METHOD FOR DETERMINING AN OPTIMAL TRAJECTORY MINIMIZING THE ENERGY CONSUMPTION OF A MOTOR VEHICLE

Abstract

The invention relates to a method, implemented by a calculation system embedded in a motor vehicle or by a computer, for determining an optimal vehicle trajectory while minimizing the vehicle's energy consumption, the calculation system or the computer comprising: - a dynamics model module (M1) and energy consumption model module (M2) configured to define driving parameters, - an optimization module (M3) configured to define driving constraints as a function of the driving parameters, - a trajectory determination module (M4) by calculations according to a Pontryagin minimum principle, - at least one multi-segment adaptation module (M9-M11) configured to adapt the calculations to several successive segments, to associate each segment with a driving mode, and to categorize the sequence of driving modes into an acceleration sequence; a deceleration sequence or an economical driving sequence.Figure 1.

Description

Title of the invention: METHOD FOR DETERMINING AN OPTIMAL TRAJECTORY MINIMIZING THE ENERGY CONSUMPTION OF A MOTOR VEHICLE

[0001] The invention relates to a method for determining an optimal vehicle speed trajectory while minimizing the vehicle's energy consumption for the same travel time. The method is suitable for both electric vehicles and conventional internal combustion engine vehicles. The invention further relates to a corresponding calculation system and computer program.

[0002] Numerous tips and training courses on economical driving (generally called "eco-driving") are shared to limit vehicle energy consumption. However, these tips do not guarantee an actual reduction in consumption for a given route, considering a given travel time and initial speed trajectory.

[0003] A calculation method for guaranteeing an eco-driving trajectory, that is, a speed trajectory minimizing energy consumption for the same travel time as the initial speed trajectory, has been developed previously. It consists of using a dynamic programming algorithm to calculate the optimal speed trajectory by considering: - a cost function (energy expenditure): the vehicle's consumption; - the dynamics of the system: the speed of the vehicle; - the multiple constraints of the problem: travel time, regulated speeds and maximum accelerations of the vehicle.

[0004] To calculate this optimal speed trajectory, dynamic programming relies on calculating each optimal speed sub-trajectory. Indeed, recursively, for a given distance segment and at each initial speed, all possible speed variations are evaluated (according to the cost function), and the best variation is retained for each initial speed. The next distance segment then uses the previous results to construct the sequence of optimal trajectories.

[0005] Unfortunately, this methodology can only have a good level of optimality if there is a good discretization of the vehicle speed steps and distance traveled.

[0006] Furthermore, this method has the drawback of a significant computation time (several minutes), high computing power, and high memory size since All eventualities are calculated. Consequently, an embedded and real-time application of this algorithm is not feasible.

[0007] A known solution to this problem is detailed in patent document FR 3 124 147 A1. This document describes a computer-implemented calculation system for determining a trajectory while minimizing the energy consumption of a motor vehicle. The system comprises a dynamics and energy consumption modeling module configured to define driving parameters, an optimization module configured to define driving constraints based on these driving parameters, a multi-segment adaptation module configured to adapt the calculations to several successive segments where at least one driving parameter is substantially constant, and a trajectory determination module.More specifically, this module calculates an energy-efficient speed trajectory using a set of analytical equations that solve a simplified version of the eco-driving problem for vehicles, particularly electric and hybrid vehicles. These analytical solutions (in the form of speed profiles to be applied) are derived using Pontryagin's minimum principle, which minimizes a Hamiltonian function of the driving parameters. The solution described in this document relies on a specific expression of the eco-driving problem compatible with a fast and low-error solution using Pontryagin's minimum principle. Ultimately, this solution allows the calculation of an eco-driving trajectory to be integrated into a vehicle or a mobile application. The solution can thus be implemented in real time and allows this type of algorithm to be embedded in an automotive computer or a mobile phone.To achieve this, two problems are solved simultaneously: . - significantly reduce the computing power, processing time, and memory required to obtain an eco-driving trajectory; and - maintain an optimality close to the calculation by dynamic programming while respecting the end of travel time constraint while proposing a reduction in consumption compared to the original (non-optimized) cycle.

[0008] However, a drawback of the solution described in this patent document is that the multi-segment adaptation module suffers from a lack of precision and completeness in determining an optimal speed trajectory for each segment. Furthermore, the solution described in this patent document does not take into account the vehicle's coasting phases, as it assumes a constant transmission efficiency. This impacts the overall performance and precision of the solution and introduces suboptimality. "Coasting phase" refers to any phase during which the vehicle decelerates solely from the due to its inertia, without regenerative braking. Furthermore, the solution described in patent document FR 3 124 147 Al does not take into account the limiting constraints of the vehicle's acceleration, nor the adaptation of the final conditions of the calculated sub-trajectories when the different constraints are not compatible with each other.

[0009] To overcome the shortcomings of the prior art, the invention proposes a method, implemented by a computing system embedded in a motor vehicle or by a computer, for determining an optimal vehicle trajectory while minimizing the vehicle's energy consumption, the computing system or computer comprising: - a dynamics and energy consumption modeling module configured to define driving parameters, - an optimization module configured to define driving constraints based on driving parameters, - a trajectory determination module by calculations according to a Pontryagin minimum principle minimizing a so-called Hamiltonian function of said rolling parameters; - at least one multi-section adaptation module configured to adapt calculations to several successive sections where at least one driving parameter is substantially constant, to associate each section with one of the following driving modes: - maximum acceleration; - constant speed; - maximum deceleration; and to categorize the sequence of driving modes into a sequence of acceleration; a sequence of deceleration or a sequence of economical driving; The process includes the following steps, implemented for each section of the journey: - an initialization of a final position constraint sf of the vehicle, an initial velocity constraint vo of the vehicle, a final velocity constraint vf of the vehicle, a maximum velocity constraint vmax of the vehicle, and minimum and maximum acceleration limits { min,max} of the vehicle; - a selection of a sequence of driving modes from among the aforementioned sequences of driving modes, the acceleration sequence corresponding to a sequence for which the initial speed constraint vo is distinct from the final speed constraint vf and the maximum speed constraint vmax is equal to the final speed constraint vf, the deceleration sequence corresponding to a sequence for which the initial speed constraint vo is distinct from the speed constraint final vf and the maximum speed constraint vmax is equal to the initial speed constraint vo, the economical driving sequence corresponding to any sequence other than the acceleration sequence and the deceleration sequence; - a calculation, for the said selected sequence of driving modes, of a trajectory not subject to the constraints of speed and acceleration; - a verification that the maximum speed constraint vmax and / or the minimum and maximum acceleration limits u {mi^wx} are respected by the vehicle, the trajectory not subject to the speed and acceleration constraints calculated during the previous step being determined to be the optimal trajectory of the vehicle for said section if the maximum speed constraint vmax and / or the minimum and maximum acceleration limits “ {mwnax} are respected by the vehicle; - if the maximum speed constraint vmax and / or the minimum and maximum acceleration limits “ are not respected by the vehicle, a calculation, for said section selected chain of driving modes, of a trajectory subject to speed and acceleration constraints, the calculated trajectory being determined as the optimal trajectory of the vehicle for said section; the final optimal trajectory being formed by the concatenation of the optimal trajectories calculated for all segments of the journey.

[0010] In the context of the invention, the term "module" is understood as a set of hardware elements and program code instructions to perform a given action, in particular a calculation.

[0011] The method for determining an optimal trajectory for a motor vehicle according to the invention is more precise and comprehensive than prior art calculation methods (and therefore more efficient in terms of minimizing the vehicle's energy consumption). The method according to the invention notably takes into account the vehicle's coasting phases, which improves its accuracy. Furthermore, the method according to the invention allows the calculation of an eco-driving trajectory to be integrated into a vehicle's computer or into a mobile phone application, for example. The proposed invention also makes it possible to determine the vehicle's dynamics based on parameters accessible to a corresponding vehicle's computer, to obtain a theoretical optimization of the route, and to enable route determination with simplified calculations that limit processor processing time.The method according to the invention is finally suitable for both electric vehicles and conventional internal combustion engine vehicles.

[0012] According to one embodiment, the motor vehicle is a motor vehicle with an internal combustion engine, and the method further comprises an additional step which consists, if the maximum speed constraint vmax and / or the minimum and maximum acceleration limits {mwa*} are respected by the vehicle, in determining whether a value of The vehicle speed vgp(p) at which a gear change is necessary is reached. Then, if this speed value v^(p) is reached, a step is performed to divide the trajectory at this speed value vgp(p) and calculate the trajectory profile with the next gear engaged. The step verifying that the maximum speed constraint vmax and / or the minimum and maximum acceleration limits [minoux] are respected by the vehicle is repeated after this trajectory division and trajectory profile calculation step. This allows for consideration of the case where the motor vehicle is an internal combustion engine vehicle, such vehicles constituting the majority of the vehicle fleet currently in circulation.This additional step allows for a theoretical optimization of the trajectory profile for each segment of the journey, which is suitable for a motor vehicle with an internal combustion engine.

[0013] According to one variant, the step of calculating a trajectory subject to speed and acceleration constraints comprises the following phases: - a switching time initialization tseq(i) which defines the sequence of driving modes in the optimal trajectory, as a function of a fully constrained time sequence; - if a particular driving mode in the sequence is not present in the trajectory to be calculated, an assignment of a predefined value to the corresponding switching time; - a deletion, in the sequence of driving modes, of the or each driving mode which is not present in the trajectory to be calculated, and a deletion of the corresponding switching time tsec / i) whose value is equal to said predefined value; - for each driving mode remaining in the sequence of driving modes: - a generation of a time vector comprising a set of points corresponding to the points that will make up the trajectory to be calculated; - a use of said generated time vector to evaluate a set of analytical functions for said driving mode; - a recording of the resulting trajectory and a reset of the initial points for the next driving mode in the sequence of driving modes.

[0014] According to one embodiment, the calculation system or computer further comprises a module for calculating average speed over a horizon, taking into account information on speed limits, obstacles, and traffic as a function of distance, preferably with a margin on this speed. This allows for precise calculations of the journey parameters, in particular the journey time.

[0015] According to one variant, the computing system or computer further comprises a penalty calculation module (M7) impacting average speed according to the equation WtDc - £ (a + ^+^v2) + T (6) with V = Vref + € where, WtDc is the average kilometer consumption ^ref is the average speed of the original driving cycle (in m / s) e is a parameter to be calibrated in order to achieve the desired travel time (in m / s) y is a variable associated with the speed ratio of the vehicle when it is a vehicle with an internal combustion engine, or a coefficient indicating the efficiency of the vehicle's transmission when it is an electric vehicle üq = a + mg sin( / XvH is the rolling and slope resistance (in N) a is the rolling resistance at zero speed (in N); 9 is the slope of the road (in rad); ai is the vehicle's rolling resistance (in N / (m / s)) a2 is the vehicle's aerodynamic drag (in N / (m2 / s2)) P is the penalty prioritizing travel time over energy gain

[0016] This helps to limit errors in calculating journey parameters, in particular journey time.

[0017] According to one variant, the method further includes an initial step of initializing an average speed of the vehicle and initializing a value for the penalty fi prioritizing the duration of the journey over the energy gain.

[0018] According to one variant, the calculation system or computer further comprises a module for calculating optimal cruising speed according to the equation vopt,c = arg min (13) Or, m, T is the speed and torque of the electric machine when the vehicle is an electric vehicle, or the engine speed and torque when the vehicle is a thermal engine vehicle, associated with the speed V (in rad / s and N / m); V is the speed window used for the search for v°i*f (in m / s); T) is the map of the energy consumption of the electric machine when the vehicle is an electric vehicle, or of the fuel consumption of the engine when the vehicle is an internal combustion engine vehicle; is the scaling factor associating the time penalty with the optimal constant speed.

[0019] This makes it possible to compensate for the absence of the aerodynamic resistance term in the acceleration dynamics of the vehicle, which could lead to an optimal speed that would underestimate the energy gain of a lower speed.

[0020] The method can be implemented in a motor vehicle battery management system, when the motor vehicle is an electric vehicle.

[0021] The method can also be implemented to determine an optimal trajectory for a motor vehicle with an internal combustion engine, minimizing the vehicle's energy consumption.

[0022] Another object of the invention relates to a computer program product comprising program code instructions for the execution of the steps of a process according to the invention, when said program is running on a computer or on a computing system embedded in a motor vehicle.

[0023] The program product can be loaded into the memory of a motor vehicle battery management system, serving as a computer, when the motor vehicle is an electric vehicle.

[0024] The invention also relates to a motor vehicle comprising a computer program product according to the invention.

[0025] The invention will be further detailed by describing non-limiting embodiments, and based on the following accompanying figures in which: - [Fig. 1] schematically illustrates a method according to the invention; and - [Fig.2] schematically illustrates some particular steps of the method of [Fig.1].

[0026] The invention relates to an analytical solution to the eco-driving problem using Pontryagin's Minimum principle. This solution relies on a specific expression of the eco-driving problem compatible with a fast and low-error solution using Pontryagin's Minimum principle. Ultimately, this solution allows for the integration of an eco-driving trajectory calculation into a vehicle or mobile application.

[0027] More specifically, the invention proposes a method, implemented by a calculation system embedded in a motor vehicle or by a computer, for determining an optimal trajectory of the vehicle while minimizing the energy consumption of the vehicle.

[0028] The computing system or computer comprises: - a dynamics model module M1 and energy consumption module M2 configured to define driving parameters, in particular in a step S1 of defining driving parameters such as maximum and minimum accelerations, and maximum speed, and other parameters of this type; - an M3 optimization module configured to define driving constraints such as speed limits, obstacles, lights, stopping areas (or stops) depending on the distance to be covered, based on said driving parameters; - a trajectory determination module M4 by calculations according to a Pontryagin minimum principle minimizing a so-called Hamiltonian function of said driving parameters, with in particular a target travel time over a horizon; - at least one multi-section adaptation module M9-M11 configured to adapt calculations to several successive sections where at least one of said driving parameters is substantially constant, to associate each section with one of the following driving modes: - maximum acceleration; - constant speed; - maximum deceleration; and to categorize the sequence of driving modes into an acceleration sequence; a deceleration sequence or an economical driving sequence.

[0029] In order to obtain a calculation method that is compatible in terms of optimality and computation time, the analytical solution consists, according to the preferred variant, of mathematically describing the problem so that it is compatible with a fast solution using Pontryagin's minimum principle: - The models of vehicle dynamics and energy consumption are simplified while limiting the loss of accuracy compared to the models used in dynamic programming. The optimization method is Pontryagin's minimum principle. This principle minimizes a function, the Hamiltonian, which contains the cost (here, the vehicle's instantaneous fuel consumption), the weighted dynamics of speed and acceleration, and a penalty on travel time. Optimizing a segment is then faster since it consists of solving a problem at both ends (Two Points Boundary Value Problem). - In the preferred variant, each Hamiltonian is expressed in such a way as to solve a piecewise optimization problem while taking into account the final states of the previous piece as well as the initial states of the next piece. The assembly of these Hamiltonians then yields a linear system with variable time and constant piecewise dynamics.

[0030] The description of the invention may assume a flat road or a constant road gradient for each segment thereof. The impact of a variable road gradient will modify the expression of the Hamiltonian. Furthermore, the invention will address the fully constrained analytical solution in torque, acceleration, and velocity.

[0031] The proposed solution is embeddable in real time, which allows it to be applied to a vehicle with computing resources close to those already available.

[0032] Prior art solutions for reducing energy consumption (eco mode, eco-driving training) currently offered generally rely on lowering the average driving speed and therefore resulting in a delay compared to the initial travel time. The invention makes it possible to minimize energy consumption for a given average speed in order to guarantee a timely arrival for the user.

[0033] In particular, the vehicle dynamics model is defined according to Newton's second law: s(t)=v(t) (1) f(r) = ±(FM-Fr(ty) (2) Or s is the position of the vehicle (in m); v is the speed of the vehicle (in m / s); f is the time (in s); m is the total mass of the vehicle including the inertia of rotating parts (in kg); the force resisting the movement of the vehicle being: Fr(t) = a0 + aj v(t) + a2 2 (3) Or üq — â + mg sin(^y)) is the rolling and slope resistance (in N); ai is the rolling resistance (in N / (m / s)); S is the acceleration due to Earth's gravity (in m / s2); 0 is the slope of the road (in rad); is the aerodynamic resistance (in N / (m2 / s2)) the tensile force being: F,(,)=222 (4) Or Rt is the transmission speed ratio; T is the torque of the vehicle's electric machine when the latter is an electric vehicle, or the engine torque of the vehicle when the latter is a vehicle with an internal combustion engine (in Nm); j tire is the radius of the wheel (in m). The vehicle's speed can be deduced from the speed of the electric machine or the internal combustion engine (u' in rad / s): v(0 = (5)

[0034] A penalty P is used to influence travel time. This parameter has proven in the past to be complex to calibrate. The solution proposed here facilitates its calibration because it establishes the relationship between the impact of P on the average cycle speed and the average energy expenditure.

[0035] Thus, the calculation system preferably further comprises a penalty calculation module M7 having an impact on the average speed according to the equation WtDc - +6?2v2) + | (6) with 1' = ^ref + £ Or, WtDc is the average fuel consumption per kilometer. Vref is the average speed of the original driving cycle (in m / s). e is a parameter to be calibrated to achieve the desired travel time (in m / s). y is a variable associated with the vehicle's speed ratio when it is an internal combustion engine vehicle, or a coefficient indicating the efficiency of the vehicle's transmission when it is an electric vehicle. üq — â + mg sin(^(5')) is the rolling resistance and the slope resistance (in N) ai is the rolling resistance of the vehicle (in N / (m / s) a2 is the aerodynamic resistance of the vehicle (in N / (m2 / s2) / i is the penalty that prioritizes travel time over energy gain

[0036] Therefore, in the case where the average fuel consumption per kilometer is minimized, the minimum of WtDc allows us to deduce a law of P according to the average speed: dWtD, _ q ? g2v) (7) dv — T

[0037] Unlike dynamic programming, which allows the consumption term to be used directly in its algorithm, Pontryagin's minimum principle minimizes at each instant a Hamiltonian H that represents the instantaneous cost of L and the weighting of each dynamic of the problem. This is implemented by the determination module M4.

[0038] In particular, the determination module M4 is configured to minimize the so-called Hamiltonian function H, which is such that: x = H(t) x(t) (8) x = {5; v, 1, 2V} (9) M sit^Kta (10) Hb if you <t<th Ht = L . . Hk sitk_^t^tk U \Hk sir^tït^tf Or 2ç — - — 0 6 aces (12)

[0039] Preferably, the calculation system further includes an average speed calculation module M5 over a horizon taking into account information on speed limits, obstacles, and traffic as a function of distance, preferably with a margin on this speed. This is done in particular in a step S2.

[0040] We assume that knowledge of the horizon allows us to access speed limits, obstacles, and traffic as a function of distance. Combining these elements then allows us to define the speed limit as a function of distance and to deduce an average speed over the entire horizon, called Vref.

[0041] Reference Q1 relates to iterations, references RI and R2 relate respectively to "yes" and "no" answers to the questions corresponding to references Q1 and Q2. References S and E designate respectively a start and an end of method.

[0042] It is possible to add a margin to this average speed using a parameter e. This is done in particular in a step S3.

[0043] Next comes the calculation of the penalty P detailed above, in particular in a step S4.

[0044] Next comes the calculation of an optimal cruising speed V'W in particular in a step S5.

[0045] The absence of aerodynamic drag in the vehicle's acceleration dynamics can lead to an optimal speed that underestimates the energy savings from a lower speed. Furthermore, eco-driving trajectories resulting from dynamic programming tend to include a constant speed phase, below the maximum permitted speed, which would induce significant energy savings. For these reasons, the optimal cruising speed v°p^c can be defined according to minimizing energy expenditure per kilometer.

[0046] Thus, according to one aspect, the calculation system further comprises a module for calculating optimal cruising speed M8 according to the equation = ar e min Mx( &.T)z+P (13) Or, œ, T is the speed and torque of the electric machine when the vehicle is an electric vehicle, or the engine speed and torque when the vehicle is a thermal engine vehicle, associated with the speed V (in rad / s and N / m); V is the speed window used for the search (in m / s); T) is the map of the energy consumption of the electric machine when the vehicle is an electric vehicle, or of the fuel consumption of the engine when the vehicle is an internal combustion engine vehicle.

[0047] The interaction between the system of differential equations and the conditions of Multiple constraints must be combined to find the switching times that define the sequence of driving modes in the optimal trajectories. This is done using the matrix representation (27), (28), (32) described above, which gives a linear time-varying system. A solution to the linear time-varying Hamiltonian system can be found using the exponential matrix: x ( tf ) — eHK ( LA; )... ) eH“ ( ) x(ïq) (14) allowing for an analytically optimized speed profile where Vmax — vopt,c_ With this procedure, different sets of analytical solutions can be obtained for which the unknown variables Xs>0, Xv>0, tk, and tf are determined as a function of the driving mode sequence, t = [tk i,tk), where XSjO is the initial position co-state. After obtaining these driving mode equations, as well as those for s(t) and Xv(t) and the expressions for the unknown variables (initial co-state conditions, switching time, and final journey time), a complete trajectory can be calculated as a function of the specific driving mode sequence required. The final journey time is determined by evaluating the Hamiltonian function for a final time equal to zero: (15)

[0048] Next comes a division of the problem into several sections, in particular in a step S6.

[0049] In the case of an application on a driving cycle, it is proposed in the invention to first divide the optimization problem into several segments according to the distance where the maximum speed is constant.

[0050] Next, stops can be defined by a single point between two segments where the speed limit is zero. Finally, preferably, if a sequence of several speed limit segments involves acceleration or deceleration beyond the values ​​defined for the vehicle, then the intermediate segment is omitted.

[0051] The initial speed of a section corresponds to the final speed of the previous section.

[0052] The final speed defined for each segment corresponds to the limit speed of this section.

[0053] Next comes an association of sections with driving modes, in particular in a step S7.

[0054] Each section is associated with one of the following driving modes: - MA: Maximum Acceleration; - CS: Constant Speed; - MD: Maximum deceleration (Maximum Deceleration).

[0055] In certain specific driving models, additional driving modes may be added, such as: - a mode corresponding to a phase of vehicle acceleration; and / or - a mode corresponding to a vehicle deceleration phase; and / or - a mode corresponding to a coasting phase of the vehicle; and / or - a mode corresponding to a braking phase of the vehicle.

[0056] Next, all the segments are combined to calculate an analytical solution by deducing the speed profile, travel time, and fuel consumption, particularly in phase S8. Reference Q2 concerns determining whether or not the target travel time assumption has been met. If not, step S9 is initiated, which involves adjusting the value of the margin parameter €. Modules M9-M12, corresponding respectively to steps S6-S9, can be provided for implementing these steps. If the deduced travel time is greater than the desired travel time, then the value e can be increased. This will result in an increase in P and therefore = voptc

[0057] In more detail the phase S8, the process includes, during this phase S8, the steps S10 to S20 represented on the [Fig.2] and implemented for each section of the path.

[0058] Step S10 consists of an initialization of a final position constraint sf of the vehicle, an initial velocity constraint 'o of the vehicle, a final velocity constraint Fy of the vehicle, a maximum velocity constraint vmax of the vehicle, and minimum and maximum acceleration limits [mirumax | of the vehicle.

[0059] The next step S12 consists of selecting a sequence of driving modes from among the aforementioned sequences of driving modes, the sequence acceleration sequence corresponding to a sequence for which the initial speed constraint vo is distinct from the final speed constraint vf and the maximum speed constraint vnm is equal to the final speed constraint vf, deceleration sequence corresponding to a sequence for which the initial speed constraint vo is distinct from the final speed constraint and the maximum speed constraint vmax is equal to the initial speed constraint vo, economical driving sequence corresponding to any sequence other than the acceleration sequence and the deceleration sequence.

[0060] The next step S14 consists of a calculation, for the sequence of driving modes selected during step S12, of a trajectory not subject to the constraints of speed and acceleration.

[0061] The next step S16 consists of verifying that the maximum speed constraint vmax and / or the minimum and maximum acceleration limits w{minjnax} are respected by the vehicle. During this step S16, if the maximum speed constraint vmax and / or the minimum and maximum acceleration limits &{minjnax} are respected by the vehicle, the trajectory not subject to the speed and acceleration constraints calculated during the previous step S14 is determined to be the optimal trajectory of the vehicle for the current segment. Otherwise, phase S14 includes a subsequent step S20. During step S16, if the maximum speed constraint vmax and / or the minimum and maximum acceleration limits “{minjnax} are respected by the vehicle, a specific case exists if the motor vehicle is a motor vehicle with an internal combustion engine.In this case, the process further includes a step S17 following step S16, which consists of determining whether a vehicle speed value Vp(p) for which a gear change is necessary is reached. If this speed value Vp(p) is reached, a step S18 is performed to divide the trajectory at this speed value Vp(p) and to calculate the trajectory profile with the next gear engaged. The verification step S16 is then repeated after this step S18.

[0062] The next step S20 consists of calculating, for the sequence of driving modes selected during step S12, a trajectory subject to speed and acceleration constraints. The trajectory calculated during this step S20 is then determined to be the optimal trajectory of the vehicle for the current section.

[0063] Preferably, the calculation step S20 comprises the following phases: - an S201 initialization of switching time tse / î} Which define the sequence of driving modes in the optimal trajectory, according to a fully constrained time sequence; - if a particular driving mode in the sequence is not present in the trajectory to be calculated, an assignment S202 of a predefined value to the corresponding switching time tse(^ï); - a deletion S203, in the sequence of driving modes, of the or each driving mode which is not present in the trajectory to be calculated, and a deletion S204 of the corresponding switching time whose value is equal to the predefined value assigned during step S202; - for each driving mode remaining in the sequence of driving modes: - an S205 generation of a time vector comprising a set of points corresponding to the points that will make up the trajectory to be calculated; - an S206 use of the time vector generated during phase S205 to evaluate a set of analytical functions for the current driving mode; - an S207 recording of the resulting trajectory and an S208 reset of the initial points for the next driving mode in the sequence of driving modes.

[0064] At the end of phase S8 of the process, the final optimal trajectory is formed by the concatenation of the optimal trajectories calculated for all the segments of the path.

[0065] In one variant, depending on the information available on the horizon, the following choice is made: - If the algorithm does not have information on the end of the driving cycle or on a variation of the speed limit, and the current speed is less than or equal to the speed limit, then a sequence of category "Accelerations" is chosen; - If the vehicle's speed is positive and equal to the limit speed, and the algorithm has information about the end of the cycle, then we choose a sequence from the "Decelerations" category; - If the vehicle is stopped and the algorithm has information on the end of the driving cycle then a sequence from the "Eco-driving" category (also called eco-driving) is chosen;

[0066] - If the algorithm does not have information on the end of the driving cycle but has information on a reduction of speed limits over a horizon for which the current speed is less than or equal to the current speed limit, then we choose a sequence from the category "Eco-driving" (also called eco-driving).

[0067] By default, the selected sequences are the longest. However, it may be advantageous to define a method for selecting a shorter driving mode sequence in order to limit the load on the computer.

[0068] Each sequence has its own expression of the final time, input constraints and driving mode change times.

[0069] In one variant, depends on the power of the battery with auxiliaries included when the vehicle is an electric vehicle, or on a consumption model linking energy consumption to a cruising speed when the vehicle is a vehicle with an internal combustion engine.

[0070] In one variant, a minimum speed is added to the calculations of the optimization module.

[0071] Another object of the invention relates to a computer program product comprising program code instructions for the execution of the steps of a process as described above, when said program is running on a computer or on a computing system embedded in a motor vehicle.

[0072] The program can, for example, be loaded into the memory of a battery management system of a motor vehicle, serving as a computer, when the vehicle is an electric vehicle.

[0073] The invention also relates to a motor vehicle comprising a computer program product as described above.

Claims

Claims

1. Method, implemented by a calculation system embedded in a motor vehicle or by a computer, for determining an optimal trajectory of the vehicle by minimizing the energy consumption of the vehicle, the calculation system or the computer comprising: - a module of dynamic models (Ml) and energy consumption (M2) configured to define driving parameters, - an optimization module (M3) configured to define driving constraints as a function of the driving parameters, - a trajectory determination module (M4) by calculations according to a Pontryagin minimum principle minimizing a so-called Hamiltonian function of said driving parameters; - at least one multi-section adaptation module (M9-M11) configured to adapt the calculations to several successive sections where at least one driving parameter is substantially constant, to associate each section with one of the following driving modes: - maximum acceleration; - constant speed; - maximum deceleration; and to categorize the sequence of driving modes into an acceleration sequence; a deceleration sequence or an economical driving sequence; the method being characterized in that it comprises the following steps, implemented for each section of the journey: - an initialization (S 10) of a final position constraint sf of the vehicle, an initial speed constraint vo of the vehicle, a final speed constraint vf of the vehicle, a maximum speed constraint vmax of the vehicle, and minimum and maximum acceleration limits a [ mitunax} of the vehicle; - a selection (S 12) of a sequence of driving modes from among the aforementioned sequences of driving modes, the acceleration sequence corresponding to a sequence for which the initial speed constraint vo is distinct from the final speed constraint Vf and the maximum speed constraint vmax is equal to the final speed constraint Vf, the deceleration sequence corresponding to a sequence for which the initial speed constraint vo is distinct from the final speed constraint vf and the

2. maximum speed constraint vmax is equal to the initial speed constraint vo, the economical driving sequence corresponding to any sequence other than the acceleration sequence and the deceleration sequence; - a calculation (S 14), for said selected sequence of driving modes, of a trajectory not subject to speed and acceleration constraints; - a verification (S 16) that the maximum speed constraint vmax and / or the minimum and maximum acceleration limits w {minjnax} are respected by the vehicle, the trajectory not subject to the speed and acceleration constraints calculated during the previous step being determined as being the optimal trajectory of the vehicle for said section if the maximum speed constraint vmax and / or the minimum and maximum acceleration limits {minjmix} are respected by the vehicle; - if the maximum speed constraint vmax and / or the minimum and maximum acceleration limits {nùnjnax} are not respected by the vehicle, a calculation (S20), for said selected sequence of driving modes, of a trajectory subject to speed and acceleration constraints, the calculated trajectory being determined as being the optimal trajectory of the vehicle for said section; the final optimal trajectory being formed from the concatenation of the optimal trajectories calculated for all the sections of the journey.Method according to claim 1, in which the motor vehicle is a motor vehicle with a thermal engine, and the method further comprises a following step (S 17) which consists, if the maximum speed constraint vmax and / or the minimum and maximum acceleration limits w {mîivnax} are respected by the vehicle, in determining whether a vehicle speed value p} for which a gear change is necessary is reached, then, if this speed value v?p(p) is reached, a step (S 18) of dividing the trajectory at this speed value p) and calculating the trajectory profile with the next gear engaged, the step (S 16) of verifying that the maximum speed constraint vmax and / or the minimum and maximum acceleration limits w {nmmx] are respected by the vehicle being looped back at the end of this step (S 18) of dividing the trajectory and calculating the trajectory profile.

3. Method according to claim 1 or 2, in which the step (S20) of calculating a trajectory subject to the speed and acceleration constraints comprises the following phases: - an initialization (S201) of switching times which define the sequence of driving modes in the optimal trajectory, according to a fully constrained time sequence; - if a particular driving mode in the sequence is not present in the trajectory to be calculated, an assignment (S202) of a predefined value to the corresponding switching time tset / l); - a deletion (S203), in the sequence of driving modes, of the or each driving mode which is not present in the trajectory to be calculated, and a deletion (S204) of the corresponding switching time whose value is equal to said predefined value;- for each driving mode remaining in the sequence of driving modes: - a generation (S205) of a time vector comprising a set of points corresponding to the points which will compose the trajectory to be calculated; - a use (S206) of said generated time vector to evaluate a set of analytical functions for said driving mode; - a recording (S207) of the resulting trajectory and a reinitialization (S208) of the initial points for the next driving mode in the sequence of driving modes.;

4. Method according to any one of claims 1 to 3, in which the calculation system or the computer further comprises an average speed calculation module (M5) over a horizon taking into account information on speed limits, obstacles, traffic as a function of distance, preferably with a margin on this speed.

5. Method according to any one of claims 1 to 4, in which the calculation system or the computer further comprises a penalty calculation module (M7) having an impact on the average speed according to the equation WtDc- j ^ + 0^ + ^2^ + | with = + £ where, WtDc is the average kilometer consumption Vref is the average speed of the original driving cycle (in m / s) e is a parameter to be calibrated in order to achieve the desired travel time (in m / s) y is a variable associated with the vehicle's speed ratio when the latter is a vehicle with a thermal engine, or a coefficient indicating the efficiency of the vehicle's transmission when the latter is an electric vehicle ûq — â + mg sin(^(4y)) is the rolling and slope resistance (in N) a is the rolling resistance at zero speed (in N); 0 is the road slope (in rad); ai is the rolling resistance of the vehicle (in N / (m / s) a2 is the aerodynamic resistance of the vehicle (in N / (m2 / s2) fl is the penalty prioritizing the travel time over the energy gain

6. The method of claim 5, wherein the method further comprises an initial step of initializing an average speed of the vehicle and initializing a value for the penalty [1 prioritizing the duration of the journey over the energy gain.

7. Method according to any one of claims 1 to 6, in which the calculation system or the computer further comprises an optimal cruising speed calculation module (M8) according to the equation . \ (13) vopt.c = arg min kv P \ / where, îd, T is the speed and torque of the electric machine when the vehicle is an electric vehicle, or the speed and torque of the engine when the vehicle is a vehicle with a thermal engine, associated with the speed V (in rad / s and N / m); V is the speed window used for the search for v°pt* (in m / s); T) is the map of the energy consumption of the electric machine when the vehicle is an electric vehicle, or of the fuel consumption of the engine when the vehicle is a vehicle with a thermal engine; z is the scale factor associating the time penalty with the optimal constant speed.

8. A computer program product comprising program code instructions for carrying out the steps of a method according to any one of claims 1 to 7, when said program operates on a computer or on a computing system embedded in a motor vehicle.

9. A motor vehicle comprising a computer program product according to claim 8.

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