A method, device and system for detecting battery health status

Abstract

The embodiments of the present invention relate to the field of battery detection technology and disclose a method, device and system for detecting the health status of a battery. The system includes a new energy vehicle, in which a rechargeable and dischargeable battery is provided. The method first obtains vehicle charging and discharging data in the new energy vehicle, and then determines whether the battery is sufficiently stationary based on the vehicle charging and discharging data to determine the stationary state of the battery. Then, based on the stationary state of the battery, different models are selected to calculate the current available capacity of the battery. Finally, based on the current available capacity, the current battery health status of the new energy vehicle is calculated. The detection method provided by the embodiment of the present invention can accurately calculate the current available capacity of the battery regardless of whether the vehicle is sufficiently stationary, thereby calculating the current battery health status of the new energy vehicle and realizing rapid detection of the battery health status.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of battery detection, and in particular to a method, device, and system for detecting the health status of a battery. Background Art

[0002] In recent years, with the rapid development of electric vehicles, their market share has steadily increased. Lithium batteries, the power source of electric vehicles, face a complex operating environment and difficult-to-accurately simulate electrochemical mechanisms. Rapid testing technology and equipment for the health of lithium batteries have long been a challenge. Furthermore, not only do car owners urgently need to understand the health of their batteries, but the used car market, vehicle repair stations, and battery recycling companies are also in urgent need of breakthroughs in rapid lithium battery testing technology.

[0003] Currently, most battery state of health (SOH) estimation methods are to use offline testing of relevant experimental data of batteries from the same batch, and then further estimate the current available capacity of the battery through curve fitting or interpolation methods. The current state of health (SOH) of the battery is estimated by comparing it with the factory nominal capacity of the battery.

[0004] Among them, for estimating the available capacity, the currently commonly used method is to use the data of the Battery Management System (BMS) collected on the vehicle side, and obtain the open circuit voltage-state of charge (SOC-OCV) curve of the offline experimental data by querying the single cell voltage, so as to obtain the battery's charging start and end state of charge (State of Charge, SOC) and the accumulated power during the charging process, and estimate the current available capacity of the battery.

[0005] In the process of implementing the embodiments of the present invention, the inventors found that there are at least the following problems in the above-mentioned related technologies: the above-mentioned method of estimating the available capacity of the battery has many shortcomings in engineering applications. In order to more accurately obtain the initial state of charge (SOC) of charging, sufficient rest time is required before charging to eliminate the battery polarization voltage. However, most vehicles, especially commercial vehicles, cannot meet the conditions of sufficient rest before charging. Summary of the Invention

[0006] The embodiments of the present application provide a method, device, and system for detecting the health status of a battery.

[0007] The purpose of the embodiment of the present invention is achieved through the following technical solutions:

[0008] To solve the above technical problems, in the first aspect, an embodiment of the present invention provides a method for detecting the health status of a battery, which is applied to a new energy vehicle, wherein the new energy vehicle is provided with a rechargeable and dischargeable battery. The method includes: obtaining vehicle charging and discharging data in the new energy vehicle; judging whether the battery has been sufficiently rested based on the vehicle charging and discharging data to determine the resting state of the battery; selecting different models to calculate the current available capacity of the battery based on the resting state of the battery; and calculating the current battery health status of the new energy vehicle based on the current available capacity.

[0009] In some embodiments, judging whether the battery has been sufficiently rested based on the vehicle charging and discharging data to determine the rest state of the battery includes: obtaining the rest data of the new energy vehicle before charging; calculating the rest time of the new energy vehicle before charging based on the rest data; obtaining a preset sufficient rest time; judging whether the rest time is greater than the sufficient rest time; if so, the battery has been sufficiently rested before charging; if not, the battery has not been sufficiently rested before charging.

[0010] In some embodiments, the method of selecting different models to calculate the current available capacity of the battery based on the static state of the battery includes: obtaining vehicle charging and discharging data during the use of the new energy vehicle, and selecting different models to obtain the start and end charge states of the battery during charging; calculating the total charged capacity of the battery by the ampere-hour integration method based on the vehicle charging data; and calculating the current available capacity of the battery based on the difference between the total charged capacity and the start and end charge states of the battery.

[0011] In some embodiments, the selecting different models to obtain the starting and ending state of charge of the battery during charging includes: when the battery has been sufficiently rested before charging, obtaining the initial state of charge of the battery at the start of charging through a rest correction model; when the battery has not been sufficiently rested before charging, obtaining the initial state of charge of the battery at the start of charging through a depolarization model.

[0012] In some embodiments, obtaining the initial state of charge of the battery at the start of charging through the static correction model includes: obtaining the cell voltage of the battery at the start of charging based on the vehicle charging data; and querying the open circuit voltage-state of charge relationship curve based on the cell voltage at the start of charging of the battery to obtain the initial state of charge of the battery at the start of charging.

[0013] In some embodiments, obtaining the initial state of charge of the battery at the start of charging through a depolarization model includes: obtaining the voltage of the new energy vehicle at the end of discharge, and obtaining discharge data of the new energy vehicle between the end of discharge and the time when the state of charge before the end of discharge is a preset percentage; obtaining a depolarization model of the battery; substituting the discharge data into the depolarization model for prediction, and calculating the voltage of the battery at the time when it is fully rested; and querying the open circuit voltage-state of charge relationship curve based on the voltage of the battery at the time when it is fully rested to obtain the initial state of charge of the battery at the start of charging.

[0014] In some embodiments, obtaining the depolarization model of the battery includes: obtaining experimental data of a battery of the same type or model as the battery in the new energy vehicle; preprocessing the experimental data; establishing data feature engineering based on the preprocessed experimental data; and training the depolarization model based on the data feature engineering.

[0015] In some embodiments, the obtaining of experimental data of a battery of the same type or model as the battery in the new energy vehicle includes: fully charging the experimental battery and allowing it to stand still; setting the discharge current of the experimental battery and discharging it to a set power value; allowing the experimental battery to stand still; setting the discharge current of the experimental battery again and discharging it to the next initial power value until the experimental battery is fully discharged; and recording the battery voltage, discharge current, discharge temperature, and sampling time during the discharge process to obtain the experimental data.

[0016] In some embodiments, the charging data includes the charging start time, the charging end time, and the real-time current value during the charging process. The total charging capacity of the battery is calculated by the ampere-hour integration method based on the vehicle charging data. The calculation formula is:

[0017]

[0018] Among them, Q charge represents the total capacity charged, t1 represents the charging start time, t2 represents the charging end time, and I represents the real-time current value during the charging process.

[0019] In some embodiments, the current available capacity of the battery is calculated based on the total charged capacity and the difference between the start and end state of charge of the battery, and the calculation formula is:

[0020]

[0021] Among them, Q total Indicates the current available capacity of the battery, Q charge Indicates the total charged capacity, SOC endIndicates the state of charge of the battery at the end of charging, SOC beg Indicates the state of charge of the battery when charging begins.

[0022] In some embodiments, the current battery health status of the new energy vehicle is calculated based on the current available capacity, and the calculation formula is:

[0023]

[0024] Among them, SOH represents the current health status of the battery of the new energy vehicle, Q total Indicates the current available capacity of the battery, Q normal Indicates the nominal capacity of the battery.

[0025] To solve the above technical problems, in the second aspect, an embodiment of the present invention provides a detection device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method described in the first aspect above.

[0026] In order to solve the above technical problems, in a third aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the method described in the first aspect above.

[0027] In order to solve the above technical problems, in the fourth aspect, an embodiment of the present invention further provides a computer program product, wherein the computer program product includes a computer program stored on a computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the method described in the first aspect above.

[0028] To solve the above technical problems, in the fifth aspect, an embodiment of the present invention also provides a battery health status detection system, including: a new energy vehicle, in which a rechargeable and dischargeable battery is provided; and a detection device as described in the second aspect, which is connected to the new energy vehicle and is used to detect the battery health status of the battery.

[0029] Compared with the prior art, the beneficial effects of the present invention are: different from the prior art, the embodiments of the present invention provide a battery health status detection method, device and system, which includes a new energy vehicle, and a rechargeable and dischargeable battery is provided in the new energy vehicle. The method first obtains the vehicle charging and discharging data in the new energy vehicle, and then judges whether the battery is sufficiently stationary based on the vehicle charging and discharging data to determine the stationary state of the battery. Then, according to the stationary state of the battery, different models are selected to calculate the current available capacity of the battery. Finally, according to the current available capacity, the current battery health status of the new energy vehicle is calculated. The detection method provided in the embodiment of the present invention can calculate the current available capacity of the battery regardless of whether the vehicle is sufficiently stationary, thereby calculating the current battery health status of the new energy vehicle and realizing rapid detection of the battery health status. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] One or more embodiments are exemplarily described by pictures in the corresponding drawings. These exemplified descriptions do not constitute limitations on the embodiments. Elements / modules and steps with the same reference numerals in the drawings are represented as similar elements / modules and steps. Unless otherwise stated, the figures in the drawings do not constitute a scale limitation.

[0031] Figure 1 This is a flow chart of a method for detecting battery health status provided in Example 1 of the present invention;

[0032] Figure 2 yes Figure 1 A sub-flowchart of step S200 in the detection method shown;

[0033] Figure 3 yes Figure 1 A sub-flowchart of step S300 in the detection method shown;

[0034] Figure 4 yes Figure 3 A sub-flowchart of step S310 in the detection method shown;

[0035] Figure 5 is an open circuit voltage-state of charge relationship curve provided by an embodiment of the present invention;

[0036] Figure 6 yes Figure 3 Another sub-flowchart of step S310 in the detection method shown;

[0037] Figure 7 is a schematic diagram of a depolarization model provided by an embodiment of the present invention;

[0038] Figure 8 yes Figure 6 A sub-flowchart of step S312b in the detection method shown;

[0039] Figure 9 This is a sampling example diagram of the sampling time and sampled battery voltage of a lithium battery discharge-stationary experiment provided by an embodiment of the present invention;

[0040] Figure 10 This is a hardware structure diagram of a battery health status detection device provided in the second embodiment of the present invention;

[0041] Figure 11 This is a structural diagram of a battery health status detection system provided in Example 3 of the present invention. DETAILED DESCRIPTION

[0042] The present invention will be described in detail below with reference to specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those skilled in the art, several variations and improvements can be made without departing from the scope of the present invention. These all fall within the scope of protection of the present invention.

[0043] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0044] It should be noted that, unless there is a conflict, the various features of the embodiments of the present invention may be combined with each other and are all within the scope of protection of this application. In addition, although the functional modules are divided in the device schematics and the logical order is shown in the flow charts, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flow charts.

[0045] Unless otherwise defined, all technical and scientific terms used in this specification have the same meanings as those commonly understood by those skilled in the art to which this invention belongs. The terms used in this specification and in the description of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" as used in this specification includes any and all combinations of one or more of the relevant listed items.

[0046] In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0047] Specifically, the embodiments of the present invention are further described below with reference to the accompanying drawings.

[0048] Example 1

[0049] The embodiment of the present invention provides a method for detecting the health status of a battery. The method can be applied to a new energy vehicle provided with a rechargeable battery. Figure 1 , which shows the process of a battery health status detection method provided by an embodiment of the present invention, the method includes but is not limited to the following steps:

[0050] Step S100: obtaining vehicle charging and discharging data of the new energy vehicle;

[0051] In an embodiment of the present invention, first, it is necessary to obtain the charging and discharging data of the vehicle battery in the new energy vehicle to further determine whether the new energy vehicle has been sufficiently stationary, and to calculate the current available capacity and battery health status of the battery based on the existing charging and discharging data. The charging and discharging data includes the current and temperature during the charging and discharging process, the battery cell voltage and state of charge at each moment during the charging and discharging process, the stationary time before charging, the data sampling time, etc. In addition, the vehicle charging and discharging data can be collected by the battery management system (BMS) in the new energy vehicle.

[0052] Step S200: judging whether the battery has been sufficiently rested based on the vehicle charge and discharge data to determine the rest state of the battery;

[0053] In the embodiment of the present invention, after obtaining the charge and discharge data of the vehicle, it is necessary to determine whether the battery is sufficiently stationary, so that different methods are used to perform the next step of calculation for the two states of sufficient stationary and insufficient stationary. For details, please refer to Figure 2 , which shows Figure 1 A sub-process of step S200 in the detection method, wherein judging whether the battery has been sufficiently rested based on the vehicle charge and discharge data to determine the rest state of the battery, includes:

[0054] Step S210: Acquire static data of the new energy vehicle before charging;

[0055] Step S220: Calculating the rest time of the new energy vehicle before charging based on the rest data;

[0056] Step S230: obtaining a preset sufficient rest time;

[0057] Step S240: Determine whether the resting time is greater than the sufficient resting time; if so, jump to step S250; if not, jump to step S260;

[0058] Step S250: The battery has been allowed to stand for a long time before charging;

[0059] Step S260: The battery is not allowed to rest sufficiently before charging.

[0060] In an embodiment of the present invention, the method for determining whether the battery is sufficiently stationary before charging is to obtain the stationary time t before charging of the vehicle according to the stationary data. s , combined with the pre-set vehicle full static time t a To judge, when t s >t a When the battery is determined to have been sufficiently rested before charging, the process then jumps to step S311a to query and obtain the initial charge state. If t s <t a , it is determined that the battery has not been sufficiently rested before charging, and the process jumps to step S311b to calculate the initial state of charge. The preset sufficient rest time can be pre-set or calculated based on expert experience, laboratory data, or big data analysis of historical vehicle data, and can be set according to actual needs.

[0061] Step S300: selecting different models to calculate the current available capacity of the battery according to the static state of the battery;

[0062] In the embodiment of the present invention, for the two states of the battery having been fully rested before charging and the battery not having been fully rested before charging, the state of charge during the battery charging process is calculated by selecting two different models, the ampere-hour integration method and the depolarization model, so as to calculate the current available capacity of the battery. For details, see Figure 3 , which shows Figure 1 A sub-process of step S300 in the detection method, wherein different models are selected to calculate the current available capacity of the battery according to the static state of the battery, includes:

[0063] Step S310: acquiring vehicle charging and discharging data during the use of the new energy vehicle, and selecting different models to obtain the start and end state of charge of the battery during charging;

[0064] On the one hand, the different models are selected to obtain the starting and ending state of charge of the battery during charging. When the battery has been fully rested before charging, the initial state of charge of the battery at the beginning of charging is obtained by using the rest correction model; specifically, see Figure 4 , which shows Figure 3 A sub-process of step S310 in the detection method, wherein the step of obtaining the initial state of charge of the battery at the start of charging by using the static correction model, includes:

[0065] Step S311a: acquiring the cell voltage of the battery at the start of charging according to the vehicle charging data;

[0066] Step S312a: querying an open circuit voltage-state of charge relationship curve according to the cell voltage at the start of charging of the battery to obtain the initial state of charge of the battery when charging starts.

[0067] In the embodiment of the present invention, first, by analyzing the vehicle charging and discharging data, the single cell voltage at the start of battery charging can be obtained. Then, according to the single cell voltage at the start of battery charging, the following query is performed: Figure 5 The open circuit voltage-state of charge relationship curve shown, that is, the OCV-SOC curve, can be used to obtain the vehicle's initial state of charge SOC. beg .

[0068] On the other hand, the different models are selected to obtain the starting and ending state of charge of the battery during charging. When the battery is not fully rested before charging, the depolarization model is used to predict the initial state of charge of the battery at the beginning of charging. Specifically, see Figure 6 , which shows Figure 3 Another sub-process of step S310 in the detection method, obtaining the initial state of charge of the battery at the start of charging by using the depolarization model, includes:

[0069] Step S311b: obtaining the voltage of the new energy vehicle at the end of discharge, and obtaining discharge data of the new energy vehicle between the end of discharge and the time when the state of charge reaches a preset percentage before the end of discharge;

[0070] In the embodiments of the present invention, please refer to Figure 7 , which shows the schematic diagram of the depolarization model, Figure 7 In the example, the preset percentage moment is the moment when the vehicle's state of charge is 5% before the end of discharge, where t1 is the moment when the vehicle's SOC is 5% before the end of discharge, t2 is the moment when the vehicle's discharge ends, and t3 is the moment when the vehicle is fully stationary after the end of discharge. First, it is necessary to obtain the voltage of the new energy vehicle at the moment t2 when discharge ends, and obtain the voltage of the new energy vehicle at the moment t1 when the state of charge before the end of discharge is the preset percentage.

[0071] Step S312b: obtaining a depolarization model of the battery;

[0072] Furthermore, a depolarization model of the battery is obtained to further calculate the state of charge. The depolarization model needs to be obtained by analyzing and training experimental data of the same battery or the same type of battery before executing the detection method of this application. Specifically, see Figure 8 , which shows Figure 6 In a sub-process of step S312b of the detection method, obtaining the depolarization model of the battery includes:

[0073] Step S3121b: Acquire experimental data of a battery of the same type or model as the battery in the new energy vehicle;

[0074] Among them, it is necessary to conduct a discharge-rest experiment under specific experimental conditions to obtain depolarization model experimental data, and the acquisition of experimental data of a battery of the same type or model as the battery in the new energy vehicle includes: fully charging the experimental battery and fully resting it; setting the discharge current of the experimental battery and discharging it to a set power value; fully resting the experimental battery; setting the discharge current of the experimental battery again and discharging it to the next initial power value until the experimental battery is fully discharged; recording the battery voltage, discharge current, discharge temperature, and sampling time during the discharge process to obtain the experimental data.

[0075] Specifically, see Figure 9 , which shows a sampling example of the sampling time and sampled battery voltage of the lithium battery discharge-stationary experiment. The sampling steps can be specifically: step 1) fully charge the target battery and fully stand it, at which time the battery is 100% SOC; step 2) set the current to 0.1C for discharge, and discharge to the initial value of the power -5% SOC; step 3) fully stand it, and the standing time in the present invention is 0.5 hours; step 4) cycle steps 2) and 3) until the battery SOC is 0; It should be noted that, Figure 8 This is just an example of recording the battery voltage. During the experiment, it is necessary to synchronously record experimental data such as battery voltage, discharge current, discharge temperature, sampling time, etc., and it is also necessary to perform the experiment under different current and temperature conditions. For example, different current conditions can be set to 0.1C, 0.2C, 0.3C, 0.4C, and 0.5C, and different temperature conditions can be set to 0℃, 10℃, 35℃, and 45℃.

[0076] Step S3122b: preprocessing the experimental data;

[0077] After obtaining the experimental data, it is necessary to pre-process the experimental data to facilitate the next step of feature establishment. The data pre-processing includes abnormal data processing, charging and discharging, and static working condition labeling, etc.

[0078] Step S3123b: establishing data feature engineering based on the preprocessed experimental data;

[0079] In the embodiment of the present invention, since the depolarization process of the battery is affected by many factors of the discharge condition, it is necessary to select several typical data features to establish data feature engineering. The data features can preferably be the discharge end voltage, average discharge rate, discharge time, and average discharge temperature, which are denoted as x. i(i=1, 2, 3, 4). It should be noted that in the process of establishing the data feature engineering, the establishment of the feature engineering is not limited to the above-mentioned four typical data features that affect battery depolarization. The embodiment of the present invention only uses the four features of discharge end voltage, average discharge rate, discharge time, and average discharge temperature. This is because too many features may lead to increased correlation between features and increase the complexity of the depolarization model. If necessary, more data features can be added according to actual needs.

[0080] Step S3124b: Perform depolarization model training based on the data feature engineering.

[0081] Finally, the polarization voltage y is obtained by calculating the voltage after each full discharge and rest period minus the discharge end voltage, and a suitable regression model is selected to establish a depolarization model. In the process of establishing the data feature engineering, the depolarization algorithm model can be further studied to improve the accuracy of the model in predicting the polarization voltage. For example, when a linear regression model is selected, the depolarization model can be expressed as:

[0082] y=ω0+ω1x1+φ2x2+ω3x3+ω4x4+ξ

[0083] After screening the data of the vehicle n segments that meet the sufficient static conditions and converting the data set into a matrix form, the depolarization model can be expressed as:

[0084]

[0085] After normalizing the data and converting it to a distribution between [0, 1], the depolarization model can be expressed as:

[0086]

[0087] The loss function of the depolarization model is defined as:

[0088]

[0089] Through parameter tuning, model training, and model optimization, the value of the loss function L(ω) is minimized, and the optimal depolarization model is finally evaluated. The detection method provided in an embodiment of the present invention calculates the depolarization model of the battery's initial state of charge when the battery is not fully rested before charging.

[0090] Step S313b: Substituting the discharge data into the depolarization model for prediction, and calculating the voltage of the battery when it is fully rested;

[0091] Please continue to see above Figure 7 According to the principle of the depolarization model, when the vehicle stops discharging at time t2, its voltage is u endDue to the polarization of the lithium battery, the voltage will gradually rise until the fully static moment t3, at which time the voltage is the polarization voltage u a The voltage rise value from time t2 to time t3 is the polarization voltage u p , that is, the calculation formula for the voltage of the battery when it is fully rested is:

[0092] u a =u end +u p

[0093] Among them, u a represents the voltage of the battery at the time t3 when it is fully rested, u end represents the voltage of the new energy vehicle at the end of discharge time t2, u p represents the polarization voltage.

[0094] The embodiment of the present invention adopts the depolarization model to directly predict the vehicle voltage u at time t3 through the data between t1 and t2. a , without the need for the vehicle to rest between t2 and t3.

[0095] Step S314b: querying an open circuit voltage-state of charge relationship curve based on the voltage of the battery when it is fully rested, so as to obtain the initial state of charge of the battery when charging begins.

[0096] The voltage u of the battery at the time of sufficient rest is obtained by prediction and calculation in step S314b above. a Then, similarly to step S312a, by querying Figure 5 The open circuit voltage-state of charge relationship curve or open circuit voltage-state of charge relationship table shown can be used to obtain the vehicle charging initial state of charge SOC beg .

[0097] Step S320: Calculating the total charging capacity of the battery by the ampere-hour integration method according to the vehicle charging data;

[0098] The charging data includes the charging start time, the charging end time, and the real-time current value during the charging process. The total charging capacity of the battery is calculated based on the vehicle charging data using the ampere-hour integration method. The calculation formula is:

[0099]

[0100] Among them, Q charge represents the total capacity charged, t1 represents the charging start time, t2 represents the charging end time, and I represents the real-time current value during the charging process.

[0101] Step S330: Calculate the current available capacity of the battery according to the difference between the total charged capacity and the starting and ending state of charge of the battery.

[0102] After the total charged capacity is calculated in step S320 and the initial state of charge of the battery is calculated or predicted in step S310, the current available capacity of the battery can be calculated by querying the state of charge of the battery at the end of charging through charging data. Specifically, the current available capacity of the battery is calculated based on the difference between the total charged capacity and the initial and final states of charge of the battery, and the calculation formula is:

[0103]

[0104] Among them, Q total Indicates the current available capacity of the battery, Q charge Indicates the total charged capacity, SOC end Indicates the state of charge of the battery at the end of charging, SOC beg Indicates the initial state of charge when charging of the battery begins, SOC end -SOC beg Indicates the difference between the starting and ending state of charge of the battery.

[0105] Step S400: Calculate the current battery health status of the new energy vehicle based on the current available capacity.

[0106] In the embodiment of the present invention, the nominal capacity Q of the battery is obtained through the basic information of the vehicle battery. normal , combined with the current available capacity Q of the battery calculated in step S300 total , the current health status of the battery of the new energy vehicle can be calculated, wherein the basic information of the battery can be obtained by querying the model and type of the battery. Specifically, the current health status of the battery of the new energy vehicle is calculated based on the current available capacity, and the calculation formula is:

[0107]

[0108] Among them, SOH represents the current health status of the battery of the new energy vehicle, Q total Indicates the current available capacity of the battery, Q normal Indicates the nominal capacity of the battery.

[0109] Example 2

[0110] The present invention also provides a detection device, see Figure 10 , which shows that it is possible to perform Figures 1 to 9The hardware structure of the detection device 10 of the battery health status detection method.

[0111] The detection device 10 includes: at least one processor 11; and a memory 12 in communication with the at least one processor 11. Figure 10 The memory 12 stores instructions that can be executed by the at least one processor 11, and the instructions are executed by the at least one processor 11 so that the at least one processor 11 can perform the above Figures 1 to 9 The processor 11 and the memory 12 may be connected via a bus or other means. Figure 10 The bus connection is taken as an example.

[0112] Memory 12, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions / modules corresponding to the battery health status detection method in the embodiment of the present application. Processor 11 executes the non-volatile software programs, instructions, and modules stored in memory 12 to execute various server functional applications and data processing, thereby implementing the battery health status detection method in the above method embodiment.

[0113] The memory 12 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the battery health status detection device, etc. In addition, the memory 12 may include a high-speed random access memory and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 12 may optionally include a memory remotely located relative to the processor 11, and these remote memories may be connected to the battery health status detection device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0114] The one or more modules are stored in the memory 12, and when executed by the one or more processors 11, perform the battery health status detection method in any of the above method embodiments, for example, perform the above described Figures 1 to 9 method steps.

[0115] The above-mentioned product can execute the method provided in the embodiment of this application, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not fully described in this embodiment, please refer to the method provided in the embodiment of this application.

[0116] The present application also provides a non-volatile computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, which are executed by one or more processors, for example, to execute the above-described Figures 1 to 9 method steps.

[0117] The present application also provides a computer program product, including a computer program stored on a non-volatile computer-readable storage medium, wherein the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the battery health status detection method in any of the above method embodiments, for example, executing the above-described Figures 1 to 9 method steps.

[0118] Example 3

[0119] The embodiment of the present invention provides a battery health status detection system, see Figure 11 , which shows the structure of a battery health status detection system provided by an embodiment of the present invention. The battery health status detection system 100 includes: a new energy vehicle 20, in which a rechargeable and dischargeable battery BAT is provided; and a detection device 10 as described in Example 2, which is connected to the new energy vehicle 20 and is used to detect the battery health status of the battery BAT.

[0120] It should be noted that the detection device 10 can be a device, module or unit arranged in the new energy vehicle 20, or it can be a device independently arranged separately from the new energy vehicle 20, or it can be a device, module or unit in the automobile diagnostic equipment, etc. The detection device 10 and the new energy vehicle 20 need to at least be able to establish a communication / communication connection. Specifically, the actual structure, setting location, connection method, etc. of the detection device 10 can be set according to the needs of the actual application scenario, and there is no need to stick to the limitations of the embodiments of the present invention.

[0121] The detection system provided by the embodiment of the present invention adopts the detection method shown in Example 1 to detect the battery health status of the vehicle. The vehicle does not need to be stationary for a long time before charging. The battery health status can be estimated immediately and accurately after charging is completed. There is no need for external battery detection equipment. The vehicle charging and discharging data can be obtained through the battery management system BMS in the new energy vehicle 20 through only one actual charging and discharging behavior of the battery BAT, thereby calculating the current health status of the vehicle battery and realizing rapid detection.

[0122] An embodiment of the present invention provides a method, device and system for detecting the health status of a battery. The system includes a new energy vehicle, which is equipped with a rechargeable and dischargeable battery. The method first obtains vehicle charging and discharging data in the new energy vehicle, and then determines whether the battery is sufficiently stationary based on the vehicle charging and discharging data to determine the stationary state of the battery. Then, based on the stationary state of the battery, different models are selected to calculate the current available capacity of the battery. Finally, based on the current available capacity, the current battery health status of the new energy vehicle is calculated. The detection method provided in the embodiment of the present invention can calculate the current available capacity of the battery regardless of whether the vehicle is sufficiently stationary, thereby calculating the current battery health status of the new energy vehicle and realizing rapid detection of the battery health status.

[0123] It should be noted that the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0124] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a general hardware platform, and of course, can also be implemented by hardware. Those skilled in the art can understand that all or part of the processes in the above embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0125] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Under the concept of the present invention, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations in different aspects of the present invention as described above. For the sake of simplicity, they are not provided in detail. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in this field should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting a battery health status, characterized in that: Applied to a new energy vehicle, wherein the new energy vehicle is provided with a rechargeable and dischargeable battery, the method comprises: Obtaining vehicle charging and discharging data of the new energy vehicle; determining whether the battery has been sufficiently rested based on the vehicle charge and discharge data to determine a rest state of the battery; Obtaining vehicle charging and discharging data during use of the new energy vehicle, selecting different models to obtain the start and end states of charge of the battery during charging; calculating the total charged capacity of the battery using an ampere-hour integration method based on the vehicle charging data; and calculating the current available capacity of the battery based on the difference between the total charged capacity and the start and end states of charge of the battery; Calculating a current battery health status of the new energy vehicle based on the current available capacity; When the battery is not fully rested before charging, the initial state of charge of the battery at the start of charging is predicted using a depolarization model, specifically: Obtaining the voltage of the new energy vehicle at the end of discharge, and obtaining discharge data of the new energy vehicle between the end of discharge and the time when the state of charge reaches a preset percentage before the end of discharge; obtaining a depolarization model of the battery; substituting the discharge data into the depolarization model for prediction, and calculating the voltage of the battery at the time of full rest; and querying an open circuit voltage-state of charge relationship curve based on the voltage of the battery at the time of full rest to obtain an initial state of charge of the battery when charging begins; Wherein, obtaining the depolarization model of the battery includes: Acquiring experimental data of a battery of the same type or model as the battery in the new energy vehicle, including fully charging the experimental battery and allowing it to fully rest; setting a discharge current for the experimental battery and discharging it to a set power value; allowing the experimental battery to fully rest; again setting the discharge current for the experimental battery and discharging it to a next initial power value until the experimental battery is fully discharged; and recording the battery voltage, discharge current, discharge temperature, and sampling time during the discharge process to obtain the experimental data; Preprocessing the experimental data; Establishing data feature engineering based on the preprocessed experimental data; The depolarization model is trained based on the data feature engineering.

2. The detection method according to claim 1, wherein The determining, based on the vehicle charge and discharge data, whether the battery has been sufficiently rested to determine the rest state of the battery includes: Obtaining static data of the new energy vehicle before charging; Calculating the rest time of the new energy vehicle before charging based on the rest data; Get the preset sufficient rest time; Determining whether the standing time is greater than the sufficient standing time; If so, the battery has been sufficiently rested before charging; If not, the battery was not sufficiently rested before charging.

3. The detection method according to claim 1, wherein The selecting different models to obtain the start and end state of charge of the battery during charging includes: When the battery has been sufficiently rested before charging, an initial state of charge of the battery at the start of charging is obtained through a rest correction model.

4. The detection method according to claim 3, characterized in that The step of obtaining the initial state of charge of the battery at the start of charging by using the static correction model includes: Obtaining the cell voltage of the battery at the start of charging according to the vehicle charging data; According to the cell voltage at the start of charging of the battery, an open circuit voltage-state of charge relationship curve is queried to obtain the initial state of charge of the battery when charging starts.

5. The detection method according to any one of claims 1 to 4, characterized in that The charging data includes the charging start time, charging end time, and the real-time current value during the charging process. The total charging capacity of the battery is calculated based on the vehicle charging data using the ampere-hour integration method, and the calculation formula is: in, Indicates the total charging capacity, Indicates the charging start time, Indicates the charging end time, Indicates the real-time current value during the charging process.

6. The detection method according to claim 5, characterized in that The current available capacity of the battery is calculated based on the difference between the total charged capacity and the starting and ending state of charge of the battery, and the calculation formula is: in, represents the current available capacity of the battery, Indicates the total charging capacity, Indicates the state of charge of the battery at the end of charging, Indicates the state of charge of the battery when charging begins.

7. The detection method according to claim 6, characterized in that The current battery health status of the new energy vehicle is calculated based on the current available capacity, and the calculation formula is: in, Indicates the current battery health status of the new energy vehicle. represents the current available capacity of the battery, Indicates the nominal capacity of the battery.

8. A detection device, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

9. A battery health status detection system, characterized in that: include: New energy vehicles, wherein the new energy vehicles are provided with rechargeable and dischargeable batteries; The detection device according to claim 8, wherein the detection device is connected to the new energy vehicle and is used to detect the battery health status of the battery.

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