Battery online internal resistance identification method and system based on voltage plateau period

Abstract

The invention relates to a battery online internal resistance identification method and system based on a voltage plateau period, and belongs to the technical field of battery parameter identification, and the method comprises the steps: continuously collecting the terminal voltage and the working current of a battery, and estimating the current state of charge; screening out a stable working window of the battery in a set charge state interval; acquiring the open-circuit voltage of the battery in the stable working window; and battery internal resistance identification is completed based on the open-circuit voltage of the battery. According to the method, the voltage platform characteristics of the lithium iron phosphate battery are ingeniously utilized, the OCV is regarded as a constant in a short time, the problems that in a traditional method, the OCV and the internal resistance voltage drop are coupled and are difficult to separate are effectively solved, and the identification precision is remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of battery parameter identification technology, and in particular to a method and system for identifying the online internal resistance of a battery based on the voltage plateau period. Background Technology

[0002] Lithium-ion batteries, as key energy storage components, are widely used in electric vehicles, energy storage power stations, and consumer electronics. The Battery Management System (BMS) is central to ensuring the safe, reliable, and efficient operation of batteries. Within the BMS, the battery's internal resistance is a crucial parameter for assessing its State of Health (SOH), power performance, and heat generation characteristics. An increase in battery internal resistance is often a direct indication of battery aging; therefore, accurately acquiring internal resistance values ​​online is essential for battery life prediction, fault diagnosis, and thermal management.

[0003] Lithium iron phosphate (LFP) batteries are gaining increasing market share due to their advantages such as high safety, long cycle life, and low cost. However, a significant electrochemical characteristic of LFP batteries is the existence of a very flat voltage plateau region during charge and discharge, meaning that the open circuit voltage (OCV) changes very little over a wide range of states of charge (SOC).

[0004] Existing battery internal resistance identification methods are mainly divided into two categories: offline identification and online identification.

[0005] Offline identification methods include electrochemical impedance spectroscopy (EIS) and hybrid pulse power characteristic (HPPC) testing. EIS can accurately measure impedance information at different frequencies, but its equipment is expensive and the testing process is complex, making it unsuitable for the real-time operating conditions of vehicles or energy storage systems. While HPPC testing can effectively obtain internal resistance, it requires a specific pulse current profile, interrupting the normal operation of the battery, and is also considered an offline test.

[0006] Online identification methods typically rely on equivalent circuit models (such as the Thevenin model and the Rint model) and utilize algorithms like the Kalman filter and recursive least squares (RLS) for parameter identification. The core of these methods is to calculate the internal resistance based on the relationship between voltage, current, and open-circuit voltage.

[0007] However, for lithium iron phosphate batteries, the OCV-SOC curve is extremely flat due to the presence of a voltage plateau region. This means that even small voltage measurement errors or model errors can lead to significant deviations in SOC estimation. Conversely, within the plateau region, large changes in SOC only cause slight changes in OCV. This presents a significant challenge to traditional online identification methods when applied to lithium iron phosphate batteries: it is difficult to accurately separate the voltage drop caused by internal resistance from the voltage change caused by OCV variations, resulting in poor accuracy and unstable convergence in the internal resistance identification results.

[0008] Therefore, there is an urgent need for a new method that can overcome the influence of the voltage plateau region characteristics of lithium iron phosphate batteries and achieve accurate and reliable online internal resistance identification. Summary of the Invention

[0009] To address the aforementioned problems, the purpose of this invention is to provide a method and system for identifying the online internal resistance of a battery based on the voltage plateau period.

[0010] A method for identifying the online internal resistance of a battery based on the voltage plateau period includes:

[0011] Step 1: Continuously collect the battery's terminal voltage and operating current and estimate the current state of charge;

[0012] Step 2: Select the stable operating window of the battery within the set state of charge range;

[0013] Step 3: Obtain the open-circuit voltage of the battery within the stable operating window;

[0014] Step 4: Identify the battery's internal resistance based on the battery's open-circuit voltage.

[0015] Preferably, step 2: selecting the stable operating window of the battery within the set state of charge range includes:

[0016] Within the set state of charge range, a sliding window with a time length of T is selected, and the current data within the sliding window is continuously monitored. When the standard deviation of the current within the sliding window meets the set conditions, it is taken as the stable operating window of the battery.

[0017] Preferably, in step 2, the formula for calculating the standard deviation of the current is:

[0018]

[0019] in, The standard deviation of current. This indicates the number of data points within the window. This represents the i-th current value within the window. This represents the average current within the window. This indicates the preset current stability threshold.

[0020] Preferably, in step 3, the open-circuit voltage corresponding to the SOC value at the beginning of the stable operating window is taken.

[0021] Preferably, step 4: identifying the battery's internal resistance based on the battery's open-circuit voltage includes:

[0022] Step 4.1: Within a stable operating window, calculate the average value of the terminal voltage and the average value of the current;

[0023] Step 4.2: Calculate the battery internal resistance using the average value of the terminal voltage, the average value of the current, and the battery open-circuit voltage.

[0024] Preferably, in step 4.2, the formula for calculating the battery internal resistance is:

[0025]

[0026] in, This represents the average value of the terminal voltage. This represents the average value of the current. This indicates the open-circuit voltage of the battery. This indicates the battery's internal resistance.

[0027] Preferably, in step 4.2, the battery internal resistance is input into the filter and smoothed to obtain the final battery internal resistance.

[0028] The present invention also provides a battery online internal resistance identification system based on voltage plateau period, comprising:

[0029] The parameter module is used to continuously collect the battery's terminal voltage and operating current and estimate the current state of charge.

[0030] The working window filtering module is used to filter out the stable working window of the battery within the set state of charge range.

[0031] An open-circuit voltage acquisition module is used to acquire the open-circuit voltage of the battery within the stable operating window.

[0032] The parameter identification module is used to identify the battery's internal resistance based on the battery's open-circuit voltage.

[0033] The present invention also provides an electronic device, including a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the transceiver, the memory, and the processor are connected via the bus, characterized in that the computer program, when executed by the processor, implements the steps in the above-described method for identifying the online internal resistance of a battery based on a voltage plateau period.

[0034] The present invention also provides a storage medium storing a computer program thereon, characterized in that, when the computer program is executed by a processor, it implements the steps in the above-described method for identifying the online internal resistance of a battery based on a voltage plateau period.

[0035] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0036] This invention relates to a battery online internal resistance identification method based on voltage plateau period. Compared with the prior art, this invention cleverly utilizes the voltage plateau characteristics of lithium iron phosphate batteries, treating OCV as a constant in a short period of time, effectively solving the problem of OCV being coupled with internal resistance voltage drop and difficult to separate in traditional methods, and significantly improving the identification accuracy.

[0037] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of the present 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 only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 A flowchart of a battery online internal resistance identification method based on voltage plateau period provided by the present invention;

[0040] Figure 2 The schematic diagram shows a battery online internal resistance identification method based on voltage plateau period provided by the present invention. Detailed Implementation

[0041] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0042] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0043] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0044] Please see Figure 1 A method for identifying the online internal resistance of a battery based on the voltage plateau period, comprising:

[0045] Step 1: Continuously collect the battery's terminal voltage and operating current and estimate the current state of charge;

[0046] Step 2: Select the stable operating window of the battery within the set state of charge range;

[0047] In step 2, a sliding window of time length T is selected within the set state of charge interval, and the current data within the sliding window is continuously monitored. When the standard deviation of the current within the sliding window meets the set conditions, it is taken as the stable operating window of the battery.

[0048] Step 3: Obtain the open-circuit voltage of the battery within the stable operating window;

[0049] Step 4: Identify the battery's internal resistance based on the battery's open-circuit voltage.

[0050] Furthermore, step 4 includes:

[0051] Step 4.1: Within a stable operating window, calculate the average value of the terminal voltage and the average value of the current;

[0052] Step 4.2: Calculate the battery's internal resistance using the average terminal voltage, the average current, and the battery's open-circuit voltage. The formula for calculating the battery's internal resistance is:

[0053]

[0054] in, This represents the average value of the terminal voltage. This represents the average value of the current. This indicates the open-circuit voltage of the battery. This indicates the battery's internal resistance.

[0055] The battery internal resistance is input into a filter and then smoothly updated to obtain the final battery internal resistance.

[0056] In practical applications, the battery online internal resistance identification method of this invention includes the following steps:

[0057] Step 1: Data Acquisition and Preprocessing. Continuously acquire the battery terminal voltage V(t) and operating current I(t), and obtain the current state of charge (SOC) estimate SOC(t) through the battery management system (BMS).

[0058] Step 2: Voltage Plateau Region Determination. A predefined SOC range is set as the voltage plateau region, for example... , (e.g., SOC is between 20% and 85%). The system determines in real time whether the current battery SOC(t) falls within this range. Only when... Only then will the subsequent identification process be triggered.

[0059] Step 3: Select a stable operating window within the voltage plateau region. Set a sliding window with a time length of T and continuously monitor the current data within the window. Calculate the standard deviation of the current within this window. or rate of change A valid "stable working window" is considered to have been found when the following stability conditions are met: Figure 2 As shown.

[0060]

[0061] Where N is the number of data points within the window. This represents the average current within the window. This is a preset current stability threshold (e.g., 0.1A). This step aims to eliminate operating conditions with drastic current fluctuations and ensure that voltage changes are primarily contributed by internal resistance.

[0062] Step 4: Approximate Open Circuit Voltage (OCV) Processing. For the selected stable operating window, due to its short time span (usually a few seconds) and the battery being in the voltage plateau region, the SOC change within the window can be considered minimal, and the corresponding OCV value is approximately a constant value. This OCV value can be obtained by referring to a pre-calibrated OCV-SOC relationship table, taking the OCV corresponding to the SOC value at the beginning of the window:

[0063]

[0064] Step 5: Internal Resistance Calculation Within a stable operating window, the battery's voltage-current relationship can be simplified as follows:

[0065]

[0066] To improve accuracy, the data points within the window are averaged. The average terminal voltage within the window is calculated. and the average value of current Then, the ohmic resistance is calculated using the following formula. :

[0067]

[0068] To ensure the validity of the calculation, the average current value is required. The absolute value is greater than a minimum threshold This is to avoid calculation errors caused by a denominator that is zero or too small.

[0069] Step Six: Result Filtering and Update The calculated results will be filtered and updated. As an observation, the value is input into a filter (such as a low-pass filter, moving average filter, or simplified Kalman filter) to smoothly update the historical internal resistance value. This effectively suppresses noise and glitches that may exist in a single calculation, resulting in a more stable and reliable internal resistance parameter.

[0070] Taking a BMS (Battery Management System) of an electric vehicle as an example, the implementation process of this invention will be further explained. This BMS manages a lithium iron phosphate battery pack with a nominal capacity of 150Ah.

[0071] 1. Parameter presets:

[0072] Voltage plateau range: =25%, =85%.

[0073] Stable working window duration: T = 5 seconds.

[0074] o Current stability threshold: =0.2 A.

[0075] o Current effectiveness threshold: =1 A.

[0076] The oBMS already stores an accurate OCV-SOC lookup table.

[0077] 2. Operation process:

[0078] oBMS acquires and records the battery pack's terminal voltage, current, and SOC at a period of 100ms.

[0079] At a certain moment, the BMS detects that the SOC is 60%, entering the preset voltage plateau region, and initiates the internal resistance identification logic.

[0080] oBMS begins analyzing current data from the most recent 5 seconds (50 data points). Assuming that within a certain 5-second window, the calculated current standard deviation is 0.15A, less than the threshold of 0.2A, and the average current is -20A (discharge), with an absolute value greater than 1A, this window is considered valid.

[0081] oBMS records that the SOC at the start of this window is 60.1%, and the corresponding value is obtained from the table. =3.285 V.

[0082] oBMS calculates the average voltage within this 5-second window as follows: =3.265 V.

[0083] Calculate the internal resistance using the formula:

[0084]

[0085] The calculated 1.0 mΩ is used as the new measurement value and fed into the moving average filter. If the previous four historical values ​​are [0.98, 0.99, 0.97, 0.99] mΩ, then the updated internal resistance value is:

[0086]

[0087] oBMS updated 0.986 mΩ to the current official internal resistance parameter of the battery for subsequent power prediction and SOH estimation.

[0088] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0089] 1. High precision and high reliability: This invention cleverly utilizes the voltage plateau characteristics of lithium iron phosphate batteries to treat OCV as a constant in a short period of time, effectively solving the problem of OCV being coupled with internal resistance voltage drop and difficult to separate in traditional methods, thus significantly improving the identification accuracy.

[0090] 2. Truly online and non-disruptive identification: The entire identification process is completed automatically during normal battery operation, without the need for specific test signals, and does not interfere with the normal operation of the battery.

[0091] 3. Low computational cost and easy to implement: The algorithm mainly involves data filtering, averaging and one division operation, which has a small computational load, low performance requirements for the BMS main control chip, and is easy to deploy on existing hardware platforms.

[0092] 4. No additional hardware required: This method relies solely on the existing voltage and current sensors and SOC estimation function of the BMS, without incurring any additional hardware costs.

[0093] 5. Strong applicability: Specifically designed for the electrochemical characteristics of lithium iron phosphate batteries, it solves the technical difficulties recognized in the industry and has strong engineering application value.

[0094] The present invention also provides a battery online internal resistance identification system based on voltage plateau period, comprising:

[0095] The parameter module is used to continuously collect the battery's terminal voltage and operating current and estimate the current state of charge.

[0096] The working window filtering module is used to filter out the stable working window of the battery within the set state of charge range.

[0097] An open-circuit voltage acquisition module is used to acquire the open-circuit voltage of the battery within the stable operating window.

[0098] The parameter identification module is used to identify the battery's internal resistance based on the battery's open-circuit voltage.

[0099] Compared with the prior art, the beneficial effects of the battery online internal resistance identification system based on voltage plateau period provided by the present invention are the same as the beneficial effects of the battery online internal resistance identification method based on voltage plateau period described in the above technical solution, and will not be repeated here.

[0100] The present invention also provides an electronic device, including a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor. The transceiver, the memory, and the processor are connected via the bus. The computer program, when executed by the processor, implements the steps in the above-described method for identifying the online internal resistance of a battery based on a voltage plateau period. Compared with the prior art, the beneficial effects of the electronic device provided by the present invention are the same as those of the above-described method for identifying the online internal resistance of a battery based on a voltage plateau period, and will not be elaborated upon here.

[0101] The present invention also provides a storage medium storing a computer program thereon, characterized in that, when the computer program is executed by a processor, it implements the steps in the above-described method for identifying the online internal resistance of a battery based on a voltage plateau period. Compared with the prior art, the beneficial effects of the storage medium provided by the present invention are the same as the beneficial effects of the above-described method for identifying the online internal resistance of a battery based on a voltage plateau period, and will not be elaborated here.

[0102] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for identifying the online internal resistance of a battery based on the voltage plateau period, characterized in that, include: Step 1: Continuously collect the battery's terminal voltage and operating current and estimate the current state of charge; Step 2: Select the stable operating window of the battery within the set state of charge range; Step 3: Obtain the open-circuit voltage of the battery within the stable operating window; Step 4: Identify the battery's internal resistance based on the battery's open-circuit voltage.

2. The battery online internal resistance identification method based on voltage plateau period according to claim 1, characterized in that, Step 2: Selecting the stable operating window of the battery within the set state of charge range, including: Within the set state of charge range, a sliding window with a time length of T is selected, and the current data within the sliding window is continuously monitored. When the standard deviation of the current within the sliding window meets the set conditions, it is taken as the stable operating window of the battery.

3. The battery online internal resistance identification method based on voltage plateau period according to claim 2, characterized in that, In step 2, the formula for calculating the standard deviation of the current is: in, The standard deviation of current. This indicates the number of data points within the window. This represents the i-th current value within the window. This represents the average current within the window. This indicates the preset current stability threshold.

4. The battery online internal resistance identification method based on voltage plateau period according to claim 3, characterized in that, In step 3, the open-circuit voltage corresponding to the SOC value at the beginning of the stable operating window is taken.

5. The battery online internal resistance identification method based on voltage plateau period according to claim 4, characterized in that, Step 4: Identifying the battery's internal resistance based on the battery's open-circuit voltage, including: Step 4.1: Within a stable operating window, calculate the average value of the terminal voltage and the average value of the current; Step 4.2: Calculate the battery internal resistance using the average value of the terminal voltage, the average value of the current, and the battery open-circuit voltage.

6. The battery online internal resistance identification method based on voltage plateau period according to claim 5, characterized in that, In step 4.2, the formula for calculating the battery internal resistance is: in, This represents the average value of the terminal voltage. This represents the average value of the current. This indicates the open-circuit voltage of the battery. This indicates the battery's internal resistance.

7. The battery online internal resistance identification method based on voltage plateau period according to claim 6, characterized in that, In step 4.2, the battery internal resistance is input into the filter and smoothed to obtain the final battery internal resistance.

8. A battery online internal resistance identification system based on voltage plateau period, characterized in that, include: The parameter module is used to continuously collect the battery's terminal voltage and operating current and estimate the current state of charge. The working window filtering module is used to filter out the stable working window of the battery within the set state of charge range. An open-circuit voltage acquisition module is used to acquire the open-circuit voltage of the battery within the stable operating window. The parameter identification module is used to identify the battery's internal resistance based on the battery's open-circuit voltage.

9. An electronic device comprising a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the transceiver, the memory, and the processor are connected via the bus, characterized in that, When the computer program is executed by the processor, it implements the steps in the battery online internal resistance identification method based on voltage plateau period as described in any one of claims 1-7.

10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps in the battery online internal resistance identification method based on voltage plateau period as described in any one of claims 1-7.

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