Vehicle and control method thereof

Abstract

The present invention relates to a vehicle and a control method thereof, wherein the vehicle includes: a battery module, which includes a plurality of battery cells; a battery pack, which includes a plurality of battery modules; a battery cell sensor, which is configured to measure the voltage of the plurality of battery cells; a battery module sensor, which is configured to measure the voltage of the battery module and the current of the battery module; and a controller, which is configured to perform data processing based on data obtained by the battery cell sensor and the battery module sensor.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of Korean Patent Application No. 10-2019-0153346 filed on November 26, 2019, in the Korean Intellectual Property Office, the entire contents of which are incorporated herein by reference. Technical Field

[0003] The present invention relates to a vehicle and a control method thereof, and in particular to a vehicle for managing the charge of a vehicle battery pack and a control method thereof. Background Art

[0004] The electrical energy used to power electric vehicles is supplied by a battery system. Depending on the driving environment, the battery system may utilize batteries with different characteristics. In such cases, overcharging or overdischarging due to voltage imbalances between battery cells or modules can cause problems in the energy storage system (ESS).

[0005] Therefore, in order to estimate the status of a battery module or battery pack, the battery system needs to identify and control the status of battery cells as secondary components through various sensors.

[0006] However, a vehicle is equipped with a large number of battery cells. To determine the status of each battery cell, a number of sensors corresponding to the number of battery cells are required. Consequently, determining the status of each battery cell is difficult, as a high-specification communication device is required to process the information obtained by these multiple sensors. Summary of the Invention

[0007] Accordingly, an aspect of the present invention is to provide a vehicle and a control method thereof for configuring a battery system of the vehicle using a smaller number of sensors and operating a stable battery system.

[0008] According to one aspect of the present invention, a vehicle includes: a battery module including a plurality of battery cells; a battery pack including a plurality of battery modules; a battery cell sensor configured to measure voltages of the plurality of battery cells; a battery module sensor configured to measure the voltage of the battery module and the current of the battery module; and a controller. The controller is configured to perform data processing based on data obtained by the battery cell sensor and the battery module sensor. The controller is configured to: obtain a first charge of the battery cell and a correction value of the battery cell based on the voltage of the battery cell and the current of the battery module; obtain a first error covariance of the battery cell and a Kalman gain of the battery cell based on the first charge of the battery cell and the correction value of the battery cell; obtain a second error covariance of the battery cell by fusing the first error covariance and the Kalman gain; obtain the charge of the battery module and the charge of the battery pack based on the voltage of the battery module, the current of the battery module, the second error covariance, and the Kalman gain; obtain a second charge of the battery cell corrected from the first charge based on the charge of the battery module and the charge of the battery pack; and output the second charge of the battery cell.

[0009] The controller may be configured to obtain a first charge level of the battery cell and a correction value of the battery cell based on a value obtained by dividing a current of the battery module by the number of battery modules connected in parallel.

[0010] The controller may be configured to obtain a first error covariance and a Kalman gain based on an extended Kalman filter.

[0011] The correction value of the battery cell may include: an estimated voltage of the battery cell, a model error of the battery cell, and a system variable of the battery cell.

[0012] The controller may be configured to determine the initial value according to a pre-stored charge / discharge curve.

[0013] The controller may be configured to output the power of the battery pack when the second power level of the battery unit is greater than 20% and less than 80% of the maximum power level of the battery pack.

[0014] The controller may be configured to output the maximum power of the battery cell when the second power of the battery cell is greater than 80% of the maximum power of the battery cell.

[0015] The controller may be configured to output the minimum power of the battery cell when the second power of the battery cell is less than 20% of the maximum power of the battery cell.

[0016] According to another aspect of the present invention, a vehicle control method includes: measuring the voltage of a battery cell, the voltage of a battery module, and the current of the battery module; obtaining a first charge of the battery cell and a correction value of the battery cell based on the voltage of the battery cell and the current of the battery module; obtaining a first error covariance of the battery cell and a Kalman gain of the battery cell based on the first charge of the battery cell and the correction value of the battery cell; obtaining a second error covariance of the battery cell by fusing the first error covariance and the Kalman gain; obtaining the charge of the battery module and the charge of the battery pack based on the voltage of the battery module, the current of the battery module, the second error covariance, and the Kalman gain; obtaining a second charge of the battery cell corrected from the first charge based on the charge of the battery module and the charge of the battery pack; and outputting the second charge of the battery cell.

[0017] Obtaining the first charge of the battery cell and the correction value of the battery cell may include obtaining the first charge of the battery cell and the correction value of the battery cell based on a value obtained by dividing the current of the battery module by the number of battery modules connected in parallel.

[0018] Obtaining the first error covariance of the battery cell and the Kalman gain of the battery cell may include: obtaining the first error covariance and the Kalman gain based on an extended Kalman filter.

[0019] The correction value of the battery cell may include: an estimated voltage of the battery cell, a model error of the battery cell, and a system variable of the battery cell.

[0020] Obtaining the first charge level of the battery cell and the correction value of the battery cell based on the voltage of the battery cell and the current of the battery module may include determining an initial value based on a pre-stored charge / discharge curve.

[0021] Outputting the second power level of the battery cell may include outputting the power level of the battery pack when the second power level of the battery cell is greater than or equal to 20% and less than or equal to 80% of the maximum power level of the battery pack.

[0022] Outputting the second charge of the battery cell may include: when the second charge of the battery cell is greater than 80% of the maximum charge of the battery cell, outputting the maximum charge of the battery cell.

[0023] Outputting the second charge of the battery cell may include outputting a minimum charge of the battery cell when the second charge of the battery cell is less than 20% of a maximum charge of the battery cell. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Some aspects and / or other aspects of the present invention will become clearer and more easily understood through the following description of embodiments in conjunction with the accompanying drawings, in which:

[0025] Figure 1is a block diagram of a battery system for a vehicle according to an embodiment of the present invention.

[0026] Figure 2 FIG. 4 is a control block diagram of a battery system for a vehicle according to an embodiment of the present invention.

[0027] Figure 3 is a flowchart illustrating a method of controlling a vehicle according to an embodiment of the present invention.

[0028] Figure 4 Shown are charge / discharge curves according to an embodiment of the present invention.

[0029] Figure 5 and Figure 6 The change in the voltage of the battery cell and the change in the charge of the battery cell are shown.

[0030] Figure 7 A diagram showing the relationship between the power output of a battery cell. DETAILED DESCRIPTION

[0031] Throughout the specification, the same reference numerals denote the same elements. Not all elements of the embodiments of the present invention are described. The description of elements that are well known in the art or that overlap with each other in the embodiments is omitted. Terms used throughout the specification, such as " part"," module"," member"," Blocks” etc. can be implemented in software and / or hardware, and multiple “ part"," module"," Component" or A block can be implemented as a single component, or a single part"," module"," member"," A "block" can include multiple elements.

[0032] It should be further understood that the term "connect" or its derivatives refers to both direct and indirect connections. Indirect connections include connections through wireless communication networks.

[0033] It should be further understood that when the terms "comprises," "includes," and / or "comprising" are used in this specification, they identify the presence of the stated features, values, steps, operations, elements, and / or components. Such terms do not exclude the presence or addition of one or more other features, values, steps, operations, elements, components, and / or groups thereof, unless the context clearly indicates otherwise.

[0034] In the specification, it should be understood that when an element is referred to as being 'on / under' another element, it can mean being directly on / under the other element, or one or more intermediate elements may also be present.

[0035] Terms including ordinal numbers such as "first" and "second" may be used to explain various components, but these components are not limited by the terms. These terms are only used to distinguish one component from another.

[0036] As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0037] Hereinafter, the embodiments and operating principles of the present invention will be described with reference to the accompanying drawings.

[0038] Figure 1 is a block diagram of a battery system for a vehicle according to an embodiment of the present invention. Figure 2 FIG. 4 is a control block diagram of a battery system for a vehicle according to an embodiment of the present invention.

[0039] The battery pack 10 may be configured by connecting a plurality of battery cells C in series to supply various output voltages to the vehicle. Alternatively, the battery pack 10 may be configured by connecting a plurality of battery cells C in parallel according to the charge / discharge capacity required for the battery pack 10 .

[0040] Battery cell C represents the basic unit of a battery capable of charging and discharging electrical energy. For example, battery cell C may include a positive electrode, a negative electrode, a separator, an electrolyte, and an aluminum casing. In this example, battery cell C may include various secondary batteries, such as lithium-ion batteries, lithium polymer batteries, nickel-cadmium batteries, nickel-metal hydride batteries, and nickel-zinc batteries.

[0041] When a plurality of battery cells C are connected in series and / or in parallel, the battery pack 10 may first configure battery modules 10 - 1 to 10 -N including at least one battery cell C. The battery pack 10 may include at least one battery module 10 - 1 to 10 -N and various sensors.

[0042] The battery pack 10 may be connected to the battery cell sensor 100 and the battery module sensor 200 , or may be implemented as a single body including both the battery cell sensor 100 and the battery module sensor 200 .

[0043] The battery cell sensor 100 may include a plurality of voltage sensors and measure the voltage of each battery cell C. In another example, the battery cell sensor 100 may include a plurality of voltage sensors and a plurality of current sensors. The battery cell sensor 100 may measure the voltage and current of each battery cell C.

[0044] The battery module sensor 200 may include a plurality of voltage sensors and a plurality of current sensors and may measure the voltage and current of the battery modules 10 - 1 to 10 -N.

[0045] The battery cell sensor 100 and the battery module sensor 200 can be connected to the controller 300 and provide the obtained data to the controller 300 so that the controller 300 performs data processing. The battery cell sensor 100 measures the voltage of the battery cell. The battery module sensor 200 measures the voltage of the battery module. The battery cell sensor 100 and the battery module sensor 200 can provide the controller 300 with the battery cell voltage, the battery module voltage, and the battery module current.

[0046] The controller 300 may include at least one non-volatile computer-readable medium or memory 302, in which a program including computer-executable instructions for performing the above-mentioned operations and the operations described below may be stored. The controller 300 may include at least one processor 301 for executing the stored program. When the controller 300 includes multiple memories 302 and multiple processors 301, the multiple memories 302 and the multiple processors 301 may be integrated on a single chip or may be physically separate.

[0047] The physical configuration of the controller 300 has been described above. In the following, the components are classified based on the operational aspects and computational aspects of the controller 300. The data flow and data processing performed by each component will be described in detail below. In one example, see Figure 2 , the controller 300 may include: a battery cell modeling unit 310, a battery cell state observer 320, a data fusion unit 330, a parameter observer 340, a battery pack state observer 350 and a battery pack modeling unit 360. However, Figure 2 The elements shown in FIG are schematically divided to facilitate understanding of data flow and data processing. There is no restriction on the operation objects.

[0048] The battery cell modeling unit 310 receives the voltage of the battery cell from the battery cell sensor 100. The battery pack modeling unit 360 receives the voltage of the battery module and the current of the battery module from the battery module sensor 200. The battery cell modeling unit 310 calculates the charge (i.e., state of charge SOC), estimated voltage, model error, and system variables of each battery cell based on the voltage of the battery cell, the voltage of the battery module, and the current of the battery module. Specifically, the battery cell modeling unit 310 calculates the ideal current value of the battery cell based on the value obtained by dividing the current of the battery module measured by the battery module sensor 200 by the number of parallel connected battery cells included in the battery module. The battery cell modeling unit 310 can calculate the charge and correction value (the estimated voltage of the battery cell, the model error of the battery cell, and the system variable of the battery cell) of each battery cell based on the calculated ideal current value of the battery cell.

[0049] The battery cell modeling unit 310 may calculate the charge amount of the battery cell as a state variable to be estimated based on Equation 1 below.

[0050] <Equation 1>

[0051]

[0052] In Equation 1, N represents the number of battery cells in the battery pack, and P represents the number of parallel battery packs. k,n Indicates the charge of the battery cells in the battery pack, u k and θ k Represent the current and capacity of the battery pack respectively.

[0053] The first equation of Equation 1 is a state equation designed based on the current integration method. The second equation of Equation 1 corresponds to a measurement equation based on the terminal voltage of the battery pack. Generally, the current integration method requires a current value. However, since the battery cell sensor 100 only measures voltage, the current value can be calculated using the ideal current value of the battery cell, which is calculated based on the value obtained by dividing the battery module current measured by the battery module sensor 200 by the number of battery cells connected in parallel.

[0054] The battery modeling unit 360 may calculate the charge of the battery and the capacity of the battery as state variables to be estimated based on Equation 2 below.

[0055] <Equation 2>

[0056]

[0057]

[0058] In Equation 2, x kIndicates the battery charge. and Represents the measurement equation.

[0059] On the other hand, as shown in Equation 2, since the battery pack modeling unit 360 has two state variables to measure, each of the state equation and the measurement equation can be divided into two parts. Therefore, the battery pack modeling unit 360 can update information about the battery module charge, battery module capacity, and terminal voltage based on the battery module voltage and battery module current.

[0060] The noise information applied in the extended Kalman filter can be used to predict the state of the battery system. In this case, as shown in the following equation 3, the noise information can be defined as a constant value based on the above state equation and measurement equation.

[0061] <Equation 3>

[0062]

[0063]

[0064] In Equation 3, w x 、v x 、w θ and v θ is the independent variable, R x , Q x 、R θ and Q θ is the covariance matrix of Gaussian noise.

[0065] The battery cell state observer 320 calculates a first error covariance for each charge level of each battery cell and a Kalman gain for the battery cell based on an extended Kalman filter (EKF). The battery cell state observer 320 can correct the charge level of the battery cell initially calculated based on the calculated first error covariance and Kalman gain.

[0066] On the other hand, as shown in the following equation 4, the extended Kalman filter involved in this embodiment can use the above-mentioned state equation and measurement equation as state variables of the system and use partial derivatives to linearize the nonlinear system.

[0067] <Equation 4>

[0068]

[0069]

[0070]

[0071]

[0072]

[0073] In Equation 4, A K and C K Jacobians representing the state equation, H K Jacobians representing the measurement equation.

[0074] On the other hand, in order to calculate the error covariance involved in this embodiment, it is necessary to set an initial value. In this case, the error covariance can be calculated by the following equation 5. The error covariance can include the error covariance of the power and the error covariance of the capacity.

[0075] <Equation 5>

[0076]

[0077] In Equation 5, P o，N represents the initial error covariance of the battery cells in the battery pack, P o，pack Represents the initial error covariance of the battery pack. SOC table，N and OCV table，N Indicates from Figure 4 The SOC and OCV data are obtained from the .

[0078] As shown in Equation 6 below, the error covariance may have various values ​​depending on the initial value, and the initial value may be set to a constant. However, depending on the initial charge state or the error covariance of the battery cell / module / battery pack, the accuracy may be reduced. Therefore, the calculation of the error covariance according to the present embodiment may be performed based on the initial value based on the pre-stored charge / discharge curve. Figure 4 , a graph showing the relationship between open circuit voltage (OCV) and SOC. The charge / discharge curve corresponds to stored data reflecting the characteristics of the battery extracted in advance through an electrical characteristic experiment.

[0079] <Equation 6>

[0080]

[0081] In Equation 6, x o，N Indicates the initial charge of the battery cell in the battery pack, x o，pack Indicates the initial charge of the battery pack, θ o，pack Indicates the initial capacity of the battery pack.

[0082] Data fusion unit 330 receives the first error covariances and Kalman gains of the battery cells from battery state observer 320. Data fusion unit 330 generates new data combining the first error covariances and Kalman gains, and generates new data combining the first error covariances and Kalman gains. In this case, the Kalman gains can be provided to battery pack modeling unit 360 to estimate and correct the battery module's charge level, and the second error covariances can be provided to battery cell modeling unit 310 to correct the error covariances of the battery cells.

[0083] After determining the initial value of the error covariance, the data fusion unit 330 calculates a second error covariance based on the first error covariance and the Kalman gain. The second error covariance of the battery pack capacity and the battery pack capacity can be updated based on the following equation 7 and the battery pack state equation described above. Furthermore, the capacity of the battery module can be determined based on the capacity of the battery pack.

[0084] <Equation 7>

[0085]

[0086] In Equation 7, θ K，pack Indicates the capacity of the battery pack, S K Represents the error covariance of the capacity. “-” means the predicted value, and “+” means the calibrated value.

[0087] The battery pack modeling unit 360 calculates an estimated voltage of the battery pack 10 and a charge level of the battery pack 10 based on the model information and a second error covariance of the battery modules generated based on the voltage and current of the battery modules. The battery pack modeling unit 360 provides the estimated voltage of the battery pack 10 and the charge level of the battery pack 10 to the battery pack state observer 350. However, the battery pack state observer 350 does not apply the aforementioned extended Kalman filter. The battery pack state observer 350 can correct the charge level of the battery pack 10 based on the error information of the battery pack 10, the Kalman gain generated by the cell state observer 320, and the charge level of the battery pack 10 calculated by the battery pack modeling unit 360.

[0088] Specifically, as shown in Equation 8 below, the battery pack state observer 350 may correct and update the charge levels of the battery cells and the battery pack based on the capacity of the battery pack.

[0089] <Equation 8>

[0090]

[0091] In Equation 8, x k，N Indicates the charge of the battery cells in the battery pack, x k，pack Indicates the battery pack's charge, θ k，pack Indicates the capacity of the battery pack.

[0092] The battery cell state observer 320 inputs the value obtained by dividing the battery module current and battery module capacity by the number of battery cells connected in parallel in the battery module into the battery cell state equation, and can calculate the charge of each battery cell. In this case, the second error covariance of the battery pack can be used as the error covariance of the charge of the battery cell. The error covariance of the charge of the battery cell can be calculated by applying the noise parameter and system variables of each battery cell. The second error covariance, noise parameter, and system variables can be used to obtain the Kalman gain. This is shown in Equation 9 below.

[0093] <Equation 9>

[0094]

[0095] In Equation 9, Represents the Kalman gain of the battery cells in the battery pack.

[0096] In addition, a voltage error with respect to the voltage of the battery cell measured by the battery cell sensor 100 may be obtained based on the following Equation 10. The current battery cell capacity is corrected based on the obtained voltage error.

[0097] <Equation 10>

[0098]

[0099] In Equation 10, Error N Represents the model error of the battery cells in the battery pack.

[0100] The battery pack's charge can be corrected based on the Kalman gain of each cell. The error covariance of the battery pack can be calculated based on the Kalman gain of the cell and the system variables. This is shown in Equations 11 and 12 below.

[0101] <Equation 11>

[0102]

[0103] <Equation 12>

[0104]

[0105] In Equation 11, Indicates the calibrated charge level of the battery pack. represents the predicted capacity of the battery pack, and N represents the number of battery cells in the battery pack.

[0106] In Equation 12, is the error and variance of the battery pack's charge, and / is an elementary matrix.

[0107] In the case of the battery cell capacity, the Kalman gain may be calculated based on the following equation 13. The capacity of the battery cell is updated based on equation 14. The second error covariance may be calculated based on the updated value as shown in the following equation 15, where the second error covariance is the new error covariance.

[0108] <Equation 13>

[0109]

[0110] <Equation 14>

[0111]

[0112] <Equation 15>

[0113]

[0114] In Equation 13, The Kalman gain representing the capacity of the battery pack.

[0115] In Equation 14, Indicates the calibrated capacity of the battery pack. Indicates the predicted capacity of the battery pack.

[0116] In Equation 15, represents the calibration error covariance of the capacity. Represents the forecast error covariance of capacity.

[0117] The parameter observer 340 calculates the capacity of the battery module 10 using an extended Kalman filter based on the charge level of the battery module 10. The parameters used in this case may be the battery pack error information, battery pack system variables, and battery pack charge level output from the battery pack modeling unit 360. In this example, the capacity of the battery module itself can be estimated. The parameter observer 340 can calculate the ideal capacity of the battery cell by dividing the capacity of the battery module by the number of parallel connections. The calculated ideal capacity of the battery cell can be input into the battery cell modeling unit 310.

[0118] The data flow and data processing of each component included in the controller 300 have been described above. Figure 3 A control method according to this sequence is described in detail.

[0119] Figure 31 is a flow chart showing a method for controlling a vehicle according to an embodiment of the present invention. However, this is only a preferred embodiment for achieving the purpose of the present invention, and some components may be added or deleted as needed.

[0120] When the battery cell voltage, the battery module voltage, and the battery module current are measured (step 301 ), the controller 300 performs calculation based on the battery cell voltage, the battery module voltage, and the battery module current.

[0121] The controller 300 determines initial parameters and sets initial values ​​of state variables to calculate the charge (ie, state of charge SOC), estimated voltage, model error, and system variables of each battery cell (step 302 ). The controller 300 calculates parameters of the battery cell model (step 303 ).

[0122] The controller 300 calculates the charge, Kalman gain, and error covariance of the battery cell (step 304). The results calculated in step 304 can be applied to the process of outputting the charge of the battery pack and the maximum / minimum charge of the battery cell.

[0123] The controller 300 fuses the Kalman gain data and the error covariance data (step 305). Specifically, the controller 300 may receive the first error covariance of the battery cell and the Kalman gain of the battery cell. The controller 300 may calculate a second error covariance, which is new data obtained by fusing the first error covariance with the Kalman gain.

[0124] The controller 300 calculates the parameters of the battery module model (step 306). The controller 300 calculates the charge of the battery pack and the capacity of the battery pack (step 307). In this case, the charge of the battery pack and the capacity of the battery pack can be calculated based on the second error covariance.

[0125] The controller 300 updates the error covariance of the battery module and the capacity of the battery cell (step 308 ). The controller 300 calculates a new error covariance, a new battery cell charge, and a new battery cell capacity by applying the updated error covariance and battery cell capacity to step 304 .

[0126] When the charge of the battery cell is greater than 20% and less than 80% (which is a safe interval) (step 309), the controller 300 outputs the charge of the battery pack (step 310). When the charge of the battery cell exceeds 80% (which is an overcharge interval), the battery cell outputs the maximum charge (step 311), wherein the maximum charge is the charge of the battery cell with the highest charge among the multiple battery cells. When the charge of the battery cell is less than 20% (which is an overdischarge interval), the battery cell may output the minimum charge (step 312), wherein the minimum charge is the charge of the battery cell with the lowest charge among the multiple battery cells. The battery cell may output the maximum or minimum charge to output the total charge by utilizing information about the charge of multiple battery cells pre-estimated based on the interval of the total charge of the battery module to enable stable operation of the battery.

[0127] On the other hand, the present invention does not utilize the current information in the battery cells, but only the voltage information. Therefore, it can save the sensors used in the battery system. However, the present invention can accurately estimate the internal state of multiple battery cells.

[0128] Figure 5 and Figure 6 The change in the voltage of the battery cell and the change in the charge of the battery cell are shown.

[0129] like Figure 5 and Figure 6 As shown in Figure 1, as the battery cell ages, the voltage change in the low-power range becomes sharper. Therefore, in order to monitor the stable range of the battery based on the voltage of the battery cell, the sampling period of the control board should be shorter.

[0130] Furthermore, accurate voltage information needs to be monitored based on the voltage. During power conversion, variations between battery cells may occur, which is not simply voltage deviation information. Furthermore, when noise caused by external factors is applied to the voltage sensor, inaccurate voltage information may be measured, resulting in poor stability or inaccurate control.

[0131] The present invention can use the extended Kalman filter to diagnose the status of each battery cell through data, and can indirectly diagnose faults of the battery cells included in the battery pack through the power level of the battery cell / battery module / battery pack. In other words, the present invention can perform indirect fault diagnosis based on the change in power level.

[0132] Figure 7 A diagram showing the relationship between the power output of a battery cell.

[0133] refer to Figure 7, as a result of estimating the power of the battery module, the power of the battery pack through state fusion is utilized within the safe range (20% < SOC < 80%). Based on the power of the fused battery pack, by utilizing the maximum value of the power of the battery cells in the range of 80% or above, and the minimum power value of the battery cells in the range of 20% or below, the battery operating system can operate safely.

[0134] Even when a smaller number of sensors are applied to the battery system, the vehicle according to the embodiments of the present invention can determine the exact state of the battery cells.

[0135] The disclosed embodiments can be implemented in the form of a non-volatile recording medium storing instructions executed by a computer. These instructions can be stored in the form of program code. When these instructions are executed by a processor, they can generate program modules to perform the operations in the disclosed embodiments. The recording medium can be implemented as a computer-readable recording medium.

[0136] Computer-readable recording media include various recording media in which instructions that can be decoded by a computer are stored, such as read-only memory (ROM), random access memory (RAM), magnetic tapes, magnetic disks, flash memories, optical data storage devices, etc.

[0137] Although the embodiments of the present invention have been described for illustrative purposes, those skilled in the art should understand that various modifications, additions, and deletions are possible without departing from the scope and spirit of the present invention. Therefore, the embodiments of the present invention are not described for restrictive purposes.

[0138] Even when a smaller number of sensors are applied to the battery system, the vehicle according to the embodiments of the present invention can determine the exact state of the battery cells.

Claims

1. A vehicle comprising: a battery module comprising a plurality of battery cells; a battery pack comprising a plurality of battery modules; a battery cell sensor configured to measure voltages of a plurality of battery cells; a battery module sensor configured to measure a voltage of the battery module and a current of the battery module; as well as a controller configured to perform data processing based on data obtained by the battery cell sensors and the battery module sensors; The controller is configured to: obtain a first power level of the battery cell and a correction value of the battery cell based on the voltage of the battery cell and the current of the battery module; Based on the first power of the battery cell and the correction value of the battery cell, a first error covariance of the battery cell and a Kalman gain of the battery cell are obtained; by fusing the first error covariance and the Kalman gain, a second error covariance of the battery cell is obtained; based on the voltage of the battery module, the current of the battery module, the second error covariance and the Kalman gain, the power of the battery module and the power of the battery pack are obtained; based on the power of the battery module and the power of the battery pack, a second power of the battery cell corrected from the first power is obtained; and the second power of the battery cell is output.

2. The vehicle according to claim 1, wherein The controller is configured to obtain a first charge of the battery cell and a correction value of the battery cell based on a value obtained by dividing a current of the battery module by the number of parallel-connected battery cells included in the battery module.

3. The vehicle according to claim 1, wherein The controller is configured to obtain a first error covariance and a Kalman gain based on an extended Kalman filter.

4. The vehicle according to claim 1, wherein The correction value of the battery cell includes: an estimated voltage of the battery cell, a model error of the battery cell, and a system variable of the battery cell.

5. The vehicle according to claim 1, wherein The controller is configured to determine an initial value based on a pre-stored charge / discharge curve.

6. The vehicle according to claim 1, wherein The controller is configured to output the power of the battery pack when the second power of the battery unit is greater than 20% and less than 80% of the maximum power of the battery pack.

7. The vehicle according to claim 1, wherein The controller is configured to output the maximum power of the battery cell when the second power of the battery cell is greater than 80% of the maximum power of the battery cell.

8. The vehicle according to claim 1, wherein The controller is configured to output the minimum power of the battery cell when the second power of the battery cell is less than 20% of the maximum power of the battery cell.

9. A vehicle control method, the control method comprising: Measuring the voltage of the battery cell, the voltage of the battery module, and the current of the battery module; Obtaining a first power level of the battery cell and a correction value of the battery cell based on the voltage of the battery cell and the current of the battery module; Obtaining a first error covariance of the battery cell and a Kalman gain of the battery cell based on the first power level of the battery cell and the correction value of the battery cell; Obtaining a second error covariance of the battery cell by fusing the first error covariance and the Kalman gain; Obtaining the power of the battery module and the power of the battery pack based on the voltage of the battery module, the current of the battery module, the second error covariance, and the Kalman gain; obtaining a second charge of the battery cell corrected from the first charge based on the charge of the battery module and the charge of the battery pack; Outputting a second charge of the battery cell.

10. The control method according to claim 9, wherein: Obtaining a first power level of the battery cell and a correction value of the battery cell includes: A first capacity of the battery cell and a correction value of the battery cell are obtained based on a value obtained by dividing the current of the battery module by the parallel number of battery cells included in the battery module.

11. The control method according to claim 9, wherein: Obtaining the first error covariance of the battery cell and the Kalman gain of the battery cell includes: A first error covariance and a Kalman gain are obtained based on an extended Kalman filter.

12. The control method according to claim 9, wherein: The correction value of the battery cell includes: an estimated voltage of the battery cell, a model error of the battery cell, and a system variable of the battery cell.

13. The control method according to claim 9, wherein: Obtaining a first power of the battery cell and a correction value of the battery cell based on the voltage of the battery cell and the current of the battery module includes: The initial value is determined based on a pre-stored charge / discharge curve.

14. The control method according to claim 9, wherein: Outputting the second power of the battery unit includes: When the second power level of the battery unit is greater than or equal to 20% and less than or equal to 80% of the maximum power level of the battery pack, the power level of the battery pack is output.

15. The control method according to claim 9, wherein: Outputting the second power of the battery unit includes: When the second power of the battery cell is greater than 80% of the maximum power of the battery cell, the maximum power of the battery cell is output.

16. The control method according to claim 9, wherein: Outputting the second power of the battery unit includes: When the second power level of the battery cell is less than 20% of the maximum power level of the battery cell, the minimum power level of the battery cell is output.

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