Method for calculating missing range for a plug-in hybrid vehicle

Abstract

The invention relates to a method for calculating the missing range for an electric battery of a plug-in hybrid vehicle.According to the invention, the method comprises the following steps: - acquisition (S51) of a route to be followed, the route passing through a first zero-emission zone and a second zero-emission zone distinct from the first, - division (S52) of the route into successive segments, the segments comprising two output segments corresponding to a final segment of the first zero-emission zone and a final segment of the second zero-emission zone, - calculation (S53), successively for each segment of the route: - of an estimated change in electrical energy over the segment, - of the electrical energy expected in the battery at the end of the segment, - if the segment corresponds to one of the two output segments, of a missing range as a function of the expected electrical energy, said missing range being recorded, - display (S54) of at least one data point relating to said recorded missing ranges. Figure for the abstract: Fig. 4.

Description

Title of the invention: Method for calculating missing range for a plug-in hybrid vehicle Technical field of the invention

[0001] The present invention relates generally to plug-in hybrid vehicles.

[0002] It relates more particularly to a method of calculating a missing range for an electric battery of a plug-in hybrid vehicle.

[0003] The invention finds a particularly advantageous application in plug-in hybrid vehicles with an average electric range, that is to say, a range in pure electric driving mode of around one hundred kilometers. Such vehicles can therefore operate in zero-emission zones thanks to their electric motor. State of the art

[0004] Efforts to improve air quality in cities, particularly by reducing particulate matter levels, have led to the establishment of urban zones where access is restricted to low-emission motor vehicles. Regulations have been put in place accordingly, resulting in the creation of Low Emission Zones (LEZs).

[0005] In order to pursue these efforts within the framework of an energy transition, cities are now focusing on the implementation of Zero Emission Zones (hereinafter referred to as "ZEZs"). Within these zones, only so-called "zero-emission" modes of transport will be permitted. These zero-emission modes correspond, for example, to travel on foot, or using non-motorized two-wheelers (bicycles, scooters, etc.), or electric or hybrid vehicles, provided that the latter can operate with their internal combustion engine switched off.

[0006] Thus, the challenges of the energy transition are driving the development of electric and hybrid vehicles. This development is in synergy with the future deployment of zero-emission zones (ZEZs) in urban areas, the latter of which are potentially set to multiply rapidly in the coming years, in order to meet efforts to improve air quality.

[0007] Hybrid vehicles, in particular plug-in hybrid vehicles (also known as PHEVs, for "Plug-in hybrid electric vehicle" in English) are an important lever in the context of this energy transition and the implementation of ZZEs.

[0008] Indeed, a plug-in hybrid vehicle includes a conventional thermal drivetrain (with an internal combustion engine and a fuel tank) and an electric drivetrain (with an electric motor and an electric traction battery that can be charged from a power outlet).

[0009] Such a hybrid vehicle can be powered solely by its electric drive system, or solely by its internal combustion engine drive system, or simultaneously by both its electric and internal combustion engine drive systems. It is also possible to recharge the traction battery using the power generated by the internal combustion engine, or by recovering the kinetic energy generated by the vehicle during braking.

[0010] A plug-in hybrid vehicle is therefore able to operate in zero-emission zones, thanks to its electric drive mode, which is a zero-emission mode. However, the vehicle's range when powered solely by its electric drive system is generally limited. Indeed, compared to a standard electric vehicle, a plug-in hybrid vehicle has a relatively short range in electric driving mode. The range in kilometers of a plug-in hybrid vehicle is around one hundred kilometers, compared to several hundred kilometers for a standard electric vehicle.

[0011] A method for estimating the energy consumption of an electric battery within a zero-emission zone is known from patent US20220402477 A1. This estimate is used to determine a target energy level upstream of the zero-emission zone, so that the vehicle can cross it, and thus manage energy consumption appropriately.

[0012] However, the question then arises of the autonomy of the electric battery of the plug-in hybrid vehicle when a driver has to deal with crossing several zero-emission zones.

[0013] Thus, particularly if the driver encounters several distinct ZZEs (Zones Énergétiques - Low Emission Zones) during a journey, the driver then faces the risk of not having enough battery range to cross these different ZZEs. Presentation of the invention

[0014] In order to remedy the aforementioned drawback of the prior art, the present invention proposes to help the driver adapt his behavior by estimating the missing range on the electric battery for each of the different ZZEs encountered on his route.

[0015] More particularly, the invention proposes a method for calculating the missing range for an electric battery of a plug-in hybrid vehicle, in which the following steps are provided: - acquisition of a route to be undertaken, the route crossing a first zero-emission zone and a second zero-emission zone distinct from the first, - division of the route into successive segments, the segments comprising two exit segments corresponding to a final segment of the first zero-emission zone and a final segment of the second zero-emission zone, - Calculation, successively for each segment of the journey: - of an estimated variation in electrical energy on the segment, - of the electrical energy expected in the electric battery at the end of the segment, - if the segment corresponds to one of the two exit segments, of a missing range as a function of the expected electrical energy, the missing range being recorded, - display of at least one piece of data relating to the missing autonomies recorded.

[0016] Thus, thanks to the invention, the driver can be warned sufficiently in advance in case of risk of insufficient range when crossing several distinct zero emission zones.

[0017] It can then adapt its behavior accordingly, in order to avoid being immobilized within a zero emission zone due to a charging fault on the electric battery.

[0018] For example, it can switch from an electric driving mode to a hybrid driving mode in order to recharge or preserve the charge of the electric battery outside of zero-emission zones.

[0019] This switch between an electric driving mode and a hybrid driving mode can also be imposed by the on-board software of the hybrid vehicle.

[0020] Having visibility on the range in the face of several zero emission zones allows the driver to be more proactive, for example, by planning a battery charging stage for the vehicle at an appropriate stage of his journey (for example before crossing a first ZZE, when his range would allow this crossing, if there is no possibility of charging between this first ZZE and a second ZZE).

[0021] Other advantageous and non-limiting features of the method according to the invention, taken individually or in all technically possible combinations, are as follows: - the estimated electrical energy variation on the segment, the planned electrical energy and the missing range respectively include an estimated electrical variation value on the segment in electric mode, a remaining energy value in electric mode and a missing range in electric mode, - the estimated variation in electrical energy on the segment, the planned electrical energy and the missing autonomy each include a value of electrical variation estimated on the segment in hybrid mode, a remaining energy value in hybrid mode and a missing range in hybrid mode, - the electrical energy expected at the end of said segment is equal to the sum of the estimated change in electrical energy over the segment and an electrical energy expected at the end of a segment immediately preceding the segment, or is equal to the sum of the estimated change in electrical energy over the segment and a minimum electrical operating energy, - a calculation of the expected electrical energy at the end of the segment is chosen by comparing said expected electrical energy in the electric battery to the minimum energy threshold, - during the step of dividing the route into successive segments, each of the segments is associated with characteristic attributes and in which, during the calculation step, a calculation of the variation of estimated electrical energy on a segment is made as a function of the characteristic attributes associated with the segment, - During the calculation stage, a calculation of the estimated variation of electrical energy over a segment is made based on the characteristics of the plug-in hybrid vehicle. - during the calculation stage, a calculation of the estimated variation of electrical energy on a segment is made based on the behavior of a driver of said plug-in hybrid vehicle. - at the display stage, at least one data relating to said missing ranges includes a missing range value on the first zero-emission zone and a missing range value on the second zero-emission zone - at the display stage, at least one data relating to missing ranges includes a total missing range value in the electric battery to cross the first zero-emission zone and the second zero-emission zone of the journey.

[0022] The invention also relates to a plug-in hybrid vehicle, comprising a thermal drive chain and an electric drive chain, characterized in that it further comprises a computer programmed to implement a calculation method having the characteristics listed above, taken individually or according to all possible combinations.

[0023] Of course, the various features, variants, and embodiments of the invention can be combined in various ways, provided they are not incompatible or mutually exclusive. Detailed description of the invention

[0024] The following description with regard to the attached drawings, given by way of non-limiting examples, will make it clear what the invention consists of and how it can be carried out.

[0025] On the attached drawings:

[0026] [Fig. 1] schematically represents a plug-in hybrid vehicle adapted to implement a method for calculating a possible missing range according to the invention;

[0027] [Fig.2] represents an example of a journey to be made by the plug-in hybrid vehicle of [Fig.1], this journey passing through zero-emission zones;

[0028] [Fig.3] is a table illustrating attribute values ​​characterizing segments of the path of the [Fig.2]

[0029] [Fig.4] is a flowchart representing steps of the method of [Fig.1], in order to carry out the path of [Fig.2];

[0030] [Fig.5] is a table illustrating outputs determined during the implementation of the method in [Fig.4].

[0031] In [Fig.1], a motor vehicle is shown, comprising a chassis, the latter supporting in particular a powertrain, bodywork elements and passenger compartment elements.

[0032] In particular, in [Fig.1], the motor vehicle shown corresponds to a plug-in hybrid vehicle 1, in which the powertrain comprises a thermal drive chain 10 and an electric drive chain 11.

[0033] The thermal traction chain 10 includes in particular a fuel tank and an internal combustion engine supplied by the tank.

[0034] The electric traction chain 11 comprises, for its part, a traction battery and one or more electric motor(s) alternating with electric current by the traction battery, also called electric battery 110.

[0035] The plug-in hybrid vehicle 1 also includes a power outlet allowing the traction battery to be charged locally, for example on the electrical network of a home, or from a dedicated electric charging station.

[0036] The traction battery of a plug-in hybrid vehicle 1 has a maximum electrical energy capacity that typically varies from 5 kWh to 40 kWh. With such maximum electrical energy values ​​on the traction battery, the plug-in hybrid vehicle 1 is thus capable of traveling a distance ranging, for example, from 10 km to 200 km before requiring a new charge of the traction battery.

[0037] The plug-in hybrid vehicle 1 also includes a geolocation system 12 and a navigation system 13, the two systems sometimes being combined into a single system.

[0038] The geolocation system 12 conventionally includes an antenna for receiving signals relating to the geolocated position of the vehicle, and the navigation system 13 includes a memory for storing a map of a country, a region, a city, at least one input interface, and an output interface, for example a screen 130. This screen 130 allows to visually illustrate the geographical position of the vehicle on the map stored in memory 142.

[0039] For example, this screen 130 is a touchscreen. In this case, the screen 130 also serves as the input interface for the navigation system 13, allowing the driver to enter information. Alternatively, an input interface for the navigation system 13 may include voice control via a microphone.

[0040] The geolocation system 12 (also called a GPS system), in addition to receiving the position of the plug-in hybrid vehicle 1, is also adapted to implement a geofencing function. Furthermore, the geolocation system 12 is also adapted to receive connected and evolving mapping data in real time, for example, online mapping data such as Google Maps®.

[0041] The vehicle also includes an electrical control unit (or ECU for "Electronic Control Unit" in English), referred to here as calculator 14.

[0042] This calculator 14 includes a processor 140 and a memory unit (hereafter referred to as "memory 142").

[0043] In particular, the processor 140 of the computer 14 is adapted to implement embedded software. This embedded software comprises computer programs including instructions; the execution of these instructions allows the control of various functions of the plug-in hybrid vehicle 1.

[0044] The computer 14 is connected to the navigation system 13 and the geolocation system 12 by a main inter-component communication network of the vehicle, for example a CAN data bus.

[0045] Furthermore, for the implementation of the invention, the computer 14 is here connected to several sensors, which in particular allow us to know the instantaneous fuel consumption of the internal combustion engine, the instantaneous electrical current consumption of the electric motor(s), and the driving behavior (sporty, classic, calm, ...) of the driver of the plug-in hybrid vehicle 1, etc.

[0046] During travel, in order to go from a starting location 20 to an arrival location 22, the plug-in hybrid vehicle 1 takes a path, which is designated as a route 2.

[0047] Within the framework of the invention, this route 2 is defined by the navigation system 13 of the plug-in hybrid vehicle 1, based on data communicated by the geolocation system 12, and data stored in the memory 142 of the navigation system 13.

[0048] Such a path 2 is illustrated in [Fig.2].

[0049] This journey 2 may include sections within zero-emission zones, referred to as ZZE 31, 32, 33 in the following description. This is particularly the case if the plug-in hybrid vehicle 1 is travelling in an urban area (i.e. a city).

[0050] These ZZE 31, 32, 33 correspond to geographical areas defined in the urban space, where only modes of transport and vehicles with zero greenhouse gas emissions are tolerated.

[0051] By "emission", it is understood in particular to mean emission of polluting species, such as, for example, emission of nitrogen dioxide (NO2) and / or emission of fine particles (PM10, PM2.5).

[0052] In order to improve air quality and the quality of life in urban areas, the number of geographical zones, such as ZZE 31, 32, and 33, where emissions are regulated, is increasing. Within these ZZE 31, 32, and 33 zones, only motorized vehicles with zero greenhouse gas emissions and equipped with geofencing are permitted to circulate.

[0053] These ZZE 31, 32, 33 can for example be detected thanks to the geofencing function of the plug-in hybrid vehicle 1. When driving within a ZZE 31, 32, 33, only the electric drive chain 11 of the plug-in hybrid vehicle 1 is used, in order to comply with emission regulations.

[0054] The route 2 to be travelled is therefore determined by the navigation system 13, before being divided into adjacent and successive segments 24.

[0055] Each segment 24 of the journey 2 is characterized by attributes including in particular an identifier number, a length of segment 24, a type of segment 24, a maximum authorized speed on segment 24, a statistical average speed, a road traffic speed, a slope, a criterion related to emission regulations for a geographical area where segment 24 is located.

[0056] By way of example, the identifier number (noted as No. on [Fig.3]) is in the form of an integer identifying segment 24 among successive segments 24 and corresponds to its order in a list.

[0057] The length L of segment 24 is expressed here in kilometers.

[0058] The type of segment 24 characterizes the road by a numerical value, for example "residential, city, national road, motorway, other...", where an attribute equal to 1 may, for example, correspond to a motorway, an attribute equal to 2 may correspond to a national road, an attribute equal to 3 to an urban area, etc.

[0059] The maximum authorized speed v on segment 24 corresponds to a regulatory speed, while the statistical average speed vm corresponds to an average speed measured on segment 24, and the road traffic speed vt or speed

[0060]

[0061]

[0062]

[0063]

[0064]

[0065]

[0066]

[0067]

[0068] Instantaneous is a speed actually observed on segment 24. These attributes are given by a numerical value in kilometers per hour (km / h) for example. The slope corresponds to a degree of inclination of the road relative to the horizontal of segment 24, expressed in degrees or as a percentage. The criterion related to emission regulations indicates whether yes (the attribute then takes the value 1) or no (the attribute then takes the value 0), segment 24 is located in a geographical area corresponding to a ZZE 31, 32, 33. Faced with the future multiplication of ZZE 31, 32, 33, the route 2 taken by the plug-in hybrid vehicle 1 is likely to cross several distinct geographical areas corresponding to different ZZE 31, 32, 33, as shown in [Fig.2]. In this case, the path 2 presents several sets of successive segments 24 included in ZZE 31, 32, 33, the sets being separated by at least one segment 24 located outside a ZZE 31, 32, 33. These different attributes have values ​​obtained from data communicated by the geolocation system 12, for example through the georeferencing function for the criterion related to emission regulations, or for road traffic speed, and data stored in the memory 142 of the navigation system 13. These attributes are communicated to the computer 14 by the navigation system. 13 in the form of a table as shown in [Fig.3]. Only a portion of the possible attributes are represented there. Within the framework of this description, a method for calculating a missing autonomy SOC^y^ SOC2^ for the electric battery 110 of the plug-in hybrid vehicle 1 is proposed. This method is illustrated by the flowchart in [Fig.4]. Indeed, in order to assist the driver of the plug-in hybrid vehicle 1 facing a journey 2 comprising several different ZZE 31, 32, 33, it is necessary to estimate an evolution of an available electrical energy on the electric battery 110 over the successive segments 24, in order to predict a possible missing range soc^soc1^ to cross the different ZZE 31, 32, 33 which comprise the journey 2. This estimation of the evolution of an electrical energy of the electric battery 110 in order to determine the possible missing autonomy on each of the different ZZE 31, 32, 33 is for example carried out several times during the journey 2. It is thus possible to take into account the evolutions of the different parameters involved in the estimation.

[0069] Moreover, and advantageously, this estimate is made for the two driving modes available on the plug-in hybrid vehicle 1, i.e. an electric driving mode and a hybrid driving mode.

[0070] The purely electric driving mode, or electric mode, corresponds to a driving mode (or driving mode) where the plug-in hybrid vehicle 1 uses only its electric drive chain 11, powered by the electric battery 110, on the different segments 24 of the journey 2.

[0071] The hybrid driving mode, or hybrid mode, corresponds to a default driving mode of the vehicle. In this default mode, the plug-in hybrid vehicle 1 optimally uses its thermal powertrain 10 and its electric powertrain 11 to propel itself on the various segments 24 of the journey 2, except for the segments 24 located in geographical areas associated with ZZE 31, 32, 33. On these segments 24, the electric driving mode is mandatory.

[0072] The estimates of available electrical energy on the electric battery 110 differ greatly depending on which of the driving modes the driver has adopted on the preceding segments 24 of the ZZE 31, 32, 33. It is therefore advantageous to take into account the driver's free will. Indeed, the driver may prefer and therefore choose one or the other of the driving modes.

[0073] The proposed method is implemented jointly by the navigation system 13, the geolocation system 12, and the computer 14.

[0074] The method comprises, in summary, the following main steps: - Acquisition S51 of a route 2 to be completed, - division S52 of said route 2 into 24 successive segments, - Calculation S53, iteratively for all segments 24 of route 2: - of a variation in electrical energy ASOÉ^f, ASOË^nax estimated on segment 24, - of electrical energy expected Eshy^ Eseiec in the electric battery 110 at the end of segment 24, - If conditions related to an exit from a ZZE 31, 32, 33 are met, with a missing autonomy eg^C^f, a function of the planned electrical energy, the missing autonomy being recorded, - display S54 to the driver of at least one piece of data relating to missing ranges recorded during the iterations.

[0075] Some of the main steps of the method, in particular the calculation step S53 and the display step S54, are here executed at the start of the journey and then at regular time intervals, for example once every three minutes, in order to refine the accuracy of the estimate provided to the driver as they travel the route. Here, we will only describe the implementation of these steps at the start of the journey.

[0076] Alternatively, the aforementioned steps can be repeated as soon as a significant change of state has been detected by one of the sensors of the plug-in hybrid vehicle 1, for example when the total weight of the vehicle increases or decreases, in order to take into account this variation in mass during the calculation step S53.

[0077] A first step, also called acquisition step S51, includes an acquisition of a journey 2 to be carried out by the plug-in hybrid vehicle 1.

[0078] This first step is carried out for example when starting the motor vehicle.

[0079] Here, the driver uses the touch screen 130 of the navigation system 13 to set an arrival location 22. The navigation system 13, taking into account a departure location 20 provided by the geolocation system 12 and the data stored in memory 142, calculates a route 2 to be taken, taking into account, for example, the driver's preferences, such as the duration of the route 2, the type of road, etc.

[0080] The entire method is reset from the acquisition step S51 in case of modification of path 2.

[0081] Alternatively, route 2 can be acquired via a voice command from the driver, or by taking into account the driver's habits, in order to automatically deduce an arrival location 22, for example, his place of work.

[0082] The second step, namely the division step S52, consists of dividing the path 2 into successive segments 24, and aggregating the attributes characterizing these segments 24, in order to form a table listing the associated attributes for the different segments 24. As a reminder, such a table is represented in [Fig.3].

[0083] This step is performed by the navigation system 13, based on route 2, data in memory, but also data collected by the georeferencing function or data from online mapping, for example from Google Maps®. Thus, the table's attribute values ​​can be modified during route 2.

[0084] The calculation step S53 is implemented by a calculation function of the embedded software. The function comprises six sub-functions detailed below. These six sub-functions are shown in [Fig. 4].

[0085] The calculation function is executed iteratively, via a FOR loop traversing the values ​​of the identifying numbers of route 2. An index of the FOR loop, denoted s, therefore successively takes a value from 1 to sf, where sf corresponds to the identifying number of the last segment 24 of route 2.

[0086] For example, and in a non-limiting manner, sf can be equal to 18, in the case where the path 2 is divided into seventeen segments 24, numbered from 1 to 18.

[0087] Thus, for each of the segments 24 of the path 2, the six sub-functions are executed successively, incrementing the value of the index s successively by steps of 1 between each execution.

[0088] The calculation function is initialized during an INIT step. During this initialization, output variables and internal variables are set to zero, or initialized to a value measured by a sensor and sent to the computer 14.

[0089] Output variables determined by the calculation function are represented in the form of a table shown in [Fig.5].

[0090] A first sub-function 531 of the calculation function determines and returns the distance (f) remaining to be travelled on the segment 24 of index s. In particular, this distance ds is equal to the length of the segment, except for the segment that the vehicle travels.

[0091] For this purpose, the first sub-function 531 receives the following as input variable: - a table listing, for the different segments 24 of route 2, the length L of these segments 24, - a sinst index corresponding to the identification number of segment 24 on which the plug-in hybrid vehicle 1 is currently located - a remaining distance to be covered on segment 24 with index sinst, that is to say- This function calculates the remaining distance to be traveled on segment 24, where the plug-in hybrid vehicle 1 is located at the time the calculation function is executed. This segment 24, where the plug-in hybrid vehicle 1 is located, is also called the current segment 24, or the instantaneous segment 24.

[0092] For example, the table listing the distance of the segments 24 of route 2 is sent by the navigation system 13. In particular, this table can be generated from the table in [Fig. 3]. Here, the table gives more precisely a cumulative length of the segments 24, the length being accumulated from the first segment 24 of the route. Alternatively, the table could directly list the length of each of the segments 24.

[0093] The sinst index corresponding to the identification number of segment 24 on which the plug-in hybrid vehicle 1 is currently located is sent by the navigation system 13.

[0094] The remaining distance to be travelled on segment 24 with index sinst is returned by another function of the embedded software.

[0095] The first sub-function 531 calculates the distance to be traveled on the segment 24 with index s as follows:

[0096] If s > sinst then the distance ds is equal to the distance of the segment 24 of index s as determined in from the table.

[0097] In other words, if the plug-in hybrid vehicle has not yet reached segment 24 with index s, then the distance ds to be covered on segment 24 with index s is equal to the total distance of segment 24.

[0098] If s=sinst, then the vehicle is currently located on segment 24 considered in the loop of the calculation function. The distance ds is equal to the remaining distance to be traveled on segment 24 with index sinst.

[0099] Finally, if s < sinst, the distance ds is zero. Indeed, in this case, the plug-in hybrid vehicle 1 has already passed the segment 24 with index s considered in the loop of the calculation function.

[0100] The first sub-function 531 therefore returns a numerical value, given in kilometers, as shown in the second column of the table in [Fig.5].

[0101] A second sub-function 532 returns variables calculated by a third function of the embedded software, estimating energy variations per kilometer.

[0102] In particular, the second subfunction 532 returns variations in electrical energy per kilometer ASOEsmaxjinp ASOE^ km on the segment 24 of index s, comprising a minimum variation value of electrical energy per kilometer ESOE}^^ on the segment 24 of index s, and a maximum variation value of electrical energy per kilometer i\SOE,max km on the segment 24 of index s.

[0103] The maximum variation in electrical energy per kilometer ASOEsnuix km on segment 24 of index s corresponds to a kilometer variation in the electrical energy available on the electric battery 110 when the plug-in hybrid vehicle 1 operates in hybrid mode, i.e. using its thermal drive chain 10 to the maximum of its capacity in order to recharge the electric battery 110.

[0104] The minimum variation value of electrical energy per kilometer ÀSOE^ km on the segment 24 of index s corresponds to a kilometer variation of the electrical energy available on the electric battery 110 when the plug-in hybrid vehicle 1 operates in pure electric mode, i.e. using only its electric drive chain 11 with the electric battery 110 as the sole source of energy.

[0105] These values ​​of variation of electrical energy per kilometer âSOEstnax km, MOE^ km on segment 24 index s are given in watt-hours per kilometer (wh / km), and represent a variation of the electrical energy available on the electric battery 110 per kilometer traveled.

[0106] In other words, the values ​​of variation of electrical energy per kilometer on the segment 24 of index s represent an energy cost per kilometer generated by the journey of the rechargeable electric vehicle on this segment 24. These values ​​thus represent a charge or a discharge of the electric battery 110, depending on the positive sign (charge) or negative sign (discharge).

[0107] The second sub-function 532 also returns a maximum state of charge value of the electric battery 110 SOCs / nax on segment 24 with index s. This maximum state of charge value SOC^^ (from the English "State of Charge") characterizes a maximum value of electrical energy in the electric battery 110 for segment 24 with index s. Its value is given by a percentage charge (%) of the battery. This maximum state of charge value SOGsmax is estimated for driving in pure electric mode.

[0108] The third function estimating, for segment 24 with index s, the minimum and maximum variations in electrical energy per kilometer ASOS^ km, ^SOE"1^^ and the maximum state of charge SOCÏ","^ is an energy consumption estimation function. Such a function is used within the framework of an energy optimization method, as described, for example, in documents FR3061471 Bl, or FR3038277 Bl, and more particularly in document FR3061470 BL

[0109] The third-party function takes into account data from journey 2, for example, the table listing for the different segments 24, the associated attributes, driver behavior, vehicle mass, and characteristics of the plug-in hybrid vehicle 1.

[0110] Driver behavior includes, for example, relaxed or sporty driving. This behavior does indeed influence the energy consumption of the hybrid vehicle.

[0111] By characteristics of the plug-in hybrid vehicle 1, it is understood for example mechanical data, a model of the vehicle, etc.

[0112] The function can, for example, return the estimated variables in the form of a table listing the estimates obtained for each of the segments 24 of the route 2.

[0113] Furthermore, it is this third-party energy consumption estimation function that imposes, if segment 24 with index s is located within a geographical area of ​​a ZZE 31, 32, 33, a minimum value of variation in electrical energy per kilometer at SOEstl^}tkm equal to a maximum value of variation in electrical energy per kilometer ASOEsnun: km. Indeed, on these segments 24, the electric driving mode is mandatory.

[0114] The result of the second function is illustrated by the third column of the table in [Fig.5].

[0115] A third sub-function 533 takes as input the outputs of the first sub-function 531 and the second sub-function 532, in order to determine an estimated variation of electrical energy ^SOE^^ ASOEsmax on the segment 24 of index s.

[0116] More specifically, the third sub-function 533 returns a maximum variation of electrical energy ^OEsmax and a minimum variation of electrical energy ASOEsmin over the whole of the segment 24 of index s from the estimates obtained by the second sub-function 532. Unlike the second sub-function 532, the third sub-function 533 takes into account the distance ds of the segment 24 of index s.

[0117] The minimum change in electrical energy is given by the following formula: ions]

[0119] This minimum electrical energy variation value corresponds to an electrical energy variation on the electric battery 110 for an electric mode.

[0120] Similarly, the maximum variation value of electrical energy is given by the following formula:

[0121] tâOE^x = ds*ASOEsmaxktn

[0122] This maximum electrical energy variation value ASOE\ltux corresponds to an electrical energy variation on the electric battery 110 for a hybrid mode, or electric if the index segment 24 is included in a zero emission zone.

[0123] The sequence of the first, second and third sub-functions 531, 532, 533 made it possible to arrive at the calculation of an estimated electrical energy variation &SOEsmin on the segment 24 of index s.

[0124] The fourth sub-function 534 calculates the electrical energy expected in the electric battery 110 Ehyb, E^^ at the end of segment 24 with index s, taking into account the preceding segments 24.

[0125] The fourth sub-function 534 takes as input: - the estimated variation in electrical energy on segment 24 with index s, including the maximum variation in electrical energy - the minimum variation of electrical energy ASOE]^ - the maximum state charge value SO(fmax^ - a target state of charge (SOC) value f, - an equivalence factor Q, - the table listing for the different segments 24, the associated attributes, - the sinst index of segment 24 on which the plug-in hybrid vehicle 1 is currently located.

[0126] The electrical energy expected in the electric battery Eshyh, Eseiec at the end of segment 24 with index s is calculated in hybrid mode and in electric mode, taking into account respectively of the maximum variation of electrical energy ASOE^x and the minimum variation of electrical energy àSOEsfnin-

[0127] The fourth sub-function 534 first calculates a minimum energy threshold $OEth in the following manner: SOEth = SOCf*Q + m.

[0128] Where SOEth corresponds to the minimum energy threshold given in Wh, Q corresponds to the equivalence factor in Wh / %, SOCy corresponds to the target state of charge value in %, and etm corresponds to a margin given in Wh. It advantageously allows for consideration of potential estimation errors in the third-party function that determines the estimated energy consumption.

[0129] Here, in the example shown in Figure 5, the minimum energy threshold SOEth is equal to 20 kWh, with a margin of m = 10 Wh, an equivalence factor 0 = 1 kWh / %, and a target state of charge value equal to SOCf = 20%. These values ​​may vary depending on the characteristics of path 2.

[0130] The value used for the margin is derived from a linear interpolation stored in the memory 142 of the computer 14. Its value depends on a maximum permissible electrical energy in the electric battery 110 Em(jX). For example, the car manufacturer may decide that if Emax = 2000 Wh, then the margin m is equal to 1000 Wh, or that if Emax = 20 kWh, m = 500 Wh. In other words, the higher the battery capacity, the lower the margin can be.

[0131] The electrical energy expected in the electric battery 110 Eshyb, Eselec at the end of segment 24 with index s for a hybrid mode is calculated as follows: [° 132 1

[0133] Where Eÿ is equal to the electrical energy provided in the electric battery 110 at the end of segment 24 with index s-1 for a hybrid mode.

[0134] In the particular case where the index s is strictly less than then:

[0135] tfhyb= Einst,

[0136] where Einst corresponds to an instantaneous electrical energy measured by a sensor.

[0137] Thus, since it is an iterative calculation, at each iteration, the value of the predicted electrical energy E^ in the battery on the previous segment 24 is incremented by the variation of the electrical energy ^SO^max for the segment 24 of index s.

[0138] Following the same reasoning, the electrical energy provided in the electric battery 110 at the end of segment 24 with index s for an electric mode is calculated as follows:

[0339] + &SOE-Mi

[0140] Where Ese[ec is equal to the electrical energy provided in the electric battery 110 at the end of segment 24 of index s-1 for an electric mode.

[0141] In the particular case where the index s is strictly less than si™t, then: [01421 e,i„=

[0143] where Einst corresponds to the instantaneous electrical energy measured by a sensor.

[0144] Nevertheless, the value of electrical energy provided in the electric battery 110 EshyI„ E1^ at the end of segment 24 with index s, whether in hybrid or electric driving mode, is saturated by the maximum electrical energy that can be stored in the battery in the segment with index s, Esniax- This maximum electrical energy that can be stored in the battery for a given segment 24 E^* is limited relative to the maximum energy Emax^ in order to preserve the battery's longevity.

[0145] Thus, if: Eselec > E?max then we apply a threshold Eselec = Esmw, and / or if: Eshyb > then we apply a threshold Eshyb = E"nax.

[0146] This maximum electrical energy that can be stored in the electric battery 110 Esm9X on the index segment s is determined as follows: Æmax — SOE Q, o^SOCL is determined by the second sub-function 532.

[0147] Furthermore, if an exit from ZZE 31, 32, 33 is detected between segment 24 with index s and the preceding segment 24 with index s-1, and the electrical energy expected in the electric battery 110 Eshyb, Esclec at the end of segment 24 with index s for hybrid or electric mode is less than SOEth, then this means that from segment 24 with index s (inclusive) onwards, the plug-in hybrid vehicle no longer has sufficient charge on its electric battery 110 to continue driving in pure electric mode. This means, in particular, that the plug-in hybrid vehicle 1 lacked electrical energy during the ZZE 31, 32, 33 from which it has just exited.

[0148] It is therefore assumed that during the ZZE 31, 32, 33, the driver has recharged the electric battery 110 of his vehicle, so that upon exiting the ZZE, the electric battery has an electrical energy equal to the minimum SOEth energy threshold.

[0149] This charging hypothesis translates as follows:

[0150] Eshyb = SOEtb and / or Eseiec = SOElh, if the condition is verified.

[0151] The fifth sub-function 535 determines, after segment 24 with index s, whether the plug-in hybrid vehicle 1 exits a ZZE 31, 32, 33. In other words, the fifth sub-function 535 determines whether segment 24 with index s is the last in a succession of segment 24 within the geographical perimeter of a ZZE 31, 32, 33. In this case, there is an exit from the geographical perimeter of the ZZE 31, 32, 33 following segment 24 with index s.

[0152] The fifth sub-function 535 returns a value equal to 1 if this is the case, and a value equal to 0 otherwise.

[0153]

[0154]

[0155]

[0156]

[0157]

[0158] In other words, the fifth sub-function 535 returns the value 1 if segment 24 with index s is within the geographical boundaries of a ZZE 31, 32, 33, and the following segment 24, with index s+1, is not within these geographical boundaries. Otherwise, the fifth sub-function 535 returns the value 0. An example of values ​​obtained following the execution of the fifth sub-function 535 is illustrated in the sixth column of the table in [Fig.5]. The sixth sub-function 536 determines, if applicable, a missing autonomy SOC^^ soc^^ for the ZZE 31, 32, 33 within which the segment 24 with index s is located. The sixth sub-function 536 returns a missing autonomy SOC^y SOC^^ when the fifth sub-function returns the value 1. More specifically, the sixth sub-function 536 determines, for the corresponding ZZE 31, 32, 33, a missing range value for the hybrid SOC^^ mode and a missing range value for the electric SOCZZE- mode For this, the sixth sub-function 536 takes as input variables the electrical energy expected in the electric battery 110 Eseiec at the end of the segment 24 of index s returned by the fourth sub-function 534, and the value returned by the fifth sub-function 535. If an output from ZZE 31, 32, 33 is detected after segment 24 with index s, that is, if the value returned by the fifth sub-function 535 is equal to 1, then the sixth sub-function 536 returns the missing autonomy SOCZZE^ SOCZZE> on ZZE 31, 32, 33 corresponding to segment 24 with index s.

[0159] Otherwise, i.e. the fifth sub-function 535 returns the value 0, the sixth sub-function 536 has no output variable.

[0160] Thus, the sixth sub-function 536 returns an output variable only once for each of the segments 24 included in the geographical perimeter of a given ZZE 31, 32, 33, when an exit from this ZZE 31, 32, 33 is detected by the fifth sub-function 535.

[0161] In the case where the fifth sub-function 535 returns a value equal to 1, then the missing autonomy value for the ZZE 31, 32, 33 in which the segment 24 with index s is included is given by the following formulas:

[0162] SOCZZE = (sOE,h- Em) IQ** » s « SOC^ = 0% otherwise, in the in the case of hybrid driving, where the range is given as a percentage; and [0i63] SOCZ™ =(SOEth-Esdec)lQ^E^elec <soethetsoczze = 0% , dans le cas d’une conduite en mode hybride, où l’autonomie est donnée %.

[0164] Alternatively, the missing autonomy SOC^E, ^^elec ' maybe given in Wh.

[0165] Thus, the embedded software calculation function implemented during calculation step S53 successively returns, for each of the distinct ZZE 31, 32, 33 that the plug-in hybrid vehicle 1 will traverse on its route 2, a missing range SOC^E, including a missing range value in hybrid driving mode SOC^f and a missing range value in electric driving mode SOCZ^E-

[0166] These autonomy values ​​returned successively for the different ZZE 31, 32, 33 distinct included in the journey 2 are stored in the calculator 14. For example, the different values ​​returned by the sixth sub-function 536 are stored in an array.

[0167] During the display step S54, the missing range values ​​on the various ZZE 31, 32, 33 of journey 2 are displayed to the driver.

[0168] For example, a missing range SOC^E, SOCZ^E, for the next ZZE 31, 32, 33, relative to the current location of the plug-in hybrid vehicle 1 is displayed to the driver on the screen 130 of the navigation system 13.

[0169] Alternatively, a total missing range on the electric battery 110 in order to complete journey 2 in its entirety in one driving mode or the other can be displayed to the driver.

[0170] Advantageously, the proposed method adapts to the number of ZZE 31, 32, 33 encountered during journey 2. In particular, the described method is suitable for situations where several ZZE 31, 32, 33 are encountered during journey 2. In this case, a prediction of all the ZZE 31, 32, 33 encountered provides the driver with better planning for their journey 2.

[0171] Advantageously, the method takes into account both a hybrid driving mode and an electric driving mode during its calculations. The driver thus has a free choice between traveling route 2 in electric mode or in hybrid mode, fully aware of the available range.

[0172] Fig. 5 illustrates the implementation of the calculation step S53, in particular, the values ​​determined by the different sub-functions, and their evolution from segment 24 to segment 24. This table is given for illustrative purposes only and is in no way limiting.

[0173] This table is determined for a case where sinst is equal to 1, with a remaining distance to travel the instantaneous segment 24 equal to km. Furthermore, it is assumed that the constant variables used in the calculation function take the following values:

[0174] Ew / «x=20 kWh, m=600 Wh, Einst=10 kWh, SOEth=1 kWh, Q=200 Wh / %.

[0175] Thus, segments 24 with indices from 2 to 4 inclusive correspond to a portion of the journey 2 included in the surveyor's perimeter of a first ZZE 31.

[0176] In particular, segment 24 with index s equal to 4, corresponds to a situation where the sixth sub-function 536 calculates the missing autonomy on the electric battery 110 is calculated, because an output of ZZE 31, 32, 33 is detected by the fifth sub-function 535.

[0177] The missing range value for the first ZZE 31 is equal to 0% for both driving modes, i.e. the plug-in hybrid vehicle 1 has the necessary electrical energy to cross this first ZZE 31 regardless of the driving mode used before reaching this ZZE.

[0178] Segments 24 with indices from 9 to 12 correspond to crossing a second ZZE 32, distinct from the first. In particular, since segment 24 with index 12 corresponds to the last segment 24 of this second ZZE 32, the sixth function calculates a missing range on this second ZZE 32. Here, there is a 30.8% missing range on the electric battery 110, if electric mode has been engaged. If the plug-in hybrid vehicle is driven in hybrid mode outside of the ZZEs, there is no missing range issue when crossing the second ZZE 32.

[0179] In the event that the driver has adopted electric mode, it is assumed in segment 24 index 13 that the driver has taken the necessary steps before or during the second ZZE 32 to have at least the minimum threshold of electrical energy at the exit of the ZZE 32. A message may also be displayed in the driver's view to indicate that he or she should carry out this necessary recharging or change driving mode, for example switch to hybrid mode in order to cross the ZZE 32.

[0180] Thus, on segment 24 with index 13, Es^ec = 26 kWh.

[0181] Segments 24 with an index ranging from 14 to 17 are included in the perimeter geographical of a third ZZE 33.

[0182] In particular, for segment 24 with index 17, the missing range in hybrid mode is equal to SOC^^ = 1%, while the missing range in electric mode is equal to SOC^E = As with segment 24 with index 13, it is assumed for segment 24 with index 18 that the driver has taken the necessary steps to leave the ZZE 33 with sufficient electrical energy. On this segment 24 with index 18, E^c = 26 kWh and E8^ = 26 kWh.

[0183] The present invention is in no way limited to the embodiments described and represented, but a person skilled in the art will be able to make any variation in accordance with the invention.

[0184] For example, the missing range could be calculated for only one of the two driving modes, for example, electric mode only, or conversely, only hybrid mode. It is notably possible to calculate the missing range (SOC) in hybrid mode only from a certain number of ZZEs. Alternatively, it is also possible to calculate the missing range in electric mode only if the electrical energy in the battery falls below a threshold.< / soethetsoczze>

Claims

Demands

1. A method for calculating the missing range for an electric battery (110) of a plug-in hybrid vehicle (1), wherein the following steps are provided: - acquisition (S51) of a route (2) to be taken, said route (2) passing through a first zero-emission zone (31, 32, 33) and a second zero-emission zone (31, 32, 33) distinct from the first zero-emission zone (31, 32, 33), - division (S52) of said route (2) into successive segments (24), said segments (24) comprising two output segments (24) corresponding to a final segment (24) of the first zero-emission zone (31, 32, 33) and a final segment (24) of the second zero-emission zone (31, 32, 33), - calculation (S53), successively for each segment (24) of the route (2): - of a variation of estimated electrical energy ( / \SOEs ■ ? ASOE'max) on said segment (24), - of electrical energy expected in the electric battery Eselef) at the end of said segment (24),- if said segment (24) corresponds to one of the two output segments (24), of a missing autonomy (çqçZZE, depending on said planned electrical energy, said missing autonomy (SOC^^ SOC^ being recorded, - display (S54) of at least one data relating to said missing autonomies SOC2?^ recorded.,

2. Calculation method according to claim 1, wherein said estimated electrical energy variation ( / \SOEs ■ ' ASOEsma^) on said segment (24), said predicted electrical energy (Eh^ Eseiec) and said missing autonomy SOCZZE^ comprise respectively an estimated electrical variation value ^^OES • ) on said segment (24) in electric mode, a predicted electrical energy value (E^^ in electric mode and a missing autonomy (SOCZ2E^ in m°dc electric.

3. Calculation method according to any one of claims 1 or 2, wherein said estimated electrical energy variation (ASOE^^ ASOEsftUiX) on said segment (24), said predicted electrical energy (Eshyh, Ese[ec) and said missing range (SOCZ^) comprise respectively an estimated electrical variation value (ASOE^^ on said segment (24) in hybrid mode, a predicted electrical energy value (Eshyb) in hybrid mode and a missing range in hybrid mode.

4. Calculation method according to any one of claims 1 to 3, wherein said electrical energy expected in the electric battery (Eshyb, Esetee) at the end of said segment (24) is equal to the sum of said estimated electrical energy variation (ASOEsinax) over said segment (24) and an electrical energy expected in the electric battery (E^y^ ^eiec^ at the end of a segment immediately preceding said segment (24) or is equal to the sum of said estimated electrical energy variation (ASOEf^, ASOE^n,^ over said segment (24) and a minimum energy threshold (SOEth).

5. A calculation method according to claim 4, wherein a calculation of said expected electrical energy (E^b, Eseiec) at the end of said segment (24) is chosen by comparing said expected electrical energy in the electric battery (E^i» Eselec) to said minimum energy threshold (SOEthY

6. Calculation method according to any one of claims 1 to 5, wherein, during the division step (S52), each of the segments (24) is associated with characteristic attributes and wherein, during the calculation step (S53), a calculation of said estimated electrical energy variation (ASOEsini„, ASOEfntax) on a segment (24) is made as a function of the characteristic attributes associated with said segment (24).

7. Calculation method according to any one of claims 1 to 6, wherein, during the calculation step (S53), a calculation of said estimated electrical energy variation (ASOEfmi„, ASOEfmar) over a segment (24) is made as a function of the characteristics of the plug-in hybrid vehicle (1).

8. Calculation method according to any one of claims 1 to 7, wherein, during the calculation step (S53), a calculation of said estimated electrical energy variation (àSOE^, over a segment (24) is made as a function of a driver's behavior of said plug-in hybrid vehicle (1).

9. Calculation method according to any one of claims 1 to 8, wherein at the display step (S54), at least one data relating to said missing autonomies SOCZZE^ includes a missing autonomy value on the first zero emission zone (31, 32, 33) and a missing autonomy value on the second zero emission zone (31, 32, 33).

10. Calculation method according to any one of claims 1 to 9, wherein at the display step (S54), at least one data relating to said missing autonomies (SQÇzZe) includes a total missing autonomy value in the electric battery to cross the first zero emission zone (31, 32, 33) and the second zero emission zone (31, 32, 33) of the journey (2).

11. Plug-in hybrid vehicle (1) comprising a thermal drivetrain (10) and an electric drivetrain (11), characterized in that it further comprises a computer (14) programmed to implement a calculation method according to any one of claims 1 to 10.

Images