, a battery pack with 15 lithium-ion batteries (B1-B15) is used as an example. It includes three submodules, forming a 15-cell series circuit topology model. Each submodule consists of five individual batteries connected end-to-end in positive and negative electrodes (B1-B5, B6-B10, and B11-B15, respectively; B6-B10 are omitted in the figure). Each individual battery is independently configured in parallel with a separate parallel branch. Each parallel branch includes a corresponding switch (Q1-Q18) and / or diode (D1-D18) for each individual battery (B1-B15). The diodes are used to prevent reverse current surges (for example, diodes D1-D16 protect the voltage spikes generated when the corresponding switches M1-M16 are turned off). Each parallel branch also includes a corresponding inductor (L1-L9) for each individual battery (B1-B15), which, in combination with the switch, forms a buck-boost balancing circuit. In addition, each submodule is also configured with an active balancing circuit connected in parallel to each submodule as an intra-group balancing channel. Each intra-group balancing circuit includes its own corresponding switch tube (Q16-Q18) and / or its own corresponding diode (D16-D18) and / or its own corresponding inductor (L9-L10).

[0024] In some embodiments, the intra-group balancing channel and / or the inter-group balancing channel is a hierarchical buck-boost circuit.

[0025] Optionally, the working state of the layered buck-boost circuit is mainly divided into two states: inductor charging and inductor freewheeling.

[0026] This embodiment achieves decentralized management of the battery pack's physical layer by decomposing the battery pack into several independent submodules, each configured as an autonomous control unit. Furthermore, through an innovative buck-boost dual-channel topology, a three-dimensional energy scheduling network is established, from intra-pack voltage balancing to inter-pack power, enabling efficient energy redistribution between cells, submodules, and at the system level.

[0027] Step 120 : Real-time operating condition signals and state of charge signals of each single battery are collected, and the mean state of charge of the battery pack, the range between groups, and the difference between adjacent single batteries are estimated.

[0028] In some embodiments, the real-time operating condition signals of the individual cells include the real-time voltage, current, and temperature signals of the individual cells, and the state of charge value is calculated based on the real-time voltage, current, and temperature signals of the individual cells. Based on the state of charge value, the mean state of charge of the battery pack, the state of charge difference between adjacent individual cells, and the range between packs are determined.

[0029] Step 130 : Based on the fuzzy control algorithm, a balancing current signal is generated according to the state of charge mean of the battery pack, the range between the packs, and the difference between adjacent single cells.

[0030] The balanced current signal includes an intra-group balanced control signal and an inter-group balanced control signal.

[0031] In some embodiments, generating intra-group balancing control signals and inter-group balancing control signals includes: inputting the battery pack's SOC mean and the difference between adjacent cells into an intra-group balancing controller, inputting the battery pack's SOC mean and the inter-group range difference into an inter-group balancing controller, and dynamically adjusting the pulse width modulation (PWM) duty cycle using a fuzzy control algorithm to generate the intra-group balancing control signals and inter-group balancing control signals. Based on this, embodiments of the present application achieve balancing between any individual cells while reducing energy loss caused by electronic components, enabling precise control of balancing current and improving energy transfer efficiency.

[0032] In an exemplary embodiment, the domains of the battery pack state of charge mean and the difference between adjacent single cells input to the intra-group balancing controller are [0, 20%] and [0, 60%] respectively; the domains of the battery pack state of charge mean and the inter-group range input to the inter-group balancing controller are [0, 1] and [0, 10%] respectively.

[0033] In some embodiments, based on a fuzzy control algorithm, a balancing current signal is generated through the average state of charge of the battery pack, the extreme difference between the groups, and the difference between adjacent single cells, including: based on the average state of charge of the battery pack, the extreme difference between the groups, and the difference between adjacent single cells, a pulse width modulation signal for driving a switching device is generated through a fuzzy control algorithm, wherein the pulse width modulation signal includes a first control signal for adjusting the charge and discharge time of the inductor within the group and a second control signal for controlling the on and off of the balancing channel between the groups.

[0034] For example, the input parameter in the inter-group balancing controller (or inter-group balancing fuzzy controller) is the mean value of the battery group and between-group range , output PWM duty cycle and adjust the energy transfer rate between groups. The region is divided into [0, 0.2], [0.2, 0.8], [0.8, 1], and the fuzzy input variable Divided into 3 fuzzy subsets: small (S), medium (M), and large (L). Fuzzy input variables The domain is set to [0, 10], which is divided into five fuzzy subsets: [0, 0.5], [0.5, 1.5], [1.5, 3], [3, 5], and [5, 10], which are defined as VS, S, M, L, and VL respectively. Very big, and It is also very large, which means that the battery power differences between battery packs are large. Therefore, it is necessary to control the PWM duty cycle and use a larger balancing current to reduce the balancing time. and They are calculated by the following formulas: (1) (2) in, Indicates the average state of charge of the entire battery pack. Indicates the extreme value of the battery pack's state of charge. Indicates the current single battery SoC value, and The SoC values ​​represent the maximum and minimum values ​​of the average SoC between battery packs, respectively. For the single-cell balancing strategy, the system input features are: the difference (absolute value) between the average SOC of the battery pack as a whole and the adjacent single-cell SOC, and the SOC difference between the target balanced cells.

[0035] The input parameter in the intra-group balancing (fuzzy) controller is the mean value of the entire battery group. The difference between adjacent batteries , output PWM duty cycle and adjust the balanced current. and The domains are set to [0, 20%] and [0, 60%] respectively. Region division [0, 5], [0, 10], [5, 15], [10, 20], [15, 20], The regions are divided into [0, 5], [0, 10], [5, 15], [10, 20], [15, 60]. The fuzzy variables after conversion are and Corresponding to and , which are divided into 5 fuzzy subsets: very small (VS), small (S), medium (M), large (L), and very large (VL). If Very big, and is also large, which reflects that the battery pack has large differences in power levels among individual cells. Therefore, it is necessary to control the PWM duty cycle and use a larger balancing current to reduce the balancing time. Similarly, this two-dimensional deviation monitoring mechanism provides accurate decision-making basis for the fuzzy controller by quantifying the coupling relationship between overall deviation and local difference. and They are calculated by the following formulas: (3) (4) in, It represents the absolute difference between the average state of charge of the whole battery pack and the average state of charge of the adjacent balanced batteries. Indicates the absolute difference in state of charge of adjacent batteries. and Indicates the battery SoC value of adjacent cells in balancing.

[0036] In some embodiments, the pulse width modulation duty cycle range is [47%, 53%], and the balancing current of the balancing current signal is (0, 2)A. In some embodiments, the defuzzification of the fuzzy control algorithm is performed using the center of gravity method.

[0037] In some embodiments, the pulse width modulation duty cycle is dynamically adjusted using a fuzzy control algorithm, including: dividing the input battery pack state of charge mean, inter-group range, and difference between adjacent single cells into five fuzzy subsets (VS, S, M, L, VL) using a membership function; and calculating the output pulse width modulation duty cycle using the centroid method, using the formula:

[0038] in, is the pulse width modulation duty cycle, is the output variable domain, is the membership function.

[0039] For example, the duty cycle of the control switch adjusts the effect of the balanced current, and the domain of the control switch PWM duty cycle is set to [47, 53], and the corresponding average current domain is (0, 2) A. The balanced current is defined to satisfy the following regional divisions [47, 47.5], [47, 48.7], [47.5, 50], [48.7, 50.7], [50, 53], and the corresponding definitions are VS, S, M, L, VL. When there is a small deviation in the power, a current balance with a smaller duty cycle of 48.7% is used. For large power deviations, a large current fast balance with a duty cycle greater than 50.7% is used. Based on this, the embodiment of the present application can have a two-dimensional deviation monitoring mechanism, which provides an accurate decision-making basis for the fuzzy controller by quantifying the coupling relationship between the overall deviation and the local difference.

[0040] Step 140 , energy transfer between adjacent single cells is achieved through intra-group balancing control signals and intra-group balancing channels, and cross-group energy scheduling between multiple sub-modules is achieved through inter-group balancing control signals and the cross-group inductor module of the inter-group balancing channel, so as to achieve battery energy balancing in layers.

[0041] In some embodiments, layered battery energy balancing includes: when the battery pack is in a static state, the intra-group balancing channel and the inter-group balancing channel work together, and the battery energy transmission path is shortened by 30% compared to the transmission path when the intra-group balancing channel and the inter-group balancing channel do not work together; when the battery pack is in a charging state, the first stage of controlling battery energy balancing is switched to the state of charge balancing control stage, and the second stage of controlling battery energy balancing is switched to the voltage balancing control stage; when the battery pack is in a discharging state, when the extreme difference value is greater than 2%, the battery energy balancing is controlled to trigger a high current balancing mode (duty cycle greater than 50.7%), and when the extreme difference value is less than 0.5%, the battery energy balancing is controlled to switch to a maintenance mode (duty cycle ≤ 48.7%).

[0042] In some embodiments, the step-by-step balancing strategy under charging state includes: when the battery pack is in charging state, introducing a balancing current adaptive attenuation mechanism in the second stage to automatically reduce the balancing current intensity when the single cell voltage approaches the threshold voltage, so as to avoid overcharging damage through the adaptive attenuation mechanism.

[0043] In some embodiments, the intra-group balancing channel uses a single inductor buck-boost circuit to achieve energy transfer between adjacent single cells; the inter-group balancing channel performs energy cross-level scheduling between multiple sub-modules through a cross-group inductor module.

[0044] This embodiment realizes decentralized management of the physical layer of the battery pack by decomposing the battery pack into several independent sub-modules, each of which is configured as an autonomous control unit. At the same time, through the innovatively designed buck-boost dual-channel topology, a three-dimensional energy scheduling network from intra-group voltage balancing to inter-group power is established, realizing efficient redistribution of energy between single cells, sub-modules and system layers. Combined with the dynamic fuzzy control algorithm, the accuracy of intra-group voltage balancing, inter-group power balancing and dynamic threshold adaptation are improved, realizing multi-dimensional, high-precision battery pack energy balancing management, and achieving the effects of improving battery energy balancing efficiency, optimizing dynamic response speed and reducing battery energy loss. Through the above-mentioned collaborative control, the present application achieves multi-dimensional energy balancing and high-precision control of millisecond-level response of battery packs, reducing the capacity attenuation rate of the battery pack by 42% and increasing the charge and discharge cycle life by 37%.

[0045] Refer to the attached Figure 2 As shown in Figures 2(a)-2(f), 2(a), 2(c), and 2(e) show the charge state changes of each single cell in the energy balancing process of the existing traditional buck-boost battery pack in the three states of rest, charge, and discharge, respectively. Figure 2 (b), 2(d) and 2(f) show the charge state changes of each single cell in the energy balancing process of the layered buck-boost battery pack in the embodiment of the present application under the three states of rest, charge and discharge. Figure 2As shown in (a)-2(f), in order to verify that the battery pack energy balancing control strategy of the layered buck-boost circuit shows significant performance advantages over traditional balancing technology under various working conditions, active balancing is performed in the static state, charging state, and discharging state respectively.

[0046] Refer to the attached Figure 2 As shown in (a) and 2 (b), when simulating that the battery pack is actually in a static state, the embodiment of the present application achieves a breakthrough improvement in the state of charge balancing efficiency through the following technical means: adopting a layered circuit topology structure, the battery pack is decomposed into several independent sub-modules, and the energy transfer range is significantly expanded through the synergistic effect of the intra-group balancing channel and the cross-group balancing channel; based on the fuzzy logic control strategy, the switch duty cycle is dynamically adjusted to make the balancing current accurately match the state of charge distribution characteristics within the battery pack; experimental data show that compared with the traditional single-layer buck-boost circuit balancing scheme, the present application can reduce the state of charge range from 0.92% to 0.68% in 2000 seconds, shorten the range convergence time by 513.2 seconds (a reduction of 37.0%), and reduce the temperature rise during the balancing process by about 28%.

[0047] Refer to the attached Figure 2 As shown in (c) and 2 (d), when the simulated battery pack is actually in a discharge state, the embodiment of the present application achieves dual optimization of balancing efficiency and safety through the following technical means: constructing a dynamically adjustable inter-group balancing channel, combining the inductive energy storage and diode freewheeling characteristics, and realizing cross-group energy redistribution while maintaining output voltage stability; designing a dual-threshold trigger mechanism, automatically switching to a large current balancing mode when the SoC range is greater than 2%, and switching to a maintenance balancing mode when the SoC range is less than 0.5%; test results show that during the discharge process, the SoC range is reduced from 0.97% of the traditional solution to 0.47%, the range convergence time is shortened by 620.7 seconds (a decrease of 43.3%), and the single-cell voltage dispersion at the end of discharge is controlled within 30mV.

[0048] Refer to the attached Figure 2 As shown in Figures 2(e) and 2(f), when the simulated battery pack is actually in a discharge state, in order to address the risks of concentration polarization and lithium plating that are prone to occur during the charging process, the embodiments of the present application achieve efficient balancing and safety protection through the following technical means: a step-by-step balancing strategy is adopted, focusing on state-of-charge balancing in the early stage of charging, and switching to voltage balancing in the later stage of charging to avoid overcharging damage; an innovative "balanced current adaptive attenuation" mechanism is introduced to automatically reduce the balancing intensity when the cell voltage approaches the cut-off voltage; measured data show that the range of the state of charge during the charging stage is reduced from 1.17% of the traditional solution to 0.54%, the range convergence time is shortened by 460.8 seconds (a decrease of 33.3%), and the charging efficiency is improved by about 12%.

[0049] The battery pack energy balancing method of the hierarchical Buck-Boost active balancing system and the hierarchical buck-boost circuit in this application significantly improves the balancing efficiency and performance of lithium battery packs through an innovative composite control architecture. Specifically, it has the following outstanding advantages: This application uses a fuzzy control algorithm to dynamically adjust the balancing strategy in real time, including automatically adjusting the balancing current magnitude and direction based on battery state-of-charge differences. This effectively addresses the inefficiency of traditional balancing methods due to fixed parameters. Through a fuzzy inference mechanism with multiple input variables, the system can accurately identify the imbalance state of the battery pack and make the optimal balancing decision.

[0050] In terms of adaptability, this application verifies the adaptability of the fuzzy control active balancing strategy to different battery states and operating conditions by testing and demonstrating good performance in multiple different states such as charging, discharging, and static.

[0051] In terms of balancing accuracy, this application uses the state of charge as a balancing variable, combined with precise adjustment of the fuzzy controller, to control the difference in the state of charge of each single battery to within 2%. The unique "level-cross-level" balancing mechanism ensures the consistency of the entire battery pack and effectively extends the battery pack life.

[0052] In terms of safety, this application's adaptive balancing strategy intelligently adjusts the balancing intensity based on the battery's operating state (stationary, charging, discharging), preventing damage to the battery caused by excessive balancing current. Furthermore, the robustness of the fuzzy controller ensures stable system operation under various operating conditions.

[0053] This application effectively solves the problems of long balancing paths, low efficiency, and poor adaptability in the existing technology, and provides a more efficient and reliable battery balancing solution for electric vehicles and energy storage systems, with significant economic benefits and application value.

[0054] This application addresses the algorithmic aspect, employing active balancing using a fuzzy control algorithm to achieve energy balance across the battery's state of charge. A multi-channel active balancing strategy is designed to achieve energy balance among individual cells in the battery pack while also providing cross-level scheduling of supplementary energy balance through inter-pack balancing. Analysis and simulation results demonstrate that this topology achieves faster balancing than existing single-layer bust-boost circuits, reducing balancing times by 37%, 43.7%, and 33.3% for stationary, discharging, and charging conditions, respectively, compared to traditional single-layer buck-boost circuits.

[0055] Refer to the attached Figure 3 As shown, the embodiment of the present application also provides a specific implementation process of a battery pack energy balancing method of a layered buck-boost circuit, including: In the process of charging a high-energy battery to a low-energy battery, the buck-boost circuit is in the inductor charging stage. The switch tube is turned on, and the input power is used to charge the inductor. The input power forms a red solid line loop through the switch tube Q1 and the inductor L1. To the inductor Charge, such as Figure 3 The clockwise dotted line loop ① shows this. To avoid magnetic saturation, the discontinuous conduction mode is used.

[0056] The following shows the calculation of single battery according to Kirchhoff's voltage law Voltage:

[0057] in, express The voltage and initial value of the inductor current , L is the inductor, and the inductor current when the switch is turned on is:

[0058] in, r is the resistance of the loop, t For time, Switch on time. The rate of change is:

[0059] Therefore, the current growth rate can be controlled by selecting a suitable inductor. The maximum loop inductance current can be obtained when for:

[0060] When the buck-boost circuit is in the inductor discharge stage, the switch tube Q 1 When the inductor is turned off, it passes through the diode D 1 ,inductance L、 Forming a red solid line loop, the inductor L1 To monomer Charging, such as Figure 3 As shown in the counterclockwise dotted line loop ② in the figure. At this time, the polarity of the input and output are exactly opposite, which can be expressed as:

[0061] in, express MOS The loop current after the tube is closed, is the output side voltage, and the MOS off time is The switching cycle is T , the duty cycle is DThe relationships among the parameters are as follows:

[0062] At this time, there is an equilibrium capacity that satisfies the input period current integration:

[0063] The average current during the equalization process satisfies:

[0064] Adjust the relationship between the MOS conduction time and the period to regulate the output average current to , and then adjust the equalization duration.

[0065] Refer to the appendix Figure 4 As shown, for the convenience of understanding the control logic of the battery energy equalization of the present application, a flowchart of a specific implementation process of a battery pack energy equalization method of a hierarchical buck-boost circuit in an embodiment of the present application is provided. As shown in the appendix Figure 4 As shown, after starting, the system first collects the state of charge data and voltage data of each single battery, and sets the in-group equalization threshold as a, the inter-group equalization threshold as b, and the global condition threshold as , and then calculates the key parameter x according to the above method. Input the key parameter x and determine whether to start equalization: if x < a, end the start program; if x ≥ a, further determine to perform inter-group equalization when x > b, otherwise perform in-group equalization, and the process terminates after equalization is completed. In this embodiment, the priority of battery energy equalization is further controlled by setting hierarchical thresholds, ensuring that the battery pack operates more efficiently and stably. Refer to the appendix Figure 5 As shown, an embodiment of the present application also provides a battery pack energy equalization system 500 for a hierarchical buck-boost circuit, including: a structure building module 510, a battery state monitoring module 520, a control signal generation module 530, and an energy transfer module 540. Among them: The structure building module 510 is used to divide the battery pack into multiple sub-modules, each sub-module includes at least two series-connected single batteries, configure an active equalization circuit connected in parallel to each sub-module as an in-group equalization channel, and configure a bidirectional energy transfer circuit for connecting adjacent sub-modules as an inter-group equalization channel; The battery state monitoring module 520 is used to collect the real-time working condition signals of each single battery in real time, and estimate the average state of charge, the inter-group range, and the difference between adjacent single batteries of the battery pack; The control signal generation module 530 is used to generate an equalization current signal based on a fuzzy control algorithm through the average state of charge, the inter-group range, and the difference between adjacent single batteries of the battery pack, and the equalization current signal includes an in-group equalization control signal and an inter-group equalization control signal; The energy transfer module 540 is used to realize energy transfer between adjacent single cells through the intra-group balancing control signal and the intra-group balancing channel, and to realize cross-level energy scheduling between multiple sub-modules through the inter-group balancing control signal and the cross-group inductor module of the inter-group balancing channel, so as to achieve battery energy balancing in a hierarchical manner.

[0066] In addition, the battery pack energy balancing system 500 for the hierarchical buck-boost circuit may also include an active balancing module. The active balancing module may include a balancing module, a fuzzy control module, a charge-discharge module, or an acquisition and display module, etc., which is used to drive the power switches in the Buck-Boost circuit according to the balancing control signal to achieve energy transfer. The acquisition and display module is used to collect real-time operating condition signals from each single cell, the fuzzy control module is used to host and run the fuzzy control algorithm, the charge-discharge module is used to regulate battery energy in different states, and the balancing module is used to achieve cross-level energy scheduling between multiple submodules and energy transfer between adjacent single cells.

[0067] In some embodiments, the battery pack energy balancing system 500 of the layered buck-boost circuit of the present application also includes a battery status monitoring module for real-time collection of the voltage, current, temperature and charge status signals of each single cell; a processor module for executing the above-mentioned battery pack energy balancing method of the layered buck-boost circuit and calculating the balancing control signal; and a power switch driving module for driving the power switch tube in the buck-boost circuit according to the balancing control signal to realize energy transfer.

[0068] The battery pack energy balancing system of the layered buck-boost circuit of the present application has a double-layer buck-boost circuit topology structure, which breaks through the limitations of traditional adjacent balancing and realizes direct energy transfer between any cells. The coordinated work of intra-group balancing and inter-group balancing greatly shortens the energy transmission path, and increases the balancing speed by more than 30% compared with traditional solutions. The embodiment of the present application can also solve the imbalance problem of lithium battery packs connected in series in electric vehicles and energy storage systems, and realizes a layered topology structure of a double-layer buck-boost circuit. This topology structure can reduce energy loss by reducing the energy propagation path during the balancing process, thereby improving the efficiency and speed of balancing.

[0069] An embodiment of the present application further provides an electric vehicle, a battery pack energy balancing system equipped with a layered buck-boost circuit, and the system is configured to execute the above-mentioned battery pack energy balancing method of the layered buck-boost circuit.

[0070] It is understood that the above embodiments are merely exemplary embodiments for illustrating the principles of the present application, and the present application is not limited thereto. Those skilled in the art may make various modifications and improvements without departing from the spirit and substance of the present application, and such modifications and improvements are also considered to be within the scope of protection of the present application.

Claims

1. A battery pack energy balancing method for a layered buck-boost circuit, characterized in that: include: Divide the battery pack into a plurality of submodules, each submodule comprising at least two single cells connected in series, configure an active balancing circuit connected in parallel to each submodule as an intra-group balancing channel, and configure a bidirectional energy transfer circuit for connecting adjacent submodules as an inter-group balancing channel; Collecting real-time operating condition signals of each of the single cells in real time, and estimating the state of charge mean, inter-group range, and difference between adjacent single cells of the battery pack; Based on a fuzzy control algorithm, a balancing current signal is generated according to the state of charge mean of the battery group, the inter-group range, and the difference between the adjacent single batteries. The balancing current signal includes an intra-group balancing control signal and an inter-group balancing control signal. Energy transfer between adjacent single cells is achieved through the intra-group balancing control signal and the intra-group balancing channel, and cross-level energy scheduling between the multiple sub-modules is achieved through the inter-group balancing control signal and the cross-group inductor module of the inter-group balancing channel, so as to achieve hierarchical battery energy balancing.

2. The method according to claim 1, characterized in that Generating the intra-group balancing control signal and the inter-group balancing control signal includes: The state of charge mean of the battery pack and the difference between the adjacent single cells are input into the intra-group balancing controller, the state of charge mean of the battery pack and the inter-group range difference are input into the inter-group balancing controller, and the pulse width modulation duty cycle is dynamically adjusted through the fuzzy control algorithm to generate the intra-group balancing control signal and the inter-group balancing control signal.

3. The method according to claim 1, characterized in that When the battery pack is in a stationary state, the intra-group balancing channel and the inter-group balancing channel work together; when the battery pack is in a charging state, the first stage of the battery energy balancing is controlled to switch to the state of charge balancing control stage, and the second stage of the battery energy balancing is controlled to switch to the voltage balancing control stage; when the battery pack is in a discharging state, when the range value is greater than 2%, the battery energy balancing is controlled to trigger the high current balancing mode, and when the range value is less than 0.5%, the battery energy balancing is controlled to switch to the maintenance mode.

4. The method according to claim 2, characterized in that The domains of the state of charge mean of the battery group and the difference between the adjacent single cells input to the intra-group balancing controller are [0, 20%] and [0, 60%] respectively; The domains of the state of charge mean of the battery group and the inter-group range input to the inter-group balancing controller are [0, 1] and [0, 10%] respectively; The pulse width modulation duty cycle range is [47%, 53%], and the balancing current of the balancing current signal is (0, 2)A.

5. The method according to claim 2, characterized in that The fuzzy control algorithm is based on which a balancing current signal is generated by using the state of charge mean of the battery pack, the inter-pack range, and the difference between adjacent single cells, including: Based on the state of charge mean of the battery pack, the inter-group range and the difference between adjacent single cells, a pulse width modulation signal driving a switching device is generated by a fuzzy control algorithm. The pulse width modulation signal includes a first control signal for adjusting the charge and discharge time of the inductor within the group and a second control signal for controlling the on and off of the inter-group balancing channel; The defuzzification of the fuzzy control algorithm is performed using the center of gravity method.

6. The method according to claim 3, characterized in that The step-by-step balancing strategy under the charging state includes: When the battery pack is in a charging state, an adaptive attenuation mechanism for balancing current is introduced in the second stage to automatically reduce the balancing current intensity when the cell voltage approaches a threshold voltage, thereby avoiding overcharging damage through the adaptive attenuation mechanism.

7. The method according to claim 3, characterized in that The intra-group balancing channel uses a single-inductor buck-boost circuit to achieve energy transfer between adjacent single cells; The inter-group balancing channel performs cross-level energy scheduling among the multiple sub-modules through the cross-group inductor module.

8. The method according to claim 5, characterized in that The dynamically adjusting the pulse width modulation duty cycle by the fuzzy control algorithm comprises: Dividing the input state of charge mean of the battery pack, the inter-group range, and the difference between the adjacent single cells into five fuzzy subsets (VS, S, M, L, VL) through a membership function; The output pulse width modulation duty cycle is calculated by the center of gravity method, and the formula is: in, is the PWM duty cycle, is the output variable domain, is the membership function.

9. A battery pack energy balancing system with a layered buck-boost circuit, characterized in that: include: A structural building module for dividing the battery pack into multiple submodules, each submodule comprising at least two single cells connected in series, an active balancing circuit connected in parallel to each submodule as an intra-group balancing channel, and a bidirectional energy transfer circuit for connecting adjacent submodules as an inter-group balancing channel; A battery status monitoring module is used to collect real-time operating condition signals of each of the single cells and estimate the mean state of charge of the battery pack, the range between groups, and the difference between adjacent single cells; a control signal generating module, configured to generate a balancing current signal based on a fuzzy control algorithm and the state of charge mean of the battery pack, the inter-pack range, and the difference between adjacent single cells, wherein the balancing current signal includes an intra-pack balancing control signal and an inter-pack balancing control signal; An energy transfer module is configured to implement energy transfer between adjacent single cells through the intra-group balancing control signal and the intra-group balancing channel, and implement cross-level energy scheduling between the multiple sub-modules through the inter-group balancing control signal and the cross-group inductance module of the inter-group balancing channel, so as to achieve hierarchical battery energy balancing.

10. An electric vehicle, equipped with a battery pack energy balancing system with a layered buck-boost circuit, characterized in that: The system is configured to execute the battery pack energy balancing method of the hierarchical buck-boost circuit according to any one of claims 1 to 8.

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