METHOD FOR CALCULATING AN OFFICIAL RATIO RELATED TO THE PREDICTED RANGE OF A MOTOR VEHICLE

Abstract

A method for calculating an official ratio (CEVRR) relating to the predicted range of an electric vehicle of interest, the method comprising providing a certified range (UNR) measured under homologation conditions on the vehicle in its new condition, with reference to a reference driving cycle, including urban (UDDS) and highway (HFDS) driving phases; calculating the average current energy consumption during the urban and highway driving phases, based on the state of health (SOHR) of the electric battery, the usable energy capacity (UBE), and the total mileage driven; calculating the first and second predicted ranges (RG1, RG2), starting from a fully charged battery, over the urban and highway driving phases; adding the first and second predicted ranges via a predefined weighting to obtain a total predicted range (RGT), which is then divided by the certified range to obtain the official ratio. Figure 3

Description

Title of the invention: METHOD FOR CALCULATING AN OFFICIAL RATIO RELATING TO A PREDICTED AUTONOMY OF A MOTOR VEHICLE

[0001] The invention relates to a method for calculating an official ratio relating to a predicted autonomy of an electric traction vehicle.

[0002] The official ratio in question is representative of a drift in the characteristics of the vehicle of interest compared to its new condition, particularly with regard to regulations of Californian origin.

[0003] The invention also relates to a device on board an electrically powered vehicle having the function of calculating the official ratio in question.

[0004] The driving range in electric traction mode of electrified vehicles is determined during approval tests defined by regulatory procedures.

[0005] Bench test cycles, usually carried out with the help of a driving robot, make it possible to determine the driving autonomy.

[0006] Regulatory bodies in the United States of America, including the state of California, refer to a reference combined driving cycle called here EPA2 in relation to the SAE J1634 standard.

[0007] The EPA2 reference combined driving cycle includes urban driving phases, road / motorway driving phases and, for certain variants of the test protocol, where applicable, constant speed driving phases.

[0008] In addition, the state of California has recently introduced the requirement for automobile manufacturers to calculate and make available to the authorities, during the life of the vehicle, an official ratio relating to the mileage range of said vehicle in its current condition compared to the mileage range of the vehicle in new condition, this ratio referring to the ranges measured under the conditions of the regulatory protocol. For the record, this ratio, called here the official ratio, is called Certified Electric Vehicle Range Retention (CEVRR) in the original English in the Californian prescription.

[0009] This official ratio is the quantified image of a drift in the characteristics of the vehicle of interest compared to its new condition, mainly due to its aging. Generally the electrical capacity of the battery erodes over time, and moreover the efficiency of certain components in the powertrain may degrade over time, and / or resistance factors may increase.

[0010] Note that this ratio is a dimensionless number (a percentage ratio) and the kilometer ranges can be expressed indifferently in miles or in kilometers of this fact.

[0011] Californian regulations also provide for in-service verifications, known as "ISV" (for "In-Service Verification" in English), of the effective autonomy of the vehicle in its current state of aging, based on real measurements in reference to the EPA2 reference combined driving cycle.

[0012] In the state of the art, methods are known for estimating the autonomy in use of an electric vehicle, that is to say, a distance in kilometers that the driver can still hope to travel before his battery pack is discharged and the vehicle immobilized. These known methods provide an autonomy calculated according to the recent average use of the driver, but do not provide the predicted autonomy of interest in the present document.

[0013] Document FR3104263A1 describes a method for estimating the autonomy of an electric vehicle from the state of health of the electric traction battery of the vehicle, taking into account the combination of calendar aging and aging by cycling of the battery. Document FR3015048Al discloses a method for evaluating a quantity of energy available in an electric vehicle electric battery, taking into account aging of the battery, so as to determine the autonomy of the vehicle. These disclosures of the state of the art essentially deal with the impact of aging on the energy available in the electric traction battery.

[0014] The inventors sought to provide the official ratio sought, in a simple, reliable and precise manner, and this in a transparent manner for the user of the vehicle.

[0015] To this end, the present invention proposes a method for calculating an official ratio relating to a predicted autonomy of a vehicle of interest, representative of a drift in the characteristics of the vehicle of interest compared to its new condition, in particular with regard to regulations of Californian origin, the vehicle of interest being electrically powered and comprising an electric battery, characterized in that the method comprises: - have an approved autonomy (UNR) measured under approval conditions on the vehicle of interest in new condition or on a similar vehicle, with reference to a reference driving cycle (EPA2), which contains urban driving phases (UDDS) and motorway driving phases (HFDS), - estimate or acquire a state of health (SOHR) of the electric battery and a useful energy capacity (UBE) of the electric battery, on the vehicle of interest in its current state, - acquire the total mileage traveled by the vehicle of interest, - a consumption calculation step including a calculation of a first current average energy consumption per unit distance (CS1) in the urban driving phases and a second average current energy consumption per unit distance (CS2) in motorway driving phases, depending on the state of health (SOHR) of the electric battery, the useful energy capacity (UBE) and the total mileage traveled, - a range calculation step comprising a calculation of a first predicted range (RG1) of the vehicle of interest, from its fully charged battery, over the urban driving phases and a calculation of a second predicted range (RG2) of the vehicle of interest from its fully charged battery, over the motorway driving phases, - a final calculation step in which the first and second predicted autonomies are added via a predefined weighting, to obtain a total predicted autonomy (RGT) which is divided by the approved autonomy (UNR) in order to obtain the official ratio (CEVRR).

[0016] Thanks to the provisions promoted above, it is possible to provide an accurate and reliable estimate of the total predicted autonomy and the official ratio.

[0017] It is noted that the calculation of the official ratio can be done only from time to time, it can be repeated for example after having traveled a certain distance and / or after a certain period of time such as a week or a month, the values ​​of this official ratio only evolve slowly over time.

[0018] In practice, the official ratio noted CEVRR is expressed by the division CEVRR = RGT / UNR, where RGT is the total predicted autonomy here and UNR is the approved autonomy.

[0019] The official ratio is equal to 1 (or 100%) when the vehicle of interest is new, then it slowly decreases as it is used (calendar aging, cycling aging and mileage aging). When the official ratio approaches a threshold of 0.7 (70%), or another threshold depending on the type of electrochemistry of the battery cells, it may be time to plan a replacement of the battery pack. This official ratio can be a relevant indicator in the context of a sale of the vehicle for used sale in addition to the information on mileage traveled, to estimate in particular the financial value of the vehicle.

[0020] This official ratio can be verified if necessary by the authorities, via real tests carried out on the vehicle in question under the conditions of the EPA2 approval cycle.

[0021] According to one embodiment, the consumption calculation step comprises: - have a first calibration table giving a first correction factor for urban driving phases, the first correction factor being a function on the one hand of the state of health of the electric battery, and on the other hand of the useful energy capacity, - have a second calibration table giving a second correction factor for motorway driving phases, the second correction factor being a function on the one hand of the state of health of the electric battery, and on the other hand of the useful energy capacity.

[0022] The first correction factor acts as a multiplying factor of the average energy consumption approved for urban driving phases (CSH1).

[0023] The second correction factor acts as a multiplying factor of the average energy consumption approved for motorway driving phases (CSH2).

[0024] According to one embodiment, the consumption calculation step further comprises: - having a third calibration table relating to the total mileage traveled, giving a third correction factor.

[0025] The third correction factor acts as a multiplying factor of the average energy consumption approved per unit distance over urban driving phases and motorway driving phases.

[0026] According to one embodiment, the respective calculations of the first and second predicted autonomies comprise a division of the useful energy capacity by the current average energy consumption per unit distance, respectively for the urban driving phases and for the motorway driving phases.

[0027] In other words, if RG1 is the first predicted autonomy, CS1 is the first current average energy consumption per unit distance, and UBE is the useful energy capacity, then RG1 = UBE / CS1.

[0028] Similarly, if RG2 is the second predicted autonomy, CS2 is the second current average energy consumption per unit distance, then RG2 = UBE / CS2

[0029] According to one embodiment, in the final calculation step, a first weight is assigned to the first predicted autonomy and a second weight is assigned to the second predicted autonomy, the sum of the first and second weights being equal to 1.

[0030] In other words, if W1 is the first weight and W2 is the second weight, then the total predicted autonomy is: RGT = W1 * RG1 + W2 * RG2, with Wl+W2=l.

[0031] According to one embodiment, the first weight is equal to 0.55 and the second weight is equal to 0.45. In other words, W1 = 0.55 and W2 = 0.45.

[0032] According to one embodiment, the reference driving cycle (EPA2) comprises a first urban driving phase, then a first motorway driving phase, then a second urban driving phase, then a first constant speed driving phase, then a third urban driving phase, then a second motorway driving phase, then a fourth urban driving phase and then a second constant speed driving phase. This is a cycle representative of typical driving.

[0033] The invention also relates to an on-board device comprising a calculator battery management system configured to implement the method as briefly described above. It is the battery management computer, also called BMS, which carries out most of the steps in the method promoted above, apart from the total mileage traveled which is obtained from the instrument cluster or another on-board computer of the vehicle.

[0034] The invention also relates to an electric vehicle comprising a battery pack, an electric powertrain and a battery management computer configured to implement the method as briefly described above.

[0035] The invention will be further detailed by the description of non-limiting embodiments, and on the basis of the appended figures illustrating variants of the invention, in which: [Fig.l] is a schematic representation of a reference combined driving cycle used by the United States Environmental Protection Agency, named in the original English language 'Environmental Protectoin Agency'; [Fig.2] shows a schematic diagram of an electric traction chain in an electric traction vehicle; [Fig.3] schematically shows a functional flowchart of the method implemented in the present invention.

[0036] An electric vehicle VH comprises an electric battery 1, also called a battery pack, which comprises a plurality of electrochemical cells as known per se. We are interested here in 100% electric vehicles without an internal combustion engine, all the autonomy being provided by the battery pack. The most common traction batteries on electric vehicles are batteries based on a Lithium-Ion type electrochemistry.

[0037] Regarding the quantity of energy stored in the battery pack, in practice we are talking about several tens of kWh. A 100% electric vehicle battery has an energy storage capacity typically between 40 kWh and 100 kWh, depending on the target autonomy, the weight and the consumption of said vehicle.

[0038] The autonomy of the vehicle of interest in the present document is quite substantial, we are talking about at least 250 km. The target autonomies of the vehicles covered by the invention can range from 250 km to 600 km, without excluding higher autonomies.

[0039] The term 'electrically driven vehicle' also covers electrically driven vehicles. The main electric motor 3 may in fact be arranged either on the rear axle of the vehicle or on the front axle of the vehicle, or a motor unit on each axle. The vehicle in question may be a private vehicle, a utility vehicle, a truck, a bus; there is no limitation on the type of vehicle covered by the present invention.

[0040] The electric powertrain, illustrated in [Fig.2], comprises the battery pack 1, an electric machine 3, an inverter 2 controlled by a control unit 6 of the electric machine, a transmission 4 comprising a reducer and a differential, a battery management computer 5, called in practice BMS by the English name (Battery Management System). The output of the differential drives a wheel shaft which itself drives a wheel 10 (only one shown in [Fig.2]). A braking device 7 is provided on each of the wheels. The high voltage network HV, coupled to the battery 1, is connected to the 12 Volt 12V network by a DC / DC converter marked 8.

[0041] The vehicle of interest in new condition, or a similar vehicle, passes homologation tests.

[0042] This results in an approved UNR autonomy measured under approval conditions on the vehicle of interest in new condition or on a similar vehicle, with reference to an EPA2 reference driving cycle.

[0043] The EPA2 reference driving cycle contains UDDS urban driving phases and HFDS motorway driving phases (this corresponds to the acronym 'HFEDS' in the EPA2 combined cycle).

[0044] More precisely, as illustrated in [Fig. 1], the reference driving cycle EPA2 comprises a first urban driving phase UDDSi, then a first motorway driving phase HFDSi, then a second urban driving phase UDDS2, then a first constant speed driving phase CSCi, then a third urban driving phase UDDS3, then a second motorway driving phase HFDS2, then a fourth urban driving phase UDDS4, then a second constant speed driving phase CSC2.

[0045] The reader may refer to the SAE J1634 standard “Battery Electric Vehicle Energy Consumption and Range Test Procedure” in its latest revision of April 2021.

[0046] Approval tests or calibration tests also make it possible to establish or measure reference consumption data.

[0047] The average energy consumption approved for each urban driving phase CSH1 of the EPA2 reference driving cycle and the average energy consumption approved for each motorway driving phase CSH2 of the EPA2 reference driving cycle are officially established and recorded.

[0048] Generally speaking, for a given road law and a determined mass of the electric vehicle, the kilometer driving range in electric traction mode of the vehicle is given by the maximum quantity of usable electrical energy in the fully charged battery pack divided by the average energy consumption of the vehicle for a unit distance traveled (kilometer). The useful energy capacity noted UBE is the quantity of usable electrical energy in the battery pack when it is fully charged, in its current state of aging.

[0049]

[0050] In the present invention, the manner of estimating the useful energy capacity UBE in the fully charged battery pack of the vehicle is not addressed. The UBE information considered here is determined by a dedicated algorithm hosted in a computer of the vehicle, for example the battery management computer BMS, and is provided by the latter to the on-board software module of interest. Reference may be made, for example, to the two prior art documents cited in the introduction above in this document.

[0051] The UBEH information is the maximum certified usable energy quantity of the fully charged battery pack of the vehicle in new condition. The UBEH information is available information from the vehicle, declared during the approval for obtaining the certificate of conformity. The useful energy capacity UBE can be expressed as a proportion of UBEH. UBE decreases over time starting from UBEH.

[0052] The SOHR information represents the estimated state of health of the battery pack which deteriorates with its aging and which is typically estimated as a function of the ratio between its current internal ohmic resistance RIc and its internal ohmic resistance in the new state RIn, namely, SOHR = G(RIc / RIn) G being a bijective function.

[0053] The determination of the current internal ohmic resistance RIc is unknown in itself and therefore not detailed here. The determination of the current ohmic resistance RIc and the state of health information SOHR are functions that can be performed by the battery management computer 5 (BMS).

[0054] As the vehicle is used, the total mileage traveled KMT increases, the useful energy capacity UBE undergoes erosion, the state of health SOHR also undergoes erosion, these two erosions depend on the number and depth of charge / discharge cycles. This erosion phenomenon is a slow drift which is a materialization of the aging of the vehicle's battery pack.

[0055] Furthermore, the energy consumption of the vehicle operating in electric traction mode can be affected by various elements related to the aging of the vehicle, in particular the items indicated and commented on below, from A) to l):

[0056] A) Road law and vehicle mass affect the energy consumption of the vehicle. However, for the estimation of the state of the approved autonomy, the measurements for the in-service verification "ISV" will be carried out by taking the characteristics of the certificate of conformity for the new vehicle. Road law and vehicle mass therefore have no impact here and it is not necessary to model any evolution over time.

[0057] B) The losses linked to the braking device 7 do not change significantly over time and are not taken into account. Indeed, the residual torque for 0 bars of hydraulic pressure in the braking system is integrated into the road law, so that any possible evolution over time will be compensated by the test bench to find the road law of the new vehicle. A marginal evolution can occur when the braking system is of the so-called "hybrid" type allowing a mix of dissipative braking and regenerative braking in the electric drive train of the vehicle. In such a braking system, the residual pressure is dependent on the action of a spring which will tend to relax over time, but will only induce a negligible drop in the residual hydraulic pressure.

[0058] C) The regeneration capacity of the battery pack by regenerative braking is affected by the aging of its electrochemical cells. The aging of the electrochemical cells results in an increase in their internal resistance. When the state of charge known as "SOC" (for "State of Charge" in English) of the battery pack is high, the maximum charging current of the battery pack must be limited so as not to exceed a maximum voltage of the cells. Indeed, the maximum voltage Vmax of a cell is given by the equality Vmax=Vvide-Rint*Imax, with Vvide, Rint and Imax being respectively the no-load voltage of the cell, its internal resistance and the maximum charging current. The reduction in the maximum charging current of the battery pack results in a decrease in the recovered electrical power, which results in an increase in the energy consumption of the vehicle.The health status of the battery pack, represented by the above-mentioned SOHR information, is representative of the internal resistance of the battery pack cells and is taken into account to model this aging effect.

[0059] D) The maximum amount of usable electrical energy in the fully charged battery pack decreases over time. The maximum amount of current usable electrical energy of the fully charged battery pack, i.e., at the instant in question, is indicated by the aforementioned UBE information.

[0060] In the electric traction mode, the energy consumption of the vehicle is determined by a weighting between the consumption at the start of the cold cycle (UDDSi in [Fig.l]) and the consumption at the end of the hot cycle. The weight of the consumption of the cold cycle compared to that of the hot cycle depends on the quantity of usable electrical energy. The quantity of usable electrical energy, represented by the UBE information, therefore affects the energy consumption of the vehicle determined in accordance with the EPA2 protocol and is taken into account because it decreases over time.

[0061] E) The rotating electrical traction machine 3 of the vehicle may undergo a change in its performance with aging. The demagnetization of the permanent magnets at the end of their life can lead to a change in the energy efficiency of the machine. The impact of the demagnetization of the magnets is difficult to evaluate, because it can be positive, at high speed for example, leading to a reduction in the machine's energy losses, or, on the contrary, be negative, with, for example, high torques at low speed which lead to an increase in the machine's losses. In any case, the effect of demagnetization of the magnets remains limited. By adopting a pessimistic approach to the impact of aging on machine losses, we will consider here a linear increase in machine losses as a function of mileage, informed by the aforementioned KMT information, to model this effect of aging.

[0062] F) The transmission reducer 4 associated with the rotating electrical traction machine of the vehicle is little affected by aging. Except in the event of a malfunction, the losses due to the gear teeth do not change over time. The losses due to the bearings decrease slightly over time. The alteration of the characteristics of the lubricating oil is considered here to be negligible. The same is true, mutatis mutandis, for the differential.

[0063] G) The power inverter 2 ensuring the alternating-direct conversion (called "AC / DC") between the battery pack and the rotating electrical traction machine is affected over time by an increase in the conduction resistances of its power transistors (resistance called "Rdson" for "MOSFET" type transistors). At the end of its life, the potential increase in inverter losses is estimated at approximately 10%, with a pessimistic approach. Here, a linear increase in inverter losses as a function of mileage, provided by the aforementioned KMT information, will be considered to model this effect of aging.

[0064] H) The DC-DC converter 8 providing DC-DC conversion (called “DC / DC”) between the high voltage power supply network (“HV” network) and the low voltage power supply network (12 V network) has a low weight in the energy consumption of the vehicle. The evolution of its efficiency over time is not taken into account here.

[0065] I) Concerning the accessories on the high voltage HV network and on the low voltage 12 V network, those which are activated during the tests of the EPA2 protocol have energy yields which are not very sensitive to aging. However, the increase over time of the internal resistance of the battery pack can cause an increase in the internal temperature thereof, with consequent increased stress on the components of the cooling system. The state of health of the battery pack, represented by the aforementioned SOHR information, is representative of the internal resistance of the battery pack and is taken into account here to model this effect of aging.

[0066] We therefore note that only some of the items A) to I) give rise to consideration in relation to the total mileage traveled, and some in relation to the state of health SOHR and the useful energy capacity UBE.

[0067] In [Fig.3], the boxes marked MULT implement a multiplication operation, the boxes marked DIV implement a division operation, and the box marked ADD implements an addition operation.

[0068] To summarize, the method comprises the following steps: a- have an approved UNR autonomy measured under approval conditions on the vehicle of interest in new condition or on a similar vehicle, with reference to an EPA2 reference driving cycle, which contains UDDS urban driving phases and HFDS motorway driving phases.

[0069] The approval work also makes it possible to establish the average approved energy consumption for each phase of urban driving CSH1 and the average approved energy consumption for each phase of motorway driving CSH2, on the EPA2 reference driving cycle.

[0070] b- estimate or acquire a SOHR state of health of the electric battery and a useful energy capacity UBE of the electric battery, on the vehicle of interest in its current state, as explained above.

[0071] c- acquire the total mileage traveled KMT by the vehicle of interest. The total mileage traveled KMT is obtained from the instrument cluster, a dashboard, or another on-board computer of the vehicle.

[0072] d- calculate a first current average energy consumption per unit distance CS1 in the urban driving phases UDDS and a second current average energy consumption per unit distance CS2 in the motorway driving phases HFDS, depending on the health status SOHR of the electric battery, the useful energy capacity UBE and the total mileage traveled KMT.

[0073] Step d- advantageously comprises: dl- have a first calibration table C2D-1 giving a first correction factor FC1 for the UDDS urban driving phases, the first correction factor being a function on the one hand of the SOHR state of health of the electric battery, and on the other hand of the useful energy capacity UBE,

[0074] d2- have a second C2D-2 calibration table giving a second correction factor FC2 for HFDS motorway driving phases, the second correction factor being a function on the one hand of the SOHR state of health of the electric battery, and on the other hand of the useful energy capacity UBE.

[0075] The first and second calibration tables, C2D-1 and C2D-2, are also called in practice two-dimensional maps, which may comprise for example between 100 points and 300 points. According to an exemplary embodiment, the values ​​of the points which form the values ​​of the correction factors FC1, FC2 are typically between 0.9 and 1. Values ​​lower than 0.9 are not excluded.

[0076] Step d- advantageously further comprises:

[0077] d3- have a third CALKM calibration table relating to mileage total traveled giving a third correction factor FC3.

[0078] In the illustrated example, a CALKM mapping is used to adjust the weight of the total mileage KMT. In a variant, one can have a simpler relationship, for example an affine or low-degree polynomial function which makes it possible to obtain a third correction factor FC3.

[0079] For example, we could choose a simple relationship of the type FC3 = 1 - [3 x KMT, [3 being a scaling coefficient. FC3 can be worth 0.9 for a total mileage traveled of 80,000 km, without this example being limiting.

[0080] Finally, regarding the consumption calculation step d-, in the illustrated example, the following multiplications are carried out (reference 21 in [Fig.3]) to obtain the estimated consumption of the vehicle in its current state.

[0081] CS1 = CSH1 xFCl xFC3

[0082] CS2 = CSH2 x FC2 x FC3

[0083] The process continues with: e- calculate a first predicted autonomy RG1 of the vehicle of interest, from its fully charged battery, on the urban driving phases and a second predicted autonomy RG2 of the vehicle of interest from its fully charged battery, on the motorway driving phases.

[0084] The following divisions are carried out (reference 22 in [Fig.3]) to obtain the predicted autonomies of the vehicle in its current state: RG1 = UBE / CS1 and RG2 = UBE / CS2.

[0085] f- a final calculation step in which the first and second predicted autonomies are added via a predefined weighting, to obtain a total predicted autonomy RGT which is divided by the approved autonomy in order to obtain the official ratio CEVRR.

[0086] In practice, the multiplication boxes marked 23, with the addition box which follows, carry out the operations: RGT = W1 * RG1 + W2 * RG2, with Wl+W2=l.

[0087] According to the EPA2 reference driving cycle, we have W1 = 0.55 and W2 = 0.45.

[0088] The division box on the right of [Fig.3] performs the operations CEVRR = RGT / UNR.

Claims

Claims

1. Method for calculating an official ratio (CEVRR) relating to a predicted autonomy of a vehicle of interest, representative of a drift in the characteristics of the vehicle of interest compared to its new condition, in particular with regard to regulations of Californian origin, the vehicle of interest being electrically powered and comprising an electric battery, characterized in that the method comprises: - have an approved autonomy (UNR) measured under approval conditions on the vehicle of interest in new condition or on a similar vehicle, with reference to a reference driving cycle (EPA2), which contains urban driving phases (UDDS) and motorway driving phases (HFDS), - estimate or acquire a state of health (SOHR) of the electric battery and a useful energy capacity (UBE) of the electric battery, on the vehicle of interest in its current state, - acquiring the total mileage traveled by the vehicle of interest, - a consumption calculation step (d-) comprising a calculation of a first current average energy consumption per unit distance (CS1) in the urban driving phases (UDDS) and a second current average energy consumption per unit distance (CS2) in the motorway driving phases (HFDS), depending on the state of health (SOHR) of the electric battery, the useful energy capacity (UBE) and the total mileage traveled, - an autonomy calculation step (e-) comprising a calculation of a first predicted autonomy (RG1) of the vehicle of interest, from its fully charged battery, on the urban driving phases (UDDS) and a calculation of a second predicted autonomy (RG2) of the vehicle of interest from its fully charged battery, on the motorway driving phases (HFDS), - a final calculation step (f-) in which the first and second predicted autonomies are added via a predefined weighting, to obtain a total predicted autonomy (RGT) which is divided by the approved autonomy in order to obtain the official ratio (CEVRR).

2. Method according to claim 1, characterized in that the consumption calculation step (d) comprises: - have a first calibration table (C2D-1) giving a first correction factor (FC1) for urban driving phases (UDDS), the first correction factor being a function on the one hand of the state of health (SOHR) of the electric battery, and on the other hand of the useful energy capacity (UBE), - have a second calibration table (C2D-2) giving a second correction factor (FC2) for the motorway driving phases (HFDS), the second correction factor being a function on the one hand of the state of health (SOHR) of the electric battery, and on the other hand of the useful energy capacity (UBE).

3. Method according to claim 2, characterized in that the consumption calculation step (d) further comprises: - having a third calibration table (CALKM) relating to the total mileage traveled (KMT) giving a third correction factor (FC3).

4. Method according to any one of claims 1 to 3, characterized in that the respective calculations of the first and second predicted autonomies comprise a division of the useful energy capacity (UBE) by the current average energy consumption per unit distance (CS1, CS2), respectively for the urban driving phases and for the motorway driving phases.

5. Method according to any one of claims 1 to 4, characterized in that in the final calculation step (f), a first weight (W1) is assigned to the first predicted autonomy and a second weight (W2) is assigned to the second predicted autonomy, the sum of the first and second weights being equal to 1.

6. Method according to claim 5, characterized in that the first weight (W1) is equal to 0.55 and the second weight (W2) is equal to 0.

45.

7. Method according to any one of claims 1 to 6, characterized in that the reference driving cycle (EPA2) comprises a first urban driving phase (UDDSi), then a first motorway driving phase (HFDSi), then a second urban driving phase (UDDS2), then a first constant speed driving phase (CSCi), then a third urban driving phase (UDDS3), then a second motorway driving phase (HFDS2), then a fourth urban driving phase (UDDS4), then a second constant speed driving phase (CSC2).

8. On-board device comprising a battery management computer (5) configured to implement the method according to one of claims 1 to 7.

9. Electrically powered vehicle comprising a battery pack (1), an electric powertrain and a battery management computer (5) configured to implement the method according to one of claims 1 to 7.

Images