METHOD FOR ESTIMATING THE TEMPERATURE OF A PRISMATIC ELECTRICAL STORAGE CELL IN A LITHIUM-ION ELECTRICAL BATTERY

Abstract

The method comprises a data acquisition step, a thermal distribution estimation step within the cell (MP), and a thermal gradient calculation step based on the thermal distribution. The estimation step includes calculations based on an application of the Fourier heat equation, using the so-called "finite volume" method, and a mesh (MD) modeling a spiral layer winding of the cell. The mesh comprises parallelepiped cells (Mi1, Mi3) modeling a central part (PC) and rounded cells (Mi2, Mi4) modeling lateral flanks (FG, FD) of the winding. According to the invention, the rounded cells of one flank and the rounded cells of the other flank have different radii of curvature (rmax, rmin), with a rounded cell of one flank having, within the same layer of the winding, a radius greater than that of a corresponding rounded cell of the other flank. Figure 5

Description

Title of the invention: METHOD FOR ESTIMATING THE TEMPERATURE OF A PRISMATIC ELECTRICAL STORAGE CELL IN A LITHIUM-ION TYPE ELECTRICAL BATTERY

[0001] The present invention relates generally to the field of thermal management of lithium-ion type electric batteries incorporating prismatic electric storage cells. More particularly, the invention relates to a method for estimating the temperature in a lithium-ion type prismatic electric storage cell. The method of the invention is applicable in particular for the thermal management of lithium-ion type electric traction batteries in electrified vehicles.

[0002] In an electrified vehicle, such as an all-electric vehicle or a thermal-electric hybrid vehicle, the electric traction battery can release a significant amount of heat when it is used to drive the vehicle. Thermal management of the electric traction battery is necessary to maximize its lifespan, availability, and performance. Knowledge of the temperature of the battery's electrical storage cells, more precisely, the spatial distribution of the temperature therein, makes it possible to calculate internal thermal gradients in these cells. These internal thermal gradients are used for the thermal management of the battery, in particular by controlling its cooling system.They can also be used to activate degraded vehicle traction modes ensuring less demand on the battery, to reduce its recharging times via optimized control of the electrical charging power, as well as to anticipate breakdowns and prevent thermal runaway of the battery.

[0003] Methods for estimating the temperature in a lithium-ion type electrical storage cell are known in the state of the art. These methods use thermal modeling of the cell to obtain an estimate of the internal temperature thereof.

[0004] A classic modeling approach is to consider the cell as a homogeneous and isotropic material. This results in a simple model of the cell, but which does not allow obtaining the internal thermal gradients in the latter, due to the isotropy hypothesis. More elaborate models take into account the anisotropy of the materials and allow obtaining a spatial distribution of the temperature in the cell, but these models remain too simple and lack accuracy for reliable estimation of internal thermal gradients.

[0005] Furthermore, complex models based on finite element analysis, known as "FEA" for "Finite Element Analysis" in English, are known, which provide a detailed definition of the structure of the cell and make it possible to achieve high precision in the spatial distribution of the temperature in the cell. With such models, it is possible to validly estimate the internal thermal gradients in the cell, but their complexity requires significant computing capacity, which considerably limits the usefulness of these models for certain real-time applications, such as in particular the thermal management of electric traction batteries in electrified vehicles. Document CN109902372A describes a method for estimating the temperature of the above type for a prismatic lithium-ion cell.The CN109902372A process requires three-dimensional (3D) modeling using computer-aided design software, such as AutoCAD® or SolidWorks®, with careful discretization of the cell's spiral layer winding, known as a jelly roll. It requires considerable computing resources that are not always available, particularly in a vehicle battery management system, known as a BMS.

[0006] In the literature, optimized models for cylindrical cells are described, which require little computation time, take into account the anisotropy of the materials and are capable of evaluating an internal thermal gradient in the cell.

[0007] In the article "Aging effect of temperature gradients in Li-ion cells experimental and simulative investigations and the consequences on thermal battery management", presented at the symposium "26th Electric Vehicle Symposium and Exposition (EVS26), Eos Angeles, California, May 6 - 9, 2012", the authors Matthias Fleckenstein et al. disclose a method for evaluating the internal thermal gradient in a prismatic lithium-ion cell. The method uses the finite volume method, using the Fourier heat equation, and proposes for the calculation a discretization mesh of the prismatic cell into 4x5x6 elementary cells.

[0008] The discretization mesh described in the aforementioned article, illustrated in [Fig.l], is based on an approximate geometric representation CE of a prismatic cell in the form of three superimposed loop layers CS1, CS2 and CS3. The spiral winding of the layers on each other is not taken into account. The spiral winding introduces a variation of the radius of curvature in the same layer. The discretization mesh proposed in the aforementioned article results in a lack of precision in the calculation of the spatial distribution of the temperature. In addition, the heat transfer is considered here only in the radial direction (see arrow DR in [Fig.l]), between central cells MC and external cells ME.

[0009] It is desirable to provide a solution that does not have the above drawbacks mentioned in the prior art and adapted for integration into an electrified vehicle, to reliably estimate the temperature and thermal gradients in prismatic lithium-ion type electrical storage cells.

[0010] According to a first aspect, the invention relates to a method for estimating the temperature in a lithium-ion type prismatic electrical storage cell comprising a data acquisition step, a step for estimating a thermal spatial distribution in the prismatic electrical storage cell and a step for calculating a thermal gradient in the prismatic electrical storage cell from the thermal spatial distribution, the thermal spatial distribution estimation step comprising calculations based on an application of the Fourier heat equation, with the so-called “finite volume” method and a predetermined discretization mesh modeling a spiral winding of layers called a “jelly roll” of the prismatic electrical storage cell,the discretization mesh comprising a plurality of parallelepiped meshes modeling a central part of the winding and another plurality of rounded meshes modeling first and second rounded lateral flanks distant from the winding. According to the invention, the rounded meshes modeling the first flank and the rounded meshes modeling the second flank have different radii of curvature, a rounded mesh of the first flank having, in the same layer of the winding, a radius of curvature greater than that of a corresponding rounded mesh of the second flank, so as to faithfully model the spiral winding of one layer on the other.

[0011] According to a particular characteristic, the thermal spatial distribution estimation step comprises three-dimensional calculations in real time, from the thermal spatial distribution, to estimate and follow an evolution of one or more thermal gradients of the prismatic electrical storage cell in a three-dimensional space.

[0012] According to another particular characteristic, the thermal spatial distribution estimation step comprises automatic consideration of physicochemical parameters and thermophysical characteristics of the layers.

[0013] The invention also relates to a computer comprising a memory storing program instructions for implementing the method as briefly described above.

[0014] The invention also relates to an assembly of an electric battery comprising a plurality of prismatic lithium-ion type electric storage cells and a computer, integrated in a vehicle, the computer being a computer as described above. In a particular embodiment for an electrified vehicle, the electric battery is an electric traction battery. In another embodiment particular use, the calculator included in this set is a battery management calculator of the so-called “BMS” type.

[0015] The invention also relates to a vehicle comprising an assembly as briefly described above.

[0016] Other advantages and characteristics of the present invention will appear more clearly on reading the detailed description below of several particular embodiments of the invention, with reference to the appended drawings, in which:

[0017] [Fig.l] is a three-dimensional representation of a prior art discretization mesh of a lithium-ion type prismatic electrical storage cell.

[0018] [Fig.2] is a block diagram showing schematically in a simplified manner an electrical architecture of an electric vehicle in which a particular embodiment of the method according to the invention is implemented.

[0019] [Fig.3] is a three-dimensional representation of a discretization mesh for a prismatic lithium-ion type electrical storage cell, used in the method of the invention.

[0020] [Fig.4] is a block diagram showing functional blocks of the method according to the invention.

[0021] [Fig.5] is a front plan view of the discretization mesh of [Fig.3] showing the distinct radii of curvature, taken into account by the method of the invention, of distant rounded meshes in the same layer of the spiral layer winding of a prismatic lithium-ion type electrical storage cell.

[0022] [Fig.6] is a schematic representation of an assembly formed of a prismatic lithium-ion type electrical storage cell and a cooling plate.

[0023] [Fig.7] shows, as an example, a charge / discharge current curve and a corresponding curve of an estimated thermal gradient across [Fig.6].

[0024] With reference to Figs. 2 to 5, a particular embodiment of the method according to the invention is now described. In this exemplary embodiment, the method is implemented in an electrified vehicle in the form of an all-electric vehicle EV shown in [Fig. 2]. The EV vehicle comprises an electric powertrain integrating an eGMP electric powertrain. The eGMP electric powertrain is supplied with energy by a high-voltage battery pack BAT_HV, through a reversible electric converter of the DC / AC type (not shown).

[0025] The BAT_HV battery pack here comprises a plurality of prismatic lithium-ion MP electrical storage cells typically integrated into parallelepiped modular boxes, which store electrical energy, as well as conductive buses for electrical connection of the cells and a thermal management system. (not shown). The BAT_HV battery pack is managed by a BMS computer.

[0026] The BMS calculator is connected to an eCAN data communication network, typically of the “CAN” type, of the vehicle and hosts embedded software modules which perform various management and measurement functions for the BAT_HV battery pack, such as for example an estimation of a state of charge called “SOC” (for “State Of Charge” in English) and an estimation of a state of health called “SOH” (for “State Of Heath” in English).

[0027] The implementation of the method according to the invention uses an embedded software module M0D_SW which is hosted here in the aforementioned BMS computer of the vehicle. As shown in [Fig.2], the software module M0D_SW is implanted in a memory MEM of the BMS computer. The BMS computer can cooperate, under the supervision of the software module M0D_SW, with one or more other computers of the vehicle for the implementation of the method according to the invention, in particular here the eVCU computer which is the supervisor computer of the electric powertrain of the vehicle. The software module M0D_SW authorizes the implementation of the method according to the invention by the execution of program code instructions by a processor (not shown) of the BMS computer.

[0028] As shown schematically in [Fig.2], for the implementation of the method according to the invention, the software module M0D_SW uses different information INF_MD, detailed below, which is typically already available in the BMS computer, obtained from another computer, such as the eVCU computer, and / or provided by measurement sensors of the battery pack BAT_HV. The software module M0D_SW outputs three-dimensional spatial distribution information of temperature D_T, thermal gradient GD and alert AL.

[0029] In [Fig. 3], an example of an MD discretization mesh used by the method of the invention for a prismatic electric storage cell of the MP lithium-ion type is represented in three dimensions (3D) in an orthogonal spatial reference frame (X, Y, Z).

[0030] As visible in [Fig.3], the MD discretization mesh comprises a plurality of parallelepiped meshes modeling a parallelepiped central portion PC of the spiral layer winding and a plurality of rounded meshes modeling first and second distant rounded lateral flanks FG and FD of the spiral layer winding.

[0031] In the example shown, the MP cell is formed by a spiral winding of four layers CCI to CC4. The MD mesh comprises four slices T1 to T4 of the same height along the Z axis. In each slice T1, T2, T3 or T4, the layers are each represented by four corresponding adjacent meshes. With the four slices, a complete layer is therefore discretized into 4x4 meshes.

[0032] Thus, for example, as illustrated in [Fig.3], in slice T1, layer CC4 is discretized here into four meshes M4b M42, M43 and M44. The meshes M4i and M43 have parallelepiped geometric shapes. The meshes M42 and M44 have rounded geometric shapes with respective distinct radii of curvature rmax and rmin, to faithfully represent the spiral winding of one layer on the other. The radius of curvature rmax of the mesh M42 is greater than that rmin of the mesh M44. The volume of the mesh M42 is therefore greater than that of the mesh M44.

[0033] Each of the layers CCI to CC4 is formed of a plurality of sub-layers, typically eight layers, shown schematically in the enlargement AG of [Fig. 3]. These sub-layers correspond to a stack of sheets having different physico-chemical parameters and thermo-physical characteristics, namely in particular, different materials, thicknesses, densities, thermal capacities and thermal conductivities. These sub-layers correspond in particular to an aluminum collector sheet, a copper collector sheet, two separator sheets, two anode sheets and two cathode sheets.

[0034] The treatment process implemented in the method according to the invention is now described below with particular reference to [Fig.4] and [Fig.5].

[0035] As shown schematically in [Fig.4], the processing process essentially comprises four functional blocks B1, B2 to B4. These functional blocks B1 to B4 are respectively a data acquisition block, a thermal spatial distribution calculation block, a thermal gradient estimation block and a block for restoring estimation and alert results.

[0036] The functional block B1 has the function of acquiring and storing various information necessary for implementing the method of the invention, such as the aforementioned INF_MD information. This INF_MD information includes in particular geometrical characteristic data of the spiral layer winding of the MP cell, data of the aforementioned thermo-physical characteristics of the sub-layers, electrical capacity and power data, charge / discharge current and voltage data of the MP cell, state of charge “SOC” and state of health “SOH” data, boundary data such as measured and / or estimated temperatures of contact surfaces with a cooling system, the surrounding ambient air, etc., and / or other data, depending on the application. Fixed geometrical, thermo-physical and other characteristic data are acquired and stored beforehand.Variable data (current, voltage, cooling system temperature, etc.) are typically acquired in real time as the treatment process runs.

[0037] The thermal spatial distribution calculation block B2 essentially uses four main calculation functions Fl to F4. Block B2 outputs the above-mentioned three-dimensional spatial temperature distribution information D_T.

[0038] The function Fl uses the Fourier heat equation EQ1 and the so-called "finite volume" method for temperature calculations in the different meshes. The calculations are carried out in a three-dimensional frame shown in [Fig.5] having an axial axis (coordinate 1), a radial axis (coordinate r) and an ortho-radial axis (coordinate z). In the equation EQ1, the variable Tyj represents the temperature in the mesh My, py the density of the mesh My and Cysa specific heat capacity, Qy the total heat generated by the mesh My and Vy its volume, and Xr, Xi and Xz the thermal conductivities in the three axes considered and Sr, Si and Sz the contact surfaces between meshes in the three axes considered.

[0039] Function F2 uses equations EQ2 and EQ3 to calculate respectively the density py of the mesh My and its specific heat capacity Cy, from the thermo-physical characteristics of the above-mentioned sub-layers. In equations EQ2 and EQ4, for the sub-layer considered, Vi represents the volume of the sub-layer in the mesh My, py its density, M; its mass and Cpi its heat capacity.

[0040] Function F3 is responsible for calculating the contact surfaces between the meshes and their volumes.

[0041] Also referring to [Fig.5], the calculation for the rounded meshes Mi2, Mi4, is detailed and uses equations EQ4 to EQ6 of a sub-function F30. For the parallelepiped meshes Mn, Mi3, the calculation is not detailed and is carried out by a sub-function F31.

[0042] Equations EQ4 give the radii of curvature of the rounded meshes Mi2, Mi4, for a layer i, i being the number of the layer in the form of an increasing integer from the central layer to the external layer of the spiral winding of layers.

[0043] In equation EQ4, rmax, rmaxi / i+i, and rmin iZi, rmini / i+i, represent respectively the small and large radii for the two rounded meshes Mi2 and Mi4 of layer i, and rmax0 / i and rmin0 / i the small radii for the two rounded meshes Mn and M 14 of the first central layer i=l, knowing that d and e are respectively the thickness of layer i and the thickness of a hollow central space of the winding.

[0044] Equations EQ5 are used to calculate the contact surfaces between meshes Sr, Si and Sz, in the three axes considered, for the rounded meshes Mi2 and Mi4 of layer i, with dz being the height of the mesh. The volumes Vy for the rounded meshes Mi2 and Mi4 are given by equations EQ6.

[0045] The function F4 is responsible for calculating the total heat Qy produced in the considered mesh My. An electrical model is used here to evaluate the production of heat.

[0046] Block B3 receives the three-dimensional spatial temperature distribution information D_T provided by block B2 and estimates in real time and in three dimensions (3D) one or more thermal gradients GD, according to the need and / or the application. The spatial temperature distribution information D_T and thermal gradient GD are delivered as input to block B4.

[0047] Block B4 is responsible for returning the estimated information D_T and GD to one or more recipient systems and for implementing one or more preprogrammed alert strategies AL which are based on the exploitation of the information D_T, GD. Depending on the application, the information D_T, GD and AL will be intended for one or more system control strategies (battery cooling system, battery management system, electric powertrain, electric charging station or others), for a preventive maintenance system or others.

[0048] Tests and simulations were carried out by the inventive entity and made it possible to verify the accuracy of the estimates obtained using the method of the invention.

[0049] With reference to [Fig.6] and [Fig.7], for illustrative purposes, a simulation of estimating a thermal gradient GD in an MP cell mounted on an RE cooling plate has been carried out. The thermal gradient GD is estimated for given boundary conditions and a charge / discharge current having a specific profile.

[0050] The current profile Ic shown in [Fig.7] was determined in order to study its effect on the thermal gradient GD during charging and discharging of the MP cell.

[0051] The MP cell is subjected to thermal conduction by a lower face in contact with the cooling plate RE. The thermal gradient GD considered here is that between a lower section of the MP cell close to the plate RE and an upper section distant from the MP cell.

[0052] For this simulation, the ambient air temperature is set at 25°C and the cooling temperature is set at 30°C.

[0053] [Fig.7] shows the thermal gradient GD observed in the MP cell during a DCH discharge phase and a subsequent CH recharge phase. The thermal gradient GD reaches GD = 0.7 °C approximately during the CH charge phase and is higher than that observed GD = 0.2 °C during the DCH discharge phase. This is mainly due to the fact that the current le is higher during the CH recharge phase, namely, approximately 60 A here while it is only approximately 20 A during the DCH discharge phase.

[0054] This simulation shows that the temperature difference between the upper and lower sections of the MP cell increases significantly at high load rates, particularly when the cooling plate temperature is low. The method of the invention, by providing a precise estimation of thermal gradients, allows effective thermal management of the MP cell, so as to maintain its performance and meet safety requirements.

[0055] The method of the invention, unlike the methods of the state of the art based on complex models, is frugal in computing resources and can be implemented in the battery management system of an electrified vehicle. The mesh used in the method of the invention offers the advantage of being parametric, which makes it adaptable to different spiral layer windings of prismatic cells of the lithium-ion type. It allows the elementary layers to be wound on each other, thus facilitating the passage of heat from one layer to another. Furthermore, the mesh of the method of the invention is flexible and allows the number of meshes to be chosen along three axes (axial axis, radial axis and ortho-radial), which provides the possibility of optimizing the simulation time for real-time monitoring of the evolution of the thermal gradient.It should also be noted that the physicochemical parameters of the elementary layers, as well as the parameters of the electrothermal model, can be calculated automatically by the process.

[0056] The invention is not limited to the particular embodiment which has been described here by way of example. Those skilled in the art, depending on the applications of the invention, will be able to make various modifications and variants falling within the scope of protection of the invention.

Claims

Claims

1. A method for estimating the temperature in a lithium-ion type prismatic electrical storage cell (MP) comprising a data acquisition step (B1), a step for estimating a thermal spatial distribution (B2) in said prismatic electrical storage cell (MP) and a step for calculating a thermal gradient (B3) in said prismatic electrical storage cell (MP) from said thermal spatial distribution, said thermal spatial distribution estimation step (B2) comprising calculations (F1) based on an application of the Fourier heat equation, with the so-called "finite volume" method and a predetermined discretization mesh (MD) modeling a spiral winding of layers called a "jelly roll" of said prismatic electrical storage cell (MP), said discretization mesh (MD) comprising a plurality of parallelepiped meshes (Mu,Mi3) modeling a central portion (PC) of said winding and another plurality of rounded meshes (Mi2, Mi4) modeling first and second distant rounded lateral flanks (FG, FD) of said winding, characterized in that said rounded meshes (Mi2) modeling said first flank (FG) and said rounded meshes (Mi4) modeling said second flank (FD) have different radii of curvature, a rounded mesh (Mi2) of said first flank (FG) having, in the same layer (i) of said winding, a radius of curvature (rmax) greater than that (rmin) of a corresponding rounded mesh (Mi4) of said second flank (FD), so as to faithfully model the spiral winding of one layer on the other.,

2. Method according to claim 1, characterized in that said thermal gradient calculation step (B3) comprises three-dimensional calculations in real time, from said thermal spatial distribution, to estimate and follow an evolution of one or more thermal gradients (GD) of said prismatic electrical storage cell (MP) in a three-dimensional space.

3. Method according to claim 1 or 2, characterized in that said step of estimating thermal spatial distribution (B2) comprises automatic consideration of physicochemical parameters and thermophysical characteristics (F2) of said layers.

4. Calculator (BMS) characterized in that it comprises a memory (MEM) storing program instructions (M0D_SW) for the implementation of the method according to any one of claims 1 to 0

5. 3. Assembly of an electric battery (BAT_HV) comprising a plurality of prismatic electric storage cells of the lithium-ion type (MP) and a computer, integrated in a vehicle (VE), characterized in that said computer is a computer (BMS) according to claim 4.

6. Assembly according to claim 5, integrated into an electrified vehicle (VE), characterized in that said electric battery is an electric traction battery (BAT_HV) of said electrified vehicle (VE).

7. Assembly according to claim 5 or 6, characterized in that said calculator is a battery management calculator of the so-called “BMS” type.

8. Vehicle (VE) characterized in that it comprises an assembly (BAT_HV, BMS) according to any one of claims 5 to 7.

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