Method for quantifying a degradation mode of a lithium-ion cell
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- ENTROVIEW
- Filing Date
- 2026-01-19
- Publication Date
- 2026-08-06
Smart Images
Figure EP2026051179_06082026_PF_FP_ABST
Abstract
Description
[0001] Method for quantifying a degradation mode of a lithium-ion cell
[0002] [1] The invention relates to a method for quantifying a degradation mode of a lithium-ion cell. The invention also relates to a recording medium and an electronic battery management system for implementing this method. The invention also relates to a motor vehicle incorporating this battery management system.
[0003] [2] To quantify a cell's degradation mode, the differential voltage analysis method is used. This method is known by the acronym DVA (Differential Voltage Analysis) and is hereafter referred to as the DVA method. The incremental capacity analysis method is also used. This latter method is known by the acronym ICA (Incremental Capacity Analysis) and is hereafter referred to as the ICA method. These methods are presented, for example, in the following article: Pastor-Fernandez, C. et al.: "A SoH Diagnosis and Prognosis Method to Identify and Quantify Degradation Modes in Li-Ion Batteries Using the IC / DV Technique," in Proceedings of the 6th Hybrid and Electric Vehicles Conference (HEVC 2016); Institution of Engineering and Technology: London, UK, 2016; 2-3 / 11 / 2016. Hereafter, this article is simply referred to as "Pastor-Fernandez2016."It is also possible to consult the following document: Jingyi Chen et al.: “Peak-Tracking Method to Quantify Degradation Modes in Lithium-Ion Batteries via Differential Voltage and Incremental Capacity”, Journal of Energy Storage, Volume 45, January 2022, 103669, downloadable from the following link: https: / / spiral.imperial.ac.Uk / bitstream / 10044 / l / 92598 / 2 / 2021-IC-DV%20model%20paper_04092021%20-%20revision_woChangeMarked.pdf.
[0004] [3] The DVA method is based on the analysis of the first derivative of the voltage curve of a lithium-ion cell as a function of its capacity during a charge or discharge cycle. The curve that represents the evolution of the first derivative of the voltage as a function of the cell's capacity is subsequently called the "DV curve." As the cell ages, the DV curve changes. In particular, the position and amplitude of certain patterns of interest, such as peaks or valleys, change. Some of these changes are related to a particular degradation mode of the cell. For example, the shifts of certain patterns of interest in the DV curve are caused by a degradation mode known by the acronym LAM ("Lost of Active Material") and subsequently referred to as "LAM mode."The displacements of these patterns of interest relative to reference positions are used to quantify this LAM mode, that is, to determine the importance of this LAM mode relative to a reference state of the cell. Typically, the reference state of the cell is the cell's new state.
[0005] [4] The ICA method works similarly to the DVA method except that it uses the curve representing the evolution of the first derivative of the cell's capacitance with respect to the voltage across its terminals. This curve is subsequently called the "IC curve".
[0006] [5] A drawback of the DVA and ICA methods is that they require a slow cell cycle, either charging or discharging, so that all patterns of interest are readily detectable in the DV or IC curve. Indeed, the faster the charging or discharging cycle, the more difficult it becomes to detect certain patterns of interest in the DV and IC curves, making the quantification of some degradation modes very imprecise or even impossible. Typically, a slow cell charging or discharging cycle suitable for quantifying a degradation mode using the DVA or ICA method lasts at least ten hours and, more often than not, more than twenty hours.
[0007] [6] The invention aims to remedy this drawback by proposing a quantification method which makes it possible to shorten the duration of the charge or discharge cycle used to quantify a mode of degradation.
[0008] [7] The invention is set forth in the attached set of claims.
[0009] [8] The invention will be better understood upon reading the following description, given solely by way of non-limiting example and made with reference to the drawings in which:
[0010] - Figure 1 is a partial schematic illustration of a motor vehicle equipped with an electric battery; - Figures 2 and 3 are graphs that represent various curves containing patterns of interest for quantifying a mode of degradation in a battery cell of the vehicle in Figure 1.
[0011] - Figure 4 is a flowchart of a process for quantifying the degradation modes of a battery cell in the vehicle shown in Figure 1,
[0012] - Figures 5 to 7 are graphs illustrating different functions used during the implementation of the process in Figure 4.
[0013] [9] In this description, the terminology, conventions, and definitions of the terms used in this text are introduced in Chapter I. Detailed examples of embodiments are then described in Chapter II with reference to the figures. Variants of these embodiments are presented in Chapter III. Finally, the advantages of the different embodiments are specified in Chapter IV.
[0014]
[0010] Chapter I: Definitions, terminology and conventions:
[0015]
[0011] In the figures, the same references are used to designate the same elements.
[0016]
[0012] In the remainder of this description, the well-known characteristics and functions of a person skilled in the art are not described in detail.
[0017]
[0013] The expression "an element made of a material A" or the expression "an element made of material A" means that material A represents 90% or 95% of the mass of that element.
[0018]
[0014] A lithium-ion cell is one of the components of a battery capable of storing electrical energy. It is a closed assembly typically containing two electrodes, a separator, and an electrolyte. The negative electrode, called the "anode," is generally made of graphite or another carbon-rich material. Its role is to store lithium ions during the charging process. The positive electrode, called the "cathode," is generally made from metallic compounds such as nickel, manganese, and cobalt oxides (NMC) or lithium iron phosphate oxides (LFP). The cathode stores lithium ions when the battery discharges. The electrolyte is a substance that allows the transport of lithium ions between the anode and the cathode during charge and discharge cycles. The electrolyte is often in liquid form, as a gel, or as a solid polymer.The electrolyte can be a liquid solution of lithium salts dissolved in an organic solvent. The separator is a thin, permeable membrane that prevents direct contact between the anode and cathode, which would cause a short circuit, while still allowing lithium ions to pass through. The separator material is often a microporous polymer. Finally, a cell has an outer casing inside which all the cell components (anode, cathode, electrolyte, and separator) are enclosed. The casing can be rigid, like a metal shell, or flexible. This casing protects the internal components and ensures the structural integrity of the cell.
[0019]
[0015] A battery or a “battery pack” typically comprises several cells electrically connected in series and / or in parallel.
[0020]
[0016] The capacity of a cell, denoted Q in this text, designates the quantity of charge currently stored in that cell. The capacity Q is equal to the result of integrating the intensity of the charging or discharging current of that cell as a function of the time elapsed since a starting instant t0 when the capacity Q o The capacity of the cell is known or taken to be equal by convention, for example, to 0 Ah. The capacity Q is expressed in Ah.
[0021]
[0017] The state of charge of a cell represents the percentage of time that cell is filled. The state of charge is designated by the acronym SOC (State of Charge). It is equal to 100% when the amount of electrical energy stored in the cell is at its maximum. It is equal to 0% when the amount of energy stored in the cell is at its minimum, that is, when no more electrical energy can be extracted from the cell to power an electrical load. The state of charge is related to the cell's capacity by the following equation: SOC(t) = Q(t) / Q ma x, where:
[0022] - SOC(t) is the state of charge at time t,
[0023] - Q(t) is the cell's capacity at time t,
[0024] - Qmax is the maximum capacity of the cell.
[0025] It is noted that the Qmax capacity decreases over time.
[0026]
[0018] The health state of a cell represents its current state compared to its initial state. The health state is often referred to by the acronym SOH (State of Health). The health state is equal to 100% when the cell's capacity is equal to its initial capacity, that is, before any use of the cell. Here, the SOH is defined by the following relationship: SOH = 100*Capa / Capa ini , where: - Capa is the current capacity of the cell, and
[0027] - Capa™ is the initial capacity of the cell.
[0028]
[0019] The definitions of the capacity Q, the state of charge and the state of health of a battery are identical to the corresponding definitions given in the case of a cell except that in these definitions, the term "cell" is replaced by the term "battery".
[0029]
[0020] The term "internal temperature" refers to the temperature at the core of the cell. If the temperature inside the cell is relatively uniform, the internal temperature is close to the temperature measurable on the external surface of that battery cell. Thus, the internal temperature also refers to the temperature of the cell's external surface.
[0030]
[0021] The symbol “*” denotes scalar multiplication.
[0031]
[0022] Chapter: Example of an embodiment
[0032]
[0033]
[0023] Figure 1 represents an electrically powered motor vehicle 2, more commonly known as an "electric vehicle." Electric vehicles are well known, and only the structural elements necessary to understand the remainder of this description are presented. Vehicle 2 comprises:
[0034] - an electric motor 4 capable of rotating drive wheels 6 to propel the vehicle 2 along a road 8, and
[0035] - a battery 10 which supplies electrical energy to the motor 4.
[0036]
[0024] The battery 10 has two electrical connection terminals 12 and 14 and several electrical cells connected between these terminals 12 and 14. The terminals 12 and 14 are connected to the electrical loads to be powered. Here, they are therefore connected in particular to the electric motor 4.
[0037]
[0025] To simplify Figure 1, only four electrical cells 18 to 21 are shown. Typically, these electrical cells are grouped into several tiers, and these tiers are connected in series between terminals 12 and 14. Here, only two tiers are shown. The first tier comprises cells 18 and 19, and the second tier comprises cells 20 and 21. Each tier has several branches connected in parallel. Each branch of a tier has one or more electrical cells in series. Here, the first tier has two branches, and each branch has a single electrical cell. The second tier is structurally identical to the first tier in the example shown in Figure 1.
[0038]
[0026] Here, all the cells of the battery 10 are structurally identical except for manufacturing tolerances. Therefore, only cell 18 is now described in more detail.
[0039]
[0027] The cell 18 has two electrical connection terminals 30, 32 which electrically connect it to the other cells and to the terminals 12 and 14 of the battery 10. The cell 18 is also mechanically fixed, without any degree of freedom, to the other cells of the battery 10 to form what is commonly called a "pack" of cells. The cell 18 is capable of storing electrical energy when it is not being used. This stored electrical energy is then used to power the motor 4, which discharges the cell 18. At other times, the cell 18 can also receive electrical energy, which charges it.
[0040]
[0028] Cell 18 is a lithium-ion cell. For example, here it is an NMC (Nickel-Manganese-Cobalt) cell. An NMC cell is a type of lithium-ion cell in which the cathode is primarily composed of metal oxides of nickel (Ni), manganese (Mn), and cobalt (Co). For one mole of manganese and one mole of cobalt, the number of moles of nickel in the cathode is often between one and eight. The anode is generally made of graphite, which allows the storage of lithium ions during discharge and the release of these ions during charging. Here, silicon is added to the graphite anode to increase its specific capacity. The electrolyte is a liquid or gel that conducts lithium ions, often based on lithium salts dissolved in an organic solvent. The separator is a thin membrane that prevents direct contact between the cathode and the anode, while allowing the passage of lithium ions.
[0041]
[0029] The battery 10 also comprises, for each cell:
[0042] - a voltmeter that measures the voltage between the terminals of this cell,
[0043] - an ammeter that measures the intensity of the current flowing through this cell, and
[0044] - a thermometer that measures the internal temperature of the cell.
[0045]
[0030] To simplify Figure 1, only a voltmeter 34, an ammeter 36, and a thermometer 38 of cell 18 are shown. Hereafter, the term "voltage V" refers to the voltage measured by the voltmeter 34. The term "current i" refers to the current measured by the ammeter 36. The term "temperature Ti" refers to the internal temperature measured by the thermometer 38.
[0046]
[0031] Here, to measure the internal temperature of cell 18, the thermometer 38 is in direct thermal and mechanical contact with the outer envelope of cell 18. The thermometer 38 is directly fixed on cell 18.
[0047]
[0032] Finally, the battery also includes a sensor 39 which measures a physical quantity representative of the ambient temperature Ta. The ambient temperature Ta is the temperature of the external environment in which the cell 18 is immersed. For example, here, the sensor 39 is a thermometer housed between an outer casing of the battery 10 and the outer casings of the various cells 18 to 21.
[0048]
[0033] The vehicle 2 includes an electronic battery management system 40, better known by the acronym BMS (Battery Management System). The function of this system 40 is, in particular, to determine the state of charge of the battery 10. To determine this state of charge, the system 40 is capable of estimating the state of charge of each cell of the battery 10. Here, the system 40 is also configured to estimate the capacity Q of each cell, the entropy variation of each cell, and to quantify the degradation modes of the cell 18.
[0049]
[0034] To perform these different tasks, the system 40 is electrically connected to each sensor of the battery 10 to acquire the measurements from these sensors.
[0050]
[0035] Here, the system 40 includes a memory 42 and a programmable electronic computer 44, capable of executing instructions stored in the memory 42. For this purpose, the memory 42 includes the instructions necessary for the execution of the process of figure 4.
[0051]
[0036] This memory 42 also contains the initial values of the various parameters necessary for the execution of this process.
[0052]
[0037] The vehicle 2 also includes a charging or discharging device 50 and a human-machine interface 52, both connected to the system 40.
[0053]
[0038] The device 50 allows the battery 10, and therefore each of its cells, to be charged or discharged with a current whose intensity is equal to a current setpoint determined by the computer 44. By way of illustration only, in this embodiment, the device 50 is a charger / discharger capable of both charging and discharging the battery 10 with a current whose intensity is controlled by the computer 44.
[0039] The human-machine interface 52 allows various information about the battery 10 to be displayed, including at least the quantification of a degradation mode for each cell and, in particular, for cell 18. The quantification of a degradation mode is a relative quantification with respect to a reference state of the cell. Here, the reference state is the state of the cell when it is new. This quantification is typically expressed as a number.This number can be a percentage expressed relative to the reference state. For example, this percentage is calculated as described in chapter 2.3 of Pastor-Fernandez2016.
[0054]
[0040] By way of illustration, in this embodiment, the human-machine interface 52 includes a screen to display the quantification of one or more degradation modes of each cell of the battery 10.
[0055]
[0041] The graph in Figure 2 represents two curves DV which respectively bear the references DVœo and DV C / 3. On this graph and the following graphs, the x-axis represents the capacitance Q expressed in arbitrary units (aU). The y-axis is graduated in arbitrary units (aU). The curve DVœo was obtained by recording the voltage V for a very large number of different capacitances Q(t) of cell 18 during a slow charging cycle of cell 18. More precisely, the curve DVC / 2O was obtained by charging cell 18 with a charging current whose intensity is constant and equal to C / 20, where C is the nominal capacity in Ah of cell 18. With such a current of intensity C / 20, the state of charge of cell 18 goes from 0% to 100% in twenty hours. The curve DV C / 3 was obtained in the same way as the DVœo curve except that a fast charge cycle of cell 18 was used. More precisely, the DV curve CThe state of charge of cell 18 was obtained by charging it with a constant current of C / 3. With this current, the state of charge of cell 18 increased from 0% to 100% in three hours. The two charging cycles, slow and fast, of cell 18 were performed immediately after each other, so that cell 18 experienced little to no aging between the two charging cycles, and its condition remained unchanged.
[0056]
[0042] As explained in the Pastor-Fernandez2016 article, the DVœo curve contains patterns of interest whose positions and amplitudes change as a function of the aging of cell 18. In particular, certain displacements of a specific group of patterns are caused by a particular mode of degradation of cell 18. Thus, by studying the displacements of the patterns of this specific group, relative to a reference state, it is possible to quantify the importance of this particular mode of degradation at work in cell 18. Typically, the reference state is the position of the patterns of the specific group but in a DVœo curve constructed for cell 18 when it is new.
[0057]
[0043] In the case of cell 18, the DVc / 20 curve has five patterns of interest. Hereafter, these patterns are referred to as "pattern D". Si", "D1, D2, D3 and D4 pattern". On the graph in Figure 2, the locations of these patterns D1, D1, D2, D3 and D4 in the curve DV C / 2o are designated by arrows bearing the references, respectively, "D Si "D1", "D2", "D3", and "D4". Pattern D S D1, D1 to D4 are peaks. Motifs D1, D1, and D3 are related to reactions that occur in the anode. Motifs D2 and D4 are related to reactions that occur in the cathode and, in particular, to the lithium insertion reaction in the cathode's active material.
[0058]
[0044] The DV curve C / 3 also contains the same patterns, but their amplitudes are weaker, or even so weak for some of them that they are no longer detectable. Here, patterns DI, D2, and D4 are detectable in the DV curve. C / 3. The amplitude of the pattern D Siis very weak, so much so that it is barely detectable. The D3 pattern, meanwhile, is no longer detectable in the DV curve C / 3. This illustrates that the faster the charging cycle, the more difficult it is to detect patterns of interest, and therefore the greater the imprecision in quantifying degradation modes. In some cases, such as the one illustrated with the DV curve, C / 3, the fact that a pattern is no longer detectable in the curve can make it impossible to quantify certain modes of cell degradation 18. This is why it is generally accepted that the DVA and ICA methods can only be implemented with slow charge or discharge cycles, i.e. cycles that last more than ten hours and, generally, more than fifteen or twenty hours.
[0059]
[0045] The graph in Figure 3 again represents the curve DV C / 3 and, on the same graph, a DS curve C / 3. The DS curveC / 3 represents the opposite of the evolution of the first derivative of the entropy change AS of cell 18 with respect to the cell's capacity Q. The DS curve C / 3 was obtained:
[0060] - by recording the entropy variation AS for a very large number of different capacitances Q of cell 18 during the same fast charging cycle as that used to construct the points of the DV curve C / 3, then by calculating the first derivative dAS / dQ of the entropy change AS with respect to the capacity Q to obtain a DS curve org which represents the evolution of the derivative dAS / dQ as a function of the cell's capacity Q, and finally
[0061] - by multiplying this DS curve org by -1 to obtain the DS curve C / 3.
[0062]
[0046] It has already been observed that the evolution of the first derivative of the entropy change with respect to the capacity Q includes patterns, respectively, dS1, dS1, dS2, dS3 and dS4 corresponding, respectively, to patterns D S i, Dl, D2, D3 and D4 are observable in the DV^o curve. The positions of the dSsi, dSl, dS2, dS3 and dS4 motifs change as a function of cell aging 18 in the same way as has been described for the D motifs S 1, D1, D2, D3 and D4. On this subject, reference is made for example to the following article: Wojtala, ME and AL: “Entropy Profiling for the Diagnosis of NCA / Gr-SiOx Li-Ion Battery Health”, Journal of Electrochemical Society, 2022, 169, 100527.
[0063]
[0047] As illustrated by the graph in Figure 3, , in the curve DS C / 3 It is possible to detect the pattern dS3 which corresponds to the pattern D3, whereas this pattern D3 is not detectable in the curve DV C / 3. Thus, the DS curves C / 3 and DV C / 3 are complementary because patterns undetectable in one of these curves are detectable in the other, and vice versa. Therefore, when taken in combination, the DS curves C / 3 and DV C / 3 contain all the information necessary to quantify the degradation modes of cell 18, even if these curves were constructed using a fast charging cycle rather than a slow charging cycle. This property is subsequently exploited to make the duration of the charging or discharging cycle used to quantify a degradation mode less than a threshold S0, below which the DVA and ICA methods no longer function or are too imprecise. The threshold S0 here is equal to the duration of the charging or discharging cycle for which at least one of the patterns Dsi, Dl, D2, D3, and D4 becomes difficult to detect in the resulting DV curve. In this application, one of the patterns Dsi, Dl, D2, D3, and D4 becomes difficult to detect when its amplitude is ten times smaller than the amplitude of another of the patterns D S 1, D1, D2, D3 and D4.
[0064]
[0048] In the case of cell 18, pattern D3 is not detectable in the DVC / 3 curve and pattern D Si is difficult to detect, whereas the corresponding dS3 and dSsi patterns are easily detectable in the DS curve C / 3. Therefore, the dS3 and dSsi patterns are subsequently selected, instead of the D3 and Dsi patterns, as patterns of interest to be used to quantify cell degradation modes. Conversely, the dS2 pattern is not detectable in the DS curve. C / 3 while the corresponding pattern D2 is detectable in the curve DV C / 3. Therefore, motif D2 is selected as one of the other motifs of interest to be used to quantify modes of degradation of cell 18.
[0065]
[0049] When a pattern of interest is detectable in the DV curve C / 3 and that the corresponding pattern is also detectable in the DS curve C / 3, then the pattern of interest selected as the one to be used to quantify cell 18 degradation modes can be either the pattern contained in the DVC / 3 curve or the pattern contained in the DS curve C / 3. In the case of cell 18, this situation is encountered for patterns DI and D4. Subsequently, by way of illustration, the five patterns of interest selected to quantify the modes of degradation of cell 18 are patterns dSsi, DI, D2, dS3 and dS4.
[0066]
[0050] The operation of the system 40 will now be described using the method of figure 4 and in the particular case of the quantification of several modes of degradation of the cell 18. Everything that is described thereafter in the particular case of the cell 18 also applies to the other cells of the battery 10.
[0067]
[0051] The process begins with a phase 100 of initialization of the values of the various parameters necessary to execute the process of figure 4. Phase 100 includes in particular the recording in memory 42 of two reference functions fa.ret, fc.ret which are described later.
[0068]
[0052] Once the initialization phase 100 is complete, the execution of a phase 102 quantifying the degradation modes of cell 18 is triggered. When phase 102 is running, the vehicle 2 cannot be used because a charging cycle of cell 18 under predetermined conditions must be performed. Thus, for example, the execution of phase 102 is triggered manually by a user when the vehicle 2 is parked for several hours and the device 50 is electrically connected to a charging station, for example, a fast charging station.
[0069]
[0053] When phase 102 is triggered, if cell 18 is not fully discharged during step 104, the computer 44 commands device 50 to discharge cell 18 until its state of charge (SOC) reaches a value SOCmin. The SOCmin value is the minimum SOC state of charge. This SOCmin value is usually set to 0%. The SOCmin value generally corresponds to a known minimum voltage.
[0054] When the state of charge of cell 18 is equal to SOCmin, during step 106, the computer 44 commands device 50 to perform a charging cycle of cell 18. During this charging cycle, cell 18 is charged from the charging terminal from its state of charge equal to SOCmin to a state of charge equal to SOCmax. The SOCmax value is the maximum SOC state of charge value that cannot be exceeded.This SOCmax value can be equal to or less than 100%. In step 106, the charging cycle is performed under predetermined and known conditions. For example, here, the current intensity i is constant throughout the duration D of the charging cycle. Furthermore, the current intensity i is chosen so that the duration D is greater than a predetermined threshold SI. The threshold SI is equal to the shortest duration of the charging cycle beyond which, if a pattern is not detectable in the DV curve, the corresponding pattern in the DS curve is detectable, and vice versa. Additionally, here, the current intensity i is also chosen so that the duration D is less than the threshold S0 and, preferably, SO / 2. Thus, typically, the current intensity i is less than C or C / 2 and greater than C / 10 or C / 5. In this example, the charging current intensity i is equal to C / 3 throughout the duration D of the charging cycle.
[0070]
[0055] In parallel with step 106, during a measurement step 110, at each instant k, the voltmeter 34, the ammeter 36, the thermometer 38, and the sensor 39 measure, respectively, the voltage V, the current i, and the temperatures Ti and Ta. These measurements Vm k , im k , Ti k and Ta k are immediately acquired by system 40 and stored in memory 42. Step 110 is executed at each instant k of a time sequence of instants {0; 1; 2; ...; k; k+1; ...}. Here, these instants k are repeated at a constant frequency f. The duration of the constant interval between two immediately consecutive instants k and k+1 is denoted At. The duration At is equal to 1 / f. For example, the duration At is between 0.2 s and 1 min.
[0071]
[0056] In parallel with step 110, during a step 112, at each instant k2, the computer 44 estimates the value Q k2 of capacity, the SOC value k2 of the state of charge and the AS valuek2 of the entropy variation AS of cell 18. These estimated values Q k2 , SOC k2 and AS k2 are acquired by the computer 44 and stored in memory 42. Each instant k2 is an instant in a time sequence of instants {0; 1; 2; ...; k2; k2+1; ...}. Here, these instants k2 repeat at a constant frequency f2. The frequency f2 is chosen to be equal to or less than the frequency f. When the frequency f2 is less than the frequency f, the set of instants k2 is a subset of the set of instants k. Between any two successive instants k2 and k2+1, there are therefore several instants k. During step 112, the computer 44 uses the measurements of the voltage V, the current i, and the temperatures Ti and Ta acquired at instants k preceding or equal to instant k2 to estimate the values Q k 2, SOC k 2 and AS k2 For example, the Q value k2is estimated by integrating, between times k = 0 and k = k2, the intensity of the charging current measured by the ammeter 36. The SOC values k2 and AS k2 are estimated using the same method as described in application WO2024 / 146723 or in the application filed on September 10, 2024 under number FR2409598 by Entroview. Therefore, step 112 is not described in further detail.
[0072]
[0057] Once the charging cycle is complete, i.e., after the state of charge has reached the SOCmax value, the process continues with a step 120 of constructing the points of a DV curve and a DS curve from the Vm values k2 and estimated values Q k2 and AS k2acquired during the charging cycle. To construct the different points of the DV curve, for each instant k2, the calculator 44 calculates the first derivative of the voltage V with respect to the capacitance Q at that instant k2. To construct the different points of the DS curve, for each instant k2, the calculator 44 calculates the first derivative of the entropy change AS with respect to the capacitance Q at that instant k2 and then multiplies this first derivative by -1. At the end of this step 120, the resulting DV and DS curves are, for example, those shown in the graphs of Figures 5 to 7.
[0073]
[0058] Next, the computer 44 proceeds to a step 124 of quantifying at least one degradation mode of the cell 18 as a function of differences between current positions of the patterns dSsi, DI, D2, dS3 and dS4 and reference positions for each of these patterns.
[0074]
[0059] Here, during an operation 126, the computer 44 determines in the DV and DS curves the current positions of the selected patterns of interest to be used to quantify the degradation modes of the cell 18. As previously stated, these are the patterns dSsi, DI, D2, dS3 and dS4.
[0075]
[0060] To this end, in step 126, the computer 44 models the patterns dSsi, D1, D2, dS3, and dS4 present in the curves DV and DS by Gaussians, respectively, Gss, Gl, G2, G3, and G4.
[0061] For this purpose, for the pattern dSsi, the computer 44 selects the portion of the curve DS that contains only this pattern dSsi and then determines the parameters m and a that allow obtaining the Gaussian Gsi that minimizes the difference between this selected portion of the curve DS and the Gaussian G S j. The equation of the Gaussian G Si is as follows: G S i(Q) = [1 / (o*(2*n) 0,5 ]*exp[-(Qm) 2 / (2*o) 2], Or :
[0076] - Q is the variable that represents the Q capacity of the cell,
[0077] - o is the standard deviation of the Gaussian distribution,
[0078] - n is the symbol that denotes the number pi,
[0079] - "exp" is the exponential function which is equal to its own derivative and takes the value 1 at 0,
[0080] - m is the average.
[0081]
[0062] Here, by way of illustration, for the determination of the parameters m and o, only the portion of the selected DS curve that lies above a baseline is taken into account. For example, this baseline passes through the bottom of the trough located immediately to the right of the modif dSsi. An example of a Gaussian curve Gsi obtained after modeling the modif dSsi in the DS curve is shown in the graph in Figure 5.
[0082]
[0063] The value of the mean m of the Gaussian Gsi obtained after this modeling, is equal to the current position determined for the pattern dSsi.
[0083]
[0064] What has been described above in the particular case of the dSsi pattern is repeated for the other patterns DI, D2, dS3 and dS4 in order to also obtain the Gaussians Gl, G2, G3 and G4. When the pattern to be modeled is located on the curve DV, it is the portion of this curve DV that contains only this pattern that is selected for its modeling by a Gaussian.
[0084]
[0065] The graph in Figure 5 represents only the Gaussians Gsi, Gl, and G3, which model patterns representative of anode degradation modes. The graph in Figure 6 represents only the Gaussians G2 and G4, which model patterns representative of cathode degradation modes.
[0085]
[0066] Here, the calculator 44 is configured to quantify the following degradation modes of cell 18:
[0086] - a loss of active materials in the anode, subsequently called LAM mode a ,
[0087] - a loss of active materials in the cathode, subsequently called LAM mode C - a cyclable lithium consumption subsequently called LLI mode.
[0088]
[0067] To quantify the LAM mode a During operation 130, the calculator 44 constructs a function f a which models only the dSsi, DI, and dS3 motifs whose positions vary primarily as a function of the cell anode's aging. For example, here, the equation of the function f a is as follows: f a (Q) = G S i(Q) + G1(Q) + G3(Q), where:
[0089] - Q is the variable that represents the capacity of cell 18 and varies between 0 and Q max, Qmax being the quantity of electrical charges stored in the cell when its state of charge is equal to SOC maxj and
[0090] - Gsi(Q), G1(Q) and G3(Q) are the functions of the Gaussians determined during step 126.
[0091]
[0068] An example of a function f a The result thus obtained is represented by a dotted line on the graph in Figure 5.
[0092]
[0069] Then, during an operation 132, the calculator 44 estimates the values of a coefficient Cc a of contraction and a shift in a which minimize the gap fa(Q)-f a ,ref(Q*Cc a + d a ) on a range of values of the capacitance Q which contains all the dSsi, DI and dS3 patterns modeled in the function f a The function f a , r ef is the function that models the same dSsi, DI and dS3 patterns as the function f abut for a reference state of cell 18. Here, the reference state of the cell is the new state, that is, the state of cell 18 before its first use. The function f a , re f is typically obtained in the same way as described previously for the function f a except that it's the new cell 18 that's used. Thus, to construct the function f a.re f, these are the Vm measurements k , im k , Ti k and Ta k measured during a charge cycle of the new cell that is used. Preferably, this charge cycle of the new cell 18 is carried out under the same predetermined conditions as those used in step 106. Thus, here, the charge cycle of the new cell 18 is carried out with a current whose intensity is constant and equal to C / 3. The construction of the function f a , ref is, for example, performed during the initialization phase 100 or by the cell manufacturer 18. Examples of DV curves re f, DS re f used to construct the function f a , re f are represented on the graphs in Figures 5 and 6. On these curves DV re f and DS re f, the patterns dSsi, DI, D2, dS3 and dS4 are designated by the references, respectively, dSsi.ret, Dl re f, D2 re f, dS3 re f and dS4ref. An example of a function f a , re The constructed function f is represented by a solid line in Figure 5. In revolution of the function f a , re f depending on the capacitance Q, the Gaussians Gsi, G1 and G3 bear, respectively, the references Gss.ref, Glret and G3 re f.
[0093]
[0070] The function f a , ret is a function of the reference positions of each of the motifs dSsi, DI and dS3, that is to say here the positions of the Gaussians Gss.ref, Glret and G3 re t. Conversely, the function f a , re f is independent of the current positions of the dSsi, DI, and dS3 motifs determined from the DV and DS curves. The values of the coefficient Cc a and the offset of a are therefore functions of the current positions of the dSsi, DI, and dS3 patterns relative to the reference positions for these same dSsi, DI, and dS3 patterns. Indeed, the values of the coefficient Cc a and the offset of a change depending on the current positions of the dSsi, DI and dS3 patterns relative to their respective reference positions.
[0094]
[0071] Once the values of the coefficient Cc a and the offset of a estimated, during operation 134, the quantification of the LAM mode a is taken as equal to Ll(Cc a), where L1 is a predetermined linear function. For example, the function L1 is: L1(C1) a ) = 1-Cc a Thus, here, the quantification of the LAM mode a is independent of the value of the offset d a .
[0095]
[0072] To quantify the LAM mode C During operation 136, the calculator 44 proceeds in a similar manner to what was described for LAM mode a during operation 130, except that it uses patterns D2 and dS4. Thus, during operation 132, the calculator 44 constructs a function f c which models only the D2 and dS4 motifs whose positions vary primarily as a function of the aging of the cell cathode. The equation of the function f c is as follows: f c (Q) = G2(Q) + G4(Q). An example of a function f c The result thus obtained is represented by dotted lines on the graph in Figure 6.
[0096]
[0073] Then, during an operation 138, the calculator 44 estimates the values of a coefficient Cc c of contraction and a shift in c which minimize the gap fc(Q)-f c ,ref(Q*Cc c + d c ) over a range of values of the capacitance Q that contains all the patterns D2 and dS4. The function f c ,ret is the function that models the same patterns D2 and dS4 but for the reference state of cell 18. The function f c ,ref is obtained in the same way as described previously for the function f c except that these are the Vm measurements k , im k , Ti k and Ta k measured during the charging cycle of the new cell that is used. The construction of the function f c ,ref is for example performed at the same time as the function f a , re t is constructed. An example of a function f cThe constructed reference is represented by a solid line in Figure 6. In the evolution of the function f c , re f as a function of the capacitance Q, the Gaussians G2 and G4 bear, respectively, the references G2 re f and G4 re f.
[0097]
[0074] Once the value of the coefficient Cc c estimated, during step 140, the quantification of the LAM mode C is taken as equal to Ll(Cc c ), where L1 is the same predetermined linear function as that used in operation 134.
[0098]
[0075] To quantify the LLI mode, during an operation 142 the calculator 44 estimates the amplitude A r of the convergence between the functions f a and f c based on the values of the offsets d a and c estimated during operations 132 and 138. For example, the amplitude A r is taken equal to d a -d c The greater the amplitude A rThe greater the convergence between the functions f a and f c is important. If the amplitude A r is negative, this means that the functions f a and f c move away from each other.
[0099]
[0076] Next, the quantization of the LLI mode is taken to be equal to L2(A r ), where L2 is a pre-recorded linear function. For example, the function L2 is: L2(A r ) = (Ar-Ar,ref) / A r ,ref, where A r , r ef is the magnitude of the convergence between the functions f a , ref and fc.ret-
[0077] Once the quantification of the degradation modes of cell 18 is completed, the determined quantifications are used during a phase 150. For example, during phase 150, the computer 44 performs at least one of the following operations: - commanding the human-machine interface 52 to indicate to a human, via this human-machine interface, the determined quantification for each of the degradation modes, and / or
[0100] - the control of the charging or discharging of cell 18 according to the quantification determined for one or more of the degradation modes in order to adapt the use of cell 18 to its current state of health and, for example, try to slow down its aging.
[0101]
[0078] Chapter III: Variants:
[0102]
[0079] Variations of the quantification method:
[0103]
[0080] The execution of the quantification process is not necessarily triggered manually by a user. It can also be triggered automatically when certain predetermined conditions are met. For example, the execution of the quantification process is triggered automatically if the vehicle has traveled, since the last execution of the quantification process, a distance greater than a predetermined threshold and the vehicle has been stationary for several hours.
[0081] In all embodiments described in this application, the charging cycle under predetermined conditions can be replaced by a discharging cycle under predetermined conditions. For example, the discharging cycle consists of discharging the cell 18 from a fully charged state to a fully discharged state, using a current with a constant intensity, for example, equal to C / 3.
[0104]
[0082] Other predetermined conditions can be used during the charge or discharge cycle. For example, during the charge or discharge cycle, the time required to charge the cell is divided into several main intervals separated from each other by secondary intervals. During the main intervals, the cell is charged using a current of constant intensity. During the secondary intervals, the cell is charged using a current of constant intensity that is two or three times greater than during the main intervals. Typically, the duration of each secondary interval is shorter than the duration of the main intervals.
[0105]
[0083] The duration of the charge or discharge cycle may exceed the SO threshold. In this case, the duration of the quantification process is not necessarily shorter than the duration of a quantification process using only the DV curve. However, the combined use of the DV and DS curves may still offer certain advantages, such as increasing the accuracy of the quantification. This increase in accuracy is explained by the fact that the patterns of interest selected in the DS curve have more characteristic amplitudes or shapes, which allow their positions to be determined more precisely than if only the DV curve were used.
[0106]
[0084] In a simplified embodiment, the acquired intensity i is taken to be equal to the intensity setpoint transmitted to the charging / discharging device 50 of the cell 18. In this case, the intensity i is not measured by the ammeter 36 during the charging or discharging cycle.
[0107]
[0085] In step 120, instead of constructing the points of the DV curve, the points of an IC (Incremental Capacitance) curve are constructed. The points of the IC curve are constructed by calculating the first derivative of the capacitance Q with respect to the voltage V. Then, the IC curve is used in place of the DV curve. The IC curve is obtained from the same data used to construct the points of the DV curve. In this text, every lesson taught in the specific case of the DV curve can be transposed to the case where the IC curve is used instead of the DV curve.
[0108]
[0086] A feature of interest in the curves obtained at the end of step 120 is not necessarily a peak. It may also be a valley. In this case, this valley is modeled in subsequent steps, for example, using the negative of a Gaussian curve. This is particularly the case if one of the curves obtained at the end of step 120 is the IC curve.
[0109]
[0087] It is also possible to directly use the dAS / dQ curve instead of the DS curve C / 3, which represents the opposite of the dAS / dQ curve. In this case, the patterns dS1, dS1, dS2, dS3, and dS4 are valleys. However, it is also possible to model these valleys using inverted Gaussians and thus implement the same process as described in Chapter II. In this case, the functions f a and fa.ret have valleys at the locations of the dSsi and dS3 patterns and a peak at the location of the Dl pattern. Similarly, the functions f c and f c ,re f include a valley at the location of pattern dS4 and a peak at the location of pattern D2.
[0110]
[0088] The patterns of interest correspond to variations in slope. Thus, in step 120, dV / dQ, dAS / dQ, or dQ / dV curves are constructed because, in these curves, the patterns of interest are then peaks or valleys, which facilitates their identification. However, such variations in slope can also be identified directly in the V(Q), AS(Q), or Q(V) curves without using its first derivative, where:
[0111] - V(Q) is the evolution of the voltage V as a function of the capacitance Q,
[0112] - AS(Q) is the evolution of the variation AS of entropy as a function of the capacitance Q, and - Q(V) is the evolution of the capacitance Q as a function of the voltage V.
[0113] Thus, in this text, a curve representing the evolution of the first derivative can also be the underivative curve. In this case, the patterns of interest are slopes and not peaks or valleys.
[0114]
[0089] Although the state of charge SOC always varies between 0% and 100% and does not take into account the cell's capacity loss due to aging, it is possible to replace the capacity Q with the state of charge SOC to construct the DV and DS curves. In this case, the DV curve corresponds to the dV / dSOC curve, and the DS curve corresponds to the -dAS / dSOC curve.
[0090] During operation 126, the current positions of the patterns of interest can be determined differently. For example, the resulting DV and DS curves are filtered using a low-pass filter or modeled using a polynomial function so that each pattern of interest corresponds to a bump. Then, the current position of each pattern is taken to be equal to the position of the peak of the bump that corresponds to that pattern.It is also possible to use a learning algorithm (“Machine Learning” in English) which automatically extracts the positions and, possibly, the amplitudes of the patterns from the DV and DS curves.
[0115]
[0091] The number of motifs of interest used may vary, particularly depending on the structure of cell 18. However, the minimum number of motifs of interest used is two, i.e., one motif of interest contained in the curve DV and another motif of interest contained in the curve DS. However, generally, the number of motifs of interest is greater than four so that the functions f a and f c Each function contains at least two patterns. The fact that the functions f a and f c Each one contains at least two patterns, allowing us to estimate the Cc coefficients a , Cc c and the amplitude A r of the rapprochement and therefore to quantify the LAM modes a , LAM b and LLI.
[0116]
[0092] During operations 130 and 136, other embodiments of the functions f a and f c are possible. For example, in the functions f a and f c The patterns of interest are modeled using a function other than a Gaussian. For example, each pattern is modeled by a Dirac function whose value is equal to one at the pattern's position and zero everywhere else.
[0117]
[0093] The sum of the functions f a and f c allows us to obtain a function f g which models, in a single curve, all the patterns of interest in the cell. Similarly, the sum of the functions f a , re f and f c , re f allows us to obtain a function f g , re f, which models, in a single curve, all the patterns of interest of the cell in its reference state and, in particular, their positions. Examples of functions f gand f g , re The functions f are represented in the graph in Figure 7. g and f g , re f can be constructed directly without going through an intermediate step of constructing the functions f a , f c , fa.ret and f c For example, for all points on the curve DS, the points on the curves DV and DS with the same x-coordinate are multiplied by each other to obtain a combined curve. Then, the function f g is obtained by modeling the patterns present in this combined curve. Alternatively, one or more degradation modes are quantified using only the functions f g and f g , re f.
[0094] In another embodiment, the contraction and shift coefficients are estimated by another method that does not use the functions f a and f cand the functions fa.ret and fc.ret. For example, the contraction coefficients are directly estimated based on the deviations, for each motif of interest, between its current position and its reference position. In this case, the functions f a and f c and the functions f a , r ef and fc.ret are not constructed.
[0118]
[0095] Depending on the degradation mode to be quantified and the cell structure, it is possible to quantify this degradation mode without using a contraction coefficient or a shift. For example, only the magnitude of the difference between the current position and the reference position of a motif of interest is taken into account to quantify this degradation mode.
[0119]
[0096] The functions f a , ref and fc.ret can be common to all cells in battery 10 that are structurally identical. Thus, it is not necessary to memorize these functions f a , re f and fc.ret for each identical cell.
[0120]
[0097] Alternatively, the reference position of each motif is not the position of that motif in the new cell. For example, the reference position of each motif is the position of that motif measured at a reference time t. Time t re t can be chosen by the driver or a mechanic. For example, for an electric vehicle, the time t re The time at which the reference positions are measured corresponds to the moment when the driver acquired this used vehicle. In this case, the reference positions are not those measured on the new cell.
[0121]
[0098] In a simplified embodiment, during quantification step 124, only one degradation mode or only some of the degradation modes chosen from the group consisting of the LAM mode a , of the LAM mode C and of the LLI mode, is quantified. In this case, one or more of operations 130 to 134, 136 to 140 and 142 are omitted.
[0122]
[0099] The teaching given here is not limited to the quantification of LAM modes a, LAMc and LLI. The teaching provided here can also be used to quantify any degradation mode of a cell that results in a change in the positions of several patterns of interest relative to their reference positions. In particular, in a cell where a loss of conductivity results in a displacement of certain patterns of interest, then the teaching provided here can be applied to quantify the degradation mode known by the English term "conductivity loss" and designated by the expression "CL mode".
[0100] Other embodiments of the operating phase 150 are possible. For example, in a simplified embodiment, the computer 44 does not control the human-machine interface 52 to indicate the quantifications determined for each of the determined degradation modes.In this case, for example, the determined degradation mode quantification is directly used by the electronic control unit to adjust the cell's charging and discharging without the determined quantification being communicated to the driver. In another embodiment, the electronic control unit simply stores the determined quantification in memory. Then, during vehicle maintenance, the determined quantification is accessible to a mechanic but not to the driver.
[0123]
[0101] Other variants:
[0124]
[0102] Other embodiments of cell 18 are possible. For example, alternatively, the anode does not contain silicon. In this case, the DV and DS curves are devoid of the D motifs Si and even in its new condition. Under these conditions, during the execution of the quantification process, the use of the D patterns Si and dSsi is omitted.
[0125]
[0103] What has been described in the specific case of an NMC cell applies to all lithium-ion cell technologies. For example, it also applies to a cell whose cathode is made of NCA (Nickel-Cobalt-Aluminum) or LFP (Lithium-Iron-Phosphate). In these latter two cases, the anode is typically made of graphite or graphite to which silicon has been added. As mentioned previously, depending on the cell structure, the number of motifs of interest and their shapes vary. Thus, steps 126 and 124 must be adapted accordingly.
[0126]
[0104] The thermometer 38 can be housed inside the envelope of the cell 18.
[0127]
[0105] The sensor 39 can be placed outside the outer casing of the battery 10.
[0128]
[0106] In addition to a quantification method such as one of those described here, the battery management system 40 can also implement other methods of quantifying a degradation mode using either only the DV curve or only the DS curve.
[0129]
[0107] Device 50 can be solely a charger or solely a discharger.
[0130]
[0108] The device 50 may be housed outside the vehicle. In this case, the battery 10 and the system 40 are connected to the device 50 by an external cable connected to an electrical outlet in the vehicle only when the vehicle is parked. For example, the device 50 is housed in a charging station attached to the parking space. The device 50 may also consist of several components, some of which are housed inside the vehicle and others outside the vehicle.
[0131]
[0109] Numerous other embodiments of the human-machine interface 52 are possible. For example, the human-machine interface includes an indicator light that illuminates only when the quantification of one of the degradation modes satisfies a predetermined condition. In this latter case, the screen can be omitted.
[0132]
[0110] The teaching given here in the specific case of a cell and battery of an electric vehicle applies to all cells and batteries, whether or not they are used in an electric vehicle. For example, it applies to the cells contained in a telephone or a lamp. It also applies to used cells and batteries as well as new ones. In particular, applying the quantification method to a new cell makes it possible to detect a defective new cell immediately after its manufacture if the functions fa.ret and f c , reThe values of the functions used were measured on another structurally identical, non-defective new cell. A failure during the manufacturing of a new cell can also be detected when the functions fa.ret and fc.ret are measured at an initial time during the manufacturing of that cell. Then, at a later time during the manufacturing of the same cell, the quantification process described here is implemented using the functions fa.ret and f. c These values are measured at the initial time. This allows us to track the evolution of the cell's degradation modes during the manufacturing process and thus identify a failure if this evolution is too significant. Typically, a failure is detected if this evolution exceeds one or more predetermined thresholds.
[0133]
[0111] In another embodiment, the method for quantifying the degradation modes of a cell is applied to several different cells. Then, the quantification of these degradation modes is used to group together cells whose degradation modes are similar. For example, cells whose quantified degradation modes are close to each other are grouped within the same battery to form homogeneous cell batteries. In this context, one of the compared cells is, for example, chosen as the reference cell, and the functions fa.ret and f c ,ret are measured on this cell.
[0112] Several of the variants described above can be combined in the same embodiment.
[0134]
[0113] Chapter IV: Advantages of the embodiments described:
[0135]
[0114] Quantifying a degradation mode using both the DV and DS curves makes it possible to reduce the duration of the charge or discharge cycle while still being able to accurately quantify the degradation mode. Indeed, the quantification method described here continues to function correctly even if the duration of the charge or discharge cycle has been reduced to a point where some of the patterns of interest in the DV and DS curves are no longer detectable.
[0136]
[0115] Choosing the duration of the charge or discharge cycle below the SO threshold makes it possible to substantially reduce the time required to quantify a mode of degradation.
[0137]
[0116] Modeling the patterns using Gaussians allows for a more precise determination of their positions in the DV and DS curves. This therefore increases the accuracy of the process.
Claims
25 Demands 1. A method for quantifying a degradation mode of a lithium-ion cell, this method comprising the execution of the following steps by an electronic computer: a) the acquisition (110) of the voltage between cell terminals for different capacitances of this cell during a charge or discharge cycle of the lithium-ion cell under predetermined conditions, then b) from the voltages acquired for different cell capacities, the construction (120) of the points of a first curve chosen from the group consisting of: - a curve that represents the evolution of the first derivative of the voltage across the cell terminals with respect to the cell's capacitance, and - a curve that represents the evolution of the first derivative of the cell's capacitance with respect to the voltage between the terminals of that cell, then c) the quantification (124) of the degradation mode as a function of a difference between the position of a first motif of interest in the first constructed curve and a first pre-recorded reference position for this first motif, in which: - Step a) also includes, for the different cell capacities, the acquisition of the intensity of the cell's charge or discharge current, the acquisition of the cell's internal temperature, and the acquisition of the ambient temperature. - step b) further involves, from the voltages, the intensities of the charging or discharging current, the internal temperatures and the ambient temperatures acquired for the different capacitances of the cell, the construction of the points of a second curve which represents the evolution of the first derivative of the variation of the entropy of the cell with respect to the capacitance of the cell, and - during step c), the quantification of the degradation mode is also a function of a difference between the position of a second motif of interest in the second curve and a second pre-recorded reference position for this second motif.
2. A method according to claim 1, wherein, during step a) (110), the duration of the charging or discharging cycle is less than a threshold S0, the threshold S0 being equal to the duration of the charging or discharging cycle for which the amplitude of a third motif in the first curve is ten times less than the amplitude of the first motif in this first curve, this third motif being the motif which corresponds to the second motif but in the first curve.
3. Method according to claim 2, wherein, at step a) (110), the duration of the charge or discharge cycle is less than SO / 2.
4. A method according to any one of the preceding claims, wherein, during step a) (110), the duration of the charge or discharge cycle is greater than a threshold SI, the threshold SI being equal to the smallest duration of the charge or discharge cycle for which the first pattern is detectable in the first curve and the second pattern is detectable in the second curve.
5. A method according to any one of the preceding claims, wherein step c) comprises modeling (126) each motif by a Gaussian whose mean is equal to the position of that motif.
6. A method according to any one of the preceding claims, wherein, in step c), the quantification of the degradation mode comprises: - from the points of the first and second curves constructed during step b), the construction (130, 136) of a first function f awhich models only the patterns whose positions vary according to the aging of a cell anode and a second function f c which models only the patterns whose positions vary depending on the aging of a cell cathode, then - at least one of the following operations: - the estimation (132) of a coefficient Cc a of contraction and a shift in a which minimizes the gap f a (Q)-f a ,ref(Q*Cc a + d a ) over a range of capacitance values that contains all the patterns whose positions vary according to the aging of the anode, and then the quantification (134) of a loss of active material in the anode from this coefficient Cc a estimated, where f a , re f is a pre-recorded reference function that models the same patterns as the function f abut when they each occupy their reference positions, Tl - the estimation (138) of a coefficient Cc c of contraction and a shift in c which minimizes the gap fc(Q)-f c ,ref(Q*Cc c + d c ) over a range of capacitance values that contains all the patterns whose positions vary according to cathode aging, and then the quantification (140) of a loss of active material in the cathode from this coefficient Cc c estimated, where f c , re f is a pre-recorded reference function that models the same patterns as the function f c but when they each occupy their respective reference positions, - the estimate (130, 138) of the magnitude of the convergence between the functions f a and f c based on the shift of the function f a with respect to the function f a , re f and the shift of the function f cwith respect to the function f c , re f, then the quantification (142) of a cyclable lithium consumption from the estimated amplitude.
7. A method according to any one of the preceding claims, wherein the method comprises performing at least one of the following operations by the electronic computer: - the control (150) of a human-machine interface to indicate to a human being, via this human-machine interface, the quantification of the degradation mode determined during step c), and - the control (150) of the charging or discharging of the cell according to the quantification of the degradation mode determined during step c).
8. A method according to any one of the preceding claims, wherein the method comprises, the control (106), by the electronic computer, of the intensity of the charging or discharging current of the cell to execute the charging or discharging cycle of the cell under predetermined conditions during which, in step a), the voltage, the intensity of the charging or discharging current, the internal temperature and the ambient temperature are acquired for different capacities.
9. A method according to any one of the preceding claims, wherein: - the method comprises measuring (110), using electronic sensors, the voltage, internal temperature, and ambient temperature, and 28 - during step a), the voltage, internal temperature and ambient temperature acquired are the voltage, internal temperature and ambient temperature measured by these electronic sensors.
10. A method according to any one of the preceding claims, wherein the lithium-ion cell comprises an anode containing graphite.
11. Information storage medium (42) readable by an electronic computer, characterized in that it includes instructions for the execution of a quantification process according to any one of the preceding claims, when these instructions are executed by the electronic computer.
12. Electronic battery management system equipped with at least one lithium-ion cell, this system comprising an electronic computer (44) programmed to execute an automatic method for quantifying a degradation mode of the lithium-ion cell, characterized in that the computer (44) is programmed to execute the automatic method for quantifying a degradation mode of a lithium-ion cell according to any one of claims 1 to 10.
13. Motor vehicle comprising: - at least one drive wheel (6), - an electric motor (4) capable of rotating this drive wheel to move the motor vehicle, - a battery (10) comprising at least one lithium-ion cell (18-21) capable of storing electrical energy and, alternately, of releasing electrical energy to power the electric motor, this cell comprising two terminals (30, 32) through which it is electrically connected to the electric motor, - a voltmeter (34) electrically connected between the terminals of the cell to measure the voltage between these terminals, - an ammeter (36) connected in series with the electrical cell to measure the intensity of the current flowing through this cell, - a thermometer (38) capable of measuring an internal temperature of the electrical cell,29 - a sensor (39) capable of measuring a physical quantity representative of the ambient temperature, and - an electronic battery management system (40) connected to the voltmeter, ammeter and thermometer, this management system comprising a programmable electronic computer (44) configured to quantify a degradation mode of a battery cell from the measurements of the thermometer, voltmeter and ammeter, characterized in that the battery management system (40) conforms to claim 12.