Charging control method of rechargeable battery module by means of dynamic programming algorithm

Abstract

The invention relates to a charging control method for a rechargeable battery module, which is used in the field of motor vehicles, in particular for so-called ultra-fast recharging stations. The charging method judiciously implements a dynamic programming optimization algorithm to generate an optimal charging plan. To this end, the method comprises the following steps: determining (E01) a grid-like division of the charging range of the battery module, calculating (E02) the charging current between each point of the grid, calculating (E03, E04) a charging plan to reach each point of the grid, selecting (E05) the optimal charging plan to reach each point according to an optimization criterion, and then recording (E06) in a current setting value table the charging current that can reach each point according to each optimal plan.

Description

Technical Field

[0001] The field of the invention relates to a method for calculating a charge profile of a rechargeable battery system, in particular for charging electric vehicles. Background Art

[0002] Today, the range of electric vehicles is still relatively low compared to that of thermal vehicles. For longer trips, motor vehicle manufacturers seek to limit the range constraints and, for this purpose, aim to provide recharging solutions that can fully charge the battery during the twenty minutes of rest recommended every two hours of driving.

[0003] To this end, it is known to implement some constant charging current charging protocols. However, the constant current charging profiles provided so far are based on theoretical internal parameters of the battery system, which remain constant during charging and are valid for a predetermined initial state. However, in real driving situations, environmental conditions and vehicle conditions may differ from the theoretical conditions. These differences may damage the integrity of the battery and accelerate the aging of the battery.

[0004] As is known from the prior art, document EP2276139A2 provides a method for fast charging of a battery system, which alternates successive charging phases with constant direct current and constant voltage in order to increase the charging current and thereby reduce the charging time while avoiding degradation of the battery state. More precisely, the mathematical model of the battery comprises a functional component that is variable according to the state of charge and that is able to reduce the charging voltage in order to prevent lithium plating phenomena (generally denoted by the English term “LithiumPlating”).

[0005] An alternative strategy is described in document US2017 / 0267116A1, in which the charging control method takes into account the driver's driving habits in order to adapt the target charge level. More precisely, according to this solution, the regenerative braking phases pre-recorded in the memory during daily trips can be predicted to determine an optimized charging profile with the measure of adapting the recharging energy quantity according to the expected driving profile. In addition, thermal regulation of the battery system is performed in order to operate the recharging in optimal thermal conditions.

[0006] In addition, the so-called fast charging protocol, which is operated on a recharging station with an electrical power of 350 kW (ultra-fast charging station) and delivers a charging current of up to 400 A, causes premature aging of the battery cells, which is caused in particular by a temperature increase of the cells. The solution described above is designed to utilize the maximum current of the ultra-fast charging station and therefore disadvantageously causes accelerated aging of the battery system.

[0007] Furthermore, when fast charging is triggered under high temperature conditions, protection mechanisms limit the charging current, thus increasing the recharging time due to saturation. In particular, the charging methods known in the prior art do not take into account the initial conditions to achieve full charging in a satisfactory time. Summary of the invention

[0008] There is therefore a need to overcome the above problems. An object of the present invention is to provide an improved charging management method that is capable of adapting the charging profile according to the initial charging conditions to ensure that a predetermined recharge level is reached within a constrained duration. Another object of the present invention is to limit premature saturation during fast charging. Another object of the present invention is to provide a charging method that enables a user to manage the aging of the vehicle battery system caused by fast charging.

[0009] More specifically, the present invention relates to a method for charging a rechargeable battery module, the method comprising determining a charging plan and controlling a charging current setpoint according to the charging plan. According to the present invention, the method further comprises the following consecutive steps:

[0010] -a) recording in a memory the partitioning of the charging range of the battery module in the form of a grid, wherein the grid is a two-dimensional grid according to the temperature step and the charging evolution variable step,

[0011] -b) for each point of the grid, calculating a unit charging current value, each of the unit charging currents corresponding to a temperature state change of the battery module toward each adjacent point therein according to the charging evolution variable step size,

[0012] -c) for each so-called point, calculating at least one charging plan, said at least one charging plan defining a series of unit charging current values ​​from a predetermined initial point to each so-called point,

[0013] -d) calculating an optimization criterion for each charging plan, said optimization criterion being dependent on the temperature variation of the battery modules of said charging plan and said optimization criterion making it possible to select the best charging plan,

[0014] -e) for each point of the grid, selecting an optimal charging plan according to the optimization criterion, wherein the optimal charging plan defines a series of unit charging current values,

[0015] -f) for each point of the grid, recording the last unit charging current value in a series of values ​​of the optimal charging plan into a charging current setting value table,

[0016] - g) during charging of the battery module, determining the charging current setpoint by reading the table according to the instantaneous state of the battery module corresponding to each so-called point.

[0017] According to a variant, the selection of the optimal charging plan for each point e) is also based on an adjustment factor, which is an adjustment factor for adjusting the charging duration of the charging plan relative to the aging level of the battery module during the charging of the charging plan.

[0018] According to a variant, the adjustment factor depends on a charging counter which is activated in the event of detection of activation of a predetermined so-called fast-charging charging mode.

[0019] According to a variant, the control factor is also dependent on at least one state parameter of the battery module, which characterizes the aging of the battery module.

[0020] According to a variant, the regulation factor also depends on configurable parameters manually configurable by a user of the battery module, said configurable parameters making it possible to modify the duration of charging of the optimal plan selected and to modify the ageing grade.

[0021] According to a first embodiment, each point of the grid corresponds to a temperature value of the battery module and a state of charge value of the battery module, and the optimization criterion is a variable that characterizes the duration of the charging plan relative to a temperature variation of the charging plan.

[0022] According to a modification of the first embodiment, the current setting value table is a map that transmits the value of the current setting value according to the instantaneous temperature and the instantaneous state of charge of the battery module being charged.

[0023] According to a variation of the first embodiment, the optimal charging plan for each point of the grid is a reverse charging plan, wherein the initial point has a state of charge value between 70% and 100% state of charge of the battery module, preferably 80% state of charge.

[0024] According to a second embodiment of the method, each point of the grid corresponds to a temperature value of the battery module and a charging duration value of the battery module from the moment charging is triggered, and the optimization criterion is a variable that characterizes a change in the amount of energy of the charging plan relative to a change in the temperature of the charging plan.

[0025] According to a variation of the second embodiment, the current set value table is a set value vector that transmits the value of the current set value according to the instantaneous state of charge of the battery module being charged.

[0026] According to a variant, during the temperature state change of the battery module from each so-called point to the adjacent point, a unit charging current is calculated from each point to the adjacent point according to a predetermined electrical model of the battery module and according to the charging current limit imposed on the battery module. The unit charging current is constant with respect to the charging evolution variable step size, with respect to the state of charge step size according to the first embodiment or with respect to the charging duration step size according to the second embodiment.

[0027] According to a variant, the method comprises recording in a memory the optimization criteria of the optimal charging plan for each point of the grid, and the selection of the optimal charging plan for each point is based on the optimization criteria of the previous point of each so-called point of the optimal charging plan. The method thus reuses the optimization calculations that have been performed for the previous point of the grid.

[0028] The present invention also relates to a charging control computer for a battery module, the charging control computer comprising a computing module for implementing a so-called dynamic programming recursive algorithm, the computing module being configured to execute at least steps a) to f) of the charging method according to any one of the above-mentioned embodiments, so as to record a charging current setting value table into the memory of the computer, and being able to determine the charging current setting value by reading the table according to the instantaneous state of the battery module during charging of the battery module.

[0029] The invention also relates to a motor vehicle comprising a battery system equipped with such a charging management computer for a battery module of the battery system.

[0030] The present invention also relates to a motor vehicle including a battery system, wherein the battery system is equipped with a charging management computer for a battery module in the battery system, wherein the computer includes a memory (in which a mapping sent by a method according to any one of the variants of the first embodiment of the method is recorded), and includes a communication interface coupled to a recharging pile, and the computer is configured to send a charging current set value to the recharging pile by reading the mapping based on the instantaneous parameters of the state of charge and temperature of the battery system.

[0031] The present invention further relates to a computer program product comprising instructions, which, when executed by a battery system control unit, cause the battery system control unit to implement any embodiment of the method for charging a battery module according to the present invention.

[0032] Implementing a so-called dynamic programming optimization algorithm to determine the optimal charging profile has the advantage of being able to deliver a charging current setpoint value that is optimal in terms of charging duration constraints and / or acceptable aging constraints. In addition, the charging method adapts the charging current setpoint value according to the initial conditions of the temperature and state of charge of the battery module in order to operate the recharging of the battery module in the optimal duration to reach the target state of charge. Thanks to the charging method, the battery system judiciously manipulates the charging current setpoint value to prevent current saturation limiting phenomena caused by large temperature rises of the battery module. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Other characteristics and advantages of the invention will become more apparent on reading the detailed description which follows and the accompanying drawings, given as non-limiting examples, in which:

[0034] - Figure 1 A functional diagram of a rechargeable battery system according to the present invention is shown.

[0035] - Figure 2 A simplified functional diagram of a charging current control module is shown according to a first specific embodiment of the method (so-called offline calculation mode).

[0036] - Figure 3 A block diagram of a charging method for a battery module according to the present invention is shown, which charging method is capable of sending a charging current setting value determined according to a so-called dynamic programming optimization algorithm.

[0037] - Figure 4 A portion of a battery charging range grid during performance of a first embodiment of the method is schematically shown.

[0038] - Figure 5 An electrical model of the battery system is shown, which is implemented for calculating the charging current during the execution of the charging method according to the invention.

[0039] - Figure 6 A battery charging range grid is schematically shown, wherein a charging plan between an initial point and a final target point is shown, which is calculated according to a first embodiment of the charging method of the present invention.

[0040] - Figure 7 An example of a map of an optimal charging profile, which is calculated based on the first embodiment of the present invention, is schematically shown.

[0041] - Figure 8 is a graph showing the charge current manipulation and the temperature evolution of a battery system during a test phase implementing the charging method according to the invention.

[0042] - Fig. 9 A simplified functional diagram of a charging current control module according to a second specific embodiment of the method (so-called online calculation mode) is shown.

[0043] - Fig.10 A portion of a battery charging range grid during performance of a second embodiment of the method is schematically shown.

[0044] - Fig.11 The optimum charging current vector is schematically shown as a function of the battery system state of charge value. DETAILED DESCRIPTION

[0045] Figure 1 A battery system 10 is schematically described, which is equipped with a battery module consisting of one battery cell or a plurality of battery cells. The system is specifically configured for implementing the charging method according to the invention. Here, the invention is described as an example for the application of a rechargeable electric motor vehicle. Of course, the invention is applicable to any type of industrial application including a rechargeable battery system that can be recharged at a recharging station.

[0046] Typically, in the examples described here, the vehicle comprises a battery system comprising a battery module equipped with a plurality of electrical units, for example using lithium-ion technology, which are electrically connected in a series architecture and / or in a parallel architecture by means of one or more battery subsystems. The method is advantageously applied to power battery systems that can receive a charging voltage (between 200 V and 500 V, or even up to 1000 V), in particular to charging represented by "fast charging" in this specification. However, it is noted that the method does not exclude application to the charging of a single battery unit.

[0047] The battery system 10 comprises a control unit 12 of the computer type with integrated circuits, usually denoted BMS (i.e., "Battery Management System"), which comprises a recharging interface for cooperating with a recharging post 13 that is outside the vehicle and connected to the electrical network. For example, the recharging post 13 is designed to operate according to a compatible recharging voltage with standardized power levels (FC10, FC20, FC50, HPC150, HPC250, HPC350) ranging from 10 kW to more than 350 kW. More precisely, the recharging interface of the battery system 10 of the vehicle is designed to operate at an electrical voltage of at least between 200 V and 1000 V and can withstand a maximum electrical current of about 500 A. The recharging interface is compatible, for example, with the standard DIN SPEC 70121 (relating to electromobility - digital communication between a DC recharging station and an electric vehicle for regulating DC charging in a combined charging system) and the standard ISO 15118 (relating to road vehicles - communication interface between vehicle and electrical network).

[0048] As described above, the invention proposes implementing a charging method capable of delivering a charging current setpoint CCR based on an optimal charging profile obtained by an optimization algorithm, such as a dynamic programming optimization algorithm (the acronym DP, usually expressed in English as "Dynamic Programming Algorithm Optimization"). The optimization algorithm DP is capable of determining the charging current that is optimal in terms of one or more imposed optimization criteria. The optimization criteria are, for example, the charging duration, the amount of energy to be charged in a determined duration or the aging of the battery module during charging.

[0049] This implementation can be implemented to control the charging current by means of a calculation module 11, which is configured to send a charging current setpoint CCR at least according to an instantaneous state parameter PT of the battery module being charged, which instantaneous state parameter is sent by the control unit 12. Of course, other inherent operating parameters of the vehicle can be taken into account, such as the thermal regulation capability of the battery system.

[0050] The calculation module 11 can be installed in the battery system 10 by means of a computer dedicated to calculating the charging current set value CCR, and cooperates with the control unit 12, such as Figure 1As shown above. However, this embodiment is not necessary. It is conceivable that the functions implemented by the calculation module 11 are integrated with the BMS control unit 12, or are further located outside the battery system 10, for example, in the control unit of the vehicle. In the case of a hybrid vehicle, the control unit is, for example, the thermal engine computer, traction motor computer or monitoring computer of the vehicle. In the latter embodiments, the current set value CCR is sent directly to the recharging pile 13 without the need for a gateway (via the control unit 12 of the BMS). Therefore, according to the present invention, the calculation module 11 can be implemented in the form of a software module (or information (or "software")), or in the form of an electronic circuit (or "hardware"), or in the form of a combination of an electronic circuit and a software module.

[0051] Now, Figure 2 More precisely, a functional block 600 is described for implementing the functions implemented by the calculation module 11 in order to operate a first embodiment of the charging method according to the invention (so-called offline calculation mode). According to this calculation mode, a charging profile is recorded in the memory of a computer in the form of a table, a matrix or a map, the optimal charging current value of which is calculated independently of the charging trigger and independently of the initial conditions of the battery module at the time of charging. For example, the method provides that the optimal charging profile can be calculated by the calculation module 11 on request (in a manner loaded by the on-board calculation module 11) (at any time during the vehicle's service life in the factory during vehicle manufacturing or after sales).

[0052] It is also not excluded that the optimal distribution can be determined by a remote computing module accessible via a communication interface (e.g. a vehicle after-sales management center, a factory, an online management platform, or even a dealer). The last case has the advantage that it avoids having computing resources loaded in the vehicle to implement the optimization algorithm DP. Therefore, all or part of the steps of the method are designed to be operated by a computing module of the vehicle or in cooperation with a computing module outside the vehicle.

[0053] More precisely, the input of the functional block 600 receives data marked 605 to 612 sent by the battery system of the vehicle. The block 600 comprises a first functional block 601 which operates a fast charge counter function performed by the battery system. The block 601 counts the number of fast charges performed by the battery system during the useful life of the battery system. The counting performed according to the counter value enables the estimation of the degree of battery cell aging caused by electrical activities related to fast charging, in particular temperature rise and high charging currents.

[0054] The functional block 600 also comprises a second functional block 602 for sending an adjustment factor 613 for adjusting the charging duration relative to the aging level suffered by the battery module being charged, the adjustment being carried out in particular according to the information sent by the fast charging counter 601, according to a configurable parameter 606 which can be manually configured by a user of the battery system (via a human-machine interface, such as the dashboard of the vehicle) (the configurable parameter enables the charging duration to be modified and the aging level suffered by the battery system during recharging), according to one or more parameters 609, 610 characterizing the aging state of the battery system (for example, data 609 relating to the internal resistance of the single components of the battery system and / or data 610 relating to the full charge capacity of the battery system). The aging level is understood to be the degradation suffered by the single components of the battery system during the execution of a fast charge, degradation caused by high charging currents and sudden temperature rises. The aging state parameters are determined by analysis and diagnostic functions known to those skilled in the art and loaded in the control unit of the BMS system.

[0055] For example, the adjustment factor is configurable in a value range between 0 and 1, a value of 1 optimizes the charging time, a value of 0 reduces the aging level (in exchange, longer charging time), and intermediate values ​​manipulate the trade-off between charging time and aging level. As will be seen later in this specification, the adjustment factor 613 defines which charging plan will be selected after calculating all possible charging plans according to the value of the optimization criterion for each charging plan. This factor does not directly affect the calculation of the unit charging current.

[0056] The block 600 also includes a third functional block 603, the function of which is to send an instantaneous state of charge SOC value 614 and an instantaneous temperature value 615 of the battery system according to the data 607, 608 received as input quantities of each unit constituting the battery system. In particular, the optimal charging current is limited by the unit with the highest state of charge SOC, by the unit with the maximized temperature, and by the unit with the minimized temperature.

[0057] Finally, block 600 also includes a fourth functional block 604, the function of which is to send an optimal charging current setting value CCR according to the charging method according to the invention. To this end, the input end of block 604 receives a regulation coefficient value 613, a state of charge SOC value 614 and a unit temperature value 615, a battery system aging state value 609, 610, and data 611 related to the maximum charging current that can be sent by the recharging station and data related to the water temperature (this data is, for example, a fixed variable).

[0058] In a preferred variant of the first embodiment, block 604 comprises a mapping in the form of a table of current setpoints CCR, recorded in the memory of the battery system control unit, to send the value of the current setpoint as a function of the temperature 614 and the instantaneous state of charge 615 selected by block 603. More precisely, a mapping is established by block 604, by operating all the calculation steps in a manner loaded in the vehicle, or by operating all the calculation steps by an external calculation module, so as to avoid having specific calculation resources specific to the implementation of the algorithm DP integrated in the battery system, as described above.

[0059] In addition, the first and second blocks 601, 602 are not indispensable. The first and second blocks are advantageously capable of adjusting the charging current setpoint value according to the aging level and / or according to configuration parameters determined by the user, so as to adapt the charging duration according to the impact of the fast charging. However, in a simplified variant, it is conceivable that the charging method sends an optimal setpoint value CCR without taking into account the aging.

[0060] exist Figure 3 Having said that, the algorithm of the method is now described, which is used to carry out a first embodiment of the charging method (the so-called offline mode). In a first step E01, the charging method comprises a first recording step for recording in the memory of the BMS control unit a discretization of the division of the charging range of the battery module in the form of a grid, the grid being a two-dimensional grid according to temperature steps and charge evolution variable steps. In this first embodiment, the charge evolution variable of the battery module used in the grid is the state of charge of the battery module. The temperature step and the state of charge step are constant over the entire charging range.

[0061] However, it is not excluded that the step size is variable in order to obtain a finer charging current control accuracy for a specific charging area.

[0062] The grid has the advantage of dividing the large charging range of the battery system into a plurality of small meshes, for each of which the optimal charging current is calculated. Each mesh defines the temperature variation of the battery module being charged between two temperature values ​​relative to the state of charge variation between two state of charge SOC values. The mesh is bounded by the points of the grid, each of which is associated with a temperature value and a state of charge SOC value. The variation can be represented by the terms "fineness", "resolution" or "grid step". Next, based on the optimization algorithm DP and the optimal current value in terms of a predetermined optimization criterion, the method selects the optimal charging plan for the entire charging range.

[0063] exist Figure 4, a portion of a grid 100 is schematically and simplified, wherein state of charge SOC values ​​are displayed on the abscissa axis and temperature T values ​​are displayed on the ordinate axis. Each point Mi,j is associated with a temperature range of a battery module being charged and a state of charge range of said battery module. The grid covers a charging range of the battery module, which is defined, for example, between temperatures between 25° and 45° and between states of charge SOC between 5% and 90% of the total capacity of the battery system. Other charging ranges are conceivable depending on the needs sought, typically a state of charge range spread between 10% and 80% of the total system capacity is sufficient to cover the range requirements of the vehicle.

[0064] The grid step size may be a few tenths of a degree Celsius, for example between 0.5 and 1 degrees Celsius, and on the state of charge SOC axis a few tenths of a state of charge SOC percentage, for example between 0.5% state of charge and 5% state of charge. It is understood that the selected resolution of the grid is not limiting at all and depends, among other things, on the performance sought and the available computing and storage resources, especially when the optimization calculations are loaded in the vehicle.

[0065] Next, in the second step E02 of the charging method, Figure 4 As shown, the method includes calculating unit charging current values ​​I1, I2, and I3 for each point Mi,j, and each of the unit charging current values ​​is associated with the temperature state change of the battery module to each adjacent point Mi-1,j; Mi-1,j-1; Mi-1,j-3 adjacent to point Mi,j according to the charge state step.

[0066] More precisely, for a change in state of one or more cells with respect to temperature, the unit charging current value I1 , I2 , I3 is constant over the state of charge step of said grid.

[0067] To simplify, Figure 4 Only the calculation for the unit current values ​​I1 to I9 constituting the three charging plans PC1, PC2, PC3 between the initial point Mi,j and the target point Mi-3,j-3 is shown. However, embodiments of the calculation method are implemented for all neighboring points or for a selected part of the neighboring points.

[0068] According to the optimization algorithm DP, the calculation of the unit charging current (for example I1 to I9) is repeated from the initial point Mi,j to the predetermined final target point Mm,n. For this first embodiment, the transition from one calculation cycle to another is implemented step by step on the change in the state of charge SOC of the grid.

[0069] In addition, according to the first embodiment (so-called offline mode), if Figure 4 As can be seen above, it is noted that the point-by-point repetitive calculation cycle of the unit charging currents I1 to I9 occurs according to a path that is reversed relative to the charge variations and temperature variations that usually occur during the charging of the battery system (usually expressed as a "backward" calculation of the DP algorithm in English). In fact, according to the execution of the optimization pursuit of the recursive optimization algorithm DP, the calculation of the unit charging current is carried out (accompanied by the decreasing charge variation and temperature variation). Therefore, the initial point has a state of charge value between 70% and 100% of the state of charge of the battery system, preferably 80%. The predetermined final target point Mm,n has a state of charge value between 0% and 20% of the state of charge of the battery, preferably 5%.

[0070] The calculation of the unit currents I1, I2, and I3 is performed based on the electrical model of the battery system and the electrical constraints of the system. Figure 5 In FIG. 1 , an n-order Foster electrical model that can be used as an example is shown. In addition, the imposed electrical constraints for limiting the unit current value are, in particular, the acceptable temperature, the acceptable maximum current, the maximum voltage, and the power value of the recharging post. These data are received as input information to operate as follows Figure 2 Note that, in general, the acceptable maximum current is constrained by the maximum current value of the unit (which depends on the state of charge SOC of the battery system) and by the maximum current value of the charging pile (e.g., 400A on a 350kW charging pile). One or the other of the latter two values ​​imposes a maximum limit.

[0071] refer to Figure 4 , it is stipulated that the unit charging current I1 corresponds to a constant charging current so that the state of the battery system can change from a point Mi,j (associated with a temperature state j and a state of charge SOCi) to an adjacent point Mi-1,j (associated with a temperature state j having the same value but associated with a state of charge SOC having a low value i-1 according to a grid resolution). The unit charging current I2 corresponds to a constant charging current so that the state of the battery system can change from a point Mi,j (associated with a temperature state j and a state of charge SOCi) to an adjacent point Mi-1,j-1 (associated with a temperature state having a low value j-1 according to a grid resolution and a state of charge SOC having a low value i-1).

[0072] The unit charging current value is calculated by means of the following two equations providing a quadratic equation whose solution can obtain a charging current that allows conversion from one point to an adjacent point. The temperature change amount and the SOC change amount depend on the number of meshes corresponding to the state change of the battery module.

[0073] -M.cp.dTbat / dt=Ri 2 +hs(Teau-Tbat),

[0074] - and, dSOC / dt = I / C,

[0075] Where dSOC / dt is the change in the state of charge of the mesh, M is the mass of the battery system, Cp is the heat capacity, dTbat / dt is the temperature change from one point to an adjacent point, R is the resistance of the battery system, which is a function of the state of charge and the instantaneous temperature, i is the unit charging current, HS is the heat exchange coefficient multiplied by the exchange cross section, Tbat is the instantaneous temperature of the battery system, and Teau is a fixed variable (e.g. 30°C).

[0076] Based on the value of the unit charging current for switching from one point to an adjacent point, the method determines a unit duration to operate the charge variation under the action of the unit charging current when switching from one point to another. This unit duration will be subsequently used to calculate the value of the optimization criterion of the charging plan to reach the target point.

[0077] Next, in a third step E03 of the charging method, the method comprises determining a charging plan PCn defining a series of unit charging current values ​​with constant values ​​in order to be able to reach the target point from the initial point through a plurality of intermediate meshes.

[0078] refer to Figure 4 The initial point Mi,j and the target point Mi-3,j-3 mentioned are the points of repeated calculation cycles, which limit the changes in the state of charge SOC of multiple charging plans. The charging plans PC1, PC2, and PC3 between points Mi,j and Mi-3,j-3 are composed of current setting values ​​[I1, I4, I7], [I2, I5, I8], and [I3, I6, I9] respectively.

[0079] Next, in a fourth step E04, the method comprises calculating for each charging plan PCn an optimization criterion COPn, the optimization criterion depending on the variation of the temperature T and the variation of the state of charge SOC of the charging plan, and the optimization criterion enabling the selection of the best charging plan. In this first offline embodiment, the optimization criterion is the duration of the charging plan. The charging duration is not a necessary criterion. It can be seen that for the second embodiment, the optimization criterion is the variable of the SOC charging variation. Furthermore, it is noted that the calculation of the optimization criterion is performed for each calculation cycle of the optimization algorithm DP, as long as the predetermined final target point Mm,n is not reached.

[0080] refer to Figure 4 , note that PC1 and PC3 have both charging plans where the temperature variation is stagnant over a portion of the charging plan (I1 for PC1, I6, I9 for PC3). This therefore indicates that the charging durations COP1, COP3 (for PC1 and PC3, respectively) may be too high, while PC2 shows a constant temperature variation with an equal SOC charging variation. A weak or zero temperature variation over a section of the charging plan may indicate saturation of the charging current and therefore a high duration.

[0081] Next, for each target point, the method comprises a fifth step E05 for selecting the optimal charging plan according to the optimization criterion COPn for each charging plan PCn. To this end, the method compares the charging duration of each charging plan and selects the charging plan with the minimum duration. Figure 4 , assuming that the charging plan PC2 has a lower charging duration COP2 than the plans PC1 and PC3. The method thus selects the plan PC2 considered as the optimal plan by taking into account the optimization criterion of the charging duration to reach the target point Mi-3,j-3 from the initial point Mi,j.

[0082] Again, it is noted that, for each calculation cycle of the optimization algorithm DP, steps E01 to E05 are repeatedly performed step by step according to the grid (with a decreasing state of charge variation), as long as the predetermined final target point Mm,n is not reached. In a preferred variant of the first embodiment, the initial point may be one of the points associated with a state of charge SOC of the battery module (for example 80%), and the final target point may be one of the points associated with a state of charge SOC of 5%.

[0083] refer to Figure 6, wherein a grid 100 between an initial point Mi,j (e.g. for a state of charge SOC of 80% and 45 degrees Celsius) and a final target point Mm,n (e.g. for a SOC of 5% and 25 degrees Celsius) is schematically shown in a simplified manner for a better understanding. The method is shown in this figure at the last calculation cycle, wherein three charging plans 101, 102, 103 are shown. Here, plan 102 is the optimal plan with the minimum charging duration. In this embodiment, the initial point is preferably selected with a maximized state of charge and with a maximized limit on the battery module temperature in order to allow the highest current value allowed by the battery module. Other values ​​are also conceivable.

[0084] Furthermore, according to an embodiment of the optimization algorithm DP, for each point of the grid, the method comprises recording in the memory of the BMS control unit the optimization criterion of the optimal charging plan, here the optimization criterion being the duration of the charging plan according to the first embodiment. Then, the method comprises selecting the optimal charging plan between the initial point Mi,j and the predetermined final target point Mm,n according to the optimization criterion of each intermediate point (of the charging plan integrating the final target point Mm,n). In this way, the method saves computing resources by reusing the value of the optimization criterion of each intermediate calculation cycle (already calculated before reaching the final cycle).

[0085] Next, once the final target point Mm,n of the grid is reached, the method comprises a recording step E06 for recording in the memory of the BMS system control unit a table of charging current setpoints, the table storing, for each point, the last value of a series of unit charging currents capable of reaching the optimal charging plan for each so-called point. In this first embodiment of off-line calculation, the setpoint table is a mapping for sending charging current setpoints CCR as a function of the instantaneous values ​​of the state of charge SOC and the temperature.

[0086] Still reference Figure 4 , where the target point is point Mi-3,j-3, for which the optimal plan selected is plan PC2, because this plan has the minimum duration to experience the charging change defined by the plan in the acceptable temperature range. Thus, for point Mi-3,j-3, the unit charging current recorded in the set value table is the unit charging current value I8. Note that in the case of this example, point Mi-3,j-3 is an intermediate point between the initial point Mi,j and the predetermined final target point.

[0087] Finally, for all (or some) of the points of the grid 100, the current setpoint table records the last value in a series of unit charging currents that can achieve the optimal schedule for these so-called points.

[0088] If the mapping is determined (e.g. in the factory) by a computer located outside the vehicle, the table is recorded in the configuration platform of the battery system and subsequently configured in the memory of the BMS control unit during vehicle manufacturing. The mapping can be updated during the service life of the vehicle, either by the vehicle when it is loaded with a program configured to implement the entire charging method, or by an update module.

[0089] exist Figure 7 , an example of a mapping 300 is schematically shown, which is capable of sending an optimal charging current setting value, which is recorded in the memory of the vehicle battery system. The mapping indexes the state of charge SOC range and the temperature T range, here, for example, from 0% to 100% SOC, from 25°C to 45°C temperature. The mapping sends the charging current value CCR according to the instantaneous value of the state of charge SOC and the temperature T of the vehicle battery system. The fineness of the mapping 300 is directly related to the fineness of the grid 100.

[0090] To simplify the calculation of the mapping, it is conceivable that the table cells may contain default values, for example over the entire row or the entire column. In fact, it is conceivable that the range of SOC values ​​and temperature values ​​is configured by a single optimal unit charging current value, regardless of the battery's aging state or the optimization criterion.

[0091] It is noted that steps E01 to E06 are performed before charging is triggered, either in the factory before being put into service, or during the service life of the vehicle. Once the vehicle is led to a recharging post, information is communicated between the vehicle and the post, in particular compatible charging currents. Once recharging is triggered, the charging method comprises determining E07 a charging current setpoint CCR by reading a mapping according to instantaneous values ​​of state of charge SOC and temperature sent by the battery system BMS. This charging current setpoint CCR is then transmitted to the post in real time according to the instantaneous values ​​of state of charge SOC and temperature of the battery system.

[0092] Furthermore, according to a preferred variant of the method, during step E05, the selection of the optimal charging plan between the initial point and the predetermined final target point Mm,n is based on an adjustment coefficient 613, which is Figure 2 Based on the value of the optimization criterion COPn, the method selects a charging plan whose duration is a function of the value of an adjustment factor used to configure a compromise between the charging duration and the aging level suffered.

[0093] According to the method, the adjustment coefficient value 613 evolves in proportion to the increment of the fast charge counter 601 so as to reduce the aging level as the counted number of fast charges increases. In a variant of the method, the adjustment coefficient value 613 evolves in proportion to the aging state parameter values ​​609, 610 so as to reduce the aging level as the battery system state degrades.

[0094] In order to illustrate the implementation test of the charging method according to the present invention, Figure 8 In the figure, two graphs are shown which illustrate a sequence of manipulations for the charging current. In the upper part, the charging current setpoint CCR transmitted to the recharging post during the recharging process is shown. The value Imax represents the maximum current limit value allowed according to the instantaneous conditions. In the lower part, the temperature evolution of the battery system during the same recharging process is shown. These graphs confirm that the current constraints and temperature constraints are observed. It has been found that the value of the charging current is adapted according to the initial recharging condition values ​​in terms of temperature and state of charge SOC.

[0095] Furthermore, by modifying the value of the regulation factor, the tests have shown that the charging method can increase the service life of the battery system, in particular by increasing the acceptance of fast charging quantities.

[0096] Fig. 9 A second embodiment of the functional block 600 for implementing the charging method is now described, in which all steps are performed when a charging operation of the vehicle is triggered. This second mode is represented as an "online" calculation mode. The calculation of the method for sending the table of charging current setpoints therefore depends on the initial conditions of the battery system at the moment of recharging in terms of temperature, state of charge SOC and state of aging, and aims at providing the optimal charging current setpoint only for the current recharging operation.

[0097] The second embodiment Figure 2 The difference is that this second embodiment firstly comprises a functional block 701, the function of which is to send a table of charging current set values ​​CCR, which this time depends only on the instantaneous value of the state of charge SOC of the battery system. Once the charging is triggered, the calculation must be carried out and the count can optionally be updated during charging. Several major differences from the first embodiment should be pointed out. This calculation mode avoids recording a charging profile map (which is intended to respond to all recharging situations that the vehicle may encounter), but in exchange, the vehicle needs to integrate the computing resources required for the execution of the optimization algorithm DP.

[0098] In this second embodiment, the module 600 comprises a fifth functional block 702 for planning recharging, the function of which is to activate the calculation of a table of charging current setpoints.

[0099] The module 600 further includes a sixth functional block 703 , the function of which is to read the charging current setting value table according to the instantaneous value of the state of charge SOC of the battery system.

[0100] Figure 3 A flow chart of the method according to this second embodiment can also be shown. During step E01, the functional block 701 records in the memory of the BMS control unit a discretized division of the charging range of the battery system in the form of a second grid, the second grid being a two-dimensional grid according to the temperature step and the charging evolution variable step. In this second embodiment, the evolution variable characterizes the charging duration after the triggering moment of recharging. The triggering moment is the planned start moment of the application of the charging current on the charging pile of the battery system. The mesh defines the temperature variation of the battery module being charged between two temperature values, and defines the charging duration variation between two charging moments after the triggering moment.

[0101] exist Fig.10 , a portion of a second grid 200 is schematically shown in a simplified manner, wherein the charging duration t value is shown on the abscissa axis and the temperature T value is shown on the ordinate axis. Each point Mi,j is associated with a temperature value and a duration value of the battery module being charged. The second grid 200 covers the temperature charging range of the battery module, which is defined, for example, between a temperature between 25° and 45° and a charging duration, for example, for fast charging, the charging duration may be about 20 minutes. The value of the charging duration defined by the grid 200 does not limit the present invention at all.

[0102] The step size of the grid on the temperature axis may be a few tenths of a degree Celsius, for example between 0.5 and 1 degree Celsius, and the grid on the time axis may be of the order of seconds or minutes. It is understood that the chosen resolution of the grid is not at all limiting and depends inter alia on the performance sought and the computing and storage resources available in the vehicle.

[0103] During step E02, the calculation of the unit charging current is performed identically to the first embodiment (for the equations, the electrical model used and the electrical constraints imposed), said unit charging current having a constant value over the charging duration step of the grid, with the difference that, for the planned moment of triggering the charging, a point-by-point transition is initiated at an initial point associated with the instantaneous value of the temperature of the battery system, the predetermined final target point Mm,n having a charging duration value from a few seconds to tens of minutes (preferably a charging duration value of about twenty minutes) and corresponding to a planned state of charge of the battery modules between 80% and 90% (in the case of a full recharging of the battery system, so-called fast charging). Of course, the method can also be applied to incomplete charging with a short duration.

[0104] As in the first embodiment, the optimization algorithm is a dynamic programming algorithm DP. The algorithm is recursive and is performed mesh by mesh for repeated calculation cycles (this time in the ascending direction of charging with respect to temperature and charging duration). Note that the transition from one calculation cycle to another is implemented step by step, with the duration variation defined by the grid.

[0105] refer to Fig.10 ,It is observed that the charging plan from point Mi,j to point Mi+3,j+3 increases this time in terms of temperature and duration. Fig.10 Only the calculation for the unit current values ​​I1 to I9 constituting the three charging plans PC1, PC2, PC3 between the initial point Mi,j and the target point Mi-3,j-3 is shown. However, embodiments of the calculation method are implemented for all neighboring points or for a selected part of the neighboring points.

[0106] In this second embodiment, the method also comprises a determination step E03 for determining a charging plan PCn defining a series of unit charging current values ​​to be able to reach each target point from the initial point through a plurality of intermediate meshes.

[0107] Next, in a fourth step E04, according to this second embodiment, the method comprises calculating the optimization criterion COPn for each charging plan PCn, wherein the optimization criterion is the amount of recharged energy planned for the charging duration defined by the initial point and the target point and the variation of the temperature. The planned energy variation or the planned state of charge of the charging plan (for the planned charging duration) is recorded in the memory of the battery system BMS in order to establish a table of charging current setpoints.

[0108] Next, for each point, during a fifth step E05, the functional block 701 selects the optimal charging plan for said point according to the amount of recharged energy of each charging plan PCn. The optimal plan will be the one with the greatest increase in the state of charge.

[0109] As in the first embodiment, the selection of the optimal plan may optionally depend on an adjustment factor 613, thereby being able to favor the amount of charged energy in the duration defined by the charging plan of the grid at the expense of the aging level suffered by the battery system, or to reduce the effect of the recharging on the aging level at the expense of the amount of energy and therefore the overall charging duration. The adjustment factor may also depend on the fast charge counter, one or more aging state parameters of the battery module, or a configurable parameter that can be manually configured by the user (to favor the charging duration or the aging level suffered during recharging).

[0110] Next, once a predetermined final target point Mm,n of the grid is reached (for example a point of the grid corresponding to a planned state of charge of approximately 80% of the battery modules), in a step E06, the battery system BMS control unit records a table of charging current setpoints in a memory of the BMS, the table storing for each point the last value of the unit charging current (as part of the optimal charging plan for each point) and the value of the planned energy variation set for recharging for the charging duration. The predetermined final target point Mm,n has, for example, a charging duration value of between 15 and 25 minutes, preferably of the order of 20 minutes when the charging involves a complete recharging of the battery modules.

[0111] In this second embodiment, the set value table is an optimum charging current vector that sends a charging current set value CCR according to the value of the planned energy variation from the time when recharging is triggered, relative to the initial state of charge SOC level.

[0112] As Fig.11 As shown schematically, functional block 701 transmits a vector 400 of charging current CCR to block 703, the function of which is to transmit a charging current value CCR to a recharging post during recharging E07 according to the energy variation measured from the triggering of said recharging or according to the instantaneous state of charge SOC of said battery system. This vector 400 is calculated from the triggering of said recharging and can be updated during the charging operation.

Claims

1. A method for charging a rechargeable battery module, the method comprising determining a charging plan and controlling a charging current setting value according to the charging plan, characterized in that: The charging method further comprises the following consecutive steps: a) recording ( E01 ) in a memory the partitioning of the charging range of the rechargeable battery module in the form of a grid, the grid being a two-dimensional grid according to the temperature step and the charge evolution variable step, -b) for each point of the grid, calculating (E02) a unit charging current value (I1-I3), each of the unit charging current values ​​corresponding to a change in the temperature state of the rechargeable battery module toward each adjacent point (Mi-1,j; Mi-1,j-1; Mi-1,j-3) therein according to the charging evolution variable step size, -c) for each so-called point, calculating (E03) at least one charging plan (PC1, PC2, PC3), said at least one charging plan defining a sequence of unit charging current values ​​from a predetermined initial point (Mi,j) to each so-called point, -d) calculating (E04) an optimization criterion for each charging plan (PC1, PC2, PC3), said optimization criterion being dependent on the temperature variation of the rechargeable battery modules of said charging plan and said optimization criterion enabling the selection of the optimal charging plan, -e) for each point of the grid, selecting (E05) an optimal charging plan (PC2) according to the optimization criterion, the optimal charging plan defining a series of unit charging current values ​​(I2, I5, I8), -f) for each point of the grid, recording (E06) the last unit charging current value (I8) in a series of unit charging current values ​​of the optimal charging plan (PC2) into the charging current setting value table (300), -g) during charging of the rechargeable battery module, determining (E07) the charging current set value by reading the charging current set value table according to the instantaneous state of the rechargeable battery module corresponding to each so-called point.

2. The charging method according to claim 1, characterized in that: The selection of the optimal charging plan for each point e) is also based on an adjustment factor (613), which is an adjustment factor for adjusting the charging duration of the charging plan relative to the aging level of the rechargeable battery module during the charging period of the charging plan.

3. The charging method according to claim 2, characterized in that: The adjustment factor (613) depends on a charging counter (601) which is activated when the activation of a predetermined so-called fast charging mode is detected.

4. The charging method according to claim 2 or 3, characterized in that: The adjustment factor (613) also depends on at least one state parameter (609; 610) of the rechargeable battery module, the at least one state parameter characterizing the aging of the rechargeable battery module.

5. The charging method according to claim 2 or 3, characterized in that: The adjustment factor (613) also depends on configurable parameters (606) that can be manually configured by a user of the rechargeable battery module, which configurable parameters enable the charging duration of the selected optimal plan to be modified and the aging level to be modified.

6. The charging method according to any one of claims 1 to 3, characterized in that: Each point of the grid corresponds to a temperature (T) value of the rechargeable battery module and a state of charge (SOC) value of the rechargeable battery module, and the optimization criterion is a variable that characterizes a charging duration of the charging plan relative to a temperature variation of the charging plan.

7. The charging method according to claim 6, characterized in that: The charging current setting value table is a map (300) that transmits the value of the charging current setting value (CCR) according to the instantaneous temperature (T) and the instantaneous state of charge (SOC) of the rechargeable battery module being charged.

8. The charging method according to claim 6, characterized in that: The optimal charging plan for each point of the grid is a reverse charging plan, wherein the initial point (Mi,j) has a state of charge value between 70% and 100% state of charge of the rechargeable battery module.

9. The charging method according to claim 8, characterized in that: The initial point (Mi,j) has a state of charge value of 80% of the state of charge of the rechargeable battery module.

10. The charging method according to any one of claims 1 to 3, characterized in that: Each point of the grid corresponds to a temperature (T) value of the rechargeable battery module and a charging time (t) value of the rechargeable battery module from the moment charging is triggered, and the optimization criterion is a variable that characterizes a change in the amount of energy of the charging plan relative to a change in temperature of the charging plan.

11. The charging method according to claim 10, characterized in that: The charging current set value table is a set value vector (400) that sends the value of the charging current set value (CCR) according to the instantaneous state of charge (SOC) of the rechargeable battery module being charged.

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