ACCURATE ESTIMATION OF A MINIMUM STATE OF CHARGE OF A CELLULAR BATTERY

Abstract

A method is implemented in a system comprising a cellular battery having an estimated current internal resistance and an estimated current state of charge. This method comprises a step (10) in which a minimum state of charge that the cellular battery must have at the end of a predefined discharge cycle is estimated, based on information representative of this estimated current internal resistance, and a maximum power that the cellular battery must be capable of delivering at the end of the predefined discharge cycle. Figure 3

Description

Title of the invention: ACCURATE ESTIMATION OF A MINIMUM STATE OF CHARGE OF A CELLULAR BATTERY Technical field of the invention

[0001] The invention relates to cellular batteries, and more precisely to the estimation of the minimum state of charge of such batteries. State of the art

[0002] Cellular batteries are used in many systems to store electrical energy intended to power at least one electrical machine (possibly a motor) and / or an electrical power supply circuit. This is the case, for example, although not limited to, in vehicles (possibly of the automobile type).

[0003] Some of these cellular batteries comprise electrical energy storage cells, possibly electrochemical (for example of the lithium-ion (or Li-ion) or Ni-Mh or Ni-Cd type). It will be noted that in the case of a vehicle, the cellular battery may be a so-called "main" (or "traction" or even "power") battery because it is responsible for supplying electrical current to an on-board network, via a converter, and to an electric motor of the powertrain (or GMP), or a so-called "service" battery because it is of the very low voltage type (typically between 12 V and 48 V) and responsible for supplying electrical current to the on-board network in the absence of a main battery (and therefore an electric motor) or instead of or in addition to the main battery.

[0004] In the following and the preceding, the term "on-board network" means an electrical supply network to which electrical (or electronic) equipment (or components) consuming electrical energy are coupled.

[0005] As is known to those skilled in the art, cellular batteries are subject to management of certain of their parameters in order to be able to be used optimally, with a minimized risk of failure and incident, for example for the safety and peace of mind of users of the systems. For example, this management can allow diagnostics to be carried out intended to optimize the use and the lifespan of the cellular battery, to reduce repair costs and to anticipate a major malfunction.

[0006] Among the parameters managed, we can notably cite the total energy available in the cellular battery (or UBE (“Useful Battery Energy”)) and its derivatives such as for example the energy health state of the cellular battery (or SOHE (“State Of Health of Energy”) - also called certified energy state (or SOCE (“State Of Certified Energy"))). It is recalled that these derivatives are, for example and in particular, used to estimate the mileage range of a vehicle as precisely as possible so as not to overestimate or underestimate performance.

[0007] It has been proposed, in particular in patent document FR-A1 3130039, to estimate the information representative of the total energy available in the cellular battery as a function of the current states of charge (SOH (“State Of Health”)), current resistive health states (or SOHR (“State Of Health of Resistance”)), current capacity health states (or SOHC (“State Of Health of Capacity”)), and a time interval during which the cellular battery is allowed to discharge under a chosen discharge current and at a reference temperature. It is recalled that the current resistive health state (or SOHR) of a cell increases with aging and therefore its impact on energy dissipation increases.

[0008] The method of estimating the information representative of the total energy available in the cellular battery, presented above, offers fairly good results. However, the developments of certain national or international standards require that the level of precision on the total energy available in the cellular battery (or UBE) and its derivative (energy state of health (or SOHE) or certified energy state (or SOCE)) be ever greater. It is recalled that this level of precision is determined by comparing the total energy available measured with the total energy available estimated during a predefined discharge cycle, for example of the WLTP type (“Worldwide harmonized Light vehicles Test Procedure”).

[0009] Currently, the aforementioned estimation method does not allow a high level of precision to be achieved. This results in particular from the fact that it does not take into consideration the minimum state of charge that the cellular battery must have at the end of a predefined discharge cycle. Indeed, currently the calculation of the total energy available in the cellular battery (or UBE) does not adapt in real use the level of the minimum state of charge to satisfy a given power level at the end of a predefined discharge cycle, even though this level can vary dynamically in the life cycle of the vehicle.

[0010] The invention therefore aims in particular to improve the situation. Presentation of the invention

[0011] For this purpose, it proposes in particular an estimation method intended to be implemented in a system comprising a cellular battery having an internal resistance currently estimated and a state of charge currently estimated.

[0012] This estimation method is characterized by the fact that it comprises a step in which a minimum state of charge that the cellular battery must have at the end of a predefined discharge cycle, based on information representative of the estimated internal resistance in progress, and a maximum power that the cellular battery must be capable of delivering at the end of this predefined discharge cycle.

[0013] Thanks to this estimation of the minimum state of charge, it is now possible to estimate in the system, in a very precise and very reliable manner, the total energy available in the cellular battery and its derivatives such as for example the energy health state or the certified energy state, which in particular makes it possible to comply with the high levels of precision imposed by the developments of certain national or international standards.

[0014] The estimation method according to the invention may include other characteristics which may be taken separately or in combination, and in particular:

[0015] - in its step, we can estimate the minimum state of charge in addition to of a current temperature outside the cell battery;

[0016] - in its step, one can estimate the minimum state of charge using at least one table establishing a correspondence between minimum charge states and pairs of maximum power and information representative of internal resistance;

[0017] - in the presence of the first two options, in its step, we can estimate the state of minimum load using tables each establishing a correspondence between minimum load states and pairs of maximum power and information representative of the internal resistance for a temperature, the temperature varying from one table to another;

[0018] - in its step, the information can be equal to the internal resistance estimated in current, or it may be a current resistive health condition which is a function of the current estimated internal resistance.

[0019] The invention also provides a computer program product comprising a set of instructions which, when executed by processing means, is capable of implementing an estimation method of the type presented above, in a system comprising a cellular battery having an estimated current internal resistance and an estimated current state of charge, to estimate a minimum state of charge that this cellular battery must have at the end of a predefined discharge cycle.

[0020] The invention also provides an estimation device intended to equip a system comprising a cellular battery having a current estimated internal resistance and a current estimated state of charge.

[0021] This estimation device is characterized by the fact that it comprises at least one processor and at least one memory arranged to carry out the operations consisting of estimating a minimum state of charge that the cellular battery must have at the end of a predefined discharge cycle, as a function of information, representative of the current estimated internal resistance, and of a maximum power that the cellular battery must be capable of delivering at the end of this predefined discharge cycle.

[0022] The invention also proposes a system comprising, on the one hand, a cellular battery having an estimated current internal resistance and an estimated current state of charge, and, on the other hand, an estimation device of the type presented above.

[0023] For example, this system may constitute a vehicle, possibly of the automobile type. Brief description of the figures

[0024] Other characteristics and advantages of the invention will appear on examining the detailed description below, and the appended drawings, in which:

[0025] [Fig.l] schematically and functionally illustrates an exemplary embodiment of a vehicle comprising a GMP with an electric motor powered by a cellular battery associated with a battery calculator, and an estimation device according to the invention,

[0026] [Fig.2] schematically and functionally illustrates an exemplary embodiment of a battery calculator comprising an estimation device according to the invention, and

[0027] [Fig.3] schematically illustrates an example of an algorithm implementing an estimation method according to the invention. Detailed description of the invention

[0028] The invention aims in particular to propose an estimation method, and an associated estimation device DE, intended to allow a very precise and very reliable estimation of the minimum state of charge ecmin that the cellular battery BC of a system S must have at the end of a predefined discharge cycle.

[0029] In the following, it is considered, by way of non-limiting example, that the system S is a motor vehicle, such as for example a car, as illustrated in [Fig.l]. But the invention is not limited to this type of system. It relates in fact to any type of system comprising at least one rechargeable cellular battery whatever the mode. Thus, it relates to vehicles (land, sea (or river), and air), mobile machines (including those which provide a lifting function), electronic devices (possibly household appliances and / or possibly mobile), fixed or stationary installations (possibly industrial), such as for example electrical energy supply installations, and buildings, for example. By way of purely illustrative example, the cellular battery BC of a system S can be connected to a renewable energy source (in particular photovoltaic or wind).

[0030] Furthermore, it is considered in the following, by way of non-limiting example, that the system S (here a vehicle) comprises a powertrain (or GMP) of the all-electric type (and therefore whose drive is provided exclusively by at least one electric motor MME). But the GMP could be of the hybrid type (thermal and electric).

[0031] Furthermore, it is considered in the following, by way of non-limiting example, that the cellular battery BC is a main battery (or traction or even power). But the cellular battery which is the subject of the estimations could be a service battery (possibly rechargeable via a converter supplied with electrical energy by a main battery).

[0032] [Fig.l] schematically shows a system S (here a vehicle) comprising an electric GMP transmission chain, an on-board network RB, a power supply group comprising a service battery BS and (here) a converter CV associated with a cellular battery BC (itself associated with a battery calculator CB), and an estimation device DE according to the invention.

[0033] The on-board network RB is an electrical power supply network to which electrical (or electronic) equipment (or components) that consume electrical energy are coupled.

[0034] The service battery BS is responsible for supplying electrical energy to the on-board network RB, in addition to that supplied by the CV converter powered by the cellular battery BC, and sometimes instead of this CV converter (in particular when the GMP is asleep and the CV converter is inactive). For example, this service battery BS can be arranged in the form of a very low voltage type battery (typically 12 V, 24 V or 48 V). It is rechargeable at least by the CV converter. It is considered in the following, by way of non-limiting example, that the service battery BS is of the 12 V Lithium-ion type.

[0035] The transmission chain has a GMP which is, here, purely electric, and therefore which comprises, in particular, an electric driving machine MME, a motor shaft AM, and a transmission shaft AT. Here, the term “electric driving machine” means an electric machine arranged so as to provide or recover torque to move the system S (here a vehicle). The operation of the GMP is supervised by a supervision computer CS.

[0036] The electric motor MME (here an electric motor) is coupled to the cellular battery BC, in order to be supplied with electrical energy, as well as possibly to supply this cellular battery BC with electrical energy (for example during a regenerative braking phase). It is coupled to the motor shaft AM, to provide it with torque by rotational drive. This motor shaft AM is here coupled to a reducer RD which is also coupled to the transmission shaft AT, itself coupled to a first train T1 (here of wheels), preferably via a differential DI.

[0037] This first train T1 is here located in the front part PVV of the vehicle S. But in a variant this first train T1 could be the one which is here referenced T2 and which is located in the rear part PRV of the vehicle S.

[0038] The driving machine MME is, here, also coupled to the converter CV which is also indirectly coupled to the service battery BS, in particular to recharge it with electrical energy from the cellular battery BC and converted.

[0039] This CV converter is a current converter electrically coupled, here, to a CN charging connector of the vehicle S, for example. It is also responsible for supplying the on-board network RB with electrical energy from the cellular battery BC and converted when the GMP is in operation or when the GMP is asleep but the vehicle S is in a phase of recharging its cellular battery BC, in addition to ensuring the recharging of the service battery BS.

[0040] For example, the cellular battery BC may comprise N electrochemical electrical energy storage cells CE, with N > 1. Also for example, each cell (electrochemical electrical energy storage) CE may be of the lithium-ion (or Li-ion) type. But this is not obligatory. Indeed, it could be of the Ni-Mh or Ni-Cd type, for example. Also for example, the cellular battery BC may be of the low voltage type (typically 450 V for illustrative purposes). But it could be of the medium voltage or high voltage type.

[0041] It will be noted, as illustrated non-limitingly in [Fig. 1], that the N cells CE can be distributed in MC modules which are coupled together, for example in series, within the cell battery BC. Here, the term “MC module” means a group of at least one cell CE. When an MC module comprises several cells CE, the latter (CE) can be coupled together in series and / or in parallel.

[0042] It will also be noted that the cellular battery BC is associated with a battery box BB which notably comprises means for measuring voltage, current and internal temperature (not illustrated) and the battery calculator CB. The latter (CB) notably centralizes the current measurements, the voltage measurements and the internal temperature measurements, and estimates parameters of the cellular battery BC as a function of these measurements, and notably its internal resistance rie, its minimum voltage and its state of charge (or SOC (“State Of Charge”)).

[0043] Among the parameters of the cellular battery BC that the battery calculator CB is able to estimate, there is at least the current internal resistance rie of the cellular battery BC and the maximum power pmax that the cellular battery BC must be able to deliver at the end of a predefined discharge cycle.

[0044] The estimated current internal resistance is often referred to as DCR (Direct Current Resistance). It can, for example, be estimated using the formula DCR = SOHR*DCRini, where SOHR is the current resistive state of health (State Of Health of Resistance), and DCRini is the estimated initial internal resistance of the cell battery BC (i.e., when it is new).

[0045] The maximum power pmax can, for example, be estimated by means of at least a first correspondence table (or mapping) determined beforehand and establishing a correspondence between maximum powers and pairs of state of charge (or SOC) and internal resistance for a given external temperature. It should be noted that it is possible to use several first correspondence tables (or mappings) associated respectively with different external temperatures. But instead of using at least one first correspondence table (or mapping) one could use at least one mathematical equation to estimate the maximum power pmax.

[0046] It is recalled that when the internal resistance rie increases, the maximum power pmax available decreases.

[0047] It will also be noted that in the example illustrated non-limitingly in [Fig. 1] the vehicle S also comprises a distribution box BD to which the service battery BS, the converter CV and the on-board network RB are coupled. This distribution box BD is responsible for distributing in the on-board network RB the electrical energy which is produced by the converter CV or stored in the service battery BS, for the supply of the electrical components (or equipment) coupled to the on-board network RB, according to power supply requests received (in particular from the supervision computer CS of the GMP).

[0048] As mentioned above, the invention proposes in particular an estimation method intended to allow a very precise and very reliable estimation of the minimum state of charge ecmin that the cellular battery BC must have at the end of a predefined discharge cycle.

[0049] In the following, it is considered, by way of non-limiting example, that the predefined discharge cycle is of the WLTP type. However, the invention is not limited to this type of “standardized” discharge cycle.

[0050] This (estimation) method can be implemented at least partially by the estimation device DE (illustrated in FIGS. 1 and 2) which comprises for this purpose at least one processor PR1, for example a digital signal processor (or DSP ("Digital Signal Processor")), and at least one memory MD. This estimation device DE can therefore be produced in the form of a combination of electrical or electronic circuits or components (or "hardware") and software modules (or "software").

[0051] The memory MD is live in order to store instructions for the implementation by the processor PR1 of at least part of the estimation method. The processor PR1 may comprise integrated (or printed) circuits, or several integrated (or printed) circuits connected by wired or wireless connections. An integrated (or printed) circuit is understood to mean any type of device capable of carrying out at least one electrical or electronic operation.

[0052] In the example illustrated non-limitingly in Figures 1 and 2, the device The DE estimation device is part of the CB battery calculator (and therefore, here, of the BB battery box). But this is not mandatory. Indeed, the DE estimation device could include its own dedicated calculator, which can then be coupled to the CB battery calculator.

[0053] As illustrated non-limitingly in [Fig. 3], the (estimation) method, according to the invention, comprises a step 10 which is implemented in the system S (here a vehicle) each time a predefined discharge cycle is carried out in this system S.

[0054] In this step 10, the minimum state of charge ecmin that the cellular battery BC must have at the end of the predefined discharge cycle (just carried out) is estimated (for example, the estimation device DE). It will be understood that the minimum state of charge ecmin is the lower limit that must not be exceeded during a discharge of the cellular battery BC so that the latter (BC) is capable of providing a maximum power pmax to the system S (for example, to travel at a chosen speed when it constitutes a vehicle).

[0055] This estimation is carried out according to information iri, representative of the current estimated internal resistance rie, and of the maximum power pmax that the cellular battery BC must be capable of delivering at the end of this predefined discharge cycle.

[0056] Thanks to this estimation of the minimum state of charge ecmin as a function of at least the information iri and the maximum power pmax, it is now possible to estimate in the system S, in a very precise and very reliable manner, the total energy available in the cellular battery BC (or UBE (Useful Battery Energy)) and its derivatives such as for example the energy health state of the cellular battery BC (or SOHE (State Of Health of Energy) - also called certified energy state (or SOCE (State Of Certified Energy))). This makes it possible in particular to comply with the high levels of precision imposed by the developments of certain national or international standards. In addition, this makes it possible to make the estimation of the kilometer autonomy of the system S more precise and more reliable when it constitutes a vehicle, and thus to better satisfy the users of this system S.

[0057] Furthermore, the estimation of the minimum state of charge ecmin as a function of the maximum power pmax is particularly useful because it makes it possible to take into account any request for adjustment of the power level (upwards) during the life cycle of the system S, for example due to a degradation of the efficiency of the electric motor MME with aging and / or an additional overconsumption of the power induced by the needs of at least one electrical consumer other than the electric motor MME (such as the CV converter or a heating / air conditioning installation) and / or the current mass of the system S when it constitutes a vehicle.

[0058] It will be understood that it is at least the processor PR1 and memory MD of the estimation device DE which are arranged to carry out the operations consisting of estimating the minimum state of charge ecmin.

[0059] It will be noted that in step 10 one (preferably the battery calculator CB) may possibly start by determining the information iri and / or the maximum power pmax. But this is not obligatory. Indeed, the information iri and / or the maximum power pmax may have been determined previously (preferably less than six months before the predefined discharge cycle is carried out to avoid it having changed significantly in the meantime).

[0060] It will also be noted that in step 10 one (for example the estimation device DE) can estimate the minimum state of charge ecmin as a function not only of the information iri and the maximum power pmax, but also of the current temperature outside the cellular battery BC. In this case, given that the maximum power pmax varies as a function of the temperature, it is preferable in step 10 to start by determining at least the maximum power pmax in order to be sure that it actually corresponds to the current temperature outside the cellular battery BC. In this case, the estimation device DE may possibly be arranged so as to determine at least the maximum power pmax.

[0061] For example, in step 10 one (for example the estimation device DE) can estimate the minimum state of charge ecmin using at least a second previously determined correspondence table (or mapping) establishing a correspondence between minimum states of charge and pairs of maximum power and information representative of the internal resistance. When there is no pair of maximum power and information representative of the internal resistance corresponding exactly to the information iri and maximum power pmax, one can, for example, perform a linear interpolation from “neighboring” pairs.

[0062] But instead of using at least a second correspondence table (or mapping) one could use at least one mathematical equation to estimate the minimum state of charge ecmin.

[0063] When it is also desired to take into account the current temperature outside the cellular battery BC, in step 10 one (for example the estimation device DE) can estimate the minimum state of charge ecmin using second correspondence tables (or maps) previously determined and each establishing a correspondence between minimum states of charge and pairs of maximum power and information representative of the internal resistance for a temperature. In this case, the temperature varies from one second table to the other.

[0064] But instead of using second correspondence tables (or maps) one could use at least one mathematical equation to estimate the state of charge minimum ecmin.

[0065] Also for example, in step 10 one (for example the estimation device DE) can use information iri which is equal to the current estimated internal resistance rie. Alternatively, the information can be the current resistive health status (or SOHR), which is a function of the current estimated internal resistance rie.

[0066] It will also be noted, as illustrated non-limitingly in [Fig.2], that the battery calculator CB (or the dedicated calculator of the estimation device DE) can also comprise a mass memory MM1, in particular for the temporary storage of parameter values ​​useful for determining the information iri and maximum power pmax or the information iri and maximum power pmax, and any intermediate data involved in all its calculations and processing.Furthermore, this battery calculator CB (or the dedicated calculator of the estimation device DE) may also comprise an input interface IE for receiving parameter values ​​useful for determining the information iri and maximum power pmax or the information iri and maximum power pmax for using them in calculations or processing, possibly after having formatted and / or demodulated and / or amplified them, in a manner known per se, by means of a digital signal processor PR2. In addition, this battery calculator CB (or the dedicated calculator of the estimation device DE) may also comprise an output interface IS, in particular for delivering a message containing the estimated minimum state of charge ecmin.

[0067] It will also be noted that the invention also proposes a computer program product (or computer program) comprising a set of instructions which, when executed by processing means of the electronic circuit (or hardware) type, such as for example the processor PR1, is capable of implementing the estimation method described above to estimate the minimum state of charge ecmin that the cellular battery BC of the system S must have at the end of a predefined discharge cycle.

Claims

Claims

1. Estimation method for a system (S) comprising a cellular battery (BC) having an estimated current internal resistance and an estimated current state of charge, characterized in that it comprises a step (10) in which a minimum state of charge that said cellular battery (BC) must have at the end of a predefined discharge cycle is estimated, as a function of information, representative of said estimated current internal resistance, and of a maximum power that said cellular battery (BC) must be capable of delivering at the end of said predefined discharge cycle.

2. Method according to claim 1, characterized in that in said step (10) said minimum state of charge is estimated as a function furthermore of a current temperature outside said cellular battery (BC).

3. Method according to claim 1 or 2, characterized in that in said step (10) said minimum state of charge is estimated using at least one table establishing a correspondence between minimum states of charge and pairs of maximum power and information representative of the internal resistance.

4. Method according to the combination of claims 2 and 3, characterized in that in said step (10) said minimum state of charge is estimated using tables each establishing a correspondence between minimum states of charge and pairs of maximum power and information representative of the internal resistance for a temperature, said temperature varying from one table to another.

5. Method according to one of claims 1 to 4, characterized in that in said step (10) said information is equal to said current estimated internal resistance.

6. Method according to one of claims 1 to 4, characterized in that in said step (10) said information is a current resistive health state as a function of said current estimated internal resistance.

7. Computer program product comprising a set of instructions which, when executed by processing means, is capable of implementing the information estimation method according to one of claims 1 to 6, in a system (S) comprising a cellular battery (BC) having a current estimated internal resistance and a current estimated state of charge, to estimate a minimum state of charge that said cellular battery (BC) must have at the end of a predefined discharge cycle.

8. Estimation device for a system (S) comprising a cellular battery (BC) having an estimated current internal resistance and an estimated current state of charge, characterized in that it comprises at least one processor (PR1) and at least one memory (MD) arranged to carry out the operations consisting of estimating a minimum state of charge that said cellular battery (BC) must have at the end of a predefined discharge cycle, as a function of information, representative of said estimated current internal resistance, and of a maximum power that said cellular battery (BC) must be capable of delivering at the end of said predefined discharge cycle.

9. System (S) comprising a cellular battery (BC) having a current estimated internal resistance and a current estimated state of charge, characterized in that it further comprises an estimation device (DE) according to claim 8.

10. System according to claim 9, characterized in that it constitutes a vehicle.

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