Method for measuring the deceleration of a wheel of a motor vehicle

Abstract

The invention relates to a method 1 for controlling a vehicle braking system comprising the provision of at least one WSS wheel speed sensor and an algorithm that uses data provided by this sensor to estimate an instantaneous speed value and a deceleration of the wheel, calculated from said algorithm, which includes a polynomial fitting step 102 based on the sensor data. Figure for the abstract: Figure 1

Description

Title of the invention: Method for measuring the deceleration of a wheel of a motor vehicle

[0001] The invention relates to a method for measuring the deceleration of a wheel of a motor vehicle.

[0002] Currently, a deceleration measurement is obtained from data from the system bus (CAN: Controller Area Network); however, this measurement is highly filtered and affected by a significant delay. Therefore, it cannot be used effectively to control the tasks of a braking system.

[0003] The object of the invention is to propose a method for a smoothed measurement of deceleration, with a lower delay than reading from the system bus.

[0004] According to the invention, a control method for a vehicle braking system includes providing at least one wheel speed sensor (WSS: Wheel Speed ​​Sensor) and data processing implementing an algorithm that uses data provided by this sensor to estimate an instantaneous speed value and a deceleration of the wheel, this algorithm including a polynomial fitting step from the sensor data.

[0005] The process advantageously comprises: - an emission, by the sensor, of successive pulses corresponding to a distance traveled; - a time-stamping step, that is, a recording of an instant corresponding to each pulse, and the recording of successive instants in a memory and the storage in this memory of the last N instants thus recorded; and, - the polynomial adjustment step being carried out from the last N instants recorded in the memory.

[0006] Advantageously, during the polynomial adjustment step, a curve is obtained having a formula of the type: P(t) = | at² + bt + c

[0007] Where: - P(t) is the instantaneous position of the wheel at time t; - a, b and c are coefficients from the polynomial adjustment calculation.

[0008] Then, we deduce from the formula P(t): an instantaneous speed of the wheel: S(t) = at + b and an instantaneous acceleration of the wheel: A(t) = a

[0009] Preferably, when a measured time between two successive moments becomes greater than a threshold value, an immobilization beacon is activated, then one applies a model of progressive decrease to zero of the values ​​of velocity and then acceleration.

[0010] Several embodiments of the invention will be described below, by way of non-limiting examples, with reference to the accompanying drawings in which:

[0011] [Fig. 1] represents a logic diagram schematically illustrating a process according to the invention;

[0012] [Fig.2] illustrates a timestamp in the process of [Fig.1];

[0013] [Fig.3] illustrates a polynomial adjustment step in the process of [Fig.1];

[0014] [Fig.4] illustrates a restraint step in the process of [Fig.1];

[0015] [Fig.5] illustrates linear wheel speed measurements during acceleration phase, according to the method of [Fig.1], in comparison with measurements according to a method of the prior art;

[0016] [Fig. 6] illustrates wheel acceleration measurements, during the acceleration phase, according to the method of [Fig.1], in comparison with measurements according to the same method of the prior art;

[0017] [Fig.7] illustrates linear wheel speed measurements during deceleration phase, according to the method of [Fig. 1], in comparison with measurements taken using the same method of the prior art; and,

[0018] [Fig.8] illustrates wheel acceleration measurements during deceleration, according to the method of [Fig.1], in comparison with measurements according to the same method of the prior art.

[0019] In this description, the term acceleration is used interchangeably, whether its value is positive, i.e., corresponding to an increase in speed, or negative, i.e., corresponding to a decrease in speed. The term deceleration is used when one specifically wants to designate an acceleration value that is actually negative.

[0020] Figure 1 is a flowchart illustrating a method 1 for determining the deceleration of a wheel of a vehicle, in particular for controlling an intelligent braking system and a vehicle dynamic control (VDC) system. This method comprises steps 101-105, including: - a first step 101, to time-stamp successive pulses M emitted by a WSS speed sensor of a wheel 2 of the vehicle, with reference to a clock H, and to record each instant t of each pulse M in a memory 3; then, - a second step 102, to establish a polynomial fit from the last N instants t recorded and to deduce values ​​of speed and acceleration; - a third step 103, to apply a model of progressive reduction to zero of the velocity values ​​and then of deceleration, when a difference between two successive instants tn, tn+i becomes greater than a threshold DT; then, - a fourth step 104, to apply a Kalman filter, taking into account a possible F(ABS) alert from the anti-lock braking system (ABS); then, - a fifth step 105 to transmit the calculated data to an intelligent braking system SB and a vehicle dynamic control system VDC (Vehicle Dynamic Control).

[0021] In the illustrated example, the clock H is a clock of a microprocessor (CPU) of the on-board computer. As illustrated in [Fig.2], the memory 3 used to store the times t is of the FIFO type (for "First In First Out"), in which eight successive times t3-ti0 are stored, a new time tu recorded replacing in memory 3 the time t3 which is stored there the oldest.

[0022] The polynomial adjustment is established from the last eight instants t recorded, that is to say the eight instants stored in memory 3, that is to say that N is equal to 8 (N=8), knowing that between two pulses M emitted by the WSS sensor, the wheel travels a given constant distance L; this distance L can be an angular distance or a linear distance traveled by its periphery, this angular distance and this linear distance being proportional to each other.

[0023] Polynomial fitting allows the calculation of a curve with the equation: P(t) = 4at² + bt + C

[0024] Where: - P(t) is the instantaneous position of the wheel at time t; - a, b and c are coefficients from the polynomial adjustment calculation.

[0025] Then, we deduce from P(t): - an instantaneous speed of the wheel at time t: S(t) = at + b - and an instantaneous acceleration of the wheel at time t: A(t) = a

[0026] Typically, for each wheel rotation, forty-eight (48) pulses M are emitted by the WSS sensor. This number may be insufficient to allow a calculation of the acceleration usable by the SB braking system. This deficiency is compensated for by the use of the polynomial fit and the resulting P(t) curve, which is renewed with each new pulse M received.

[0027] When the wheel rotates too slowly, the number of pulses M per unit of time becomes too low for the calculation to be accurate. This is the case when the vehicle's speed becomes too low, or when the vehicle is stopped, or when the wheel slips, spins, or is locked. Thus, during the deceleration phase, the gap between two successive instants tn, tn+i becomes greater than a threshold DT, that is to say when the velocity S(t) passes below a corresponding threshold, the curve resulting from the polynomial fitting becomes unusable.

[0028] We then proceed to the third step 103, in which: - if the time difference is less than DT (tn+[ - tn+i < DT) then, the acceleration is given the value A(t) calculated in the previous step 102; and, - if the time difference is greater than DT (tn+i - tn+i> DT) then, we substitute for the curve P(t) a deceleration model, such as the one illustrated in [Fig.4], by which we perform a standstill correction which gives the acceleration a forced value which brings it back to zero, preferably gradually.

[0029] Thus, in the deceleration model illustrated in [Fig.4], the deceleration A(t) is kept substantially constant, so that the velocity decreases linearly, and then, when the velocity has reached a zero value, the acceleration is rapidly and progressively brought back to zero.

[0030] In the fourth step 104, the data obtained in the previous steps are subjected to corrections using a Kalman filter. When an F(ABS) alert is issued by the ABS anti-lock braking system, it is taken into account in this step 104.

[0031] In the fifth step 105, the calculated and filtered data are transmitted to the SB braking system and the VDC dynamic control system.

[0032] Figures 5 to 8 illustrate the advantages of a method according to the invention.

[0033] At [Fig. 5]: - a curve C51 illustrates a wheel speed curve calculated according to the method of the invention; - a C52 curve illustrates a wheel speed curve calculated according to the prior art from data from the CAN bus; and, - a C53 curve illustrates a vehicle speed curve calculated according to the prior art from data from the CAN bus.

[0034] It is observed that the invention makes it possible to calculate a smoother speed curve with less delay relative to the signals collected via the CAN bus.

[0035] At [Fig.6]: - a curve C61 illustrates a wheel acceleration curve calculated according to the method of the invention; and, - a C62 curve illustrates an acceleration curve calculated according to the prior art from data from the CAN bus.

[0036] It is observed that the invention makes it possible to calculate a smoother, more precise acceleration curve with less delay relative to the signals collected via the CAN bus.

[0037] At [Fig.7]:

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[0045] - a curve C71 illustrates a wheel speed curve, calculated according to the method of the invention; - a C72 curve illustrates a wheel speed curve, calculated according to the prior art from data from the CAN bus; and, - a C73 curve illustrates a vehicle speed curve, calculated according to the prior art from data from the CAN bus. The C51, C61, C71 curves, calculated according to the invention, have a refresh rate of approximately one millisecond (1 ms). The speed curve of the C72 wheel, calculated according to the prior art, is established with a refresh rate of only twenty milliseconds (20 ms) and with a delay of about twenty-five milliseconds (25 ms) on the C71 curve established according to the invention. The speed curve of the C73 vehicle calculated according to the prior art, is established with an even lower refresh rate of only forty (40 ms) milliseconds and with an even greater delay of about one hundred and sixty milliseconds (160 ms) on the C71 curve established according to the invention. At [Fig. 8]: - a curve C81 illustrates a realistic deceleration curve calculated according to the method of the invention; and, - a C82 curve illustrates a deceleration curve calculated according to the prior art from data from the CAN bus. In the illustrated example, the Kalman filter used in step 102 for WSS signal processing is defined by the following equations. The prediction equations are: .r= Ax+Bu P = APA t + Q The update equations are: s=cpct+rk=pcts1 xx' + K(y-Cx~) P=P-KCP Equations in which: speed position defines the state of the system acceleration u = 0 is the control input y - x is the measured output A? Aï2 / 2 is the state transition matrix Ouch 1. 0 ] 7cst the input transition matrix 0 is the output matrix t4 Ouch 3 / 2 a A AC / 2 is the noise matrix of the process . HAS / 2 / 2 with ^e-abs if ABS is activated

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[0051] or ^E-normai in other cases 'crj 0 1 is the measurement noise matrix 0 Matrices in which: Ai is the sampling period; is the variance of the process; and, vi, ^v, and are the variances of the position, velocity, and acceleration measures. As shown in Figures 5 to 8, the notable advantages of a method according to the invention for deceleration control, for a closed-loop intelligent braking system (SmartBrake, in English). It will indeed become apparent to the man of the art that various modifications can be made to the methods of implementation described above, in the light of the teaching which has just been disclosed to him. In particular, the Kalman filter may be different from the one presented in this description. List of references 1: Method according to the invention 2: wheel 3: memory 101: First step of process 1 102: Second step of process 1 103: Third step of process 1 104: Fourth step of process 1 105: Fifth step of process 1 a, b, c: polynomial adjustment coefficients A(t): instantaneous acceleration C51, C61, C71, C81: curves established by a method according to the invention; C52, C53, C62, C72, C73, C82: curves established according to the prior art; DT: threshold period F(ABS): Anti-lock Braking System (ABS) warning H: clock L: distance traveled between two successive impulses M M: pulse emitted by the wheel speed sensor N: number of the last moments recorded in memory 3 P(t): instantaneous position S(t): instantaneous velocity SB: Intelligent braking system. t: instant of an impulse M VDC: Vehicle Dynamic Control System WSS: Wheel speed sensor

Claims

Demands

1. A method (1) for controlling a braking system (SB) of a vehicle comprising an algorithm that uses data (M) provided by a wheel speed sensor (WSS) (2) to estimate an instantaneous speed value (V(t)) and a deceleration (A(t)) of the wheel, said algorithm comprising a polynomial fitting step (102) from said sensor data.

2. A method according to claim 1, characterized in that it comprises: - an emission, by the sensor (WSS), of successive pulses (M) corresponding to a distance (L) traveled; - a step (101) for a timestamp (101), that is to say a reading by a clock (H) of an instant (t) corresponding to each pulse (M), and the recording of said successive instants (t) in a memory (3) and the storage in said memory of the last N instants (t) thus recorded; and, - the step (102) of polynomial adjustment being carried out from said last N instants (t) recorded in said memory (3).

3. Method according to claim 2, characterized in that at the polynomial fitting step (102), a curve is deduced having a formula of the type: P(O at2 + bt + c Where: - P(t) is an instantaneous position of the wheel; and, - a, b and c are coefficients, then, the instantaneous velocity (S(t)) of the wheel (2) and the instantaneous acceleration (A(t)) of said wheel are deduced from said formula.

4. A method according to any one of claims 1 to 3, characterized in that when a difference between two successive instants (tn, tn+i) becomes greater than a threshold value (DT) an immobilization beacon is activated, and a model of progressive decrease to zero of the speed and acceleration values ​​is applied (103).

5. A method according to any one of claims 1 to 3, characterized in that a Kalman filter defined as follows is applied. The prediction equations are: x = Ax + Bu P = AP Âr + Q The update equations are: s=cpct+rk=pctsx x = x~ + K(y-Cx~) P = P -KCP Equations in which: position defines the state of the system, velocity, acceleration. w = 0 is the control input, J, ~ x is the measured output, ' 1 Af AT / 2 ' is the state transition matrix, A = 0 1 At .00 1 . g — [ 0 0 0 ]r is the input transition matrix, ■ 1 0 0 ■ is the output matrix, c= 0 1 0 .00 1 . ■ Af4 / 4 M3 / 2 &P12 ' is the noise matrix of Q= M3I2 Ar zv Af 1 . process with ^x-abs if ABS is enabled or ^z-^r / miZ in other cases, <7^ () 0 cr2 0 0 is the measurement noise matrix; '2 a Matrices in which: is the sampling period; Cv is the variance of the process; and <?*, <7y, et sont respectivement les variances des mesures de position, vitesse et accélération.

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