Method for controlling the actuation of a braking system employing predictive control techniques and related braking system

Abstract

There is described a method for controlling the actuation of an electronic or electro-mechanical or electro-hydraulic braking system of a vehicle employing predictive control techniques and performed by means of a plurality of calculation steps carried out by electronic processing, wherein each calculation step provides an actuation system of the braking system with a respective actuation command. The method first includes providing an actuation system model which represents states of the actuation system. Such states comprise current and at least one of position or speed of the actuation system. The aforesaid model is characterized by parameters indicative of the electrical and mechanical and / or dynamic properties of the actuation system. The method further comprises, for each of the calculation steps, the following actions: - measuring and / or estimating a value for each of the states of the actuation system at an instant associated with the aforesaid calculation step; and measuring and / or estimating, at the same instant associated with the calculation step, a value for at least one of the following control quantities: braking system clamping force and / or braking system clamping pressure and / or braking system fluid pressure and / or braking torque; - determining the aforesaid parameters indicative of electrical and mechanical and / or dynamic properties of the actuation system based on the aforesaid measured and / or estimated states, on one or more of said measured or estimated control quantities, and on an actuation command determined and supplied to the actuation system at the previous calculation step; - based on the states and control quantities of the actuation system determined in the calculation step, predicting a plurality of future values for each of the states and for the aforesaid control quantities of the actuation system, the future values referring to values assumed by the aforesaid states and control quantities of the actuation system at a respective plurality of future instants associated with respective calculation steps within a predetermined prediction horizon; - determining a reference trajectory of the aforesaid control quantities, comprising predicted values assumed by the control quantities at each of the future instants of the prediction horizon, based on information representative of a request for braking force and based on information indicative of dynamic and / or thermal parameters and / or of a configuration of the braking system and / or of the wheel on which of the braking system acts or of the respective tire and / or of the friction conditions between tire and road; - computing a plurality of actuation command values referring to a respective plurality of future instants associated with respective calculation steps within a predetermined control horizon, based on the predicted value of the aforesaid at least one control quantity and reference trajectory of the aforesaid at least one control quantity; - selecting the first value of the aforesaid plurality of actuation command values, and providing the actuation system with an actuation command having such a first selected actuation value. A braking system controlled by the aforesaid control system is further described.

Description

[0001] "Method for controlling the actuation of a braking system employing predictive control techniques and related braking system"

[0002] DESCRIPTION

[0003] TECHNOLOGICAL BACKGROUND OF THE INVENTION

[0004] Field of application.

[0005] The present invention relates to a method for controlling the actuation of an electronic or electro-mechanical or electro-hydraulic braking system by employing predictive control techniques performed through a plurality of calculation steps performed by means of electronic processing, wherein each calculation step provides an actuation system of the braking system with a respective actuation command.

[0006] The present invention also relates to a braking system to which the aforesaid control method is applied, or which is controlled by such a control method.

[0007] Description of the prior art.

[0008] In the field of vehicle braking systems, the problem of the control of a force and / or pressure reference (whether a request from the driver or a request from other on-board electronic system) by electro-actuated braking systems (whether electro-mechanical or electro-hydraulic) is currently commonly addressed by implementing, in the electronic control unit (ECU), control laws derived from the PID (Proportional Integrative Derivative) theory.

[0009] In the PID-type control scheme, the processing of the error signal between the clamping force or hydraulic pressure reference signal in the caliper and its measurement (by means of sensors) or estimation (by means of estimation algorithms) results in a command action (control law output), the value of which is the linear combination, or sum, of the Proportional, Integrative, Derivative contributions.

[0010] Such a known solution is shown, in simplified form, in the diagram in figure 1.

[0011] A known evolution of the PID control law is described in international patent application WO 2018 / 122741 A1 , to the same Applicant.

[0012] Such a solution (shown in figure 2) introduces and employs a variability of the coefficients Kp, Ki, Kd which govern the control law according to non-linear laws, which consider the operating conditions (ECU supply battery voltage value, operating temperature, etc.) and particular indices related to the dynamic evolution of the force request (e.g., amplitude and derivative of the error signal processed by the ECU).

[0013] These types of evolutions and improvements are mainly aimed at modifying the following aspects:

[0014] - control action responsiveness in particular situations (e.g., panic braking event or application of braking force with stationary vehicle);

[0015] - braking action robustness upon varying the operating conditions to achieve better dynamic performance (stopping distances);

[0016] - driving comfort in the full spectrum of maneuvers in vehicle use cases.

[0017] The known technical solutions, and in particular the solutions based on PID-type control techniques, have the following features and drawbacks: a) the control law is based on the reaction of the algorithm to changes in force request (reference), and the behavior of the system (force measurement or estimation) cannot predict the evolutions of the request (reference) and response (measurement) of the system, and thus cannot achieve optimal performance and robustness; b) the application calibration process to achieve the desired performance and robustness requires considerable experimental effort in terms of both man hours (calibration personnel) and bench hours (actuator test benches and climate cells).

[0018] Based on the above discussion, the need is apparent to devise improved methods for controlling a braking system, which provide improved performance and robustness and in particular overcome and solve the limitations and drawbacks mentioned above at points a) and b).

[0019] Such needs are not fully met by the prior art.

[0020] SUMMARY OF THE INVENTION

[0021] It is the object of the present invention to provide a method for controlling the actuation of an electronic or electro-mechanical or electro-hydraulic braking system of a vehicle, such as to allow obviating at least partially the drawbacks complained of above with reference to the prior art and responding to the aforesaid needs particularly felt in the technical field considered.

[0022] Such an object is achieved by a method according to claim 1.

[0023] Further embodiments of such a method are defined in claims 2-21.

[0024] It is a further object of the invention to provide an electronic or electro-mechanical or electro-hydraulic braking system capable of performing the aforesaid method. Such an object is achieved by a method according to claim 22.

[0025] Further embodiments of the braking system are defined in claims 23-24.

[0026] BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Further features and advantages of the method and system according to the invention will be apparent from the following description of preferred embodiments, given by way of non-limiting indication, with reference to the accompanying drawings, in which:

[0028] - figure 1 is a simplified block diagram which shows a PID-type control technique according to the prior art;

[0029] - figure 2 is a simplified block diagram which shows an evolution, also known, of the PID-type control technique, employing a "gain scheduler" block;

[0030] - figure 3 is a diagram which shows a control technique with predictive control model, MPC, employed in the method according to the present invention;

[0031] - figure 4 is a block diagram of a control architecture for a braking system, according to an embodiment of the method of the invention;

[0032] - figure 5 shows a functional “actuation system model” block used in an embodiment of the method according to the invention;

[0033] - figure 6 shows a functional “reference trajectory generator” block used in an embodiment of the method according to the invention;

[0034] - figure 7 shows a functional “optimizer and cost function” block used in an embodiment of the method according to the invention;

[0035] - figure 8 shows a functional “adaptation function” block used in an embodiment of the method according to the invention;

[0036] - figure 9 shows a functional “advanced diagnosis and predictive maintenance” block used in an embodiment of the method according to the invention;

[0037] - figure 10 shows a functional “state estimator” block used in an embodiment of the method according to the invention;

[0038] - figure 11 shows a functional braking “force / pressure / torque estimator” block used in an embodiment of the method according to the invention;

[0039] - figure 12 shows a block diagram which shows the operations performed by an embodiment of the method according to the invention;

[0040] - figures 13-15 diagrammatically show respective architectures of three braking systems according to the invention, i.e., three vehicle braking systems to which the control method according to the invention can be applied;

[0041] - figures 16 and 17 are block diagrams of respective detailed control architectures for a braking system, according to two respective embodiments of the method of the invention.

[0042] DETAILED DESCRIPTION

[0043] Referring to figures 3-17, a method for controlling the actuation of an electronic or electro-mechanical or electro-hydraulic braking system of a vehicle is described.

[0044] The method employs predictive control techniques and is performed through a plurality of calculation steps performed by means of electronic processing, where each calculation step provides an actuation system of the braking system with a respective actuation command.

[0045] The method first includes providing an actuation system model which represents states of the actuation system. Such states comprise electric current and at least one of position and speed of the actuation system; each state of the actuation system, on the whole, is thus characterized by a respective value of the actuation system current and by respective values of position and / or speed of the actuation system.

[0046] The aforesaid model is characterized by parameters indicative of the electrical and mechanical and / or dynamic properties of the actuation system.

[0047] The method further comprises, for each of the aforesaid calculation steps, the following actions:

[0048] - measuring and / or estimating a value for each of the states of the actuation system (i.e. , current and also position and / or speed) at an instant associated with the aforesaid calculation step;

[0049] - measuring and / or estimating, at the same aforesaid instant associated with the calculation step, a value for at least one of the following control quantities: braking system clamping force and / or braking system clamping pressure and / or braking system fluid pressure and / or braking torque;

[0050] - determining the aforesaid parameters indicative of electrical and mechanical and / or dynamic properties of the actuation system based on the aforesaid measured and / or estimated states, and based on one or more of the aforesaid measured or estimated control quantities, and based on an actuation command determined and supplied to the actuation system at the previous calculation step;

[0051] - based on the states and control quantities of the actuation system determined in the calculation step, predicting a plurality (n) of future values for each of the aforesaid states and for at least one of the aforesaid control quantities of the actuation system, the future values referring to values assumed by the aforesaid states and control quantities of the actuation system at a respective plurality (n) of future instants associated with respective calculation steps within a predetermined prediction horizon;

[0052] - determining a reference trajectory of at least one of the aforesaid control quantities, comprising predicted values assumed by the at least one control quantity at each of the plurality (n) of future instants of the prediction horizon, based on information representative of a request for braking force and based on information indicative of dynamic and / or thermal parameters and / or of a configuration of the braking system and / or of the wheel on which the braking system acts or the respective tire and / or of the friction conditions between tire and road; - computing a plurality (m) of actuation command values referring to a respective plurality (m) of future instants associated with respective calculation steps within a predetermined control horizon; such a calculation action is performed at least based on the predicted value of the aforesaid at least one control quantity and reference trajectory of the aforesaid at least one control quantity;

[0053] - selecting the first value of the aforesaid plurality of actuation command values, and providing the actuation system with an actuation command having the aforesaid first selected actuation value.

[0054] As disclosed above, the aforesaid method is used to control an actuation system of an electronic or electro-mechanical or electro-hydraulic braking system of a vehicle.

[0055] The term "electronic braking system" here refers to a braking system provided with an actuation system and an electronic unit (i.e. , electronic control unit).

[0056] The term "electro-mechanical or electro-hydraulic braking system" here refers to a braking system provided with an actuation system but without an electronic unit or electronic control unit.

[0057] The actuation system can be electro-actuated in different manners, e.g., with electro-mechanical or electro-hydraulic actuation.

[0058] The present method applies to all the above-mentioned different types of braking systems.

[0059] According to an embodiment of the method, the aforesaid computing action is performed by optimizing and / or minimizing a predetermined cost function based on information comprising: constraints to which the cost function must be subjected, duration of the prediction horizon, duration of the control horizon, predicted value of the aforesaid at least one control quantity, and reference trajectory of the aforesaid at least one control quantity.

[0060] According to an embodiment of the method, the aforesaid states of the actuation system comprise an electric current (also simply referred to as "current" in the preceding part and in the remainder of this description) which supplies or flows through the actuation system (or through a motor of the actuation system), a position of the actuation system (i.e., an operating position of the actuation system motor), and a speed of the actuation system (i.e., an operating speed of the actuation system motor).

[0061] According to an embodiment, the method is iterative, and the aforesaid determination, prediction and computation actions comprise updating the actuation system model, the prediction values, the reference trajectory, and the plurality m of actuation command values at each calculation step. According to different specific implementation options, the method employs any subset or all the control quantities mentioned above, i.e., clamping force of the braking system, clamping pressure of the braking system, braking system fluid pressure, braking torque. In particular, the method employs any subset or all of the control quantities mentioned above in the aforesaid actions of measuring and / or estimating at least one control quantity, determining parameters indicative of electrical and mechanical and / or dynamic properties of the actuation system, predicting a plurality of future values for each of the aforesaid control quantities of the actuation system, determining a reference trajectory for each of the aforesaid control quantities, computing a plurality of future values of actuation command, based on each of the aforesaid control quantities.

[0062] According to an embodiment of the method (shown in detail in figure 16), the states of the system are estimated and the control quantities are measured.

[0063] According to another embodiment of the method (shown in detail in figure 17), the states of the system are measured and the control quantities are estimated.

[0064] According to an embodiment of the method, the actions described above are performed as follows:

[0065] - the action of measuring a value for each of the states of the actuation system or measuring a value for at least one of the control quantities is performed by respective sensors;

[0066] - the action of estimating a value for each of the states of the actuation system is performed by means of a "system state estimator” software module (also referred to as a “state estimator” for brevity in this description);

[0067] - the action of estimating a value for at least one of the control quantities is performed by means of a "control quantity estimator" software module;

[0068] - the action of determining parameters indicative of electrical and mechanical and / or dynamic properties of the actuation system is performed by means of an "adaptation function” software module;

[0069] - the action of predicting a plurality n of future values for each of the states and at least one of the control quantities of the actuation system is performed by a software module which implements the aforesaid “actuation system model”;

[0070] - the action of determining a reference trajectory is performed by a "reference trajectory generator" software module;

[0071] - the action of calculating a plurality of actuation command values and selecting and providing an actuation command is performed by an "optimizer" software module.

[0072] Different implementation options of the aforesaid embodiment are shown, with different levels of detail, in figures 4, 16 and 17.

[0073] According to different possible implementation options of method, the aforesaid parameters indicative of electrical and mechanical and / or dynamic properties of the actuation system comprise any subset or all of the following parameters:

[0074] - equivalent electrical resistance (Rm) of the actuation system, and / or

[0075] - torque constant (Km) of an electric motor of the actuation system or associated with the actuation system, and / or

[0076] - mechanical efficiency (pm) of a transmission system of the vehicle, and / or

[0077] - shape factor (zeal) of the hysteresis of a caliper of the braking system.

[0078] According to different possible implementation options of the method, the aforesaid information indicative of dynamic and / or thermal parameters and / or of a configuration of the braking system and / or of the wheel on which the braking system acts or of the respective tire and / or of friction conditions between tire and road comprises any subset or all the following information,

[0079] - longitudinal slip of the wheel, and / or

[0080] - vehicle dynamics signals comprising yaw rate and / or distribution angle and / or lateral acceleration and / or longitudinal acceleration, and / or

[0081] - tire inflation pressure, and / or tire temperature, and / or

[0082] - vertical force acting at the contact point between tire and road, and / or tire-road friction coefficient.

[0083] According to an embodiment of the method, the aforesaid information comprising constraints to which cost function and durations of the prediction horizon and of the control horizon must be subjected comprises setting or calibration parameters predefined in a control unit of the braking system or comprises signals from other functional modules of the control unit.

[0084] According to an implementation option of the method, the aforesaid actuation command comprises a supply voltage or current of an electric motor included in the actuation system of the braking system.

[0085] With reference to figures 5-11 , further details are provided below regarding the aforesaid modules which implement the method steps, according to respective implementation examples.

[0086] According to an implementation option, shown in figure 5, the input signals to the actuation system model are:

[0087] - measured or estimated clamping pressure and / or force;

[0088] - command to the actuation system or motor; - torque constant of a motor of the actuation system or associated with the actuation system (“motor constant” in figure 5);

[0089] - electrical resistance of the aforesaid motor;

[0090] - efficiency of the actuation system;

[0091] - shape factor of the hysteresis function of a caliper of the braking system;

[0092] - prediction horizon.

[0093] The output signals from the actuation model are:

[0094] - predicted clamping pressure and / or force and / or torque;

[0095] - predicted speed of the actuation system and / or the respective motor;

[0096] - predicted position of the actuation system and / or the respective motor;

[0097] - predicted current of the motor associated with the actuation system.

[0098] According to an implementation option of the method, the actuation system model implements a linear time-invariant model, where the outputs and states of the system are determined by a linear combination of the time variations / derivatives of the states and by the value of the input, and the parameters forming the equations are constant over time.

[0099] Such a linear time-invariant model can be described by the following equations: x(t) — Ax(i) 4- Bu(i) y(t) ™ Cx(i) + Du(i)

[0100] According to another implementation option of the method, the actuation system model implements a linear time-variant model, where the outputs and states of the system are determined by a linear combination of the time variations / derivatives of the states and by the value of the input, and the parameters forming the equations are not constant over time.

[0101] Such a linear time-variant model can be described by the following equations:

[0102] According to another implementation option of the method, the actuation system model implements a non-linear time-variant model, where the outputs and states of the system are determined by a non-linear combination of the time variations / derivatives of the states and by the value of the input, and the parameters forming the equations are not constant over time.

[0103] Such a non-linear time-variant model can be described by the following equations:

[0104] In the equations above: x(t) is a state vector, which represents the states of the system; y(t) is an output vector, which represents the outputs of the system; u(t) is an input or control vector, which represents the inputs or control commands of the system;

[0105] A, B, C, D, A(t), B(t), C(t), D(t), which correlate the aforesaid vectors, are thus matrices.

[0106] According to an implementation option, shown in figure 6, the input signals to the reference trajectory generator are:

[0107] - force (or clamping pressure or torque) request from a braking distribution module;

[0108] - longitudinal slip of a wheel with which the braking system is associated;

[0109] - vehicle dynamics signals comprising yaw rate and / or distribution angle and / or lateral / longitudinal acceleration of the vehicle;

[0110] - air pressure inside a tire of said wheel and temperature of such a tire;

[0111] - vertical force acting at the tire-road contact point;

[0112] - road-tire friction coefficient.

[0113] According to an implementation option, shown in figure 7, the input signals to the “optimizer and cost function” block are: a prediction horizon value, a control horizon value, the predicted clamping force, the clamping force trajectory, and also one or more constraints for optimization.

[0114] In an implementation example of the method, the cost function depends on the measured values Y of the quantity to be optimized, on the reference trajectory Rs in the prediction horizon, on the command values II, on a weight matrix R of the command action, and on the prediction horizon Np.

[0115] Further example details of the cost function will be described below.

[0116] According to an implementation option, shown in figure 8, the input signals to the adaptation function are: the estimated or measured value of clamping force, the estimated or measured value of current, the estimated or measured value of position, the estimated or measured value of speed, the command to the motor.

[0117] According to an implementation option, shown in figure 10, the input signals to the state estimator are: the previous measurement of clamping force, the predicted clamping force, the previous command to the motor, the future command to the motor.

[0118] According to an implementation option, shown in figure 11 , the input signals to the control quantity estimator (i.e., force / pressure / torque estimator) are: past estimation of the clamping force and / or pressure and / or torque, previous command to the motor, future command to the motor, current measurement, position measurement, speed measurement.

[0119] According to an embodiment, the method comprises the further action of processing the aforesaid parameters indicative of electrical and mechanical and / or dynamic properties of the actuation system, or actuation system model parameters, to obtain predictive diagnostic and / or predictive maintenance information of the actuation system.

[0120] According to an implementation option of such an embodiment, the aforesaid processing action comprises comparing said parameters with reference values which define the health of the actuation system.

[0121] According to an implementation option of such an embodiment, the aforesaid predictive diagnostic and / or predictive maintenance information of the actuation system is transmitted to a remote data management system, for example, in the cloud.

[0122] According to an implementation example, the aforesaid functions are performed by an "advanced diagnosis and predictive maintenance" software module as shown in figure 9, which has as inputs the motor resistance, a motor constant, the actuator efficiency, the hysteresis shape factor, and generates as output an information on the health of the actuator or actuation system.

[0123] With reference to figures 13-15, an electronic or electro-mechanical or electro- hydraulic braking system included in the invention is described below. Such a braking system comprises processing means configured to perform a control method according to any of the previously described embodiments.

[0124] According to an implementation option, such processing means comprise electronic processing means and / or processors or microprocessors, which are made or included, for example, in an electronic unit or an electronic control unit of the vehicle and / or braking system. According to an embodiment, the braking system comprises at least one electro- hydraulic or electro-mechanical actuation system.

[0125] According to an embodiment, the braking system comprises a braking system of the Brake-by-Wire, BbW, type adapted to be employed in a vehicle with a central electronic control unit ECU.

[0126] According to an embodiment, the braking system comprises a braking system of the Brake-by-Wire, BbW, type adapted to be employed in a vehicle with a central electronic control unit ECU and two electronic control units of the braking system.

[0127] According to an embodiment, the braking system comprises a braking system of the Brake-by-Wire, BbW, type adapted to be employed in a vehicle with a central electronic control unit (ECU) and a single electronic control unit of the braking system.

[0128] The embodiments disclosed above also show examples of braking systems to which the control method of the present invention can be applied.

[0129] Further details of the control method and braking system of the invention, according to different embodiments, will be given below, by way of mere non-limiting example, referring again to figures 3-17.

[0130] First of all, for the sake of description clarity, some general concepts of the control techniques using predictive control model, MPC, known per se in general terms, are shown in figure 3.

[0131] The predictive control model is defined, in the technical field considered here, as an optimal control based on the model of the system to be controlled.

[0132] It is the purpose of the control MPC to minimize a cost function by respecting possible constraints related to, for example, actuation dynamics.

[0133] At each step of execution, the best command to the system to be controlled, which minimizes the cost function over a specific time horizon, is calculated.

[0134] Figure 3 shows the time patterns, in a discrete series of instants preceding and following a present instant k, of a reference trajectory r, a control variable y, and a control action u. With reference to the abscissa axis, a control horizon (i.e. , a period of time which elapses between the instants “k + Ni” and “k + Nu") and a prediction horizon (i.e., a period of time between instants “k” and “k + N ) are also shown.

[0135] The following additional example information is provided with reference to the functional blocks shown in figures 4, 5-11 and 16-17 (previously shown as "software modules").

[0136] A. Actuation system model

[0137] Such a functional block represents the model of the actuation system implemented, for example, in the processing means of an electronic unit of the vehicle, and has the purpose of predicting the behavior of the system in the prediction horizon; it consists of the numerical representation of the system dynamics.

[0138] As previously described, in different embodiments of the control method, three different types of actuation models are provided: linear time-invariant model, linear timevariant model, non-linear time-variant model.

[0139] The input and output signals of the model, according to an embodiment, have already been described above, with reference to figure 5.

[0140] The predicted value of clamping force and / or pressure is used as the input of the cost function optimization functional unit (described in paragraph C below)

[0141] B. Reference trajectory generator

[0142] This block (shown in figure 6) is the functional unit of the control method which generates the trajectory of the reference signal of clamping force or pressure or braking torque useful in the prediction horizon.

[0143] The trajectory is represented by "n" reference force / pressure values, where "n" is the duration (amount of time instants) of the prediction horizon over which the calculation / optimization of the control action takes place.

[0144] The vector of force and / or pressure reference data (defined as a trajectory) is calculated by an electronic processing and calculation unit (e.g., included in an electronic control unit, ECU) as a function of a set of internal signals which can be obtained from measurements or estimations of quantities such as, for example (as discussed above): force request from braking distribution module; longitudinal slip of the wheel; vehicle dynamics signals (such as yaw rate, distribution angle, lateral / longitudinal acceleration); air pressure inside the tire; tire temperature; vertical force acting at the tire-road contact point; tire-road friction coefficient.

[0145] The internal signals listed above are the inputs of the functional reference generation block, the only output of which is the trajectory of the reference of clamping force or fluid pressure of the braking system or braking torque consisting of the number of samples equal to the number of samples of the prediction horizon in which the functional optimization block and cost function operates.

[0146] The trajectory output signal of the force reference is used as input by the functional optimization and cost function unit ("optimizer") described in paragraph C below.

[0147] C. Optimizer (and cost function)

[0148] The functional "optimization and cost function" block (also referred to as "optimizer" for brevity in this description) is shown in figure 7. The control scheme based on predictive control model, MPC, includes solving an optimization problem at each calculation iteration.

[0149] The optimization consists in minimizing a "cost function" or "performance index" by considering any constraints to which the optimal control solution must be subjected.

[0150] A specific example of a cost function, used in an embodiment of the present method, is expressed by the following formulas: where: in which the involved quantities are matrices:

[0151] J: cost function;

[0152] Y: measurement;

[0153] Rs: trajectory of the command action reference in the prediction horizon;

[0154] II: command;

[0155] Np: prediction horizon;

[0156] R: weight matrix of the command action.

[0157] In the formulas shown above, the superscript symbol T is the transposed matrix, as known.

[0158] According to specific implementation examples employed in the present method, the cost function must be subjected to constraints expressed as the limits of the following quantities:

[0159] - amplitude of the command action:

[0160] - change in the amplitude of the command action between one time instant and the previous time instant:

[0161] - amplitude of the outputs of the model used for prediction: subject to the following conditions:

[0162] D. Adaptation function

[0163] An adaptation function (shown in fig. 8) of the numerical model used to predict the system behavior was developed for the present method in order to improve the performance and robustness of the actuation system.

[0164] The adaptation consists in updating the key parameters of the model at each calculation iteration (i.e., at each step of execution of the control function inside the processing unit), before calculating the prediction of the system behavior evolution.

[0165] In this implementation example, the key parameters of the model subject to adaptation and resulting from the calculation of the adaptation function are:

[0166] Rm: equivalent electrical resistance of the system;

[0167] Km: torque constant of the electric motor; qm: mechanical efficiency of the transmission system; zeal: hysteresis shape factor of the caliper.

[0168] The parameters Rm, Km, qm, zeal are shown, in figure 8, with reference numerals 29, 30, 31 , 32.

[0169] The adaptation function has the control action command signal "u" and the actuation system measurement "y" (clamping pressure and / or force) as inputs.

[0170] E. Advanced diagnosis and predictive maintenance

[0171] As noted above, the introduction of the adaptation function allows monitoring the above parameters subject to adaptation at each step of execution of the control method.

[0172] According to an implementation option, the method also involves a functional "advanced diagnostics and predictive maintenance" block (figure 9) configured to detect the health of the system by appropriately processing the aforesaid information.

[0173] The aforesaid pieces of information, e.g., Rm (29), Km (30), qm (31), zeal (32), updated at each step of execution, are then processed by a diagnostics and predictive maintenance function (implemented by the functional block considered here) to determine the actual state of the actuator, the evolution of its efficiency, and predict possible malfunction in the next cycles of use.

[0174] According to an implementation option, the health information is then sent to a network of remote servers, e.g., in the "Cloud," for monitoring and activating maintenance services.

[0175] F. State estimator

[0176] This functional block (shown in figure 10) is used in the embodiment of the method in which information regarding the system states is not obtained by means of dedicated sensors. In this case, an estimation algorithm (implemented by the functional block considered here) is needed to provide the "actuation system model" module with an estimated value of the internal states of the actuation system, and in particular of the electric motor responsible for converting energy from electric to mechanical.

[0177] According to the embodiment shown in figure 10, the information provided by the state estimator is the estimations of the "Current," "Position," and "Speed” states.

[0178] In the embodiment of the method which involves dedicated sensors for detecting the quantities listed above, the "state estimator" module is not strictly necessary. However, according to an implementation option, it can still be provided to perform measurement noise filtering operations and thus improve the quality of information.

[0179] If there are no dedicated sensors for measuring the system states, the functional block in figure 10 can be used in the implementation solution shown in figure 16.

[0180] If dedicated sensors for measuring the braking system clamping force or fluid pressure or braking torque are not available, the estimator of such quantities is necessary.

[0181] According to different implementation options, one or more of the aforesaid quantities are estimated.

[0182] The functional "force / pressure / torque estimator" block, shown in figure 11 , performs the function of clamping force estimation and can be used in the implementation solution shown in figure 17.

[0183] Referring now to the flowchart in figure 12, the steps carried out in an embodiment of the control method, consisting in this example of the sequence of operations (1)-(6) depicted in figure 12 and described in more detail in the following paragraphs. This sequence of operations is executed by the electronic processing unit at each cycle of execution of the instructions contained in the control software installed in the electronic processing unit. (1). Estimation of the clamping force / brakinq system pressure / brakinq torque states.

[0184] At each step of execution of the software installed in the electronic control unit, this embodiment of the method includes estimating the system states or one of the following quantities according to the system configurations: clamping force, braking system fluid pressure, braking torque.

[0185] Hence, depending on the implementation options, such a control method can use a state estimator or a clamping force or pressure estimator.

[0186] The reported braking actuation system states are "Current," "Position," and "Speed".

[0187] Such states are sent as inputs to the functional block described above in paragraph D, relating to the prediction model adaptation function.

[0188] If there is no force sensor, the functional "estimator" block can be used for estimating the clamping force / pressure (output) by making use of the "Current," "Position," "Speed" measurements (inputs).

[0189] (2). Adaptation of the parameters of the prediction model

[0190] Such an adaptation is performed based on the following information:

[0191] - clamping force / pressure or braking torque, as measured by a sensor or as estimated by the estimator block F;

[0192] - command to the motor at the previous calculation step (from the "optimizer" block C);

[0193] - current, as measured by a sensor or estimated by the estimator block F;

[0194] - position, as measured by a sensor or estimated by the block estimator F;

[0195] - speed, as measured by a sensor or estimated by the block estimator F.

[0196] Based on the aforesaid information, the adaptation function D calculates the following parameters of the actuation system model (also mentioned above): Rm (equivalent electrical resistance of the system), Km (torque constant of the electric motor), qm (mechanical efficiency of the transmission system), zeal (hysteresis shape factor of the caliper).

[0197] According to an implementation option, the model parameters calculated by the adaptation function are processed by a diagnosis function (functional block E), which, by comparing the parameters with reference values, defines the health of the actuation system.

[0198] According to an implementation option, the health of the actuation system is sent through a "wireless" network to a remote data management system (in a cloud-type solution). (3). Model update and prediction

[0199] The parameters calculated in the previous step by the adaptation function D are updated in the prediction model A, and the prediction of the behavior of the actuation system is calculated by executing the functional block A.

[0200] The prediction of the behavior consists of "n" values of the following quantities:

[0201] - force / pressure / braking torque,

[0202] - current,

[0203] - position,

[0204] - speed, where "n" is the duration of the prediction horizon.

[0205] (4). Updating the trajectory of the clamping force / pressure request reference.

[0206] The trajectory information consists of "n" force / pressure values where "n" is the duration of the prediction horizon. It is calculated by the functional unit described above in paragraph B.

[0207] As already disclosed above, with reference to an embodiment of the method, the pieces of information considered for processing are measurements or estimations of the following quantities:

[0208] - force request from a braking distribution module;

[0209] - longitudinal slip of the wheel;

[0210] - vehicle dynamics signals (yaw rate and / or distribution angle and / or lateral acceleration and / or longitudinal acceleration of the vehicle);

[0211] - tire inflation pressure;

[0212] - tire temperature;

[0213] - vertical force acting at the tire-road contact point;

[0214] - tire-road friction coefficient.

[0215] According to an implementation option, the aforesaid information is measured by sensors and acquired by the electronic processing unit (in which the control method of the invention is implemented) by means of a dedicated electrical signal or through a digital data communication network (data bus) present on the vehicle.

[0216] (5). Optimization

[0217] The optimization operation consists of a mathematical process which minimizes the cost function in compliance with the constraints (e.g., the constraints previously indicated in paragraph C).

[0218] At each calculation step, a number "m” of command values to the actuation system is determined, where "m" is the duration of the control horizon. Such values represent the optimal solution which is a function of the following input information:

[0219] - constraints which the cost function optimizer must respect (provided by module C);

[0220] - duration (number of values) of the prediction horizon (provided by calibration or other functional modules);

[0221] - duration (number of values) of the control horizon (provided by calibration or other functional modules);

[0222] - prediction of clamping force / pressure (provided by module A);

[0223] - trajectory of the clamping force / pressure reference (provided by module B).

[0224] The pieces of information on the durations of the control and prediction horizons may be parameters of control system settings (calibrations) or signals from other functional modules present in the software loaded on the electronic control unit.

[0225] The output information from operating step (5) is thus represented by a series of command values to the actuation system which is related to the motor supply voltage to be applied within the control horizon ("m" values corresponding to "m" instants of time). (6). Generation of command to the actuation system

[0226] The result of the optimization process (5) is processed at the step of execution (6) so that only the first value of the "m" command values is selected. At each calculation cycle, comprising the execution of steps (1) through (6), the command value is thus updated with a new value.

[0227] Figures 13-15 show some of the possible architectures to which the predictive control method for braking actuation systems of the present invention can be applied.

[0228] The control strategy can be integrated into centralized electronic architectures for controlling the vehicle also including, inter alia, the "Brake-by-Wire" (BbW) system control functions (implementation example shown in figure 13).

[0229] Furthermore, the control strategy can be integrated into electronic architectures for controlling the vehicle with a central unit which additionally include a Brake-by-Wire (BbW) type control unit for each axle (implementation example shown in figure 14).

[0230] Furthermore, the control strategy can be integrated into electronic architectures for controlling the vehicle with a central unit which additionally include a unique Brake-by- Wire (BbW) control unit for the entire braking system (implementation example shown in figure 15).

[0231] Figures 16 and 17 depict in detail, and in complete form, block diagrams of respective control architectures for a braking system, according to two respective embodiments of the control method in which the system states are estimated and the control quantities are measured (figure 16) and in which the system states are measured and the control quantities are estimated (figure 17).

[0232] The details of the various functional blocks correspond to those shown in figures 5-11. More specifically, the inputs and outputs of the various blocks, in the detailed diagrams in figures 16 and 17, are marked with reference numerals corresponding to those used in figures 5-11.

[0233] As can be seen, the objects of the present invention as previously indicated are fully achieved by the method described above by virtue of the features disclosed above in detail. The advantages and technical problems solved by the method according to the invention were mentioned above, with reference to the various features and aspects of the method.

[0234] In particular, the control method described above, in the context of electronic or electro-mechanical or electro-hydraulic braking systems, allows optimizing the braking action performance and the reduction of calibration time and cost when being applied to the vehicle.

[0235] The adoption of this control method based on a prediction model allows introducing advanced diagnostic methods based on the monitoring of key parameters of the system model, and thus generating data on the health of systems equipping vehicle fleets.

[0236] Furthermore, the application of the method described above, based on the concepts of "Model Predictive Control", to the control of actuators for braking systems is a radical evolution from the prior art of the braking system control, which is instead based on PI D technology and on its subsequent evolutions, the principles and limitations of which have been outlined above in the description of the prior art.

[0237] In brief, the main features and advantages of the method of the invention are:

[0238] - predicting the evolution of the behavior of the actuation system;

[0239] - estimating and monitoring the key parameters of the system for diagnostic purposes;

[0240] - obtaining optimal performance throughout the operating range;

[0241] - generating data useful for predictive maintenance of the braking system.

[0242] Furthermore, by virtue of the application of the control method according to the present invention, the set of parameters subjected to calibration is reduced compared to the solutions representing the background art described above, benefiting the management of calibrations and the calibration process, thus achieving a reduction in the time and cost of the calibration procedure. In order to meet contingent needs, those skilled in the art may make changes and adaptations to the embodiments of the method and braking system described above or can replace elements with others which are functionally equivalent, without departing from the scope of the following claims. Each of the features described above as belonging to a possible embodiment can be implemented irrespective of the other embodiments described.

Claims

CLAIMS1 . A method for controlling the actuation of an electronic or electro-mechanical or electro-hydraulic braking system of a vehicle, wherein the method employs predictive control techniques and is performed through a plurality of calculation steps performed by electronic processing, wherein each calculation step provides a respective actuation command to an actuation system of the braking system, wherein the method comprises:- providing an actuation system model which represents states of the actuation system, said states of the actuation system comprising current and at least one of position or speed, said model being characterized by parameters indicative of electrical and mechanical and / or dynamic properties of the actuation system; and wherein the method further comprises, for each of said calculation steps, the following actions:- measuring and / or estimating a value for each of said states of the actuation system at an instant associated with said calculation step;- measuring and / or estimating, at said instant associated with the calculation step, a value for at least one of the following control quantities: braking system clamping force and / or braking system clamping pressure and / or braking system fluid pressure and / or braking torque;- determining said parameters indicative of electrical and mechanical and / or dynamic properties of the actuation system based on said measured and / or estimated states, and based on one or more of said measured or estimated control quantities, and based on an actuation command determined and supplied to the actuation system at the previous calculation step;- based on the states and control quantities of the actuation system determined in the calculation step, predicting a plurality (n) of future values for each of said states and for at least one of said control quantities of the actuation system, said future values referring to values assumed by said states and control quantities of the actuation system at a respective plurality (n) of future instants associated with respective calculation steps within a predetermined prediction horizon;- determining a reference trajectory of at least one of said control quantities, comprising predicted values assumed by said at least one control quantity at each of said plurality (n) of future instants of the prediction horizon, based on information representative of a request for braking force and based on information indicative of dynamic and / or thermal parameters and / or of a configuration of the braking system and / or of the wheel onwhich the braking system acts or the respective tire and / or of the friction conditions between tire and road;- computing a plurality (m) of actuation command values referring to a respective plurality (m) of future instants associated with respective calculation steps within a predetermined control horizon, wherein said computation action is performed at least based on the predicted value of said at least one control quantity and reference trajectory of said at least one control quantity;- selecting the first value of said plurality of actuation command values, and providing the actuation system with an actuation command having said first selected actuation value.

2. A method according to claim 1 , wherein said computing action is performed by optimizing and / or minimizing a predetermined cost function based on information comprising: constraints to which the cost function must be subjected, duration of the prediction horizon, duration of the control horizon, predicted value of said at least one control quantity, and reference trajectory of said at least one control quantity.

3. A method according to any one of claims 1 or 2, wherein said states of the actuation system comprise both an electric current supplying or flowing through the actuation system, and a position of the actuation system, and a speed of the actuation system.

4. A method according to any one of the preceding claims, wherein said method is iterative, and wherein said determination, prediction, and computation actions comprise updating the actuation system model, the prediction values, the reference trajectory, and the plurality (m) of actuation command values at each calculation step.

5. A method according to any one of claims 1-4, wherein the states of the system are estimated and the control quantities are measured.

6. A method according to any one of claims 1-4, wherein the states of the system are measured and the control quantities are estimated.

7. A method according to any one of the preceding claims, wherein:- the action of measuring a value for each of said states of the actuation systemor measuring a value for at least one of the control quantities is performed by respective sensors;- the action of estimating a value for each of said states of the actuation system is performed using a "system state estimator” software module;- the action of estimating a value for at least one of the control quantities is performed using a "control quantity estimator" software module;- the action of determining parameters indicative of electrical and mechanical and / or dynamic properties of the actuation system is performed using an "adaptation function” software module;- the action of predicting a plurality (n) of future values for each of said states and at least one of said control quantities of the actuation system is performed by a software module implementing said actuation system model;- the action of determining a reference trajectory is performed by a "reference trajectory generator" software module;- the action of calculating a plurality (m) of actuation command values and selecting and providing an actuation command is performed by an "optimizer" software module.

8. A method according to any one of the preceding claims, wherein said parameters indicative of electrical and mechanical and / or dynamic properties of the actuation system comprise:- equivalent electrical resistance (Rm) of the actuation system, and / or- torque constant (km) of an electric motor of the actuation system or associated with the actuation system, and / or- mechanical efficiency (pm) of a transmission system of the vehicle, and / or- shape factor (zeal) of the hysteresis of a caliper of the braking system.

9. A method according to any one of the preceding claims, wherein said information indicative of dynamic and / or thermal parameters and / or of a configuration of the braking system and / or of the wheel on which the braking system acts or the respective tire and / or of friction conditions between tire and road comprises:- longitudinal slip of the wheel and / or- vehicle dynamics signals comprising yaw rate and / or distribution angle and / or lateral acceleration and / or longitudinal acceleration, and / or- tire inflation pressure, and / or- tire temperature, and / or- vertical force acting at the contact point between tire and road, and / or- tire-road friction coefficient.

10. A method according to any one of the preceding claims, wherein said information comprising constraints to which cost function, prediction horizon duration, and control horizon duration must be subjected comprises setting or calibration parameters predefined in a control unit of the braking system or comprises signals from other functional modules of the control unit.

11. A method according to any one of the preceding claims, wherein said actuation command comprises a supply voltage or current of an electric motor included in the actuation system of the braking system.

12. A method according to any one of the preceding claims, wherein the input signals to the actuation system model are:- measured or estimated clamping pressure and / or force;- command to the actuation system;- torque constant of a motor associated with the actuation system;- electrical resistance of said motor associated with the actuation system;- efficiency of the actuation system;- shape factor of the hysteresis function of a caliper of the braking system; and wherein the output signals from the actuation model are:- predicted pressure and / or clamping force;- predicted speed of the actuation system and / or the respective motor;- predicted position of the actuation system and / or the respective motor;- predicted current of the motor associated with the actuation system.

13. A method according to any one of the preceding claims, wherein: the actuation system model implements a linear time-invariant model, wherein the outputs and states of the system are determined by a linear combination of the time variations / derivatives of the states and by the value of the input, and the parameters forming the equations are constant over time; or the actuation system model implements a linear time-variant model, wherein the outputs and states of the system are determined by a linear combination of the timevariations / derivatives of the states and by the value of the input, and the parameters forming the equations are not constant over time; or the actuation system model implements a non-linear time-variant model, wherein the outputs and states of the system are determined by a non-linear combination of the time variations / derivatives of the states and by the value of the input, and the parameters forming the equations are not constant over time.

14. A method according to any one of the preceding claims, wherein the input signals to the reference trajectory generator are:- force request from a braking distribution module;- longitudinal slip of a wheel with which the braking system is associated;- vehicle dynamics signals comprising yaw rate and / or distribution angle and / or lateral / longitudinal acceleration of the vehicle;- air pressure inside a tire of said wheel;- temperature of said tire;- vertical force acting at the tire-road contact point;- road-tire friction coefficient.

15. A method according to any one of the preceding claims, wherein the input signals to the optimizer and cost function are: a prediction horizon value, a control horizon value, the predicted clamping force, the clamping force trajectory, and one or more constraints for optimization, and wherein the cost function depends on the measured values (Y) of the quantity to be optimized, the reference trajectory (Rs) in the prediction horizon, the command values (II), a weight matrix (R) of the command action, and the prediction horizon (Np).

16. A method according to any one of the preceding claims, wherein the input signals to the adaptation function are: the estimated or measured value of clamping force, the estimated or measured value of current, the estimated or measured value of position, the estimated or measured value of speed, the command to the motor.

17. A method according to any one of the preceding claims, wherein the input signals to the state estimator are: the previous clamping force measurement, the predicted clamping force, the previous command to the motor, the future command to the motor.

18. A method according to any one of the preceding claims, wherein the input signals to the control quantity estimator are: past estimation of the clamping force and / or pressure and / or torque, previous command to the motor, future command to the motor, current measurement, position measurement, speed measurement.

19. A method according to any one of the preceding claims, comprising the further action of:- processing said parameters indicative of electrical and mechanical and / or dynamic properties of the actuation system, or actuation system model parameters to obtain predictive diagnostic and / or predictive maintenance information of the actuation system.

20. A method according to claim 19, wherein said processing action comprises comparing said parameters with reference values which define the health of the actuation system.

21. A method according to claim 20, wherein said predictive diagnostic and / or predictive maintenance information of the actuation system is transmitted to a remote data management system, for example in the cloud.

22. An electronic or electromechanical or electro-hydraulic braking system for a vehicle, comprising processing means configured to perform a control method according to any one of claims 1-21.

23. A braking system according to claim 22, comprising at least one electro-hydraulic or electro-mechanical actuation system.

24. A braking system according to claim 23, comprising a Brake- by- Wire, BbW, type braking system adapted to be used in a vehicle with a central electronic control unit (ECU), and / or comprising a Brake-by-Wire, BbW, type braking system adapted to be used in a vehicle with a central electronic control unit (ECU) and two electronic control units of the braking system, and / or comprising a Brake-by-Wire, BbW, type braking system adapted to be used in a vehicle with a central electronic control unit (ECU) and a single electronic control unit of the braking system.

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