KR20230020028A - Systems and methods for predicting battery integrity - Google Patents

Abstract

According to an embodiment of the present invention, a system for predicting battery integrity includes: an information collection unit which collects state information of a battery cell transmitted from a battery measurement module located in a remote location; and an information processing unit which predicts whether or not there is a failure of the battery cell, remaining lifespan, and replacement time using the collected state information of the battery cell.

Description

Secondary battery health monitoring and analysis {Systems and methods for predicting battery integrity}

The present invention relates to a system and method for predicting battery health.

Today's gasoline, diesel, and other engine vehicles using fossil fuels have various problems, such as environmental pollution due to exhaust gas, global warming due to carbon dioxide, respiratory disease due to ozone generation, and fuel exhaustion.

To solve this problem, an electric vehicle (EV) that runs using a battery as a power source and a drive motor as a drive source, or a hybrid electric vehicle (HEV) that runs using an engine and a drive motor as a drive source (HEV) ), eco-friendly electric vehicles such as fuel cell electric vehicles (FCEVs) that run using a fuel cell and a driving motor as a power source and a driving source have been developed.

In such an electric vehicle, a battery is used, and a battery state of charge (SOC) is measured using a battery management system (BMS), and a life state of the battery is predicted. Battery life (remaining capacity) is affected by factors (current, temperature, discharge depth, SOC, time).

Existing battery life prediction uses a method of predicting by inducing a polynomial using experimental data through an accelerated life test according to factors. However, this method has a disadvantage in that there is no method for correcting the predicted value, and thus an error between the life prediction and the measured value occurs.

Another method is to use a formula based on current integration. This is a method of predicting the remaining capacity by using the difference in SOC and the integrated value of the current over time. However, in order to accurately predict SOC, it is necessary to use the voltage value in a sufficiently static safe state of the battery or to predict SOC using a very accurate current sensor, but cumulative errors in current integration occur due to the actual driving environment and offset of the current sensor. Therefore, the use of these methods is limited.

An object of the present invention is to provide a system and method for predicting battery health.

A battery health prediction system according to an embodiment of the present invention for solving the above problems includes an information collection unit for collecting state information of a battery cell transmitted from a battery measurement module located in a remote location; and an information processing unit that predicts whether or not there is a failure of the battery cell, a remaining service life, and a replacement time of the battery cell by using the collected state information of the battery cell.

In one embodiment, the state information is impedance, minimum allowable current, minimum allowable voltage, maximum allowable current, maximum allowable voltage, minimum allowable temperature, maximum allowable temperature, current current, current voltage, current internal temperature, state (discharge, charge, standby), voltage waveform, current waveform, number of charge/discharge, and production year.

In one embodiment, the information processing unit is characterized in that it predicts a failure or lifespan by comparing state information of the collected batteries based on failure diagnosis values of batteries diagnosed as failure or failure among the same model.

The information processing unit is characterized in that it determines whether the battery circuit is old and whether there is a failure through a comparison between the harmonic distortion rate measured at a first time point and the harmonic distortion rate measured at a second time point of the battery.

In one embodiment, the battery may further include an alarm unit that transmits an alarm signal to a user terminal when a malfunction is diagnosed.

In one embodiment, the information processing unit calculates voltage/current harmonics and phase using sampling data of voltage/current frequency output from a battery located in a remote location, and calculates the voltage/current harmonics and phase using variability of the voltage/current harmonics and phase. It is characterized by predicting the lifespan and failure point of the battery.

In one embodiment, the battery measurement module is characterized in that it includes a BMS communication relay board for converting the measured state information of the battery into a predetermined communication message and transmitting it to the information collection unit.

A battery health prediction method according to an embodiment of the present invention for solving the above problems includes collecting state information of a battery in a battery measurement module, compressing and transmitting sample data of the collected information; And after restoring the sample data of the state information of the battery cell compressed and transmitted by the information collection unit, the information processing unit analyzes the distortion rate of the voltage/current sample frequency of the battery cell, and harmonic distortion between the first and second points in time. Diagnose whether or not there is a failure of the battery cell through the differential rate, and predict the time of failure or remaining life of the battery cell to be diagnosed by using the battery cell status information and the failure diagnosis value of the battery diagnosed as failure or failure among the same model as a reference After that, the battery cell includes a step of transmitting a result value about failure, remaining life, etc. to the user terminal in the form of an alarm.

Using the battery health prediction system and method according to an embodiment of the present invention, there is an advantage in that remaining life and replacement time can be diagnosed based on remotely collected state information of the battery.

1 is a network configuration diagram of a system for predicting battery health according to an embodiment of the present invention.
FIG. 2 is a detailed configuration diagram of the battery measurement module shown in FIG. 1 .
FIG. 3 is a detailed configuration diagram of the information processing unit shown in FIG. 1 .
4 is a flowchart illustrating a method for predicting battery health according to an embodiment of the present invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

The embodiments of the present invention are provided to more completely explain the present invention to those skilled in the art, and the following examples may be modified in many different forms, and the scope of the present invention is as follows It is not limited to the examples. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the spirit of the invention to those skilled in the art.

In addition, in the following drawings, the thickness or size of each layer is exaggerated for convenience and clarity of explanation, and the same reference numerals refer to the same elements in the drawings. As used herein, the term "and/or" includes any one and all combinations of one or more of the listed items. In addition, the meaning of "connected" in the present specification means not only when member A and member B are directly connected, but also when member A and member B are indirectly connected by interposing member C between member A and member B. do.

Terms used in this specification are used to describe specific embodiments and are not intended to limit the present invention. As used herein, the singular form may include plural forms unless the context clearly indicates otherwise. Also, when used herein, “comprise, include” and/or “comprising, including” refers to a referenced form, number, step, operation, member, element, and/or group thereof. presence, but does not preclude the presence or addition of one or more other shapes, numbers, operations, elements, elements and/or groups.

In this specification, terms such as first and second are used to describe various members, components, regions, layers and/or portions, but these members, components, regions, layers and/or portions are limited by these terms. It is self-evident that These terms are only used to distinguish one element, component, region, layer or section from another region, layer or section. Thus, a first member, component, region, layer or section described in detail below may refer to a second member, component, region, layer or section without departing from the teachings of the present invention.

In addition, the control unit (controller) and/or other related devices or components according to the present invention may be implemented using any suitable hardware, firmware (eg, application specific semiconductor), software, or a suitable combination of software, firmware, and hardware. can For example, various components of a control unit (controller) and/or other related devices or parts according to the present invention may be formed on one integrated circuit chip or on separate integrated circuit chips. In addition, various components of the control unit (controller) may be implemented on a flexible printed circuit film, and may be formed on a tape carrier package, a printed circuit board, or the same substrate as the control unit (controller). In addition, various components of the control unit (controller) may be processes or threads executed in one or more processors in one or more computing devices, which execute computer program instructions to perform various functions mentioned below. and can interact with other components. Computer program instructions are stored in memory that can be executed in a computing device using standard memory devices, such as, for example, random access memory. Computer program instructions may also be stored on other non-transitory computer readable media, such as, for example, a CD-ROM, flash drive, or the like. In addition, those skilled in the art related to the present invention will understand that the functions of various computing devices can be combined with each other, integrated into one computing device, or the functions of a particular computing device can be incorporated into one or more other computing devices without departing from the exemplary embodiments of the present invention. It should be recognized that it can be dispersed in the field.

Hereinafter, a system and method for predicting battery health according to an embodiment of the present invention will be described in more detail based on the accompanying drawings.

1 is a network configuration diagram of a battery health prediction system according to an embodiment of the present invention, FIG. 2 is a detailed configuration diagram of a battery measurement module shown in FIG. 1, and FIG. 3 is a detailed diagram of an information processing unit shown in FIG. It is a composition diagram.

As shown in FIG. 1, the battery health prediction system 100 according to an embodiment of the present invention includes a battery measurement module 200, an information collection unit 300, and a battery life and replacement time prediction unit 300. do.

The battery measurement module 200 may be a module capable of mutual communication with an information collection unit to be described later through an Ethernet method.

The battery measurement module 200 may be configured to measure state information according to characteristic values such as voltage and resistance of a battery cell.

Here, the status information is impedance, minimum allowable current, minimum allowable voltage, maximum allowable current, maximum allowable voltage, minimum allowable temperature, maximum allowable temperature, current current, current voltage, current internal temperature, state (discharge, charge, standby), It may be information including at least one of a voltage waveform, a current waveform, the number of charge/discharge, and a production year.

The battery measurement module 200 may include a plurality of sensors for measuring the above-described state information. It may include sensors capable of performing current/voltage measurement, temperature measurement, and optical code scanning.

In addition, the battery measuring module 200 may include a measuring means having a measuring space whose size is variable according to the size and shape of the battery inserted therein.

In addition, the battery measurement module 200 may be a module equipped with a waveform analysis algorithm for analyzing a voltage waveform and a current waveform according to time of the measured current/voltage.

More specifically, the battery measurement module 200 includes a temperature sensor 201, a voltage sensor 202, a current sensor 203, a cell balancing circuit 204 and a monitoring circuit 205, and a measurement unit 210 composed of It includes a control unit 220 and a communication unit 230.

On the other hand, the battery measurement module 200 further includes a battery cell measurement space unit (not shown) including a space in which a measurement position that meets the specifications of various types of battery cells is displayed as a space for measuring state information of a battery cell. can include

The measurement unit 210 senses the temperature, voltage, and current of the battery over time through a temperature sensor, voltage sensor, and current sensor, and performs cell balancing of temperature, voltage, and current through a monitoring circuit 205. . here, The monitoring unit 205 monitors the minimum allowable current, the minimum allowable voltage, the maximum allowable current, the maximum allowable voltage, the minimum allowable temperature, and the maximum allowable temperature of the battery cell based on the variability of temperature, voltage and current with time. can be config. The monitoring unit 205 may perform cell balancing of the plurality of battery cells 111 through the cell balancing circuit 204 . In some examples, the supervisory circuit 205 may include or be referred to as an Analog Front End (AFE) IC, Cell Voltage Monitoring (CVM) IC.

Next, the controller 220 may be configured to receive temperature, voltage, and current information from the monitoring circuit and calculate the temperature of the battery cell, the charge/discharge rate of the battery cell per hour, the capacity of the battery cell, and the voltage deviation between the battery cells.

A reference temperature range, a charge/discharge rate per reference time, a reference capacity range, and a reference voltage deviation may be stored in the memory of the controller 205 .

In some examples, the reference temperature range is 0 ° C to 50 ° C, the reference charge/discharge rate per hour is 0.01 C to 0.1 C, the reference capacity range is 20% to 40% and 80% to 100%, and the reference voltage deviation is 1 mV to 1000 mV. It can be set to and stored in memory in advance.

In particular, the voltage deviation between the battery cells appears relatively large when the capacity of the battery cells is between 80% and 100% during charging and between 20% and 40% during discharging.

Accordingly, in an embodiment of the present invention, cell balancing is performed at a time when a voltage deviation between battery cells is relatively large.

In addition, the control unit 220 may be configured to generate sample data of state information measured in a battery cell, and then compress and provide the sample data.

The communication unit 230 may communicate with the information collection unit 300 through short-range and/or long-distance communication methods, and may transmit compressed sample data of the measured state information of the battery cell.

The communication unit 230 may include a BMS communication relay board for converting sample data of compressed battery state information into a predetermined communication message and transmitting the same to an information collection unit described later.

Meanwhile, the communication unit 230 may transmit sample data of compressed battery state information to the information processing unit 400 through an Open API.

Next, the information collection unit 300 may be configured to perform Ethernet communication with the battery measurement module 200 located in a remote location and collect state information of the battery measured by the battery measurement module 200 .

Next, the information processing unit 400 may be configured to determine the lifespan and replacement time of the battery using the collected state information of the battery, and provide the determined result to the user terminal.

More specifically, the information processing unit 400 It is possible to predict failure or lifespan by comparing state information of batteries collected based on diagnostic values of batteries diagnosed as faulty or defective in the same model.

also, The information processing unit 400 may determine whether the battery circuit is old and has a failure through a comparison between the harmonic distortion rate measured at a first time point and the harmonic distortion rate measured at a second time point of the battery.

In addition, the information processing unit 400 may further include an alarm unit that transmits an alarm signal to a user terminal when the battery is faulty.

In addition, the information processing unit 400 The voltage/current harmonics and phase are calculated using sampling data of the voltage/current frequency output from the battery located in the remote location, and the lifespan and failure point of the battery can be predicted using the variability of the voltage/current harmonics and phase. there is.

More specifically, the information processing unit 400 includes an analysis unit 410, a harmonic distortion rate calculation unit 420, a comparison unit 430, a failure diagnosis and prediction unit 440, and an alarm unit 450.

The analysis unit 410 analyzes harmonics and phases through the voltage/current frequency of the battery cell measured by the battery measurement module restored by the information collection unit.

Here, the analyzer 410 may analyze the measured voltage/current frequency after a predetermined time from the initial measurement point in the battery cell.

In addition, the analysis unit 410 analyzes the temperature change according to the time change of the battery cell collected by the information collection unit 300 .

Next, the harmonic distortion calculation unit 420 may be configured to analyze the distortion rate of the harmonic waveform of the battery cell calculated by the analysis unit 410 .

The comparator 430 may be configured to compare the harmonic distortion measured at a first point of time of the battery cell with the harmonic distortion measured at a second point in time.

The failure diagnosis and prediction unit 440 determines the presence or absence of a failure of the battery cell based on the result of the comparison unit, for example, the difference between the harmonic distortion rate measured at the first bookstore and the harmonic distortion rate measured at the second point in time.

In addition, the fault diagnosis and prediction unit 440 collects the state information of the battery collected by the government collection unit (impedance, minimum allowable current, minimum allowable voltage, maximum allowable current, maximum allowable voltage, minimum allowable temperature, maximum allowable temperature, The remaining life of the battery and replacement time are determined using current current, current voltage, current internal temperature, state (discharge, charge, standby), voltage waveform, current waveform, and number of charge/discharge cycles.

At this time, the failure diagnosis and prediction unit 440 uses the failure diagnosis value of the battery diagnosed as failure or failure among the same model as a reference and compares it with the state information of the battery cell to be diagnosed to determine the failure time or remaining life of the battery cell. can predict

The alarm unit 450 may be configured to transmit, in the form of an alarm, the predicted value for the failure of the battery cell and the remaining lifespan of the battery cell diagnosed by the failure diagnosis and prediction unit 440 to the user terminal.

4 is a flowchart illustrating a method for predicting battery health according to an embodiment of the present invention.

Referring to FIG. 4 , in the battery health prediction method S700 according to an embodiment of the present invention, first, the battery measurement module 200 collects state information of the battery, and then compresses sample data of the collected information to obtain information It is transmitted to the collection unit 300 (S710).

Here, the battery measurement module 200 may be a module capable of mutual communication with an information collection unit described later in an Ethernet manner, and the battery measurement module 200 provides state information according to characteristic values such as voltage and resistance of a battery cell. It may be a configuration that measures . Here, the status information is impedance, minimum allowable current, minimum allowable voltage, maximum allowable current, maximum allowable voltage, minimum allowable temperature, maximum allowable temperature, current current, current voltage, current internal temperature, state (discharge, charge, standby), It may be information including at least one of a voltage waveform, a current waveform, the number of charge/discharge, and a production year. The battery measurement module 200 may include a plurality of sensors for measuring the above-described state information. It may include sensors capable of performing current/voltage measurement, temperature measurement, and optical code scanning.

In addition, the battery measuring module 200 may include a measuring means having a measuring space whose size is variable according to the size and shape of the battery inserted therein. In addition, the battery measurement module 200 may be a module equipped with a waveform analysis algorithm for analyzing a voltage waveform and a current waveform according to time of the measured current/voltage.

Next, when the sample data of the state information of the battery cell compressed and transmitted by the information collection unit 300 is restored (S721), the information processing unit 400 analyzes the distortion rate of the voltage/current sample frequency of the battery cell (S722). )do.

At this time, the harmonic distortion rate includes the harmonic distortion rate of the voltage / current frequency measured at the first time point (initial stage) and the harmonic distortion rate of the voltage / current frequency measured at the second time point (end stage) of the battery cell.

Thereafter, the information processing unit 400 diagnoses whether or not the battery cell has a failure through a difference in harmonic distortion between the first time point and the second time point. In addition, the information processing unit 400 predicts the time of failure or remaining service life of the battery cell to be diagnosed by using the state information of the battery cell and the failure diagnosis value of the battery diagnosed as failure or failure among the same model as a reference (S724).

Thereafter, the information processing unit 400 transmits a resultant value of the failure of the battery cell, remaining life, etc. to the user terminal in the form of an alarm (S725).

Therefore, using the battery health prediction system and method according to an embodiment of the present invention provides an advantage of diagnosing the remaining service life and replacement time based on the state information of the battery collected remotely.

A “unit” used in one embodiment of the present invention may be implemented as a hardware component, a software component, and/or a combination of hardware components and software components. For example, devices and components described in the embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA), It may be implemented using one or more general purpose or special purpose computers, such as a programmable logic unit (PLU), microprocessor, or any other device capable of executing and responding to instructions. The processing unit includes an operating system (OS) and one or more programs running on the operating system.

of software applications can be performed. A processing device may also access, store, manipulate, process, and generate data in response to execution of software. For convenience of understanding, there are cases in which one processing device is used, but those skilled in the art will understand that the processing device includes a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that it can include. For example, a processing device may include a plurality of processors or a processor and a controller. Other processing configurations are also possible, such as parallel processors.

Software may include a computer program, code, instructions, or a combination of one or more of the foregoing, which configures a processing device to operate as desired or processes independently or collectively. You can command the device. Software and/or data may be any tangible machine, component, physical device, virtual equipment, computer storage medium or device, intended to be interpreted by or to provide instructions or data to a processing device. , or may be permanently or temporarily embodied in a transmitted signal wave. Software may be distributed on networked computer systems and stored or executed in a distributed manner. Software and data may be stored on one or more computer readable media.

The method according to the embodiment of the present invention may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer readable medium. The computer readable medium may include program instructions, data files, data structures, etc. alone or in combination. Program commands recorded on the medium may be specially designed and configured for the embodiment or may be known and usable to those skilled in computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. - includes hardware devices specially configured to store and execute program instructions, such as magneto-optical media, and ROM, RAM, flash memory, and the like. Examples of program instructions include high-level language codes that can be executed by a computer using an interpreter, as well as machine language codes such as those produced by a compiler. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

The present invention is not limited by the foregoing embodiments and accompanying drawings. It will be clear to those skilled in the art that the components according to the present invention can be substituted, modified, and changed without departing from the technical spirit of the present invention.

100: battery health prediction system
200: battery measurement module
210: measuring unit
201: temperature sensor
202: voltage sensor
203: current sensor
204: cell balancing circuit
205: supervisory circuit
220: control unit
230: communication department
300: information collection department
400: information processing department
410: analysis unit
420: harmonic distortion rate calculation unit
430: comparison unit
440: fault diagnosis and prediction unit
450: alarm unit

Claims (8)

an information collection unit that collects state information of a battery cell transmitted from a battery measurement module located in a remote location; and
A battery health prediction system comprising an information processing unit that predicts whether or not there is a failure of the battery cell, remaining lifespan, and replacement time of the battery cell using collected state information of the battery cell.

According to claim 1,
The status information
Impedance, minimum allowable current, minimum allowable voltage, maximum allowable current, maximum allowable voltage, minimum allowable temperature, maximum allowable temperature, current current, present voltage, current internal temperature, status (discharge, charge, standby), voltage waveform, current A battery health prediction system including at least one of waveform, charge/discharge count, and production year.
According to claim 1,
The information processing unit
A battery health prediction system, characterized in that for predicting a failure or lifespan by comparing state information of a battery collected based on a diagnostic value of a battery diagnosed as failure or failure in the same model.
According to claim 3,
The information processing unit
A battery health prediction system for determining the aging and failure of the battery circuit through comparison between the harmonic distortion rate measured at a first time point of the battery and the harmonic distortion rate measured at a second time point of the battery.
According to claim 4,
The battery health prediction system further comprising an alarm unit for transmitting an alarm signal to a user terminal when the battery is diagnosed.

According to claim 1,
The information processing unit
Calculating voltage/current harmonics and phase using sampling data of voltage/current frequency output from the battery located in the remote location, and predicting the lifespan and failure point of the battery using the variability of the voltage/current harmonics and phase Battery health prediction system, characterized in that.
According to claim 1,
The battery measurement module
A battery health prediction system comprising a BMS communication relay board that converts the measured state information of the battery into a predetermined communication message and transmits it to the information collection unit.
After collecting state information of the battery in the battery measurement module, compressing and transmitting sample data of the collected information; and
After restoring the sample data of the state information of the battery cell compressed and transmitted by the information collection unit, the information processing unit analyzes the distortion rate of the voltage/current sample frequency of the battery cell, and the harmonic distortion rate between the first time point and the second time point. It diagnoses the failure of the battery cell through the car, and predicts the failure time or remaining life of the battery cell to be diagnosed by using the battery cell status information and the failure diagnosis value of the battery diagnosed as failure or defect among the same model as a reference. and then transmitting, in the form of an alarm, a resultant value of the failure of the battery cell, remaining life, etc. to a user terminal.

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