Battery health status analysis method and system, battery management system, storage medium

Abstract

The present invention relates to a method and system for analyzing the state of health of a battery, a battery management system, and a storage medium, including: predicting the battery operating voltage based on a pre-established battery model to obtain a predicted value of the battery operating voltage and a predicted value of the battery open-circuit voltage; obtaining an actual measured value of the battery operating voltage obtained by actually measuring the battery operating voltage; calculating a change in battery internal resistance according to the predicted value of the battery operating voltage, the predicted value of the battery open-circuit voltage, and the actual measured value of the battery operating voltage; wherein the change in battery internal resistance is the increase in the internal resistance of the battery in the current state relative to the battery in the original state; and determining the state of health of the battery according to the change in battery internal resistance. Through the present invention, the state of health of a specific battery can be effectively identified, which is simple and highly reliable.

Description

Technical Field

[0001] The present invention relates to the field of battery technology, and in particular to a battery health status analysis method and system, a battery management system, and a storage medium. Background Art

[0002] The estimated analysis of the battery state of health (SOH) is of great significance to other battery states, including the available state of charge (SOC) of the remaining charge in the battery, the remaining energy (SOE) of the battery, the power state (SOP) of the battery, and the determination of the driving range.

[0003] At present, the methods for calculating SOH with increased internal resistance include laboratory testing, statistical methods, and adaptive algorithms based on models and filters. Among them, the method based on laboratory testing is not suitable for engineering development and use; the method based on statistical methods is conducive to the charging, discharging, and static data of the battery throughout its entire use cycle, and the relationship between the battery health status and the above data is fitted based on the measured data, thereby obtaining the battery health status; because it is an open-loop method, it cannot identify the situation when the battery cell characteristics change abnormally; the adaptive algorithm based on models and filters uses electrochemical models or equivalent circuit models, it identifies the parameters of the model, and uses filters to estimate SOC and SOH. Because its algorithm structure is relatively complex and has many influencing variables, its stability often does not meet the requirements at present.

[0004] Therefore, it is urgent to propose a battery health status analysis method with simple algorithm structure and high reliability to effectively identify the health status of a specific battery. Summary of the invention

[0005] The purpose of the present invention is to provide a battery health status analysis method and system, a battery management system, and a storage medium to effectively identify the health status of a specific battery, which is simple and highly reliable.

[0006] To achieve the above object, the present invention provides a battery health status analysis method in a first aspect, comprising:

[0007] Based on the pre-established battery model, the battery operating voltage is predicted to obtain a battery operating voltage prediction value and a battery open circuit voltage prediction value;

[0008] Obtaining a measured value of the battery operating voltage obtained by actually measuring the battery operating voltage;

[0009] Calculate the battery internal resistance change amount based on the predicted battery operating voltage value, the predicted battery open-circuit voltage value, and the measured battery operating voltage value; wherein the battery internal resistance change amount is the increase in the internal resistance of the battery in the current state relative to the battery in the original state.

[0010] Determine the battery health state according to the battery internal resistance change amount.

[0011] Optionally, the calculating the battery internal resistance change amount according to the predicted battery operating voltage value and the measured battery operating voltage value is specifically to calculate the battery internal resistance change amount according to the following least squares formula;

[0012] y(k) = A(k)x + e(k)

[0013] wherein, (k) represents the k-th calculation process of the battery internal resistance change amount, y(k) = ΔU(k), ΔU = U Mdulmeas - OCV set - OV set , A(k) = [OV set (k) 1], e(k) is the noise in the calculation process, U Mdulmeas is the measured battery operating voltage value, OCV set is the battery operating voltage predicted by the battery model, OV set is the difference between the predicted battery operating voltage value and the predicted battery open-circuit voltage value, dR is the battery internal resistance change amount, and off is a preset value.

[0014] Optionally, the determining the battery health state according to the battery internal resistance change amount is specifically to calculate the battery health value according to the following formula;

[0015]

[0016] wherein, SOH R is the battery health value, R BOL is the nominal internal resistance value of the battery, and dR is the battery internal resistance change amount.

[0017] Optionally, the obtaining the predicted battery operating voltage value and the predicted battery open-circuit voltage value by predicting the battery operating voltage based on a pre-established battery model includes:

[0018] Obtain the current battery operating current and the current battery operating voltage, and predict the battery operating voltage value and the battery open-circuit voltage value based on the current battery operating current, the current battery operating voltage, and the pre-established battery model; wherein the pre-established battery model is a second-order battery model.

[0019] A second aspect of the present invention proposes a battery health state analysis system, including:

[0020] A voltage prediction value acquisition unit, configured to predict the battery operating voltage based on a pre-established battery model to obtain a battery operating voltage prediction value and a battery open-circuit voltage prediction value;

[0021] A measured voltage value acquisition unit, configured to obtain a measured battery operating voltage value obtained by actually measuring the battery operating voltage;

[0022] An internal resistance calculation unit, configured to calculate a change in battery internal resistance according to the battery operating voltage prediction value, the battery open-circuit voltage prediction value, and the measured battery operating voltage value; wherein the change in battery internal resistance is the increase in the internal resistance of the battery in the current state relative to the original state of the battery; and

[0023] A battery health determination unit, configured to determine the battery health state according to the change in battery internal resistance.

[0024] Optionally, the internal resistance calculation unit is specifically configured to:

[0025] Calculate the change in battery internal resistance according to the following least squares formula;

[0026] y(k) = A(k)x + e(k)

[0027] wherein, (k) represents the k-th calculation process of the change in battery internal resistance, y(k) = ΔU(k), ΔU = U Mdulmeas -OCV set -OV set , A(k) = [OV set (k) 1], e(k) is the noise in the calculation process, U Mdulmeas is the measured battery operating voltage value, OCV set is the battery operating voltage predicted by the battery model, OV set is the difference between the battery operating voltage prediction value and the battery open-circuit voltage prediction value, dR is the change in battery internal resistance, and off is a preset value.

[0028] Optionally, the battery health determination unit is specifically configured to:

[0029] Calculate the battery health value according to the following formula;

[0030]

[0031] wherein, SOH R is the battery health value, R BOL is the nominal internal resistance value of the battery, and dR is the change in battery internal resistance.

[0032] Optionally, the voltage prediction value acquisition unit is specifically used for:

[0033] Obtain the current working current and the current working voltage of the battery, and predict the working voltage of the battery to obtain the predicted value of the working voltage of the battery and the predicted value of the open-circuit voltage of the battery according to the current working current and the current working voltage of the battery and the pre-established battery model; wherein the pre-established battery model is a second-order battery model.

[0034] The third aspect of the present invention proposes a battery management system, including the battery health state analysis system described in the first aspect.

[0035] The fourth aspect of the present invention proposes a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the battery health state analysis method described in the first aspect are realized.

[0036] Implementing the above-mentioned battery health state analysis method and system, battery management system, and storage medium has at least the following beneficial effects: predicting the working voltage of the battery based on the pre-established battery model to obtain the predicted value of the working voltage of the battery and the predicted value of the open-circuit voltage of the battery, and according to the predicted value of the working voltage of the battery, the predicted value of the open-circuit voltage of the battery and the measured value of the working voltage of the battery, and then identifying the increase in the internal resistance of the battery, and analyzing and determining the health state of the battery according to the increase in the internal resistance; applicable to the health analysis of various types of batteries, so as to be able to effectively identify the health state of a specific battery, with simple use and high reliability.

[0037] Other features and advantages of the present invention will be described in the following specification. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0039] Figure 1 It is a flowchart of a battery health state analysis method in an embodiment of the present invention.

[0040] Figure 2 It is a schematic diagram of a second-order battery model in an embodiment of the present invention.

[0041] Figure 3 It is a schematic diagram of the comparison result between the predicted voltage value and the measured voltage value during the battery charging process in an embodiment of the present invention.

[0042] Figure 4 It is a schematic diagram of the structure of a battery health state analysis system in another embodiment of the present invention. Detailed implementation manners

[0043] Various exemplary embodiments, features, and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. In addition, for a better illustration of the present invention, numerous specific details are given in the following specific embodiments. Those skilled in the art should understand that the present invention can be implemented without some specific details. In some instances, means well known to those skilled in the art are not described in detail so as to highlight the gist of the present invention.

[0044] Refer to Figure 1 , an embodiment of the present invention provides a method for analyzing the state of health of a battery, including the following steps S1 to S3:

[0045] Step S1: Predict the battery operating voltage based on a pre-established battery model to obtain a predicted value of the battery operating voltage and a predicted value of the battery open-circuit voltage.

[0046] Among them, in this embodiment, the pre-established battery model is a second-order battery model, and the equivalent circuit diagram of the second-order battery model is as Figure 2 shown; the basic equation of the second-order battery model is shown as the following formula:

[0047]

[0048] Specifically, the predicted value of the battery operating voltage and the predicted value of the battery open-circuit voltage can be obtained by acquiring the current operating current and the current operating voltage of the battery, and performing battery operating voltage prediction calculation according to the current operating current and the current operating voltage of the battery and the above equations of the pre-established battery model;

[0049] Step S2: Obtain the measured value of the battery operating voltage obtained by actually measuring the battery operating voltage.

[0050] Specifically, generally, a battery management system will be configured for a storage battery. The battery management system is for intelligent management and maintenance of each battery unit, preventing the battery from overcharging and over-discharging, extending the service life of the battery, and monitoring the state of the battery. In this step, the measured value of the battery operating voltage can be obtained by acquiring the real-time detection data of the battery operating voltage by other detection units of the Battery Management System (BMS), and there is no need to add new measuring elements.

[0051] Step S3: Calculate the change amount of the battery internal resistance according to the predicted value of the battery operating voltage, the predicted value of the battery open-circuit voltage, and the measured value of the battery operating voltage; where the change amount of the battery internal resistance is the increase in the internal resistance of the battery in the current state relative to the original state of the battery;

[0052] Specifically, during a single charge, the change in the working voltage of the battery is as shown in Figure 3 shown in Figure 3 , where the measured actual value of the battery working voltage, the predicted value of the battery working voltage predicted by the model, and the change process of the battery open-circuit voltage are shown. The solid line with an arrow represents the voltage change increment during the actual battery working voltage charging process, and the dashed line with an arrow represents the voltage change increment during the battery working voltage charging process predicted by the model. Obviously, due to the aging of the battery, the internal resistance increases, resulting in the measured actual value of the battery working voltage being greater than the predicted value of the battery working voltage predicted by the model.

[0053] Based on the above changes in the battery internal resistance and the resulting changes in the measured voltage, we can obtain the following equation:

[0054] OV set (1 + dR) + off = U Mdulmeas -OCV set

[0055] where both sides of the above equation represent the difference between the measured actual value of the battery working voltage and the predicted value of the battery working voltage.

[0056] where OV set is the difference between the predicted value of the battery working voltage and the predicted value of the battery open-circuit voltage; dR is the change in the battery internal resistance, expressed as a percentage; off is a preset value; U Mdulmeas is the measured actual value of the battery working voltage; OCV set is the battery working voltage predicted by the battery model.

[0057] Define the variable ΔU = U Mdulmeas -OCV set -OV set , then the above equation can be written as:

[0058]

[0059] Furthermore, the above equation can be written as the following least squares formula:

[0060] y(k) = A(k)x + e(k)

[0061] where (k) represents the k-th calculation process of the change in the battery internal resistance, y(k) = ΔU(k), A(k) = [OV set (k) 1], e(k) is the noise during the calculation process;

[0062] According to the above least squares formula, the change in the battery internal resistance dR can be calculated.

[0063] Step S4. Determine the battery health state according to the battery internal resistance change amount.

[0064] Exemplarily, the battery health value is specifically calculated according to the following formula;

[0065]

[0066] where SOH R is the battery health value, R BOL is the nominal internal resistance value of the battery, and dR is the battery internal resistance change amount.

[0067] It can be understood that the battery health state is of great significance for the full life cycle management of the power battery of an electric vehicle. When the internal resistance of the battery increases due to long-term use, resulting in large changes in various battery parameters, it causes great difficulties in battery management and control; accurately estimating the battery health state can provide a reference for more accurate estimation of other battery states, making the battery management and control strategy more precise, and at the same time being able to give early warnings of various safety problems caused by battery aging, so it has great significance. The method of the embodiment of the present invention is based on a pre-established battery model to predict the battery operating voltage to obtain the battery operating voltage prediction value and the battery open-circuit voltage prediction value, and according to the battery operating voltage prediction value, the battery open-circuit voltage prediction value and the measured battery operating voltage value, further identify the increase in the battery internal resistance, and analyze and determine the battery health state according to the increase in the internal resistance; it is applicable to the health analysis of various types of batteries, so as to effectively identify the health state of a specific battery, with simple use and high reliability.

[0068] Referring to Figure 4 , another embodiment of the present invention proposes a battery health state analysis system, including:

[0069] A voltage prediction value acquisition unit 1, configured to predict the battery operating voltage based on a pre-established battery model to obtain a battery operating voltage prediction value and a battery open-circuit voltage prediction value;

[0070] A voltage measured value acquisition unit 2, configured to acquire a measured battery operating voltage value obtained by actually measuring the battery operating voltage;

[0071] An internal resistance calculation unit 3, configured to calculate the battery internal resistance change amount according to the battery operating voltage prediction value, the battery open-circuit voltage prediction value and the measured battery operating voltage value; where the battery internal resistance change amount is the increase in the internal resistance of the battery in the current state relative to the battery in the original state; and

[0072] A battery health determination unit 4, configured to determine the battery health state according to the battery internal resistance change amount.

[0073] Specifically, the internal resistance calculation unit 3 is specifically configured to:

[0074] The change in battery internal resistance is calculated according to the following least squares formula;

[0075] y(k) = A(k)x + e(k)

[0076] where (k) represents the k-th calculation process of the change in battery internal resistance, y(k) = ΔU(k), ΔU = U Mdulmeas -OCV set -OV set , A(k) = [OV set (k) 1], e(k) is the noise in the calculation process, U Mdulmeas is the measured value of the battery operating voltage, OCV set is the battery operating voltage predicted by the battery model, OV set is the difference between the predicted value of the battery operating voltage and the predicted value of the battery open-circuit voltage, dR is the change in battery internal resistance, and off is a preset value.

[0077] Specifically, the battery health determination unit 4 is specifically configured to:

[0078] Calculate the battery health value according to the following formula;

[0079]

[0080] where SOH R is the battery health value, R BOL is the nominal internal resistance value of the battery, and dR is the change in battery internal resistance.

[0081] Specifically, the voltage prediction value acquisition unit 1 is specifically configured to:

[0082] Obtain the current battery operating current and the current battery operating voltage, and predict the battery operating voltage and the battery open-circuit voltage according to the current battery operating current and the current battery operating voltage and a pre-established battery model; wherein the pre-established battery model is a second-order battery model.

[0083] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0084] It should be noted that the system described in the above embodiments corresponds to the method described in the above embodiments. Therefore, the parts not detailed in the system described in the above embodiments can be obtained by referring to the content of the method described in the above embodiments, that is, the specific step content recorded in the method of the above embodiments can be understood as the functions that can be realized by the system of this embodiment, and will not be elaborated here.

[0085] Moreover, when the battery health state analysis system described in the above embodiments is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0086] Another embodiment of the present invention provides a battery management system, including the battery health state analysis system described in the above embodiments.

[0087] Specifically, lithium batteries usually need to be used in conjunction with a Battery Management System (BMS). The battery management system can monitor parameters such as battery voltage, temperature, and current, and perform protection based on these data, such as overcharge / overdischarge protection, high temperature / low temperature protection, overcurrent protection, etc.; the battery management system in this embodiment refers to not only realizing the conventional monitoring and protection functions, but also including the function of analyzing the battery health state.

[0088] Another embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the battery health state analysis method described in the above embodiments are realized.

[0089] Specifically, the computer-readable storage medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0090] The above has described the embodiments of the present invention. The above description is exemplary and not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes are obvious to those of ordinary skill in the art in the technical field without departing from the scope and spirit of the described embodiments. The selection of the terms used herein is intended to best explain the principles of the embodiments, practical applications, or improvements to the technology in the market, or to enable other ordinary technical personnel in the technical field to understand the disclosed embodiments.

Claims

1. A method for analyzing the state of health of a battery, characterized in that, including: predicting the battery operating voltage based on a pre - established battery model to obtain a predicted value of the battery operating voltage and a predicted value of the battery open - circuit voltage; obtaining a measured value of the battery operating voltage obtained by actually measuring the battery operating voltage; calculating a change in battery internal resistance according to the predicted value of the battery operating voltage, the predicted value of the battery open - circuit voltage, and the measured value of the battery operating voltage; wherein the change in battery internal resistance is the increase in the internal resistance of the battery in the current state relative to the battery in the original state; determining the state of health of the battery according to the change in battery internal resistance; wherein, the calculating the change in battery internal resistance according to the predicted value of the battery operating voltage and the measured value of the battery operating voltage is specifically calculated to obtain the change in battery internal resistance according to the following least - squares formula; y(k) = A(k)x + e(k) Among them, (k) represents the k-th calculation process of the change in battery internal resistance, y(k) = ΔU(k), ΔU = U Mdulmeas -OCV set -OV set , A(k) = [OVset(k) 1], e(k) is the noise in the calculation process, U Mdulmeas is the measured value of the battery working voltage, OCV set is the battery working voltage predicted by the battery model, OV set is the difference between the predicted value of the battery working voltage and the predicted value of the battery open-circuit voltage, dR is the change in battery internal resistance, and off is a preset value.

2. The battery health state analysis method according to claim 1, characterized in that, the determining the state of health of the battery according to the change in battery internal resistance is specifically calculated to obtain a battery health value according to the following formula; Among them, SOH R is the battery health value, R BOL is the nominal internal resistance value of the battery, and dR is the change in the battery internal resistance.

3. The method for analyzing the state of health of a battery according to claim 1, wherein the predicting the battery operating voltage based on a pre - established battery model to obtain a predicted value of the battery operating voltage and a predicted value of the battery open - circuit voltage includes: obtaining the current operating current and the current operating voltage of the battery, and predicting the battery operating voltage based on the current operating current and the current operating voltage of the battery and a pre - established battery model to obtain a predicted value of the battery operating voltage and a predicted value of the battery open - circuit voltage; wherein the pre - established battery model is a second - order battery model.

4. A battery health status analysis system, characterized in that, including: a voltage prediction value acquisition unit, configured to predict the battery operating voltage based on a pre - established battery model to obtain a predicted value of the battery operating voltage and a predicted value of the battery open - circuit voltage; a voltage measured value acquisition unit, configured to obtain a measured value of the battery operating voltage obtained by actually measuring the battery operating voltage; an internal resistance calculation unit, configured to calculate a change in battery internal resistance according to the predicted value of the battery operating voltage, the predicted value of the battery open - circuit voltage, and the measured value of the battery operating voltage; wherein the change in battery internal resistance is the increase in the internal resistance of the battery in the current state relative to the battery in the original state; and a battery health determination unit, configured to determine the state of health of the battery according to the change in battery internal resistance; wherein, the internal resistance calculation unit is specifically configured to: calculate the change in battery internal resistance according to the following least - squares formula; y(k) = A(k)x + e(k) Among them, (k) represents the k-th calculation process of the change in battery internal resistance, y(k) = ΔU(k), ΔU = U Mdulmeas -OCV set -OV set , A(k) = [OVset(k) 1], e(k) is the noise in the calculation process, U Mdulmeas is the measured value of the battery operating voltage, OCV set is the battery operating voltage predicted by the battery model, OV set is the difference between the predicted value of the battery operating voltage and the predicted value of the battery open-circuit voltage, dR is the change in battery internal resistance, and off is a preset value.

5. The battery health state analysis system according to claim 4, wherein the battery health determination unit is specifically configured to: calculate the battery health value according to the following formula; Among them, SOH R is the battery health value, R BOL is the nominal internal resistance value of the battery, and dR is the change in the battery internal resistance.

6. The battery health status analysis system according to claim 4, wherein the voltage prediction value acquisition unit is specifically configured to: obtain the current operating current and the current operating voltage of the battery, and predict the battery operating voltage based on the current operating current and the current operating voltage of the battery and a pre - established battery model to obtain a predicted value of the battery operating voltage and a predicted value of the battery open - circuit voltage; wherein the pre - established battery model is a second - order battery model.

7. A battery management system, characterized in that, including the battery health status analysis system according to any one of claims 4 - 6.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the battery health status analysis method according to any one of claims 1 - 3.

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