Classifications

• • B—PERFORMING OPERATIONS; TRANSPORTING
  • B60—VEHICLES IN GENERAL
  • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
  • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
  • B60W40/12—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to parameters of the vehicle itself, e.g. tyre models
  • B60W40/13—Load or weight
• • B—PERFORMING OPERATIONS; TRANSPORTING
  • B60—VEHICLES IN GENERAL
  • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
  • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
  • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
  • B60W40/101—Side slip angle of tyre
• • B—PERFORMING OPERATIONS; TRANSPORTING
  • B60—VEHICLES IN GENERAL
  • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
  • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
  • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
  • B60W40/103—Side slip angle of vehicle body
• • B—PERFORMING OPERATIONS; TRANSPORTING
  • B60—VEHICLES IN GENERAL
  • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
  • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
  • B60W40/12—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to parameters of the vehicle itself, e.g. tyre models
  • B60W40/13—Load or weight
  • B60W2040/1323—Moment of inertia of the vehicle body
  • B60W2040/1346—Moment of inertia of the vehicle body about the yaw axis
• • B—PERFORMING OPERATIONS; TRANSPORTING
  • B60—VEHICLES IN GENERAL
  • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
  • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
  • B60W2050/0001—Details of the control system
  • B60W2050/0019—Control system elements or transfer functions
  • B60W2050/0028—Mathematical models, e.g. for simulation
  • B60W2050/0029—Mathematical model of the driver
• • B—PERFORMING OPERATIONS; TRANSPORTING
  • B60—VEHICLES IN GENERAL
  • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
  • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
  • B60W2050/0001—Details of the control system
  • B60W2050/0019—Control system elements or transfer functions
  • B60W2050/0028—Mathematical models, e.g. for simulation
  • B60W2050/0031—Mathematical model of the vehicle
  • B60W2050/0033—Single-track, 2D vehicle model, i.e. two-wheel bicycle model

Definitions

• the present invention relates to a method for identifying a vertical moment of inertia and drift rigidities front and rear of a motor vehicle comprising at least two steered wheels.
• the vertical moment of inertia and the drift rigidities are parameters that are used in many vehicle control systems, such as the trajectory control system for example.
• the value of the drift rigidities is conventionally calculated a priori from a predetermined distribution of the loads in a test vehicle, the inertia being calculated separately by other methods. Then the values thus calculated are integrated into the calculators of all the vehicles of the corresponding fleet.
• the object of the present invention is to solve the aforementioned problem and for this purpose has a method for identifying a vertical moment of inertia and drift rigidities front and rear of a motor vehicle comprising at least two wheels characterized in that it comprises a step of measuring a yaw rate and a transverse acceleration of the vehicle and a step of simultaneously identifying said moment of inertia and said rigidities as parameters of a parametric model of a predetermined type of vehicle based on measurements of yaw rate and transverse acceleration.
• the method comprises one or more of the following features:
• the parametric model is a model of two-wheeled vehicle without dangling according to the relations:
• ⁇ ⁇ t ⁇ o
• V (O, and r (t) v ( ⁇ (t) + ⁇ (t)) ⁇ (t) where t is the time;
• Di is the drift stiffness of the tires of the front wheels of the vehicle
• D 2 is the drift stiffness of the rear wheels of the vehicle
• Li is a predetermined value of the distance from the center of gravity of the vehicle to the front axle thereof;
• M is a predetermined mass of the vehicle
• L 2 is a predetermined value of the distance from the center of gravity of the vehicle to the rear axle thereof; ⁇ is the yaw rate; ⁇ is an angle of drift of the vehicle; ⁇ is the transverse acceleration;
• V is a longitudinal speed of the vehicle
• Gold 1 and ⁇ 2 are steering angles of front and rear wheels respectively
• the parametric model is a model of a two-wheeled vehicle without dangling
• the identification step comprises a step of measuring the yaw rate and the reduced transverse acceleration of the vehicle and a step of calculating said moment of inertia and said stiffnesses as a function of the yaw rate and the speed of yaw; measured reduced transverse acceleration;
• the identification step comprises a step of minimizing a cost function consisting of a weighted sum of a first term relating to the measured yawing acceleration and a second term relating to the measured transverse acceleration ;
• the cost function is a function according to the relation:
• F is the cost function
• t is the time
• At is a measurement time
• Di is the drift stiffness of the front wheels of the vehicle
• D 2 is the drift stiffness of the rear wheels of the vehicle
• / z is the moment of inertia vertical
• ⁇ is a modeled yaw rate using the model of the predetermined type
• ⁇ measured is measured yaw speed
• ⁇ Rmemree is the reduced acceleration measured
• W 1 and w 2 are predetermined weights ;
• the identification step includes a step of estimating a measurement noise on the measurement of the transverse acceleration and a step of calculating the moment of inertia and rigidity drifts as a function of the estimated measurement noise;
• the step of estimating the measurement noise is a step of estimating a constant additive noise
• the calculation step comprises a step of minimizing a cost function according to the relation: where F is the cost function, t is the time, At is a measurement time, Di is the drift stiffness of the front wheels of the vehicle, D 2 is the drift stiffness of the rear wheels of the vehicle, / z is vertical moment of inertia, ⁇ is a yaw rate Modeled modeled using the model of the predetermined type, ⁇ is a vehicle drift angle modeled by the predetermined type model, V is a predetermined vehicle speed, d is the estimate of the measurement noise, and W 1 and w 2 are predetermined weights; the step of estimating the measurement noise implements a linear state observer based on the model of predetermined type;
• the minimization of the cost function J and the minimization of the cost function F are iterated until the satisfaction of a predetermined stopping criterion, the values obtained by the minimization of the function J being used for the minimization the function F, and vice versa;
• the weighting on the term relating to the measurement of the yaw rate is equal to the term R (I 5 I) of the matrix R and the weighting on the term relating to the measurement of the transverse acceleration is equal to the term R ( 2,2) of the matrix R.
• the subject of the present invention is also a computer program product comprising instructions that are capable, when executed by computer, of implementing a method of the aforementioned type.
• FIG. 1 is a flowchart of a method according to the invention
• FIG. 2 is a graph of curves of the temporal evolution of a measured yaw rate and a yaw rate modeled using the final values of the parameters obtained by the method according to the invention
• FIG. 3 is a graph of curves of the temporal evolution of a measured transverse acceleration and of an acceleration modeled using the values of the parameters obtained by the method according to the invention.
• a method of identifying the vertical moment of inertia and the drift rigidities front and rear of a four-wheeled motor vehicle whose four wheels are steered starts with a step 6 of initialization.
• This step 6 consists of measuring the mass M of the vehicle and determining the position of its center of gravity.
• the vehicle speed is set to a predetermined value V.
• the method then continues with a step 10 for measuring the yaw rate of the vehicle, that is to say the speed of rotation of the vehicle around a vertical axis passing through its center of gravity, then by a step 12 measuring the transverse acceleration at the center of gravity of the vehicle and by a step 14 of measuring a steering angle Or 1 of the front wheels of the vehicle and a steering angle a 2 of the rear wheels of the vehicle.
• a step 10 for measuring the yaw rate of the vehicle that is to say the speed of rotation of the vehicle around a vertical axis passing through its center of gravity
• a step 12 measuring the transverse acceleration at the center of gravity of the vehicle
• a step 14 of measuring a steering angle Or 1 of the front wheels of the vehicle and a steering angle a 2 of the rear wheels of the vehicle are measured for a duration ⁇ t and then sampled at a predetermined period Te, the duration ⁇ t and the period Te being chosen so as to satisfy identification constraints, as is known in the field of identification.
• the method continues with a step 18 of optimizing the problem according to the following relationships is implemented: - ⁇ R (t) fdt (1)
• t is the time
• Di is the drift stiffness of the tires of the front wheels of the vehicle
• D 2 is the drift stiffness of the rear wheels of the vehicle
• Li is a predetermined value of the distance from the center of gravity of the vehicle to the front axle thereof;
• L 2 is a predetermined value of the distance from the center of gravity of the vehicle to the rear axle thereof; ⁇ is a modeled yaw rate; ⁇ is a modeled vehicle drift angle, i.e. the angle that the vehicle velocity vector makes with a longitudinal axis thereof;
• ⁇ measured is ⁇ ⁇ measured yaw rate; ⁇ 'K R my urea is the measured reduced acceleration; ? and
• W 1 and w 2 are predetermined weights. It will be noted that the relations (2), (3) and (4) are those of a parametric model of the so-called "two-wheel model without dangling".
• step 16 of the method continues with a step 20 of optimizing the measurement noise on the acceleration in which it is assumed that the difference between the real value transverse acceleration ⁇ and the measured value ⁇ m esuxée thereof is due to a constant additive disturbance d, that is to say that
• Step 20 comprises a substep 22 of calculating a gain matrix
• ⁇ is an estimate of the yaw rate
• ⁇ is an estimate of the drift angle of the vehicle
• d is an estimate of the additive perturbation on the measurement of the transverse acceleration.
• the values D 1 (Jc), D 2 (Jc) and I 2 (Jc) are set at the values D 1 , D 2 and I 2 calculated in the substep 24 implemented during the previous iteration, the sub-step 24 step 24 being described below.
• the values D 1 (Jc), D 2 (Jc) and I 2 (Jc) are set by the designer to start the algorithm. An estimate or a rough measurement of the vertical moment and the rigidities can for example be enough to start the algorithm.
• the matrix K is synthesized by a classical linear quadratic method, that is to say as a solution of the problem of minimization of the quadratic cost function according to the relation:
• Q (k) and R (k) are positive definite matrices, for example calculated according to the state matrices of the relations (7) and (8) in a manner known per se.
• the value of the gain matrix K (k) is then fixed to the value of the gain matrix K calculated at the end of this minimization problem.
• Step 20 then continues with a sub-step 24 of solving the optimization problem according to the relation: (10) with ⁇ checking relations (2), (3) and (4) and d satisfying the following relations:
• the calculated value of the cost function F is stored and the values D 1 (k), D 2 (k) and I z (k) are set to the values D 1 , D 2 and / z calculated at the end of this optimization problem.
• a test is implemented to find out if a stopping criterion of the algorithm is satisfied. For example, if the value of the cost function F has not decreased by more than 1% during the last ten iterations of the algorithm, it is stopped and the values finally retained for the drift rigidities before and back and the vertical moment of inertia are the values D x ⁇ k), D 2 (k) and I z (k) recently calculated.
• the substep 28 then loops back on the substep 24 for the calculation of a new value K (k) of the observer's gain followed by the calculation new values D x (k), D 2 (k) and I z (k) of the forward and reverse drift rigidities and the vertical moment of inertia.
• the minimization of the cost function F according to the relation (10) therefore consists in minimizing both the yaw rate modeling error ⁇ and the measurement noise d of the transverse acceleration ⁇ of the vehicle.
• the weights W 1 and w 2 are equal to R (1, 1) and R (2.2) respectively, so as to normalize the contributions of the two terms appearing in the cost function of the relation (10).
• FIG. 2 a measured yaw rate and a corresponding yaw rate are plotted, modeled using the model according to equations (2), (3) and (4) with vertical moment of inertia values and front and rear drift rigidities those obtained by the method described above.
• FIG. 3 shows a measured transverse acceleration and a corresponding transverse acceleration rate, predicted using the observer as previously described, with the values of vertical moment of inertia of front and rear drift and gain of the observer those obtained by the method according to the second variant described above.
• the method just described also applies to a vehicle of which only the front wheels are steered.
• the steering angle of the rear wheels is zero and there is no need to measure it.
• an algorithm has been described based on a model of the two-wheeled vehicle without dangling, it is possible to use more complete models of the behavior of the vehicle.
• the preceding relationships are supplemented by a modeling of the ballad of the wheels by the incorporation of terms relating to the dynamics of establishing the transverse forces of the wheels.

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• Engineering & Computer Science (AREA)
• Physics & Mathematics (AREA)
• Automation & Control Theory (AREA)
• Mathematical Physics (AREA)
• Transportation (AREA)
• Mechanical Engineering (AREA)
• Steering Control In Accordance With Driving Conditions (AREA)
• Control Of Driving Devices And Active Controlling Of Vehicle (AREA)

Applications Claiming Priority (2)

Publications (1)

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Cited By (1)

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• 2007
  • 2007-07-02 FR FR0756226A patent/FR2918337B1/fr not_active Expired - Fee Related
• 2008
  • 2008-04-22 JP JP2010514046A patent/JP2010531773A/ja not_active Withdrawn
  • 2008-04-22 EP EP08805677A patent/EP2160314A1/fr not_active Withdrawn
  • 2008-04-22 WO PCT/FR2008/050719 patent/WO2009004194A1/fr active Application Filing

Non-Patent Citations (1)

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