A method for fast estimation of reference temperature of all single cells within a battery pack

Abstract

A kind of quick estimation method of reference temperature of all monomer batteries in battery pack, it is related to lithium ion battery technical field.Based on the distance between the voltage of monomer battery without temperature sensor and the voltage of all monomer batteries with temperature sensor is calculated by Euclidean distance, the battery index with minimum distance difference is obtained as target battery;The measured temperature of the obtained target battery is used as the reference temperature of the monomer battery without temperature sensor;The obtained reference temperature is used as data for embedded deployment and application, considering the storage space capacity of embedded system, online deployment and temperature estimation strategy is designed.Based on the minimum Euclidean distance between the measurable voltage parameter and the voltage of monomer battery with temperature sensor, the reference temperature is obtained, and the embedded deployment strategy is set, the limited temperature sensor measurable information is fully utilized, and the temperature estimation of all monomer batteries in battery pack is quickly and effectively realized.

Description

Technical Field

[0001] This invention relates to the field of lithium-ion battery technology, specifically a method for rapidly estimating the reference temperature of all individual cells within a battery pack. Background Technology

[0002] A battery pack contains numerous individual cells, and due to limitations in cost, space, and wiring, only a limited number of temperature sensors are placed on the surfaces of critical individual cells within the battery pack, while the temperatures of other individual cells cannot be effectively monitored. Therefore, accurate estimation of the temperature of each individual cell in the battery pack is crucial for ensuring battery performance, monitoring, and preventing thermal runaway.

[0003] Most current battery temperature estimation methods are designed for individual cells, including direct measurement methods, electrochemical impedance spectroscopy (EIS)-based methods, model-based methods, and data-driven methods. Individual cell temperature estimation is fundamental to battery pack temperature estimation. Direct measurement methods require built-in temperature sensors, which are impractical due to cost, space, and wiring constraints within the battery pack. EIS-based methods require specialized testing equipment and circuits, making them unsuitable for online application in actual battery packs. Model-based methods require establishing battery thermal models, such as lumped-state or dual-state models, and temperature estimation models. These methods must consider the internal heat generation and transfer mechanisms of the battery, necessitating a trade-off between accuracy and complexity. Furthermore, the applicability of battery thermal models and temperature estimation models to various operating conditions is poor, requiring continuous adjustment and updates to model parameters. Moreover, most existing methods only simulate small-scale... For battery packs with numerous individual cells, establishing a high-order temperature estimation model based on the location of limited temperature sensors is complex and difficult to deploy and apply in embedded battery management systems. Data-driven methods do not require consideration of the battery's heat generation and transfer mechanisms; they only need to use data-driven algorithms to establish the mapping relationship between parameters such as voltage, current, and state of charge and temperature. However, the established data-driven model relies on a large amount of modeling data. For temperature estimation of battery packs, the model has poor robustness because the heat generation and transfer mechanisms of individual cells in different locations within the battery pack are inconsistent.

[0004] In summary, existing battery temperature estimation methods suffer from poor applicability to operating conditions, failure to consider actual battery pack structures, insufficient utilization of measurable parameter information, and difficulty in embedded deployment and application, thus failing to meet the requirements for effective estimation of battery temperature in battery pack form. Summary of the Invention

[0005] To address the shortcomings of the prior art, this invention provides a rapid method for estimating the reference temperature of all individual cells within a battery pack. It obtains the reference temperature based on the minimum Euclidean distance between measurable voltage parameters and the terminal voltage of the individual cell equipped with a temperature sensor. Furthermore, it employs an embedded deployment strategy to fully utilize limited measurable temperature sensor information, enabling rapid and effective temperature estimation of all individual cells within the battery pack.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a rapid estimation method for the reference temperature of all individual cells in a battery pack, comprising the following steps:

[0007] Step 1: Select a target battery with measurable temperature information based on the distance between measurable voltage parameters.

[0008] For battery packs with built-in temperature sensors in critical locations, temperature affects the terminal voltage of individual cells, with higher temperatures resulting in higher terminal voltages. To measure the differences in terminal voltage between individual cells, the distance between the terminal voltage of each cell without a temperature sensor and the terminal voltages of all cells with temperature sensors is calculated based on Euclidean distance, as shown below:

[0009]

[0010] In the formula, ED represents the calculation of Euclidean distance. This indicates the terminal voltage of a single battery cell without a temperature sensor. This represents the terminal voltage of the individual battery cell equipped with a temperature sensor, M represents the number of individual battery cells without a temperature sensor, and ω represents the number of individual battery cells equipped with a temperature sensor.

[0011] The battery index with the minimum distance difference is obtained based on the calculated distance. Best as follows:

[0012]

[0013] The target battery is a single cell equipped with a temperature sensor, identified by the battery index with the smallest distance difference.

[0014] Step 2: Obtain the reference temperature based on the target battery with measurable temperature information.

[0015] The measured temperature of the target battery is used as the reference temperature for a single cell without a temperature sensor, as shown in the following formula:

[0016]

[0017] In the formula, T n This indicates the temperature of a single battery cell without a temperature sensor, T. sThis indicates the temperature of the individual battery cell equipped with a temperature sensor;

[0018] Step 3: Set up a sliding window, design an online temperature estimation strategy, and deploy and apply it online.

[0019] Using the obtained reference temperature as data, and considering the storage capacity of the embedded system, the following online deployment and temperature estimation strategy is designed for embedded deployment and applications:

[0020] 3.1. Set a fixed sliding window size according to the storage capacity of the embedded system. When the stored data capacity is less than or equal to the sliding window size, under the current window conditions, for a single cell without a temperature sensor, calculate the distance between the terminal voltage of each single cell with a temperature sensor by formula (5), and obtain the reference temperature of the single cell at the current moment by formula (6) and formula (7).

[0021] 3.2 When the stored data capacity is greater than the sliding window size, the stored data is reduced by odd or even positions based on the sliding window length sequence, as shown in the following formula:

[0022] Z(1:2:N w )=[] (8)

[0023] In the formula, N w Z represents the sliding window size, and Z represents the number of sliding windows. w A window of data length storing the sequence;

[0024] After the data deletion is completed, data will continue to be stored based on 3.1 until the reference temperature of all individual cells in the battery pack that do not have temperature sensors is obtained.

[0025] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention obtains the reference temperature by means of the minimum Euclidean distance between the measurable voltage parameter and the terminal voltage of the individual battery cell equipped with a temperature sensor, and sets up an embedded deployment strategy to quickly and effectively estimate the temperature of all individual batteries in the battery pack, which has the following advantages:

[0026] 1. It can maximize the use of the limited temperature sensing information within the battery pack to achieve temperature estimation of all individual cells within the battery pack;

[0027] 2. It can be quickly deployed and applied to achieve efficient temperature estimation and monitoring of all individual cells within the battery pack;

[0028] 3. No need to consider complex heat generation and heat transfer mechanisms, no need for a large amount of operating data modeling, the temperature of all individual cells in the battery pack can be estimated quickly and effectively based on the relationship between temperature and measurable voltage parameters.

[0029] 4. It eliminates the need to consider complex information such as the actual structure of the battery pack and whether the cooling system is on, making it more suitable for practical applications;

[0030] 5. It can provide a basis for predicting driving range and estimating aging status, and is also beneficial to the thermal safety and safe driving of electric vehicles. Attached Figure Description

[0031] Figure 1 This is a flowchart of the present invention;

[0032] Figure 2 This is a schematic diagram of the data storage and processing principle of the present invention;

[0033] Figure 3 This is a comparison chart of temperature estimation results for different individual cells under -7℃ conditions in the examples;

[0034] Figure 4 This is a comparison chart of temperature estimation results for different individual cells under -30℃ conditions in the examples. Detailed Implementation

[0035] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the invention, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0036] like Figures 1-2 As shown, a rapid estimation method for the reference temperature of all individual cells in a battery pack includes the following steps:

[0037] Step 1: Select a target battery with measurable temperature information based on the distance between measurable voltage parameters.

[0038] For battery packs with built-in temperature sensors at key locations, temperature estimation can be achieved based on the limited measurable temperature information within the battery pack. For the same battery pack, the operating conditions experienced by each individual cell are the same under the same operating conditions, that is, the current flowing through each individual cell is the same. The battery heat generation formula, considering both ohmic heat and polarization heat, is as follows:

[0039] Q(k)=I(k)·(U OCV (k)-U t (k)) (1)

[0040] In the formula, I represents current, and U OCV U represents the open-circuit voltage. t Q represents the terminal voltage, Q represents the heat generated, and k represents the current sampling time.

[0041] The temperature variation of a single cell originates from its open-circuit voltage and terminal voltage, and the relationship between open-circuit voltage and state of charge is as follows:

[0042] U OCV (k)=f(SOC(k)) (2)

[0043] In the formula, f represents the nonlinear relationship between the state of charge and the open-circuit voltage, and SOC represents the state of charge.

[0044] Since the current flowing through all individual cells in the battery pack is the same, the ampere-hour integral definition equation based on the state of charge is as follows:

[0045]

[0046] In the formula, ΔT represents the sampling time, and C cap This represents the nominal capacity, and k-1 represents the previous sampling time.

[0047] Without considering the differences between individual cells, the difference in state of charge (SOC) originates from the initial SOC values ​​obtained from the initial terminal voltage differences. Therefore, from the perspective of battery heat generation analysis, the temperature difference of individual cells mainly comes from the terminal voltage. Furthermore, the electrical model equations for individual cells are as follows for different temperature differences:

[0048] U t (k)=U OCV (k)-I(k)·R0-I(k)·R p (4)

[0049] In the formula, R0 represents the ohmic internal resistance, R p This indicates the polarization resistance.

[0050] Therefore, it can be seen that the difference between temperature and the open-circuit voltage and state of charge of a single cell is very small, and there is a clear linear relationship between temperature and the ohmic internal resistance and polarization internal resistance of a single cell. The higher the temperature, the lower the ohmic internal resistance and polarization internal resistance. Therefore, temperature has a significant impact on the terminal voltage of a single cell, with the terminal voltage being higher at higher temperatures.

[0051] Based on the above analysis, there is a close relationship between the terminal voltage and temperature of a single cell. That is, the temperature of a single cell can be obtained by considering the difference in terminal voltage between individual cells and the temperature relationship between individual cells. Therefore, to measure the difference in terminal voltage between individual cells, the distance between the terminal voltage of each cell without a temperature sensor and the terminal voltages of all cells with temperature sensors is calculated based on Euclidean distance, as shown below:

[0052]

[0053] In the formula, ED represents the calculation of Euclidean distance. This indicates the terminal voltage of a single battery cell without a temperature sensor. This represents the terminal voltage of the individual battery cell equipped with a temperature sensor, M represents the number of individual battery cells without a temperature sensor, and ω represents the number of individual battery cells equipped with a temperature sensor.

[0054] The battery index with the minimum distance difference is obtained based on the distance calculated using formula (5). Best as follows:

[0055]

[0056] The target battery is the cell with a temperature sensor located by the battery index with the smallest distance difference. Since the smaller the Euclidean distance between the targets, the more correlated the targets are, the measured temperature of the target battery can be used as the reference temperature of the cell without a temperature sensor.

[0057] Step 2: Obtain the reference temperature based on the target battery with measurable temperature information.

[0058] Using the target battery obtained in step one, the measured temperature of this target battery is used as the reference temperature for individual cells without a temperature sensor, as shown in the following formula:

[0059]

[0060] In the formula, T n This indicates the temperature of a single battery cell without a temperature sensor, T. s This indicates the temperature of the individual battery cell equipped with a temperature sensor;

[0061] Step 3: Set up a sliding window, design an online temperature estimation strategy, and deploy and apply it online.

[0062] Using the reference temperature obtained in step two as data, for embedded deployment and application, taking into account the storage space capacity of the embedded system, combined with... Figure 2 The data storage and processing principle shown is illustrated, and the online deployment and temperature estimation strategy is designed as follows:

[0063] 3.1. Set a fixed sliding window size according to the storage capacity of the embedded system. When the stored data capacity is less than or equal to the sliding window size, under the current window conditions, for a single cell without a temperature sensor, calculate the distance between the terminal voltage of each single cell with a temperature sensor by formula (5), and obtain the reference temperature of the single cell at the current moment by formula (6) and formula (7).

[0064] 3.2 When the stored data capacity is greater than the sliding window size, the stored data is reduced by odd or even positions based on the sliding window length sequence, as shown in the following formula:

[0065] Z(1:2:N w )=[] (8)

[0066] In the formula, N w Z represents the sliding window size, and Z represents the number of sliding windows. w A window storage sequence of data length.

[0067] After the data is reduced using formula (8), the data is stored again based on 3.1.

[0068] Based on the above strategy, the same method can be used to obtain the reference temperature in real time for all individual cells in the battery pack that do not have temperature sensors.

[0069] Example

[0070] This embodiment verifies the battery pack's CLTC operating condition data at different temperatures. The experiment is based on battery data from a built-in temperature sensor. The battery is a 133Ah ternary lithium-ion battery, and the sliding window size is set to 200. The method of this invention obtains the temperature estimation results of different individual cells under the battery pack's CLTC operating condition at different temperatures. The temperature estimation results of different individual cells at -7℃ and -30℃ are shown in Table 1.

[0071] Table 1 Temperature estimation results for different individual cells

[0072]

[0073] Specific temperature estimation results comparison chart Figure 3 and Figure 4 As shown in the figure, the reference curve is the actual temperature curve measured by the temperature sensor, and the estimated curve is the estimated temperature curve obtained by the method of the present invention. It can be seen from the above experimental results that the method proposed in this invention can accurately estimate the temperature of individual cells in the battery pack under different operating conditions.

[0074] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0075] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A rapid method for estimating the reference temperature of all individual cells in a battery pack, characterized in that: Includes the following steps: Step 1: Select a target battery with measurable temperature information based on the distance between measurable voltage parameters. For battery packs with built-in temperature sensors in critical locations, temperature affects the terminal voltage of individual cells, with higher temperatures resulting in higher terminal voltages. To measure the differences in terminal voltage between individual cells, the distance between the terminal voltage of each cell without a temperature sensor and the terminal voltages of all cells with temperature sensors is calculated based on Euclidean distance, as shown below: In the formula, ED represents the calculation of Euclidean distance. This indicates the terminal voltage of a single battery cell without a temperature sensor. This represents the terminal voltage of the individual battery cell equipped with a temperature sensor, M represents the number of individual battery cells without a temperature sensor, and ω represents the number of individual battery cells equipped with a temperature sensor. The battery index with the minimum distance difference is obtained based on the calculated distance. Best as follows: The target battery is a single cell equipped with a temperature sensor, identified by the battery index with the smallest distance difference. Step 2: Obtain the reference temperature based on the target battery with measurable temperature information. The measured temperature of the target battery is used as the reference temperature for a single cell without a temperature sensor, as shown in the following formula: In the formula, T n This indicates the temperature of a single battery cell without a temperature sensor, T. s This indicates the temperature of the individual battery cell equipped with a temperature sensor; Step 3: Set up a sliding window, design an online temperature estimation strategy, and deploy and apply it online. Using the obtained reference temperature as data, and considering the storage capacity of the embedded system, the following online deployment and temperature estimation strategy is designed for embedded deployment and applications: 3.

1. Set a fixed sliding window size according to the storage capacity of the embedded system. When the stored data capacity is less than or equal to the sliding window size, under the current window conditions, for a single cell without a temperature sensor, calculate the distance between the terminal voltage of each single cell with a temperature sensor by formula (5), and obtain the reference temperature of the single cell at the current moment by formula (6) and formula (7). 3.2 When the stored data capacity is greater than the sliding window size, the stored data is reduced by odd or even positions based on the sliding window length sequence, as shown in the following formula: Z(1:2:N w )=[] (8) In the formula, N w Z represents the sliding window size, and Z represents the number of sliding windows. w A window of data length storing the sequence; After the data deletion is completed, data will continue to be stored based on 3.1 until the reference temperature of all individual cells in the battery pack that do not have temperature sensors is obtained.

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