Electronic circuit for determining the state of charge of a battery cell

Abstract

The invention relates to an electronic circuit (100) for determining a state of charge (114) of a battery cell of a battery system, in particular of an electrically driven vehicle, wherein the electronic circuit (100) is designed to: obtain a plurality of measured values (101) of an open-circuit voltage of the battery cell and associated time values (102) at which the measured values (101) of the open-circuit voltage are detected; determine a balancing voltage (112) of the battery cell with reference to a predetermined mathematical function (111) of the time values (102) associated with the measured values (101) of the open-circuit voltage on the basis of a linear regression (110) of the plurality of measured values (101) of the open-circuit voltage; determine the state of charge (114) of the battery cell on the basis of a predetermined characteristic curve (113) which indicates a relationship between the balancing voltage (112) and the state of charge (114) of the battery cell.

Description

Technical Field

[0001] This invention relates to an electronic circuit and a corresponding method for determining the state of charge of individual battery cells in a battery system, for example, for electric vehicles. In particular, this invention relates to online prediction of aging-related relaxation of individual battery cells, such as lithium-ion single-cell batteries, using a computationally and memory-efficient linear regression method. Background Technology

[0002] Battery management systems (BMS) can be found in the interconnection of various battery cells, such as traction batteries in electric vehicles, uninterruptible power supplies, mobile phones, or laptops. One of the main challenges is determining the state of charge (SOC), which, for many battery types, can only be determined imprecisely based on battery voltage and internal resistance. The determination and display of battery status or remaining operating time is often unreliable.

[0003] The BMS or BMU (Battery Management Unit) periodically wakes up and uses the CMC (Charge Module Controller) to determine the battery's open-circuit voltage. Depending on the state of charge and temperature, the open-circuit voltage becomes a quasi-equilibrium voltage after a certain time (relaxation time). The equilibrium voltage allows for reliable determination of the battery's state of charge (OCV recalibration). However, the relaxation time increases significantly as the state of charge and temperature decrease. Therefore, after a short period, such as half an hour, or during a short period of parking, the open-circuit voltage still deviates significantly from the equilibrium voltage because the individual battery cells have not yet reached equilibrium.

[0004] Determining the State of Charge (SOC) using the open-circuit voltage can only be done with a certain degree of inaccuracy. Furthermore, the relaxation degree, and consequently the accuracy of the SOC determination, changes as the battery ages. Summary of the Invention

[0005] One object of the present invention is to provide a method for improving the determination of the state of charge of individual battery cells in a battery system, for example, for electric vehicles.

[0006] In particular, the object of the present invention is to provide a state of charge determination method, wherein, taking aging into account, a simple and computationally efficient method is used to determine the SOC with higher accuracy after a short period of time.

[0007] This objective is achieved by having the features of the independent claims. Advantageous embodiments are the subject matter of the dependent claims, the specification, and the drawings.

[0008] This invention is based on the following concept: the time curve of the open-circuit voltage to the equilibrium voltage of a single cell in a battery is approximated (fitted) using a new mathematical function. The parameters of this function can be accurately determined online after several data points. This also takes into account the single-cell tolerance, measurement error, and aging effect that affect the parameter values. Due to the function type, the parameters can be determined using a computationally efficient regression method.

[0009] With the help of this invention, SOC can be determined with higher accuracy after a short period of time, taking into account aging, using a simple and computationally efficient method.

[0010] To predict the equilibrium voltage shortly after a certain time, especially at low temperatures and under charging conditions, only three parameters are needed for the first time, instead of four, which minimizes storage overhead. Furthermore, to determine the parameters online, only a linear rather than a nonlinear regression method is required, allowing for further optimization of computation time. Moreover, the results of the new method show significantly higher accuracy than previous methods across certain SOC and temperature ranges.

[0011] Therefore, the solution proposed here is superior to previously used methods, which, to technically solve the problem, employ a mathematical function consisting of two nested exponential functions and use a constant part as the fitting function. However, determining the online parameters required computationally and memory-intensive nonlinear methods due to the function type in the previously used methods, which can be omitted using the new method presented here. While the previously used methods could only accurately predict the equilibrium value after a time interval on the order of the relaxation time, the new method proposed here can already predict the equilibrium value well before reaching the relaxation time. In the previous methods, aging effects were typically considered by measuring the prescribed aged cells, while in the new method presented here, aging is taken into account in the solution.

[0012] The solution described herein is applicable to customer-specific and targeted solutions for identifying battery status in electric vehicles, but it is also applicable to other battery-powered systems such as laptops, mobile communication devices, and uninterruptible power supplies. With this solution according to the invention, the battery can operate more gently and safely throughout its entire lifespan.

[0013] According to a first aspect of the invention, this objective is achieved by an electronic circuit for determining the state of charge of a battery cell in a battery system, particularly for electric vehicles, wherein the electronic circuit is designed to: obtain multiple measurements of the open-circuit voltage of the battery cell and associated time values, at which the measured values ​​of the open-circuit voltage are detected; determine the equilibrium voltage of the battery cell based on a linear regression of the multiple measurements of the open-circuit voltage, with reference to a predetermined mathematical function of the time values, which are associated with the measured values ​​of the open-circuit voltage; and determine the state of charge of the battery cell based on a predetermined characteristic curve indicating the relationship between the equilibrium voltage and the state of charge of the battery cell.

[0014] This electronic circuit ensures improved determination of the state of charge (SOC) of individual battery cells in battery systems, such as those in electric vehicles. Within this circuit, the SOC can be determined with greater accuracy using a simple, computationally efficient method, taking into account aging, even after a short period of time.

[0015] According to one embodiment of the electronic circuit, a predetermined mathematical function defines the time curve of the no-load voltage of a single battery cell.

[0016] By defining the time curve of the open-circuit voltage using mathematical functions, electronic circuits can efficiently determine an estimate of the open-circuit voltage based on linear regression of measured values. This estimate accurately predicts the time curve of the open-circuit voltage. Consequently, the electronic circuits can very accurately infer the state of charge of individual battery cells.

[0017] This achieves the following technical advantages: the mathematical function accurately represents the time curve of the no-load voltage of a single battery cell, enabling rapid regression and approximation.

[0018] According to an exemplary implementation of the electronic circuit, the predetermined mathematical function is a linear function.

[0019] If the mathematical function is linear, the electronic circuit can quickly and resource-efficiently determine the estimated value of the no-load voltage, meaning the calculation time is short and complex calculation steps are not required.

[0020] According to an exemplary implementation of the electronic circuit, the predetermined mathematical function is a linear function that depends on: a first parameter, or a first parameter and a second parameter, or a first parameter, a second parameter, and a third parameter.

[0021] This achieves the following technical advantages: fewer parameters are required compared to previous methods that required four parameters. Therefore, the computational complexity of three or fewer parameters is lower than that of previous methods.

[0022] According to an exemplary implementation of the electronic circuit, a predetermined mathematical function defines the time curve of the cell's open-circuit voltage in relation to the relaxation time of the cell.

[0023] This achieves the following technical advantages: the estimated value of the no-load voltage can be indicated based on the relaxation time of the battery cell, which is a characteristic time constant of the battery cell.

[0024] According to an exemplary implementation of the electronic circuit, the predetermined mathematical function is determined as follows:

[0025] U OCV (θ)=f(a,b,c)=a+b×θ+c×log(θ), where, U OCV (θ) represents the time curve of the no-load voltage of a single battery cell, which depends on the variable θ, which represents the time related to the relaxation time of the single battery cell, and wherein a predetermined mathematical function depends on the first parameter a, the second parameter b, and the third parameter c.

[0026] This achieves the following technical advantages: such a mathematical function can very accurately approximate the exponential curve of the no-load voltage of a single battery cell. (See below...) Figures 3 to 5 Tests, for example, show that there is a very small deviation compared to the actual curve of the open-circuit voltage.

[0027] According to an exemplary implementation of the electronic circuit, the electronic circuit is designed to determine at least one of three parameters based on statistical analysis of measured values ​​of the open-circuit voltage and associated time values, at which the measured values ​​of the open-circuit voltage are detected.

[0028] This achieves the following technical advantages: statistical evaluation can be determined using common statistical functions such as mean, variance, and correlation, which are standard functions that can be determined effectively and quickly.

[0029] According to an exemplary implementation of the electronic circuit, the electronic circuit is designed to perform statistical evaluation based on the determination of the following function:

[0030]

[0031]

[0032] Among them, y i The measured value of the no-load voltage, x i This represents the relevant time values ​​at which the open-circuit voltage was measured. The variable n represents the number of measurements.

[0033] This achieves the following technical advantages: these functions can be easily determined from current measurements and time values. The accuracy of the prediction increases with the number of measurements, n. As the number of measurements, n, increases, the prediction becomes increasingly accurate.

[0034] According to an exemplary implementation of the electronic circuit, the electronic circuit is designed to provide a first estimate of the balance voltage of the battery cell by determining a first parameter before the relaxation time of the battery cell is reached.

[0035] This achieves the following technical advantages: when determining the first estimate solely by evaluating the first parameter 'a', a very good approximation of the no-load voltage already exists, as demonstrated by tests, for example, see [link to relevant documentation]. Figure 6 And the following related descriptions.

[0036] According to an exemplary implementation of the electronic circuit, the electronic circuit is designed to provide a second estimate of the balance voltage of the battery cell by determining a second parameter before the relaxation time of the battery cell is reached, wherein the second estimate is determined as the sum of the first parameter and the second parameter.

[0037] This achieves the following technical advantages: when determining the second estimate by evaluating the first parameter a and the second parameter b, a very accurate approximation of the no-load voltage is produced. Furthermore, this approximation saves resources and can be quickly determined using electronic circuitry.

[0038] According to an exemplary embodiment of the electronic circuit, the electronic circuit is designed to store the time curve of at least a first parameter in a memory, and is also designed to determine the balance voltage of the battery cell based on the stored time curve of at least the first parameter when further determining the state of charge of the battery cell.

[0039] This achieves the following technical advantages: the electronic circuitry can perform online predictions based on early estimates of the time curve, resulting in more accurate and faster estimations. Therefore, as more past state-of-charge determinations are considered, the time required to accurately predict the state of charge is reduced. As the number of measurements increases (n>>0), increasingly accurate results are obtained. In this context, the term "fast" means the same accuracy, but at an earlier point in time.

[0040] According to an exemplary implementation of the electronic circuit, the time curve extends from the start of determining the state of charge to the relaxation time of the individual battery cells.

[0041] This achieves the following technical advantages: the parameter a is stored for each cycle from the start of measurement to the relaxation time of the battery cell, and can be taken into account when determining the state of charge in the future.

[0042] According to an exemplary embodiment of the electronic circuit, the electronic circuit is designed to store multiple time curves of at least a first parameter in a memory for determining the state of charge of a battery cell sequentially over time, and is also designed to determine the aging of a battery cell based on the multiple time curves of the state of charge of the battery cell.

[0043] This achieves the following technical advantages: aging is also considered in the online prediction of the relaxation of individual battery cells, and aging can even be clearly determined from the recorded time curves.

[0044] According to a second aspect of the invention, this objective is achieved by a battery management system comprising: at least one charging module controller for detecting multiple measurements of the open-circuit voltage on at least one battery cell of a battery system, particularly for electric vehicles, and detecting multiple associated time values ​​at which the open-circuit voltage measurements are detected; and electronic circuitry according to the first aspect for determining the state of charge of at least one battery cell of the battery system.

[0045] Similar to the electronic circuitry in the first aspect, this also offers the advantage of improved determination of the state of charge (SOC) of individual battery cells in, for example, battery systems for electric vehicles. In such a battery management system, considering aging, a simple, computationally efficient method allows for the determination of SOC with greater accuracy after a short period.

[0046] According to a third aspect of the invention, this objective is achieved by a method for determining the state of charge (SOC) of a battery cell in a battery system, particularly for electric vehicles, wherein the method comprises the following steps: acquiring multiple measurements of the open-circuit voltage of the battery cell and associated time values, at which the measured SOC values ​​are detected; determining the equilibrium voltage of the battery cell based on a linear regression of the multiple measured SOC values ​​and a predetermined mathematical function relating the time values ​​to the measured SOC values; and determining the SOC of the battery cell based on a predetermined characteristic curve indicating the relationship between the equilibrium voltage and the SOC of the battery cell.

[0047] Similar to the electronic circuitry according to the first aspect, the method according to the third aspect also offers the advantage of improved determination of the state of charge (SOC) of individual battery cells in, for example, electric vehicles. In this method, considering aging, a simple and computationally efficient approach allows for the determination of SOC with higher accuracy within a short period.

[0048] According to a fourth aspect of the invention, this objective is achieved by a computer program having program code for executing the method according to the third aspect on an electronic circuit according to the first aspect or a battery management system according to the second aspect.

[0049] This achieves the following technical advantages: computer programs can be easily executed on the vehicle controller, meeting real-time requirements without parts costs or the need for additional external hardware components. Attached Figure Description

[0050] The invention will now be described in more detail with reference to embodiments and accompanying drawings. In these drawings:

[0051] Figure 1 A schematic diagram of an electronic circuit 100 for determining the state of charge of a battery cell according to the present disclosure is shown.

[0052] Figure 2 This is a view of an exemplary time curve 200 representing the open-circuit voltage of a single battery cell;

[0053] Figure 3 This is a view showing the deviation of 300 between the measured and estimated values ​​of the open-circuit voltage of a battery cell at a temperature of -10 degrees Celsius, based on an example.

[0054] Figure 4 This is a view showing the deviation of 400 between the measured and estimated values ​​of the open-circuit voltage of a single battery cell at a temperature of +10 degrees Celsius, based on an example.

[0055] Figure 5 This is a view showing the deviation of 500 between the measured and estimated values ​​of the open-circuit voltage of a single cell at a temperature of +25 degrees Celsius, based on an example.

[0056] Figure 6 This is a view of characteristic curve 600 and parameter a at a temperature of +25 degrees Celsius, as shown in the example. This characteristic curve describes the relationship between the equilibrium voltage and state of charge of a single battery cell; and

[0057] Figure 7 This is a schematic diagram of a method 700 for determining the state of charge of a battery cell according to the present disclosure. Detailed Implementation

[0058] In the following detailed description, reference is made to the accompanying drawings, which form a part of the invention, in which specific embodiments of the invention can be implemented by way of illustration. It should be understood that other embodiments may be utilized and structural or logical changes may be made without departing from the spirit of the invention. Therefore, the following detailed description should not be construed as limiting. Furthermore, it should be understood that features of the various embodiments described herein can be combined with each other unless explicitly stated otherwise.

[0059] These aspects and embodiments are described with reference to the accompanying drawings, wherein like reference numerals generally refer to like parts. In the following description, numerous specific details are set forth for purposes of explanation in order to provide a thorough understanding of one or more aspects of the invention. However, it will be apparent to those skilled in the art that one or more aspects or embodiments may be implemented with less specific detail. In other instances, well-known structures and components are shown schematically to facilitate the description of one or more aspects or embodiments. It should be understood that other embodiments may be utilized, and structural or logical changes may be made, without departing from the spirit of the invention.

[0060] In the following description, references are made to individual battery cells and the Battery Management System (BMS), as well as the Charge Module Controller (CMC). For a battery cell, such as a lithium-ion single cell, to operate safely, its voltage and temperature must be continuously monitored. This is accomplished using monitoring electronics, or single-cell monitoring electronics, or simply CSE. Individual cells in a battery are combined into a single-cell module. Each single-cell module has a monitoring electronics device, or CSE, to which the individual battery cells are connected. The CSE measures the voltage and temperature of the single cell.

[0061] The Battery Management System (BMS) is the central controller for the battery. Information from each individual Cell Surveillance Equipment (CSE) is aggregated in the BMS. The BMS uses the individual cell voltage to determine the current state of charge (SOC), issues balancing commands, and takes over communication with the vehicle. It also ensures that individual battery cells are not overcharged or over-discharged.

[0062] The following describes the behavior of a single battery cell in relation to relaxation time. Relaxation time here describes the characteristic time it takes for the system, i.e., the battery cell in this case, to approach (usually exponentially) a resting state. This resting state corresponds to the equilibrium voltage on the battery cell. Clearly, after a relaxation time constant, the system moves significantly towards equilibrium. After three to six relaxation time constants, relaxation is generally considered to be essentially complete.

[0063] In the following description, reference is made to electronic circuits. An electronic circuit is a combination of electrical, especially electronic, devices (such as diodes and transistors) arranged to form a functional layout. Electronic circuits can perform very simple functions, such as the blinking of a light or the control of an automatic door. However, many complex technological devices, such as computers or electric vehicles, are based on electronic circuits, typically in the form of integrated circuits (ICs). ICs typically contain a combination of many electrically interconnected electronic semiconductor devices, such as transistors, diodes, and / or other active and passive devices.

[0064] Figure 1 A schematic diagram of an electronic circuit 100 for determining the state of charge of a battery cell in a battery system according to the present disclosure is shown. For example, the battery system may be a battery system for an electric vehicle.

[0065] Electronic circuit 100 is designed to obtain multiple measurements 101 of the open-circuit voltage of a battery cell and associated time values ​​102 at which the open-circuit voltage measurements 101 are detected. Electronic circuit 100 is also designed to determine the equilibrium voltage 112 of the battery cell based on a linear regression 110 of the multiple open-circuit voltage measurements 101, with reference to a predetermined mathematical function 111 of the time values ​​102, which are correlated with the open-circuit voltage measurements 101. Electronic circuit 100 is also designed to determine the state of charge 114 of the battery cell based on a predetermined characteristic curve 113, which indicates the relationship between the equilibrium voltage 112 and the state of charge 114 of the battery cell.

[0066] With the help of electronic circuit 100, taking into account aging, a simple and computationally efficient method can be used to determine the State of Charge (SOC) with higher accuracy after a short period of time.

[0067] The time curve of the open-circuit voltage to the equilibrium voltage of a single cell in the battery is fitted using a new mathematical function 111, the parameters of which can be accurately determined online after several data points. This takes into account single-cell tolerance, measurement error, and aging effects that affect the parameter values. Due to the function type, the parameters can be determined using a computationally efficient regression method 110.

[0068] The electronic circuit 100 can be composed of hardware and / or software.

[0069] For example, in electronic circuit 100, a predetermined mathematical function 111 can specify the time curve 200 of the open-circuit voltage of a single battery cell, such as... Figure 2 As shown in the image.

[0070] The predetermined mathematical function 111 can be a linear function.

[0071] For example, the predetermined mathematical function 111 can be a linear function that depends on: a first parameter (hereinafter referred to as parameter a), or a first parameter and a second parameter (hereinafter referred to as parameter b), or a first parameter, a second parameter and a third parameter (hereinafter referred to as parameter c).

[0072] The predetermined mathematical function 111 can define the time curve 200 of the no-load voltage of the battery cell based on the relaxation time of the battery cell, such as... Figure 2 As shown in the image.

[0073] For example, the predetermined mathematical function 111 can be determined as follows:

[0074] U OCV (θ)=f(a,b,c)=a+b×θ+c×log(θ),

[0075] Here, U OCV (θ) represents the time curve of the no-load voltage of a single cell, which depends on the variable θ, which represents the time related to the relaxation time of the single cell. The predetermined mathematical function depends on the first parameter a, the second parameter b, and the third parameter c, as described in more detail below.

[0076] The electronic circuit 100 can be designed to determine at least one of three parameters based on statistical analysis of the measured value 101 of the open-circuit voltage and the associated time value 102 at these time values.

[0077] Electronic circuit 100 can be designed to perform statistical analysis based on the determination of the following functions:

[0078]

[0079]

[0080] Here, y i The measured value of the no-load voltage is 101,x i The relevant time values ​​102 represent the measured values ​​101 of the open-circuit voltage detected at these time values, as described in more detail below.

[0081] The electronic circuit 100 can be designed to provide a first estimate of the balance voltage 112 of the battery cell by determining a first parameter before the relaxation time of the battery cell is reached, as described in more detail below.

[0082] Electronic circuit 100 can be designed to provide a second estimate of the balance voltage 112 of the battery cell by determining a second parameter before the relaxation time of the battery cell is reached, wherein the second estimate is determined as the sum of the first and second parameters, as described in more detail below.

[0083] Electronic circuit 100 can be designed to store at least the time curve 600 of the first parameter 602 in a memory. Electronic circuit 100 can also be designed to determine the equilibrium voltage 112 of a battery cell based on the stored time curve 600 of at least the first parameter 602 when further determining the state of charge 114 of the battery cell, as described below. Figure 6 To describe in more detail.

[0084] The time curve 600 extends from the start of determining the state of charge 114 to the relaxation time of the individual battery cells, as described in more detail below.

[0085] Electronic circuit 100 can be designed to store multiple time curves 600 of at least a first parameter 602 in a memory for determining the state of charge 114 of a battery cell sequentially over time, as described below for... Figure 6 A more detailed description is provided, and the aging of the battery cells is determined based on multiple time curves 600 of the state of charge 114 of the battery cells.

[0086] The electronic circuit 100 can be applied in, for example, a battery management system (BMS) for electric vehicles. This battery management system includes at least one charging module controller for detecting multiple measurements 101 of the open-circuit voltage on at least one battery cell in a battery system, such as that of an electric vehicle, and for detecting multiple associated time values ​​102 at which the open-circuit voltage measurements 101 are detected. The battery management system includes the aforementioned electronic circuit 100 for determining the state of charge 114 of at least one battery cell in the battery system.

[0087] The operation of electronic circuit 100 is described in more detail below using a lithium-ion single battery as an example.

[0088] The innovation lies in the relaxation of lithium-ion single cells, which is caused by U cell (t) Single cell voltage [V] description, no longer using the exponential method commonly used in the literature:

[0089]

[0090] Instead, a new mathematical function is used:

[0091] U OCV (θ)=f(a,b,c)=a+b×θ+c×log(θ)

[0092] in,

[0093] Here, τ f =R f C f and τct =R ct C dl R represents different time constants. f For polarization resistance, C f Let be the capacitance, and RT be the relaxation time. In the new mathematical function 111, a, b, and c are parameters determined online based on the aging, state of charge, and temperature of the single cell using a well-known "regression" method. In this application (relaxation), the variable t is time, which will be renamed "x" below.

[0094] What makes the new function 111 special is that it is a linear equation, where the parameters can be mathematically determined by least-squares fitting, just like a linear equation.

[0095] For example, vertical least squares fitting (least squares fitting) is done by calculating the vertical deviation R of a set of n data points. 2 This is accomplished by the sum of squares:

[0096] R 2 ≡∑[y i -f(x i a1, a2, ..., a n )] 2

[0097] For the function f above, R 2 The necessary condition for the minimum value is as follows:

[0098]

[0099] For i = 1, ..., n, the following equation is obtained:

[0100]

[0101] These equations can be solved with respect to parameters a, b, and c. (Abbreviations are not included.)

[0102]

[0103]

[0104] nenner=-2×(S lnx )×(s x )×(S xlnx )+n×(S xlnx ) 2 +(s lnx ) 2 ×(s x 2)+s lnx 2×((s x ) 2 -n×sx 2)

[0105] get:

[0106]

[0107]

[0108]

[0109] To determine parameters a, b, and c, n data points consisting of time and voltage values ​​are used. As before: the larger n is, the more accurately the function can be used to predict the equilibrium voltage.

[0110] According to the formula, for the equilibrium voltage of a single cell, after a relaxation time RT, the following relationship is obtained:

[0111] U OCV (θ=1)=a+b

[0112] On the one hand, there exists a time t less than RT for the measured value. On the other hand, b is very small. Therefore, if a is used for the equilibrium voltage, an almost constant value of the function curve is adopted. Even if t is still less than RT, i.e., θ < 1, this means here that...

[0113] b×θ≈c×log(θ)

[0114] Furthermore, various experiments have shown that parameter b is extremely small. This can be seen from the comparison between parameter a and the equilibrium voltage. Here, the value of a can be determined with this level of precision after only 10 minutes.

[0115] The algorithm is explained below. Using this algorithm, the state of charge can be accurately determined after a short period of time using the no-load voltage. The value of the function parameter "a" is recorded in the characteristic curve family after, for example, 15 minutes, and if a balance voltage calculated using SOC almost exists, it is stored, for example, after the relaxation time RT. Figure 6 As shown, the value of "a" can also be directly approximated as a voltage balancer. A function is generated that describes the relationship between the parameter "a" and the SOC (whose value is between 0 and 100).

[0116] If the algorithm has been sufficiently learned, for example, after 15 minutes, the final value can be determined as follows: divide the SOC range into four equal ranges and fit the value pairs {a, SOC} again using the same fitting function. It is recommended to store the new parameters with different names, such as α, β, γ. In the next no-load phase, the expected state of charge can be calculated after a short time. Then, the values ​​in the table are updated periodically to account for aging.

[0117] Figure 2 This is a view of an exemplary time curve 200 of the no-load voltage of a single battery cell.

[0118] The open-circuit voltage begins at time t = 0 with a value of approximately 3.505V, then transitions to an equilibrium state approximately exponentially, reaching this equilibrium state after about 8000 seconds. An equilibrium voltage of approximately 3.53V is then generated. The time curve was measured at a temperature of -10 degrees Celsius.

[0119] With the aid of the aforementioned electronic circuitry, the State of Charge (SOC) can be determined with greater accuracy using a simple, computationally efficient method, taking aging into account, in a very short time. This is... Figure 2 The view is shown here. The parameters of the fitting function used here are determined after 3600 seconds and extrapolated to 5400 seconds.

[0120] The no-load voltage curve was extrapolated very well, so much so that in Figure 2 The difference between the measured open-circuit voltage and the estimated open-circuit voltage cannot be seen in the view.

[0121] Figure 3 This is a view showing the deviation of 300 between the measured and estimated values ​​of the open-circuit voltage of a single battery cell at a temperature of -10 degrees Celsius, based on an example.

[0122] To predict the equilibrium voltage shortly afterward, especially under cryogenic and charging conditions, only three parameters are needed initially instead of four, minimizing storage overhead. Furthermore, to determine the parameters online, only a linear rather than a nonlinear regression method is required, further optimizing computation time. In addition, the previous method 301, which employed the conventional exponential method:

[0123]

[0124] Compared to the novel method 302 described here, the new method is based on the above-mentioned methods already targeted at... Figure 1 The new mathematical function described:

[0125] U OCV (θ)=f(a,b,c)=a+b×θ+c×log(θ)

[0126] The results showed significantly more accurate results than before in certain SOC and temperature ranges.

[0127] Figure 3The diagram shows a comparison of the squared mean between measured and approximate values ​​for a temperature of -10°C using the new method 302 and the previously used method 301 – x1000 – with respect to SOC, expressed as a percentage. It is noteworthy that the new method 302 shows a significantly worse result only at one SOC value, but similar or even better results elsewhere. This is presumably dependent on the specific single cell being examined, and better results could be expected when measuring with other single cells.

[0128] The method described herein is applicable to all energy cells, particularly polymer cells such as silicon polymer cells and lead-acid cells. It has been shown that particularly good results can be obtained using conventional lead-acid starter batteries (i.e., the cells currently used as starter batteries in almost all vehicles). Therefore, electronic circuitry 100 can also be advantageously used with, for example, lead-based starter batteries, such as in a BMS system for monitoring starter batteries.

[0129] Figure 4 This is a view showing the deviation of 400 between the measured and estimated values ​​of the open-circuit voltage of a single cell at a temperature of +10 degrees Celsius, based on an example.

[0130] Figure 4 This illustrates the new method 402, which uses the method described above. Figure 1 In the case of the mathematical function 111 described above, and for the previously used method 401 based on the above exponential function, for a temperature of +10°C, the comparison of the square mean between the measured value and the approximate value - x1000 with respect to SOC is expressed as a percentage.

[0131] Here, the new method 402 also shows significantly worse results only at one SOC value, but shows similar or better results elsewhere.

[0132] Figure 5 This is a view showing the deviation of 500 between the measured and estimated values ​​of the open-circuit voltage of a single cell at a temperature of +25 degrees Celsius, based on an example.

[0133] Figure 5 This illustrates the new method 502, which uses the method described above. Figure 1 In the case of the mathematical function 111 described above, and for the previously used method 501 based on the above exponential function, for a temperature of +25°C, the comparison of the square mean between the measured value and the approximate value - x1000 with respect to SOC is expressed as a percentage.

[0134] Here, the new method 502 also shows significantly worse results only at one SOC value, but shows similar or better results elsewhere.

[0135] In summary, it can be determined that the advantage lies in the fact that the performance of available memory (RAM) and the CPU can be improved through the method according to the invention presented herein, meaning that additional and more complex algorithms can be implemented on the BMU using the same hardware. In cases where the same functionality exists in the battery core, sometimes cheaper chips can thus be used.

[0136] Figure 6 This is a view of characteristic curve 600 and parameter a at a temperature of +25 degrees Celsius, as shown in the example. This characteristic curve describes the relationship between the equilibrium voltage and state of charge of a single battery cell. A measured value 601 and an estimated value 602 of the equilibrium voltage are shown, here represented by parameter a, as described above.

[0137] The parameter 'a' comes from a new mathematical function, as described above for... Figure 1 As already stated, it is expressed as follows:

[0138] U OCV (θ)=f(a,b,c)=a+b×θ+c×log(θ).

[0139] In this characteristic curve, approximately 10% state of charge (SOC) is achieved at a balance voltage of 3.4V. Approximately 35% SOC is achieved at a balance voltage of 3.6V. Approximately 80% SOC is achieved at a balance voltage of 4V. Approximately 98% SOC is achieved at a balance voltage of 4.2V. Almost no difference is observed between the measured balance voltage (601) and the estimated balance voltage (602), as indicated by parameter a, except perhaps at very low SOC values.

[0140] based on Figure 6 The view shown allows for the development of an algorithm that can accurately determine the state of charge (SOC) after a short period using the no-load voltage. The value 602 of parameter "a" of mathematical function 111 is recorded in the family of characteristic curves and, if a near-equal voltage calculated using SOC exists, is stored, for example, after the relaxation time RT. Figure 6 As shown, the deviation between the measured value 601 and the estimated value of the balance voltage is very small and almost negligible. Therefore, the value of "a" can be directly approximated for the balance voltage. A function is generated that describes the relationship between the parameter "a" and SOC (whose value is between 0 and 100), as follows: Figure 6 As shown in the image.

[0141] If the algorithm has been sufficiently learned, for example, after a short period of time—long before the relaxation time—the final value can be determined as follows: divide the SOC range into four equal ranges and fit the value pairs {a, SOC} again using the same fitting function. It is recommended to store the new parameters with different names, such as α, β, γ. In the next no-load phase, and then after a short time, the expected state of charge can be calculated. The values ​​in the table are then periodically updated to account for aging.

[0142] Figure 7 This is a schematic diagram of a method 700 for determining the state of charge of a battery cell in a battery system according to this disclosure. The battery system may be, for example, a battery system for an electric vehicle.

[0143] Method 700 includes the following steps: acquiring multiple measurements 101 of the open-circuit voltage of a single battery cell and associated time values ​​102, and detecting the measurements 101 of the open-circuit voltage at these time values. (As described above regarding...) Figure 1 The process involves: determining the equilibrium voltage 112 of the 702 battery cell based on a linear regression 110 of multiple measured values ​​101 of the open-circuit voltage, with reference to a predetermined mathematical function 111 of time values ​​102, where these time values ​​are associated with the measured values ​​101 of the open-circuit voltage; and determining the state of charge 114 of the 703 battery cell based on a predetermined characteristic curve 113, which indicates the relationship between the equilibrium voltage 112 and the state of charge 114 of the battery cell.

[0144] In addition, a computer program with program code can be provided for executing method 700 on electronic circuit 100 or battery management system, as described above for... Figure 1 As stated above.

[0145] List of reference numerals

[0146] 100 Electronic Circuits

[0147] Measured value of open-circuit voltage of 101 battery cells

[0148] 102 related time values, at which the open-circuit voltage measurement was detected.

[0149] 110 Linear Regression

[0150] 111 Predetermined mathematical functions

[0151] 112 Balanced Voltage

[0152] The characteristic curve specified in 113 indicates the relationship between the equilibrium voltage and the state of charge of a single battery cell.

[0153] 114 charging status, SoC

[0154] Time curve of 200 open-circuit voltage

[0155] 300 The deviation between the measured and estimated values ​​of the no-load voltage

[0156] Bias of the 301 index method

[0157] 302 Deviations from the method according to the present invention

[0158] 400 Deviation between measured and estimated values ​​of no-load voltage

[0159] Bias of the 401 index method

[0160] 402 Deviations from the method according to the present invention

[0161] 500 The deviation between the measured and estimated values ​​of the no-load voltage

[0162] Bias of the 501 index method

[0163] 502 Deviations from the method according to the present invention

[0164] The characteristic curve specified in 600 indicates the relationship between the equilibrium voltage and the state of charge of a single battery cell.

[0165] 700 Method for determining the state of charge of a single battery cell

[0166] 701 First Method Steps

[0167] 702 Second Method Steps

[0168] 703 Third Method Steps

Claims

1. An electronic circuit (100) for determining the state of charge (114) of a battery cell in a battery system, wherein, The electronic circuit (100) is designed to: Multiple measurements (101) of the open-circuit voltage of the battery cell and associated time values ​​(102) are obtained, and the measurements (101) of the open-circuit voltage are detected at these time values. The equilibrium voltage (112) of the battery cell is determined by a linear regression (110) based on multiple measurements (101) of the open-circuit voltage and a predetermined mathematical function (111) of the time values ​​(102) associated with the measurements (101). The state of charge (114) of the battery cell is determined based on a predetermined characteristic curve (113), which indicates the relationship between the equilibrium voltage (112) and the state of charge (114) of the battery cell. The predetermined mathematical function (111) is a function that depends on three or fewer parameters.

2. The electronic circuit (100) according to claim 1, in, The predetermined mathematical function (111) defines the time curve (200) of the no-load voltage of the battery cell.

3. The electronic circuit (100) according to claim 1, in, The predetermined mathematical function (111) defines the time curve (200) of the no-load voltage of the battery cell in relation to the relaxation time of the battery cell.

4. The electronic circuit (100) according to claim 3, in, The predetermined mathematical function (111) is determined as follows: ， Among them, U OCV (θ) represents the time curve of the no-load voltage of the battery cell, which depends on the variable θ, which represents the time related to the relaxation time of the battery cell, and wherein the predetermined mathematical function depends on the first parameter a, the second parameter b, and the third parameter c.

5. The electronic circuit (100) according to claim 4, in, The electronic circuit (100) is designed to determine at least one of the three parameters based on a statistical analysis of the measured value (101) of the open-circuit voltage and the associated time value (102), at which the measured value (101) of the open-circuit voltage is detected.

6. The electronic circuit (100) according to claim 5, in, The electronic circuit (100) is designed to perform statistical evaluation based on the determination of the following function: Wherein, yi represents the measured value of the no-load voltage (101), and xi represents the relevant time value (102), at which the measured value of the no-load voltage (101) is detected.

7. The electronic circuit (100) according to any one of claims 3 to 6, in, The electronic circuit (100) is designed to provide a first estimate of the balance voltage (112) of the battery cell by determining the first of the three parameters before the relaxation time of the battery cell is reached.

8. The electronic circuit (100) according to claim 7, in, The electronic circuit (100) is designed to provide a second estimate of the equilibrium voltage (112) of the battery cell by determining the second of the three parameters before the relaxation time of the battery cell is reached. The second estimated value is determined to be the sum of the first parameter and the second parameter.

9. The electronic circuit (100) according to any one of claims 3 to 6 and claim 8, in, The electronic circuit (100) is designed to store the time curve (600) of at least the first parameter (602) of the three parameters in a memory, and The electronic circuit (100) is designed to determine the balance voltage (112) of the battery cell based on the stored time curve (600) of at least the first parameter (602) when further determining the state of charge (114) of the battery cell.

10. The electronic circuit (100) according to claim 9, in, The time curve (600) extends from the beginning of determining the charging state (114) to the relaxation time of the battery cell.

11. The electronic circuit (100) according to claim 10, in, The electronic circuit (100) is designed to store multiple time curves (600) of at least the first parameter (602) in the memory for determining the state of charge (114) of the battery cells sequentially over time; The electronic circuit (100) is designed to determine the aging of the battery cell based on multiple time curves (600) of the state of charge (114) of the battery cell.

12. The electronic circuit (100) according to claim 1, wherein, The battery system is the battery system of an electric vehicle.

13. A battery management system, comprising: At least one charging module controller is configured to detect multiple measurements (101) of the open-circuit voltage on at least one battery cell of the battery system, and to detect multiple associated time values ​​(102) at which the measurements (101) of the open-circuit voltage are detected; and An electronic circuit (100) for determining the state of charge (114) of at least one battery cell of the battery system according to any one of the preceding claims.

14. The battery management system according to claim 13, wherein, The battery system is the battery system of an electric vehicle.

15. A method (700) for determining the state of charge (114) of a battery cell in a battery system, wherein, The method (700) comprises the following steps: Acquire (701) multiple measurements (101) of the open-circuit voltage of the battery cell and associated time values ​​(102), and detect the measurements (101) of the open-circuit voltage at these time values; The equilibrium voltage (112) of the battery cell is determined (702) by a linear regression (110) of multiple measured values ​​(101) of the open-circuit voltage and by referring to a predetermined mathematical function (111) of the time value (102), which is associated with the measured value (101) of the open-circuit voltage. and The state of charge (114) of the battery cell is determined (703) based on a predetermined characteristic curve (113), which indicates the relationship between the equilibrium voltage (112) and the state of charge (114) of the battery cell. The predetermined mathematical function (111) is a function that depends on three or fewer parameters.

16. The method (700) according to claim 15, wherein, The battery system is the battery system of an electric vehicle.

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