A method and system for temperature control during the formation process of lead-acid battery plates

Abstract

This invention provides a temperature control method and system for the formation process of lead-acid battery plates, relating to the field of lead-acid battery technology. The invention employs an MPC algorithm, enabling precise tracking of the target current trajectory and providing a stable control foundation for the formation process. Regarding temperature control, by real-time monitoring of the electrolyte temperature to ultimately adjust the power supply, the electrolyte temperature can be effectively maintained within the optimal formation range. Its unique rolling optimization mechanism endows the system with excellent anti-interference capabilities, maintaining stable operation even under complex conditions. Simultaneously, the adaptive adjustment function based on real-time temperature monitoring data allows the system to dynamically optimize control parameters, continuously improving control performance. The established temperature feedback-based closed-loop power supply control achieves automatic adjustment of the electrolyte temperature, significantly improving the stability and reliability of the formation process, and providing a theoretical basis and technical support for the optimization of lead-acid battery manufacturing processes.

Description

Technical Field

[0001] This invention relates to the field of lead-acid battery technology, and specifically to a temperature control method and system for the electrode formation process of lead-acid batteries. Background Technology

[0002] Currently, in the battery manufacturing process, the initially cured and dried plates are mainly composed of substances such as PbO, 3PbOPbSO4H2O, 4PbOPbSO4, PbSO4, PbOPbSO4, and Pb. In these initial plates, the positive electrode basically contains no PbO2, a discharge-capable active material, and the negative electrode also contains a small amount of Pb, making effective discharge impossible. To address these issues, an electrochemical process is needed to form the plates. This involves connecting the positive plate to the positive terminal of the power supply and the negative plate to the negative terminal in a dilute sulfuric acid electrolyte. This process transforms the lead paste on the positive plate into a substance primarily composed of PbO2, and the lead paste on the negative plate into a substance primarily composed of spongy lead. This process is essentially a transformation of the plates from "raw" to "ripe," also known as an "activation" process.

[0003] Currently, two main formation methods are used: one is tank formation, where positive and negative plates are connected alternately in a dedicated formation tank, then connected to a DC power supply, and electrolyte is injected for energization; the other is battery formation, where the plates are assembled into an electrode group, placed in a battery casing, and electrolyte is injected for energization. However, tank formation suffers from acid mist pollution and requires additional plate washing and drying procedures. While battery formation can avoid these problems, systematic research on formation process parameters is still lacking. Therefore, optimizing plate formation process parameters to improve formation efficiency has become a critical issue that urgently needs to be addressed. Summary of the Invention

[0004] The purpose of this invention is to provide a temperature control method and system for the electrode formation process of lead-acid batteries, which can realize automatic adjustment of electrolyte temperature, significantly improve the stability and reliability of the formation process, and provide a theoretical basis and technical support for the optimization of lead-acid battery manufacturing process.

[0005] To achieve the above objectives, the present invention provides a temperature control method for the electrode formation process of a lead-acid battery, comprising: Establish a power-current model for the plate formation process of lead-acid batteries; Determine the target power supply based on the given target current and power supply-current model; The state equation for predicting electrolyte temperature is obtained based on the heat balance equation of the formation tank. The electrolyte temperature is collected in real time, and a model predictive control algorithm is used to optimize and solve the state equation for electrolyte temperature prediction at each sampling time, and output the optimal power supply change at each sampling time. Based on the optimal power supply change and the target power supply, the optimal power supply at each sampling moment is obtained, thereby realizing closed-loop control of power supply based on electrolyte temperature feedback.

[0006] According to the temperature control method for the electrode formation process of a lead-acid battery provided by the present invention, the power supply-current model is as follows: P = (2 + 0.02t)I + (0.3e) -t / 15 )I 2 Where P is the power supply, t is the time, I is the current passing through the formation tank, and e is the base of the natural logarithm. According to the temperature control method for the formation process of lead-acid battery plates provided by the present invention, the formula for calculating the target power supply is as follows:

[0007] Among them, P ref For the target power supply, I ref The target current. According to the temperature control method for the formation process of lead-acid battery plates provided by the present invention, the heat balance equation of the formation tank is as follows:

[0008] Where m is the mass of the electrolyte, C p Let be the specific heat capacity of the electrolyte, η be the power-to-thermal conversion efficiency coefficient, P(t) be the power supplied at time t, T(t) be the electrolyte temperature at time t, h be the overall heat transfer coefficient, A be the effective heat dissipation area, and T be the total heat dissipation area. water This refers to the water bath temperature. According to the temperature control method for the electrode formation process of a lead-acid battery provided by the present invention, the electrolyte temperature prediction state equation is as follows:

[0009] Where T(k+1) is the electrolyte temperature at time k+1, T s At time k, T(k) is the electrolyte temperature at time k, and P(k) is the power supply at time k. According to the temperature control method for the electrode formation process of a lead-acid battery provided by the present invention, the objective function for optimization is:

[0010] Where, N p For prediction in the time domain; N cTo control the time domain; T ref ΔP(k+i|k) represents the target reference temperature; T(k+i|k) represents the predicted temperature at time k+i; ΔP(k+i|k) represents the change in power supply at time k+i; Q is the state weight matrix; R is the control weight matrix. According to the present invention, a temperature control method for the electrode formation process of a lead-acid battery is provided, where 10 ≤ N p ≤20, 3≤N c ≤5. According to the temperature control method for the electrode formation process of a lead-acid battery provided by the present invention, the constraints for optimization include input constraints and state constraints. The input constraints include power supply amplitude constraints and power supply change constraints, and the state constraints include current constraints and electrolyte temperature constraints. According to the present invention, a temperature control method for the electrode formation process of a lead-acid battery is provided, wherein the state constraints specifically include: When 0 < k ≤ 8h, the current passing through the formation tank at time k is less than or equal to the maximum allowable current. When 8 < k ≤ 32h, 10℃ ≤ T(k) ≤ 45℃. Secondly, the present invention provides a temperature control system for the electrode formation process of a lead-acid battery, comprising: A module was created to establish a power-current model for the formation process of lead-acid battery plates. The determination module is used to determine the target power supply based on a given target current and power supply-current model; The prediction module is used to obtain the electrolyte temperature prediction equation based on the heat balance equation of the formation tank. The solution module is used to collect electrolyte temperature in real time and use model predictive control algorithm to optimize the state equation for electrolyte temperature prediction at each sampling time, and output the optimal power supply change at each sampling time. The control module is used to obtain the optimal power supply at each sampling moment based on the optimal power supply change and the target power supply, thereby realizing closed-loop control of power supply based on electrolyte temperature feedback. This invention has at least the following technical effects: This invention provides a temperature control method and system for the formation process of lead-acid battery plates. Employing an MPC algorithm, it can accurately track the target current trajectory, providing a stable control foundation for the formation process. In terms of temperature control, by real-time monitoring of the electrolyte temperature to ultimately adjust the power supply, the electrolyte temperature can be effectively maintained within the optimal formation range (10℃-45℃), with a preferred control temperature of 40℃. Its unique rolling optimization mechanism endows the system with excellent anti-interference capabilities, maintaining stable operation even under complex conditions. Simultaneously, the adaptive adjustment function based on real-time temperature monitoring data enables the system to dynamically optimize control parameters, continuously improving control performance. The established temperature feedback-based closed-loop power supply control achieves automatic adjustment of the electrolyte temperature, significantly improving the stability and reliability of the formation process, and providing a theoretical basis and technical support for the optimization of lead-acid battery manufacturing processes. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0012] In the attached diagram: Figure 1 This is a flowchart of the temperature control method for the lead-acid battery electrode formation process of the present invention. Detailed Implementation

[0013] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0014] The following detailed description of some embodiments of the present invention will be provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0015] Studies have shown that electrolyte temperature is a key factor affecting the formation quality of the electrodes. Below 5℃, the active material on the negative electrode is prone to detachment, the positive electrode exhibits peeling, and the electrochemical reaction efficiency decreases, leading to incomplete conversion of lead sulfate in the electrodes; simultaneously, reduced gas evolution results in decreased electrode porosity. Above 45℃, gas evolution and grid corrosion intensify, reducing the mechanical strength of the electrodes. Therefore, the formation electrolyte temperature should ideally be controlled within the range of 10℃-45℃.

[0016] After the battery is filled with electrolyte, approximately 50%-60% of the PbO reacts exothermically with H₂SO₄, causing the temperature to rise by 30℃-36℃. To improve production efficiency, manufacturers generally adopt rapid formation processes, leading to increased formation current and further temperature increases. To ensure formation quality, water bath cooling is typically used. The electrolyte temperature during formation is mainly affected by three factors: the exothermic polarization reaction, the ohmic loss of the electrolyte, and water bath heating.

[0017] Experiments have confirmed that the α-PbO2 content of the positive electrode plate is approximately 30% at an 18℃ water bath temperature. α-PbO2 mainly functions as a framework, while β-PbO2 contributes more to capacity. Too low a water bath temperature leads to insufficient battery capacity, while too high a temperature reduces the content of α-PbO2, accelerating capacity decay. Therefore, the water bath temperature should ideally be maintained at 40℃ to effectively stabilize thermal balance and reduce the impact of power supply fluctuations. Since water bath heating makes temperature changes controllable and small in magnitude, instantaneous power supply changes will not significantly affect the thermal balance of the electrolyzer, making power supply adjustment theoretically feasible.

[0018] Please see Figure 1 This invention provides a temperature control method for the formation process of lead-acid battery plates, comprising the following steps: Step 1: Establish a power-current model for the formation process of lead-acid battery plates; Specifically, a formation cell voltage model is established to analyze the relationship between cell voltage and formation current, electrode potential, and electrolyte resistance. The formation cell voltage consists of three parts: U=E + -E - +IR0 where U is the cell voltage of the formation tank (or the voltage of a single cell), and E + E is the positive electrode potential. - R0 is the electrode potential of the negative electrode, I is the current flowing through the formation tank, and R0 is the electrolyte resistance between the positive and negative electrodes.

[0019] Power supply P=UI= (E + -E - +IR0) I, expanding, we get: P=I(E + -E - )+I 2 R0 Analysis of key time points in the formation process yielded the following table showing the variation patterns of formation process parameters:

[0020] Based on the aforementioned analysis results, the potential difference (E) + -E -The relationship between the voltage and time is as follows: approximately 2.4V in the initial stage and approximately 2.65V in the later stage; the change pattern of resistance R0 is as follows: the resistance R0 is relatively large in the initial stage (approximately 0.3Ω), the resistance R0 decreases in the middle stage (approximately 0.2Ω), and the resistance R0 is very small in the later stage (close to 0).

[0021] Through data fitting and analysis, the general relationship is obtained as: P(t)=[E + (t)-E - (t)]I+R(t)I 2 .

[0022] The potential difference is fitted linearly: E + (t)-E - (t) = 2.0 + 0.02t (V); The resistance is fitted using an exponential function: R0(t) = 0.3exp(-t / 15)(Ω).

[0023] The final model for the relationship between power supply and current, i.e., the power supply-current model, is as follows: P = (2 + 0.02t)I + (0.3e) -t / 15 )I 2 Where P is the power supply, t is the time, and e is the base of the natural logarithm.

[0024] Step 2: Determine the target power supply based on the given target current and the power supply-current model; Specifically, the control method based on the power-current relationship: Based on the established power-current relationship model, the tank current can be precisely controlled by adjusting the power supply. For a given target current I... ref At time t, the required target power supply is: (1) When calculating current based on power, a quadratic equation needs to be solved due to the presence of a quadratic term. The quadratic formula can then be used to find the roots of a quadratic equation (removing roots where the current is negative): (2) Step 3: Obtain the electrolyte temperature prediction equation based on the heat balance equation of the formation tank; Specifically, to achieve predictive control of the electrolyte temperature, a heat balance equation for the formation tank is established. The rate of change of the electrolyte temperature depends on the difference between the heat generation rate and the heat dissipation rate: (3) Where m is the mass of the electrolyte, C pLet be the specific heat capacity of the electrolyte, η be the power-to-thermal conversion efficiency coefficient, P(t) be the power supplied at time t, T(t) be the electrolyte temperature at time t, h be the overall heat transfer coefficient, A be the effective heat dissipation area, and T be the total heat dissipation area. water Let T be the water bath temperature. The above equation is then discretized using the Euler method after deformation, with the sampling time being T. s The electrolyte temperature prediction state equation used in the MPC (Model Predictive Control) algorithm is obtained as follows: (4) Step 4: Real-time acquisition of electrolyte temperature, and optimization of the electrolyte temperature prediction state equation at each sampling time using a model predictive control algorithm, outputting the optimal power supply change at each sampling time; Specifically, a unified MPC algorithm is used to solve the following optimization problem at each sampling time throughout the entire formation cycle: optimizing the state equation for predicting the electrolyte temperature and outputting the optimal power supply change at each sampling time; the objective function for this optimization is: (5) Where: N p For prediction in the time domain, take values ​​of 10-20; N c To control the time domain, we take values ​​of 3-5; T ref The target reference temperature is set to 40℃; T(k+i|k) represents the predicted temperature at time k+i; ΔP(k+i|k) represents the change in power supply at time k+i; Q is the state weight matrix used to adjust the priority of temperature tracking error; R is the control weight matrix used to adjust the priority of power change smoothness. Both Q and R are 1×1 matrices and require manual adjustment; and for parameter x, , T represents the transpose operation.

[0025] The constraints for this optimization solution include input constraints and state constraints, among which, Input constraints include: Power supply amplitude constraint: Pmin≤P(k+i)≤Pmax(6) Constraint on power supply variation: -ΔPlim≤ΔP(k+i)≤ΔPlim(7) In the formula, Pmin and Pmax are the minimum and maximum power supply values, respectively, P(k+i) is the power supply at time k+i; ΔPlim is the threshold for power supply change, and ΔP(k+i) is the power supply change at time k+i.

[0026] State constraints (which need to be divided into stages based on the characteristics of the formation process) include: 1) Initial stage (0-8h): Increase current hard constraint: I k ≤Isafe(8; Among them, I k Let be the current passing through the formation tank at time k, which is obtained from equation (2); Isafe is the maximum allowable current, which serves as an indicator to prevent the plate from overheating.

[0027] 2) Mid-to-late stage (8-32h): At this time, the resistance R0 decreases, and the main constraint is temperature. 10℃≤T(k)≤45℃(9).

[0028] Furthermore, the specific implementation steps of the MPC algorithm are as follows: 1. Collect the current electrolyte temperature T actual ; 2. Calculate the temperature deviation: ΔT = T ref -T actual ; 3. State estimation: using the current electrolyte temperature T actual and current power supply P actual Correct the initial state of the model predictive control algorithm; 4. Rolling optimization: Based on the corrected state, in the prediction time domain N p Iterative prediction is performed within the system, and a quadratic programming problem is solved (under constraints, the power supply corresponding to the minimum value of the objective function J(k) is obtained), resulting in a set of optimal power supply control increment sequences ΔU={ΔP(k),ΔP(k+1),…}. 5. Update power output: Take the first value ΔP(k) in the sequence as the current actual control quantity, that is, the optimal power supply change. Based on the optimal power supply change and the target power supply, obtain the optimal power supply corresponding to each sampling time. 6. The current optimal current is obtained through the power supply-current model, which can be used for real-time monitoring and safety threshold judgment.

[0029] Based on the same inventive concept, another embodiment of the present invention provides a temperature control system for the lead-acid battery electrode formation process, used to implement the temperature control method for the lead-acid battery electrode formation process of the aforementioned embodiment. The system includes: A module was created to establish a power-current model for the formation process of lead-acid battery plates. The determination module is used to determine the target power supply based on the given target current and the power supply-current model; The prediction module is used to obtain the electrolyte temperature prediction equation based on the heat balance equation of the formation tank. The solution module is used to collect electrolyte temperature in real time and use model predictive control algorithm to optimize and solve the state equation for electrolyte temperature prediction at each sampling time, and output the optimal power supply change at each sampling time. The control module is used to obtain the optimal power supply at each sampling moment based on the optimal power supply change and the target power supply, so as to realize closed-loop control of power supply based on electrolyte temperature feedback.

[0030] It should be noted that the temperature control system of this invention is a closed-loop power supply control system based on electrolyte temperature feedback, and its control effect is analyzed as follows: Initial control. In the early stages of formation, due to the relatively large electrolyte resistance R0 (approximately 0.3Ω), the relationship between power supply and current is mainly determined by the quadratic term I. 2 R0 is determined. At this point, the control strategy focuses on preventing excessive current from causing a rapid temperature rise. The MPC algorithm predicts that the initial resistance R0 is relatively high; if the power supply is too large, it will lead to I... 2 R increases sharply, so the optimal solution will automatically limit the power output to meet temperature and current constraints.

[0031] Mid-to-late stage control. In the mid-to-late stages of formation, the potential difference (E...) + -E - As the linear term (E) gradually increases, the linear term (E) + -E - In the power supply expression, I plays a dominant role. At this point, precise control of the formation current can be indirectly achieved by accurately adjusting the power supply, thereby dominating the linear heat generation term and realizing electrolyte temperature control.

[0032] In summary, the temperature control method and system for the lead-acid battery plate formation process employs the MPC algorithm, enabling precise tracking of the target current trajectory and providing a stable control foundation for the formation process. Regarding temperature control, by real-time monitoring of the electrolyte temperature to ultimately adjust the power supply, the electrolyte temperature can be effectively maintained within the optimal formation range (10–45℃), with a preferred control temperature of 40℃. Its unique rolling optimization mechanism endows the system with excellent anti-interference capabilities, maintaining stable operation even under complex conditions. Simultaneously, the adaptive adjustment function based on real-time temperature monitoring data allows the system to dynamically optimize control parameters, continuously improving control performance. The established temperature feedback-based closed-loop power supply control achieves automatic adjustment of the electrolyte temperature, significantly improving the stability and reliability of the formation process, and providing a theoretical basis and technical support for the optimization of lead-acid battery manufacturing processes.

[0033] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. It should be understood that the invention is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A temperature control method for the formation process of lead-acid battery plates, characterized in that, include: Establish a power-current model for the plate formation process of lead-acid batteries; Based on the given target current and the power-current model, determine the target power supply. The state equation for predicting electrolyte temperature is obtained based on the heat balance equation of the formation tank. The electrolyte temperature is collected in real time, and a model predictive control algorithm is used to optimize and solve the state equation for predicting the electrolyte temperature at each sampling time, and output the optimal power supply change corresponding to each sampling time. Based on the optimal power supply change and the target power supply, the optimal power supply corresponding to each sampling moment is obtained, thereby realizing closed-loop control of power supply based on electrolyte temperature feedback.

2. The temperature control method for the lead-acid battery plate formation process according to claim 1, characterized in that, The power supply-current model is as follows: P=(2+0.02t)I+(0.3e -t / 15 )I 2 Where P is the power supply, t is the time, I is the current passing through the formation tank, and e is the base of the natural logarithm.

3. The temperature control method for the lead-acid battery plate formation process according to claim 2, characterized in that, The formula for calculating the target power supply is: Among them, P ref For the target power supply, I ref The target current.

4. The temperature control method for the lead-acid battery plate formation process according to claim 2, characterized in that, The heat balance equation for the formation tank is: Where m is the mass of the electrolyte, C p Let be the specific heat capacity of the electrolyte, η be the power-to-thermal conversion efficiency coefficient, P(t) be the power supplied at time t, T(t) be the electrolyte temperature at time t, h be the overall heat transfer coefficient, A be the effective heat dissipation area, and T be the total heat dissipation area. water This refers to the water bath temperature.

5. The temperature control method for the lead-acid battery plate formation process according to claim 4, characterized in that, The state equation for predicting the electrolyte temperature is: Where T(k+1) is the electrolyte temperature at time k+1, T s At time k, T(k) is the electrolyte temperature at time k, and P(k) is the power supply at time k.

6. The temperature control method for the lead-acid battery electrode formation process according to claim 5, characterized in that, The objective function for optimization is: Where, N p For prediction in the time domain; N c To control the time domain; T ref ΔP(k+i|k) represents the target reference temperature; T(k+i|k) represents the predicted temperature at time k+i; ΔP(k+i|k) represents the change in power supply at time k+i; Q is the state weight matrix; R is the control weight matrix.

7. The temperature control method for the lead-acid battery plate formation process according to claim 6, characterized in that, 10≤N p ≤20,3≤N c ≤5。 8. The temperature control method for the lead-acid battery plate formation process according to claim 6, characterized in that, The constraints for the optimization solution include input constraints and state constraints. The input constraints include power supply amplitude constraints and power supply change constraints. The state constraints include current constraints and electrolyte temperature constraints.

9. The temperature control method for the lead-acid battery plate formation process according to claim 8, characterized in that, The state constraints specifically include: When 0 < k ≤ 8h, the current passing through the formation tank at time k is less than or equal to the maximum allowable current. When 8 < k ≤ 32h, 10℃ ≤ T(k) ≤ 45℃.

10. A temperature control system for the formation process of lead-acid battery plates, characterized in that, include: A module was created to establish a power-current model for the formation process of lead-acid battery plates. The determination module is used to determine the target power supply based on the given target current and the power supply-current model; The prediction module is used to obtain the electrolyte temperature prediction equation based on the heat balance equation of the formation tank. The solution module is used to collect electrolyte temperature in real time and use model predictive control algorithm to optimize and solve the state equation for electrolyte temperature prediction at each sampling time, and output the optimal power supply change at each sampling time. The control module is used to obtain the optimal power supply at each sampling moment based on the optimal power supply change and the target power supply, so as to realize closed-loop control of power supply based on electrolyte temperature feedback.

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