Battery monitoring device, battery monitoring method, battery pack, and electric vehicle

Abstract

A battery monitoring apparatus according to the present application is for a battery assembly provided with a case and a plurality of battery cells accommodated in the case. The battery monitoring apparatus includes a first sensor for detecting an internal temperature of the case, a second sensor for detecting an internal pressure of the case, a third sensor for detecting an internal gas of the case, a power supply circuit for generating an operating voltage by using direct current of the battery assembly, and a controller for switching the first sensor, the second sensor, and the third sensor from a stopped state to an operating state by using the operating voltage. The controller monitors an internal abnormality of the battery assembly based on detection values collected from the respective sensors in the operating state.

Description

Technical Field

[0001] This disclosure relates to techniques for monitoring internal anomalies in battery packs having multiple battery cells, and more specifically, to battery monitoring devices and methods for monitoring internal anomalies in battery packs having multiple battery cells, battery packs including the battery monitoring devices, and electric vehicles including the battery packs.

[0002] This application claims priority to Korean Patent Application No. 10-2020-0135553, filed with the Korean Intellectual Property Office on October 19, 2020, the disclosure of which is incorporated herein by reference in its entirety. Background Technology

[0003] Recently, the demand for portable electronic products such as laptops, cameras, and mobile phones has increased rapidly, and with the widespread development of electric vehicles, energy storage devices, robots, and satellites, much research is being conducted on high-performance batteries that can be recharged repeatedly.

[0004] Currently, commercially available batteries include nickel-cadmium batteries, nickel-metal hydride batteries, nickel-zinc batteries, and lithium batteries. Among them, lithium batteries have almost no memory effect, and therefore, they are receiving more and more attention than nickel-based batteries due to their advantages of being easy to charge at any time, having a low self-discharge rate, and high energy density.

[0005] Generally, a battery pack includes at least one battery assembly with multiple battery cells and a housing that houses the battery cells. A battery cell is manufactured by housing the electrode stack and electrolyte within the housing and sealing the housing. The housing isolates the electrode assembly and electrolyte from the external environment to ensure the safe use of the battery cell.

[0006] When the battery cell casing cracks, harmful substances (such as electrolytes) may leak out. The causes of casing cracking can be categorized as external and internal. Since external causes (such as strong external impacts) are difficult to predict, internal causes need to be considered for the safe operation of the battery pack.

[0007] Internal causes leading to casing rupture can occur in the following sequence: As the battery cell temperature rises, gas is generated more rapidly within the cell, increasing internal pressure and causing the casing to gradually expand. When the expansion exceeds its limit, the casing eventually ruptures, and the gas trapped inside escapes. Summary of the Invention

[0008] Technical issues

[0009] This disclosure is designed to address the aforementioned problems, and therefore aims to provide an apparatus and method for monitoring internal anomalies of a battery assembly using sensors that independently detect parameters (i.e., temperature, pressure, gas) associated with a housing rupture of a battery cell included in the battery assembly, a battery pack including the apparatus, and an electric vehicle including the battery pack.

[0010] These and other objects and advantages of this disclosure will be understood from the following description and will become apparent from embodiments of this disclosure. Furthermore, it will be readily understood that the objects and advantages of this disclosure can be achieved by the means set forth in the appended claims and combinations thereof.

[0011] Technical solution

[0012] A battery monitoring device according to one aspect of this disclosure is used in a battery assembly having a housing and a plurality of battery cells housed within the housing. The battery monitoring device includes: a first sensor configured to detect the internal temperature of the housing; a second sensor configured to detect the internal pressure of the housing; a third sensor configured to detect the internal gas of the housing; a power supply circuit configured to generate an operating voltage using direct current from the battery assembly; and a controller configured to, upon receiving a monitoring start command while the first, second, and third sensors are controlled to be in an idle state, change the first, second, and third sensors from an idle state to an awake state using the operating voltage. The controller is configured to monitor internal anomalies of the battery assembly based on detection values ​​collected from each of the first, second, and third sensors in the awake state.

[0013] When a monitoring start command is received, the controller can be configured to collect detection values ​​from a first sensor at a first sampling rate, collect detection values ​​from a second sensor at a second sampling rate, and collect detection values ​​from a third sensor at a third sampling rate.

[0014] When a first abnormal condition is detected (in the first abnormal condition, the detection value collected from the first sensor is equal to or greater than a first threshold, the detection value collected from the second sensor is less than a second threshold, and the detection value collected from the third sensor is less than a third threshold), the controller can be configured to collect detection values ​​from the first sensor at a fourth sampling rate equal to or less than a first sampling rate, collect detection values ​​from the second sensor at a fifth sampling rate greater than a second sampling rate, and collect detection values ​​from the third sensor at a sixth sampling rate equal to or greater than a third sampling rate.

[0015] When a second abnormal condition is detected (in the second abnormal condition, the detection value collected from the second sensor is equal to or greater than the second threshold, and the detection value collected from the third sensor is less than the third threshold), the controller can be configured to: collect detection values ​​from the first sensor at a seventh sampling rate equal to or less than the fourth sampling rate, collect detection values ​​from the second sensor at an eighth sampling rate equal to or less than the fifth sampling rate, and collect detection values ​​from the third sensor at a ninth sampling rate greater than the sixth sampling rate.

[0016] The controller can be configured to perform a predetermined safety function when a third anomaly is detected, in which the detection value collected from a third sensor is equal to or higher than a third threshold.

[0017] The controller can be configured to collect detection values ​​from each of the first, second, and third sensors that are in a wake-up state at a first sampling rate when a monitoring start command is received.

[0018] The controller can be configured to determine a first anomaly indicator by applying a first correlation function to detection values ​​collected from each of the first, second, and third sensors. The controller can also be configured to, when a first anomaly is detected, collect detection values ​​from each of the first, second, and third sensors at a second sampling rate greater than a first sampling rate, wherein the first anomaly indicator is equal to or greater than a first threshold indicator in the first anomaly.

[0019] The controller can be configured to determine a second anomaly index by applying a second correlation function to detection values ​​collected from each of the first, second, and third sensors. The controller can also be configured to collect detection values ​​from each of the first, second, and third sensors at a third sampling rate greater than the second sampling rate when a second anomaly is detected, in which the second anomaly index is equal to or greater than a second threshold index. The weight assigned to the detection values ​​collected from the second sensor by the second correlation function is greater than the weight assigned to the detection values ​​collected from the second sensor by the first correlation function.

[0020] The controller can be configured to determine a third anomaly indicator by applying a third correlation function to detection values ​​collected from each of the first, second, and third sensors. The controller can also be configured to execute predetermined safety functions when a third anomaly is detected, in which the third anomaly indicator is equal to or greater than a third threshold indicator. The weight assigned to the detection values ​​collected from the third sensor by the third correlation function is greater than the weight assigned to the detection values ​​collected from the third sensor by the second correlation function.

[0021] According to another aspect of this disclosure, the battery pack may include battery monitoring equipment.

[0022] According to another aspect of this disclosure, an electric vehicle may include a battery pack.

[0023] According to another aspect of this disclosure, a battery monitoring method can be executed by a battery monitoring device, the battery monitoring device comprising: a first sensor configured to detect the internal temperature of a housing of a battery assembly, the housing containing a plurality of battery cells; a second sensor configured to detect the internal pressure of the housing; a third sensor configured to detect the internal gas of the housing; a power supply circuit configured to generate an operating voltage using direct current from the battery assembly; and a controller. The battery monitoring method includes: when a monitoring start command is received while the first, second, and third sensors are controlled to be in an idle state, the controller uses the operating voltage to change the first, second, and third sensors from an idle state to an awake state; and the controller monitors internal anomalies of the battery assembly based on detection values ​​collected from each of the first, second, and third sensors in the awake state.

[0024] Technical effect

[0025] According to at least one embodiment of this disclosure, internal anomalies of a battery assembly can be monitored using sensors that independently detect parameters (i.e., temperature, pressure, gas) associated with a housing rupture of a battery cell included in the battery assembly.

[0026] According to at least one embodiment of the present disclosure, the sampling rate of at least one sensor can be adjusted according to the severity of the anomaly corresponding to the detection value collected from each sensor, thereby rapidly detecting internal anomalies of the battery assembly and reducing unnecessary power consumption required to monitor internal anomalies of the battery assembly.

[0027] The effects of this disclosure are not limited to those described above, and those skilled in the art will clearly understand these and other effects from the appended claims. Attached Figure Description

[0028] The accompanying drawings illustrate preferred embodiments of the present disclosure and, together with the detailed description of the present disclosure described below, are provided to provide a further understanding of the technical aspects of the present disclosure; therefore, the present disclosure should not be construed as being limited to the drawings.

[0029] Figure 1 The diagram is an exemplary illustration of the configuration of an electric vehicle according to the present disclosure.

[0030] Figure 2 This is an exemplary flowchart illustrating a battery monitoring method according to a first embodiment of the present disclosure.

[0031] Figure 3 This is an exemplary flowchart illustrating a battery monitoring method according to a second embodiment of the present disclosure. Detailed Implementation

[0032] The preferred embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. Before the description, it should be understood that the terms or words used in the specification and appended claims should not be construed as limited to their general and dictionary meanings, but rather as being interpreted based on their meanings and concepts corresponding to the technical aspects of this disclosure, on the basis of allowing the inventors to appropriately define the terms for the best interpretation.

[0033] Therefore, the embodiments described herein and the examples shown in the accompanying drawings are only the most preferred embodiments of this disclosure and are not intended to fully describe the technical aspects of this disclosure. It should be understood that various other equivalents and modifications can be made to them at the time of filing the application.

[0034] Terms including ordinal numbers such as “first” and “second” are used to distinguish one element from another among various elements, rather than to limit elements by the terminology.

[0035] Unless the context clearly indicates otherwise, the term "comprising," as used in this specification, specifies the presence of the mentioned element but does not exclude the presence or addition of one or more other elements. Additionally, the term "unit" refers to at least one processing unit of function or operation, which can be implemented individually or in combination by hardware and software.

[0036] Furthermore, as will be further understood throughout the specification, when an element is referred to as being “connected to” another element, it can be directly connected to the other element or there can be an intermediary element.

[0037] Figure 1 The diagram illustrates, by way of example, the configuration of an electric vehicle 1 according to the present disclosure.

[0038] Reference Figure 1 The electric vehicle 1 includes a battery pack 2, a relay 3, an inverter 4, an electric motor 5, and an advanced controller 6.

[0039] Battery pack 2 includes battery module 10 and battery monitoring device 100.

[0040] Relay 3 is connected in series to battery assembly 10 via a pair of power paths, which connect the positive and negative terminals of battery assembly 10 to the positive and negative terminals of inverter 4, respectively. Relay 3 controls the switching between on and off states in response to a switching signal from battery monitoring device 100. Relay 3 can be a mechanical relay that is switched on / off by the electromagnetic force of a coil, or a semiconductor switch such as a metal-oxide-semiconductor field-effect transistor (MOSFET).

[0041] Inverter 4 is configured to convert direct current (DC) power from battery assembly 10 into alternating current (AC) power in response to commands from advanced controller 6.

[0042] The motor 5 operates using alternating current from the inverter 4. The motor 5 can be, for example, a three-phase AC motor.

[0043] The battery assembly 10 includes a plurality of battery cells 11 and a housing 12. The housing 12 defines the overall shape of the battery assembly 10 and provides internal space therein for accommodating the plurality of battery cells 11. The housing 12 can be bolted and secured to a battery compartment disposed in the electric vehicle 1.

[0044] Multiple battery cells 11 may be connected in series, in parallel, or both. Battery cells 11 may include, for example, lithium-ion battery cells. Battery cells 11 are not limited to a specific type and may include any type of battery cell that can be repeatedly recharged.

[0045] The battery cell 11 includes an electrode stack, an electrolyte, and a casing. The electrode stack includes a positive electrode plate, a negative electrode plate, and a separator disposed between the positive and negative electrode plates. The casing, which houses the electrode stack and the electrolyte, is completely sealed. Therefore, as long as the casing remains intact, the electrode stack, the electrolyte, and gases generated as byproducts of the charging / discharging reaction are isolated from the external environment through the casing.

[0046] The battery monitoring device 100 is configured to monitor internal anomalies of the battery assembly 10 using the detection results of the internal temperature, internal pressure and internal gas of the battery assembly 10.

[0047] The battery monitoring device 100 includes a first sensor 110, a second sensor 120, a third sensor 130, a power supply circuit 140, and a controller 150. The battery monitoring device 100 may also include an interface unit 160.

[0048] The first sensor 110 is located within the interior space of the housing 12 and is configured to generate a first detection signal representing the internal temperature of the battery assembly 10. For example, the first sensor 110 can detect the temperature between any two of the plurality of battery cells 11 as the internal temperature of the battery assembly 10. The first sensor 110 may include known temperature detection devices (such as thermistors and thermocouples).

[0049] The second sensor 120 is located within the interior space of the housing 12 and is configured to generate a second detection signal representing the internal pressure of the battery assembly 10. For example, the second sensor 120 can detect the pressure exerted by the expansion of any two of the plurality of battery cells 11 that are in contact with each other, as the internal pressure of the battery assembly 10. The second sensor 120 may include known pressure detection devices (such as strain gauges).

[0050] The third sensor 130 is located inside the housing 12 and is configured to generate a third detection signal representing the internal gas of the battery assembly 10. The third sensor 130 may include a known gas detection device (such as an air quality sensor).

[0051] The power supply circuit 140 is configured to use DC power supplied from the battery assembly 10 to generate an operating voltage at a predetermined voltage level required for the operation of the controller 150. The power supply circuit 140 may include a voltage regulator and a DC-DC converter.

[0052] The controller 150 may be implemented in hardware using at least one of the following: application-specific integrated circuit (ASIC), digital signal processor (DSP), digital signal processing device (DSPD), programmable logic device (PLD), field-programmable gate array (FPGA), microprocessor, or electrical unit for performing other functions.

[0053] The controller 150 may include memory embedded therein. The memory may include, for example, at least one type of storage medium selected from flash memory, hard disk, solid-state drive (SSD), silicon disk drive (SDD), micro multimedia card, 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). The memory may pre-store programs and data required to execute the battery management method according to the embodiments described below.

[0054] The controller 150 is operatively connected to the advanced controller 6, the first sensor 110, the second sensor 120, the third sensor 130, and the power supply circuit 140. Ooperative connection means a direct / indirect connection to transmit and receive signals in one or both directions.

[0055] The controller 150 is configured to collect detection values ​​from at least one of the first sensor 110, the second sensor 120, and the third sensor 130 during operation using the operating voltage provided by the power supply circuit 140, while simultaneously controlling the first sensor 110, the second sensor 120, and the third sensor 130 in response to commands from the advanced controller 6. Collecting detection values ​​may refer to the operation of converting analog detection signals into digital values ​​and recording them in a memory.

[0056] The controller 150 can use a voltage conversion circuit disposed therein to convert the operating voltage into a power supply voltage different from the operating voltage. The power supply voltage has a predetermined voltage level required to activate the first sensor 110, the second sensor 120, and the third sensor 130. That is, each of the first sensor 110, the second sensor 120, and the third sensor 130 operates in a wake-up state, generating an associated detection signal while being supplied with the power supply voltage. The controller 150 can change each sensor 110, 120, 130 from a wake-up state to an idle state by selectively interrupting the power supply voltage supply to each of the first sensor 110, the second sensor 120, and the third sensor 130. This stops the generation of detection signals associated with each sensor 110, 120, 130 controlled to the idle state. The first sensor 110, the second sensor 120, and the third sensor 130 can also be configured to be activated by the operating voltage, in which case the conversion from the operating voltage to the power supply voltage can be omitted.

[0057] The controller 150 can be operatively connected to each sensor 110, 120, 130 via a monitoring channel. The monitoring channel has a power supply line and a communication line. Power supply voltage from the controller 150 can be provided to each sensor 110, 120, 130 via the power supply line. The controller 150 can receive detection signals from each sensor 110, 120, 130 via the communication line and collect the received detection signals as detection values.

[0058] Interface unit 160 is configured to support wired or wireless communication between controller 150 and advanced controller 6 (e.g., electronic control unit (ECU)) of electric vehicle 1. Wired communication may be, for example, controller domain network (CAN) communication, and wireless communication may be, for example, Zigbee or Bluetooth communication. The communication protocol is not limited to a specific type and may include any communication protocol that supports wired / wireless communication between controller 150 and advanced controller 6. Interface unit 160 may include output devices (e.g., display, speaker) to provide information received from controller 150 and / or advanced controller 6 in a recognizable format.

[0059] Figure 2 This is an exemplary flowchart illustrating a battery monitoring method according to a first embodiment of the present disclosure. Figure 2 The method can be derived from Figure 1 The battery monitoring equipment 100 is executed.

[0060] Reference Figure 1 and Figure 2 In step S200, the controller 150 determines whether a monitoring start command has been received while the first sensor 110, the second sensor 120, and the third sensor 130 are controlled to be in an idle state. The advanced controller 6 can send a monitoring start command to the battery monitoring device 100 in response to user input. When the value of step S200 is "yes", step S210 is executed.

[0061] In step S210, the controller 150 supplies power to the first sensor 110, the second sensor 120, and the third sensor 130, causing them to change from an idle state to a wake-up state. Therefore, each of the first sensor 110, the second sensor 120, and the third sensor 130 generates a detection signal in the wake-up state.

[0062] In step S220, the controller 150 collects the detection values ​​of the first sensor 110, the second sensor 120, and the third sensor 130 at a first sampling rate, a second sampling rate, and a third sampling rate, respectively. The first sampling rate, the second sampling rate, and the third sampling rate can be the same or different, and each has a preset value. For example, the first sampling rate can be 100 times / second, the second sampling rate can be 10 times / second, and the third sampling rate can be 1 time / second.

[0063] In step S230, the controller 150 determines whether a first abnormal condition is detected. In the first abnormal condition, the detection value collected from the first sensor 110 is equal to or greater than a first threshold, the detection value collected from the second sensor 120 is less than a second threshold, and the detection value collected from the third sensor 130 is less than a third threshold. That is, the first abnormal condition is when the internal temperature of the battery assembly 10 rises above the threshold temperature corresponding to the first threshold, while the internal pressure and gas concentration of the battery assembly 10 are at normal levels. When the value of step S230 is "yes", step S240 is executed.

[0064] In step S240, the controller 150 collects the detection values ​​from the first sensor 110, the second sensor 120, and the third sensor 130 at a fourth sampling rate, a fifth sampling rate, and a sixth sampling rate, respectively. That is, the controller 150 sets the acquisition rate of the first detection signal from the first sampling rate to the fourth sampling rate, the acquisition rate of the second detection signal from the second sampling rate to the fifth sampling rate, and the acquisition rate of the third detection signal from the third sampling rate to the sixth sampling rate, respectively. Each of the fourth, fifth, and sixth sampling rates has a preset value. The fourth sampling rate is equal to or less than the first sampling rate. The fifth sampling rate is greater than the second sampling rate. The sixth sampling rate is equal to or greater than the third sampling rate. For example, the fourth sampling rate can be 100 times / second, the fifth sampling rate can be 50 times / second, and the sixth sampling rate can be 60 times / second. Because the fifth sampling rate is greater than the second sampling rate, the increase in internal pressure as the internal temperature rises can be accurately monitored.

[0065] In step S250, the controller 150 determines whether a second abnormal condition is detected, in which the detection value collected from the second sensor 120 is equal to or greater than a second threshold, and the detection value collected from the third sensor 130 is less than a third threshold. Since the first abnormal condition has already been detected, the detection value collected from the first sensor 110 can be omitted in determining whether the second abnormal condition has occurred. That is, the second abnormal condition is a situation in which the internal temperature of the battery assembly 10 rises above the threshold temperature corresponding to the first threshold, the internal pressure of the battery assembly 10 rises above the threshold pressure corresponding to the second threshold, and the gas concentration of the battery assembly 10 is at a normal level. When the value of step S250 is "yes", step S260 is executed.

[0066] In step S260, the controller 150 collects the detection values ​​from the first sensor 110, the second sensor 120, and the third sensor 130 at a seventh sampling rate, an eighth sampling rate, and a ninth sampling rate, respectively. That is, the controller 150 sets the acquisition rate of the first detection signal from the fourth sampling rate to the seventh sampling rate, the acquisition rate of the second detection signal from the fifth sampling rate to the eighth sampling rate, and the acquisition rate of the third detection signal from the sixth sampling rate to the ninth sampling rate. Each of the seventh, eighth, and ninth sampling rates has a preset value. The seventh sampling rate is equal to or less than the fourth sampling rate. The eighth sampling rate is equal to or less than the fifth sampling rate. The ninth sampling rate is greater than the sixth sampling rate. For example, the seventh sampling rate can be 60 times / second, the eighth sampling rate can be 50 times / second, and the ninth sampling rate can be 100 times / second. Because the ninth sampling rate is greater than the sixth sampling rate, gas leakage that occurs when the housing ruptures due to increased internal pressure can be accurately monitored.

[0067] In step S270, the controller 150 determines whether a third abnormal condition is detected, in which the detection value collected from the third sensor 130 is equal to or greater than a third threshold. Since the first and second abnormal conditions have already been detected, the detection values ​​collected from the first sensor 110 and the second sensor 120 are not used to determine whether the second abnormal condition has occurred. That is, the third abnormal condition is a situation in which, after the internal pressure of the battery assembly 10 rises above the threshold pressure corresponding to the second threshold, the gas concentration inside the casing 12 exceeds the normal level due to the rupture of the casing of at least one battery cell 11 included in the battery assembly 10. When the value of step S270 is "yes", step S280 is executed.

[0068] In step S280, controller 150 performs a predetermined safety function. The safety function may include reporting a housing rupture to the advanced controller 6. The safety function may include controlling relay 3 to enter an off state. The safety function may include outputting visual / auditory information to notify a user (e.g., the vehicle driver) of the housing rupture.

[0069] Figure 3 This is an exemplary flowchart illustrating a battery monitoring method according to a second embodiment of the present disclosure. Figure 3 The method can be derived from Figure 1 The battery monitoring equipment 100 is executed.

[0070] Reference Figure 1 and Figure 3 In step S300, while controlling the first sensor 110, the second sensor 120, and the third sensor 130 to be in an idle state, the controller 150 determines whether a monitoring start command has been received. The advanced controller 6 can send a monitoring start command to the battery monitoring device 100 in response to user input. When the value of step S300 is "yes", step S310 is executed.

[0071] In step S310, the controller 150 supplies power to the first sensor 110, the second sensor 120, and the third sensor 130, causing them to change from an idle state to a wake-up state. Therefore, each of the first sensor 110, the second sensor 120, and the third sensor 130 generates a detection signal in the wake-up state.

[0072] In step S320, the controller 150 collects detection values ​​from each of the first sensor 110, the second sensor 120, and the third sensor 130 at a first sampling rate. The first sampling rate has a preset value. For example, the first sampling rate may be 3 times / 1 second.

[0073] In step S322, the controller 150 uses a first correlation function to determine a first anomaly index representing the severity of an internal anomaly of the battery assembly 10 based on the detection values ​​collected from each of the first sensor 110, the second sensor 120, and the third sensor 130. The first correlation function is a function that outputs a combination of results to each of the detection values ​​from the first sensor 110, the second sensor 120, and the third sensor 130, applying a unique weight (conversion coefficient) for each collected detection value. Equation 1 below is an example of the first correlation function.

[0074] <Formula 1>

[0075] DI1=(C1×S1)+(C2×S2)+(C3×S3)

[0076] In Equation 1, DI1 is the first anomaly index, C1 is the first conversion coefficient, C2 is the second conversion coefficient, C3 is the third conversion coefficient, S1 is the latest detection value collected from the first sensor 110, S2 is the latest detection value collected from the second sensor 120, and S3 is the latest detection value collected from the third sensor 130. The first correlation function is not limited to Equation 1 according to the example above, and may include any other formula that outputs the result of combining the detection values ​​of each sensor 110, 120, and 130.

[0077] In step S330, the controller 150 determines whether a first abnormal situation is detected, in which a first abnormality index is equal to or greater than a first threshold index. The first abnormal situation is a situation where the battery assembly 10 is malfunctioning but the probability that the housing of the battery cell 11 may be damaged is equal to or less than a predetermined level. When the value of step S330 is "yes", step S340 is executed.

[0078] In step S340, the controller 150 collects detection values ​​from each of the first sensor 110, the second sensor 120, and the third sensor 130 at a second sampling rate greater than the first sampling rate. That is, the controller 150 increases the acquisition rates of the first, second, and third detection signals from the first sampling rate to the second sampling rate. For example, the second sampling rate could be 30 times per second.

[0079] In step S342, the controller 150 uses a second correlation function to determine a second anomaly index representing the severity of an internal anomaly of the battery assembly 10 based on the detection values ​​collected from each of the first sensor 110, the second sensor 120, and the third sensor 130. The second correlation function is a function that outputs a combination of results to each of the detection values ​​from the first sensor 110, the second sensor 120, and the third sensor 130, applying a unique weight (conversion coefficient) to each collected detection value. Equation 2 below is an example of the second correlation function.

[0080] <Formula 2>

[0081] DI2=(C4×S1)+(C5×S2)+(C6×S3)

[0082] In Equation 2, DI2 is the second anomaly index, C4 is the fourth conversion coefficient, C5 is the fifth conversion coefficient, C6 is the sixth conversion coefficient, S1 is the latest detection value collected from the first sensor 110, S2 is the latest detection value collected from the second sensor 120, and S3 is the latest detection value collected from the third sensor 130. The second correlation function is not limited to Equation 2 according to the example above, and may include any other formula that outputs the result of combining the detection values ​​of each sensor 110, 120, and 130.

[0083] It should be noted that the weight assigned to the detection values ​​collected from the second sensor 120 by the second correlation function can be greater than the weight assigned to the detection values ​​collected from the second sensor 120 by the first correlation function. For example, the fifth conversion coefficient C5 in Equation 2 is greater than the second conversion coefficient C2 in Equation 1.

[0084] In step S350, the controller 150 determines whether a second abnormal situation is detected, in which the detection value collected from the second sensor 120 is equal to or greater than a second threshold index, and the detection value collected from the third sensor 130 is less than a third threshold index. The second abnormal situation is a situation where the possibility of the housing of the battery cell 11 breaking exceeds a predetermined level due to an internal abnormality of the battery assembly 10 that is more serious than the first abnormal situation. When the value of step S350 is "yes", step S360 is executed.

[0085] In step S360, the controller 150 collects detection values ​​from each of the first sensor 110, the second sensor 120, and the third sensor 130 at a third sampling rate greater than the second sampling rate. That is, the controller 150 increases the acquisition rates of the first, second, and third detection signals from the second sampling rate to the third sampling rate. For example, the third sampling rate could be 60 times per second.

[0086] In step S362, the controller 150 uses a third correlation function to determine a third anomaly index representing the severity of an internal anomaly of the battery assembly 10 based on the detection values ​​collected from each of the first sensor 110, the second sensor 120, and the third sensor 130. The third correlation function is a function that outputs a combination of results to each of the detection values ​​from the first sensor 110, the second sensor 120, and the third sensor 130, applying a unique weight (conversion coefficient) for each collected detection value. Equation 3 below is an example of the third correlation function.

[0087] <Formula 3>

[0088] DI3=(C7×S1)+(C8×S2)+(C9×S3)

[0089] In Equation 3, DI3 is the third anomaly index, C7 is the seventh conversion coefficient, C8 is the eighth conversion coefficient, C9 is the ninth conversion coefficient, S1 is the latest detection value collected from the first sensor 110, S2 is the latest detection value collected from the second sensor 120, and S3 is the latest detection value collected from the third sensor 130. The third correlation function is not limited to Equation 3 according to the example above, and may include any other formula that outputs the result of combining the detection values ​​of each sensor 110, 120, and 130.

[0090] It should be noted that the weight assigned to the detection values ​​collected from the third sensor 130 by the third correlation function can be greater than the weight assigned to the detection values ​​collected from the third sensor 130 by the second correlation function. For example, the ninth conversion coefficient C9 of Equation 3 is greater than the sixth conversion coefficient C6 of Equation 2.

[0091] In step S370, controller 150 determines whether a third abnormal condition is detected, in which the detection value collected from third sensor 130 is equal to or greater than a third threshold index. When the value of step S370 is "yes", step S380 is executed.

[0092] In step S380, controller 150 performs a predetermined safety function. The safety function may include reporting a housing rupture to the advanced controller 6. The safety function may include controlling relay 3 to enter an off state. The safety function may include outputting visual / auditory information to notify a user (e.g., the vehicle driver) of the housing rupture.

[0093] The embodiments of this disclosure described above can be implemented not only by devices and methods, but also by programs that perform functions corresponding to the configuration of the embodiments of this disclosure, or by recording media on which programs are recorded. Through the disclosure of the above embodiments, those skilled in the art can easily implement such implementations.

[0094] While this disclosure has been described above with respect to a limited number of embodiments and accompanying drawings, this disclosure is not limited thereto and it will be apparent to those skilled in the art that various modifications and variations can be made thereto in terms of the technical aspects of this disclosure and within the equivalent scope of the appended claims.

[0095] Additionally, because many substitutions, modifications and variations can be made to the above-described disclosure by those skilled in the art without departing from the technical aspects of this disclosure, this disclosure is not limited to the above embodiments and drawings, and some or all embodiments may be selectively combined to allow for various modifications.

Claims

1. A battery monitoring device for a battery assembly, the battery assembly having a housing and a plurality of battery cells housed within the housing, the battery monitoring device comprising: A first sensor, configured to detect the internal temperature of the housing; A second sensor is configured to detect the internal pressure of the housing; A third sensor is configured to detect the internal gas of the housing; A power supply circuit configured to generate an operating voltage using the direct current from the battery assembly; as well as A controller configured to, upon receiving a monitoring start command while the first, second, and third sensors are controlled to be in an idle state, use the operating voltage to change the first, second, and third sensors from the idle state to an awake state. The controller is configured to monitor internal anomalies of the battery assembly based on detection values ​​collected from each of the first, second, and third sensors in the wake-up state. The controller is configured as follows: When the monitoring start command is received The detected values ​​are collected from the first sensor at a first sampling rate. The detected values ​​are collected from the second sensor at a second sampling rate, and The detected values ​​are collected from the third sensor at a third sampling rate. The controller is configured as follows: When the first abnormality is detected The detected values ​​are collected from the first sensor at a fourth sampling rate equal to or less than the first sampling rate. The detected values ​​are collected from the second sensor at a fifth sampling rate greater than the second sampling rate, and The detected values ​​are collected from the third sensor at a sixth sampling rate equal to or greater than the third sampling rate. In the first abnormal situation, the detection value collected from the first sensor is equal to or greater than the first threshold, the detection value collected from the second sensor is less than the second threshold, and the detection value collected from the third sensor is less than the third threshold.

2. The battery monitoring device according to claim 1, wherein, The controller is configured to: When a second anomaly is detected The detected values ​​are collected from the first sensor at a seventh sampling rate equal to or less than the fourth sampling rate. The detected values ​​are collected from the second sensor at an eighth sampling rate equal to or less than the fifth sampling rate, and The detected values ​​are collected from the third sensor at a ninth sampling rate, which is greater than the sixth sampling rate. In the second abnormal situation, the detection value collected from the second sensor is equal to or greater than the second threshold, and the detection value collected from the third sensor is less than the third threshold.

3. The battery monitoring device according to claim 2, wherein, The controller is configured to perform a predetermined safety function when a third anomaly is detected, in which the detection value collected from the third sensor is equal to or higher than the third threshold.

4. The battery monitoring device according to claim 1, wherein, The controller is configured to collect the detection values ​​from each of the first sensor, the second sensor, and the third sensor, which are in the wake-up state, at a first sampling rate when the monitoring start command is received.

5. The battery monitoring device according to claim 4, wherein, The controller is configured to: A first anomaly indicator is determined by applying a first correlation function to the detection values ​​collected from each of the first, second, and third sensors, and When the first abnormal situation is detected, the detection value is collected from each of the first sensor, the second sensor and the third sensor at a second sampling rate greater than the first sampling rate, wherein the first abnormal index is equal to or greater than the first threshold index in the first abnormal situation.

6. The battery monitoring device according to claim 5, wherein, The controller is configured to: A second anomaly indicator is determined by applying a second correlation function to the detection values ​​collected from each of the first, second, and third sensors, and When a second anomaly is detected, the detected value is collected from each of the first, second, and third sensors at a third sampling rate greater than the second sampling rate, wherein the second anomaly index is equal to or greater than the second threshold index in the second anomaly. The weight assigned by the second correlation function to the detection values ​​collected from the second sensor is greater than the weight assigned by the first correlation function to the detection values ​​collected from the second sensor.

7. The battery monitoring device according to claim 6, wherein, The controller is configured to: A third anomaly indicator is determined by applying a third correlation function to the detection values ​​collected from each of the first, second, and third sensors. When a third anomaly is detected, a predetermined security function is executed, wherein the third anomaly indicator is equal to or greater than a third threshold indicator. The weight assigned to the detection value collected from the third sensor by the third correlation function is greater than the weight assigned to the detection value collected from the third sensor by the second correlation function.

8. A battery pack comprising a battery monitoring device according to any one of claims 1 to 7.

9. An electric vehicle comprising a battery pack according to claim 8.

10. A battery monitoring method, the battery monitoring method being executable by a battery monitoring device, the battery monitoring device comprising: A first sensor is configured to detect the internal temperature of the housing of the battery assembly, in which multiple battery cells are housed; A second sensor is configured to detect the internal pressure of the housing; A third sensor is configured to detect the internal gas of the housing; A power supply circuit configured to generate an operating voltage using direct current from the battery assembly; The battery monitoring method includes the following steps: and a controller. When a monitoring start command is received while the first sensor, the second sensor, and the third sensor are all controlled to be in an idle state, the controller uses the operating voltage to change the first sensor, the second sensor, and the third sensor from the idle state to an awake state; and The controller monitors for internal anomalies in the battery assembly based on detection values ​​collected from each of the first, second, and third sensors, which are in the wake-up state. When the monitoring start command is received, the controller: The detected values ​​are collected from the first sensor at a first sampling rate. The detected values ​​are collected from the second sensor at a second sampling rate, and The detected values ​​are collected from the third sensor at a third sampling rate. Specifically, when the first abnormal situation is detected, the controller: The detected values ​​are collected from the first sensor at a fourth sampling rate equal to or less than the first sampling rate. The detected values ​​are collected from the second sensor at a fifth sampling rate greater than the second sampling rate, and The detected values ​​are collected from the third sensor at a sixth sampling rate equal to or greater than the third sampling rate. In the first abnormal situation, the detection value collected from the first sensor is equal to or greater than the first threshold, the detection value collected from the second sensor is less than the second threshold, and the detection value collected from the third sensor is less than the third threshold.

11. The battery monitoring method according to claim 10, wherein, When a second abnormal condition is detected, the controller: The detected values ​​are collected from the first sensor at a seventh sampling rate equal to or less than the fourth sampling rate. The detected values ​​are collected from the second sensor at an eighth sampling rate equal to or less than the fifth sampling rate, and The detected values ​​are collected from the third sensor at a ninth sampling rate, which is greater than the sixth sampling rate. In the second abnormal situation, the detection value collected from the second sensor is equal to or greater than the second threshold, and the detection value collected from the third sensor is less than the third threshold.

12. The battery monitoring method according to claim 11, wherein, When a third abnormal situation is detected, the controller executes a predetermined safety function, in which the detection value collected from the third sensor is equal to or higher than the third threshold.

13. The battery monitoring method according to claim 10, wherein, When the monitoring start command is received, the controller collects the detection values ​​from each of the first sensor, the second sensor, and the third sensor that are in the wake-up state at a first sampling rate.

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