A method for controlling energy storage battery pack balance

Abstract

The present invention relates to the field of energy storage technology, and more particularly to a method for balancing control of energy storage battery packs. This method addresses the optimization of energy storage battery pack state inconsistencies and balancing control systems, designing a balancing control method based on decoupling and rapid disturbance suppression technology. Based on the balancing topology of the energy storage battery pack, this method constructs a system balancing control model, seeks the optimal balancing target, and adjusts the balancing current in real time. This method rationally optimizes control response time, effectively suppresses system disturbances caused by model mismatch, and achieves consistent state of charge for the energy storage battery pack. This method is of great value in improving battery balancing efficiency, improving battery performance, and maintaining battery life.

Description

Technical Field

[0001] The present invention relates to the field of energy storage technology, and in particular to a method for balancing and controlling an energy storage battery pack. Background Art

[0002] In recent years, battery energy storage systems have been widely used in various industries, including power transmission and distribution and new energy vehicles, playing a vital role. Energy storage batteries are often composed of multiple cells connected in series or parallel. Due to differences in battery manufacturing processes and actual usage, cell voltage, state of charge (SOC), and battery degradation rates are inconsistent, limiting the overall usable capacity of the battery pack. Balancing management is an effective method to improve battery inconsistencies, enhance battery performance, and maintain battery life.

[0003] Cell balancing management is based on the battery pack system topology and employs balancing control methods to dissipate or transfer battery energy, achieving a consistent battery pack state. During balancing control, the state of charge of each cell is determined by the currents flowing through multiple balancing links in the system. This leads to a coupled relationship between the battery pack SOC and the system balancing current. Using a decoupled, single-loop control approach results in a complex system control structure and cumbersome parameter tuning.

[0004] Existing balancing control strategies often employ a SOC-based mean comparison method. This method calculates the average SOC value of the battery pack and controls battery charging and discharging based on the difference between the actual individual battery state of charge and the mean. This method is simple to operate and can achieve battery pack SOC balancing, but it is difficult to optimize dynamic processes such as balancing time.

[0005] Furthermore, existing balancing control methods often use a generic battery model based on the topology of the battery pack system. However, in actual use, due to variations in battery manufacturing processes and aging, deviations often exist between the actual model and the theoretical model, leading to battery pack model mismatch and thus affecting the performance of advanced model-based control methods. If the deviation caused by system model mismatch can be treated as a disturbance and compensated for, it is expected that balancing control performance will be improved. Summary of the Invention

[0006] The present invention provides a method for balancing control of an energy storage battery pack, which adopts decoupling and rapid disturbance suppression technology to significantly improve the dynamic performance of the balancing control process of the battery pack.

[0007] In order to achieve the purpose of the present invention, the technical solution adopted is: a method for balancing and controlling an energy storage battery pack, comprising the following steps:

[0008] 1) Real-time collection of the voltage and current of each single cell in the energy storage battery pack, and calculation of the state of charge (SOC) of each single cell i, where i = 1, 2, ..., n, and n is the total number of single cells;

[0009] 2) State of charge (SOC) of single battery i Normalize it with the real-time balancing current to obtain the normalized state of charge x i and balancing current u j , where j = 1, 2, ..., m, and m is the total number of balanced links;

[0010] 3) Based on the known topology of the energy storage battery pack balancing system, construct the normalized state of charge x i and balancing current u j The equilibrium system model between:

[0011]

[0012] In formula 1, x(t)=[x1(t),x2(t),…,x n (t)] T is the state of charge of the energy storage battery pack at time t, u(t)=[u1(t),u2(t),…,u m (t)] T is the balancing current of the energy storage battery pack at time t, Indicates the nominal capacity of the energy storage battery pack. is the nominal capacity of each single battery, Q u =diag{I L1 ,I L2 ,…,I Lm} represents the maximum current of the energy storage battery pack balancing system, I Lj is the maximum current on each balancing link, T represents the topological relationship between each single battery and the balancing link, where Q x , Q u , T constitutes the equilibrium system model describing the relationship between x(t) and u(t);

[0013] 4) Design a decoupling controller based on the topology of the energy storage battery pack balancing system to adjust the balancing current;

[0014] 5) For the mismatch of the balanced system model, the mismatch is regarded as a disturbance and a disturbance compensator is designed to compensate the balanced current u of each loop. j '(k):

[0015] u j '(k)=u j (k)+δ j (k) Formula 2

[0016] In formula 2, u j (k) is the balanced current output by the decoupling controller, δj (k) is the disturbance estimate;

[0017]

[0018] In formula 3, P j (z) is the low-pass filter function in the z domain, x j (k) is the discretized battery state of charge, G j (z) is u j (k) for x j (k) Transfer function of the equilibrium system model under action;

[0019] 6) Adjust the balancing current in real time, update the charge status of each single cell, and perform balancing control on the energy storage battery pack in a timely manner.

[0020] As an optimization solution of the present invention, in step 1), the state of charge (SOC) of each single cell is calculated using the ampere-hour integration method or the open circuit voltage method. i .

[0021] As an optimization solution of the present invention, in step 2), the normalized state of charge x i and balancing current u j Calculate according to the following formula:

[0022]

[0023]

[0024] In formula 4, is the nominal capacity of the battery, x i ∈[0,1]; In formula 5, I j is the real-time balancing current, I Lj is the maximum balancing current, u j ∈[-1,1].

[0025] As an optimization solution of the present invention, the decoupling control method of the decoupling controller is as follows:

[0026] (1) Discrete equilibrium system model can be expressed as:

[0027] x(k+1)=x(k)+Bu(k)+w(k) Formula 6

[0028] In formula 6, the discretization of x(t) can be expressed as x(k) = [x1(k), x2(k),…, x n (k)] T , u(t) can be discretized as u(k)=[u1(k),u2(k),…,u n (k)] T , T s is the sampling period, w(k) is the equilibrium system disturbance;

[0029] (2) Calculate the set value of the balancing system output, that is, the battery pack charge state after balancing is completed

[0030]

[0031]

[0032] In formula 8, x i (0) is the initial state of charge of each single battery, x r is the average of the initial state of charge values ​​of the battery pack;

[0033] (3) The controlled balanced current is solved by rolling optimization, and the optimization objective function is:

[0034]

[0035] In Formula 9, P is the prediction time domain, M is the control time domain, q is the weight coefficient of the control term, and Δu is the change in the controlled balancing current.

[0036] This invention has positive effects: it utilizes decoupling and rapid disturbance suppression techniques to improve the performance of the balancing control process for energy storage battery packs. This method seeks the optimal balancing target, adjusts the balancing current in real time, optimizes control response time, and achieves consistent state of charge for the energy storage battery pack. Furthermore, by compensating for mismatches in the battery pack balancing system model, it effectively mitigates the impact of system model mismatches on control performance. This is of great value in improving battery balancing efficiency, enhancing battery performance, and maintaining battery life. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0038] Figure 1 This is a block diagram of a method for controlling energy storage battery pack balance according to the present invention;

[0039] Figure 2 This is a topological diagram of a battery pack system according to an embodiment of the present invention;

[0040] Figure 3 1 is a diagram showing the state of charge equalization result of the energy storage battery pack based on decoupling control in an embodiment of the present invention;

[0041] Figure 4 This is a diagram of the state of charge balancing result of the energy storage battery pack based on the decoupling and rapid disturbance suppression technology in an embodiment of the present invention. DETAILED DESCRIPTION

[0042] The present invention is further described below with reference to the accompanying drawings and specific embodiments. A specific operational process illustrates the effectiveness of this method in controlling the state of charge balance of an energy storage battery pack. This implementation example is based on the technical solution of the present invention, but the scope of protection of the present invention is not limited to the following embodiments.

[0043] like Figure 1-2 As shown, a certain energy storage battery pack is based on a Buck-Boost balancing topology. It uses a PWM wave input level signal to control the on and off of switches to enable cell balancing, thereby achieving energy transfer between cells. To optimize the balancing control effect and improve the cell balancing efficiency, it was decided to adopt the technology of the present invention for balancing control management. The specific process is as follows:

[0044] 1. Real-time collection of the voltage and current of each single cell in the energy storage battery pack, and calculation of the state of charge (SOC) of each single cell using the ampere-hour integration method or the open circuit voltage method. i , i=1,2,3,4, where Table 1 shows the battery related parameter indicators.

[0045] Table 1 Battery related parameters

[0046] name Value (unit) Nominal capacity 2600 / mAh Nominal voltage 3.7 / V Maximum balancing current 2 / A Balancing inductor 22 / uH Switching frequency 50 / kHz Maximum duty cycle 45％

[0047] 2. Perform normalization preprocessing on the state of charge of the single battery and the real-time balancing current. The normalized state of charge x i and balancing current u j , (j=1,2,3,4) is calculated according to the following formula:

[0048]

[0049]

[0050] Where, is the nominal capacity of each single battery, x i ∈[0,1],I j is the real-time balancing current, I Lj is the maximum current on each balanced link, u j ∈[-1,1].

[0051] 3. Based on Figure 2 The Buck-Boost balancing topology of the energy storage battery system shown in the figure is used to construct the normalized battery pack state of charge x i and balancing current u j The equilibrium system model between:

[0052]

[0053]

[0054] Where x(t) = [x1(t), x2(t), x3(t), x4(t)] T ,u(t)=[u1(t),u2(t),u3(t),u4(t)] T , Indicates the nominal capacity of the energy storage battery pack, Q u =diag{I L1 ,I L2 ,I L3 ,I L4} represents the maximum current of the energy storage battery pack balancing system, and T represents the topological relationship between each single battery and the balancing link.

[0055] 4. Design is based on Figure 1 The decoupling controller of the energy storage battery group balancing system shown adjusts the balancing current. The decoupling control algorithm based on the energy storage battery group balancing system is as follows:

[0056] (1) Discrete equilibrium system model can be expressed as:

[0057] x(k+1)=x(k)+Bu(k)+w(k)

[0058] Where x(k) = [x1(k), x2(k), x3(k), x4(k)] T ,u(k)=[u1(k),u2(k),u3(k),u4(k)] T , T s =1 is the sampling period, w(k) is the equilibrium system disturbance;

[0059] 2) Calculate the set value of the balancing system output, that is, the battery pack charge state after balancing is completed Expressed as:

[0060]

[0061]

[0062] Where x i (0) is the normalized initial state of charge value of each single battery, which is 0.77, 0.75, 0.70 and 0.66 respectively;

[0063] 3) The controlled balancing current u(k) is solved by rolling optimization, and its optimization index is expressed as:

[0064]

[0065] Wherein, the prediction time domain P=5, the control time domain M=1, the weight coefficient of the control item q=0.1, and Δu is the change of the controlled balancing current.

[0066] 5. For the mismatch of the balanced system model, treat the mismatch as a disturbance and design a disturbance compensator to compensate for the balanced current u of the controlled loop of the system. j '(k). Since the balancing system model of each single battery is the same, the balancing current u of the system controlled loop j '(k) is expressed as:

[0067] u j '(k)=u j (k)+δ j (k),

[0068]

[0069] Where u j (k) is the balanced current output by the decoupling controller, δ j (k) is the disturbance estimate, is the filter model, for u j (k) for x j (k) Transfer function of the equilibrium system model under the action of.

[0070] 6. Adjust the balancing current in real time, update the charge status of each single cell, and perform balancing control on the energy storage battery pack in time.

[0071] like Figure 3 、 Figure 4 The figure shows the effect of different control methods on the balancing of the energy storage battery pack. Both control methods can achieve consistent state of charge for the energy storage battery pack. By comparing the time response of the energy storage battery pack balancing system, the dynamic characteristics of the energy storage battery pack balancing system with different control methods are further analyzed. The results are shown in Table 2.

[0072] Table 2 Dynamic characteristics of energy storage battery pack balancing system under different control methods

[0073] Control methods Time response / s Decoupling control 300 Decoupling and rapid disturbance suppression technology 250

[0074] As shown in Table 2, the energy storage battery pack SOC balancing control based on decoupling and rapid disturbance suppression technology has a shorter response time and better dynamic characteristics. This method effectively suppresses system disturbances during the balancing process, compensates for the balancing current, optimizes the battery pack balancing response time, and achieves consistent SOC.

[0075] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific embodiments of the present invention and are 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 energy storage battery pack balance, characterized in that: The steps include: 1) Real-time collection of the voltage and current of each single cell in the energy storage battery pack, and calculation of the state of charge (SOC) of each single cell i , where i = 1, 2, ..., n, and n is the total number of single cells; 2) State of charge (SOC) of single battery i Normalize it with the real-time balancing current to obtain the normalized state of charge x i and balancing current u j , where j = 1, 2, ..., m, and m is the total number of balanced links; 3) Based on the known topology of the energy storage battery pack balancing system, construct the normalized state of charge x i and balancing current u j The equilibrium system model between: In formula 1, x(t)=[x1(t),x2(t),…,x n (t)] T is the state of charge of the energy storage battery pack at time t, u(t)=[u1(t),u2(t),…,u m (t)] T is the balancing current of the energy storage battery pack at time t, Indicates the nominal capacity of the energy storage battery pack. is the nominal capacity of each single battery, Q u =diag{I L1 ,I L2 ,…,I Lm } represents the maximum current of the energy storage battery pack balancing system, I Lj is the maximum current on each balancing link, T represents the topological relationship between each single battery and the balancing link, where Q x , Q u , T constitutes the equilibrium system model describing the relationship between x(t) and u(t); 4) Design a decoupling controller based on the topology of the energy storage battery pack balancing system to adjust the balancing current; 5) For the mismatch of the balanced system model, the mismatch is regarded as a disturbance and a disturbance compensator is designed to compensate the balanced current u of each loop. j '(k): u j u(k) = u j (k) + δ j (k) Formula 2 In formula 2, u j (k) is the balanced current output by the decoupling controller, δ j (k) is the disturbance estimate; In formula 3, P j (z) is the low-pass filter function in the z domain, x j (k) is the discretized battery state of charge, G j (z) is u j (k) for x j (k) Transfer function of the equilibrium system model under action; 6) Adjust the balancing current in real time, update the charge status of each single cell, and perform balancing control on the energy storage battery pack in a timely manner.

2. The energy storage battery pack balancing control method according to claim 1, characterized in that: In step 1), the state of charge (SOC) of each battery cell is calculated using the ampere-hour integration method or the open circuit voltage method. i .

3. The energy storage battery pack balancing control method according to claim 2, characterized in that: In step 2), the normalized state of charge x i and balancing current u j Calculate according to the following formula: In formula 4, is the nominal capacity of each single battery, x i ∈[0,1]; In formula 5, I j is the real-time balancing current, I Lj is the maximum current on each balanced link, u j ∈[-1,1].

4. The energy storage battery pack balancing control method according to claim 3, characterized in that: The decoupling control method of the decoupling controller is as follows: (1) The energy storage battery group balancing system model is discretized, and the discretized balancing system model is expressed as: x(k+1)=x(k)+Bu(k)+w(k) Formula 6 In formula 6, the discretization of x(t) can be expressed as x(k) = [x1(k), x2(k),…, x n (k)] T , u(t) can be discretized as u(k)=[u1(k),u2(k),…,u n (k)] T , T s is the sampling period, w(k) is the equilibrium system disturbance; (2) Calculate the set value of the balancing system output, that is, the battery pack charge state after balancing is completed In formula 8, x i (0) is the initial state of charge of each single battery, x r is the average of the initial state of charge values ​​of the battery pack; (3) The controlled balanced current is solved by rolling optimization, and the optimization objective function is: In Formula 9, P is the prediction time domain, M is the control time domain, q is the weight coefficient of the control term, and Δu is the change in the controlled balancing current.

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