METHOD AND SYSTEM FOR CONTROLLING CONGESTION ON THE INTERIOR SURFACE OF AT LEAST ONE GLAZING UNIT OF A VEHICLE

Description

Previous technique

[0001] The present invention falls within the general field of managing the condition of one or more windows of vehicles, such as cars, trucks, buses, trains, and the like. More particularly, it relates to a method for regulating the presence of condensation on at least one window of a vehicle. It also relates to a system configured to implement said method. The invention finds a particularly advantageous, though not limiting, application in the case of a vehicle equipped with at least one electric motor for propulsion, such as an electric or hybrid vehicle.

[0002] Managing the risk of condensation, and therefore fogging, on the inside surface of a vehicle's windshield is of particular importance for the safety of its occupants. Indeed, fog on the windshield directly impacts the driver's visual comfort, as they need the widest and clearest possible field of vision to avoid any visual discomfort or fatigue that could compromise driving safety.

[0003] In practice, managing this risk of condensation can prove complex as it is likely to conflict with managing thermal comfort within the passenger compartment, the latter being traditionally defined as a combination between, in particular, the temperature felt by the user(s) of the vehicle, it being expected that this reaches a given value (example: a temperature determined by the driver) within said passenger compartment, and the relative or absolute humidity within said passenger compartment.

[0004] Indeed, to achieve a given thermal comfort, a climate control system, also called an "HVAC" system (acronym for the Anglo-Saxon expression "Heating, Ventilation, and Air Conditioning"), is traditionally used to heat, cool and ventilate the air circulating in the living space.

[0005] However, in many modern vehicles, this HVAC system is also used to manage the risk of windshield fogging, to the point that it even takes priority over thermal comfort. This can lead to problematic situations, such as in winter when the HVAC system cannot be used to manage fogging without introducing cold air and / or activating a cooling circuit, resulting in reduced thermal comfort and potentially an increase in the vehicle's electrical energy consumption.

[0006] To overcome this difficulty, it has been proposed to equip the windshield with dedicated heating means (example: resistive elements such as wires or metal strips, heating interlayer of laminated glazing, etc.).

[0007] Such heating methods allow for efficient defogging of the windshield, as it is directly heated with minimal heat loss to its surroundings, thus increasing the scope for optimizing the thermal management of the passenger compartment.

[0008] However, these heating systems are generally controlled by an on / off switch, operated by a vehicle user (e.g., the driver). This use of the heating system cannot therefore be considered satisfactory since it results from a deliberate action by the user, that is, an action based on a subjective criterion. Thus, it can happen that the heating system is left on simply by forgetting it, which undoubtedly has a negative impact on energy consumption.

[0009] One way to try and mitigate these drawbacks is to implement automatic control of windshield fog management. Such automatic control is often achieved using a closed-loop control system that utilizes data from temperature and / or humidity sensors. Based on this data, the heating system is controlled to minimize the risk of condensation on the windshield.

[0010] Current solutions offering closed-loop automatic control rely on traditional PID (proportional, integral, derivative) control techniques and ultimately prove unsatisfactory because they are poorly suited to reliably assessing the risk of condensation on the vehicle's windshield and to precisely regulating it. A known type of control method is disclosed by FR 3 048 214 A1.

[0011] It is important to note that all the elements set out above ultimately apply to all types of vehicle glazing, therefore in particular to glazing other than a windshield (example: rear window, side window, etc.). Description of the invention

[0012] The present invention aims to remedy all or part of the disadvantages of the prior art, in particular those set out above, by proposing a solution which allows to automatically regulate (control) the presence of fog on one or more windows of a vehicle, in a more precise and efficient manner than the solutions of the state of the art.

[0013] To this end, and according to a first aspect, the invention relates to a method for regulating the presence of condensation on the inner surface of at least one window of a vehicle, said method comprising a control loop including, during a typical iteration, the following steps: obtaining at least one signal, called a "control signal", associated with a quantity and comprising past values ​​and a current value of said quantity, a risk of condensation of moisture on the inner surface of said at least one glazing being able to be determined from said at least one quantity, determination of a predictive control of at least one actuator of the vehicle so as to maintain or lower said risk below a threshold value, said control being determined by means of a predictive model of said risk using said at least one control signal, transmission of the predictive control to said at least one actuator.

[0014] By "predictive control" we mean here a control aimed at activating / deactivating the heating means and / or activating / deactivating at least one component belonging to the air conditioning system in order to regulate the presence of condensation on said at least one window.

[0015] It should be noted that the expression "regulating the presence of condensation on said at least one pane of glass" covers several cases, namely: cases where no fog is already present on said at least one pane of glass, the regulation in question then aims to prevent the appearance of fog, cases where fog is already present on said at least one pane of glass, the regulation in question then aims to eliminate it.

[0016] Furthermore, and more specifically, the term "predictive" refers to a type of anticipatory compensation / correction control. Such predictive control falls under an advanced control technique in automatic control (the acronyms "MPC" or "MBPC" are commonly used in English to describe this technique, and correspond to the expressions "Model (Based) Predictive Control").

[0017] In its general principle, an MPC technique consists of using at least one model fed by signals. This at least one model allows the description of the evolution of one or more quantities, including quantities associated with the signals provided as input to said at least one model, in order to anticipate the future evolution of the quantities in question, and thus predict which commands are most appropriate to transmit based on this evolution.

[0018] The implementation of such an MPC technique proves particularly well-suited to the application envisaged here, namely the regulation of condensation on at least one window of the vehicle. Indeed, the MPC technique makes it possible to create an anticipatory effect with respect to the control signals, so as to generate control commands adapted to the evolution (over a defined future time horizon) of the quantities associated with the control signals.

[0019] It also helps to avoid excessive variations in the manipulated quantities (i.e. predictive control is smoother), which contributes to better use of actuators (heating means, air conditioning system).

[0020] Ultimately, the implementation of the regulation process according to the invention advantageously allows for fine regulation of the presence of condensation on said at least one window, in order to minimize the risk of condensation appearing, or, if condensation is already present, to prioritize its rapid elimination for driving safety reasons.

[0021] In particular modes of implementation, the control process may also include one or more of the following characteristics, taken individually or in all technically possible combinations.

[0022] In specific implementation modes, a plurality of control signals are obtained, including: a signal whose associated quantity is a temperature of said at least one glazing, and a signal whose associated quantity is an absolute humidity within the passenger compartment of the vehicle.

[0023] In particular modes of implementation, only one control signal is obtained, the quantity associated with said control signal being a relative humidity inside the vehicle in the vicinity of said at least one window.

[0024] By "in the vicinity of said at least one glazing", reference is made here to a gap in the windshield of the order of a few millimeters, for example less than or equal to 10 mm.

[0025] In specific implementation methods, the determination of said condensation risk, using the predictive model and for a given time step within a future time horizon, involves: obtaining a temperature of said at least one glazing as well as a dew point of the passenger compartment, a calculation of a difference between said temperature of said at least one glazing and said dew point of the passenger compartment, a comparison of said difference with at least one given value.

[0026] In specific implementation methods, the determination of said condensation risk, using the predictive model and for a given time step within a future time horizon, involves: obtaining a relative humidity inside the vehicle in the vicinity of said at least one window, a comparison of said relative humidity with at least one given value.

[0027] In particular modes of implementation, said at least one actuator includes means for heating said at least one glazing and / or at least one actuator of an air conditioning system of the vehicle passenger compartment from among: a fan, a compressor, a heating element, an air recirculation flap.

[0028] In specific implementation modes, the predictive model is configured to model: the evolution of temperature and humidity conditions at the level of the inner surface of said at least one glazing, and the evolution of temperature and humidity conditions within the passenger compartment of the vehicle due to the operation of an air conditioning system in said passenger compartment.

[0029] In specific implementation modes, the control process also includes a step of obtaining at least one signal, called a "disturbance signal", associated with a quantity and comprising past values ​​and a current value of said quantity, said at least one disturbance signal being at least one of the following: a signal whose associated quantity is the number of people in the vehicle, a signal whose associated quantity is the level of carbon dioxide present in the passenger compartment, a signal whose associated quantity is the speed of the vehicle, a signal whose associated quantity is the temperature outside the vehicle, a signal whose associated quantity is the relative or absolute humidity outside the vehicle, a signal whose associated quantity is a weather forecast data, a signal whose associated quantity is the solar power absorbed by said at least one window and / or by the passenger compartment of the vehicle.

[0030] The control process further includes a step of determining, from said at least one disturbance signal, at least one predicted value of the quantity associated with said at least one disturbance signal, the predictive model of said condensation risk also using said at least one predicted value when determining the predictive control of said at least one actuator.

[0031] Such provisions advantageously allow for the consideration of measurable disturbances that could affect predictive control. This results in a very high level of responsiveness, in terms of regulation, to conditions external to the vehicle, but also the possibility of refining (i.e., enriching) the predictive model, and therefore, a fortiori, of further increasing the accuracy of the regulation.

[0032] In certain implementation modes, the predictive control determination step involves optimizing a cost function containing at least one term from among: a difference between the risk of condensation predicted by the predictive model and said threshold value, a rate of change of the risk of condensation.

[0033] In specific implementation methods, the cost function also includes a weighting of at least one term representing a vehicle usage criterion, said at least one usage criterion comprising at least one of the following: a criterion relating to the absence of frost on said at least one window, a criterion relating to thermal comfort within the passenger compartment, a criterion relating to the consumption of electrical energy on board the vehicle and used for the operation of said at least one actuator, a criterion relating to a level of carbon dioxide within the passenger compartment, a criterion relating to a level of noise within the passenger compartment.

[0034] According to a second aspect, the invention relates to a computer program comprising instructions for implementing a control method according to the invention when said program is executed by a computer.

[0035] This program can use any programming language, and be in the form of source code, object code, or code somewhere between source code and object code, such as in a partially compiled form, or in any other desirable form.

[0036] According to a third aspect, the invention relates to a computer-readable information or recording medium on which a computer program according to the invention is recorded.

[0037] The information or recording medium can be any entity or device capable of storing the program. For example, the medium can include a storage means, such as a ROM, for example a CD-ROM or a microelectronic circuit ROM, or a recording means, for example a USB flash drive or a hard drive.

[0038] On the other hand, the information or recording medium can be a transmissible medium such as an electrical or optical signal, which can be transmitted via an electrical or optical cable, by radio, or by other means. The program according to the invention can, in particular, be uploaded to a network such as the Internet.

[0039] Alternatively, the information or recording medium may be an integrated circuit in which the program is incorporated, the circuit being adapted to execute or to be used in the execution of the process in question.

[0040] According to a fourth aspect, the invention relates to a system for regulating the presence of condensation on at least one window of a vehicle. This system comprises means configured to implement a regulation method according to the invention.

[0041] According to a fifth aspect, the invention relates to a vehicle comprising a control system according to the invention.

[0042] In particular embodiments, said vehicle includes at least one electric motor for propulsion. Brief description of the drawings

[0043] Other features and advantages of the present invention will become apparent from the description below, with reference to the accompanying drawings, which illustrate an example of an embodiment without being limiting in any way. In the figures: [ Fig. 1 ] there figure 1 schematically represents, in its environment, a particular embodiment of a control system according to the invention, said control system being configured to regulate the presence of condensation on the windshield of a vehicle; Fig. 2 ] there figure 2 schematically represents an example of the hardware architecture of the regulation system of the figure 1 ; Fig. 3 ] there figure 3 schematically represents a particular operating mode of a control loop implemented by the control system of the figure 1 to regulate the presence of fog; [ Fig. 4 ] there figure 4represents, in the form of a flowchart, a particular method of implementing a control process integrating the control loop of the figure 3 ; Fig. 5 ] there figure 5 schematically represents a particular embodiment of a control module belonging to the control system of the figure 1 and used for the operation of the control loop of the figure 3 ; Fig. 6 ] there figure 6 another particular mode of operation of the control loop; [ Fig. 7 ] there figure 7 represents, in the form of a flowchart, a particular method of implementing the regulation process integrating the control loop of the figure 6 . Description of implementation methods

[0044] The present invention belongs to the field of managing the condition of one or more windows of a vehicle, and more specifically aims at regulating (i.e. controlling) the risk of condensation of moisture (i.e. the risk of fogging) on ​​one or more windows of said vehicle.

[0045] The following description focuses more specifically on an electric car. By "electric car," we mean a car that has at least one electric motor and that, to move (i.e., to operate said at least one electric motor), uses only the electrical energy stored in one or more batteries that equip it.

[0046] For the sake of simplicity in the description, it is also considered, in a non-limiting manner, that the regulation mentioned above applies only to the windscreen of said electric car.

[0047] It is important to note, however, that the present invention is not limited to the case of an electric car, and can equally concern a hybrid car or even a car equipped solely with a combustion engine.

[0048] More generally, considering a car-type vehicle does not constitute a limitation of the invention, the latter remaining applicable to any type of vehicle capable of moving by means of on-board energy (electrical energy and / or fuel), such as a truck, a bus, a train, etc. and comprising at least one window.

[0049] Furthermore, describing the invention here solely for the windshield of the electric car represents only one implementation variant. Therefore, no limitations are attached to these aspects, making it possible to consider other types of glazing, such as a side window or a rear window of a car. Nor does anything preclude considering fog control for multiple types of glazing.

[0050] Ultimately, regardless of the type of vehicle considered and regardless of the type and number of windows considered, a person skilled in the art can easily adapt the following description.

[0051] There figure 1 schematically represents, in its environment, a particular mode of implementation of a SYS_C system for regulating the presence of fog on the windshield 110 of the electric car 100.

[0052] In the implementation of the figure 1The SYS_C control system is connected, via means of communication described in more detail later, to an HVAC (Heating, Ventilation, and Air Conditioning) system equipping the electric car 100.

[0053] Conventionally, the said HVAC system is configured to heat, cool and ventilate the passenger compartment of the vehicle equipping the electric car 100. The design and implementation details of such an HVAC system being well known to those skilled in the art, they are not repeated here.

[0054] Furthermore, in the embodiment described here, in order to control the defogging of the windshield 110, said SYS_C system is also connected to MOD_HEAT heating means equipping the windshield 110.

[0055] The heating means MOD_HEAT include, for example, a network of electrical wires incorporated into the windshield 110 (in the case of laminated glass comprising a layer in which said electrical wires are embedded). Generally speaking, all known heating means can be considered; this aspect is not limiting to the invention.

[0056] The regulation of fogging on the windshield 110 of the electric car 100 is therefore achieved, in the embodiment described herein, by means of the aforementioned heating means MOD_HEAT and the aforementioned HVAC air conditioning system. It is important to note, however, that such provisions are not limiting to the invention; for example, only the aforementioned heating means MOD_HEAT (or only the aforementioned HVAC air conditioning system) may be used to regulate fogging on the windshield 110.

[0057] Thus, the aforementioned MOD_HEAT heating means act as actuators with respect to the envisaged regulation. The same applies to the component(s) of the HVAC air conditioning system that may be used in the implementation of this regulation, such as: a fan and / or a compressor and / or a heating element (such as a heating element in a heated seat or a radiant panel in the car 100) and / or an air recirculation flap, etc.

[0058] According to the invention, the SYS_C system is configured to perform processes to regulate (i.e., control) the presence of condensation on the inner surface of the windshield 110 of the electric car 100 (i.e., the surface in direct contact with the interior environment of the car 100, i.e., the passenger compartment of the car 100). In other words, said SYS_C system is configured to generate control commands for the MOD_HEAT heating means and the HVAC air conditioning system, by implementing a control method according to the invention, described in detail below, the steps of which are included in a (closed) control loop.

[0059] The implementation of this regulation process, via the said SYS_C regulation system, advantageously allows for fine control of the risk of condensation, and therefore of fogging, on the windscreen 110 of the electric car 100, so as to guarantee excellent driving comfort, particularly with regard to safety requirements related to visibility through the said windscreen 110.

[0060] There figure 2 schematically represents an example of the hardware architecture of the SYS_C regulation system of the figure 1 .

[0061] As illustrated by the figure 2 The SYS_C control system according to the invention has the hardware architecture of a computer. Thus, said SYS_C control system includes, in particular, a processor 1_C, a random access memory 2_C, a read-only memory 3_C, and a non-volatile memory 4_C. It also has communication means 5_C.

[0062] The read-only memory 3_C of the SYS_C control system constitutes a storage medium according to the invention, readable by the processor 1_C, on which is stored a computer program PROG_C according to the invention, comprising instructions for executing steps of the control process according to the invention. The PROG_C program defines functional modules of the SYS_C control system, which rely on or control the hardware elements 1_C to 5_C mentioned above, and which include, in particular: a MOD_OBT acquisition module configured to obtain at least one signal, called a "control signal", associated with a quantity and having past values ​​and a current value of said quantity, a risk RI of condensation of moisture on the inner surface of the windscreen 110 that can be determined from said at least one quantity, a MOD_REG control module configured to determine a predictive control C_PRED of the actuators of said heating means MOD_HEAT and said HVAC air conditioning system, so as to maintain or lower said risk RI below a threshold value VS_RI, said control being determined by means of a predictive model MODEL of said risk RI, a MOD_TX transmission module configured to transmit the predictive control C_PRED to said actuators.

[0063] As is known, condensation on the windshield (110) can occur when any of the following conditions are met: relative humidity reaches 100% in the vicinity of windshield 110; air temperature in the vicinity of windshield 110 reaches the dew point; partial pressure of water in the vicinity of windshield 110 reaches the saturation vapor pressure.

[0064] These three statements are equivalent in that they each reflect the fact that if the mass of water present in the passenger compartment of the car 100 in the vicinity of the windshield 110 is greater than what the air can hold in vapor form in that vicinity, then condensation may appear on the inner surface of the windshield 110.

[0065] It follows from these considerations, and more particularly from the equivalence between the said assertions, that it is possible to define the risk of condensation RI as a function of different sets of physical quantities (a set which may refer to one or more quantities), which then conditions different embodiments of the invention with regard to the control signals intended to be obtained via said MOD_OBT acquisition module.

[0066] Control signals are associated with controllable quantities, i.e., quantities that can be acted upon. For example, a signal associated with a quantity related to the outside temperature of the car does not constitute a control signal.

[0067] Therefore, in the embodiment described here, two control signals are considered to be obtained (it being understood that each control signal represents a single quantity), which are: a signal S_T_WS whose associated quantity is a temperature T_WS of the windshield 110. It should be noted that by "temperature T_WS of the windshield 110", it refers, for this embodiment, to a temperature at the level of the inner surface of the windshield 110, a signal S_AH_CAB whose associated quantity is an absolute humidity AH_CAB inside the passenger compartment of the car 100. As is known per se, the absolute humidity AH_CAB corresponds to the proportion by weight of water vapor present in the air contained in said vicinity of the windshield 110.

[0068] From the said two control signals S_T_WS, S_AH_CAB, and on the basis of calculations known to the person skilled in the art, it is possible to determine (i.e. to estimate), in the first instance, a dew point DP_CAB of the passenger compartment of the car 100 (i.e. the temperature below which the water vapor contained in the air of the passenger compartment condenses on the surfaces, by saturation effect).

[0069] Therefore, and as a second step, the risk RI of condensation on the inner surface of the windshield 110 can be assessed by considering a risk indicator I1_RI equal to the difference between the values ​​T_WS and DP_CAB (i.e., I1_RI = T_WS - DP_CAB). More specifically, we consider, for example, that: If I1_RI is less than a first value T_INF, the RI risk is equal to 100%; if I1_RI is greater than a second value T_SUP (T_SUP being greater than T_INF), the RI risk is zero; if I1_RI is between T_INF and T_SUP (i.e., T_INF < I1_RI < T_SUP), the RI risk is expressed as follows: RI = A × I 1 _ RI − T _ INF T _ SUP − T _ INF n expression in which A and n are two given coefficients.

[0070] It should be noted that there are no limitations attached to the choice of parameters T_INF, T_SUP, A and n. In practice, these parameters are traditionally fixed during the manufacture of the car 100.

[0071] Furthermore, considering such a value of RI, when said indicator I1_RI is between T_INF and T_SUP, constitutes only one variant of the invention's implementation. Any other variant known to a person skilled in the art may be used here when it is considered that the RI risk is determined from said risk indicator I1_RI.

[0072] More generally, it is important to note that taking into account the said two control signals S_T_WS, S_AH_CAB to determine the RI risk, and therefore ultimately to implement the regulation, is not limiting of the invention.

[0073] Indeed, nothing precludes, for example, considering other embodiments in which a single control signal is obtained by the MOD_OBT acquisition module, namely, for example, a signal S_RH_CAB whose associated quantity is a relative humidity RH_CAB inside the car 100 in the vicinity of the windshield 110 (typically at a distance from the windshield 110 less than or equal to 10 mm). From said signal S_RH_CAB, the risk RI of condensation on the inner surface of the windshield 110 can be assessed by considering a risk indicator I2_RI equal to said quantity RH_CAB. More specifically, for example, it is considered that: If I2_RI is greater than a first value RH_SUP, the RI risk is equal to 100%; if I2_RI is less than a second value RH_INF (RH_SUP being greater than RH_INF), the RI risk is zero; if I2_RI is between RH_INF and RH_SUP (i.e., RH_INF < I2_RI < RH_SUP), the RI risk is expressed as follows: RI = A ′ × I 2 _ RI − RH _ INF RH _ SUP − RH _ INF n ′ expression in which A' and n' are two given coefficients.

[0074] Following considerations similar to those mentioned above, no limitation is attached to the choice of the parameters RH_INF, RH_SUP, A' and n', the latter being traditionally fixed during the manufacture of the car 100. Moreover, the fact of considering such a value of RI, when said indicator I2_RI is between RH_INF and RH_SUP, constitutes only one variant of implementation of the invention, any other variant known to the person skilled in the art being able to be used here when it is considered that the risk RI is determined from said risk indicator I2_RI.

[0075] Regarding the threshold value VS_RI, this can be either constant or variable over time, with no limitations attached to this aspect. Generally, and as considered in the embodiment described here, it is a fixed constant value (for example, during the construction of car 100), stored in the non-volatile memory 4_C, and acting as a threshold beyond which condensation is considered likely to appear on the windshield 110.

[0076] In other words, it is possible to consider this threshold value VS_RI as an operating constraint of the SYS_C control system. For the remainder of the description, we adopt the notation according to which the operating constraint(s) of the SYS_C control system form(s) a set of constraints denoted “E_CONS”.

[0077] For the purposes of this invention, the term "predictive control C_PRED" refers to an anticipatory compensation / correction type control aimed at activating / deactivating the heating means MOD_HEAT and / or activating / deactivating at least one component belonging to the HVAC air conditioning system in order to regulate the presence of fog on the windshield 110. Such a predictive control falls under an advanced control technique of automatic control (the acronyms "MPC" or "MBPC" are commonly used in English to describe this technique, and correspond to the expressions "Model (Based) Predictive Control").

[0078] The general principle of this MPC technique consists of using at least one model fed by signals. This at least one model allows the evolution of one or more quantities within the passenger compartment of the car 100 to be described, including in particular the quantities associated with the signals supplied to it as input, in order to anticipate the future evolution of the quantities in question, and thus predict which commands are most appropriate to transmit to the actuators according to this evolution.

[0079] In this regard, and as already mentioned above, the model considered for determining the predictive control C_PRED is the aforementioned predictive model MODEL, which notably uses the control signals S_T_WS and S_AH_CAB. More specifically, in the embodiment described here, the predictive model MODEL is considered to comprise: a first sub-model SS_MODEL_CAB configured to model the evolution of temperature and humidity conditions (therefore in particular to model the evolution of the quantities T_WS and AH_CAB) at the level of the inner surface of the windshield 110.

[0080] The aforementioned first sub-model SS_MODEL_CAB is therefore a hygrothermal model of the area located near the windshield 110 within the passenger compartment, A second sub-model, SS_MODEL_HVAC, is configured to model the evolution of temperature and humidity conditions within the vehicle's passenger compartment due to the operation of an HVAC air conditioning system. To this end, this sub-model, SS_MODEL_HVAC, models and simulates the operation of the HVAC system components.

[0081] Any model (i.e., any set of equations, typically differential equations) capable of modeling the evolution of temperature and humidity conditions on the inner surface of the windshield 110 (or, respectively, capable of modeling the evolution of temperature and humidity conditions inside the vehicle's passenger compartment due to the operation of an HVAC air conditioning system), and known to those skilled in the art, may be used here. In other words, the choice of a particular model, for both the first sub-model SS_MODEL_CAB and the second sub-model SS_MODEL_HVAC, constitutes only one implementation variant of the invention.

[0082] Furthermore, although it is considered here that the two sub-models SS_MODEL_CAB and SS_MODEL_HVAC are integrated into the predictive model MODEL, it is important to note that the presence of said second sub-model SS_MODEL_HVAC is, within the meaning of the invention, optional. Thus, nothing precludes considering other embodiments in which only the first sub-model SS_MODEL_CAB is integrated into said predictive model MODEL (said first sub-model SS_MODEL_CAB is in fact the one responsible for modeling the evolution of the quantities associated with the control signals S_T_WS, S_AH, CAB).

[0083] In addition to the aspects related to the use of a predictive model, the implementation of an MPC technique also conventionally involves the optimization of a cost function F. This cost function F aims primarily, within the framework of the present invention, to allow the regulation of the presence of fog on the windshield 110.

[0084] In practice, the cost function F is constructed in such a way as to at least allow the evaluation of the impact of predictions of quantities associated with the control signals S_T_WS, S_AH_CAB on the variation of the condensation risk RI. To this end, the cost function F may include at least one term from among: a difference between the risk of condensation RI and said threshold value VS_RI, a rate of change of the risk of condensation RI (by "rate of change" refers to temporal change).

[0085] In general, the theoretical foundations of the MPC technique are well known to those skilled in the art and are not repeated here. Furthermore, the manner in which the predictive control C_PRED is determined by the MOD_REG control module is detailed later through implementation methods of the control process according to the invention.

[0086] It can, however, already be noted that, in the embodiment described here, the predictive control C_PRED includes a plurality of components dedicated to the HVAC air conditioning system, namely: a C_PRED_W component for controlling the speed of a fan (i.e., a fan blowing air inside the passenger compartment of the electric car 100), a C_PRED_VC component for controlling the speed of a compressor (i.e., the compressor integrated, in a conventional manner, into the HVAC air conditioning system), a C_PRED_PT component for controlling the power of a heating element (such as a heating element equipping a heated seat or a radiant panel of the car 100), a C_PRED_PV component for controlling the angular position of an air recirculation flap.

[0087] In addition to the aforementioned components dedicated to the HVAC air conditioning system, the said C_PRED control includes, in this embodiment, a C_PRED_HEAT component for controlling the MOD_HEAT heating means.

[0088] Of course, considering the aforementioned plurality of components C_PRED_VV, C_PRED_VC, C_PRED_PT, and C_PRED_PV for the HVAC system is only one implementation variant of the invention. Therefore, nothing precludes considering only some of these components. Nor does anything preclude, as a complement or alternative, considering one or more other components associated with the HVAC system.

[0089] Furthermore, it is possible to consider that at least one component dedicated to the HVAC system or the MOD_HEAT heating means is a null component. Put another way, the invention covers modes in which only the MOD_HEAT heating means (or, respectively, only one or more components of the HVAC system) are activated by the predictive control C_PRED.

[0090] The 5_C communication means enable the SYS_C control system to transmit the C_PRED command to the MOD_HEAT heating means as well as to the HVAC system (consequently, the MOD_HEAT heating means and the HVAC system are equipped with communication means configured to receive the C_PRED control component(s) dedicated to them).

[0091] The 5_C communication means also allow the SYS_C regulation system to receive the S_T_WS, S_AH_CAB control signals.

[0092] Consequently, in the embodiment described herein, the aforementioned communication means 5_C incorporate the MOD_OBT acquisition module as well as the MOD_TX transmission module. Furthermore, the MOD_TX transmission module is also considered to be integrated into the MOD_REG control module, it being understood that nothing precludes the possibility of it being external to said MOD_REG control module. Nor does anything preclude embodiments in which the MOD_OBT acquisition module is also integrated into the MOD_REG control module.

[0093] To perform these data exchanges, the 5_C communication system includes, for example, a computer data bus capable of transmitting the C_PRED command and receiving control signals. As another example, the 5_C communication system includes a wired or wireless communication interface capable of implementing any suitable protocol known to those skilled in the art (Ethernet, Wi-Fi, Bluetooth, 3G, 4G, 5G, etc.). Generally speaking, there are no limitations on how the C_PRED command is transmitted or how the control signals are obtained.

[0094] In the embodiment described here, the control signals S_T_WS, S_AH_CAB are obtained from measurements, these measurements being acquired by acquisition means (not shown in the figures) equipping the electric car 100. The measurements carried out to obtain the control signals S_T_WS, S_AH_CAB relate to the quantities T_WS, AH_CAB.

[0095] The acquisition means configured to acquire these measurements comprise, in a known manner, an acquisition chain including a sensor dedicated to measuring each of the quantities T_WS, AH_CAB. Each of these sensors forms a sensitive element configured to provide an electrical signal based on variations in the physical quantity to which it is associated. This acquisition chain also includes, for example, an acquisition card configured to condition the electrical signal provided by a sensor, for example, by amplification and / or filtering. The acquisition means may also include, at the output of the acquisition chain, an analog-to-digital converter configured to digitize a conditioned electrical signal.

[0096] In general, the configuration of such acquisition methods is well known to those skilled in the art and is therefore not detailed further here. In particular, those skilled in the art know, firstly, how to select the appropriate sensors for measuring the quantities T_WS and AH_CAB, and secondly, how to position them.

[0097] Furthermore, although it is considered here that the acquisition means are external to the SYS_C regulation system (i.e. the MOD_OBT acquisition module does not integrate the acquisition means), nothing excludes considering, according to another variant, the opposite arrangements (i.e. the MOD_OBT acquisition module integrates the acquisition means).

[0098] It is important to note that the invention is not limited to cases where the measurements performed by the acquisition means relate directly to the quantities associated with the control signals. In particular, it is possible to consider that at least some of the measurements may concern other quantities from which the control signals can be obtained, in which case the latter may also be described as synthesis signals.

[0099] As a non-limiting example, temperature measurements can be acquired at the outer surface of the windshield 110 (i.e., the surface in direct contact with the external environment of the car 100). From these measurements, and using a model (of a type known per se) of the windshield 110 modeling the effects of thermal conduction, the control signal S_T_WS can be obtained.

[0100] It is also important to note that acquiring measurements of the quantities T_WS and AH_CAB allows access, through calculations known to those skilled in the art, to corresponding values ​​of the quantity RH_CAB, and therefore ultimately to an estimate of the risk indicator I2_RI. The reverse is also true (i.e., estimating I1_RI from measurements of the quantity RH_CAB). These considerations further illustrate that the measurements performed by the acquisition methods can relate directly or indirectly to the quantities associated with the control signals obtained by the MOD_OBT acquisition module.

[0101] We will now describe a particular operating mode of the process control loop, as implemented, in particular, by means of the SYS_C control system of the figure 2 The description of this particular mode of operation is carried out with reference to the block diagram of the figure 3which represents said control loop (i.e. the signals exchanged between the different functional modules of the SYS_C regulation system).

[0102] In parallel with the description of the operation of the control loop, we will also describe, with reference to the figure 4 , a particular method of implementing the regulation process.

[0103] As a reminder, in the method described here, the risk of condensation RI is defined from the risk indicator I1_RI mentioned above.

[0104] For the description of the figures 3 And 4 , we consider a current iteration of the control loop. This current iteration is indexed by means of the integer index "i" (consequently, the iteration that immediately follows the current iteration is indexed by the index "i+1", and so on).

[0105] The control loop is also considered to iterate over a fixed period, for example, a period of 1 second. However, it should be noted that such a period of 1 second does not in any way constitute a limitation of the invention, and nothing precludes considering another period, such as a period of less than 1 second.

[0106] Therefore, for this current iteration, and as mentioned above, each control signal has past values ​​and a current value of its associated quantity. Thus, each control signal S_X (where X can be T_WS or AH_CAB in this embodiment) has a component S_X[i] (current value) but also components S_X[i-1],...,S_X[ik], where k is a specific integer defining the size of a history of past values. To denote the set of these current and past values ​​S_X[i], S_X[i-1],...,S_X[ik], we again use the compact notation S_X[i, i-1,...,ik].

[0107] It should be noted that taking into account past values ​​for each of the control signals S_T_WS and S_AH_CAB is a conventional approach in the context of determining predictive control. Furthermore, it is understood that these past values ​​correspond to values ​​that were considered common during previous iterations of the control loop. These past values ​​are stored, as the control loop is iterated, by dedicated storage methods (e.g., the non-volatile memory 4_C of the SYS_C control system, a dedicated server external to the SYS_C control system, etc.).

[0108] As illustrated by the figure 3 The S_T_WS and S_AH_CAB control signals are obtained (received) by the MOD_OBT acquisition module. This is the subject of a step E10 of the regulation process, as illustrated by the figure 4 .

[0109] The control signals S_T_WS, S_AH_CAB thus obtained are then transmitted by the MOD_OBT acquisition module to the MOD_REG regulation module during a step E20 of the regulation process.

[0110] Upon receiving the aforementioned control signals S_T_WS, S_AH_CAB, and also based on the threshold value VS_RI extracted from the non-volatile memory 4_C, the MOD_REG control module determines the predictive command C_PRED. This is the subject of a step E30 of the regulation process, as illustrated by the figure 4 .

[0111] As a reminder, in the current implementation, the predictive control C_PRED has a plurality of components for the i+1 iteration, namely: components C_PRED_W[i+1], C_PRED_VC[i+1], C_PRED_PT[i+1], C_PRED_PV[i+1] intended for the HVAC air conditioning system, a component C_PRED_HEAT[i+1] intended for the heating means MOD_HEAT.

[0112] The predictive command C_PRED is then transmitted, via the MOD_TX transmission module, to the MOD_HEAT heating system and the HVAC air conditioning system to regulate the risk of condensation on the windshield 110. This is the subject of a stage E40 of the regulation process, as illustrated by the figure 4 .

[0113] There figure 5 is a more detailed schematic representation of the MOD_REG control module belonging to the SYS_C control system used for the operation of the control loop of the figure 3 The implementation details of step E30, executed by the REG regulation module of the figure 5 are also represented in the figure 4 .

[0114] As a reminder, we consider here, without limitation, that the predictive model MODEL used by the MOD_REG control module is formed by two sub-modules, namely the said first and second sub-modules SS_MODEL_CAB, S_MODEL_HVAC.

[0115] As illustrated by the figure 5 , said sub-model SS_MODEL_CAB first receives as input, following the execution of step 20, the control signals S_T_WS, S_AH_CAB.

[0116] The sub-model SS_MODEL_CAB then determines, during a sub-step E30_1 of step E30 of the control process, data S_T_WS[i+1],...,S_T_WS[i+j], as well as data S_AH_CAB[i+1],..., S_AH_CAB[i+j]. These data correspond to predicted values ​​over a future time horizon of size j for each of the quantities T_WS, AH_CAB associated with said control signals S_T_WS, S_AH_CAB.

[0117] It should be noted that considering predictions of the aforementioned quantities T_WS, AH_CAB over a future time horizon is a conventional approach in the implementation of an MPC technique. Furthermore, there is no limitation attached to the size of said future time horizon (i.e., to the value of the integer j), which can be chosen according to considerations well known to those skilled in the art (e.g., execution time of the control loop, accuracy of the predictive command C_PRED, etc.).

[0118] Based on the data determined during substep E30_1, the SS_MODEL_CAB submodel performs, in the implementation mode described here and for each time step m of the future time horizon (i.e., for each integer m between i+1 and i+j): a calculation of the risk indicator I1_RI[m], a determination, on the basis of the calculated risk indicator I1_RI[m], of an associated condensation risk RI[m].

[0119] The condensation risk RI determined by the sub-model SS_MODEL_CAB therefore comprises several components RI[i+1],...,RI[i+k], the calculation and determination steps described above to obtain these components being grouped in a sub-step E30_2 of the step E30 of the regulation process.

[0120] The components RI[i+1],...,RI[i+k] (= RI[i+1,...,i+j] on the figure 5 ), as well as the threshold value VS_RI of the E_CONS constraint set, are then used to perform the optimization of the cost function F. This optimization is the subject of a substep E30_3 of step E30 of the control process, as illustrated by the figure 4 , and is also symbolically represented by means of a functional block referenced "OPTIM_F" on the figure 5 (such a block has a solver function for the cost function F).

[0121] Any optimization algorithm known to a person skilled in the art can be implemented here, and the choice of a particular optimization algorithm is only one variant of the implementation of the invention.

[0122] It should be noted that the optimization of the cost function F can be achieved by also taking into account data provided by the sub-model SS_MODEL_HVAC, such as data relating to the electrical energy consumed by the HVAC system components for which the predictive control C_PRED is, at least in part, intended. Such arrangements are schematically represented in the figure 5 by means of an arrow connecting said sub-model SS_MODEL_HVAC to the OPTIM_F block.

[0123] In practice, the stopping of the cost function optimization algorithm F is conditioned by a stopping criterion. There are no limitations on the nature of this stopping criterion, which may, for example, correspond to a convergence criterion of the metric used by the cost function F (difference between the condensation risk RI predicted by the predictive model and the said threshold value VS_RI, rate of change of the condensation risk RI) and / or to a computation time having reached a given threshold and / or to the achievement of a given number of iterations during which the best solution no longer evolves.

[0124] Optimizing the cost function F ultimately generates a predictive command vector with as many components as the size j of the future time horizon used. In practice, only the first component of this vector (i.e., the component at rank i+1) is retained and corresponds to the predictive command C_PRED intended for the actuators.

[0125] It should be noted that the components of the C_PRED predictive control, in addition to being transmitted to the MOD_HEAT heating system and the HVAC air conditioning system, can also be used to: the implementation of the calculations performed by each of the said sub-models SS_MODEL_CAB, SS_MODEL_HVAC, and / or the updating of parameters of each of the said models SS_MODEL_CAB, SS_MODEL_HVAC.

[0126] To that end, and as illustrated by the figure 5 The components C_PRED_W[i+1], C_PRED_VC[i+1], C_PRED_PT[i+1], and C_PRED_PV[i+1] are also transmitted to the sub-model SSMODEL_HVAC. The component C_PRED_HEAT[i+1] is also transmitted to the sub-model SS_MODEL_CAB.

[0127] Furthermore, once the components of the C_PREP command have been transmitted to the aforementioned sub-models SS_MODEL_CAB and SS_MODEL_HVAC, additional data can be generated by the SS_MODEL_HVAC sub-model and transmitted to the SS_MODEL_CAB sub-model. For example, and as illustrated by the figure 5 This additional data includes an MP_AIR[i+1] value representing the airflow rate of the HVAC system, as well as a T_AIR[i+1] value representing the temperature of the air injected into the passenger compartment by the HVAC system. Such additional data advantageously allows the SS_MODEL_CAB submodel to refine its predictions for the next iteration of the control loop.

[0128] The invention has been described so far assuming that the control method is implemented using only the control signals (two control signals S_T_WS, S_AH, CAB or a single control signal S_RH_CAB). However, the invention is not limited by such provisions, and indeed covers other embodiments in which additional signals, besides the aforementioned control signals, are used to implement the control method.

[0129] There figure 6 schematically represents another specific mode of operation for the control loop. figure 7 represents, in the form of a flowchart, a particular method of implementing the regulation process integrating the control loop of the figure 6 .

[0130] The steps in the regulatory process of the figure 7 include steps E10, E20, E30 and E40 already described above with reference to the figure 4, but also, without limitation, sub-steps E30_1, E30_2 and E30_3 described above with reference to the figure 5 .

[0131] In the mode of the figure 6 The MOD_OBT acquisition module is configured to receive, in addition to the S_T_WS and S_AH_CAB control signals, a plurality of signals, known as "disturbance signals", including: a signal S_V_CAR whose associated quantity is a speed V_CAR of car 100, a signal S_T_EXT whose associated quantity is an outside temperature T_EXT of car 100, a signal S_RH_EXT whose associated quantity is a relative humidity RH_EXT outside of car 100, a signal S_DATA_M whose associated quantity is a meteorological prediction data M (rainfall, sunshine, etc.).

[0132] Similar to what has been described for the control signals S_T_WS, S_AH, CAB, each disturbance signal S_V_CAR, S_T_EXT, S_RH_EXT, S_DATA_M has past values ​​and a current value of the quantity associated with it.

[0133] The acquisition of said disturbance signals S_V_CAR, S_T_EXT, S_RH_EXT, S_DATA_M by the MOD_OBT acquisition module is the subject of a step E11 of the regulation process, as illustrated in figure 7 The order in which steps E10 and E11 are implemented is not limiting to the invention. For example, steps E10 and E11 can be implemented in parallel.

[0134] It should be noted that considering the aforementioned disturbance signals S_V_CAR, S_T_EXT, S_RH_EXT, S_DATA_M constitutes only one implementation variant of the invention. Therefore, nothing precludes considering, in addition to or as a replacement for one or more of the aforementioned signals S_V_CAR, S_T_EXT, S_RH_EXT, S_DATA_M, other disturbance signals, such as: a signal whose associated quantity is a number of people in the vehicle, a signal whose associated quantity is a carbon dioxide level present in the passenger compartment, a signal whose associated quantity is an absolute humidity outside the car 100, a signal whose associated quantity is a solar power absorbed by said at least one glazing and / or by the passenger compartment of the car 100.

[0135] In general, there are no limitations on the number and nature of the disturbance signals that can be considered.

[0136] In the mode of the figure 6 , the SYS_C control system also includes a MOD_DET determination module configured to determine, from the disturbance signals S_V_CAR, S_T_EXT, S_RH_EXT, S_DATA_M, at least one predicted value for each of the quantities V_CAR, T_EXT, S_RH_EXT, DATA_M.

[0137] For example, and as illustrated by the figure 6 The number of predicted values ​​for each quantity V_CAR, T_EXT, S_RH_EXT, DATA_M is equal to j, that is, the number of time steps considered for the future time horizon used by the MOD_REG control module when determining the predictive command C_PRED. However, nothing precludes considering a number other than j, for example, less than j, for the predicted values ​​for each of the quantities V_CAR, T_EXT, S_RH_EXT, DATA_M.

[0138] Following considerations similar to those mentioned above concerning the sub-models SS_MODEL_CAB and SS_MODEL_HVAC, any model (i.e., any set of equations, typically differential equations) capable of modeling the evolution of the quantities V_CAR, T_EXT, S_RH_EXT, and DATA_M, and known to those skilled in the art, may be used here. In other words, the choice of a particular model is merely one implementation variant of the invention.

[0139] The determination of the predicted values ​​for each of the quantities V_CAR, T_EXT, S_RH_EXT, DATA_M by the MOD_DET determination module is the subject of a step E13 of the regulation process, as illustrated by the figure 7 This step E13 is executed after the disturbance signals S_V_CAR, S_T_EXT, S_RH_EXT, S_DATA_M are transmitted by the acquisition module MOD_OBT to the determination module MOD_DET, this transmission being subject to a step E12 of the regulation process.

[0140] The predicted values ​​for each of the quantities V_CAR, T_EXT, S_RH_EXT, DATA_M are in turn transmitted to the MOD_REG control module during a step E21 of the regulation process. The order in which steps E20 and E21 are implemented is not limiting to the invention. For example, steps E20 and E21 can be implemented in parallel.

[0141] In the mode of the figure 6 , during the E30 step of determining the C_PRED command, the predictive model MODEL (more specifically here the sub-model SS_MODEL_CAB) uses, in addition to the control signals S_T_WS, S_AH_CAB, the predicted values ​​for each of the quantities V_CAR, T_EXT, S_RH_EXT, DATA_M.

[0142] Taking into account the predicted values ​​for each of the quantities V_CAR, T_EXT, S_RH_EXT, DATA_M advantageously allows us to refine (i.e. enrich) the models used for determining the predictive control C_PRED, and therefore a fortiori to further increase the accuracy of the regulation implemented.

[0143] The invention has also been described so far considering that the cost function F is optimized, when determining the predictive control C_PRED, by taking into account only the regulation of the presence of fog on the windshield 110. The invention is not limited by such provisions, however, and in fact covers other embodiments in which the cost function F can still take into account other aspects.

[0144] For example, the cost function F may include a weighting of at least one term representing a criterion for the use of car 100. This at least one criterion for use may include at least one of the following: a CRIT_1 criterion relating to the absence of frost on the windscreen 110, a CRIT_2 criterion relating to thermal comfort within the passenger compartment, a CRIT_3 criterion relating to the consumption of electrical energy on board the car 100 and used for the operation of the heating means MOD_HEAT and the HVAC air conditioning system, a CRIT_4 criterion relating to a level of carbon dioxide within the passenger compartment, a CRIT_5 criterion relating to a level of noise within the passenger compartment (example: noise generated by a fan of the HVAC air conditioning system, the level of noise can therefore be modulated by changing the speed of said fan).

[0145] There is no limit to the number of usage criteria (and therefore the number of terms to be weighted) that can be considered among the CRIT_p criteria (p being an integer index between 1 and 5). More generally, nothing precludes considering one or more additional usage criteria as a complement to, or alternative to, all or part of the CRIT_p criteria.

[0146] Consequently, in such embodiments, the cost function F admits a general formulation of the type F = F_D + F_CRIT, where: F_D is a term representing the sole contribution of the regulation of the presence of fog on the windshield 110 to the determination of the predictive command C_PRED, F_CRIT is a term representing the contribution of the criterion or criteria of use taken into account in the determination of the predictive command C_PRED.

[0147] For illustrative purposes only, consider the example where the CRIT_2 and CRIT_3 usage criteria are taken into account. More specifically, regarding the CRIT_2 criterion, comfort conditions are considered to relate not only to the temperature inside the passenger compartment but also to the absolute humidity within that compartment. Therefore, the CRIT_2 criterion relates to thermal comfort within the passenger compartment.

[0148] As is well known, thermal comfort within the passenger compartment can be assessed in various ways. In the example described here, it is considered, without limitation, that thermal comfort is assessed by calculating the difference between a temperature T_CAB of the passenger compartment and a setpoint temperature T_CAB_SET chosen by a user of car 100 (for example, the driver of car 100 sets the temperature T_CAB_SET to 20°C inside the passenger compartment). This setpoint temperature T_CAB_SET is obtained, for example, via the MOD_OBT control module (for example, the MOD_OBT module has a manual input interface). Furthermore, the way in which the temperature T_CAB is regulated can depend not only on the T_CAB_SET setpoint but also, for example, on the selection of an economy temperature control mode.

[0149] Other methods of assessing thermal comfort can of course still be considered, such as an assessment using a Fanger model, also known as the PMV / PPD model (acronyms for "Predicted Mean Vote" and "Predicted Percentage of Dissatisfied" in English-language literature). Generally speaking, there are no limitations on how thermal comfort is assessed within the meaning of the present invention.

[0150] In the implementation example described here, the weightings of the usage criteria CRIT_2 and CRIT_3 can be expressed as follows: F_CRIT = w 2 * F_CRIT_ 2 + w 3 * F_CRIT_ 3 , expression in which: w2 and w3 are weighting factors (i.e., positive or zero real numbers), F_CRIT_2 is a term representing the contribution of the usage criterion CRIT_2 to the term F_CRIT, F_CRIT_3 is a term representing the contribution of the usage criterion CRIT_3 to the term F_CRIT.

[0151] It should be noted that the term "weightings" covers all possible combinations of F_CRIT_2 and F_CRIT_3. In other words, nothing precludes considering the following alternatives: the weights w2 and w3 are both strictly positive, or w2 (respectively w3) is strictly positive, while w3 (respectively w2) is zero.

[0152] It can also be noted that taking into consideration one or more usage criteria in the cost function F has an impact in terms of signals intended to be obtained by the MOD_OBT acquisition module and / or operating constraints of the SYS_C regulation system which must be taken into account at the OPTIM_F optimizer level.

[0153] Thus, returning to the previous example in which the cost function F has the following expression: F = F_D + w 2 * F_CRIT_ 2 + w 3 * F_CRIT_ 3 , We understand that: With regard to criterion CRIT_2, the MOD_OBT acquisition module obtains not only, via appropriate measurements, a control signal S_T_CAB whose associated quantity is the temperature T_CAB of the passenger compartment, but also the value T_CAB_SET which constitutes a constraint belonging to the set of constraints E_CONS and which is provided as input to the optimizer OPTIM_F, with regard to criterion CRIT_3, a signal S_ELEC representing a maximum electrical power available for the operation of said heating means MOD_HEAT and said air conditioning system HVAC, and belonging to the set of constraints E_CONS, is provided as input to the optimizer OPTIM_F.

[0154] In general, for any usage criterion that may be taken into account in the optimization of the cost function F, a person skilled in the art knows how to determine the quantity(ies) (and therefore a fortiori the associated signal(s)) as well as the constraint(s) to be taken into account.

[0155] Finally, the invention has also been described so far considering the MOD_HEAT heating means and the HVAC air conditioning system as two entities external to the SYS_C control system. However, these provisions are not limiting to the invention, and nothing precludes considering embodiments in which the MOD_HEAT heating means and / or the HVAC air conditioning system belong to the SYS_C control system.

Claims

1. A method for regulating the presence of condensation on the inner surface of at least one glazed unit (110) of a vehicle (100), said method including a control loop comprising, during a current iteration, steps of: - obtaining (E10) at least one signal, referred to as a "control signal" (S_T_WS, S_AH_CAB), associated with a quantity and including a current value of said quantity, a risk of moisture condensation on the inner surface of said at least one glazed unit that may be determined from said at least one quantity, - determining (E30) a predictive command (C_PRED) for at least one actuator (MOD_HEAT, HVAC) of the vehicle so as to maintain or lower said risk below a threshold value (VS_RI), said command being determined by means of a predictive model (MODEL) of said risk using said at least one control signal, - transmitting (E40) the predictive command to said at least one actuator; said method being characterized in that said control signal comprises, in addition to the current value of said quantity, also past values of said quantity.

2. The method according to claim 1, wherein a plurality of control signals are obtained, including: - a signal (S_T_WS) whose associated quantity is a temperature of said at least one glazed unit (110), and - a signal (S_AH_CAB) whose associated quantity is an absolute humidity inside the vehicle in the vicinity of said at least one glazed unit.

3. The method according to claim 1, wherein a single control signal is obtained, the quantity associated with said control signal being a relative humidity inside the vehicle in the vicinity of said at least one glazed unit.

4. The method according to any one of claims 1 to 3, wherein the determination of said condensation risk, for a given time interval of a future time horizon, includes: - obtaining a temperature of said at least one glazed unit and of a dew point of the passenger compartment, - calculating a gap between said temperature of said at least one glazed unit and said dew point of the passenger compartment, - comparing said gap with at least one given value.

5. The method according to any one of claims 1 to 4, wherein the determination of said condensation risk, for a given time interval of a future time horizon, includes: - obtaining a relative humidity inside the vehicle in the vicinity of said at least one glazed unit, - comparing said relative humidity with at least one given value.

6. The method according to any one of claims 1 to 5, wherein said at least one actuator includes means for heating (MOD_HEAT) said at least one glazed unit (110) and / or at least one actuator of an air conditioning system (HVAC) of the passenger compartment of the vehicle (100) from: a fan, a compressor, a heating resistor, an air recirculation flap.

7. The method according to any one of claims 1 to 6, wherein the predictive model (MODEL) is configured to model: - the change in temperature and humidity conditions at the inner surface of said at least one glazed unit (110), and - the change in temperature and humidity conditions within the passenger compartment of the vehicle due to the operation of an air-conditioning system of said passenger compartment.

8. The method according to any one of claims 1 to 7, said method also including a step of obtaining (E11) at least one signal, called "disturbance signal", associated with a quantity and including past values and a current value of said quantity, said at least one disturbance signal being at least one of: - a signal whose associated quantity is a number of persons in the vehicle, - a signal whose associated quantity is a carbon dioxide level present in the passenger compartment, - a signal (S_V_CAR) whose associated quantity is a vehicle speed, - a signal (S_T_EXT) whose associated quantity is a temperature outside the vehicle, - a signal (S_RH_EXT) whose associated quantity is a relative or absolute humidity outside the vehicle, - a signal (S_DATA_M) whose associated quantity is a weather forecast item of data, - a signal whose associated quantity is a solar power absorbed by said at least one glazed unit and / or by the passenger compartment of the vehicle, the method further including a step of determining (E13), from said at least one disturbance signal, at least one predicted value of the quantity associated with said at least one disturbance signal, the predictive model (MODEL) of said condensation risk also using said at least predicted value when determining the predictive command (C_PRED) of said at least one actuator (MOD_HEAT, HVAC).

9. The method according to any one of claims 1 to 8, wherein the step of determining (E30) the predictive command includes an optimization of a cost function including at least one term from: - a difference between the condensation risk predicted by the predictive model and said threshold value (VS_RI), - a rate of change in the condensation risk.

10. The method according to claim 9, wherein the cost function also includes a weighting of at least one term representative of a vehicle usage criterion, said at least one usage criterion including at least one of: - a criterion relating to an absence of frost on said at least one glazed unit, - a criterion relating to thermal comfort within the passenger compartment, - a criterion relating to electrical energy consumption on board the vehicle and used for the operation of said at least one actuator, - a criterion relating to a carbon dioxide level within the passenger compartment, - a criterion relating to a noise level within the passenger compartment.

11. A computer program (PROG_C) including instructions for implementing a regulating method according to any one of claims 1 to 10 when said program is executed by a computer.

12. A computer-readable recording medium on which a computer program according to claim 11 is recorded.

13. A system (SYS_C) for regulating the presence of condensation on at least one glazed unit (110) of a vehicle (100), said system including means configured to implement a regulating method according to any one of claims 1 to 10.

14. A vehicle (100) including a system for regulating according to claim 13.

15. The vehicle (100) according to claim 14, said vehicle including at least one electric motor to run on.