Method for delaying the starting of a heat engine in a hybrid vehicle

Abstract

The invention relates to a method for optimizing the consumption and drivability of a hybrid vehicle, comprising a heat engine and an electric motor powered by a battery, the method comprising: a) acquiring, by a navigation system, a journey to be made, with the journey being divided into a plurality of successive segments (Ti), each segment having attributes (ATB) characterizing it; b) estimating a projection of how battery energy will vary in each segment; c) calculating a trajectory for battery energy on the basis of the current energy, the energy-variation projection and the current position of the vehicle; d) determining a classification of each segment; e) determining requests for maintaining the electric traction mode, as a function of the classification assigned to each segment; f) where appropriate, acting to maintain the electric traction mode, by delaying the starting of the internal combustion engine.

Description

[0001] DESCRIPTION

[0002] TITLE OF THE INVENTION: Method for delaying the start-up of a combustion engine on a hybrid vehicle

[0003] The present invention relates to a method for delaying the start-up of the internal combustion engine in a hybrid vehicle. The internal combustion engine is a fuel-powered engine using hydrocarbon fuel.

[0004] A hybrid vehicle typically has a powertrain with an internal combustion engine and one or more electric motors connected to a traction battery. This powertrain applies torque to the vehicle's wheels. The present invention applies to all hybrid vehicles, particularly plug-in hybrids, but also to non-plug-in hybrids. The powertrain allows for a number of possible combinations of operating modes, including traction, deceleration, and regenerative braking.

[0005] In particular, the vehicle can operate in zero emission mode ('ZEM' in this document), i.e. with the internal combustion engine stopped, the drivetrain then being in purely electric mode.

[0006] Furthermore, the vehicle can operate in hybrid mode ('HYM' in this document), meaning with the internal combustion engine running, generally contributing to the traction function, but also including engine braking. In hybrid mode, there are several variations: the electric motor can operate as a motor ('boost'), it can operate as a generator ('traction battery charging mode'), and it can also operate with zero torque (passive mode).

[0007]

[0006] The switch from one mode to another is made according to the operational conditions of use of the vehicle, in particular according to the power requirement, and the state of charge of the traction battery.

[0008] Furthermore, zero-emission mode may be imposed in certain urban areas or under certain operational conditions.

[0009] Certain parts of the vehicle's journey may be conducive to energy recovery, particularly through the electrical part of the powertrain.

[0010] It turns out that in certain circumstances, the internal combustion engine is started for very short periods of operation. This type of situation can be perceived as illogical, untimely, or even abnormal by the driver.

[0011]

[0010] The inventors sought to improve the situation, in particular to avoid using the internal combustion engine sporadically in certain cases of vehicle use.

[0012]

[0011] To this end, a method is proposed for optimizing the fuel consumption and driving pleasure of a hybrid vehicle, comprising a fuel-powered internal combustion engine and an electric motor powered by a traction battery, the method being characterized in that it comprises: a) acquiring, by means of a navigation system, a route to be followed, and defining a division of the route to be followed into a plurality of successive segments, each segment having attributes characterizing said segment; b) estimating a projection of the energy variation in the battery on each segment of the plurality of segments of the route to be followed, assuming that the vehicle remains in zero-emission electric mode; c) calculating an energy trajectory in the vehicle's battery from the current energy and the projection of the energy variation in the battery, as well as the current position of the vehicle.d) determining a classification for each segment of the plurality of segments of the journey to be carried out, based on the energy trajectory, with at least a first class indicating a favorable evolution of the energy trajectory in the battery in the segments following the segment to be classified; e) determining a series of requests to maintain the electric traction mode, with a binary delay information for each segment, based on the class assigned to each segment, with at least the binary delay information being set to 1 for a segment assigned to the first class; f) implementing, where appropriate, maintaining the electric traction mode (ZEM), by delaying the start of the internal combustion engine, based on the value of the binary delay information, for the current segment or the following segment.

[0013] Thanks to these calculations of projection of electrical energy on the near future, carried out on a recurring basis, it is possible to selectively avoid the use of starting the internal combustion engine for a short period, and thus eliminates the potential perception of an untimely phenomenon from the point of view of the driver.

[0014]

[0013] Energy projection calculations make it possible to determine whether the coming energy deficit will be restored immediately afterward by favorable conditions of the journey, i.e. whether the journey becomes favorable again for the restoration of energy to the battery.

[0015] Note that, in steps d) and e), class determination and the calculation of the binary delay information can be performed using classical algorithmic logic. However, in an alternative solution, class determination and the calculation of the binary delay information could be the outputs of an artificial intelligence-based module, for example, a supervised learning neural network module.

[0016]

[0015] Thanks to the process proposed here, the use of zero-emission mode is maximized. Fuel consumption is also reduced because the number of engine restarts is minimized, even though each restart consumes a small amount of electrical energy. Pollution is also reduced because some restarts are avoided, given that the first few seconds of operation are the most emitting of pollutants. Furthermore, since some switches between HYM and ZEM modes (and vice versa) are avoided, the long-term reliability of the system is also improved.

[0017] The vehicle's current position can be obtained through geolocation or odometry. The current position corresponds to the distance the vehicle has traveled up to the present moment.

[0018]

[0017] In this document, the term 'trajectory' refers to a series of information concerning the future path of the vehicle, not just its geometric trajectory. Apart from certain information generated by the process and stored in memory about the past path, the focus here is primarily on future information in order to make the right decision when the time comes, and therefore the work is essentially based on projections.

[0019] In one implementation, each segment is assigned a class chosen from at least three classes. Several different cases can thus be distinguished, as will be seen below.

[0020]

[0019] According to one embodiment, steps c) to f) are repeated, with a sliding horizon of predetermined depth. In other words, the process operates on a sliding computation window (or 'rolling window'). For example, the predetermined depth of the sliding computation window can range from 2 km to 10 km. The reasoning is short-term, but the constantly updated process offers significant advantages.

[0021] In one scenario, the attributes of each segment include: length, gradient, and average speed. This allows, in particular, the calculation of the electrical power required for future travel along that segment, given these attributes.

[0022]

[0021] Incidentally, the attributes may also include the type of road, the nature of the pavement, without excluding dynamic information such as congestion, traffic, ongoing works, etc.

[0023]

[0022] According to one embodiment, each section is sufficiently short to exhibit homogeneity of characteristics. This allows for efficient analysis using average values ​​across the section. In practice, a section length can range from 15 m to 80 m. Typical section lengths are around 50 meters.

[0024] For example, for a horizon of 5 km with segments of average length of 50 m, there are 100 segments to take into account.

[0025] According to one implementation, the energy calculation carried out in step b) uses vehicle characteristics which may include, in particular, the vehicle's weight, its load, and its aerodynamic drag coefficient.

[0026]

[0025] According to one embodiment, when, for a given section, the current energy (EGY_CRT) is between the lower battery energy threshold (L_BAT_EGY) and the upper battery energy threshold (H_BAT_EGY), then the class depends on the respective classes of the preceding sections and the energy demand of the following sections. Accordingly, the profile of the route before and after the section of interest is taken into account.

[0027] [0 According to one implementation, when for a given section the current energy (EGY_CRT) is greater than the upper battery energy threshold (H_BAT_EGY), then the assigned class is the first class. A simple logic can thus be applied, at least for this scenario.

[0028] According to one implementation, when, for a given section, the current energy (EGY_CRT) is below the low battery energy threshold (L_BAT_EGY) over at least a certain predetermined distance (DIST_L_MAX_BAT_EGY), then the assigned class is the third class. In this case, the engine start delay should be disabled, and the conventional logic of choosing between hybrid mode (HYM) and zero-emission mode (ZEM) remains.

[0029] According to one embodiment, when, for a given section, the current energy (EGY_CRT) is between the lower battery energy threshold (L_BAT_EGY) and the upper battery energy threshold (H_BAT_EGY), and the power demand in the following section(s) exceeds the maximum power of the electrical machine(s), then the assigned class is either Class 2 (C2) or Class 4 (C4). The distinction between classes C2 and C4 depends on the battery energy level before and after the section in question, as will be discussed later.

[0030] The invention also relates to a hybrid vehicle, comprising at least one electronic control unit in which the method as described above is implemented.

[0031] The invention will be further detailed by describing non-limiting embodiments, and based on the accompanying figures illustrating variants of the invention, in which:

[0032] - [Fig.1] schematically illustrates a functional diagram of a hybrid vehicle;

[0033] - [Fig.2] illustrates an example of the sequence of steps in the proposed process;

[0034] - [Fig.3] schematically illustrates a developed projection of a journey to be made, divided into a succession of segments, each segment being assigned attributes, each segment presenting a variation of energy, the upper curve representing the trajectory of energy stored in the battery;

[0035] - [Fig.4] is a graphical representation of a first example of a path divided into segments, with the corresponding energy trajectories;

[0036] - [Fig.5] is a graphical representation of a second example of a path divided into segments, with the corresponding energy trajectories;

[0037] [Fig. 6] is a graphical representation of a third example of a path divided into segments, with the corresponding energy trajectories.

[0038] [Fig. 7] schematically illustrates an example of the control system involved.

[0031] In the various figures, the same reference numerals designate identical or similar elements. For clarity, some elements are not necessarily shown to scale.

[0039]

[0032] With reference to Figure 1, a hybrid vehicle generally has a drivetrain 1 with a thermal engine 4 and one or more electric machines associated with a traction battery 3.

[0040]

[0033] An electric machine EM, designated 2, forms the electric traction machine. Note that there may be another traction machine on an axle other than the one illustrated in Figure 1.

[0041] The internal combustion engine 4 is an internal combustion engine powered by hydrocarbon fuel. It can be a gasoline engine or a diesel engine. The fuel is contained in a tank 15.

[0042]

[0035] In the illustrated example, the kinematic chain may include a second electric machine EM2, identified as 12, mechanically linked to the heat engine 4, which acts mainly as a generator but can also act as a motor to start the heat engine 4.

[0043]

[0036] The hybrid vehicle may be a plug-in hybrid vehicle, in which case it is equipped with an on-board charger 31 and a charging socket 30. The invention is applicable both to 'plug-in' vehicles and to vehicles equipped with a battery not rechargeable by an external source.

[0044]

[0037] The battery capacity can in practice be several tens of kWh. Depending on the target range in zero-emission mode, the energy storage capacity can typically be between 5 kWh and 60 kWh.

[0045] The state of energy (SOE) of the traction battery is defined as a parameter that characterizes the amount of energy remaining in the battery. It is an indication between 0 and 100%, similar to a fuel gauge. This parameter can also be called the state of charge (SOC) of the battery. This information can also be expressed in watt-hours.

[0046]

[0039] In a plug-in hybrid vehicle configuration, it may be desirable to maximize the use of electrical energy and therefore the on-board electronic unit for managing operating modes may be configured to target a fairly low SOE while driving.

[0047] The electric machine 2 is controlled by an inverter 11 supplied with electrical energy by the battery 3. In certain operating modes, the kinematic chain 1 allows mechanical energy to be taken from the wheels of the vehicle and returned to the battery 3. The inverter 11 and the electric machine 2 then operate in a generator mode.

[0048] The drivetrain includes a transmission 14, which usually includes a differential and may also include a more or less complex gearbox. The drivetrain terminates at the wheel 29 with a wheel shaft 16.

[0042] The drivetrain 1 can operate in zero-emission mode (ZEM in this document), namely with the internal combustion engine 4 stopped, the drivetrain is then in purely electric mode.

[0049]

[0043] Furthermore, the drivetrain 1 can operate in hybrid mode (HYM in this document), i.e., with the internal combustion engine 4 running. The internal combustion engine generally contributes to the traction function, without excluding an engine braking function.

[0050] The switch from one mode to another is made according to the operational conditions of use of the vehicle, in particular according to the power requirement, and the state of charge of the traction battery.

[0051] The vehicle is equipped with at least one electronic control unit (ECU) responsible for selecting the most appropriate mode (ZEM or HYM) based on a series of criteria. More generally, the powertrain is controlled by electronic control systems that implement basic logic for selecting the current operating mode: either zero-emission ZEM or hybrid HYM. This basic logic can be called the hybrid vehicle's energy management law.

[0052]

[0046] The choice of the appropriate mode by the electronic control unit generally depends, for example, on parameters such as the speed of the vehicle, the torque demand applied to the accelerator pedal by the driver, and the current state of charge of the battery.

[0053] The basic logic may involve pursuing a target SOE or maintaining within an SOE range between SOEmin and SOEmax, in order to preserve a good battery health as proposed in document FR3061471.

[0054] As shown in Figure 7, the control system generally includes a geolocation and navigation system 8, and a battery monitoring system 9, commonly referred to as a BMS (Battery Management System). The BMS provides information about the battery, including its temperature, and can also display the current drawn from the battery. The electronic control unit 5 includes computing resources and at least one memory area 50 for storing the tables used in the process calculations.

[0055] Furthermore, the electronic control unit 5 receives information from the HVAC heating and air conditioning system. It can optionally receive information on the vehicle's load and the presence of a towed trailer ('Load & Tow'). The electronic control unit 5 can also optionally receive the outside temperature 'T°C ext'.

[0056] Advantageously, the method promoted here proposes to make an exception to the basic logic, based on a projection reasoning on the segments of the route.

[0057]

[0051] The proposed method comprises successive steps, as illustrated in Figure 2.

[0052] Step a) comprises acquiring, using the navigation system 8, a route to be followed. The navigation system may be one of the systems on board the vehicle or may be a system available on a remote server via cellular communication between the vehicle and the remote server.

[0058] Step a) involves defining a division of the route to be taken into a plurality of successive segments Ti. In the navigation system, the route to be taken is usually partitioned into route segments. The concept of a navigation segment is notably linked to road intersections and necessary forks. The concept of a segment in this document differs from the concept of a route segment. The route to be taken consists of reaching a destination point from the current position via a calculated and planned route.

[0059] [0 Each segment is a homogeneous portion of the journey, in the sense of certain characteristics of the road traveled, particularly from the point of view of the energy required to move the vehicle on that segment.

[0060]

[0055] The reader may refer to document FR3061471 for further details regarding step a).

[0061]

[0056] All the segments Ti are adjacent; the set of segments placed end-to-end constitutes the path to be followed. An example of a path illustrated in Figure 3 begins with segment T1, then segment T2, then segment T3, then segment T4, then segment T5, and ends with segment TN. The generic segment is denoted Ti. Figure 3 represents a straight path for clarity, but the actual path is naturally often curved. However, one can still use the distance projection onto a straight line as shown in Figure 3.

[0062]

[0057] The route to be followed is reviewed periodically, in particular from time to time as the vehicle moves forward, and also as soon as a change of route is detected that deviates from the previously planned route. The navigation system then recalculates the route on a new basis. If the navigation system is not used to define a destination, the vehicle's onboard calculation methods may be based on the vehicle's usual routes; these may be, for example, the commute to and from work or any other usual route taken by the vehicle.

[0063] Each Ti segment has ATB attributes that characterize said segment.

[0064] The ATB attributes of each segment include: length, gradient, and average speed. This allows us to calculate, based on the vehicle parameters described later, the mechanical power required to move the vehicle. From this, we can deduce the electrical power required for future travel on this segment, given these attributes and the vehicle parameters.

[0065]

[0061] The gradient of the section can be expressed in degrees or as a percentage; it can be positive (uphill section) or negative (downhill section).

[0062] The average speed observed is distinct from the maximum speed limit on the section. The average speed observed is representative of the speed statistically observed on the section in question by the vehicles traveling on it. This information can be obtained by connected collaborative systems installed on board the vehicles in use, or by fixed systems installed on infrastructure, such as traffic monitoring cameras.

[0066] [0 Incidentally, ATB attributes can also include the type of road, the nature of the pavement, without excluding dynamic information such as congestion, traffic, ongoing roadworks, etc., which allows for refining the calculations presented in the previous paragraph. Wind (direction and intensity) and rain can also be taken into account where applicable.

[0067] Step b) includes an estimation of a projection of energy variation in the battery on each segment Ti of the journey to be undertaken, assuming that the vehicle remains in zero emission electric mode (ZEM).

[0068]

[0065] For section T1, the electronic control unit calculates, based on the section attributes and vehicle characteristics, the mechanical power required to move along the section. It then calculates the electrical energy required by the electric machine(s) to move along section T1 without any contribution from the internal combustion engine 4. The result is denoted E1 and expressed in watt-hours. This result may be negative in certain cases where energy is stored in the battery, for example, on a downhill section. The operation is repeated for section T2, which gives the result E2, for section T3, which gives the result E3, and generically for section Ti, which gives the result Ei.

[0069] The vehicle characteristics used in the above-mentioned calculation include, in particular, the vehicle's weight, its load, and its aerodynamic drag coefficient (Cx).

[0070]

[0067] The case of a vehicle towing a trailer or caravan is also taken into account; all the elements that increase the vehicle's weight amplify the energy calculations, both in terms of consumption and recovery. Similarly, auxiliary consumers such as the heater or the air conditioning compressor can be included in the energy expenditure. To this end, the electronic control unit 5 is designed to receive the outside temperature and / or relevant information directly from the HVAC heating and air conditioning system. Lighting consumption can also be taken into account depending on the expected lighting conditions along the route (nighttime, unlit tunnel).

[0071] The calculation of energy consumed or recovered in each section is thus as representative as possible of the vehicle's imminent journey.

[0072]

[0069] It can be seen on the stepped curve 6 shown in the middle part of Figure 3 that the energy values ​​of the sections can be positive or negative. In this case, the energy variations on sections T3, T6, and Ti are negative, while all the others are positive. When the value of Ei is positive, a quantity of electrical energy will be consumed on the section in question, whereas when the calculated value of Ei is negative, this means, conversely, that electrical energy will be recovered on the section in question.

[0073]

[0070] Step c) includes calculating an energy trajectory in the vehicle battery from the current energy EGY_CRT and the energy variation trajectory in the battery as well as the current position PC of the vehicle.

[0074]

[0071] The upper curve of Figure 3 shows the SOE gauge as a function of the distance traveled.

[0075]

[0072] The current energy value at the vehicle's current position PC is EGY_CRT. The energy value then changes according to the energy variation trajectory discussed above. For the current segment, the calculation is performed proportionally to the vehicle's progress within the current segment, based on knowledge of the current position PC.

[0076] We can see that the current energy trajectory identified as 7 decreases for the remainder of section T1 and then decreases with a less pronounced slope for section T2. ​​Conversely, the current energy trajectory 7 shows an increase in section T3 where the energy consumption variation E3 of section T3 is negative.

[0077] The next step, called d), involves determining a classification of each Ti segment, based on the energy trajectory 7.

[0078]

[0075] In the non-limiting illustrated example, each segment is assigned a class chosen from four classes C1 to C4. Alternatively, the classification could include three or more than four classes.

[0079]

[0076] The first class C1 is indicative of a favorable (or at least satisfactory) evolution of the energy trajectory in the battery in the following sections.

[0080]

[0077] Under these conditions, it is possible to apply the exception for managing modes defined by the basic logic and to delay the start of the internal combustion engine.

[0081] The process is designed to include a step (denoted c2) for determining a high battery energy threshold H_BAT_EGY and a low battery energy threshold L_BAT_EGY. The classification of the segments is established, in particular, with respect to these thresholds. These thresholds H_BAT_EGY and L_BAT_EGY are shown in Figures 4 to 6. It should be noted that these thresholds H_BAT_EGY and L_BAT_EGY are independent of any interval thresholds SOEmin and SOEmax of the basic logic mentioned above.

[0082] For the high battery energy threshold H_BAT_EGY, we can choose H_BAT_EGY = EGY_CRT + H_EGY_OFS.

[0083]

[0081] H_EGY_OFS is configurable and allows the upper threshold to be defined as the current energy summed by this strictly positive parameter. Thus, the energy trajectory will need to recover an energy level higher than the current energy to activate the maintenance of the electric traction mode, indicating that the vehicle will naturally store energy in its battery and that a hybrid traction mode is therefore probably not necessary for energy reasons.

[0084] The L_BAT_EGY threshold can be calculated as follows:

[0085] L_BAT_EGY = EGY_TG - MIN_REG_EGY_RANGE - L_EGY_OFS

[0086] EGY_TG is the target battery energy, information emitted by the basic battery energy optimization function.

[0087] L_EGY_OFS is configurable and allows you to define the lower threshold as the target energy subtracted from the MIN_REG_EGY_RANGE energy quantity and this parameter. This is the threshold below which the battery is too low, outside the normal battery regulation zone, and therefore undesirable (increased risk of low energy if a performance event occurs, potentially limiting battery power, etc.).

[0088]

[0086] It is noted that the L_BAT_EGY threshold can be made dependent on the battery temperature, or other battery-related characteristics.

[0089]

[0087] When for a given section, the current energy (EGY_CRT) is greater than the high battery energy threshold (H_BAT_EGY), then the affected class is the first class C1.

[0090] When, for a given section, the current energy EGY_CRT is lower than the low battery energy threshold L_BAT_EGY over at least a certain predetermined distance DIST_L_MAX_BAT_EGY marked 93 (see figure 5), then the assigned class is the third class C3. In this case, it is necessary to inhibit the delay of the combustion engine start; the conventional logic of choosing the hybrid mode HYM or zero emission ZEM remains.

[0091] When, for a given section, the current energy EGY_CRT is between the lower battery energy threshold L_BAT_EGY and the upper battery energy threshold H_BAT_EGY, and the power demanded in the following section or one of the following sections is greater than a maximum power of the electrical machine(s), then the class affected is a second class C2 or a fourth class C4.

[0092] More specifically, if the SOE energy level is satisfactory in the sections preceding the section under consideration, then the 2nd class C2 is chosen, whereas otherwise the 4th class C4 is chosen.

[0093] Step e) involves determining a series of requests to maintain the electric traction mode, as an exception to the basic logic. For this, a binary delay information (RETDEM) is established for each section. This binary information, when present, indicates the possibility of delaying the restart of the internal combustion engine and maintaining the zero-emission mode (ZEM).

[0094]

[0092] The RETDEM delay binary information is established according to the class assigned to each segment. For example, the RETDEM delay binary information is set to 1 for a segment assigned to the first class C1.

[0095] Figure 4 illustrates a planned route starting from a relatively high energy level in the EGY_CRT battery. In the first 3 segments, the POW consumed is very low. In the 4 e In sections 5 and 6, the power output (POW) is higher between times t11 and t12, and the energy quantity decreases quite sharply. Then, between times t12 and t13, the power consumption is again very low, and the energy quantity no longer decreases. Finally, between times t13 and t14, there is again a higher power demand and energy consumption that causes the energy quantity curve to fall below the lower threshold L_BAT_EGY. The portion below the threshold encompasses an area of ​​superelevation 91 relative to the lower threshold L_BAT_EGY.

[0096]

[0096] From time t14 the power curve goes below 0 and therefore electrical energy is recovered, which allows the energy quantity curve 7 to take an increasing slope and to go back above the lower threshold L_BAT_EGY.

[0097]

[0097] Then between times t14 and t15, the power remains negative and the energy balance is positive.

[0098] Then, between times t15 and t16, there is again a higher power demand and energy consumption that causes the energy quantity curve 7 to fall below the lower threshold L_BAT_EGY. The portion below the threshold encompasses an area 92 of overhang relative to the lower threshold L_BAT_EGY.

[0099] Then between times t16 and t17, the power absorbed is substantially negative (recovery section) and the energy balance is strongly positive.

[0100]

[0100] From time t17 passing the energy quantity curve 7 passes above the high battery energy threshold H_BAT_EGY, and the class of the section becomes C1.

[0101] Regarding the classification of each section, up to time t13, the amount of energy is between the lower threshold and the upper threshold, and therefore the class is the 2nd class C2.

[0102]

[0102] Between times t13 and t14, the quantity of energy is below the lower threshold, the class remains the 2nd class C2.

[0103]

[0103] Between times t14 and t15, the quantity of energy is above the lower threshold, the class remains the 2nd class C2.

[0104] Between times t15 and t16, the amount of energy is below the lower threshold, the class remains the 2nd class C2.

[0105]

[0105] In the lower part of Figure 4, it can be seen that the RETDEM start delay binary information of the internal combustion engine is set to the value 1.

[0106]

[0106] Step f) of the method consists of actually using the RETDEM information for the current or upcoming section. This is when the preparatory projection work discussed so far is implemented. Of course, if the SOE energy level drops more than expected during the phase in which the zero-emission mode has been maintained, then restarting the internal combustion engine 4 is possible. If, in step f), the RETDEM start-delay binary information is 0, no particular action is taken; the basic logic for selecting the zero-emission mode (ZEM) or hybrid mode (HYM) prevails. Step f) as presented here can be applied to all variant embodiments disclosed in this document.

[0107]

[0107] Incidentally, in Figure 4, an auxiliary class, denoted C2A, is identified. This class is determined when the SOE energy level is below the lower threshold, but with preceding segments having higher energy levels, and, in the case of the second segment, a brief dip below the lower threshold. Figure 5 illustrates another planned route starting from a relatively high energy level in the EGY_CRT battery. In the first three segments, the POW consumed is very low, between times t21 and t22. Several subsequent segments do show a decrease, but do not show a dip below the lower threshold L_BAT_EGY. As in the previous case, the second class, C2, is assigned, and the RETDEM binary information for the start-up delay of the internal combustion engine is set to the value 1.

[0108]

[0109] In the following sections, starting with the 4th, one or more of the sections to be followed (between times t24 and t26) are subject, in the energy trajectory projection, to a long passage below the lower threshold L_BAT_EGY. Under these conditions, the binary information for the RETDEM start delay of the internal combustion engine is set to the value 0.

[0109] It can be observed from this that there is not necessarily a one-to-one correspondence between the class of a segment and the value of the binary information RETDEM start-up delay. Here, at time t25, the class of the next segment is class C3. Here, at time t26, the class of the next segment is class C4 because a certain predetermined distance DIST_L_MAX_BAT_EGY (ref 93) has been covered with an energy level close to or below the low threshold.

[0110] The part below the threshold encloses an area 91 which is in strong slope relative to the lower threshold L_BAT_EGY.

[0111] From time t26, the power curve goes below 0 and therefore electrical energy is recovered, which allows the energy quantity curve 7 to take an increasing slope and go back above the lower threshold L_BAT_EGY.

[0112] Then between times t26 and t27, the power remains negative and the energy balance is positive, the energy quantity curve 7 temporarily passes above the high battery energy threshold H_BAT_EGY.

[0113] Then, between times t27 and t28, there is again a higher power demand and energy consumption that brings the energy quantity curve 7 below the lower threshold L_BAT_EGY. The portion below the threshold encompasses an area of ​​92 degrees of overhang relative to the lower threshold L_BAT_EGY. Then, between times t28 and t29, the absorbed power is substantially negative (recovery section) and the energy balance is strongly positive.

[0114] From time t29 the energy quantity curve 7 passes above the high battery energy threshold H_BAT_EGY and the class of the segment to follow is C1, then the RETDEM start delay binary information is set again to the value 1, whereas from times t22 to t29, the RETDEM start delay binary information is set to the value 0.

[0115] Figure 6 illustrates yet another planned route starting from a given energy level in the EGY_CRT battery. In the first two segments, the power consumption (POW) is very low between times t31 and t32, and several subsequent segments do show a decrease but do not fall below the lower threshold L_BAT_EGY. As in the previous case, the second class is assigned, and the RETDEM binary information for the start-up delay of the internal combustion engine is set to the value 1.

[0116] In subsequent sections, starting with the third, one or more of the following sections (between times t34 and t35) experience a power demand exceeding a threshold PELmax, where PELmax is the maximum power developed by the electrical machine(s). Between times t34 and t35, the classification results in class 3A, indicating that the electrical machines cannot meet the power demand and that the backup power of the internal combustion engine is mandatory. Consequently, the RETDEM binary information for the start-up delay of the internal combustion engine is set to 0.

[0117] In the documented sections, from the third onwards, it also turns out that one or more sections to follow (between times t33 and t36) are subject in the energy trajectory projection to a long passage below the lower threshold L_BAT_EGY.

[0118]

[0120] Between times t35 and t36, the process determines class C3.

[0119] Under these conditions, the RETDEM binary start delay information of the internal combustion engine is set to the value 0.

[0120]

[0122] From time t36, the class of the subsequent section of the following is class C4.

[0121]

[0123] More generally, classes C3 and C4 result in the RETDEM start delay binary information of the internal combustion engine being set to the value 0. Class C1 results in the RETDEM start delay binary information of the internal combustion engine being set to the value 0.

[0122] Steps c) to f) are repeated, with a sliding horizon of predetermined depth. In other words, we work on a sliding computation window.

[0123]

[0125] The predetermined depth of the sliding calculation window can have a distance depth of 2 km to 10 km. We are reasoning in the short term, but we benefit advantageously from recurrence. Recurrence allows us to take into account the starting of the internal combustion engine, which can occur in real life, whereas in the projection presented above, we assume that the internal combustion engine is not used for the energy projections.

[0124]

[0126] It should be noted that there is no long-term projection. The technical solution proposed here is not intended to manage the battery's energy to travel certain sections of road in all-electric mode, but rather to observe a natural increase in the battery's energy level, thus allowing for purely electric driving without starting the internal combustion engine.

[0127] It should be noted that there is no battery energy storage. The technical solution proposed here is not intended to increase the battery's energy for a given event, but rather to observe a natural increase in the battery's energy level, thus allowing for purely electric driving without starting the internal combustion engine.

[0128] It should be noted that there is no manual intervention by the driver; the system is completely transparent to the driver.

Claims

DEMANDS 1. A method for optimizing the fuel consumption and driving pleasure of a hybrid vehicle comprising a fuel-powered internal combustion engine and an electric motor powered by a traction battery, the method being characterized in that it comprises: a) acquiring, by means of a navigation system, a route to be followed, and defining a division of the route to be followed into a plurality of successive segments (Ti), each segment (Ti) having attributes (ATB) characterizing said segment; b) estimating a projection of energy variation (6) in the battery over each segment of the plurality of segments of the route to be followed, assuming that the vehicle remains in zero-emission electric (ZEM) mode; c) calculating an energy trajectory (7) in the vehicle's battery from the current energy and the projection of energy variation in the battery as well as the current position of the vehicle.d) determining a classification for each segment of the plurality of segments of the journey to be undertaken, based on the energy trajectory, with at least a first class (C1) indicating a favorable evolution of the energy trajectory in the battery in the segments following the segment to be classified; e) determining a series of requests to maintain the electric traction mode, with a binary delay information for each segment, based on the class assigned to each segment, with at least the binary delay information being set to 1 for a segment assigned the first class (C1); f) implementing, where appropriate, the maintenance of the electric traction mode (ZEM), by delaying the start of the internal combustion engine, based on the value of the binary delay information, for the current segment or the following segment.

2. Method according to claim 1, wherein each section is assigned a class chosen from at least three classes (C1-C4).

3. A method according to any one of claims 1 to 2, wherein steps c) to f) are repeated, with a sliding horizon of predetermined depth.

4. A method according to any one of claims 1 to 3, wherein the attributes (ATB) of each segment include: length, slope, average observed speed.

5. A method according to any one of claims 1 to 4, further comprising: c2) determining a high battery energy threshold (H_BAT_EGY) and a low battery energy threshold (L_BAT_EGY), the classification being established in particular with respect to these thresholds.

6. Method according to claim 6, wherein, when, for a given section, the current energy (EGY_CRT) is between the lower battery energy threshold (L_BAT_EGY) and the upper battery energy threshold (H_BAT_EGY), then the class depends on the respective class of the preceding sections, and the energy demand of the following sections.

7. Method according to claim 6, wherein, when for a given section, the current energy (EGY_CRT) is greater than the high threshold of battery energy (H_BAT_EGY), then the class affected is the first class (C1).

8. Method according to claim 6, wherein, when for a given section, the current energy (EGY_CRT) is less than the low battery energy threshold (L_BAT_EGY) over at least a certain predetermined distance (DIST_L_MAX_BAT_EGY), then the affected class is the third class (C3).

9. Method according to claim 6, wherein, when, for a given section, the current energy (EGY_CRT) is between the lower battery energy threshold (L_BAT_EGY) and the upper battery energy threshold (H_BAT_EGY), and the power demanded in the following section or one of the following sections is greater than a maximum power of the electrical machine(s), then the class affected is a second class (C2) or a fourth class (C4).

10. Hybrid vehicle, comprising at least one electronic control unit in which the method according to any one of claims 1 to 9 is implemented.

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