METHOD FOR MANAGING THE CHARGE STATE OF A TRACTION BATTERY OF A HYBRID VEHICLE

Abstract

A method for managing the charge state of a battery includes activating a float-charge phase of the battery, in which the battery is intermittently charged with a view to maintaining the charge state thereof above a predetermined target charge-state value. The method also includes detecting critical conditions of use of the battery likely to prevent the battery charge state from being maintained above the predetermined target charge-state value and increasing the predetermined target charge-state value when the critical conditions of use of the battery are detected, such as to anticipate activating the battery float-charge phase.

Claims

1-8. (canceled)

9. A method for managing a state of charge of a battery comprising a step of activating a float-charge phase of the battery, wherein the battery is intermittently charged with a view to maintaining the state of charge of the battery above a predetermined target state of charge value, the method comprising: detecting critical conditions of use of the battery likely to prevent the state of charge of the battery from being maintained above the predetermined target state of charge value; and increasing the predetermined target state of charge value when the critical conditions of use of the battery are detected, such as to anticipate the step of activating the battery float-charge phase.

10. The method as claimed in claim 9, wherein the battery is a traction battery of a hybrid vehicle comprising an internal combustion engine and an electrical machine, the step of detecting the critical conditions of use of the battery comprising: estimating a maximum charging power that it would be possible to supply to the battery considering current driving conditions of the vehicle and electrical energy supplied by the traction battery to power an on-board low-voltage electrical system of the vehicle, and comparing the maximum charging power thus estimated with a predefined power threshold of detection of the critical conditions of use of the battery.

11. The method as claimed in claim 10, wherein the estimate of the maximum charging power that it would be possible to supply to the battery comprises the following calculation:
P.sub.chargemax(t)=min((P.sub.eng(t)−P.sub.GMT(t))×η.sub.ME+P.sub.dcdc(t),Pbat.sub.max) where P.sub.chargemax(t) is the estimate of the maximum charging power that it would be possible to supply to the battery, P.sub.eng(t) is a maximum mechanical power that the internal combustion engine can supply; Pbat.sub.max is a maximum charging power authorized for the battery; P.sub.dcdc(t) is power consumed by a DC/DC converter used to allow the low-voltage on-board electrical system of the vehicle to be supplied from energy taken on the traction battery; P.sub.GMT(t) is mechanical power required for traction; and η.sub.ME is an efficiency of the electrical machine.

12. The method as claimed in claim 11, wherein the estimate of the maximum charging power is an averaged value derived from average values of a set of instantaneous values of P.sub.dcdc(t) and P.sub.GMT(t) respectively, acquired over a sliding time window.

13. The method as claimed in claim 12, wherein the sliding time window has a duration on the order of 300 s.

14. The method as claimed in claim 10, wherein the increasing the predetermined target state of charge value includes determining a target autonomy value of the vehicle in all-electric mode, an estimate of an electric energy value required to ensure the target autonomy in the current conditions of use of the vehicle and a conversion of the required electric energy value into a state of charge value by using a conversion factor that takes temperature and aging of the battery into account.

15. A device for managing a state of charge of a battery, comprising: battery control means for activating battery charging means designed to charge the battery in an intermittent manner in order to maintain the state of charge of the battery above a predetermined target state of charge value, wherein said control means are able to detect critical conditions of use of the battery likely to prevent the state of charge of the battery from being maintained above the predetermined target state of charge value and to command an increase of the predetermined target state of charge value when the critical conditions of use are detected, so as to anticipate an activation of the battery charging means.

16. A hybrid motor vehicle, comprising: a traction battery; and the device for managing the state of charge of the battery as claimed in claim 15.

Description

[0029] The following description is given with reference to a hybrid vehicle equipped with a hybrid powertrain comprising an internal combustion engine and at least one electric motor, where the “takeoff” phase of the vehicle while the vehicle is at a standstill and at low speeds (approximately 0 to 15 km/h) is ensured by the electric motor and via the electrical power from the traction battery. In order to be able to ensure the capacity of the battery to supply the energy required for traction, particularly that required for vehicle take-off without prior immobilization for charging at a standstill, the method of the invention provides for detecting critical conditions of use prejudicial to maintaining the state of charge of the battery in order to be able to activate, as required, a dedicated mode for preserving the electric energy of the battery.

[0030] To do this, a certain number of variables, already available in the vehicle, are required, including: [0031] the vehicle speed: ν.sub.veh(t); [0032] the power consumed by the DC/DC converter: P.sub.dcdc(t) (the DC/DC converter is conventionally used to make it possible to supply, from the energy drawn on the traction battery, the on-board low-voltage electrical system of the vehicle (14 VDC), on which an electrical power is available and consumed by the various electrical loads installed on board the vehicle and electrically connected to the onboard electrical system); [0033] the power supplied by the powertrain to the wheel, corresponding to the product of the torque demand at the wheel expressed by the driver (via the accelerator) and the rotation speed of the wheel: P.sub.GMT(t)=T.sub.GMT(t)×ω.sub.wheel(t) [0034] an estimate of the maximum charging power that it would be possible to supply to the battery. This value is calculated as follows:

P.sub.chargemax(t)=min((P.sub.eng(t)−P.sub.GMT(t))×η.sub.ME+P.sub.dcdc(t),Pbat.sub.max)  (1) [0035] with the following convention: a positive electrical power is a load power of the battery.

[0036] P.sub.eng(t) is the maximum mechanical power that the internal combustion engine can supply in the most favorable gear ratio. By calculating the engine speed on all existing ratios, its maximum torque on each ratio can be estimated, the product of the maximum torque and the speed giving the maximum power of the engine on each ratio, P.sub.eng(t) being given by the highest power obtained on all the ratios.

[0037] Pbat.sub.max is the maximum charging power authorized for the battery and the electric machine, this value is thus a consolidation of the performance levels that the machine can reach and the battery limitations calculated by the BMS (Battery Management System).

[0038] In the expression (1) above, we begin from the maximum mechanical power that the engine can supply P.sub.eng(t) and we subtract P.sub.GMT(t), namely the mechanical power required for traction. The remaining mechanical power (if any) is converted to electrical power via an estimated machine efficiency given by η.sub.ME. From the electrical power obtained, we subtract P.sub.dcdc(t), the electrical power that is drawn by the DC/DC converter. The resulting electrical power is reduced by Pbat.sub.max, the maximum power that can be sent to the battery.

[0039] Two distinct cases of use of the vehicle will be described below to illustrate the utility of the previous calculation for estimating the maximum charging power that it would be possible to supply to the battery.

[0040] A first use case concerns a phase of driving the vehicle at a constant speed of 50 km/h. In this case, P.sub.GMT(t) can be estimated at a low value, 10 kW for example. The value P.sub.eng(t) can be estimated at a high value. The maximum power of the engine being considered as equal to 80 kW for example, P.sub.eng(t) can then be estimated at 60 kW. P.sub.dcdc(t) is set at an average value, equal to −500 W, for example, and η.sub.ME is set at 80%.

[0041] In these conditions, the maximum theoretical charging power can be estimated at (60−10)*0.8−0.5=39.5 kW.

[0042] Nevertheless, in practice, the maximum charging power authorized for the battery is lower, equal to 20 kW for example. Thus, the maximum charging power that it would be possible to supply to the battery P.sub.chargemax(t) is ultimately estimated at 20 kW in this use case. This result reflects the fact that, if desired, 20 kW could be transferred to the battery. This does not mean that it is the command that will be applied to the vehicle. In contrast, considering the level of power that could be transferred to the battery, it can be considered that if the entire route of the vehicle takes place in these conditions of use, the probability of not being able to maintain the state of charge of the battery is zero.

[0043] Now let's examine a second case of use concerning a take-off phase of the vehicle, for example at 5 km/h. In this case, P.sub.GMT(t) will depend on the acceleration requested by the driver, but it can reach 15 kW, for example, on a frank takeoff. However, in this case of use, P.sub.eng(t) is zero, since, as explained above, the internal combustion engine cannot participate in the traction at this speed. The same values are retained for P.sub.dcdc(t) and η.sub.ME as those set for the first case of use, namely P.sub.dcdc(t)=−500 W and η.sub.ME=80%. However, in this case of use, the electric machine will operate in traction and will thus consume electric energy and no longer produce it, so that its actual yield reverses to 1/80%.

[0044] In these conditions, the maximum theoretical charging power can be estimated at (0−15)*(1/0.8)−0.5=−19.25 kW. Here, the maximum charging power is negative corresponding in fact to a discharge power. This illustrates the fact that in these conditions of use, and despite any desire to recharge the battery, discharge of the battery to −19.25 kW is inevitable. One can therefore imagine that along a route having many takeoffs, and along which the speed rarely exceeds 15 km/h, a speed at which the internal combustion engine can be used, there is a real probability of not being able to maintain the state of charge of the battery.

[0045] According to an embodiment, in order to “extrapolate” the instantaneous values of the variables described above for characterizing conditions critical to maintaining the state of charge of the battery, the sliding average method is used on a passed time window. The instantaneous values of the variables obtained in a sliding time window are thus averaged to determine a filtered signal therefrom. The length of the sliding time window is a calibration parameter of the strategy for preserving the state of charge of the battery, the order of magnitude of which is 300 s, for example. The drawback in using the sliding average is that it requires that all the elements making up the averaged sample be saved in memory. The variables used are, for example, acquired at a sampling frequency of 1 Hz, so that for a time window of 300 s, each variable must store 300 values. The RAM memory need is consequently adapted in the computer implementing the strategy for preserving the state of charge of the battery.

[0046] Thus, according to this embodiment, their averaged value is deduced from the instantaneous values of the four variables acquired as described above: [0047] the average speed of the vehicle: ν.sub.veh.sup.avg(t); [0048] the average power consumed by the DC/DC converter: P.sub.dcdc.sup.avg(t); [0049] the average power supplied by the powertrain to the wheel P.sub.PT.sup.avg(t); [0050] the maximum average charging power: P.sub.chargemax.sup.avg(t).

[0051] The maximum average charging power is the variable that will be used to determine whether or not the conditions of use are critical to maintaining the state of charge of the battery. For example, if, on average, over the duration of the sliding temporal window, i.e. over the last 300 seconds of running according to the example given above, the estimated maximum average charging power is: [0052] >>0, then, in these conditions, there is no reason to consider the risk of not being able to maintain the state of charge of the battery. [0053] close to 0, the risk of not being able to maintain the state of charge of the battery is to be considered. [0054] <0, there is a real risk of not being able to maintain the state of charge.

[0055] The power detection thresholds of critical conditions of use for the value of P.sub.chargemax.sup.avg(t), and the hystereses to avoid them, are advantageously calibration parameters of the strategy for preserving the state of charge of the battery.

[0056] If the conditions of use are not considered critical, the target state of charge value of the battery considered by the energy management law remains constant (of the order of 20%, for example), in order to promote repeatability. In the case of detection of critical conditions of use, the strategy for preserving the state of charge is thus activated, and a step for increasing the target state of charge value is implemented. More precisely, the increased target state of charge value is calculated as follows: Firstly, a target autonomy is determined, noted as Autonomy.sub.target, that we want to guarantee for the vehicle in all-electric mode (autonomy in ZEV, “Zero Emission Vehicle,” mode), in the order of 5 km, for example.

[0057] The energy required to ensure this target autonomy is estimated in the current conditions of use of the vehicle:

[00001]${\mathrm{Energy}}_{\mathrm{target}}\left(t\right)=\left[\frac{1}{{\eta }_{\mathrm{ME}}}.Math.P_{\mathrm{PT}}^{\mathrm{avg}}\left(t\right)+P_{\mathrm{dcdc}}^{\mathrm{avg}\left(t\right)}\right]\times \frac{{\mathrm{Autonomy}}_{\mathrm{target}}}{v_{\mathrm{veh}}^{\mathrm{avg}}\left(t\right)}$

[0058] where:

[00002]$\frac{1}{{\eta }_{\mathrm{ME}}}.Math.P_{\mathrm{PT}}^{\mathrm{avg}}\left(t\right)$

is the average electrical power required for traction; P.sub.dcdc.sup.avg(t) is the average electrical power consumed by the DC/DC converter, and the quotient

[00003]$\frac{{\mathrm{Autonomy}}_{\mathrm{target}}}{v_{\mathrm{veh}}^{\mathrm{avg}}\left(t\right)}$

expresses the duration required to cover the target autonomy.

[0059] Then, the estimated target energy, expressed in W/h, is translated into a percentage of target state of charge SOC_target, based on the conversion factor provided by the BMS and which takes the temperature and aging of the battery into account. Finally, the target state of charge value thus determined is limited between fixed minimum and maximum values.

[0060] It should be noted that when the conditions of use are not considered to be critical, an increase in the maximum average charging power P.sub.chargemax.sup.avg(t) is noted, leading to deactivation of the strategy for preserving the state of charge of the battery, and the target state of charge value will then return to its initial constant value.

[0061] The single appended FIGURE shows the advantages of implementing the strategy for preserving the state of charge of the battery as described above. FIG. 1 shows the speed curve of the vehicle as a function of the time according to a scenario comprising a first phase of normal driving followed by a second traffic jam phase with a 5% incline and high consumption of the electrical accessories of the vehicle and, in parallel, the curve of the maximum average charging power as estimated according to the principles outlined above and that of the state of charge of the battery (SOC).

[0062] The scenario, illustrated as an example in the FIGURE, starts with a conventional driving phase in extra-urban conditions, the initial state of charge is 65%; the vehicle is thus moving in ZEV mode, and the internal combustion engine is not used. As illustrated, at t=1000 s, the vehicle enters a traffic jam phase on an incline. The estimate of the battery charging potential, calculated by the strategy for preserving the state of charge based on the maximum charging power that it would be possible to supply to the battery in these conditions of use, then begins to drop and it closely approaches 0 at around t=1200 s. Consequently, the detection of these critical conditions triggers the activation of the strategy for preserving the state of charge. In accordance with the principles outlined above, the target state of charge value of the battery SOC_target, initially set at 20% according to the example in the FIGURE, is increased from 20 to 35%. At t=1800 s, the state of charge of the battery falls below the target state of charge value SOC_target, the vehicle exits ZEV mode driving and the strategy commands the start of maintaining the state of charge of the battery. The internal combustion engine thus starts and, when it can (vehicle speed>15 km/h), drives the electric machine operating in regenerative mode to charge the battery. As shown in the FIGURE, battery charging is not however sufficient to ensure that the state of charge of the battery is perfectly maintained in relation to the increased target state of charge value, and the state of charge of the battery decreases slowly. However, considering the dotted line, which represents an extrapolation of the change in the state of charge of the battery without implementation of the strategy, i.e. if the target state of charge value had remained at its initial value of 20% and the vehicle had not switched over to the float charge, it can be estimated that the state of charge of the battery would have reached the value of 20% at approximately t=3000 s and it is at this time only that the float charge of the battery would have been activated. Thus, this example shows that the strategy according to the invention, owing to the increase in the target state of charge value when conditions critical to maintaining the state of charge of the battery are detected, makes it possible to anticipate the activation of the maintenance of the state of charge of the battery by approximately 1200 s and thus preserve the state of charge of the battery. According to this example, at t=3000 s, the state of charge of the battery, when the strategy of the invention is implemented, is greater by approximately 12% than that which the battery would have had without the use of said strategy. This margin will advantageously allow the implementation of the battery charging phase to be delayed, as discussed in patent document FR2992274 cited above.

[0063] In addition, when the traffic jam phase is finished, the maximum charging power P.sub.chargemax.sup.avg(t) will increase until it exceeds the predefined power detection threshold of the critical conditions of use, where the target state of charge value will return to its nominal value of 20% according to the example and where the electric power will be consumed again.

[0064] The calculation means implemented to estimate the maximum charging power P.sub.chargemax.sup.avg(t) to be compared with a predefined power detection threshold in critical conditions of use for the activation of the strategy for preserving the state of charge of the battery, are implemented by a computer onboard the vehicle, for example a computer adapted to control the powertrain of the vehicle as a whole.