Method for controlling gas generation by a battery and associated control device

Abstract

A method for controlling gas generation by a battery, comprising the following steps: determining, at a given time te, the quantity of gas Xte generated by the battery between a time t0 of battery commissioning and time te, based on a history of battery usage conditions between t0 and te; estimating, using a predictive model, the quantity of gas XtEOL generated by the battery at a battery end-of-life time tEOL, based on the quantity of gas Xte and the history of battery usage conditions between t0 and te; comparing the estimated quantity of gas XtEOL with a predefined limit value L; and adjusting the battery usage conditions when the estimated quantity of gas XtEOL is greater than or equal to the limit value L. Figure for the abstract: Fig 1

Description

Title of the invention: Method for controlling gas generation by a battery and associated control device

[0001] The present invention relates, in general, to the degassing of the cells of a battery, such as a Li-ion battery incorporating a nickel-rich (Ni) lamellar oxide cathode active material.

[0002] In particular, the invention relates to the control of gas generation by a battery and in particular by the cells it incorporates and, more specifically, a method of controlling gas generation by a battery, a device for controlling gas generation by a battery, as well as a motor vehicle incorporating such a control device.

[0003] Li-ion batteries incorporating cathodes comprising Ni-rich lamellar oxide as the active material are particularly subject to gas generation, especially when high potentials (vs. Li / Li+) and high temperatures are reached.

[0004] However, gas production can be detrimental to battery performance. Gas accumulates in the pores of the electrode or between the electrode and the separator, and increases the internal resistance of the cell.

[0005] Furthermore, at a certain level of gas production, the pressure inside the cell may be high enough to rupture the cell in the case of so-called "pouch" cells, whose envelope forms a pocket, or to leak through the vent valve in the case of prismatic cells. These phenomena are referred to below as cell degassing.

[0006] During battery use, outgassing causes a drop in voltage in the affected cells. When this voltage drop is detected by a battery management system (BMS), it can lead to the battery shutting down.

[0007] Nevertheless, the battery can operate in a wide range of charge states and temperatures, without producing enough gas to cause outgassing of the cells.

[0008] The occurrence of the cell outgassing phenomenon is mainly determined by the state of charge and temperature conditions (SOC - T°) to which the battery is subjected during its lifetime.

[0009] Four main mechanisms allow us to understand the generation of gas within a cell incorporating a cathode based on a Ni-rich lamellar oxide: the formation of the SEI layer for "solid-electrolyte interphase" and the presence of impurities, which are two minor factors, as well as two main factors which are the oxidation of the electrolyte and the chemical reaction with oxygen.

[0010] The invention therefore aims to remedy these drawbacks and to propose a strategy for predicting and controlling the generation of gas in a battery in order to reduce the risks of opening the cells that compose it.

[0011] A method for controlling gas generation by a battery is therefore proposed, comprising the following steps:

[0012] the determination, at a given time f, of a quantity of gas Xte generated by the battery between a time t0 of battery commissioning and time te, as a function of a history of the battery's usage conditions between t0 and te,

[0013] the estimation from a predictive model of a quantity of gas XtE0L generated by the battery at an end-of-life time of the battery tEOL, as a function of the quantity of gas Xte and the history of the battery usage conditions between t0 and te,

[0014] the comparison of the estimated quantity of gas XtE0L with respect to a predefined limit value L, and

[0015] the adjustment of the battery usage conditions when the estimated quantity of gas XtE0L is greater than or equal to the limit value L.

[0016] Such a control method makes it possible to avoid the occurrence of battery failure by controlling the risk of cell outgassing.

[0017] The control method according to the invention is particularly advantageous for a Li-ion battery incorporating cathode materials used at high potentials, above 4.2V.

[0018] In one implementation mode, the adjustment can be performed iteratively and can include, at iteration n where n is an integer greater than or equal to 1:

[0019] the application to the battery of a combination of restrictive state of charge and temperature conditions [SOC - T]n,

[0020] the estimation from the prediction model of a quantity of gas XtEOL,[soc-Tjn generated by the battery at the end of battery life time tEOL, as a function of the combination of state of charge conditions and temperature [SOC - T]n applied,

[0021] the comparison of the quantity of gas XtEOL,[soc -Tjnestimated with respect to the predefined limit value L, and

[0022] the application of a new combination of state of charge and temperature conditions [SOC - T]n+imore restrictive than the previous combination of state of charge and temperature conditions [SOC - T]n until the estimated quantity of gas X^ol, isoc t|II+i is less than the limit value L.

[0023] In another embodiment, the adjustment can be made using artificial intelligence trained to determine an optimal combination of restrictive usage conditions leading to a quantity of gas XtE0L generated by the battery at the end of battery life tE0L lower than the limit value L, based on a database of historical battery usage conditions.

[0024] Preferably, the history of battery usage conditions between t0 and te includes the evolution of one or more battery parameters among: temperature, state of charge, current and voltage.

[0025] Advantageously, when the quantity of gas XtE0L generated by the battery at the end of battery life time tE0L is less than the limit value L, a new estimation of the quantity of gas XtE0L generated by the battery at the end of battery life time tE0L can be carried out subsequently.

[0026] The invention also relates to a device for controlling gas generation by a battery, comprising:

[0027] a connection interface capable of connecting to the battery and communicating with it to collect data relating to the battery's usage conditions; and

[0028] a computer capable of:

[0029] determine, at a given time te, a quantity of gas Xte generated by the battery between a time t0 of battery commissioning and time te, as a function of a history of battery usage conditions between t0 and te,

[0030] estimate from a predictive model a quantity of gas XtE0L generated by the battery at an end-of-life time of the battery tEOL, as a function of the quantity of gas Xte and the history of the battery usage conditions between t0 and te,

[0031] compare the estimated quantity of gas XtE0L with a predefined limit value L, and

[0032] adjust the battery usage conditions when the estimated quantity of gas XtE0L is greater than or equal to the limit value L.

[0033] In one embodiment, the computer may be capable of performing the adjustment by iteration, the computer being capable of:

[0034] apply to the battery a combination of restrictive state of charge and temperature [SOC - T]n conditions,

[0035] estimate from the prediction model of a quantity of gas XtEOL,Lsoc-Tjn generated by the battery at the end of the battery's life time tE0L, as a function of the combination of state of charge conditions and temperature [SOC - T]n applied,

[0036] compare the quantity of gas XtEOE,[soc Tjnestimated with respect to the predefined limit value L, and

[0037] apply a new combination of state of charge and temperature conditions [SOC - T]n+i more restrictive than the combination of state of charge and temperature conditions previous temperature [SOC - T]n until the estimated quantity of gas X^ol, isoc-Tjn+i is less than the limit value L.

[0038] In another embodiment, the computer may be able to adjust the battery usage conditions when the estimated quantity of gas XtE0L is greater than or equal to the limit value L by means of an artificial intelligence trained to determine an optimal combination of restrictive usage conditions leading to a quantity of gas XtE0L generated by the battery at the end of battery life tE0L less than the limit value L, based on a database of historical battery usage conditions.

[0039] Preferably, the connection interface is capable of collecting one or more data chosen from: operating temperature, current, load state distribution.

[0040] The invention also relates to a motor vehicle comprising at least one device for controlling the generation of gas by a battery as previously described.

[0041] Other purposes, advantages and features will become apparent from the following description, given for illustrative purposes only and made with reference to the accompanying drawings on which:

[0042] [Fig. 1] illustrates a method of controlling the generation of gas by a battery according to an embodiment of the invention.

[0043] [Fig.2] is a flowchart representing a method for controlling the generation of gas by a battery according to an embodiment of the invention.

[0044] In what follows, and unless otherwise indicated, the bounds of a domain of values ​​are included in that domain, in particular in the expression "between".

[0045] Furthermore, the expression "at least one" used in this description is equivalent to the expression "one or more".

[0046] Figures 1 and 2 illustrate a control method according to the invention aimed at controlling the production of gas resulting from the operation of a battery.

[0047] The battery can be any type of battery, for example a Li-ion battery, and intended for any type of use.

[0048] In one embodiment, the battery may be a battery comprising a cathode incorporating a Ni-based lamellar oxide active material, such as a Li-ion battery, particularly prone to gas generation, especially when used at potentials above 4.2 V.

[0049] By "Ni-based" is meant a material consisting mainly of Ni.

[0050] The battery includes, for example, a cathode incorporating an active material based on NMC, nickel manganese cobalt, such as NMC 622 or 811.

[0051] According to one example, the battery may be a motor vehicle battery, such as an electric or hybrid motor vehicle, but is not limited to use in a motor vehicle.

[0052] The method for controlling gas generation by the battery includes a step 100 of determining, at a time te during the battery's life, a quantity of gas Xte generated by at least one battery cell since it was put into service, i.e., between a time t0 of battery commissioning and time L

[0053] Step 100 of determining the quantity of gas Xte is carried out according to a history of the battery usage conditions between tO and te.

[0054] Preferably, the history of the battery usage conditions between t0 and te includes the history of the evolution of the battery temperature and its state of charge, known as "State Of Charge", SOC, in Anglo-Saxon terms.

[0055] The history of the battery usage conditions between t0 and k may also include, for example, the evolution of the battery current and voltage.

[0056] The quantity of gas Xte generated by the battery can thus be estimated from empirical or semi-empirical data.

[0057] The control method further includes a step 200 of estimating a quantity of gas XtE0L generated by the battery at an end-of-life time of the battery tE0L.

[0058] Step 200 of estimating the quantity of gas XtE0L is carried out from a prediction model based on the quantity of gas Xk determined previously and the history of battery usage conditions recorded between t0 and te.

[0059] By tEOL battery end of life, or "End Of Life" in Anglo-Saxon terms, we mean the moment when the performance becomes insufficient for the use of the battery, and in particular when the outgassing of the battery leads to the opening of at least one of the cells that compose it.

[0060] Step 200 of estimating the quantity of gas XtE0L generated by the battery at the end-of-life time of the battery tE0L can be carried out by the prediction model by extrapolation on the basis of the quantity of gas Xte determined previously and the history of the battery usage conditions recorded between t0 and te.

[0061] The quantity of gas XtE0L generated by the battery at the end of battery life time tE0L is to be calculated in volume and / or mass, for example in mol.

[0062] Step 200 of estimating the quantity of gas Xte generated by the battery at time te can, in addition, be carried out from physical parameters of the cells which make up the battery.

[0063] The quantity of gas Xtegenerated by the battery at time f can thus be calculated from empirical or semi-empirical data.

[0064] The method of controlling the generation of gas by the battery then includes a step of comparing the quantity of gas XtE0L obtained with respect to a predefined limit value L.

[0065] Advantageously, the limit value L can be predefined based on one or more physical parameters of the battery cells, such as the cells' capacity to contain gas without outgassing. The battery cells can be pouch-shaped or prismatic.

[0066] When the quantity of gas X^ol is less than the limit value L generated by the battery at the end of the battery's life tEOL, no outgassing of the cells is expected before the end of the battery's life. It is not necessary to limit the battery's operating conditions.

[0067] Preferably, when the quantity of gas XtE0L generated by the battery at the end of battery life time tE0L is less than the limit value L, a new estimate of the quantity of gas XtE0L generated by the battery at the end of battery life time tE0L is made later, after some time, for example a few months later, on the basis of a more complete history of battery use, in order to ensure that the quantity of gas XtE0L remains less than L.

[0068] When the calculated quantity of gas XtE0L is greater than or equal to the predefined limit value L, there is a risk of the battery cell opening before the end of its service life. It is necessary to limit the battery's exposure to certain operating conditions. The battery operating conditions are adjusted in an adjustment step 400 of the control process.

[0069] In a first embodiment, the 400 adjustment is performed by iteration.

[0070] At an iteration n, where n is an integer greater than or equal to 1, the adjustment step 400 includes the application of a combination of restrictive state of charge and temperature [SOC - T]n conditions to the battery.

[0071] In other words, at the adjustment step 400, the state of charge and temperature conditions to which the battery is subjected are reduced by applying a combination of state of charge and temperature conditions [SOC - T]n.

[0072] Since the production of gas by the battery cells is associated with the state of charge and temperature conditions to which the battery is subjected, reducing the state of charge and temperature of the battery makes it possible to limit the production of gas by the battery cells.

[0073] The quantity of gas XtEOL,[soc-Tjn generated by the battery at the end of battery life time tE0L is estimated from the prediction model, based on the combination of state of charge conditions and temperature [SOC - T]n applied.

[0074] The estimated quantity of gas XtEOL,Lsoc-Tjn is compared to the predefined limit value L.

[0075] When the estimated quantity of gas X^ol, [soc-Tjn is greater than or equal to the limit value L, a new combination of state of charge and temperature conditions [SOC - T]n+i more restrictive than the previous combination of state of charge and temperature conditions [SOC - T]n is applied.

[0076] In other words, the state of charge and temperature conditions to which the battery is subjected are further reduced by applying a new combination of state of charge and temperature conditions [SOC - T]n+i.

[0077] The new quantity of gas X^ol, isoc-Tjn+i is then estimated on the basis of the new combination of state of charge and temperature conditions [SOC - T]n+i more restrictive applied.

[0078] The control of the gas generation by the battery is thus carried out by successive approximations and a new combination of state of charge and temperature conditions more restrictive than the previous one is applied to the battery until the resulting quantity of gas Xj oi cstiméc is less than the limit value L and the risk of opening the battery cells is eliminated.

[0079] Advantageously, the control method may include a step of applying a less restrictive combination of state of charge and temperature conditions [SOC - T]n than the previous combination of state of charge and temperature conditions [SOC - T]n applied when the previous combination is so effective that the risk of outgassing has been sufficiently eliminated. The battery user can thus recover increased performance.

[0080] This step of reducing the limitation can also be carried out by iteration until the combination of state of charge and temperature conditions [SOC - T]n4la least restrictive but which still allows to remain below the limit value L is applied.

[0081] In a second embodiment, the adjustment step 400 can be carried out using artificial intelligence.

[0082] Artificial intelligence is trained to determine, in a single step, without iteration, an optimal combination of restrictive usage conditions, in particular temperature and state of charge [SOC - T], leading to a quantity of gas XtE0L generated by the battery at the end-of-life time of the battery tE0L lower than the limit value L.

[0083] The determination of the optimal combination by artificial intelligence is based on the use of a historical database of usage conditions of previously used batteries, reflecting the habits of former users of similar batteries, and whose usage conditions have been recorded in the database.

[0084] When restrictive battery temperature conditions must be applied, the temperature can be reduced by controlling a battery cooling system and / or by limiting its performance.

[0085] In addition, the state of charge can be limited by blocking the battery charging at a predetermined maximum threshold value.

[0086] Advantageously, the control method according to the invention can be implemented within a gas generation control device by a battery, incorporating all the hardware and software means for the implementation of this control method.

[0087] The control device includes a connection interface capable of connecting to the battery and communicating with it to collect data relating to the battery's usage conditions.

[0088] In addition, the control device includes a computer capable of:

[0089] determine, at a given time te, a quantity of gas Xte generated by the battery between a time t0 of battery commissioning and time te, as a function of a history of the battery's usage conditions between t0 and te,

[0090] estimate from a predictive model a quantity of gas XtE0L generated by the battery at an end-of-life time of the battery tEOL, as a function of the quantity of gas Xte and the history of the battery usage conditions between t0 and te,

[0091] compare the estimated quantity of gas XtE0L with a predefined limit value L, and

[0092] adjust the battery usage conditions when the estimated quantity of gas XtE0L is greater than or equal to the limit value L.

[0093] The connection interface may advantageously be capable of collecting one or more data selected from: the battery operating temperature, the current, the state of charge distribution.

[0094] The computer integrating the prediction model can be a specific computer or can be integrated into a battery management system, BMS, such as the BMS of a motor vehicle.

[0095] In one embodiment, the computer may be capable of performing the adjustment by iteration, the computer thus being capable of:

[0096] apply to the battery a combination of restrictive state of charge and temperature [SOC - T]n conditions,

[0097] estimate from the prediction model of a quantity of gas XtEOL,[soc-Tjn generated by the battery at the end of battery life time tE0L, as a function of the combination of state of charge conditions and temperature [SOC - T]n applied,

[0098] compare the estimated quantity of gas XtEOE,Lsoc Tjn with respect to the predefined limit value L, and

[0099] apply a new combination of state of charge and temperature conditions [SOC - T]n+i more restrictive than the previous combination of state of charge and temperature conditions [SOC - T]n until the estimated quantity of gas X^ol, isoc-Tjn+i is less than the limit value L.

[0100] Advantageously, the control device may be able to apply a former combination of state of charge and temperature conditions [SOC - T]n less restrictive than the previous combination of state of charge and temperature conditions [SOC - T]n applied when the former combination is so effective that the risk of outgassing has been sufficiently eliminated.

[0101] The control device may be able to apply this former combination of state of charge and temperature conditions [SOC - T]n4 by iteration.

[0102] In an alternative embodiment, the computer may be able to adjust the battery usage conditions when the estimated quantity of gas XtE0L is greater than or equal to the limit value L using an embedded artificial intelligence.

[0103] Artificial intelligence can be trained to determine an optimal combination of restrictive usage conditions leading to a quantity of gas XtE0L generated by the battery at the end of battery life time tE0L lower than the limit value L, based on a database of historical battery usage conditions.

[0104] Preferably, when the quantity of gas XtE0L generated by the battery at the end of battery life time tE0L is less than the limit value L, the control device is able to make a new estimation subsequently of the quantity of gas XtE0L generated by the battery at the end of battery life time tE0L.

[0105] The new estimation can be carried out at regular intervals, for example every month, as long as the limit value L is not reached.

Claims

Demands

1. A method for controlling the generation of gas by a battery, comprising the following steps: determining, at a given time te, a quantity of gas Xte generated by the battery between a time t0 of battery commissioning and time te, as a function of a history of the battery's usage conditions between t0 and te; estimating, from a predictive model, a quantity of gas XtE0L generated by the battery at a battery end-of-life time tEOL, as a function of the quantity of gas Xte and the history of the battery's usage conditions between t0 and te; comparing the estimated quantity of gas XtE0L with a predefined limit value L; and adjusting the battery's usage conditions when the estimated quantity of gas XtE0L is greater than or equal to the limit value L.

2. A method according to claim 1, wherein the adjustment is performed iteratively and comprises, at an iteration n where n is an integer greater than or equal to 1: applying to the battery a restrictive combination of state-of-charge and temperature conditions [SOC - T]n, estimating from the prediction model a quantity of gas XtEOLj[soc - rjn generated by the battery at the battery end-of-life time tEOL, as a function of the applied combination of state-of-charge and temperature conditions [SOC - T]n, comparing the estimated quantity of gas XtEOL,[soc - Tjn] with the predefined limit value L, and applying a new combination of state-of-charge and temperature conditions [SOC - T]n+i more restrictive than the previous combination of state-of-charge and temperature conditions [SOC - T]n until the quantity of gas XtEOL, Lsoc rjn+iestimated is less than the limit value L.

3. A method according to claim 1, wherein the adjustment is made using artificial intelligence trained to determine an optimal combination of restrictive usage conditions leading to a quantity of gas XtE0L generated by the battery at the end-of-life time of the battery tE0L lower than the limit value L, based on a database of historical battery usage conditions.

4. A method according to any one of the preceding claims, wherein the history of the battery usage conditions between t0 and te includes the evolution of one or more battery parameters among: temperature, state of charge, current and voltage.

5. A method according to any one of the preceding claims, wherein when the quantity of gas XtE0L generated by the battery at the end-of-life time of the battery tE0L is less than the limit value L, a new estimation of the quantity of gas XtE0L generated by the battery at the end-of-life time of the battery tE0L is subsequently carried out.

6. A device for controlling the generation of gas by a battery, comprising: a connection interface capable of connecting to the battery and communicating with it to collect data relating to the conditions of use of the battery; and a computer capable of: determining, at a given time te, a quantity of gas Xte generated by the battery between a time t0 of commissioning of the battery and time f, as a function of a history of the conditions of use of the battery between t0 and h, estimating from a predictive model a quantity of gas XtE0L generated by the battery at an end-of-life time of the battery tE0L, as a function of the quantity of gas Xte and the history of the conditions of use of the battery between t0 and te, comparing the estimated quantity of gas XtE0L with a predefined limit value L, and adjusting the conditions of use of the battery when the estimated quantity of gas XtE0L is greater than or equal to the limit value L.

7. Device according to claim 6, wherein the computer is capable of performing the adjustment by iteration, the computer being capable of: applying to the battery a combination of restrictive state of charge and temperature conditions [SOC - T]n, estimating from the prediction model a quantity of gas XtE0Lj isoc-Tjn generated by the battery at the end of battery life time tE0L, as a function of the combination of state of charge and temperature conditions [SOC - T]n applied, compare the estimated quantity of gas XtEOL,[soc-Tjn] with respect to the predefined limit value L, and apply a new combination of state charge and temperature conditions [SOC - T]n+i more restrictive than the previous combination of state charge and temperature conditions [SOC - T]n until the estimated quantity of gas X^ol, Lsoc rjn+i is less than the limit value L.

8. Device according to claim 6, wherein the computer is capable of adjusting the battery usage conditions when the estimated quantity of gas XtE0L is greater than or equal to the limit value L by means of artificial intelligence trained to determine an optimal combination of restrictive usage conditions leading to a quantity of gas XtE0L generated by the battery at the end of battery life tE0L less than the limit value L, based on a database of historical battery usage conditions.

9. Device according to any one of claims 6 to 8, wherein the connection interface is capable of collecting one or more data selected from: operating temperature, current, load state distribution.

10. Motor vehicle comprising at least one device for controlling the generation of gas by a battery according to any one of claims 6 to 9.

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