KR102530223B1 - Method and system for predicting remaining useful life(rul) of battery - Google Patents

Abstract

Embodiments are disclosed that provide a method and system for predicting the remaining useful life of a battery. The method includes measuring operating current during charge cycles and discharge cycles of a battery. The method includes calculating capacity degradation for a plurality of cycles of the battery based on a plurality of degradation parameters and the measured operating current. Deterioration parameters include operating temperature, minimum SOC, maximum SOC, and physical properties. The method includes predicting the RUL of the battery using the calculated capacity degradation.

Description

Method and system for predicting remaining useful life of battery

The embodiments below relate to methods and systems for predicting the remaining useful life of a battery.

Generally, they are widely used as rechargeable energy storage devices because of the relatively high energy, power density, and relatively low cost of batteries when compared to other storage applications. Because of inherent chemical reactions within the battery, the energy storage capacity of the battery decreases with use. The rate of loss of capacity depends on the temperature and the number of cycles in the battery.

Conventional methods of predicting the RUL of a battery typically involve data-based methods using regression based techniques. However, conventional methods require a lot of data and a large onboard computation facility. And, lots of data and large onboard computing facilities are time consuming.

Embodiments provide a mechanism to predict the remaining useful life (RUL) of a battery based on operating current and degradation parameters.

According to one aspect, a method of estimating remaining useful life includes measuring an operating current during a charge cycle and a discharge cycle of a battery; calculating capacity fade for a plurality of cycles of the battery based on a plurality of degradation parameters and the measured operating current; and estimating a remaining useful life of the battery using the calculated capacity drop.

The plurality of degradation parameters may include an operating temperature, a minimum state of charge, a maximum state of charge, and material properties.

The method may further include displaying the predicted remaining useful life to indicate a lifetime remaining until the battery reaches an end-of-life (EOL) state. there is.

According to one aspect, a system for predicting remaining useful life measures an operating current during a charge cycle and a discharge cycle of a battery, and based on a plurality of degradation parameters and the measured operating current, the battery's operating current. and a prediction unit for calculating a capacity fade over a plurality of cycles and predicting a remaining useful life of the battery using the calculated capacity fade.

The plurality of degradation parameters may include an operating temperature, a minimum state of charge, a maximum state of charge, and material properties.

The prediction unit may display the predicted remaining useful life to indicate a remaining life time until the battery reaches an end-of-life state.

1 shows a high level overview of a system for predicting the RUL of a battery, according to one embodiment.
2 is a flow diagram illustrating a method of predicting a RUL of a battery, according to one embodiment.
3 is a graph showing validation of relative capacity based on number of cycles at various reference temperatures of a conventional model under constant operating current, according to one embodiment.
4A illustrates capacity loss with cycling at different temperatures, according to one embodiment.
4B is an example of a user interface displaying a RUL to a user, according to one embodiment.
5 illustrates a computing environment implementing a method for predicting a RUL of a battery, according to one embodiment.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings.

Various changes may be made to the embodiments described below. The embodiments described below are not intended to be limiting on the embodiments, and should be understood to include all modifications, equivalents or substitutes thereto.

Terms used in the examples are used only to describe specific examples, and are not intended to limit the examples. Singular expressions include plural expressions unless the context clearly dictates otherwise. In this specification, terms such as "include" or "have" are intended to designate that there is a feature, number, step, operation, component, part, or combination thereof described in the specification, but one or more other features It should be understood that the presence or addition of numbers, steps, operations, components, parts, or combinations thereof is not precluded.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the art to which the embodiment belongs. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related art, and unless explicitly defined in this specification, they should not be interpreted in an ideal or excessively formal meaning. don't

In addition, in the description with reference to the accompanying drawings, the same reference numerals are given to the same components regardless of reference numerals, and overlapping descriptions thereof will be omitted. In describing the embodiment, if it is determined that a detailed description of a related known technology may unnecessarily obscure the gist of the embodiment, the detailed description will be omitted.

Embodiments achieve a method and system for predicting the remaining useful life of a battery. The method includes measuring operating current during charge cycles and discharge cycles of a battery. The operating current 'I' is measured during the battery's discharge cycle and charge cycle. The method includes calculating capacity degradation for a plurality of cycles of the battery based on the plurality of degradation parameters and the measured operating current 'I'.

In one embodiment, the plurality of degradation parameters include operating temperature, minimum state of charge (minimum SOC), maximum state of charge (maximum SOC), and material properties. Deterioration parameters such as minimum SOC and maximum SOC are constant values that depend on the design of the battery.

In one embodiment, capacity fade is calculated by numerically integrating the capacity fade rate.

The method also includes predicting the RUL of the battery using the calculated capacity degradation. The predicted RUL of the battery is displayed to the user as a user interface. The predicted RUL indicates the lifetime remaining until the battery reaches the EOL state. Based on the displayed RUL, the user can take necessary precautions. In addition, the RUL for the modified cycle of the battery may be displayed to the user.

Unlike conventional methods, the proposed method predicts the RUL of a battery using a physics-based method. The proposed method can be used to predict the RUL under any operating condition. The proposed method can be implemented without any additional devices or circuits. The proposed method can identify a cell or module with the lowest capacity in a battery to selectively replace a cell or module with the lowest capacity and performance.

As an example, the proposed method can be used to predict the RUL for a new drive cycle, which is a function of driving patterns and traffic conditions.

The proposed method requires less computational time than existing data-based models that predict RUL.

The proposed method can be used with data-based models.

As an example, the proposed method can be applied to most of the electric vehicle operating range and all electronic devices operating range.

1 shows a high level overview of a system for predicting the RUL of a battery, according to one embodiment. System 100 includes a battery 102, a predictor 104, a control device, and a load or generator. Battery 102 may provide electrical energy to power a load. In one embodiment, the load may be, for example, an electronic device, a laptop, or an electric vehicle. However, the load is not limited to the above example.

Battery 102 typically includes one or more electrochemical cells that store chemical energy. Chemical energy is converted into electrical energy to power a load.

In some cases, the load may be replaced by a generator used to charge battery 102.

In one embodiment, battery 102 may be a single battery or a plurality of cells, such as cell A, cell B, cell C, and cell D shown in FIG. 1 .

Battery 102 may be a rechargeable battery formed of a chemical composition that is capable of being recharged. Battery 102 may be a lithium ion battery. In one example, battery 102 may include a Lithium Nickel Cobalt Aluminum (Li NCA) positive electrode.

A control device controls the load or generator or controls the predictor 104 . The control device may include a plurality of sensors that determine the operating temperature, operating current, and degradation parameters of the battery 102 .

The prediction unit 104 may be configured to predict the remaining useful life (RUL) of the battery 102 by calculating capacity fade for a plurality of cycles of the battery 102 based on a plurality of degradation parameters. there is.

In one embodiment, degradation parameters include operating temperature, minimum SOC, maximum SOC, and physical properties.

In one embodiment, the predicted RUL of the battery 102 is displayed to the user to indicate the remaining lifetime until the battery reaches the EOL state. Based on the displayed RUL, the user can take necessary precautions. Also, the RUL for the modified cycle may be displayed to the user. Optionally, a cell with the lowest capacity and performance can be identified to replace the cell. In one example, cell B is identified as having the lowest capacity or poor performance and the user can replace cell B.

2 is a flow diagram illustrating a method of predicting a RUL of a battery, according to one embodiment. The method 200 and the descriptions below provide a basis for a control program and can be implemented using a microcontroller, microprocessor, or computer readable storage medium.

At step 202 , method 200 includes measuring an operating current during a charge cycle and a discharge cycle of battery 102 . Method 200 allows predictor 104 to measure operating current during charge and discharge cycles of battery 102 . An operating current 'I' is measured during a charge cycle and a discharge cycle of battery 102 .

At step 204 , method 200 includes calculating a capacity degradation for a plurality of cycles of battery 102 based on the plurality of degradation parameters and the measured operating current. Method 200 allows predictor 104 to calculate capacity degradation for a plurality of cycles based on a plurality of degradation parameters and a measured operating current 'I'.

The capacity in any cycle can be calculated using Equation 1.

[Equation 1]

이다.The capacity in n ^th cycle is

am.

이다.The relative capacity in n ^th cycle is

am.

이다.At the positive electrode, the state of charge SOC _pos is

am.

이다.The molar concentration of lithium in the anode is

am.

Parameters A and B(T) of Equation 1 are experimentally determined as cell parameters.

는 물성(material property)이다. 또한, 파라미터

및

는 배터리(102)의 설계(design)에 기초하는 상수(constant)이다.

is a material property. Also, the parameter

and

is a constant based on the design of battery 102.

Capacity fade is calculated by integrating the capacity fade rate with time.

Equation 1 can be integrated numerically using a sequential method (eg, trapezoidal rule) over multiple cycles to calculate the capacity fade.

[Equation 2]

In Equation 2, 'n' represents RUL and is the number of cycles of the battery before the battery reaches EOL. In other words, 'n' represents the number of cycles the battery has left until reaching EOL.

Equation 1 can be numerically integrated in the form of Equation 3 below.

[Equation 3]

및

이다. 수학식 1에

및

를 적용하는 경우, 수학식 1은 수학식 3으로 표현될 수 있다.

and

am. in Equation 1

and

When applying, Equation 1 can be expressed as Equation 3.

From Equation 2, Equation 4 below can be derived.

[Equation 4]

및

를 적용하는 경우, 수학식 2는 수학식 4로 표현될 수 있다.in Equation 2

and

When applying Equation 2, Equation 2 can be expressed as Equation 4.

In Equation 4, 'n' represents the number of cycles of the battery before the battery reaches EOL.

At step 206, the method 200 includes predicting the RUL of the battery using the calculated capacity degradation. Method 200 allows predictor 104 to use capacity degradation to measure the RUL of a battery.

At step 208, the method 200 includes indicating the predicted RUL of the battery. Method 200 allows predictor 104 to indicate the predicted RUL. In one embodiment, the RUL is displayed to the user as a UI (User Interface). The predicted RUL indicates the lifetime remaining until the battery reaches the EOL state. Based on the displayed RUL, the user can take necessary precautions. For example, RUL may be indicated as 3000 cycles, which indicates to the user that the battery's lifetime is 3000 cycles remaining for the battery to reach the EOL state. Also, the RUL for the modified cycle may be displayed to the user.

In addition, the various actions, units, steps, blocks, or acts described in the method 200 may be ordered presented, in a different order, It can be performed simultaneously (simultaneously), or a combination thereof. Also, in some embodiments, some of the actions, units, steps, blocks, or operations listed in FIG. 2 may be omitted.

3 is a graph showing validation of relative capacity based on number of cycles at various reference temperatures of a conventional model under a constant operating current, according to one embodiment. For a constant operating current 'I', a closed form solution of Equation 2 can be obtained as shown in Equation 5 below. The closed-form solution is used to justify the experimental results obtained at different operating temperatures extracted from the open literature journal "The Electrochemical Society", 156 (7), A527-A535, (2009). It can be.

[Equation 5]

In Equation 5, n is RUL, which represents the number of cycles, and K ₁ represents a constant.

In the graph, the existing model temperature values are obtained from the Journal of Electrochemical Society, 156 (7), A527-A535, (2009).

과 동일하다. Relative capacity can be predicted in a given number of cycles of battery 102 . Relative capacities can be predicted at n. As an example, if an application requires a cut-off capacity of 0.9 at a temperature of 298.15K, the cut-off capacity is predicted at about 3000 cycles, as shown in the graph of FIG. 3 . where the cut-off capacity is the relative capacity

is the same as

Comparison of experimental results at various temperatures (in FIG. 3 ) shows that the relative capacity of battery 102 can be predicted with an average accuracy of 99%.

4A illustrates capacity loss with cycling at different temperatures, according to one embodiment. As shown in FIG. 4A, the capacity of battery 102 decreases with increasing number of cycles and operating current temperature.

4B is an example of a user interface displaying a RUL to a user, according to one embodiment. As shown in FIG. 4B , RUL at various operating temperatures may be displayed to a user through a UI. Users can take necessary precautions based on the displayed RUL. The RUL for the modified cycle of the battery may be displayed to the user.

5 illustrates a computing environment implementing a method for predicting RUL of a battery according to one embodiment. The computing environment 502 includes at least one processing unit 508 equipped with a control unit 504 and an arithmetic logic unit (ALU) 506, memory 510, storage ( 512), a plurality of networking devices 516, and a plurality of input output (I/O) devices 514. The processing unit 508 is responsible for executing the instructions of the algorithm. The processing unit 508 receives commands from the control unit 504 to perform processing. Also, the logical and arithmetic operations involved in the execution of instructions are computed with the aid of the ALU 506.

The overall computing environment 502 includes multiple homogeneous and/or heterogeneous cores, multiple CPUs of different kinds, special media mdeia), and other accelerators. The processing unit 508 is responsible for processing the instructions of the algorithm. Also, the plurality of processing units 508 may be located on a single chip or may be located across multiple chips.

Algorithms including instructions and codes required for implementation may be stored in the memory unit 510 , the storage 512 , or both. At the time of execution, instructions may be fetched from corresponding memory 510 and/or storage 512 and executed by processing unit 508 .

In the case of a hardware implementation, various networking devices 516 or external I/O devices 514 may be coupled to the computing environment 502 to support the implementation via networking units and I/O device units.

Embodiments may be implemented through at least one software that runs on at least one hardware device and performs network management functions for controlling elements. The elements shown in FIGS. 1 and 5 include blocks, which can be hardware devices or combinations of hardware devices and software units.

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

As described above, although the embodiments have been described with limited drawings, those skilled in the art can apply various technical modifications and variations based on the above. For example, the described techniques may be performed in an order different from the method described, and/or components of the described system, structure, device, circuit, etc. may be combined or combined in a different form than the method described, or other components may be used. Or even if it is replaced or substituted by equivalents, appropriate results can be achieved.

Therefore, other implementations, other embodiments, and equivalents of the claims are within the scope of the following claims.

Claims (7)

A method for predicting remaining useful life performed by a system for predicting remaining useful life, comprising:
measuring an operating current during a charge cycle and a discharge cycle of the battery;
Calculating a capacity fade of the battery based on the measured operating current, maximum state of charge, minimum state of charge, state of charge limit corresponding to physical properties of the battery, and capacity in a previous cycle of the battery. ; and
predicting a remaining useful life of the battery using the calculated capacity degradation;
including,
How to predict remaining useful life.
delete According to claim 1,
displaying the predicted remaining useful life to indicate remaining life time until the battery reaches an end-of-life state;
Including more,
How to predict remaining useful life.
The operating current is measured during the charging cycle and the discharging cycle of the battery, and the measured operating current, the maximum state of charge, the minimum state of charge, the state of charge limits corresponding to the physical properties of the battery, and the previous cycle of the battery A prediction unit that calculates the capacity fade of the battery based on the capacity of and predicts the remaining useful life of the battery using the calculated capacity fade.
including,
A system for predicting remaining useful life.
delete According to claim 4,
The prediction unit,
indicating the predicted remaining useful life to indicate the remaining life time until the battery reaches an end-of-life state;
A system for predicting remaining useful life.
A computer program containing computer-executable program codes recorded on a computer-readable recording medium
measuring an operating current during a charge cycle and a discharge cycle of the battery;
Calculating a capacity fade of the battery based on the measured operating current, maximum state of charge, minimum state of charge, state of charge limit corresponding to physical properties of the battery, and capacity in a previous cycle of the battery. ; and
Executing the step of predicting a remaining useful life of the battery using the calculated capacity degradation,
A computer program containing computer-executable program codes recorded on a computer-readable recording medium.

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