Method for managing regenerative braking of an electric or hybrid motor vehicle

Abstract

A method for managing a regenerative braking of an electric or hybrid motor vehicle, comprising acquiring data via a driver assistance system and an electronic horizon provider module, calculating different deceleration values on the basis of said data, arbitrating the calculated deceleration values in order to select the most suitable value, and determining a provisional optimal regenerative power on the basis thereof.

Description

[0001] TITLE: Method for managing regenerative braking of a vehicle with an electric or hybrid motor

[0002] The invention relates to a method for managing regenerative braking of a motor vehicle with an electric or hybrid engine. The invention also relates to a method for adaptively controlling regenerative braking. The invention finally relates to a system for managing regenerative braking of a vehicle.

[0003] In the automotive industry, the autonomy of vehicles equipped with an electric powertrain, i.e. with an electric or hybrid engine, is a crucial service for users. Also, it is known to equip such vehicles with energy recovery means and methods to increase their autonomy, also called "regenerative braking". Regenerative braking is one of the operating modes of the electric powertrain allowing, when the driver takes his foot off an accelerator pedal, the deceleration of the vehicle while recovering electrical energy. Indeed, the loss of kinetic energy of the vehicle is then converted into electrical energy capable of being stored in an electric traction battery of the vehicle or directly used for driving or any other electrical consumer equipping the vehicle.Energy recovery processes can conventionally be carried out according to different regenerative powers accompanied by variable levels of quantity of recovered energy and deceleration of the vehicle. They are preprogrammed and organized according to different regenerative braking modes that can be selected by the driver, for example via a gear lever position, a paddle equipped on the vehicle's steering wheel or via predefined driving modes accessible via a human-machine interface. A disadvantage of such vehicles lies in the fact that such a selection is carried out manually by the driver. As a result, the adjustment of the regenerative braking power may be unsuitable for the vehicle's driving context and be accompanied by non-optimal or even ineffective energy recovery.Conversely, improper adjustment of regenerative braking can result in sudden deceleration that could endanger the driver and passengers.

[0004] Document CN113997792 describes a system offering automatically modulated regenerative braking services, but this still leads, in certain complex driving situations, either to excessive braking to the detriment of comfort, or to insufficient braking to the detriment of the safety of the driver and passengers.

[0005] The present invention falls within this context and aims to propose a method for managing regenerative braking of a vehicle which overcomes the above drawbacks and makes it possible to optimize the use of the vehicle, ensuring the comfort and safety of the driver and his passengers.

[0006] The invention relates to a method for managing regenerative braking of an electric or hybrid motor vehicle equipped with a driving assistance system and an electronic horizon supplier module, the method comprising, in a driving situation:

[0007] - a step of acquiring data relating to the vehicle and the environment outside the vehicle via the driving assistance system;

[0008] - a step of acquiring data relating to the environment outside the vehicle via the electronic horizon supplier module;

[0009] - a step of calculating, by a processing unit, at least one value of a first recommended deceleration on the basis of the data from the driving assistance system, and a step of calculating, by the processing unit, at least one value of a second recommended deceleration on the basis of the data from the electronic horizon supplier module; - an arbitration step, according to at least one predefined arbitration law based on at least one criterion, selecting at least one most suitable forecast deceleration value based on said criterion between the at least one recommended first deceleration value and the at least one recommended second deceleration value;

[0010] - a step of determining, as a function of the predicted deceleration value, a predicted optimal regenerative power and / or an energy recovery mode, capable of implementing such optimal regenerative power, to be applied automatically if it is detected that the driver lifts his foot from an accelerator pedal.

[0011] Notably :

[0012] - the data from the driver assistance system are at least relative to a distance and a relative speed of at least one primary target located in the road infrastructure;

[0013] - the data from the electronic horizon supplier module and are at least relative to a distance, a relative speed and a recommended speed of movement of the vehicle at the level of at least one secondary target considered located in the road infrastructure; and

[0014] - the at least one recommended first deceleration value is defined as a function of the distance and the relative speed of the at least one primary target and the at least one recommended second deceleration is defined as a function of the distance, the relative speed and the recommended speed of movement of the at least one secondary target.

[0015] Optionally, at least one arbitration criterion is selected from:

[0016] - a degree of confidence in the acquired data, specific to the data from the driving assistance system and to the data from the electronic horizon supplier module;

[0017] - a probability of relevance of the deceleration considered based on an estimated position of the vehicle in the road infrastructure;

[0018] - a degree of energy optimization of the deceleration considered; and / or

[0019] - a degree of importance of at least one recommended first deceleration value and at least one recommended second deceleration value.

[0020] The management method may further comprise:

[0021] - a step of acquiring additional data relating to limitations of the vehicle specific to a predefined driving mode and / or to at least one component equipping the vehicle selected from an electric powertrain, an electric traction battery, an electronic component, a heat exchanger, a chassis and / or shock absorbers;

[0022] - a step of limiting at least one forecast deceleration value and / or forecast optimal regenerative power by a first minimum threshold and first maximum threshold which are specific to them defined according to the additional data relating to the limitations of the vehicle.

[0023] Optionally, the management method may further include:

[0024] - a step of acquiring additional data relating to the context external to the vehicle concerning the geographical location of the vehicle, weather conditions and / or characteristics specific to a road traveled by the vehicle;

[0025] - a step of adjusting at least one recommended first deceleration value, at least one recommended second deceleration value, at least one forecast deceleration value and / or forecast optimal regenerative power to be applied based on said additional data relating to the context external to the vehicle.

[0026] Optionally, the management method further comprises:

[0027] - a step of acquiring data relating to a driving context, in particular relating to the urban, peri-urban or extra-urban location of a road traveled by the vehicle;

[0028] - a step of assigning a second predefined minimum threshold of the at least one forecast deceleration value and / or forecast optimal regenerative power to be applied as a function of the driving context. In particular, the management method may further comprise at least one prior step of providing information on at least one user preference relating to one or more energy recovery modes, to a preferred minimum and / or preferred maximum value of forecast deceleration and / or forecast optimal regenerative power, the method further comprising a step of adjusting the forecast deceleration value and / or forecast optimal regenerative power as a function of the at least one preference.

[0029] Optionally, the management method further comprises a step of transmitting a visual and / or audible information message concerning the predicted deceleration value, the at least one predicted optimal regenerative power value and / or the energy recovery mode, capable of implementing such regenerative power, to be applied automatically if it is detected that the driver lifts his foot off the accelerator pedal.

[0030] The invention also relates to a method for adaptively controlling regenerative braking of a vehicle comprising, initially, the steps of the management method according to the invention, then a step of detecting an action of a driver lifting his foot, partially or completely, from the accelerator pedal and, when it is detected that the driver lifts his foot from the accelerator pedal, at least one regenerative braking step to which the determined forecast optimal regenerative power and / or the determined energy recovery mode is automatically applied.

[0031] The invention also relates to a system for managing regenerative braking for an electric or hybrid motor vehicle equipped with a driving assistance system and an electronic horizon provider module, the system comprising hardware and / or software elements implementing the management method according to the invention, the hardware elements comprising at least one data processing unit, capable of receiving data from the driving assistance system and the electronic horizon provider module and a control module capable of controlling an electric powertrain of the vehicle.

[0032] The invention also relates to a motor vehicle with an electric or hybrid engine equipped with a driving assistance system and an electronic horizon supplier module, the vehicle further comprising a management system according to the invention.

[0033] The invention further extends to a computer program product comprising program code instructions recorded on a computer-readable medium for implementing the steps of the management method and / or the control method according to the invention when said program operates on a computer. Alternatively, the invention relates to a computer program product downloadable from a communication network and / or recorded on a data medium readable by a computer and / or executable by a computer comprising instructions which, when the program is executed by the computer, cause the latter to implement the management method and / or the control method according to the invention.

[0034] The invention finally extends to a data recording medium, readable by a computer, on which is recorded a computer program comprising program code instructions for implementing the management method and / or the control method according to the invention.

[0035] Other details, characteristics and advantages will emerge more clearly on reading the detailed description given below, for informational and non-limiting purposes, in relation to the various examples of embodiment illustrated in the following figures:

[0036] Figure 1 is a schematic view of an embodiment of a system for managing regenerative braking for a vehicle with an electric or hybrid motor. Figure 2 is a general flowchart of an example of execution of a method for adaptively controlling regenerative braking of the vehicle and of a method for managing regenerative braking of the vehicle.

[0037] Figure 3 is a flowchart detailing alternative executions of the methods according to the invention.

[0038] Figure 4 is a flowchart detailing alternative executions of the methods according to the invention.

[0039] Figure 1 schematically illustrates an embodiment of a motor vehicle 1, in particular a vehicle 1 comprising an electric powertrain 11. The vehicle 1 has an electric or hybrid engine. The vehicle 1 is capable of implementing regenerative braking, that is to say, in a known manner, of converting kinetic energy generated by the deceleration of the vehicle into electrical energy capable of being stored in an electric traction battery of the vehicle or directly used for driving. Also, the vehicle 1 is, for example, a private vehicle, utility vehicle, a truck or a bus. Optionally, the vehicle 1 considered is a connected vehicle or even an autonomous vehicle.

[0040] Throughout the description below, the vehicle 1 comprising the means for implementing the invention may also be referred to as the “ego” vehicle in order to distinguish it from other surrounding vehicles, the term “ego” in itself not conferring any technical limitation on the motor vehicle 1. The terms “primary”, “secondary”, “first” or “second” are intended to distinguish similar elements or principles and not to define a hierarchy.

[0041] The vehicle 1 is equipped with at least one driving assistance system 2, or ADAS, from the English "Advance Driving Assist System" making it possible to adapt the driving conditions of the vehicle 1, such as its longitudinal speed, according to the context in which the vehicle 1 is traveling, in particular according to primary targets present in the road infrastructure. For example, the primary targets are moving obstacles, such as vehicles of any type or pedestrians, or fixed obstacles, such as elements of the road infrastructure selected, in a non-limiting manner, from among traffic signs, authorized longitudinal speed limit signs or even traffic lights. In a known manner, such a driving assistance system 2 is capable of identifying situations relating to the external environment located in front of the vehicle by means of at least one detection means 3 equipping the vehicle 1.For example, such a detection means 3 is a sensor, a radar, a lidar and / or a camera. Preferably, the vehicle 1 ego comprises a plurality of detection means 3, equipped at the front or on the side parts of the vehicle 1 ego. These are capable of detecting the aforementioned primary targets, of identifying information provided by said targets, but also of extracting data such as the distance of the primary target considered relative to the vehicle 1 ego, or inter-distance, the relative speed of said target, corresponding to the difference in speed between the vehicle 1 ego and said target, or even, optionally, the absolute speed of the primary target considered.

[0042] The vehicle 1 is also equipped with a horizon provider module 4. Such a module comprises a location means 5 or communicates with a location means 5 equipped in the vehicle 1 in order to provide an electronic horizon, also referred to as an e-horizon, i.e. an estimated map of the road infrastructure and the environment outside the vehicle 1. The electronic horizon comprises a set of possible roads or routes located in front of the vehicle 1, particularly over a defined distance, for example of the order of 5 to 10 km, and secondary targets which may relate to any element defining the road infrastructure in such an area, as further detailed below. The electronic horizon associates in particular with each road or route a probability of being traveled by the vehicle 1.The location means 5, included in the vehicle 1 and / or in the horizon provider module 4, makes it possible to locate the position of the vehicle 1 in the road infrastructure, in particular by satellite. It integrates, for example, a system for locating the vehicle 1 and / or a map of the road infrastructure. In particular, the location of the vehicle 1 can be provided by a GPS type system, from the English acronym “Global Positioning system”. The location of the vehicle 1 makes it possible to extract from a mapping database information concerning the road infrastructure, speed limits, the topology and / or the geography of roads around the position of the vehicle 1. The location means 5 preferably comprises an inertial unit, also called a vehicle dynamics motion analyzer 1, IMU or ADMA, from the English acronym “Automotive Dynamic Motion Analyzer”.

[0043] The vehicle 1 comprises an automated management system for regenerative braking, which comprises hardware and / or software elements capable of implementing, or designed to implement, a method for managing regenerative braking 100 and / or a method for adaptive control 200 of regenerative braking of the vehicle 1, described below. Said hardware elements comprise at least one data processing unit 7 and a control module 8 capable of controlling the electric powertrain 11 of the vehicle 1.

[0044] The processing unit 7 is capable of receiving data from the driving assistance system 2 and the electronic horizon supplier module 4. It comprises at least one computer comprising hardware and software resources, more precisely at least one processor or microprocessor, capable of processing said data and executing instructions for implementing a computer program. The processing unit 7 comprises, or cooperates with, memory elements of the management system or of the vehicle 1. The control module 8 is configured to receive instructions from the processing unit 7 and to control the vehicle 1, in particular the electric powertrain 11 of the vehicle 1, as required in order to modulate a regenerative power and / or in order to select an energy recovery mode capable of implementing such regenerative power to be applied automatically.

[0045] Optionally, the management system 6 and / or the vehicle 1 further comprises a communication module 9 and / or a human-machine interface 10. The communication module 9 allows the vehicle 1 to receive data from a database or from one or more connected devices, such as a mobile phone, a connected watch or other, via a low-frequency or high-frequency wireless link. It may, for example, be a wireless link based on “cellular” or “Wifi” or “Bluetooth” technologies. The communication module 9 allows data relating to a context external to the vehicle 1 to be extracted, in particular to meteorological conditions or topological or geographical conditions of the road infrastructure. The human-machine interface 10 includes a screen.It is capable of broadcasting information, in particular an audio and / or visual message, and / or is capable of receiving data entered by a user, in particular relating to driver preferences.

[0046] An embodiment of the method 100 for managing regenerative braking of the vehicle is described below. Such a method is also comparable to a method for operating a vehicle 1 according to the invention. Such a method allows the automated management of the type of regenerative braking to be executed, i.e. the power of the regenerative braking executed, affecting in particular the intensity, or importance, of kinetic energy recovery implemented and the importance of the deceleration accompanying it. The management method 100 is intended to be executed in a driving situation, i.e. when the electric or hybrid powertrain 11 is in operation, regardless of whether the driver of the vehicle 1 takes his foot off an accelerator pedal or not. It is understood that the method does not apply to situations involving emergency systems, such as autonomous emergency braking, or AEB.

[0047] The method comprises, in a first step, a step E01 of acquiring data relating to the vehicle 1 and to the environment external to the vehicle 1 via the driving assistance system 2. For example, the data relating to the vehicle 1 concern a longitudinal speed of the vehicle 1, a position of the vehicle 1 relative to different lanes of a road traveled in question or other. The detection means 5 of the driving assistance system 2, described above, are capable of measuring and / or detecting in real time or at regular time intervals data specific to one or more primary target(s) located in the road infrastructure. The primary target considered may be a mobile obstacle, such as a vehicle 1 motor vehicle, bicycle or pedestrian. The primary target may also be fixed, for example of the type of traffic sign relating to a speed limit, stop or give way, or of the type of traffic lights.In particular, the driver assistance system 2 has image processing software to read said signs.

[0048] According to a particular embodiment, the driving assistance system 2 is capable of detecting and / or calculating a distance, or inter-distance, of the at least one primary target relative to the vehicle 1 ego and a relative speed of at least one primary target located in the road infrastructure. Such a principle extends to the different primary targets detected. For example, the relative speed of the primary target considered is defined as a function of an absolute speed of said target and the longitudinal speed of the vehicle 1 , detected at a given time t. Note that, in the case of a fixed target, the relative speed of the target is then equal to the longitudinal speed of the vehicle 1 ego. The method also comprises a step E02 of acquiring data relating to the environment outside the vehicle 1 via the electronic horizon provider module 4. The two acquisition steps E01, E02 are preferably executed simultaneously.As indicated above, the electronic horizon provider module 4 communicates to the processing unit 7 the data relating to secondary targets, in particular concerning a set of possible roads or routes located in front of the vehicle 1, in a predefined area, and any element of the road infrastructure located in such an area. In a known manner, the elements of the road infrastructure may be, by way of non-limiting example, traffic signs, such as speed limits, stop signs or give way signs, intersections, traffic lights, roundabouts, bends, pedestrian crossings or even tolls. The horizon provider module 4 detects and / or calculates in real time or at regular time intervals data specific to one or more secondary targets, in particular fixed targets located in the road infrastructure via the detection means 5 and / or the location means 5.

[0049] It is understood that, in the present method, a target considered may be a primary target and / or a secondary target, the adjectives “primary” and “secondary” here referring to a classification specific to the system or module acquiring the data relating to said target.

[0050] Similar to the driving assistance system 2, the horizon provider module 4 is able to detect and / or calculate a distance, or inter-distance, of the at least one secondary target relative to the vehicle 1 ego and a relative speed of at least one secondary target located in the road infrastructure. The same applies to different secondary targets.

[0051] According to a particular exemplary embodiment, the relative speed of the secondary target considered is defined as a function of a recommended traffic speed of the vehicle 1 at at least one secondary target considered located in the road infrastructure. Such recommended traffic speeds may be defined in advance by the automobile manufacturer. For example, a recommended traffic speed at a roundabout is of the order of 30 km / h, while such a speed is set at 0 km / h for a stop sign or for a traffic light. According to another example, such a speed may be calculated, for example as a function of a detected radius of curvature, in the case of a bend.

[0052] The acquisition of data from the driving assistance system 2 and the horizon supplier module 4 advantageously makes it possible to provide complementary data on the one hand, but also a redundancy of data relating to the same targets from different sources, more or less precise.

[0053] Once the various data have been received by the processing unit 7, the latter executes a calculation step E03 of at least one value of the first recommended deceleration D_r1 on the basis of the data from the driving assistance system 2. Similarly, the processing unit 7 executes a calculation step E04 of at least one value of a second recommended deceleration D_r2 on the basis of the data from the electronic horizon supplier module 4. Alternatively, the processing unit 7 calculates a range of values ​​of the first recommended deceleration D_r1 and / or a range of values ​​of the second recommended deceleration D_r2. The processing unit 7 thus determines at least one deceleration value considered to be optimal at a time t on the basis of the data from the driving assistance system 2 and the horizon supplier module 4 respectively, that is to say on the basis of means, targets and types of data which are specific to them.

[0054] According to a preferred embodiment, the first recommended deceleration D_r1 is calculated on the basis of a pre-calibrated law, for example arranged in the form of a map, as a function of the distance and the relative speed of the at least one primary target. A similar principle applies mutatis mutandis to the second recommended deceleration D_r2 relative to the at least one secondary target.

[0055] Thus, if the absolute speed of a primary target of the vehicle type is traveling at a speed strictly lower than the longitudinal speed of the ego vehicle, there is a risk of a rear-end collision. The processing unit 7 then defines a first deceleration D_r1 adapted to prevent a collision with this primary target. Similarly, if the detected secondary target is a sign indicating a speed limit or a secondary target for which a specific recommended traffic speed must be applied, the second deceleration is calculated to allow such a limit or recommended speed to be reached.

[0056] The processing unit 7 then executes an arbitration step E05. The arbitration step E05 is executed according to at least one predefined arbitration law, recorded on the memory element, according to at least one predefined criterion Kx, in particular according to several of said criteria Kx. Such a step aims to select at least one forecast deceleration value D_x considered to be the most suitable, according to the arbitration law and the at least one criterion considered, relative to the external context and to the vehicle 1, between the at least one recommended first deceleration value D_r1 and the at least one recommended second deceleration value D_r2. A similar principle applies mutatis mutandis for a range of forecast deceleration values ​​D_x when the at least one recommended first deceleration D_r1 and the at least one recommended second deceleration D_r2 are in the form of ranges of values.

[0057] The at least one criterion Kx is selected from a degree of confidence Dcf_x of the acquired data, a probability of relevance Pb_x of the deceleration considered as a function of the estimated position of the vehicle 1 in the road infrastructure, a degree of energy optimization Op_x of the deceleration and / or a degree of importance Lv_x of the at least one recommended first deceleration value D_r1 and of the at least one recommended second deceleration value D_r2.

[0058] The degree of confidence Dcf_x of the acquired data corresponds to a level of reliability, for example in the form of a scale or table, associated with the data from the driving assistance system 2 and the data from the electronic horizon provider module 4. In this sense, the method comprises, during the data acquisition step E01 via the assistance system, a sub-step of associating a degree of confidence Dcf_x by the driving assistance system 2 for each of the data specific to the at least one primary target. Similarly, the horizon provider module 4 associates, during the data acquisition step E02, a degree of confidence Dcf_x with the data relating to the at least one secondary target. For example, in a non-limiting manner, the degree of confidence Dcf_x depends on the type of detection means 3 used, the weather conditions, the traffic conditions, the geographical location or even the quality of a satellite connection.The degree of confidence Dcf_x can be determined by means of information from the detection means 3, the driving assistance system 2, the horizon provider module 4 and / or the location means 5. For example, data from a camera of the driving assistance system 2 has a lower degree of confidence Dcf_x at high longitudinal speed and in wet weather than at a lower longitudinal speed and in clear weather.

[0059] The probability of relevance Pb_x of the deceleration considered is a criterion linked to the estimation of the position of the vehicle in the road infrastructure and to the probability of each road or route being traveled by the ego vehicle. In other words, such a probability is indirectly linked to the relevance of the data associated with the at least one primary target or the at least one secondary target on the basis of an estimated position, via the driving assistance system 2, the horizon provider module 4 and / or the location means 5. It makes it possible to evaluate several possibilities of actions and / or routes relating to the environment outside the vehicle 1 located in front of it.Such a Kx criterion is particularly relevant when several roads are located close to each other and the vehicle equipment does not allow the vehicle 1 to be positioned in the road infrastructure with precision relative to the different possible roads and the road travelled and must therefore be based on an estimated, calculated position.

[0060] Similar to what has been explained above, the different acquisition steps E01, E02 then comprise, alternatively or additionally, a sub-step of assigning a probability of relevance Pb_x of the vehicle positioning data on the basis of information provided by the driving assistance system 2, the horizon provider module 4 and / or the location means 5 or, alternatively, the processing unit 7 assigns such a probability to said data when it receives them on the basis, in particular, of the probabilities of the roads and routes being traveled. For example, the longitudinal speed of the vehicle 1, the triggering of flashing lights and / or a route pre-recorded in the location means 5 can be used to define such probabilities.

[0061] Thus, for example, if the second recommended deceleration D_r2 is calculated on the basis of secondary targets essentially located on a road presenting a low probability of being traveled while the first recommended deceleration D_r1 is defined on the basis of data essentially relating to primary targets associated with a road presenting a higher probability of being traveled at a time t, the first recommended deceleration D_r1 will have a higher relevance probability Pb_x. The processing unit 7 will then preferentially select the first recommended deceleration D_r1 if the arbitration step E05 is executed on the basis of this arbitration criterion Kx. The degree of energy optimization Op_x of the deceleration is a criterion Kx aimed at minimizing energy losses while optimizing energy recovery.In other words, the need for slowing down is then assessed based on the need to conserve kinetic energy. This criterion Kx can be defined on the basis of at least one of:

[0062] - the distance, or inter-distance, separating the vehicle 1 ego from the at least one primary target and / or from the at least one secondary target;

[0063] - estimated durations of implementation of the first recommended deceleration D_r1 and the second recommended deceleration D_r2, for example calculated by the processing unit 7;

[0064] - an estimated quantity of energy recovered in the event of implementation of the first recommended deceleration D_r1 and the second recommended deceleration D_r2, for example calculated by the processing unit 7; and / or

[0065] - a charge level of the electric traction battery device.

[0066] The degree of importance Lv_x of the deceleration corresponds to a level of severity of the deceleration, in other words an importance of the braking. The processing unit 7 can then execute, during the arbitration step E05, a sub-step of comparing the first recommended deceleration D_r1 and the second recommended deceleration D_r2 in order to determine the largest deceleration value, i.e. the most significant or severe. The arbitration law can then be defined, preferentially, so as to automatically select the largest deceleration, for example for safety reasons.

[0067] The arbitration step E05 thus makes it possible to consider different deceleration strategies suggested by the driving assistance system 2 and the horizon provider module 4 respectively on the basis of data drawn from an environment that is more or less complementary depending on the targets, information and / or detection means 5 taken into account. The arbitration step E05 thus makes it possible to optimize the deceleration strategy to be applied at a time t by considering and judging said strategies. In particular, the arbitration step E05 makes it possible to consider deceleration strategies based on information and data provided by two separate sources, namely the horizon provider module 2 and the driving assistance system 2, in order to guarantee deceleration adapted to a wide range of situations.The arbitration step E05 thus makes it possible to optimize the deceleration strategy to be applied by selecting the most suitable strategy on the basis of the data provided by the horizon 2 supplier module and the driving assistance system 2, which are complementary in their perception of the environment outside the vehicle.

[0068] The processing unit 7 then executes a determination step E06, as a function of the forecast deceleration value D_x selected at the end of the arbitration step E05, of a forecast optimal regenerative power P_x to be applied automatically if it is detected that the driver lifts his foot from the accelerator pedal. Alternatively or additionally, the processing unit 7 can determine a pre-programmed energy recovery mode to be applied capable of implementing such an optimal regenerative power P_x.

[0069] Optionally, the calculation of the optimal regenerative power P_x can be refined by directly taking into account additional information relating to the vehicle 1 and / or the external environment, such as a mass of the vehicle 1, a slope of the road traveled by the vehicle 1 and / or a type or quality of the road traveled. This additional information can be measured in real time by the detection means 5, the driving assistance system 2, the horizon provider module 4 and / or the location means 5.

[0070] Figures 2 to 4 illustrate particular embodiments of the management method 100 implementing different limitations and adjustments that can be executed individually or in combination with each other. Optionally, the management method 100 further comprises the limitation of the predicted deceleration D_x and / or of the optimal regenerative power P_x as a function of limitations relating to the operation of the vehicle 1. In this sense, the method comprises a step E07 of acquiring additional data relating to limitations of the vehicle 1 specific to a predefined driving mode and / or to at least one component equipping the vehicle 1. Such a step can be executed simultaneously or successively with the acquisition steps E01 and E02 set out above implemented by the driving assistance system 2 and the horizon provider module 4 respectively.The limitations considered may be mechanical, chemical, thermal and / or electrochemical limitations. The at least one component considered is selected from the electric traction battery, an electronic component, in particular power electronics, a heat exchanger or chassis equipment, such as shock absorbers. The additional data considered may relate to at least one of a temperature of the component, the charge level of the traction battery, the aging state of the traction battery or the driving mode implemented at the time of execution of the method, for example a comfort, economic or sport mode.

[0071] The method then comprises a step E71 of limiting the at least one forecast deceleration value D_x by a first minimum threshold S1_min and a first maximum deceleration threshold S1_max as a function of the additional data relating to the limitations of the vehicle 1. Such a principle makes it possible, at any time, to set the limits of a range of forecast deceleration values ​​D_x capable of being applied by the vehicle 1 at a given time. In this way, if the value of the forecast deceleration D_x obtained at the end of the arbitration step E05 is included in such a limiting range, the method can continue. If the value of the forecast deceleration D_x obtained at the end of the arbitration step E05 is strictly lower than the first minimum deceleration threshold S1_min established, it is corrected so as to be equal to said first minimum threshold S1_min.Conversely, if the value of the forecast deceleration D_x obtained at the end of the arbitration step E05 is strictly greater than the first maximum deceleration threshold S1_max established, it is corrected so as to be equal to said first maximum threshold S1_max.

[0072] Additionally or alternatively, a similar principle applies mutatis mutandis for a first minimum threshold S1 p_min and a first maximum threshold S1 p_max of predicted optimal regenerative power instead of the predicted deceleration D_x, as illustrated in dotted lines in Figure 3.

[0073] For example, the predicted deceleration value D_x and / or the predicted optimal regenerative power P_x is limited when it is detected that the charge level of the electric traction battery is at its maximum, i.e. when the electrical energy generated by regenerative braking can no longer be stored.

[0074] According to a non-limiting exemplary embodiment, in order to take into account in real time the physical limitations of the components of the traction chain, the electric powertrain 11 can optionally provide the processing unit 7 with data in the form of a vector of electrical regeneration capacity as a function of the longitudinal speed of the vehicle 1, either defined according to points of fixed longitudinal speed or defined by a dynamic vector.

[0075] According to another alternative embodiment, such a principle can be applied to the first recommended deceleration D_r1 and to the second recommended deceleration D_r2 instead of the forecast deceleration D_x, that is to say prior to the arbitration step E05.

[0076] The processing unit 7 thus makes it possible to modulate the forecast deceleration strategy D_x and / or optimal regenerative power in a range of values ​​defined by the different components of the vehicle 1 and / or the driving mode applied by the vehicle 1.

[0077] Optionally, the method comprises a step E08 of acquiring additional data relating to the context external to the vehicle 1 relating to the geographical location of the vehicle 1, the weather conditions and / or the characteristics specific to the road traveled by the vehicle 1, for example its condition, its slope or its type, a radius of curvature of a bend or other. Such additional data can be measured in real time by the detection means 5, the driving assistance system 2, the horizon provider module 4 and / or the location means 5.

[0078] The method may then comprise a step E81 of adjusting the at least one recommended first deceleration value D_r1, the at least one recommended second deceleration value D_r2, the at least one predicted deceleration value D_x and / or predicted optimal regenerative power P_x to be applied as a function of said data. For example, when the road traveled has a significant downward slope, the predicted deceleration D_x and / or optimal regenerative power P_x is adjusted in order to be increased. Similarly, when the road traveled has a bend with a small radius of curvature, i.e. with a strong curvature, the predicted deceleration D_x and / or optimal regenerative power is adjusted in order to be increased.

[0079] The additional data thus provided makes it possible to define the external context with greater precision. Such an adjustment can advantageously be applied at different times in the process, in particular before or after the arbitration step E05.

[0080] Optionally, as illustrated in Figure 4, the method comprises a step E09 of acquiring data relating to a driving context, that is to say in particular relating to the urban, peri-urban or extra-urban location of a road traveled by the vehicle 1. Such data can be measured in real time by the detection means 5, the driving assistance system 2, the horizon provider module 4 and / or the location means 5.

[0081] The method may then comprise a step E91 of assigning a second predefined minimum threshold S2_min, S2p_min of the at least one forecast deceleration value D_x and / or forecast optimal regenerative power P_x to be applied depending on the driving context.

[0082] For example, when an urban or peri-urban driving context is detected, the second minimum threshold S2_min is set to a non-zero predicted deceleration value D_x and this independently of the detection of a target, primary and / or secondary, in front of the vehicle 1. Such a principle then makes it possible to ensure the implementation of regenerative braking as soon as the driver lifts his foot from the accelerator pedal, the urban or peri-urban driving context being particularly suited to the implementation of such braking. Conversely, for an extra-urban driving context, for example when the vehicle 1 is traveling on a highway, the second minimum threshold S2_min is set to a zero predicted deceleration value D_x so that no deceleration is applied, even when the driver lifts his foot from the accelerator pedal, in order to conserve energy.

[0083] In this way, if the value of the forecast deceleration D_x obtained at the end of the arbitration step E05 is strictly lower than the second minimum deceleration threshold S2_min established for the detected driving context, it is corrected so as to be greater than or equal to said second minimum threshold S2_min. Alternatively or additionally, the same applies to a second minimum threshold S2p_min applied to the forecast optimal regenerative power P_x.

[0084] According to another alternative embodiment, such a principle can be applied to the first recommended deceleration D_r1 and to the second recommended deceleration D_r2. Optionally again, as illustrated in FIG. 4, the method comprises at least one prior step E10 of providing information about at least one user preference relating to one or more energy recovery modes. Alternatively or additionally, the at least one preference relates to a preferred minimum value and / or a preferred maximum value of forecast deceleration D_x and / or of forecast optimal regenerative power. Such a preference is, for example, provided via the human-machine interface 10. Such a step notably comprises at least one sub-step of saving such a preference and / or a sub-step of modifying previously recorded data relating to said preference.

[0085] The method further comprises a step E11 of adjusting the forecast deceleration value D_x and / or the forecast optimal regenerative power P_x as a function of the at least one defined preference.

[0086] Finally, independently of the execution alternatives set out above, the method optionally comprises at least one step E12 of transmitting an information message, visual and / or audible, concerning the predicted deceleration value D_x, the predicted optimal regenerative power value P_x and / or the energy recovery mode, capable of implementing such regenerative power, to be applied automatically if it is detected that the driver lifts his foot off the accelerator pedal. Such a message can be transmitted, for example, via the human-machine interface 10 and advantageously makes it possible to inform the driver in order to allow him to understand and anticipate the envisaged regenerative braking.

[0087] As illustrated, the invention also extends to a method 200 for adaptively controlling regenerative braking of the vehicle 1. Such a method comprises, initially, the steps of the management method 100 as set out above. These steps are then followed by a step E20 of detecting an action of the driver lifting his foot, partially or completely, from the accelerator pedal, for example by means of a sensor specific to said pedal. Finally, when it is detected that the driver lifts his foot from the accelerator pedal, at least one regenerative braking step E21 is executed. The previously determined forecast optimal regenerative power P_x and / or the previously determined energy recovery mode, capable of implementing such regenerative power, is then automatically applied, without requiring intervention from the driver at the at least one regenerative braking step E21.The processing unit 7 transmits instructions to the control module 8 which adjusts the operation of the electric powertrain 11 accordingly in order to implement suitable regenerative braking and energy recovery.

[0088] The invention thus proposes a method for managing regenerative braking of an electric or hybrid motor vehicle using a driving assistance system and an electronic horizon supplier module in order to provide optimized automation of the implementation of regenerative braking at power levels, in other words levels of electrical energy recovery, adapted to the contexts outside and inside the vehicle. The proposed solution is, moreover, implemented at low cost and easily implantable on existing vehicles.

[0089] The present invention cannot, however, be limited to the means and configurations described and illustrated here and it also extends to any equivalent means or configuration and to any technically operative combination of such means insofar as they ultimately fulfill the functionalities described and illustrated in the present document.

Claims

CLAIMS 1. Method for managing (100) regenerative braking of a vehicle (1) with electric or hybrid motorization equipped with a driving assistance system (2) and an electronic horizon supplier module (4), the method comprising, in a driving situation: - a step of acquiring (E01) data relating to the vehicle (1) and to the environment outside the vehicle (1) via the driving assistance system (2); - a step of acquiring (E02) data relating to the environment outside the vehicle (1) via the electronic horizon supplier module (4); - a calculation step (E03), by a processing unit (7), of at least one value of a first recommended deceleration (D_r1) on the basis of data from the driving assistance system (2), and a calculation step (E04), by the processing unit (7), of at least one value of a second recommended deceleration (D_r2) on the basis of data from the electronic horizon supplier module (4); - an arbitration step (E05), according to at least one predefined arbitration law based on at least one criterion (Kx), selecting at least one forecast deceleration value (D_x) most suitable based on said criterion (Kx) between the at least one recommended first deceleration value (D_r1) and the at least one recommended second deceleration value (D_r2); - a step of determining (E06), as a function of the predicted deceleration value (D_x), a predicted optimal regenerative power (P_x) and / or an energy recovery mode, capable of implementing such optimal regenerative power (P_x), to be applied automatically if it is detected that the driver lifts his foot from an accelerator pedal.

2. Management method (100) according to the preceding claim, in which: - the data from the driving assistance system (2) are at least relative to a distance and a relative speed of at least one primary target located in the road infrastructure; - the data from the electronic horizon supplier module (4) and are at least relative to a distance, a relative speed and a recommended speed of circulation of the vehicle (1) at the level of at least one secondary target considered located in the road infrastructure; and - the at least one recommended first deceleration value (D_r1) is defined as a function of the distance and the relative speed of the at least one primary target and the at least one recommended second deceleration (D_r2) is defined as a function of the distance, the relative speed and the recommended speed of movement of the at least one secondary target.

3. Management method (100) according to one of the preceding claims, in which the at least one arbitration criterion (Kx) is selected from: - a degree of confidence (Dcf_x) of the acquired data, specific to the data from the driving assistance system (2) and to the data from the electronic horizon supplier module (4); - a probability of relevance (Pb_x) of the deceleration considered as a function of an estimated position of the vehicle (1) in the road infrastructure; - a degree of energy optimization (Op_x) of the deceleration considered; and / or - a degree of importance (Lv_x) of the at least one recommended first deceleration value (D_r1) and of the at least one recommended second deceleration value (D_r2).

4. Management method (100) according to one of the preceding claims, further comprising: - a step of acquiring (E01) additional data relating to limitations of the vehicle (1) specific to a predefined driving mode and / or to at least one member equipping the vehicle (1) selected from an electric powertrain (11), an electric traction battery, an electronic component, a heat exchanger, a chassis and / or shock absorbers; - a step of limiting (E71) the at least one forecast deceleration value (D_x) and / or forecast optimal regenerative power (P_x) by a first minimum threshold and first maximum threshold which are specific to them defined according to the additional data relating to the limitations of the vehicle (1).

5. Management method (100) according to one of the preceding claims, further comprising: - a step of acquiring (E08) additional data relating to the context external to the vehicle (1) concerning a geographical location of the vehicle (1), meteorological conditions and / or characteristics specific to a road traveled by the vehicle (1); - a step of adjusting (E81) the at least one recommended first deceleration value (D_r1), the at least one recommended second deceleration value (D_r2), the at least one forecast deceleration value (D_x) and / or the forecast optimal regenerative power (P_x) to be applied as a function of said additional data relating to the context external to the vehicle (1).

6. Management method (100) according to one of the preceding claims, further comprising: - a step of acquiring (E09) data relating to a driving context, in particular relating to the urban, peri-urban or extra-urban location of a road traveled by the vehicle (1); - a step of assigning (E91) a second predefined minimum threshold of at least one forecast deceleration value (D_x) and / or forecast optimal regenerative power (P_x) to be applied depending on the driving context.

7. Management method (100) according to one of the preceding claims, further comprising at least one prior step (E10) of providing information on at least one user preference relating to one or more energy recovery modes, to a preferred minimum and / or preferred maximum value of forecast deceleration (D_x) and / or of forecast optimal regenerative power (P_x), the method further comprising a step (E11) of adjusting the value of forecast deceleration (D_x) and / or of forecast optimal regenerative power as a function of the at least one preference.

8. Management method (100) according to one of the preceding claims, further comprising a step of transmitting (E12) an information message, visual and / or audible, concerning the predicted deceleration value (D_x), the at least one predicted optimal regenerative power value and / or the energy recovery mode, capable of implementing such regenerative power, to be applied automatically if it is detected that the driver lifts his foot off the accelerator pedal.

9. Adaptive control method (200) of regenerative braking of a vehicle (1) comprising, firstly, the steps of the management method (100) according to one of the preceding claims then a step of detecting (E20) an action of lifting the foot of a driver, partially or completely, from the accelerator pedal and, when it is detected that the driver lifts the foot from the accelerator pedal, at least one regenerative braking step (E21) to which the determined forecast optimal regenerative power (P_x) and / or the determined energy recovery mode is automatically applied.

10. Management system (6) of regenerative braking for a vehicle (1) with electric or hybrid motorization equipped with a driving assistance system (2) and an electronic horizon supplier module (4), the system comprising hardware and / or software elements implementing the management method according to one of claims 1 to 8 and / or the adaptive braking control method (200) according to claim 9, the hardware elements comprising at least one data processing unit (7), capable of receiving data from the driving assistance system (2) and the electronic horizon supplier module (4) and a control module (8) capable of controlling an electric powertrain (11) of the vehicle (1).

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