A method and device for controlling SOC balancing and power compensation after battery failure

Abstract

The present invention discloses a method and device for controlling SOC balancing and power compensation after a battery failure, belonging to the field of battery energy storage technology. The method and device specifically include: S1, calculating the power gap, independently setting the target SOC based on the capacity decay of the single battery, calculating the target power in combination with the total load power demand, constructing a cost function for model predictive control, and dynamically adjusting the weight coefficient; S2, establishing a dynamic SOC model based on power update for the remaining normally operating batteries, and recursively predicting the battery SOC change through power input and sampling period; S3, solving the optimal power allocation scheme for the remaining batteries through a rolling optimization algorithm under the constraints of total power balance and the maximum discharge power of the single battery; S4, converting the optimal power allocation scheme into a PWM duty cycle control signal of a bidirectional Buck-Boost converter, and accurately controlling each single battery through a microprocessor. The present invention can achieve accurate distribution and compensation of the power of the entire system after a battery failure.

Description

Technical Field

[0001] The present invention relates to the technical field of battery energy storage, and in particular to a method and device for controlling SOC balancing and power compensation after a battery failure. Background Art

[0002] As the global energy mix shifts toward a low-carbon future, the large-scale deployment of energy storage systems and electric vehicles is placing higher demands on the reliability of battery management systems (BMS). In a battery pack consisting of multiple cells connected in series or parallel, if individual cells fail due to aging, overcharging, or external shock, not only can the system's output power drop sharply, but the SOC distribution of the remaining cells can also become unbalanced, further exacerbating the inconsistency of the battery pack and even leading to safety hazards such as thermal runaway. Therefore, post-failure SOC balancing and power compensation have become core technical challenges to ensure the long life and safe operation of battery packs.

[0003] In the existing technology, traditional battery balancing methods mainly include resistance balancing and dual active full-bridge (DAB) converter control. Resistance balancing achieves SOC balancing through energy-consuming discharge. Its energy loss is proportional to the balancing time, which leads to significant efficiency loss, especially in large-capacity battery packs, and cannot achieve dynamic power compensation. Although DAB converters can achieve bidirectional energy flow through high-frequency transformers, they require complex multi-winding magnetic circuit designs and phase-shifting control strategies. The hardware structure is cumbersome and costly, and the control algorithm is highly complex, making it difficult to meet the requirements of real-time rapid response after battery failure. In addition, none of the above methods fully consider the capacity decay characteristics of individual batteries and cannot dynamically adjust the balancing target according to the remaining capacity of different batteries, resulting in insufficient balancing accuracy and the risk of overcharge / overdischarge.

[0004] In response to the above technical bottlenecks, a control method that is efficient, flexible and robust is urgently needed. Summary of the Invention

[0005] The purpose of the present invention is to provide a method and device for controlling SOC balancing and power compensation after a battery failure, to solve the following technical problems:

[0006] Traditional equalization methods such as resistance equalization and DAB converters have problems of large energy loss or complex hardware.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A method for controlling SOC balancing and power compensation after a battery failure, comprising the following steps:

[0009] S1. Calculate the power gap, set the target SOC independently based on the capacity decay of the single battery, calculate the target power based on the total load power demand, construct the cost function of the model predictive control and dynamically adjust the weight coefficient;

[0010] S2. For the remaining normal working batteries, a dynamic SOC model based on power update is established, and the battery SOC change is predicted recursively through power input and sampling period;

[0011] S3. Under the constraints of total power balance and single battery maximum discharge power, the optimal power allocation scheme for the remaining batteries is solved by a rolling optimization algorithm;

[0012] S4. Convert the target power in the optimal power allocation scheme into a PWM duty cycle control signal of the bidirectional Buck-Boost converter, and implement power dynamic compensation and SOC balancing control of a single battery cell through a microprocessor.

[0013] As a further solution of the present invention: in S1, the power gap is calculated, the target SOC is independently set based on the capacity decay of the single battery, and the target power is calculated in combination with the total load power demand, specifically:

[0014] ;

[0015] Where, is the power gap, is the output power of the jth battery among the faulty batteries;

[0016] Calculate the target SOC of each battery. The target SOC of each battery is set independently based on its capacity decay. The formula is:

[0017] ;

[0018] If the system available power is greater than the total power shortage, SOC balancing is performed, and the formula is:

[0019] ;

[0020] If the system available power is less than the total power deficit, the target SOC needs to be adjusted. The formula is:

[0021] ;

[0022] in, is the calculated target SOC of the j-th battery, is the capacity decay of the jth battery, is the nominal capacity of the jth battery, is the target SOC of the jth battery, is the real-time SOC of the j-th battery:

[0023] The formula for calculating SOC deviation is:

[0024] ;

[0025] The formula for calculating power allocation weight is:

[0026] ;

[0027] The formula for preliminary calculation of power is:

[0028] ;

[0029] like > , then let = , and then readjust, the formula is:

[0030] ;

[0031] in, Assign a power weight to the jth battery, is the sum of the SOC deviations of all batteries, is the total load power requirement of the system, is the ideal output power of the jth battery obtained by MPC solution.

[0032] As a further solution of the present invention: in S1, the cost function of the model predictive control is constructed and the weight coefficient is dynamically adjusted, specifically:

[0033] The expression of the cost function is:

[0034] ;

[0035] in, To predict discrete moments in the time domain, Indicates a battery pack that is functioning normally. is the target SOC, is the ideal output power of the jth battery obtained by MPC solution, and is the weight coefficient;

[0036] The cost function weights α and β dynamically respond to SOC differences and load fluctuations, and the formula is:

[0037] ;

[0038] Where, For the very poor, is the total load power change rate, is the total load power demand of the system;

[0039] Then normalize it, the formula is:

[0040] ;

[0041] Where, , is the final weight.

[0042] As a further solution of the present invention: in S2, for the remaining normally working batteries, a SOC dynamic model based on power update is established, and the battery SOC change is recursively predicted by power input and sampling period, specifically:

[0043] The expression of the battery SOC dynamic model is:

[0044] ;

[0045] in, is the output power of the jth battery at time k, is the SOC of the jth battery at time k, is the real-time voltage of the jth battery, is the battery capacity, Indicates a battery pack that is operating normally. is the sampling period;

[0046] Recursively deducing the expression of the battery SOC dynamic model, we obtain:

[0047] ;

[0048] in, It's prediction time The SOC is calculated based on the power integration of the past moments. is the time index within the prediction interval, and the impact of historical power on SOC is accumulated and calculated.

[0049] As a further solution of the present invention: in S3, under the constraints of total power balance and single battery maximum discharge power, the optimal power allocation scheme for the remaining batteries is solved by a rolling optimization algorithm, specifically:

[0050] Among them, the total power balance constraint formula is:

[0051] ;

[0052] Single battery maximum discharge power constraint formula:

[0053] ;

[0054] The following formula:

[0055] ;

[0056] Substituting into the cost function, we get:

[0057]

[0058] right Find the partial derivative, the goal is to find the optimal power Make Take the minimum value, the expression is:

[0059]

[0060] in, is the cost function for The gradient of , let the gradient be equal to zero, then we get:

[0061]

[0062] Finally obtained And substitute the final weight, then:

[0063] ;

[0064] like > , then let = , then adjust ,in, is the total output power, It is the maximum power of a single battery in normal operation.

[0065] As a further solution of the present invention, in S4, the target power in the optimal power allocation scheme is converted into a PWM duty cycle control signal of the bidirectional Buck-Boost converter, and the power dynamic compensation and SOC balancing control of the single battery are realized by the microprocessor, specifically:

[0066] The Buck-Boost converter includes Boost mode and Buck mode, where the expression of Boost mode is:

[0067] ; ;

[0068] The Buck model expression is:

[0069] ; ;

[0070] in, is the output voltage of the jth battery, is the sampled voltage of the jth battery, is the duty cycle of the jth battery;

[0071] Obtaining the required power through optimization , calculate the duty cycle of the Buck-Boost converter ;

[0072] Further deduction through the power relationship: When using Boost mode, use the Boost formula to calculate :

[0073] ;

[0074] when When using Buck mode, use the Buck formula to calculate :

[0075] ;

[0076] in The j-th battery target power calculated by MPC, The current is sampled for the jth battery, so:

[0077] ;

[0078] Get a single battery , the microprocessor generates PWM signals to control the single-cell Buck-Boost converter to ensure that the output power meets the power compensation requirements while ensuring .

[0079] The present invention also includes a battery failure SOC balancing and power compensation control device, which is used to implement the above-mentioned battery failure SOC balancing and power compensation control method, including:

[0080] The MPC control module is used to build a dynamic battery SOC model and optimize the cost function based on power updates. It also solves the optimal power allocation and the optimal duty cycle of each battery while satisfying the constraints of total power balance and maximum discharge power of each battery.

[0081] Bidirectional Buck-Boost converter module, used to drive power electronic converters through PWM to achieve power regulation.

[0082] Beneficial effects of the present invention:

[0083] After a battery failure occurs and is isolated by a relay or MOSFET, the present invention dynamically models the SOC of the remaining healthy batteries. Combined with model predictive control, a cost function consisting of SOC deviation and power deviation is constructed. The weights are dynamically adjusted based on SOC differences and load fluctuations. Through rolling optimization, the optimal power allocation solution is solved under total power balance and single-cell power constraints. This achieves precise distribution and compensation of overall system power, meeting the total load power demand while gradually aligning the SOC of each battery toward a target value independently set based on capacity decay, thus avoiding overcharging and over-discharging. Simultaneously, through PWM control of a bidirectional Buck-Boost converter, the operating mode is automatically switched based on the input and output voltages of the individual cells, dynamically adjusting the power of each cell. This ensures balanced SOC across each cell while meeting the total output power requirement, achieving precise control of each cell. Compared to traditional resistance balancing and dual-active full-bridge control methods, this solution offers advantages such as high energy utilization, fine control granularity, and simple hardware structure. Furthermore, through rapid post-fault power reconstruction, single-cell power constraints, and dynamic compensation mechanisms, it effectively mitigates battery pack inconsistencies, improves system safety and reliability after a fault, and significantly extends the overall battery pack service life. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] The present invention will be further described below with reference to the accompanying drawings.

[0085] Figure 1 This is a flow chart of a method for controlling SOC balancing and power compensation after a battery failure according to the present invention;

[0086] Figure 2 It is a structural diagram of the bidirectional Buck-Boost converter of the present invention. DETAILED DESCRIPTION

[0087] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0088] Example 1

[0089] See also Figure 1 As shown, this embodiment is a method for controlling SOC balancing and power compensation after a battery failure, specifically including:

[0090] The energy storage system consists of 4 lithium batteries with a nominal capacity of =100Ah, where the fault of the third battery is isolated and the remaining battery parameters are:

[0091] B1's SOC=88%, =0.2Ah, =600W, V=47V;

[0092] B2's SOC=75%, =0.5Ah, =600W, V=46V;

[0093] B4's SOC=92%, =0.3Ah, =600W, V=50V;

[0094] Operating conditions:

[0095] Total load power demand: =1.0kW;

[0096] Faulty battery power shortage: =300w;

[0097] Total available power: =3×600W=1.8kW;

[0098] Step 1: After a single cell in the energy storage system battery pack fails, the faulty cell is promptly short-circuited and isolated through a relay or MOSFET.

[0099] Step 2: Total power shortage: ;

[0100] Total available power: ; The power redundancy rate is 38.5%, which is significantly sufficient.

[0101] Calculate SOC deviation:

[0102] ;

[0103] Calculate the power allocation weight:

[0104] ;

[0105] Preliminary calculation of power:

[0106] .

[0107] Step 3: Construct the cost function:

[0108] ;

[0109] Discretize and calculate weights:

[0110] ;

[0111] Then normalize:

[0112] .

[0113] Step 4: Substitute and solve the battery SOC dynamic model expression with power update:

[0114] ;

[0115] The expression of the battery SOC dynamic model is recursively deduced:

[0116] ;

[0117] Substituting into the cost function we get:

[0118]

[0119] right Find the partial derivative, the goal is to find the optimal power Make Take the minimum value:

[0120]

[0121] in, is the cost function for The gradient of , let the gradient be equal to zero:

[0122]

[0123] Finally obtained And substitute the final weights:

[0124] .

[0125] Step 5: Calculate the duty cycle. B1 and B2 are boost mode, and B4 is buck mode.

[0126] Boost Mode:

[0127] ;

[0128] ;

[0129] ;

[0130] Buck mode:

[0131] ;

[0132] ;

[0133] ;

[0134] therefore:

[0135] ;

[0136] The optimal duty cycle is obtained so that the system can ensure SOC balance while meeting power compensation requirements.

[0137] In this embodiment, when a single cell in the energy storage system battery pack fails, resulting in insufficient output power and unbalanced SOC, the optimal single cell phase-shift duty cycle of the bidirectional Buck-Boost converter in the system is obtained through model prediction and continuously optimized, so that the power output on the AC side remains stable and the SOC is balanced, maintaining normal system operation.

[0138] Example 2

[0139] This embodiment is a device that uses the above-mentioned SOC balancing and power compensation control method after a battery failure, specifically including:

[0140] The MPC control module is used to build a battery SOC dynamic model based on power updates, construct an optimization cost function, and solve the optimal power allocation plan through rolling optimization under the conditions of satisfying the total power balance and the maximum discharge power constraints of a single battery, and further calculate the optimal duty cycle of a single battery.

[0141] The bidirectional Buck-Boost converter module is used to achieve power regulation through PWM driving of the power electronic converter, ensuring that the output of each single battery meets the power compensation requirements.

[0142] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters and thresholds in the formulas are set by technicians in this field according to actual conditions.

[0143] The above embodiments can be implemented in whole or in part via software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When loaded or executed on a computer, the processes or functions described in the embodiments of this application are fully or partially performed. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired means (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server or data center that contains a collection of one or more available media. The available medium can be magnetic media (e.g., floppy disks, hard disks, tapes), optical media (e.g., DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0144] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0145] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and modules described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0146] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules is only a logical function division. In actual implementation, there may be other division methods, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0147] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected to achieve the purpose of this embodiment according to actual needs.

[0148] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0149] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0150] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0151] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for controlling SOC balancing and power compensation after a battery failure, characterized in that: The following steps are involved: S1. Calculate the power gap, set the target SOC independently based on the capacity decay of the single battery, calculate the target power based on the deviation between the target SOC and the actual SOC, and combine the total load power demand, construct the cost function of the model predictive control and dynamically adjust the weight coefficient; The cost function of constructing model predictive control and dynamically adjusting the weight coefficient includes: The expression of the cost function is: ； in, To predict discrete moments in the time domain, Indicates a battery pack that is operating normally. is the target SOC of the jth battery, is the SOC at predicted time i, is the output power of the jth battery at predicted time i, is the target power of the jth battery, and is the weight coefficient; S2. For the remaining normal working batteries, a dynamic SOC model based on power update is established, and the battery SOC change is predicted recursively through power input and sampling period; S3. Under the constraints of total power balance and single battery maximum discharge power, the optimal power allocation scheme for the remaining batteries is solved by a rolling optimization algorithm; S4. Convert the target power in the optimal power allocation scheme into a PWM duty cycle control signal of the bidirectional Buck-Boost converter, and implement power dynamic compensation and SOC balancing control of a single battery cell through a microprocessor.

2. The method for controlling SOC balancing and power compensation after a battery failure according to claim 1, characterized in that: In S1, the power gap is calculated, the target SOC is independently set based on the capacity decay of the single battery, and the target power is calculated in combination with the total load power demand, specifically: ； Where, is the power gap, is the output power of the jth battery among the faulty batteries; Calculate the target SOC of each battery. The target SOC of each battery is set independently based on its capacity decay. The formula is: ； If the system available power is greater than the total power gap, SOC balancing is performed, and the formula is: ； If the system available power is less than the total power gap, the target SOC needs to be adjusted. The formula is: ； in, is the calculated target SOC of the j-th battery, is the capacity decay of the jth battery, is the nominal capacity of the jth battery, is the target SOC of the jth battery, is the real-time SOC of the j-th battery: The formula for calculating SOC deviation is: ； The formula for calculating power allocation weight is: ； The formula for preliminary calculation of target power is: ； like , then let , and then readjust, the formula is: ； in, Assign a power weight to the jth battery, is the sum of the SOC deviations of all batteries, is the total load power requirement of the system, is the target power of the jth battery.

3. The method for controlling SOC equalization and power compensation after a battery failure according to claim 2, characterized in that: The dynamic adjustment weight coefficient includes: The cost function weights α and β dynamically respond to SOC differences and load fluctuations, and the formula is: ； Where, is the difference between the maximum SOC value and the minimum SOC value, is the total load power change rate, is the total load power demand of the system; Then normalize it, the formula is: ； Where, , is the final weight.

4. The method for controlling SOC balancing and power compensation after a battery failure according to claim 1, characterized in that: In S2, for the remaining normal working batteries, a SOC dynamic model based on power update is established, and the battery SOC change is recursively predicted through power input and sampling period, specifically: The expression of the battery SOC dynamic model is: ； in, is the output power of the jth battery at time k, is the SOC of the jth battery at time k, is the real-time voltage of the jth battery, is the battery capacity, Indicates a battery pack that is operating normally. is the sampling period; Recursively deducing the expression of the battery SOC dynamic model, we obtain: ； in, It's prediction time The SOC is calculated based on the power integration of the past moments. is the time index within the prediction interval, and the impact of historical power on SOC is accumulated and calculated.

5. The method for controlling SOC balancing and power compensation after a battery failure according to claim 3, characterized in that: In S3, under the constraints of total power balance and single battery maximum discharge power, the optimal power allocation scheme for the remaining batteries is solved by a rolling optimization algorithm, specifically: like , then let , then adjust ,in, is the total load power requirement of the system, The maximum power of a single battery in normal operation. is the real-time voltage of the jth battery, is the battery capacity, Indicates a properly functioning battery pack.

6. The method for controlling SOC balancing and power compensation after a battery failure according to claim 1, characterized in that: In S4, the target power in the optimal power allocation scheme is converted into a PWM duty cycle control signal of the bidirectional Buck-Boost converter, and the power dynamic compensation and SOC balancing control of the single battery are realized by the microprocessor, specifically: The Buck-Boost converter includes Boost mode and Buck mode, where the expression of Boost mode is: ； ； The Buck model expression is: ； ； in, is the output voltage of the jth battery, is the sampled voltage of the jth battery, is the duty cycle of the jth battery; Obtaining the required power through optimization , calculate the duty cycle of the Buck-Boost converter ; Further deduction through the power relationship: When using Boost mode, use the Boost formula to calculate : ； when When using Buck mode, use the Buck formula to calculate : ； in The j-th battery target power calculated by MPC, The current is sampled for the jth battery, so: Get a single battery , the microprocessor generates PWM signals to control the single-cell Buck-Boost converter to ensure that the output power meets the power compensation requirements while ensuring .

7. A battery failure SOC equalization and power compensation control device, used to implement the battery failure SOC equalization and power compensation control method according to any one of claims 1 to 6, characterized in that: include: The MPC control module is used to build a dynamic battery SOC model and optimize the cost function based on power updates. It also solves the optimal power allocation and the optimal duty cycle of each battery while satisfying the constraints of total power balance and maximum discharge power of each battery. Bidirectional Buck-Boost converter module, used to drive power electronic converters through PWM to achieve power regulation.

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