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KR-20260066416-A - DEVICE AND METHOD FOR DETECTING BATTERY ABNORMAL CONDITION USING VOLTAGE DEVIATION CHANGE

KR20260066416AKR 20260066416 AKR20260066416 AKR 20260066416AKR-20260066416-A

Abstract

The present disclosure relates to a battery abnormality detection device and method using a voltage deviation change amount. An device according to one embodiment of the present disclosure includes: a memory storing at least one instruction for detecting a battery abnormality using a voltage deviation change amount; and a processor performing an operation according to the instruction. The processor calculates a voltage change amount of a battery and stores the calculated voltage change amount as a variable, calculates a voltage deviation change amount (DDVD, Differential Deviation Voltage Detection), which is a change in voltage difference occurring between each cell inside a battery module, and detects a battery abnormality using the voltage deviation change amount and the stored variable.

Inventors

  • 황규민
  • 이현준
  • 전웅
  • 고명재

Assignees

  • 에스케이온 주식회사

Dates

Publication Date
20260512
Application Date
20241104

Claims (10)

  1. A memory storing at least one instruction for detecting battery abnormalities using a change in voltage deviation; and It includes a processor that performs an operation according to the above instruction, The above processor is, Calculate the change in voltage of the battery and store the calculated change in voltage as a variable, and Calculating the Differential Deviation Voltage Detection (DDVD), which is a change in voltage difference occurring between each cell inside the battery module, and detecting battery abnormalities using the said differential deviation voltage detection and the said stored variable, Battery abnormality detection device.
  2. In paragraph 1, A battery abnormality detection device comprising: a battery equivalent circuit model voltage change calculation unit that calculates the amount of voltage change of a battery using parameters for the State of Charge (SOC) of the battery when a usage current is applied to the battery equivalent circuit model (ECM).
  3. In paragraph 2, The above processor includes a driving distance reflection unit that, when the accumulated driving distance exceeds a certain value, adjusts the ratio of at least one calculated value among the calculated values of the voltage change amount of the battery equivalent model by considering the difference in degradation degree between cells within the battery module, and sets the adjusted calculated value as a standard for the voltage deviation change amount. Battery abnormality detection device.
  4. In paragraph 2, The parameters for the State of Charge (SOC) above include the voltage change due to the capacitance of the battery equivalent model (Δt/ C1 (I k -I k-1 )) and the characteristics of the RC circuit (1 - Δt/ R1 C1 ), Battery abnormality detection device.
  5. In paragraph 3, The above-mentioned driving distance reflection unit compares the calculated voltage deviation change amount standard with the result value during driving of a normal battery, and adjusts the increase or decrease of the standard according to the current magnitude, Battery abnormality detection device.
  6. A step of calculating the voltage change amount of the battery and storing the calculated voltage change amount as a variable; A step comprising: calculating a differential deviation voltage detection (DDVD) which is a change in voltage difference occurring between each cell inside a battery module, and detecting a battery abnormality using the differential deviation voltage detection and the stored variable; Battery abnormality detection method.
  7. In paragraph 6, The step of detecting an abnormality in the above battery is, A battery abnormality detection method comprising the step of calculating the amount of voltage change of a battery using parameters for the State of Charge (SOC) of the battery when a current is applied to the battery equivalent circuit model (ECM) in a battery equivalent model voltage change amount calculation unit.
  8. In Paragraph 7, The step of calculating the voltage change amount of the above battery is, A battery abnormality detection method comprising: a step of, when the driving distance accumulated in a driving distance reflection section exceeds a certain value, adjusting the ratio of at least one calculated value among the calculated values of the voltage change amount of the battery equivalent model by considering the difference in the degree of degradation between cells in the battery module, and setting the adjusted calculated value as a standard for the voltage deviation change amount.
  9. In Paragraph 7, A battery abnormality detection method wherein the parameters for the State of Charge (SOC) above include a voltage change due to the capacitance of the battery equivalent model (Δt/ C1 (I k -I k-1 ) ) and the characteristics of the RC circuit (1 - Δt/R1 C1 ).
  10. In paragraph 8, The step of setting the above-mentioned adjusted calculated value based on the voltage deviation change amount A battery abnormality detection method that compares a standard for a calculated change in voltage deviation with a result value of a normal battery during driving, and adjusts the increase or decrease of the standard according to the magnitude of the current.

Description

Device and method for detecting battery abnormal conditions using voltage deviation change The present disclosure relates to a battery abnormality detection device and method using a voltage deviation change amount. Battery anomaly detection technology is essential to ensure the safety and performance of batteries used in various industries and electronic devices. A battery is a device that stores and releases energy through internal chemical reactions. Since excessive heat generated during the energy storage and release processes poses a risk of ignition or explosion, battery anomaly detection technology enables the prevention of accidents by detecting these risks in advance. While lithium-ion batteries are efficient due to their high energy density, they can pose significant safety issues if overcharging, over-discharging, or short circuits occur. Anomaly detection technology allows for the early detection of these problems, thereby protecting users and the surrounding environment. Furthermore, battery anomaly detection technology analyzes the battery's condition to detect signs of failure early and enables preventive maintenance when necessary. This prevents abnormal battery usage, thereby extending its lifespan. Meanwhile, conventional battery anomaly detection methods primarily rely on setting voltage fluctuations to a fixed threshold. These methods determine that a battery is faulty if the voltage change exceeds a certain level. However, because it is difficult to set an appropriate threshold for all situations, accurate diagnosis and detection of battery anomalies are challenging. Specifically, while voltage fluctuations can vary significantly depending on factors such as battery condition, usage environment, and temperature, the fixed thresholds set in conventional methods fail to adequately account for these diverse factors, thereby hindering accurate diagnosis and anomaly detection. Furthermore, generally, if a large fluctuation in current occurs in the battery, even normal cells may exceed a fixed value. For example, during rapid charging or high-output discharge, normal batteries may exhibit large voltage fluctuations; however, in such cases, relying on a fixed threshold makes it highly likely that the battery will be misdiagnosed as defective even if there are no abnormalities. Furthermore, conventional battery anomaly detection methods have a problem in that they cannot accurately diagnose the battery condition because they cannot distinguish between voltage changes that naturally occur as the battery ages and voltage changes that occur when an actual anomaly happens. Aging batteries can exhibit different voltage change patterns. However, it is difficult to distinguish voltage and current changes caused by battery aging using only fixed thresholds. FIG. 1 is a drawing for explaining a battery abnormality detection device using a voltage deviation change amount according to one embodiment of the present disclosure. FIG. 2 is a block diagram of a battery abnormality detection device using a voltage deviation change amount according to one embodiment of the present disclosure. FIG. 3 is a diagram showing the configuration of a processor according to one embodiment of the present disclosure. FIG. 4 is a graph showing the test results of analyzing the voltage deviation of a battery using the voltage deviation change amount criteria (DDVD Criteria) according to one embodiment of the present disclosure. FIG. 5 is a graph showing the voltage deviation change standard and the deviation change of the monitored ECM (Equivalent Circuit Model) according to one embodiment of the present disclosure. FIG. 6 is a diagram illustrating a battery abnormality detection method using a voltage deviation change amount according to one embodiment of the present disclosure. Hereinafter, the present disclosure will be described in detail with reference to the attached drawings. However, this is merely illustrative and the present disclosure is not limited to the specific embodiments described illustratively. Although terms such as "first," "second," etc. are used to describe various elements, components, and/or sections, it goes without saying that these elements, components, and/or sections are not limited by these terms. These terms are used merely to distinguish one element, component, or section from another. Accordingly, the first element, first component, or first section mentioned below may, within the technical scope of the present disclosure, be a second element, second component, or second section. The terms used herein are for describing the embodiments and are not intended to limit the disclosure. In this specification, the singular form includes the plural form unless specifically stated otherwise in the text. As used herein, "comprises" and/or "made of" do not exclude the presence or addition of one or more other components, steps, actions, and/or elements to the mentioned components, steps, actions, and/o