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    • 专利摘要:
    The present invention relates to a method for determining an optimum speed to be achieved for a first vehicle preceded by a second vehicle. For this method, the position, the speed and the acceleration of the second vehicle are measured (MES) to determine its trajectory (POS), and a dynamic model (MOD) of the first vehicle is constructed. Then, the speed to be achieved (VIT) is determined by minimizing (MIN) the energy consumed by the vehicle by means of the dynamic model (MIN), the minimization being constrained by the trajectory (POS) of the second vehicle.
    公开号:FR3070658A1
    申请号:FR1758212
    申请日:2017-09-06
    公开日:2019-03-08
    发明作者:Luis Leon-Ojeda；Jihun HAN；Antonio Sciarretta；Laurent Thibault；Giovanni DE NUNZIO
    申请人:IFP Energies Nouvelles IFPEN；
    IPC主号:
    专利说明:

    The present invention relates to the field of vehicle navigation, and in particular to the field of determining a speed which optimizes the energy consumed, in particular for an autonomous vehicle.
    According to the International Energy Agency, more than 50% of the oil used in the world is intended for the transport sector, including more than three quarters for road transport. According to the same agency, the transport sector was responsible for almost a quarter (23.8%) of greenhouse gas emissions and more than a quarter (27.9%) of CO 2 emissions in Europe in 2006.
    It is therefore increasingly important to increase the energy efficiency of road trips, to reduce energy consumption, whether fossil or electric. To achieve this, driver assistance systems (ADAS, for "Advanced Driver Assistance Systems") represent a promising solution, because it is economical (because you can simply use the driver's smartphone or an on-board system) and non-intrusive (because there is no need to make modifications to the mechanical components of the vehicle).
    Among the driving assistance systems, the applicant has developed a method for determining an eco-driving indicator, described in particular in patent FR 2,994,923 (US 9,286,737). This method is satisfactory, in particular because it makes it possible to determine an energy indicator on a section of the journey made by a vehicle. However, it is desirable to take into account more precisely the traffic conditions, and in particular the behavior of the vehicle preceding the vehicle in question. In addition, it is desirable to determine in real time an optimal speed predictive from an energy point of view for a future road segment.
    In addition, manufacturers are currently developing autonomous vehicles (i.e. vehicles that do not require user intervention to get around). Autonomous vehicles must take into account the vehicle's traffic context (for example: traffic, speed limits, etc.) as well as security constraints to determine its control.
    The eco-driving process described in patent FR 2,994,923 (US 9,286,737) cited above does not allow the control of an autonomous vehicle.
    Different methods for controlling the speed and movement of autonomous vehicles have been developed.
    For example, US Pat. No. 5,448,7479 deals with the control of the speed of the control of an autonomous vehicle for the purpose of preventing collision with a vehicle in front. However, the control described in this patent does not minimize the energy consumed by the vehicle. Consequently, this control is not optimal in terms of energy consumed.
    To overcome these drawbacks, the present invention relates to a method for determining an optimum speed to be achieved for a first vehicle preceded by a second vehicle. For this process, we measure the position, speed and acceleration of the second vehicle to determine its trajectory, and we construct a dynamic model of the first vehicle. Then, the speed to be reached is determined by minimizing the energy consumed by the vehicle using the dynamic model, the minimization being constrained by the trajectory of the second vehicle. Thus, the method determines a speed which avoids collision with the vehicle in front while minimizing the energy consumed. In addition, the method according to the invention is suitable for an autonomous vehicle, since the speed is determined in real time, and can therefore be directly applied for the control of the first vehicle.
    The method according to the invention
    The invention relates to a method for determining a speed to be reached for a first vehicle, the first vehicle being preceded on the road by a second vehicle. For this process, the following steps are carried out:
    a) the distance, speed and acceleration of said second vehicle preceding said first vehicle are measured;
    b) the trajectory of said second vehicle is determined by means of said measurements;
    c) a dynamic model of said first vehicle is constructed which relates the energy consumed by said first vehicle to the speed of said first vehicle; and
    d) an optimal speed to be reached by said first vehicle is determined by minimizing the energy consumed by said first vehicle, by means of said dynamic model, the minimization of energy consumed being constrained by said trajectory of said second vehicle.
    According to an embodiment of the invention, the optimal speed of said first vehicle is determined by an approach of the MPC type.
    Advantageously, said MPC type approach is carried out over a determined time horizon taking into account the traffic conditions.
    In accordance with one implementation, the minimization of the energy consumed is constrained by traffic conditions and / or by speed limits and / or by the road infrastructure on which said first vehicle travels.
    Preferably, said traffic conditions, speed limits and / or road infrastructure are obtained in real time by communication with online data services.
    In one aspect, minimization is constrained by a safety distance between said first vehicle and said second vehicle.
    According to an embodiment of the invention, the method comprises a step of controlling said first vehicle with said optimal speed.
    Advantageously, said first vehicle is an autonomous vehicle.
    Alternatively, the method comprises a step of comparing either between the optimal speed determined and the speed reached by the driver of said first vehicle, or between the optimal energy determined by means of the optimal speed and the energy consumed by the first vehicle, and a step of determining an energy conduct indicator by means of said comparison.
    According to an implementation of the invention, the optimal energy is determined by minimizing a function J, of the form J = f 0 P S ource (. U > v) dt with P S0U rce the power supplied by the engine of said first vehicle, u the torque supplied by the engine of said first vehicle, and v the speed of said first vehicle.
    According to one characteristic, the dynamic model of said first vehicle is written in the form:
    mv = F t - F a - F r - F g - F b with m the mass of said first vehicle, F, the traction force, F has the aerodynamic force, F r the rolling force, F g the gravitational force, and F b the mechanical braking force.
    According to one aspect, said dynamic model of the vehicle depends on intrinsic parameters of said vehicle.
    Advantageously, said intrinsic parameters of said vehicle are obtained from a database, or are indicated by a user.
    According to one embodiment, the trajectory of said second vehicle is determined by determining its position using an equation of the type: s Leader s h- As + ^ Leadert T 1/2 ci /, eader ^ with $ beader the position of said second vehicle, s the position of said first vehicle, As the distance between said first vehicle and said second vehicle, t time, v Leader the speed of said second vehicle and a Leader the acceleration of said second vehicle.
    Furthermore, the invention relates to a computer program product downloadable from a communication network and / or recorded on a computer-readable medium and / or executable by a processor or a server, comprising program code instructions for setting implementing the method according to one of the preceding characteristics, when said program is executed on a computer or on a portable telephone.
    Brief presentation of the figures
    Other characteristics and advantages of the method according to the invention will appear on reading the description below of nonlimiting examples of embodiments, with reference to the appended figures and described below.
    FIG. 1 illustrates the steps of the method according to a first embodiment of the invention.
    FIG. 2 illustrates the steps of the method according to a second embodiment of the invention.
    FIG. 3 illustrates the steps of the method according to a third embodiment of the invention.
    FIG. 4 illustrates a portion of the route used for the first example of application.
    FIG. 5 illustrates the curves of the speed, of the position, of the engine torque and of the energy consumed for an optimal energy solution, for the vehicle preceding the vehicle in question, for a method according to the prior art, and for a method according to the invention, in the context of a first example.
    Figure 6 illustrates a curve between the energy consumed and the arrival time in the first example.
    FIG. 7 illustrates the curves of the speed, and of the energy consumed for an optimal energy solution, for the vehicle preceding the vehicle in question, for a method according to the prior art, and for a method according to the invention, in the part of a second example.
    Detailed description of the invention
    The present invention relates to a method for determining an optimal speed to reach for a first vehicle, the first vehicle being preceded on the road by a second vehicle. The first vehicle is the vehicle considered for which the optimum speed to be reached is determined.
    The method according to the invention is suitable for any type of vehicle: thermal vehicles, hybrid vehicles, electric vehicles, etc. In addition, the vehicle can be an autonomous vehicle or not.
    5notations In the following description, the following notations are used: VFirst vehicle speed [M / s]sPosition of the first vehicle [M]mMass of the first vehicle [Kg] 10 Cô m Engine speed of the first vehicle [R / s]F t Tractive effort from vehicle to wheel [NOT]F a Aerodynamic force on the vehicle [NOT]F r Friction force undergone by the vehicle [NOT] F 9Normal force undergone by the vehicle (gravity) [NOT] 15 F b Mechanical braking force [NOT]atRoad tilt angle [Rad]PaAir density [kg / m 3 ] A fVehicle front surface [m 2 ]CDCoefficient of aerodynamic resistance [-] 20 c r Rolling resistance coefficient [-]9Gravitational acceleration [m / s 2 ]rWheel radius [M]R t Vehicle transmission report [-]9tVehicle transmission efficiency [-] 25 TEngine couple [Nm]source p r Engine power of the first vehicle [W]UEngine torque of the first vehicle [Nm] s Leader Position of the second vehicle [M]USDistance between first vehicle and second vehicle [M] 30 VLeader Second vehicle speed [M / s]^ Leader Second vehicle acceleration [m / s 2 ]tTime [S]T 1 cNo control [S]TPrediction and optimization horizon (assumption of time until next 35 stopping point which can be based on traffic and map information) [S]notNumber of control steps [-]
    Δ Control horizon [S] Go Electric machine voltage [V] ia Electric machine current [AT] Ra Electric machine resistance [Ohm] k Electric machine speed constant [-] to Current time at launch of a new optimization [S] s f Position of the first vehicle at time T (equal to the length of the road until the next stop) [M] v 0 Speed of the first vehicle at time t 0 (measured) [M / s]
    Vf Speed of the first vehicle at time T (prediction based on traffic and cartog raphic information) [m / s]
    For these notations, the derivative with respect to time is noted or by a point above the variable considered.
    The method according to the invention comprises the following steps:
    1) measurement of the distance, speed and acceleration of the second vehicle,
    2) determining the trajectory of the second vehicle,
    3) construction of a dynamic model of the first vehicle,
    4) determination of the optimal speed of the first vehicle.
    The steps for building the dynamic model of the vehicle on the one hand and for measuring and determining the trajectory of the second vehicle on the other hand can be carried out in this order, simultaneously or in reverse order.
    Preferably, the method according to the invention is executed in real time.
    Thus the method according to the invention allows a real-time determination of the optimal speed. In this way, the determined optimum speed can be applied directly to the vehicle.
    FIG. 1 illustrates, schematically and without limitation, the steps of the method according to a first embodiment of the invention.
    1) measuring the distance, speed and acceleration of the second vehicle (MES)
    2) determination of the trajectory of the second vehicle (POS) by means of the measurements (MES),
    3) construction of a dynamic model (MOD) of the first vehicle,
    4) determination of the optimal speed (VIT) of the first vehicle by minimization of the energy consumed by the first vehicle determined by means of the dynamic model (MOD), the minimization being constrained by the trajectory (POS) of the second vehicle.
    According to a second embodiment of the invention, the method can include an additional step of controlling the first vehicle on the basis of the determined optimal speed. This check consists in applying the determined optimal speed (VIT) to the first vehicle.
    FIG. 2 illustrates, schematically and without limitation, the steps of the method according to the second embodiment of the invention. In addition to the steps described in relation to FIG. 1, the method includes the following optional steps:
    - determination of road traffic (TRA), the determination of traffic can be used to determine the optimal speed by minimizing the energy consumed (MIN),
    - determination of road infrastructure (INF), the determination of road infrastructure can be used to determine the optimal speed by minimizing the energy consumed (MIN),
    - determination of speed limits (LIM), the determination of speed limits can be used to determine the optimal speed by minimizing the energy consumed (MIN),
    - determination of intrinsic vehicle parameters (PAR), these parameters can be used to build the dynamic model (MOD),
    - control of the first vehicle (CON), this control consists in applying the determined optimal speed (VIT) to the first vehicle.
    The stages of determining road traffic (TRA), road infrastructure (INF), speed limits (LIM) and intrinsic vehicle parameters (PAR) are independent. It is therefore possible to carry out only part of these steps. In addition, these steps are not linked to the control step (CON) of the first vehicle. In other words, the control step (CON) of the first vehicle can be carried out without or with all or part of these steps (TRA, INF, LIM, PAR), and these steps (TRA, INF, LIM, PAR ) can be added to the embodiment illustrated in FIG. 1.
    According to a third embodiment of the invention, the method can include an additional step of comparing either the optimal speed determined with the speed achieved by the user, or the energy actually consumed with the optimal consumed energy determined at starting from the optimal speed, then an additional step of determining an energy indicator (called eco-driving indicator) obtained by means of the comparison. This indicator can be displayed for the driver.
    FIG. 3 illustrates, schematically and without limitation, the steps of the method according to the third embodiment of the invention. In addition to the steps described in relation to FIG. 1, the method includes the following optional steps:
    - determination of road traffic (TRA), the determination of traffic can be used to determine the optimal speed by minimizing the energy consumed (MIN),
    - determination of road infrastructure (INF), the determination of road infrastructure can be used to determine the optimal speed by minimizing the energy consumed (MIN),
    - determination of speed limits (LIM), the determination of speed limits can be used to determine the optimal speed by minimizing the energy consumed (MIN),
    - determination of intrinsic vehicle parameters (PAR), these parameters can be used to build the dynamic model (MOD),
    - comparison of the determined optimal speed (VIT) with a speed achieved (COMP) or comparison of the optimal energy linked to the optimal speed (VIT) with the energy actually consumed,
    - determination of an eco-driving indicator (IND) on the basis of the comparison (COMP).
    The stages of determining road traffic (TRA), road infrastructure (INF), speed limits (LIM) and intrinsic vehicle parameters (PAR) are independent. It is therefore possible to carry out only part of these steps. In addition, these steps are not linked to the comparison (COMP) and indicator determination (IND) steps. In other words, the steps of comparison (COMP) and determination of an indicator (IND) can be carried out without or with all or part of these steps (TRA, INF, LIM, PAR), and these steps (TRA , INF, LIM, PAR) can be added to the embodiment illustrated in FIG. 1.
    All the process steps, including their variants proposed in Figures 2 and 3 are described below.
    1) Measure the distance, speed, acceleration of the second vehicle (MES)
    During this step, we measure, in real time:
    - the distance between the first vehicle and the second vehicle,
    - the speed of the second vehicle, and the acceleration of the second vehicle.
    According to an implementation of the invention, these measurements can be carried out by at least one sensor installed in the first vehicle. The sensor can be a camera, a radar, a lidar, etc. These sensors can be redundant, especially in an autonomous vehicle, in order to improve safety.
    According to another implementation of the invention, the position and the distance can be obtained by means of at least one sensor, and the speed and the acceleration can be calculated from the position and the distance.
    2) Determination of the trajectory of the second vehicle (POS)
    During this step, the trajectory of the second vehicle is determined in real time by means of the measurements made in the previous step. In other words, we determine the position of the second vehicle on the road.
    According to one embodiment of the invention, the trajectory of the second vehicle can be determined by means of an equation of the type:
    s Leader S + AS + V / ^ eader ^ 3 1/2 ^ Leader with SLeader I® position of the second vehicle, s position of the first vehicle, As the distance measured between said first vehicle and said second vehicle, t the time, v Leader the measured speed of said second vehicle and a Leader the measured acceleration of said second vehicle.
    For the method according to the invention, the position s of the first vehicle can be measured, in particular using a geolocation system (GPS). In addition, the speed of the first vehicle can be measured, in particular by means of a geolocation system (GPS).
    3) Construction of the dynamic model of the first vehicle (MOP)
    During this step, a dynamic model of the vehicle of the first vehicle is constructed. The dynamic vehicle model is a model that relates the energy consumed by the vehicle to the speed and acceleration of the vehicle. The dynamic model of the vehicle can be built using the fundamental principle of dynamics, combined with an energy model of the engine.
    According to an implementation of the invention (cf. step of determining the intrinsic parameters of the vehicle in FIG. 2), the model can be constructed from macroscopic parameters of the vehicle, for example: motorization of the vehicle, mass of the vehicle, maximum power, maximum speed, type of transmission, aerodynamic parameters, etc. Thus, the dynamic model is representative of the vehicle, and takes into account its specific characteristics.
    According to an alternative embodiment, the macroscopic parameters can be obtained from a database, which lists the various vehicles in circulation. For example, the macroscopic parameters can be obtained by indicating the registration number of the vehicle, the database associating the plate number with its design (make, model, engine ...), and comprising the macroscopic parameters of the vehicle .
    Alternatively, the macroscopic parameters can be manufacturer data entered by the user, in particular by means of an interface (for example a smartphone, the dashboard, or a geolocation system).
    The dynamic model of the vehicle may also depend on road parameters, such as the slope of the road. Such data can be obtained from a topology or a map of the road network.
    If no loss in the transmission and no slip on the wheels is present, the transmission model can be written as follows:
    y 1 n s ÎS n (Tm) 1 m r lt
    R t
    Where F t is the traction force, R t and are respectively the transmission ratio and the transmission efficiency, T m is the engine torque (electric, thermal, or hybrid by the combination of the two), v is the longitudinal speed, r is the wheel radius, and m m is the engine speed.
    From Newton's third law (i.e. the fundamental principle of dynamics), the model of the vehicle's longitudinal dynamics can be expressed using resistive forces (aerodynamics F a , bearing F r , and gravitational F g ) and the mechanical braking force, F b , as follows:
    s = v m v = F t - F a - F r - F g - F b mv = ^ -T m g s t ian (Trn) - ^ PaAfc d v 2 - mgc r - mgsin (a (s /) - F b where m is the mass of the vehicle, p a the air density, A f the front surface of the vehicle, c d the aerodynamic resistance coefficient, c r the rolling resistance coefficient, a (s) la slope of the road as a function of the position, and g the acceleration of gravity The control variable is defined as the requested engine torque u = T m .
    4) Determination of the optimal speed (MIN, VIT)
    During this step, the optimal speed of the first vehicle is determined in real time and predictively: this optimal speed:
    minimizes the energy consumed, and
    - takes into account the trajectory of the second vehicle.
    Thus, the method according to the invention makes it possible to minimize the energy consumed while taking into account the traffic conditions and while avoiding the risks of collision with the second vehicle.
    For this, the determination of the optimal speed can be carried out by a minimization method which is constrained by the trajectory of the second vehicle.
    In accordance with an implementation of the invention, the minimization method can also be constrained by at least one of the following conditions:
    - the speed limits of the road on which the first vehicle travels (and a fortiori the second vehicle),
    - traffic conditions, and
    - road infrastructure, i.e. the type of road (city road, motorway, etc.) and means of traffic control (roundabout, intersection, traffic lights, etc.).
    Taking these conditions into account makes it possible to determine an optimal speed which really corresponds to the path of the vehicle, and makes it possible to increase the safety aspect obtained by the optimal speed.
    Advantageously, information on speed limits, traffic conditions and road infrastructure can be obtained in real time by communication with online data services (from English webservices).
    In addition, the minimization method can be constrained by a safety distance between the first vehicle and the second vehicle. This safety distance can be dependent on speed, road infrastructure, traffic conditions. This constraint also makes it possible to increase the safety character obtained by the optimal speed, by avoiding the risk of collision with the second vehicle.
    According to an embodiment of the invention, the minimization method used is an approach of the MPC type. The principle of this technique is to use a dynamic model of the process inside the controller in real time in order to anticipate the future behavior of the process. In English, we use the term MPC or MBPC to qualify the predictive command: Model (Based) Predictive Control.
    For this, the spatial and temporal horizons can be divided into n no control Te. At each step an optimal command is updated and applied according to the new measurements of the second vehicle. The spatial horizon can be calculated between the current vehicle position and the next stop point. The time horizon can be retrieved via a "web service" which takes traffic conditions into account.
    The next stop is the next infrastructure obstacle that will force you to slow down. It can be estimated from a cartographic information system (for example the next intersection, traffic light or pedestrian crossing). This information can be reinforced by a camera-type sensor or by communication with the infrastructure.
    The effectiveness of predictive control systems is linked to the nature of the prediction models used or the value of the control horizon. The more precise the prediction or the shorter the horizon, the more reliable the solution will be. The present invention uses a simple prediction model which risks degrading the quality of the optimization. However, since the computation time of the solution at each step is negligible, since it is analytical, the control horizon can be short enough to guarantee almost optimal performance.
    According to one embodiment of the invention, for this optimization problem, the approach described below can be carried out.
    The energy consumption can be deduced from the power, which is a function of the torque u and the speed v of the first vehicle:
    ^ source 9
    The constraints of the problem can be given by the speed limits and the predicted trajectory of the second vehicle (determined in step 2).
    We can determine the optimal energy by minimizing a function J, of the type min / = P S ource (u, v) dt, subject to:
    h (x, t) <0 ue U, xe X $ (t 0 ) = 0,
    v (t 0 ) = v 0 , v (T) = v f with:
    U = [T m , Ffc] x = [s, v] f = [v, - h 2 v 2 - h 0 - F b ] [ 5 - s Leader> v v maxl and:
    h. = - ^, x rm hz = 2 ^ PaAfCd
    Æ o = 9 c r + gsin (a (sy),
    In order to solve the problem presented previously, two methods are generally used, the direct adjacent method and the indirect adjacent method. For this embodiment of the invention, the indirect method can be applied as follows.
    Given the presence of constraints, can be defined:
    H (u, x, λ, t) = P source (u, v ) + 3, T f (u, x, t) L (u, x, λ, t) = H (u, x, λ, t ) + p T h (p> (u, x) where p is the order of the state constraint, which is defined as the number of successive differentiations of h until the explicit appearance of the control.
    The optimal conditions can be:
    u * (t) = argmin u H (u *, x *, Â *, t), x * (t) = dL (u *, χ *, λ *, η *, t) / δλ,
    Â * (t) = dL (u *, χ *, λ *, η *, t) / dx, p * (t '). H ^ (u *, x *, t') = 0, 7 * (ί)> 0
    Because of the presence of possible jumps in the solution, the junction times can satisfy:
    F® (x, t)
    Ψ (χ, ί) = h (P ~ i ') (x i f).
    = â * (t + ) t + V pj.h ^) (x *, T),
    4-lj = 0
    Η ° (τ ~) = H ° (t + ) - P .ψ χ *, τ ^ - <7 = 0
    Where τ is the jump time of the solution and the components of the Lagrange multiplier η.
    The set of equations described above makes it possible to find an analytical solution to the problem formulated.
    Thus, an optimum speed is determined in real time energetically, while taking into account the behavior of the second vehicle, and while maintaining high safety.
    5) Control of the first vehicle
    This is an optional step corresponding to the second embodiment of the invention illustrated in FIG. 2.
    During this step, the first vehicle is checked in real time as a function of the optimal speed determined in step 4. In other words, the optimum speed determined is applied to the first vehicle. This optimal speed minimizes the energy consumed by the first vehicle while ensuring high safety conditions.
    To do this, the powertrain of the first vehicle can be controlled. It can include a heat engine, an electric machine or a hybrid system.
    This embodiment is particularly suitable for an autonomous vehicle.
    5’1 Comparison of the determined optimal speed with the speed achieved (COMP)
    This is an optional step corresponding to the first additional step of the third embodiment of the invention illustrated in FIG. 3.
    This stage is carried out at the end of a stretch of road, on which the first vehicle has driven. During this step, the optimal speed determined in step 4 is compared with the speed achieved (measured) by the vehicle.
    Alternatively, during this step, we can compare the optimal energy consumed linked to the optimal speed, and the energy actually consumed by the first vehicle.
    6’1 Determination of an eco-driving indicator (IND)
    This is an optional step corresponding to the second additional step of the third embodiment of the invention illustrated in FIG. 3.
    During this step, at least one eco-driving indicator is determined by means of the comparison carried out in step 5 ’.
    According to one aspect of the invention, the eco-driving indicator can be the difference between the energy actually consumed by the first vehicle and the energy corresponding to the determined optimal speed.
    Alternatively, the eco-driving indicator can be a ratio between the energy consumed by the first vehicle and the energy corresponding to the optimum speed determined.
    Once the energy indicator (s) have been determined, this information can be transmitted to the driver by means of a display. This display can be carried out on board the vehicle: on the dashboard, on an autonomous portable device, such as a geolocation device (GPS type), a mobile phone (smartphone type, translation of smartphone anglicism) ). It is also possible to display this indicator on a website, which the driver can consult after driving.
    The method according to the invention can be used for motor vehicles. However, it can be used in the field of road transport, the field of two-wheelers, etc.
    The invention also relates to a computer program product downloadable from a communication network and / or recorded on a computer-readable medium and / or executable by a processor or a server. This program includes program code instructions for implementing the method as described above, when the program is executed on a computer or a mobile phone or any similar system.
    Application examples
    The characteristics and advantages of the process according to the invention will appear more clearly on reading the examples of application below.
    For the two application examples, we study the case of an electric vehicle (for the first vehicle) in order to illustrate the application of the invention to a given example.
    Thanks to the regenerative braking of the electric vehicle, we can assume that the mechanical brake is not used (F b = 0), therefore u = T m in this case. A static model of the DC electric machine is used to describe the power at the source, which corresponds to the electric power of the motor, P m in this case.
    ^ source Κύα - ü) m U + - byu.V + b 2 U
    Where V a , i a and R a are respectively the voltage, the current and the resistance, k is the speed constant, and ω ιη is the speed of rotation of the motor. We can note that V a = ÏA Ί ”k (t) m and i a - -.
    For the two examples below, we consider the vehicle defined in Table 1:
    Table 1 - vehicle parameters
    Description Setting Value Vehicle mass m 1432 kg Wheel radius r 0.2820 m Transmission report R t 9.5900 Efficiency0.98 Coefficient of the static model of the electric machine bi 34.01 Coefficient of the static model of the electric machine b> 2 0.873 Coefficient h 0 185.43 Coefficient b-2 0.2996
    The first case study corresponds to a simulation study carried out using software modeling the traffic of a city on a microscopic scale. This software allows in particular to simulate the behavior of a vehicle not optimized by the present invention, in order to estimate the gains.
    The study scenario corresponds to the movement of two vehicles between a point A and a point B, passing through a roundabout and a red light, disturbances of the infrastructure not known a priori by the process of determining a speed at of the present invention. The interest of this test case is to measure the performance of the invention in real life conditions. The second vehicle travels following a Gipps profile (the Gipps model is a following car model, based on driver behavior and the life expectancy of vehicles in a traffic flow).
    FIG. 4 schematically illustrates the movement of the two vehicles between point A and point B. On this route 3, a first vehicle 1 follows a second vehicle 2. Route 3 comprises a first segment of route 4 between point A and a roundabout 5, roundabout 5, a second road segment 6 between the roundabout 5 and a traffic light 7 located at point B.
    For this first example, the simulation parameters are defined in Table 2:
    Table 2 - Taxi and simulation parameters
    Setting Value Total distance D 1000 m Total duration T 80s Inter-initial distance d 100 m Maximum speed Vmax 50 km / h Initial speed v 0 0 km / h Final speed V 50 km / h Control horizon T 2 c 0.1 s
    The invention is compared with two other approaches, in order to estimate its performance:
    1- an optimal solution found via the penalization method (BVP). This optimal solution makes it possible to quantify the gain potential but requires perfect knowledge of the trajectory of the second vehicle a priori, which is not realistic.
    2- a standard non-eco-driving profile, reference solution, without energy optimization, this solution being calculated using the Gipps model.
    In all cases, the first vehicle catches up with the second vehicle, at the distance between the two near vehicles, at the end of the road segment.
    FIG. 5 illustrates several curves of the speed of the first vehicle v (km / h), of the position of the first vehicle p (m), of the engine torque of the first vehicle C (Nm) and of the energy consumed E normalized by the distance traveled (Wh / km) by the first vehicle. On these curves, the values of the second vehicle are indicated L, the values obtained by the optimal BVP solution of the prior art are indicated O, the values obtained by the standard profile of Gipps type not eco-driving of the prior art are denoted A, and the values obtained by the method according to the invention are denoted I and are illustrated by dotted lines.
    It is interesting to observe the behavior of the method according to the invention in the face of a disturbance in the driving of the second vehicle. The figure at the top right shows that the eco-driving vehicle according to invention I arrives at the roundabout (16 s) at a lower speed compared to non-eco driving A, which makes acceleration and phases less frank deceleration. Between 40 s and 70 s all vehicles behave in the same way, whereas when the red light approaches, the eco-driving vehicle according to the invention I anticipates a better deceleration in contrast with the non-eco driving according to the PRIOR ART A. In the figure at the top right, it is observed that the constraint imposed by the trajectory of the second vehicle is respected by the eco-driving vehicle according to invention I, while in the figure at the bottom left, we notes a better limitation of the torque with the eco-driving vehicle according to invention I. Finally, in the figure at the bottom right, the energy savings, which are normalized by the distance traveled, are presented. Compared to non-eco driving according to prior art A, the invention achieves an energy saving of 31%. This significant gain is due to the optimization achieved by the present invention. In addition, it is interesting to note that the energy consumption obtained according to invention I is very close to the optimal value O although the present invention does not know all of the a priori disturbances such as the BVP approach.
    As listed in the advantages, the invention makes it possible to settle the compromise between journey times and energy consumption. This compromise is illustrated in FIG. 6. The points of the curve located on the origin of the abscissas represent the case of FIG. 5. On these curves, the values of the second vehicle are indicated L, the values obtained by the optimal solution BVP of the prior art are indicated O, the values obtained by the standard non-eco-conductive profile of the prior art are denoted A, and the values obtained by the process according to the invention are denoted I and are illustrated by a solid line black.
    As expected, when the first vehicle moves more slowly, it gains energy. For example, by letting it arrive 10% later (8 s later than the second vehicle), 5% of the gain is obtained.
    The second example of application corresponds to an actual driving on a national road. This speed profile is used as the profile followed by the second vehicle. The objective is to illustrate the response of the invention when the acceleration of the second vehicle varies, in order to test the hypothesis of constant acceleration of the second vehicle.
    For this second example, the simulation parameters are defined in Table 3:
    Table 3 - Taxi and simulation parameters
    Setting Value Total distance D 1073 m Total duration T 142s Inter-initial distance d 75 m Maximum speed Knax 50 km / h Initial speed v 0 0 km / h Final speed v f 0 km / h Control horizon You 0.1 s
    The prediction horizon (average time taken to cover the road segment considered) is provided by a cartographic webservice.
    Figure 6 illustrates several curves of the speed of the first vehicle v (km / h), and of the energy consumed E (Wh / km) normalized by the distance traveled by the first vehicle. On these curves, the values of the second vehicle are indicated L, the values obtained by the optimal BVP solution of the prior art are indicated O, the values obtained by the standard profile of Gipps type not eco-driving of the prior art are denoted A, and the values obtained by the method according to the invention are denoted I and are illustrated by a solid black line.
    In the top figure, we can see that the second vehicle L follows an acceleration profile with strong dynamics which can reduce the potential gains in energy consumption by reducing the degree of freedom of the first vehicle. However, the proposed approach I filters out some of these dynamics, in particular in the acceleration and deceleration phases. However, between 70 and 130 s, the method according to invention I offers dynamics comparable to those of the second vehicle L. This is due to the lack of visibility of the future behavior of the second vehicle L. When studying the optimal profile O , we observe a result which seems to be a filtering of the eco-driving result where the acceleration variabilities are eliminated. As for the Gipps A approach according to the prior art, there is a strong acceleration phase until it follows the profile of the second vehicle.
    The bottom figure shows some interesting energy results. As expected, the BVP O approach provides the best solution, followed by the approach according to invention I, then by the Gipps A approach according to the prior art, and finally by the energy of the second vehicle. Table 4 shows the energy losses compared to the BVP approach.
    Table 4 - Results in terms of energy gain
    Solution Energy consumed Wh / km % compared to BVP Gipps 79.37 20.43 Method according to the invention 71.56 8.60 BVP 65.90 -
    Thus, the method according to the invention makes it possible to determine a speed to be reached for the first vehicle which minimizes the energy consumed (which is not the case with the Gipps approach), while taking into account the behavior of the vehicle. which precedes it (which is not the case with the BVP approach), and while avoiding the risk of collision.
    权利要求:
    Claims (15)
    [1" id="c-fr-0001]
    1) Method for determining a speed to be reached for a first vehicle (1), the first vehicle (1) being preceded on the road (3) by a second vehicle (2), characterized in that the steps are carried out following:
    a) the distance, speed and acceleration of said second vehicle (2) preceding said first vehicle (1) are measured (MES);
    b) the trajectory (POS) of said second vehicle (2) is determined by means of said measurements (MES);
    c) a dynamic model (MOD) of said first vehicle (1) is constructed which links the energy consumed by said first vehicle (1) to the speed of said first vehicle (1); and
    d) an optimal speed (VIT) to be reached by said first vehicle (1) is determined by minimization (MIN) of the energy consumed by said first vehicle (1), by means of said dynamic model (MOD), the minimization of l energy consumed being constrained by said trajectory (POS) of said second vehicle (2).
    [2" id="c-fr-0002]
    2) Method according to claim 1, in which the optimum speed (VIT) of said first vehicle (1) is determined by an MPC type approach.
    [3" id="c-fr-0003]
    3) Method according to claim 2, wherein said MPC type approach is performed over a determined time horizon taking into account the traffic conditions.
    [4" id="c-fr-0004]
    4) Method according to one of the preceding claims, in which the minimization of the energy consumed is constrained by traffic conditions (TRA) and / or by speed limits (LIM) and / or by road infrastructure ( INF), on which said first vehicle travels (1).
    [5" id="c-fr-0005]
    5) Method according to one of claims 3 or 4, wherein said traffic conditions (TRA), speed limits (LIM) and / or road infrastructure (INF) are obtained in real time by communication with services online data.
    [6" id="c-fr-0006]
    6) Method according to one of the preceding claims, wherein the minimization is constrained by a safety distance between said first vehicle (1) and said second vehicle (2).
    [7" id="c-fr-0007]
    7) Method according to one of the preceding claims, in which the method comprises a step of checking (CON) of said first vehicle (1) with said optimal speed (VIT).
    [8" id="c-fr-0008]
    8) The method of claim 7, wherein said first vehicle (1) is an autonomous vehicle.
    [9" id="c-fr-0009]
    9) Method according to one of claims 1 to 6, wherein the method comprises a comparison step (COMP) either between the optimal speed (VIT) determined and the speed reached by the driver of said first vehicle (1), or between the optimal energy determined by means of the optimal speed (VIT) and the energy consumed by the first vehicle, and a step of determining an indicator (IND) of energy driving by means of said comparison (COMP).
    [10" id="c-fr-0010]
    10) Method according to one of the preceding claims, in which the optimal energy is determined by minimization of a function J, of the form J = f 0 P SO urce (. U > v) dt with Psourœ the power supplied by the engine of said first vehicle (1), u the torque supplied by the engine of said first vehicle (1), and v the speed of said first vehicle (1).
    [11" id="c-fr-0011]
    11) Method according to one of the preceding claims, in which the dynamic model (MOD) of said first vehicle (1) is written in the form: mv = F t - F a - F r - F g - F b with m the mass of said first vehicle (1), F, the traction force, F has the aerodynamic force, F r the rolling force, F g the gravitational force, and F b the mechanical braking force.
    [12" id="c-fr-0012]
    12) Method according to one of the preceding claims, wherein said dynamic model (MOD) of the vehicle depends on intrinsic parameters (PAR) of said vehicle.
    [13" id="c-fr-0013]
    13) The method of claim 12, wherein said intrinsic parameters (PAR) of said vehicle are obtained from a database, or are indicated by a user.
    [14" id="c-fr-0014]
    14) Method according to one of the preceding claims, in which the trajectory (POS) of said second vehicle (2) is determined by determining its position by means of an equation of the type:
    s Leader STAS + ^ Leader t T 1/2 tl /, eader ^ with ^ Leader the position of said second vehicle (2), s the position of said first vehicle (1), As the distance between said first vehicle (1) and said second vehicle (2), t time, v Leader the speed of said second vehicle (2) and a Leader the acceleration of said second vehicle (2).
    5
    [0015]
    15) Computer program product downloadable from a communication network and / or recorded on a computer-readable medium and / or executable by a processor or a server, comprising program code instructions for implementing the method according to the 'One of the preceding claims, when said program is executed on a computer or on a mobile phone.
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    同族专利:
    公开号 | 公开日
    EP3453583B1|2021-06-09|
    FR3070658B1|2019-08-30|
    CN109455179A|2019-03-12|
    EP3453583A1|2019-03-13|
    US20190071096A1|2019-03-07|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    EP2219092A1|2009-02-04|2010-08-18|Magneti Marelli S.p.A.|Method for controlling the speed of a vehicle|
    DE102011002275A1|2011-04-27|2012-10-31|Dr. Ing. H.C. F. Porsche Aktiengesellschaft|Method for prognosis of driving behavior of preceding vehicle of motor vehicle i.e. motor car, involves prognosticating driving behavior based on characteristic values and travel route data of travel route lying ahead of preceding vehicle|
    US8700256B2|2008-08-22|2014-04-15|Daimler Trucks North America Llc|Vehicle disturbance estimator and method|
    DE102009028742A1|2009-08-20|2011-02-24|Robert Bosch Gmbh|Method and control device for determining a movement information of an object|
    FR2994923B1|2012-08-31|2015-11-27|IFP Energies Nouvelles|METHOD FOR DETERMINING AN ENERGY INDICATOR OF A MOVEMENT OF A VEHICLE|
    US9934688B2|2015-07-31|2018-04-03|Ford Global Technologies, Llc|Vehicle trajectory determination|
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    WO2021115567A1|2019-12-10|2021-06-17|Zf Friedrichshafen Ag|Mpc-based trajectory tracking of a first vehicle using trajectory information on a second vehicle|
    CN112955359A|2021-03-31|2021-06-11|华为技术有限公司|Vehicle control method and device|
    法律状态:
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    2019-09-25| PLFP| Fee payment|Year of fee payment: 3 |
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    2021-09-27| PLFP| Fee payment|Year of fee payment: 5 |
    优先权:
    申请号 | 申请日 | 专利标题
    FR1758212A|FR3070658B1|2017-09-06|2017-09-06|METHOD FOR DETERMINING A SPEED TO BE REACHED FOR A FIRST VEHICLE PRECEDED BY A SECOND VEHICLE, ESPECIALLY FOR AN AUTONOMOUS VEHICLE|
    FR1758212|2017-09-06|FR1758212A| FR3070658B1|2017-09-06|2017-09-06|METHOD FOR DETERMINING A SPEED TO BE REACHED FOR A FIRST VEHICLE PRECEDED BY A SECOND VEHICLE, ESPECIALLY FOR AN AUTONOMOUS VEHICLE|
    EP18190977.1A| EP3453583B1|2017-09-06|2018-08-27|Method for determining a speed to be reached for a first vehicle preceded by a second vehicle, in particular for an autonomous vehicle|
    CN201811023758.1A| CN109455179A|2017-09-06|2018-09-04|Method for there is the first vehicle speed to be achieved of the second vehicle before determination|
    US16/123,239| US20190071096A1|2017-09-06|2018-09-06|Method for determining a speed to be reached for a first vehicle preceded by a second vehicle, in particular for an autonomous vehicle|
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