Patent Description:
Recently, there has been a rapid increase in the demand for portable electronic products such as laptop computers, video cameras and mobile phones, and with the extensive development of electric vehicles, accumulators for energy storage, robots and satellites, many studies are being made on high performance batteries that can be repeatedly recharged.

Currently, commercially available batteries include nickel-cadmium batteries, nickel-hydrogen batteries, nickel-zinc batteries, lithium batteries and the like, and among them, lithium batteries have little or no memory effect, and thus they are gaining more attention than nickel-based batteries for their advantages that recharging can be done whenever it is convenient, the self-discharge rate is very low and the energy density is high.

Recently, with the widespread of applications requiring high voltage, a battery pack including a plurality of battery cells connected in series is being widely used. As the number of battery cells included in the battery pack increases, there is an increasing likelihood that an abnormality of the battery cell occurs. Accordingly, there is an increasing need for diagnosis technology for accurately detecting an abnormality of the battery cell.

The related art monitors cell information (for example, voltage, current, temperature) including a plurality of parameters associated with a state of the battery cell, and detects an abnormality of the battery cell based on the operational state (for example, charge, discharge, rest) of the battery cell and the monitored cell information.

However, the above-described abnormality detection method requires a battery management system (BMS) to monitor the cell information of the battery cell using many sensors, so abnormality detection requires a large amount of computation and a long time. In particular, under the structure in which the power of the BMS is supplied from the battery cell, the electrical energy of the battery cell may be consumed all the time during the operation of the BMS for abnormality detection.

Moreover, the related art detects abnormality of the battery cell based on the rapid changes in the cell information of the battery cell in a short time. However, in some instances, the cell information of the faulty battery cell does not always rapidly change in a short time, and may tend to slowly change over a long period of time, failing to detect an abnormality of the battery cell at a proper time.

Document <CIT> discloses a method of diagnosing fault in a battery comprising a plurality of cells. The method comprises obtaining voltage values in time for each cell of the battery and establishing a cell voltage matrix made of elements am,n based on cell voltage values, where m represents the sampling time and n represents the cell number, setting a sliding window size, and applying calculations for identifying an abnormal variance value within each window of the sliding window.

The present disclosure is designed to solve the above-described problem, and therefore the present disclosure is directed to providing a battery diagnosis device, a battery pack, a battery system and a battery diagnosis method using a cell voltage of each of a plurality of battery cells connected in series as a single parameter for abnormality detection.

The present disclosure is further directed to providing a battery diagnosis device, a battery pack, a battery system and a battery diagnosis method for battery cell abnormality detection, in which an observation matrix is generated, the observation matrix being a dataset including a plurality of observation voltage vectors indicating a voltage history (time-series) of a cell voltage of each of a plurality of battery cells observed during the same period, and an abnormal behavior of the cell voltage of each battery cell is identified based on a result of analyzing the observation matrix.

These and other objects and advantages of the present disclosure may be understood by the following description and will be apparent from the embodiments of the present disclosure. In addition, it will be readily understood that the objects and advantages of the present disclosure may be realized by the means set forth in the appended claims and a combination thereof.

A battery diagnosis device according to the present invention includes a memory configured to store an observation matrix including a plurality of observation voltage vectors indicating a time-series of cell voltage of each of a plurality of battery cells, and a control unit configured to determine a plurality of principal component vectors, a plurality of singular values and a plurality of coefficient vectors from the observation matrix. Each coefficient vector includes a plurality of coefficients corresponding to the plurality of observation voltage vectors in a one-to-one relationship. The control unit is configured to, for each coefficient vector, determine an invalid coefficient among the plurality of coefficients by comparing the plurality of coefficients included in the corresponding coefficient vector, and detect abnormality of the battery cell corresponding to the invalid coefficient among the plurality of battery cells based on the principal component vector corresponding to the corresponding coefficient vector among the plurality of principal component vectors, the singular value corresponding to the corresponding coefficient vector among the plurality of singular values and the invalid coefficient.

The control unit may be configured to determine a first sub-matrix, a second sub-matrix and a third sub-matrix by applying a matrix decomposition algorithm to the observation matrix. The first sub-matrix includes the plurality of principal component vectors as column vectors. The second sub-matrix includes the plurality of singular values as elements of a principal diagonal. The third sub-matrix includes the plurality of coefficient vectors as row vectors.

The control unit may be configured to determine, as the invalid coefficient, the coefficient of which an absolute value of a difference between the coefficient and an average of the plurality of coefficients among the plurality of coefficients is larger than a first reference value.

The control unit may be configured to determine the first reference value to be equal to a value obtained by multiplying a standard deviation of the plurality of coefficients by a first scaling factor.

The control unit may be configured to, for each coefficient vector, extract a partial voltage vector of the observation voltage vector corresponding to the invalid coefficient among the plurality of observation voltage vectors by multiplying the principal component vector corresponding to the corresponding coefficient vector among the plurality of principal component vectors, the singular value corresponding to the corresponding coefficient vector among the plurality of singular values and the invalid coefficient, and detect the battery cell corresponding to the invalid coefficient among the plurality of battery cells as faulty when a voltage characteristic value of the partial voltage vector is larger than a second reference value.

The control unit may be configured to determine the voltage characteristic value to be equal to a difference between a maximum partial voltage and a minimum partial voltage among a plurality of partial voltages included in the partial voltage vector.

The control unit may be configured to determine the second reference value to be equal to a value obtained by multiplying a voltage resolution of a voltage measurement circuit by a second scaling factor.

The control unit may be configured to output a fault message when a ratio of a maximum singular value to a minimum singular value among the plurality of singular values is less than a preset value.

A battery pack according to another aspect of the present invention includes the battery diagnosis device.

A battery system according to still another aspect of the present invention includes the battery pack.

A battery diagnosis method according to the present invention includes determining a plurality of principal component vectors, a plurality of singular values and a plurality of coefficient vectors from an observation matrix including a plurality of observation voltage vectors indicating a time series of cell voltage of each of a plurality of battery cells. Each coefficient vector includes a plurality of coefficients corresponding to the plurality of observation voltage vectors in a one-to-one relationship. The battery diagnosis method further includes, for each coefficient vector, determining an invalid coefficient among the plurality of coefficients by comparing the plurality of coefficients included in the corresponding coefficient vector, and detecting abnormality of the battery cell corresponding to the invalid coefficient among the plurality of battery cells based on the principal component vector corresponding to the corresponding coefficient vector among the plurality of principal component vectors, the singular value corresponding to the corresponding coefficient vector among the plurality of singular values and the invalid coefficient.

Determining the invalid coefficient among the plurality of coefficients may include determining, as the invalid coefficient, the coefficient of which an absolute value of a difference between the coefficient and an average of the plurality of coefficients among the plurality of coefficients is larger than a first reference value.

Detecting abnormality of the battery cell corresponding to the invalid coefficient among the plurality of battery cells may include extracting a partial voltage vector of the observation voltage vector corresponding to the invalid coefficient among the plurality of observation voltage vectors by multiplying the principal component vector corresponding to the corresponding coefficient vector among the plurality of principal component vectors, the singular value corresponding to the corresponding coefficient vector among the plurality of singular values and the invalid coefficient, and detecting the battery cell corresponding to the invalid coefficient among the plurality of battery cells as faulty when a voltage characteristic value of the partial voltage vector is larger than a second reference value.

According to at least one of the embodiments of the present disclosure, it is possible to reduce the computational amount, time and power required for abnormality detection by using only the cell voltage except the current or temperature to detect abnormality of each of a plurality of battery cells connected in series.

In addition, according to at least one of the embodiments of the present disclosure, it is possible to improve the accuracy of battery cell abnormality detection by generating an observation matrix which is a dataset including a plurality of observation voltage vectors indicating a voltage history (time-series) of a cell voltage of each of a plurality of battery cells observed for the same period of time, and identifying an abnormal behavior of the cell voltage of each battery cell based on a result of analyzing the observation matrix.

The effects of the present disclosure are not limited to the effects mentioned above, and these and other effects will be clearly understood by those skilled in the art from the appended claims.

Therefore, the embodiments described herein and illustrations shown in the drawings are just a most preferred embodiment of the present disclosure, but not intended to fully describe the technical aspects of the present disclosure, so it should be understood that a variety of modifications could have been made thereto at the time that the application was filed.

Unless the context clearly indicates otherwise, it will be understood that the term "comprises" when used in this specification, specifies the presence of stated elements, but does not preclude the presence or addition of one or more other elements. Additionally, the term "control unit" as used herein refers to a processing unit of at least one function or operation, and this may be implemented by hardware and software either alone or in combination.

<FIG> is a diagram exemplarily showing a configuration of a battery system according to the present disclosure.

<FIG> shows an energy storage system as an example of the battery system <NUM>. Referring to <FIG>, the battery system <NUM> includes a battery pack <NUM> and a switch <NUM>. The battery system <NUM> may further include at least one of a remote controller <NUM> or a power conversion system <NUM>. The battery system <NUM> is not limited to the energy storage system, and may include any battery system having a charging function and/or a discharging function of the battery pack <NUM> provided therein, such as an electric vehicle or a battery tester.

The battery pack <NUM> includes a positive terminal P+, a negative terminal P-, a cell group <NUM> and a battery management system <NUM>. The cell group <NUM> includes a plurality of battery cells BC<NUM>~BCn (n is a natural number of <NUM> or greater) electrically connected between the positive terminal P+ and the negative terminal P-. <FIG> shows the plurality of battery cells BC<NUM>~BCn connected in series within the cell group <NUM>. Hereinafter, in providing the description in common to the plurality of battery cells BC<NUM>~BCn, the reference sign 'BC' is used to refer to the battery cell.

The positive terminal and the negative terminal of the battery cell BC are electrically coupled to other battery cell BC through a conductor such as a busbar. The battery cell BC may be a lithium ion battery cell. The battery cell BC is not limited to a particular type, and may include any type of battery cell that can be repeatedly recharged.

The switch <NUM> is installed on a power line PL for the battery pack <NUM>. While the switch <NUM> is on, power transfer from any one of the battery pack <NUM> or the power conversion system <NUM> to the other is possible. The switch <NUM> may be implemented as at least one of well-known switching devices such as a relay and a Field Effect Transistor (FET).

The power conversion system <NUM> is operably coupled to at least one of the battery management system <NUM> or the remote controller <NUM>. Operably coupled refers to directly/indirectly connected to transmit and receive a signal in one or two directions. The power conversion system <NUM> may produce the direct current power for the charge of the cell group <NUM> from the alternating current power supplied by an electrical grid <NUM>. The power conversion system <NUM> may produce the alternating current power from the direct current power from the battery pack <NUM>.

The battery management system <NUM> may include a voltage measurement circuit <NUM> and a battery controller <NUM>. The battery management system <NUM> may further include at least one of a current sensor <NUM>, a temperature sensor <NUM> or an interface unit <NUM>. The interface unit <NUM> may be included in the battery controller <NUM>.

The voltage measurement circuit <NUM> is provided to be electrically connectable to the positive terminal and the negative terminal of the battery cell BC. The voltage measurement circuit <NUM> may measure a cell voltage or a voltage across the battery cell BC, and output a signal indicating the measured cell voltage to the battery controller <NUM>.

The current sensor <NUM> is electrically connected in series to the cell group <NUM> through the power line PL. For example, a shunt resistor or a hall effect device may be used as the current sensor <NUM>. The current sensor <NUM> may measure a current flowing through the cell group <NUM>, and output a signal indicating the measured current to the battery controller <NUM>.

The temperature sensor <NUM> is disposed within a predetermined distance range from the cell group <NUM>. For example, a thermocouple may be used as the temperature sensor <NUM>. The temperature sensor <NUM> may measure a temperature of the cell group <NUM>, and output a signal indicating the measured temperature to the battery controller <NUM>.

The battery controller <NUM> is operably coupled to the voltage measurement circuit <NUM>, the current sensor <NUM>, the temperature sensor <NUM> and/or the interface unit <NUM>. At least one of the battery controller <NUM> or the remote controller <NUM> may control the on/off of the switch <NUM> according to the result of diagnosis for the cell group <NUM>.

The interface unit <NUM> may be coupled to the remote controller <NUM> of the battery system <NUM> to enable communication. The interface unit <NUM> may transmit a signal from the remote controller <NUM> to the battery controller <NUM>, and a signal from the battery controller <NUM> to the remote controller <NUM>. The signal from the battery controller <NUM> may include information for notifying abnormality of the battery cell BC. The communication between the interface unit <NUM> and the remote controller <NUM> may use, for example, a wired network such as a local area network (LAN), a controller area network (CAN) and a daisy chain and/or a wireless network such as Bluetooth, Zigbee and Wi-Fi. The interface unit <NUM> may include an output device (for example, a display, a speaker) to provide the information received from the battery controller <NUM> and/or the remote controller <NUM> in a recognizable format. The remote controller <NUM> may control at least one of the battery pack <NUM>, the switch <NUM> or the power conversion system <NUM> based on cell information (for example, cell voltage, current, temperature, SOC, abnormality of the battery cell BC) collected through communication with the battery management system <NUM>.

The battery controller <NUM> includes a memory <NUM> and a control unit <NUM>. The remote controller <NUM> may include a memory <NUM> and a control unit <NUM>. The remote controller <NUM> may further include a communication circuit <NUM>. The remote controller <NUM> may be implemented in the form of a cloud server or a mobile diagnosis device. The communication circuit <NUM> is for wired/wireless communication with the battery management system <NUM>.

Each of the control unit <NUM> and the control unit <NUM> may be implemented in hardware using at least one of application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), microprocessors or electrical units for performing the other functions.

At least one of the memory <NUM> or the memory <NUM> may pre-store programs and data necessary to perform battery diagnosis methods (diagnosis procedures) according to embodiments as described below. Each of the memory <NUM> and the memory <NUM> may include, for example, at least one type of storage medium of flash memory type, hard disk type, Solid State Disk (SSD) type, Silicon Disk Drive (SDD) type, multimedia card micro type, random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM) or programmable read-only memory (PROM). At least one of the memory <NUM> or the memory <NUM> may record data and algorithms required to detect abnormality of the battery BC by performing the following diagnosis procedures (<FIG>). The memory <NUM> and the control unit <NUM> may be integrated into a single chip. The memory <NUM> and the control unit <NUM> may be integrated into a single chip.

The battery controller <NUM> is an example of a battery diagnosis device according to the present disclosure, and the remote controller <NUM> is another example of a battery diagnosis device according to the present disclosure. That is, the diagnosis procedures described below with reference to <FIG> are performed by at least one of the battery controller <NUM> or the remote controller <NUM> provided as a battery diagnosis device.

The battery diagnosis device according to the present disclosure may perform the diagnosis procedures (see <FIG> and <FIG>) for detecting abnormality of the plurality of battery cells BC<NUM>~BCn. The diagnosis procedures may be based on voltage data (see X<NUM>~Xn in <FIG>) acquired for a specified period (for example, a predetermined time in the past) during which the cell group <NUM> is kept in a predetermined diagnosis possible state (for example, rest, constant current charge, constant voltage charge, constant current discharge). The following description will be made under the assumption that the battery controller <NUM> is provided as a battery diagnosis device.

<FIG> is a graph exemplarily showing a change in cell voltage of the battery cell over time, and <FIG> is a diagram referenced in describing an exemplary observation matrix as a dataset indicating a voltage history of the battery cell shown in <FIG>.

The control unit <NUM> may determine a voltage value of the cell voltage of each of the plurality of battery cells BC<NUM>~BCn at a predetermined time interval based on the voltage signal from the voltage measurement circuit <NUM>, and record the determined voltage value in the memory <NUM>. The preset time may be equal to a time length of a period for abnormality detection as described below.

The control unit <NUM> determines an observation matrix X including a plurality of observation voltage vectors X<NUM>~Xn over the specified period Δt for the predetermined time in the past. A moving window <NUM> may be used to determine the observation matrix X. For example, the plurality of observation voltage vectors X<NUM>~Xn indicates a time-dependent change in the cell voltage of each of the plurality of battery cells BC<NUM>~BCn measured at the preset time interval within the moving window <NUM>. The moving window <NUM> is used to set the period Δt during which the plurality of observation voltage vectors X<NUM>~Xn is obtained with the movement of the moving window <NUM> by the preset time interval at the preset time interval. The size Δt of the moving window <NUM> may be preset or adjustable by the control unit <NUM>.

The cell voltage of the battery cell BC may be measured by the voltage measurement circuit <NUM> multiple times (for example, a total of m, m is a natural number of <NUM> or greater) in time series, and the measured cell voltages may be recorded in the memory <NUM> by the control unit <NUM>. For example, where the size of the moving window <NUM> = <NUM> sec and the preset time = <NUM> sec, m=<NUM>, and thus the cell voltage of the battery cell BC is measured <NUM> times within the moving window <NUM>.

Referring to <FIG>, a curve <NUM> exemplarily indicates a time-dependent change in the cell voltage of the kth battery cell BCk among the plurality of battery cells BC<NUM>~BCn. The abnormal state may be a state that triggers an abnormal behavior of the cell voltage, for example, an internal short circuit. In <FIG>, t<NUM> and tm are the starting time and the ending time of the specified period Δt, respectively, and ti is a time point corresponding to a time index i within the specified period Δt. In the kth battery cell BCk, k is a natural number of n or smaller, and may indicate a cell index used to distinguish the plurality of battery cells BC<NUM>~BCn.

Hereinafter, the abnormality detection operation according to the present disclosure will be described on the basis of the kth battery cell BCk. The description of the kth battery cell BCk may be applied in common to the remaining battery cells BC of the plurality of battery cells BC<NUM>~BCn.

Referring to <FIG>, the observation matrix X is an m×n matrix including m rows and n columns. Hereinafter, for convenience of description, assume that m is a natural number that is larger than n, i is a natural number of <NUM> or greater and m or smaller, j is a natural number of <NUM> or greater and n or smaller, and k is a natural number of less than n.

The n column vectors of the observation matrix X may correspond to the plurality of observation voltage vectors X<NUM>~Xn in a one-to-one relationship. That is, each of the plurality of observation voltage vectors X<NUM>~Xn is a column vector of the observation matrix X, and includes m elements (the measured cell voltages). The kth observation voltage vector Xk is a time-series array of the cell voltage of the kth battery cell BCk measured m times, i.e., a time-series (set) of the measured cell voltages x<NUM> ~ xmk of the kth battery cell BCk. The kth observation voltage vector Xk may be the kth column vector of the observation matrix X. Referring to <FIG>, in the observation matrix X, 'xik' is an element (referred to as 'data' or 'component') indicating the ith measured cell voltage among the cell voltages of the kth battery cell BCj measured a total of m times within the specific period Δt.

The control unit <NUM> may extract a first sub-matrix A, a second sub-matrix B and a third sub-matrix CT from the observation matrix X by applying matrix decomposition to the observation matrix X. That is, the observation matrix X may be decomposed into the first sub-matrix A, the second sub-matrix B and the third sub-matrix CT. An algorithm used in the matrix decomposition may include, for example, Singular Value Decomposition (SVD) and Principal Component Analysis (PCA). In the specification, the superscript 'T' on the right side of the matrix indicates a transposed matrix. As shown, the product of multiplying the first sub-matrix A, the second sub-matrix B and the third sub-matrix CT is equal to the observation matrix X.

The first sub-matrix A is an m×m matrix. The second sub-matrix B is an m×n matrix. The third sub-matrix CT is an n×n matrix.

The first sub-matrix A is an orthogonal matrix, and includes a plurality of principal component vectors A<NUM>~Am. Each principal component vector of the plurality of principal component vectors A<NUM>~Am may be referred to as a 'left singular vector'. Each principal component vector includes m elements, and may be a column vector of the first sub-matrix A. That is, the first sub-matrix A may be expressed below. <MAT> <MAT>.

Among the plurality of principal component vectors A<NUM>~Am, the principal component vectors A<NUM>∼An indicate variance information of the observation matrix X. The jth principal component vector Aj corresponds to an axial direction in which the variance of elements of the observation matrix X is the jth largest one. That is, when the elements of the observation matrix X are mapped to the axis of each of the plurality of principal component vectors A<NUM>~Am once, the variance of the elements of the observation matrix X along the axis of the jth principal component vector Aj may be the jth largest.

As the variance of the jth principal component vector Aj is larger, it indicates that the jth principal component vector Aj has a larger descriptive factor for a distribution of elements of the observation matrix X. As the descriptive factor of the jth principal component vector Aj increases, the jth principal component vector Aj contains a larger amount of information associated with the common voltage behavior characteristics (for example, a tendency of normal voltage behavior) of the plurality of battery cells BC<NUM>~BCn within the moving window <NUM>. On the contrary, as the variance of the jth principal component vector Aj is smaller, the descriptive factor of the jth principal component vector Aj is lower, i.e., the jth principal component vector Aj contains a larger amount of information associated with noisy characteristics (for example, abnormal state).

The second sub-matrix B is a diagonal matrix, and includes a plurality of singular values b<NUM>~bnn as elements of a principal diagonal. That is, the second sub-matrix B may be expressed below. <MAT> <MAT>.

Where i≠j, bij is <NUM>. bjj is the jth singular value.

That is, among the total of m×n elements of the second sub-matrix B, the remaining elements except n elements b<NUM>~bnn of the principal diagonal are all <NUM>. Accordingly, among the plurality of principal component vectors A<NUM>~Am, the principal component vectors An+<NUM>~Am, may be redundant in the description of the variance information of the observation vector X.

The plurality of singular values b<NUM>~bnn may satisfy the following relationship. b<NUM> ≥ b<NUM>≥. ≥ bnn ≥ <NUM>. The plurality of singular values b<NUM>~bnn may be referred to as first to nth singular values in the descending order of size, and bjj may be the jth largest singular value among the plurality of singular values b<NUM>~bnn.

The plurality of singular values b<NUM>~bnn indicates descriptive factor information of the plurality of principal component vectors A<NUM>~An. The singular value bjj of the second sub-matrix B indicates the descriptive factor of the jth principal component vector Aj.

The third sub-matrix CT is an orthogonal matrix and includes a plurality of coefficient vectors C<NUM>T~CnT. Each coefficient vector of the plurality of coefficient vectors C<NUM>T~CnT may be referred to as a 'right singular vector'. Each coefficient vector includes n components, and may be a row vector of the third sub-matrix CT. The third sub-matrix CT may be expressed below. <MAT> <MAT>.

The plurality of coefficient vectors C<NUM>T~CnT indicates dependency information of the plurality of observation voltage vectors X<NUM>~Xn on the plurality of principal component vectors A<NUM>~An. Specifically, how much each of the plurality of observation voltage vectors X<NUM>~Xn is affected by the jth principal component vector Aj is set by the jth coefficient vector CjT. The jth coefficient vector CjT includes a plurality of coefficients cj1~cjn corresponding to the first to nth observation voltage vectors X<NUM>~Xn in a one-to-one relationship. For example, cjk of the jth coefficient vector CjT indicates the influence of the jth principal component vector Aj on the kth observation voltage vector Xk.

The first to nth principal component vectors A<NUM>~An, the first to nth singular values b<NUM>~bnn and the first to nth coefficient vectors C<NUM>T~CnT may correspond to one another in a one-to-one relationship.

The observation matrix X is equal to the multiplication of the first sub-matrix A, the second sub-matrix B and the third sub-matrix CT, and may satisfy the relationship by the following Equation <NUM>.

In Equation <NUM>, Aj is treated as a (m×<NUM>) matrix, and CjT is treated as a (<NUM>×n) matrix.

Referring to Equation <NUM>, the kth observation voltage vector Xk is equal to the sum of first to nth partial voltage vectors that depend on the first to nth principal component vectors A<NUM>~An in a one-to-one relationship, and may satisfy the relationship by the following Equation <NUM>.

In Equation <NUM>, Ykj = (bjj × Aj × cjk) is the jth partial voltage vector of the kth observation voltage vector Xk. The jth partial voltage vector Ykj of the kth observation voltage vector Xk is a voltage component of the kth observation voltage vector Xk that depends on the jth principal component vector Aj, and may be equal to the multiplication of the jth principal component vector Aj, the jth singular value bjj and the coefficient cjk. That is, the jth partial voltage vector Ykj may be the result of recovering (approximating) the kth observation voltage vector Xk using only the jth principal component vector Aj among the first to nth principal component vectors A<NUM>~An. Accordingly, the jth partial voltage vector Ykj has m elements corresponding to m elements of the kth observation voltage vector Xk in a one-to-one relationship. The element of each partial voltage vector may be referred to as 'partial voltage (or approximation voltage)', and the partial voltage vector may be referred to as 'recovery voltage vector'.

The control unit <NUM> may calculate a ratio of a maximum singular value b<NUM> to a minimum singular value bnn among the first to nth singular values b<NUM>~bnn prior to detecting abnormality of the first to nth battery cells BC<NUM>~BCn based on the first to nth principal component vectors A<NUM>~An, the first to nth singular values b<NUM>~bnn and the first to nth coefficient vectors C<NUM>T~CnT. When the ratio of the maximum singular value b<NUM> to the minimum singular value bnn is less than a preset ratio (for example, <NUM>%), the control unit <NUM> may output a fault message indicating disabled abnormality detection of the battery cell BC. The disabled abnormality detection is a situation in which there is no explicit difference in descriptive factor between the plurality of principal component vectors A<NUM>~An. That is, in the disabled abnormality detection situation, none of the plurality of principal component vectors A<NUM>~An sufficiently includes information associated with the common voltage behavior characteristics of the plurality of battery cells BC<NUM>~BCn. The cause of the disabled abnormality detection may be, for example, malfunction of the voltage measurement circuit <NUM> or abnormality in the number of battery cells BC exceeding a predetermined ratio (for example, <NUM>%) among the first to nth battery cells BC<NUM>~BCn.

When the ratio of the maximum value b<NUM> to the minimum value bnn is less than the preset ratio, the control unit <NUM> may increase the size of the moving window <NUM> by a predetermined time in the next cycle. The reason of increasing the size of the moving window <NUM> is to sufficiently reflect the common voltage behavior characteristics of the plurality of battery cells BC<NUM>~BCn in the observation vectors X.

<FIG> is a graph exemplarily showing the coefficient vector. In <FIG>, the horizontal axis indicates the cell index corresponding to each coefficient of the jth coefficient vector CjT, and the vertical axis indicates the size of each coefficient. For example, the cell index=<NUM> corresponds to the first battery cell BC<NUM>.

The control unit <NUM> determines whether there is an invalid coefficient in first to nth coefficients cj1~cjn included in the jth coefficient vector CjT by comparing the first to nth coefficients cj1~cjn. The invalid coefficient of the jth coefficient vector CjT indicates the degree of abnormal voltage behavior by the jth principal component vector Aj reflected in the voltage history of the specific battery cell corresponding to the corresponding invalid coefficient. The remaining coefficients except the invalid coefficient may be a valid coefficient.

Referring to <FIG>, the control unit <NUM> may determine an average cj_av and a standard deviation of the first to nth coefficients cj1~cjn included in the jth coefficient vector CjT. The control unit <NUM> may determine a first reference value Rj1 based on the standard deviation of the first to nth coefficients cj1~cjn. For example, the control unit <NUM> may determine the first reference value Rj1 to be equal to the multiplication of the standard deviation and a first scaling factor. The first scaling factor may be pre-recorded in the memory <NUM>.

The control unit <NUM> may determine each coefficient having an absolute value of difference between the coefficient and the average cj_av larger than the first reference value Rj1 among the first to nth coefficients cj1~cjn as the invalid coefficient of the jth coefficient vector CjT. <FIG> shows that the coefficient cjk is smaller than the average cj_av by more than the first reference value Rj1. Accordingly, the control unit <NUM> may determine the coefficient cjk as the invalid coefficient of the jth coefficient vector CjT.

<FIG> is a diagram reference in describing the relationship between the invalid coefficient and the partial voltage vector. <FIG> is a graph exemplarily showing the jth partial voltage vector Ykj of the kth observation voltage vector Xk corresponding to the invalid coefficient cjk of <FIG>. In the same way as the kth observation voltage vector Xk, the jth partial voltage vector Ykj is an (m×<NUM>) matrix. In <FIG>, the horizontal axis indicates the time index within the moving window <NUM>, and the vertical axis indicates the partial voltage.

Referring to <FIG>, the control unit <NUM> may determine a voltage characteristic value of the partial voltage vector Ykj based on m partial voltages included in the partial voltage vector Ykj. The voltage characteristic value may be a parameter indicating the influence (occupancy rate) of the partial voltage vector Ykj on the kth observation voltage vector Xk. Within the moving window <NUM>, a large rate and/or slope of the voltage change exhibited by the partial voltage vector Ykj may indicate that the abnormal voltage behavior associated with the invalid coefficient cjk is greatly reflected in the kth observation voltage vector Xk. For example, the control unit <NUM> may determine the voltage characteristic value to be equal to a difference Δykj between the maximum partial voltage ykj_max and the minimum partial voltage ykj_min among the m partial voltages of the partial voltage vector Ykj. Alternatively, the control unit <NUM> may determine the voltage characteristic value to be equal to a slope between the maximum partial voltage ykj_max and the minimum partial voltage ykj_min.

When the voltage characteristic value of the partial voltage vector Ykj is larger than a second reference value, the control unit <NUM> may detect the kth battery cell BCk corresponding to the invalid coefficient cjk as faulty. The control unit <NUM> may determine the second reference value based on the voltage resolution of the voltage measurement circuit <NUM>. For example, the control unit <NUM> may determine the second reference value to be equal to multiplication of the voltage resolution and a second scaling factor. The second scaling factor may be pre-recorded in the memory. Alternatively, the second reference value may be preset to, for example, <NUM> mV, considering the voltage resolution. The second reference value is for preventing the likelihood that a normal battery cell is wrongly detected as a faulty battery cell due to a measurement error of the cell voltage measured by the voltage measurement circuit <NUM>. When the voltage characteristic value Δykj is larger than the second reference value, the kth battery cell BCk may be determined to be faulty.

<FIG> is a flowchart exemplarily showing a battery diagnosis method according to a first embodiment of the present disclosure. The method of <FIG> may be repeated at a preset time interval.

Referring to <FIG>, in step S610, the control unit <NUM> determines an observation matrix X including ae plurality of observation voltage vectors X<NUM>~Xn corresponding to a plurality of battery cells BC<NUM>~BCn in a one-to-one relationship. The plurality of observation voltage vectors X<NUM>~Xn indicates a time series of cell voltage of each of the plurality of battery cells BC<NUM>~BCn measured multiple times m in time series within the moving window <NUM>.

In step S620, the control unit <NUM> determines a plurality of principal component vectors A<NUM>~An, a plurality of singular values b<NUM>~bnn and a plurality of coefficient vectors C<NUM>T~CnT from the observation matrix X (see Equation <NUM>).

Steps S630 to S670 may be performed once for at least one of the plurality of coefficient vectors C<NUM>T~CnT. For example, the steps S630 to S670 may be performed on a predetermined number of coefficient vectors corresponding to a predetermined number of singular values among the plurality of singular values b<NUM>~bnn in an ascending order. In another example, the steps S630 to S670 may be performed on the coefficient vector corresponding to each singular value of which a ratio to the sum of the plurality of singular values b<NUM>~bnn is equal to or less than a predetermined value.

In the step S630, the control unit <NUM> determines a first reference value Rj1 by comparing a plurality of coefficients cj1~cjn of the coefficient vector CjT. Alternatively, the first reference value Rj1 may be a preset constant, and in this case, the step S630 may be omitted.

In step S640, the control unit <NUM> determines whether at least one of the plurality of coefficients cj1~cjn is larger than the first reference value Rj1. When a value of the step S640 is "No", the method may end. When the value of the step S640 is "Yes", the method performs step S650.

In step S650, the control unit <NUM> determines the coefficient cjk larger than the first reference value Rj1 among the plurality of coefficients cj1~cjn as an invalid coefficient of the coefficient vector CjT.

In step S660, the control unit <NUM> extracts a partial voltage vector Ykj of the observation voltage vector Xk corresponding to the invalid coefficient cjk based on the principal component vector Aj, the singular value bjj and the invalid coefficient cjk (see Equation <NUM>).

In step S670, the control unit <NUM> determines a voltage characteristic value Δykj of the partial voltage vector Ykj.

In step S680, the control unit <NUM> determines whether the voltage characteristic value Δykj is larger than a second reference value. When a value of the step S680 is "No", the method may end. The value of the step S680 being "Yes" indicates that the battery cell BCk corresponding to the invalid coefficient cjk is detected as faulty. When the value of the step S680 is "Yes", the method performs step S690.

In step S690, the control unit <NUM> activates a predetermined protection operation. For example, the control unit <NUM> turns off the switch <NUM>. In another example, the control unit <NUM> outputs a diagnosis message indicating information (for example, the cell index) of the battery cell BCk detected as faulty. The diagnosis message may be transmitted and received between the battery controller <NUM> and the remote controller <NUM> through the interface unit <NUM>. The interface unit <NUM> may output visual and/or audible information corresponding to the diagnosis message.

<FIG> is a flowchart exemplarily showing a battery diagnosis method according to a second embodiment of the present disclosure. The method of <FIG> may be repeated at a preset time interval.

In the method of <FIG>, steps S710 to S790 are the same as the steps S610 to S690 of <FIG>, and the repeated description is omitted.

The method of <FIG> further including steps S722 and S724 is different from the method of <FIG>.

In step S722, the control unit <NUM> determines whether a maximum ratio of the plurality of singular values b<NUM>~bnn is equal to or larger than a preset ratio. The maximum ratio is a ratio of a maximum value b<NUM> to a minimum value bnn among the plurality of singular values b<NUM>~bnn. A value of the step S722 being "No" indicates that there is no principal component vector having sufficiently large descriptive factor than the remaining principal component vectors among the plurality of principal component vectors A<NUM>~An. When the value of the step S722 is "No", the method performs step S724. When the value of the step S722 is "Yes", the method performs the step S730.

In step S724, the control unit <NUM> outputs a fault message. The fault message indicates disabled abnormality detection. The fault message may be transmitted and received between the battery controller <NUM> and the remote controller <NUM> through the interface unit <NUM>. The interface unit <NUM> may output visual and/or audible information corresponding to the fault message.

Although the description made above with reference to <FIG> is made under the assumption that the battery controller <NUM> is provided as the battery diagnosis device, instead of the battery controller <NUM>, the remote controller <NUM> may act as the battery diagnosis device. That is, the description of each of the control unit <NUM> and the memory <NUM> may be in common to the control unit <NUM> and the memory <NUM>. When the remote controller <NUM> is provided as the battery diagnosis device, the battery management system <NUM> may transmit data indicating the plurality of observation voltage vectors X<NUM>~Xn the communication circuit <NUM> of the remote controller <NUM> through the interface unit <NUM>.

The embodiments of the present disclosure described hereinabove are not implemented only through the apparatus and method, and may be implemented through programs that perform functions corresponding to the configurations of the embodiments of the present disclosure or recording media having the programs recorded thereon, and such implementation may be easily achieved by those skilled in the art from the disclosure of the embodiments previously described.

While the present disclosure has been hereinabove described with regard to a limited number of embodiments and drawings, the present disclosure is not limited thereto and it is obvious to those skilled in the art that various modifications and changes may be made thereto within the scope of the appended claims.

Claim 1:
A battery diagnosis device, comprising:
a memory (<NUM>) configured to store an observation matrix (X) including a plurality of observation voltage vectors (X<NUM> .... Xn) indicating a time-series of cell voltage of each of a plurality of battery cells (BC<NUM> .... BCn); and a control unit (<NUM>);
characterised in that the control unit (<NUM>) is configured to determine a plurality of principal component vectors (A<NUM>... An), a plurality of singular values (b<NUM>..... bnn) and a plurality of coefficient vectors (C<NUM>T..... CnT) from the observation matrix (X),
wherein each coefficient vector includes a plurality of coefficients corresponding to the plurality of observation voltage vectors in a one-to-one relationship, and
wherein the control unit is configured to, for each coefficient vector,
determine an invalid coefficient among the plurality of coefficients by comparing the plurality of coefficients included in the corresponding coefficient vector, and
detect abnormality of the battery cell corresponding to the invalid coefficient among the plurality of battery cells based on the principal component vector corresponding to the corresponding coefficient vector among the plurality of principal component vectors, the singular value corresponding to the corresponding coefficient vector among the plurality of singular values and the invalid coefficient.