EP3122591A1

EP3122591A1 - Method for estimating the autonomy of an electric or hybrid vehicle

Info

Publication number: EP3122591A1
Application number: EP15718516.6A
Authority: EP
Inventors: Marc Lucea
Original assignee: Renault SAS
Current assignee: Renault SAS
Priority date: 2014-03-24
Filing date: 2015-03-23
Publication date: 2017-02-01
Also published as: FR3018921B1; US10442304B2; FR3018921A1; US20170101026A1; WO2015145053A1

Abstract

A method for estimating the autonomy of an electric vehicle. The present invention concerns a method for estimating the autonomy of an electric or hybrid vehicle on a predefined journey, the method including a step of estimating the energy available in the traction battery of the vehicle depending on the temperature of said battery. The method according to the invention includes a step of calculating a value representative of the change in the temperature of the battery during the journey, said value being used to estimate the available energy. Application: electric or hybrid vehicles

Description

Method for estimating the range of an electric or hybrid vehicle

The present invention relates to a method for estimating the range of an electric or hybrid vehicle. It is particularly applicable to the assessment of the autonomy of electric vehicles equipped with a navigation system.

In the current context of consensus around global warming, the reduction of carbon dioxide (CO2) emissions is a major challenge faced by car manufacturers, the standards being ever more demanding in this area.

In addition to the steady improvement in efficiency of conventional combustion engines, which is accompanied by a reduction in CO2 emissions, electric vehicles ("EV") and thermal hybrid vehicles. Electric ("HEV") is now considered the most promising solution for reducing CO2 emissions.

Different technologies for storing electrical energy have been tested in recent years to meet the needs of EVs. It now appears that lithium-ion cell batteries (Li-ion) are those likely to provide the best compromise between the power density, which promotes the performance in terms of acceleration in particular, and the energy density, which promotes autonomy. However, the use of this Li-ion technology to form traction batteries for EV is not without posing many difficulties, especially if we consider the voltage levels required, of the order of 400 volts (V ), or even considering the high temperature levels generated by the exothermic migration of lithium ions between the electrodes of Li-ion cells, whether at the discharge when the vehicle is rolling or at the load when the driver is plugging his vehicle at a charging station.

At present, the main obstacle to the development of electric vehicles remains their autonomy, which is still limited compared to conventional thermal vehicles. So, to convince potential customers to switch to an electric vehicle, it seems essential to provide the latter with energy gauges as reliable as possible, in order to limit the anxiety of breaking down, by providing the driver with an estimate of the remaining kilometric range that is as realistic as possible. This is a problem that the present invention proposes to solve.

However, the remaining kilometric range depends on a large number of parameters, which include the state of charge of the battery, the driving style of the driver, the total mass of the vehicle, the outside temperature, the conditions traffic or the difference in altitude on the journey. The method usually used is to have periodically estimated by a computer in charge of battery management (commonly referred to as the English abbreviation BMS meaning "Battery Management System"), the energy available in the traction battery. A supervision calculator (commonly referred to as EVC for Electric Vehicle Controller) uses this estimate for, based on distance, traffic and altitude information provided by a GPS system (English abbreviation). Saxon meaning "Global Positionning System"), deduce a prediction of autonomy. The EVC calculator thus performs somehow a prediction of energy required on the planned path, and compares it with the remaining energy provided by the BMS calculator. This approach, however, has several disadvantages in particular situations of temperature. It may be a hot start for a cold run, such as when the vehicle is parked in a "heated" garage and the outside temperature is well below that of the garage. The energy estimate made by the BMS calculator, which is based on its own temperature measurements taken by its sensors in the garage, is generally too optimistic, since the outside temperature at which the battery will actually be exposed for most of the time. trip is lower than that measured before departure, causing additional losses. Equivalently, when the vehicle is parked in full sun while the ambient air temperature is lower than that measured by the BMS calculator before departure, it will tend to overestimate the remaining energy. It can also be a cold start for a warm run, such as when the vehicle is parked in the shade or in an air-conditioned garage, while the outside temperature on the planned route is much better. In this case, the energy estimate provided by the BMS calculator is too pessimistic, since the losses generated by the low temperature are overestimated before departure. This is again a problem that the present invention proposes to solve.

In order to overcome this disadvantage, it is known to

US2013 / 01 10331 A1 a method for predicting the range of an electric vehicle from no longer a measured temperature value, but from a record of temperature values depending on the time of day. In this method, at different times of the day, including day or night and time in the day, are associated with temperature values recorded in the battery pack during trips previously carried out in a nearby time slot. These temperature readings are used to estimate more precisely than with a single temperature value the amount of energy available in the battery and thus to estimate more finely the autonomy of the vehicle. A disadvantage of this method is that the estimation of autonomy does not take into account the geographical peculiarities that can affect the meteorological conditions in general and the temperature in particular, since it implicitly assumes that at a time of the day it's the same temperature everywhere. Thus, in the event of a sudden change in weather conditions, which is likely in the case of journeys lasting several hundred kilometers, the prediction may be far from reality. In particular, if the driver is driving from a hot zone to a colder zone, his range may be overestimated and he may risk failure. This is again a problem that the present invention proposes to solve.

The invention aims in particular to overcome the aforementioned drawbacks, particularly those related to changing weather conditions, including temperature variations on long trips. To this end, the subject of the invention is a method for estimating the autonomy of an electric or hybrid vehicle on a predetermined path, the method including a step of estimating the energy available in the vehicle's traction battery. function of the temperature of said battery. The method according to the invention includes a step of calculating a value representative of the evolution of the temperature of the battery during the journey, said value being used to estimate the available energy.

In one embodiment, the step of calculating the representative value can advantageously include a step of cutting the path in p segments, where p is a strictly positive integer, and a step of estimating the temperature of the battery at the end of each of the p sections.

For example, the step of calculating the representative value may furthermore include that the representative value is equal to the minimum value among the p temperature values of the battery at the end of each of the p segments, or that the representative value is equal to the average value of the p temperature values of the battery at the end of each of the p sections.

Advantageously, the step of cutting the path in p sections may include a step of entering the path by a driver of the vehicle via the interface of a navigation system connected to the vehicle, as well as a step of pre-cutting the path by the navigation system in q sections, where q is a strictly positive integer less than or equal to p, such that the average speed of the vehicle estimated by the navigation system on each of the q sections varies from one section to the next on the path.

The step of cutting the path in p sections may furthermore include, if some of the sections have an estimated duration of travel greater than a predetermined threshold, a second step of redrawing said sections whose travel time is too long, such that the travel time of each of the p segments thus obtained is less than or equal to the threshold.

For example, the step of estimating the temperature of the battery at the end of each of the p segments may include, for i integer varying from 1 to p:

A step of estimating, as a function of the average speed (Vi) estimated on the i ^th section, of the average current (lmoyen_i) passing through the battery during the i ^th section;

A step of estimating the temperature (Tcooling_i), at the beginning of the i ^th section, of a coolant for heating or cooling the battery; • a step of collecting the average outside temperature (Text_i) planned on the i ^th section;

A step of estimating the temperature (Tpack (ti)) of the battery at the moment (ti) at which the vehicle reaches the end of the i ^th section, from:

o the estimated temperature of the battery at the end of the (i-1) th section (Tpack (ti-I)) or the measured temperature (Tpack) of the battery if i = 1, and / or;

o the average current (lmoyen_i) estimated crossing the battery during the ith section, and / or;

o the average outside temperature (Text_i) provided on the ith section, and / or;

o the estimated temperature (Tcooling_i) of the coolant at the beginning of the ith section.

For example, the step of estimating the temperature of the battery at the end of each of the p segments may include estimating, for i integer varying from 1 to p, the temperature (Tpack (ti)) of the battery at the end of the i ^th stretch by the equation:

t 'l) ^ (imoyen i) ² + δ ^■ Text i + Θ ^■ Tcooling i ■ (imoyen i) ² + S ^■ Text i + Θ ^■ Tcooling i

Tpack (ft ^' ) = T ki

Pac (ti -) -

δ + θ

where γ, δ and Θ can be parameters corresponding to thermal characteristics of the battery.

Advantageously, for i integer varying from 1 to p, can be provided by the navigation system the average speed on the i ^th section depending on the state of traffic on said section, and the mean outside temperature (Textj) provided on the i ^st section.

The present invention also relates to a computer comprising hardware and software means implementing such a method.

The present invention finally relates to an electric vehicle or hyubrid comprises such a computer and a dashboard on which to display the estimated autonomy.

Other characteristics and advantages of the invention will become apparent with the aid of the following description made with reference to FIGS. 1 and 2 annexed and which illustrate, by an architecture diagram and a functional diagram respectively, an embodiment of the invention.

FIG. 1 thus illustrates with an architecture diagram an exemplary embodiment of the invention. A battery pack 1 1 of an electric vehicle comprises N cells connected in series, not shown in the figure. A voltage measurement is carried out for each of these N cells, N being typically between 10 and 100 for an electric or hybrid vehicle, and Vcells the N cell voltage measurements. A set of M temperature measurements, Tcells noted, are performed by a BMS 12 computer acting as manager of the battery pack 1 1, by means of sensors inserted in the battery pack 1 1. The current flowing through the battery pack 1 1, noted Ipack, is measured by a sensor not shown in the figure. As explained above, the BMS calculator 12 plays the role of the management computer of the battery pack 1 1. From the input signals Vcells, Tcells and Ipack, the BMS calculator 12 produces the following signals:

• Tpack: it is an estimate or a representation of the temperature of the battery pack 1 1 estimated from the M Tcells measurements; it can be the maximum temperature measured among the M Tcells measurements, or the minimum temperature, or the average, or a vector containing all of these 3 minimum / maximum / average temperatures;

• Energy (Tpack): this is an estimate of the remaining energy in the battery pack 1 1 at Tpack temperature; estimated by conventional techniques described in the state of the art, Energy (Tpack) represents the energy remaining in the battery pack 1 1 for a constant power discharge, it depends both on the state of charge of the pack battery 1 1 at a given instant and its temperature Tpack;

• Energy (Trep): this is an estimate of the energy remaining in the battery pack 1 1, for a temperature value Trep representative of the temperature change of the battery pack 1 1, Trep being calculated according to the invention described in the present application by an EVC calculator 13 acting as the supervision computer of the vehicle;

• Upack: This is the voltage across the battery pack 1 1. In Figure 1, a GPS system 14 acts as a navigation calculator. Depending on the destination entered by the driver, GPS 14 provides the following information:

• Elevation difference: this is the difference in altitude between the starting point and the end point on the route indicated;

• Distance: This is the distance from the start point to the end point, for the route entered by the driver; Distance = [D1; D2; ...; Dq] denotes the vector describing the distances of q different sections forming the path, on which the average speed to be taken into account is different;

• Traffic: This is traffic status information; this signal may for example correspond to the average speed on the journey, which itself depends on the traffic conditions (e.g. stopper, work, type of traffic lane, ...); we denote Trafic = [V1; V2; ...; Vq] the vector describing the q different mean velocity values, on q different sections D1, ..., Dq;

• Text: this is the outside temperature on the trip; Text = [Text_1; Text_2; ...; Text_q] denotes the vector describing the q different mean outside temperature values, on the q different lengths of respective lengths D1, ..., Dq.

The EVC computer 13 therefore acts as a vehicle supervision computer, to which the BMS computer 12, the GPS 14 and the dashboard 15 of the vehicle are connected. From the input signals Text, Traffic, Distance, Elevation, Tpack, Ipack, Energy (Tpack) and Energy (Trep), the EVC computer 13 produces the following signals:

• Trep: it is a representative value of the temperature change of the battery pack 1 1 on the path entered by the driver; the way of calculating this value according to the invention is described later;

· Autonomie_Restante: it is about the remaining kilometric autonomy, estimated on the basis of the path and the conditions of temperature and traffic, and which corresponds to the margin of autonomy beyond the indicated destination;

• Autonomy_Total: This is the total kilometric autonomy, estimated on the basis of temperature and traffic conditions. A thermal management system 16 manages the cooling and heating of the battery pack 1 1 by a stream of air or heat transfer fluid, not shown in the figure. The thermal management system 16 is controlled by the EVC computer 13 via a control signal, the EVC computer 13 knowing the average steady state temperature of the heat transfer fluid when the system 16 is activated. This average steady-state temperature is noted Tcooling: it depends on the characteristics of the fluid and the heating / cooling strategies implemented in the EVC computer 13.

FIG. 2 illustrates in a functional diagram the same embodiment of the invention, in particular the details of the operations performed in the EVC computer 13.

A GPS information pre-processing block 21 performs a digital processing of the Distance, Text and Traffic signals supplied by the GPS system 14, so as to adapt the sectioning made by the GPS system 14 to the internal needs of the EVC computer 13. The redistribution realized in this block 21, from q sections made by the GPS system 14 (where q is a strictly positive integer), makes it possible to produce p new sections (with p integer such that p≥q), whose characteristics, in particular their durations, are adapted to the needs of thermal modeling. Thus, at the output of the preprocessing block 21, the following vectors are obtained

• Distance = [D1; D2; ...; Dp]: this is a vector describing the distances of the p successive sections forming the path;

• Traffic = [V1; V2; ...; Vp]: this is a vector describing the p different average speed values, on p different sections D1 to Dp;

• Text = [Text_1; Text_2; ...; Text_p]: this is a vector describing the p different average outdoor temperature values, on the p different lengths of respective lengths D1 to Dp.

To perform this redistribution, the criterion relates to the duration associated with each section, that is to say the duration ti = Di / Vi for i between 1 and q: these times must be less than a precalibrated threshold noted threshold_duration_tronçon, which can typically be of the order of 1 minute, so that the estimates made by the thermal model of the battery 1 1, which is described in detail later are reliable enough, particularly vis-à-vis the thermal management system 16. Indeed, too long lengths of sections do not correctly reproduce the cooling / heating strategies through the signal Tcooling, as described later . Thus, if the i ^th section provided by the GPS system 14 does not respect ti <threshold_duration_tronçon, then i ^th section is redécoupé in several sub-sections verifying ti '= Di7Vi'<threshold_duration_tronçon. The average outside temperature and the average speed on these sub-sections are identical to those of the initial section, only the distance is adapted. A block 22 of energetic balance linked to the difference in altitude estimates the energy necessary to undergo the change of altitude corresponding to the signal Descent provided by the GPS system 14, noted AE unequated. It is possible, for example, to estimate this energy by: AEdivided = M xgx Descent where M represents the total mass of the vehicle for an average load (typically with 2 passengers), where g represents the acceleration of gravity and where Elevation represents the altitude difference on the route provided by the GPS system 14.

An energy balance block 23 linked to the distance estimates, from the distance and traffic signals provided by the GPS system 14, the energy necessary to travel the distance corresponding to the distance signal supplied by the GPS system 14 under the corresponding traffic conditions. to the traffic signal provided by the GPS system 14, denoted AEdistance. Different methods are described in the state of the art for estimating AEdistance. For example, it is possible to estimate it by: AEdistance = ^ [("· V _i + β ^■ ) · D _i ]

where a and β are vehicle-dependent calibration parameters, where Vi is the average speed provided by the GPS system 14 for the i ^th section of distance Di. This energy balance over the distance takes into account the mechanical and aerodynamic friction, as well as the efficiencies of the electrical components and the power train.

A block 24 named History makes it possible to estimate the driving style of the driver, to possibly update the parameters a and β used in block 23, and the parameters γ, δ and Θ used in a thermal modeling block 26 of the pack. battery 1 1. Depending on whether the driver practices a sporty or economical driving style, these parameters can be updated to improve energy balances and target temperature estimates. The driving style may for example be described by calculating a weighted average or a root mean square of the Ipack current passing through the battery pack 1 1, or the power drawn from the battery pack 1 1, ie Upack x Ipack. A block 25 of Global Energy Balance performs the energy balance for the vehicle as a whole, from the AEdivided, AEdistance, Energy (Tpack) and Energy (Trep) signals. A signal calculated by block 25 is the following: Autonomy_reservative = [Energy (Trep) - AEdifferential - AEdistance] / Specific_consistency (Trep) where Conso_specific, in joules per kilometer, is a calibration value which depends both on the vehicle, as its mass and the type of its electric power train, and the Trep temperature;

Another signal calculated by block 25 is as follows:

Autonomie_totale = Energy (Trep) / Conso_specific (Trep) If the signal Autonomie_restante is positive, an indicator is displayed on the dashboard 15 to inform the driver on the remaining remaining estimated after his trip. Total autonomy can also be displayed. A thermal modeling block 26 of the battery pack 1 1 estimates, from the signals Text, Tpack, Tcooling, Distance, Traffic and parameters possibly updated in the history block (α, β, γ, δ, Θ), the Trep target temperature at which the battery pack 1 1 will operate during the trip. To make this estimate, a thermal model of the battery pack 1 1 is used: Trep = f (Text, Tpack, Tcooling, Distance, Traffic, History).

Firstly, the average current flowing through the battery pack 1 1 during the journey is estimated: from the pre-processed Traffic signal = [V1; V2; ...; Vp], average current values are determined on each of the p sections, we obtain the vector [lmoyen_1; lmoyen_2; lmoyen_p]. These average current values are determined by means of a table of precalibrated values dependent on the average speed. This table takes into account the characteristics of the vehicle, such as its mass or the efficiency of its electric machine or the gear ratio of its driveline.

Then, the temperatures of the battery pack 1 1 at the end of the p sections forming the path are estimated: For example, the change in the temperature of the battery pack 1 1 can be expressed, in continuous time, by the differential equation next: d ^TpaCk ^ = yl (t) ² ₊ ^. (Text (- Tpack () + 5 - (Tcooling (- Tpack ()

where Tpack (t) represents the temperature of the battery pack 1 1 at a time t, where Text (t) represents the outside temperature at time t, where Tcooling (t) represents the temperature of the cooling system at time t and where γ, δ and Θ are adjustment parameters making it possible to take into account the thermal characteristics of the battery pack 1 1, these parameters potentially being able to be updated in the block 24 History. In the second member of this last differential equation above, the first term represents internal heating of the battery pack 1 1 by Joules effect, the second term represents the heat flow between the battery pack 1 1 and the atmosphere, the third term represents the heat flow between the battery pack 1 1 and the cooling / heating heat transfer fluid.

To solve this differential equation in the EVC computer 13, we first determine the durations associated with each of the p sections, from the pre-processed information Traffic and Distance initially provided by the GPS system 14: a vector Duree = [t1, t2 ,. .., tp] describes the p durations associated with each of the p sections, with ti = Di / Vi for i integer between 1 and p.

The following algorithm can then be executed in the EVC computer 13 according to the following steps:

· Step 1: estimation of the temperature evolution of the battery pack 1 1 on the first section of length D1, the average speed V1 and the average outside temperature Text_1

o Determination of the temperature Tcooling of the heat transfer fluid: this temperature to be taken into account on the first section is determined by means of a table of precalibrated values, which describes the steady-state temperature of this heat transfer fluid as a function of the temperature of the battery pack 1 1:

Tcooling_l = table_cooling (Tpack) where Tpack is the temperature measured in the battery pack 1 1 at the moment when the driver informs his destination in the GPS system 14, where Tcooling_1 represents the average temperature of the heat transfer fluid to be taken into account on the first section where table_cooling represents the precalibrated values table. Depending on the case, this temperature Tcooling_1 may correspond to the activation of means for heating or cooling the fluid.

Calculation of the evolution of the temperature of the battery pack 1 1 on the first section: starting from the differential equation which precedes, and considering as constants on the whole of the first section the signals Text (t) = Text_1, lpack (t) = lmoyen_1, Tcooling (t) = Tcooling_1, we obtain, for the estimated temperature of the battery pack 1 1 at time t1, that is to say at the end of the first section:

(imoyen l) ² + δ ^■ Text l + Θ ^■ Tcooling l - (δ + θ) ΰ Y '(imoyen l) ² + δ ^■ Text l + Θ ^■ Tcooling l

Tpack (d) Tpack - δ + ί ⁺ + θ

• Step 2: Estimation of changes in the battery pack temperature for 1 1 of the 2 ^nd run-length D2, the average speed V2 and the average outdoor temperature text_2

o Determination of Tcooling_2 coolant temperature: this temperature to be taken into account on the 2 ^nd section is determined by means of a table of values pre-calibrated, which describes the steady-state temperature of the fluid depending on the pack temperature battery 1 1:

Tcooling_2 = table_cooling (TPACK (t)) where TPACK (tl) is the temperature of the battery pack 1 1 at the end of ¹ section estimated according to step 1 above, where Tcooling_2 represents the average temperature of the coolant to be taken into account on the ^2nd section and where table_cooling represents the table of pre-calibrated values. Depending on the case, this temperature Tcooling_2 may correspond to the activation of means for heating or cooling the fluid.

Calculation of the evolution of the temperature of the battery pack 1 1 on the ^2nd section: starting from the differential equation which precedes, and considering as constant on the whole of the ^2nd section the signals Text (t) = Text_2 , lpack (t) = lmoyen_2, Tcooling (t) = Tcooling_2, we obtain:

• (lmoyen_2) ² + δ ^■ Text_2 + Θ ^■ Tcooling_2 - {s + e) ti 7 '(lmoyen_2) ² + δ ^■ Text_2 + Θ ^■ Tcooling_2

Tpack (i2) Tpack (tl)

⁺ 7+ Θ Step i where i≤p: estimation of the temperature evolution of the battery pack 1 1 on the i ^th section of length Di, at the average speed Vi and at the mean outside temperature Text_i

o Determination of the temperature Tcooling_i of the coolant on the i ^th section: this temperature to be taken into account on the i ^th section is determined by means of a table of precalibrated values, which describes the temperature in steady state of this fluid in function the temperature of the battery pack 1 1:

Tcooling_i = table_cooling (Tpack (ti - 1)) where Tpack (ti-I) is the temperature of the battery pack 1 1 at the end of the (i-1) ^th section estimated according to step i-1, where Tcoolingj represents the average temperature of the heat transfer fluid to be taken into account on the i ^th section, and where table_cooling represents the table of precalibrated values. Depending on the case, this temperature Tcoolingj may correspond to the activation of means for heating or cooling the fluid.

Calculation of the evolution of the temperature of the battery pack 1 1 on the i ^th section: starting from the differential equation which precedes, and considering as constant on the whole of the i ^th section the signals Text (t) = Text_i , lpack (t) = lmoyen_i, Tcooling (t) = Tcooling_i, we obtain:

• (imoyen i) ² + S ^■ Text i + Θ ^■ Tcooling i "- (3 + θ} ή Y_ (imoyen i) ² + δ ■ Text i + θ ■ Tcooling i

Tpack (ft ^' ) = Tpack (ti - l) - δ + θ δ + θ

By continuing the previous steps up to step p, we thus obtain an estimate of the temperature of the battery pack 1 1 at the end of each of the p sections that constitute the path:

Tpack_est = [Tpack (tl), Tpack (t2), ..., Tpack (tp)]

Finally, the temperature Trep is determined from the vector Tpack_est obtained previously. Several approaches are possible to determine this Trep temperature that the EVC calculator 13 will return to the BMS calculator 12.

According to a first approach that could be described as "conservative", the temperature Trep can be chosen as the lowest temperature estimated on the path:

Trep = mini <i < _p (Tpack (ti))

This approach may lead to a slight underestimation of the autonomy, the losses in the battery pack 1 1 being greater at low temperature. This approach is recommended when the differences between the p different values of the Tpack_est vector are relatively small.

Another approach that could be described as

"Moderate", the temperature Trep can be chosen as the average temperature on the p sections of the route:

Trep = meani <i < _p (Tpack (ti))

This approach is recommended when the differences between the p different values of the Tpack_est vector are relatively large.

The above embodiment thus makes it possible to obtain a value representative of the evolution of the temperature of the battery pack 1 1 on the path entered by the driver via the GPS system 14, and an estimate of the range of the vehicle for this purpose. temperature value. This estimate of autonomy has the advantage of being more reliable than that which can be performed at the start of the vehicle, without taking into account the temperature changes that the battery pack will undergo during the journey.

Claims

1. Method for estimating the autonomy of an electric or hybrid vehicle on a predetermined path, the method including a step of estimating the energy available in the traction battery (1 1) of the vehicle as a function of temperature (Tpack) of said battery,

the method being characterized in that it further includes a step of calculating a representative value (Trep) of the evolution of the temperature of the battery during the journey, said value being used to estimate the available energy. 2. Method according to claim 1, characterized in that the step of calculating the representative value (Trep) includes:

a step of cutting the path in p sections, where p is a strictly positive integer;

a step of estimating the temperature of the battery (1 1) at the end of each of the p sections.

3. Method according to claim 2, characterized in that the step of calculating the representative value (Trep) furthermore includes:

the representative value is equal to the minimum value among the p temperature values of the battery at the end of each of the p segments, or;

the representative value is equal to the average value of the p temperature values of the battery at the end of each of the p sections. 4. Method according to claim 2, characterized in that the step of cutting the path in p sections includes:

a step of entering the path by a driver of the vehicle via the interface of a navigation system (14) connected to the vehicle; a step of pre-cutting of the path by the navigation system in q sections, where q is a strictly positive integer less than or equal to p, such that the average speed of the vehicle estimated by the navigation system on each of q sections varies from one section to the next on the route. A method according to claim 4, characterized in that the step of cutting the path in p sections further includes, if some of the sections q have an estimated duration of travel greater than a predetermined threshold, a second step of redistricting said sections whose travel time is too long, so that the travel time of each p sections thus obtained is less than or equal to the threshold.

Method according to claim 2, characterized in that the step of estimating the temperature of the battery (1 1) at the end of each of the p segments includes, for i integer varying from 1 to p:

an estimation step, as a function of the average speed (Vi) estimated on the i ^th section, of the average current (lmoyen_i) passing through the battery during the i ^th section;

a step of estimating the temperature (Tcooling_i) at the beginning of the i ^th section of a heat transfer fluid for heating or cooling the battery;

a step of collecting the average outside temperature (Text_i) provided on the i ^th section;

a step of estimating the temperature (Tpack (ti)) of the battery at the instant (ti) where the vehicle reaches the end of the i ^th section, from:

o the estimated temperature of the battery at the end of the (i-1) ^th section (Tpack (ti-I)) or the measured temperature (Tpack) of the battery if i = 1, and / or;

o the average current (lmoyen_i) estimated crossing the battery during the i ^th section, and / or;

o the average outside temperature (Text_i) provided on the i ^th section, and / or;

o the estimated temperature (Tcooling_i) of the heat transfer fluid at the beginning of the i ^th section.

A method according to claim 6, characterized in that the step of estimating the temperature of the battery at the end of each of the p sections includes estimating, for i integer varying from 1 to p, the temperature (Tpack (ti )) of the battery at the end of the i ^th section by the equation: T k (t 'l) ^ (imoyen i) ² + δ ^■ Text i + Θ ^■ Tcooling i (imoyen i) ² + δ ^■ Text i + θ ^■ Tcooling i

Tpack (ft ^' ) =

δ + θ δ + θ

where γ, δ and Θ are parameters corresponding to thermal characteristics of the battery. 8. Method according to claims 4 and 6, characterized in that, for i integer ranging from 1 to p, are provided by the navigation system (14): the average speed (Vi) on the i ^th section depending on the state of the traffic on said section;

the mean outside temperature (Textj) expected on the i ^th section.

9. Calculator (13) characterized in that it comprises hardware and software means (21, 22, 23, 24, 25, 26) implementing the method according to any one of the preceding claims.

10. Electric or hybrid vehicle characterized in that it comprises a computer (13) according to the preceding claim and a dashboard (15) on which to display the estimated autonomy.