• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
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    • 专利摘要:
    A method of estimating the mass of a motor vehicle comprising a front wheel train and a rear wheel train, by means of an intelligent communication device, after loading the vehicle, the method comprising the steps of: i) identify the vehicle in the intelligent communication device; (ii) taking and processing, by means of a camera of the intelligent communication device, a photograph of at least one wheel with at least one point of the vehicle being allowed to sink together when loading the vehicle with the suspension of the vehicle wheel, after loading, to determine the movement of the wheel train photographed according to the identified vehicle, the taking of a photograph of a wheel is subordinate to holding the phone in a plane perpendicular to the plane of the wheel photographed except in the vertical position of the phone; (iii) determining the travel of the train opposite to the wheel photographed in step (ii); (iv) calculating, by means of a computing unit of the intelligent communication device, the load value on the train of the wheel photographed and the load value on the opposite train according to the respective travel of these trains, to determine the total load value of the vehicle; (v) inform the user by means of the intelligent communication device of the state of charge of the vehicle.
    公开号:FR3014557A1
    申请号:FR1362176
    申请日:2013-12-05
    公开日:2015-06-12
    发明作者:Guillermo Pita-Gil
    申请人:Renault SAS；
    IPC主号:
    专利说明:

    [0001] The present invention relates generally to a method for estimating the total mass of a motor vehicle. More particularly, the invention relates to a method for estimating the total mass of a vehicle after loading.
    [0002] Knowledge of the total mass of a motor vehicle is necessary for the proper functioning of many devices embedded in the vehicle, such as damping systems, under-inflation detection systems, engine control systems (electrical, thermal or hybrid) , hill start systems, overload detection systems, lighting systems, braking systems and / or energy recovery systems ... The patent application filed under the reference FR-12-57425 discloses a method of estimating the total mass of a vehicle using an intelligent communication device, in which the optical axis of the camera must coincide with the axis of the center of the wheel. This method requires the user to lower in order to coincide the optical axis and the axis of the wheel center and thus makes handling impractical. An object of the present invention is to meet the disadvantage of the document of the prior art mentioned above and in particular to propose a method of estimating the mass after loading of a motor vehicle allowing the user to easily detect an overload of his vehicle without requiring special handling of the intelligent communication device. The invention should also provide a method requiring the least possible calculation time.
    [0003] For this purpose, a first aspect of the invention concerns a method for estimating the mass of a motor vehicle comprising a front wheel train and a rear wheel set, by means of an intelligent communication device, after loading the vehicle. , the method -2 comprising the steps of: (i) identifying the vehicle in the intelligent communication device; (ii) taking and processing, by means of a camera of the intelligent communication device, a photograph of at least one wheel with at least one point of the vehicle being allowed to sink together when loading the vehicle with the suspension of the vehicle wheel, after loading, to determine the movement of the wheel train photographed according to the identified vehicle, the taking of a photograph of a wheel is subordinate to holding the phone in a plane perpendicular to the plane of the wheel photographed except in the vertical position of the phone; (iii) determining the displacement of the train opposite to the wheel photographed in step (ii), or by measuring the angle of inclination of the vehicle after loading, by means of at least one accelerometer or inclinometer of the intelligent communication, either by taking and processing, by means of the camera of the intelligent communication device, a photograph of at least one wheel with at least one point of the vehicle brought to sink together during loading the vehicle with the suspension of a wheel of the train opposite the wheel train photographed in step (ii); (iv) calculating, by means of a computing unit of the intelligent communication device, the load value on the train of the wheel photographed and the load value on the opposite train according to the respective travel of these trains, to determine the total load value of the vehicle; (y) inform the user by means of the intelligent communication device of the state of charge of the vehicle. Such a vehicle load estimation method is very simple and quick to implement for a user having an intelligent communication device, such as for example a smart mobile phone or smartphone, also called Smartphone according to the terminology English equipped with an adequate application. Such a present solution allows the user to easily determine the weight of the vehicle, while being reliable because not dependent on the element in the vehicle. It thus allows any user to check after loading the state of charge of his vehicle and prevent any risk of overcharging that may lead -3 including overconsumption, degraded handling or a breach of security provisions provided for the model of vehicle under consideration (including the total laden weight or GVWR). Advantageously, the processing of the photograph may comprise at least one step of calculating an invariant. Advantageously, the calculation of the invariant can be a birapport performed on at least one point of the wheel and at least one point of the vehicle brought to sink together during the loading of the vehicle with the suspension of the wheel of the vehicle. Alternatively, the vehicle identification step (i) may comprise the steps of: (i.1) determining before loading the distance between the wheel center and the wheel center of the wheel to be photographed in step (ii); (i.2) determine the angle of inclination of the vehicle before loading; (i.3) determine the total allowable load of the identified vehicle. According to an advantageous variant, the step (ii) of taking and image processing may comprise the following substeps consisting of: (ii.0) taking a photograph of a wheel of the vehicle; (ii.1) transforming the captured wheel photograph into an image in 20 levels of gray; (ii.2) applying a first Gaussian blur filter to improve the image sharpness quality; (ii.3) applying a second Sobel filter to obtain the contours of the image; (Ii.4) decomposing the image into two parts, a first part relating to the wheel and a second part relating to the wheel well; (ii.5) calculate the center and radius of the wheel arch by the least squares method; (ii.6) calculating the minimum and maximum radius values of the wheel 30 according to the radius of the wheel well and the identified vehicle; -4 (ii.7) apply a third Mexican wavelet-type filter to improve the concentration of points near the center of the wheel; (ii.8) calculate the center of the wheel based on the accumulation of points in the center of the wheel, calculate the distance after loading between the wheel center and the center of the wheel well, calculate the ratio of at least one point of the wheel and of said at least one point of the vehicle being allowed to sink together during the loading of the vehicle with the suspension of the vehicle wheel; (ii.9) calculate the clearance of the wheel train photographed by the difference in distance between the wheel center and the wheel center after and before loading. According to another variant of the invention, the step (iii) of determining the displacement of the opposite train can be based on a measurement of the difference of the angle of inclination of the vehicle before and after loading, the angle of inclination being chosen as the angle between a terrestrial reference and a vehicle mark according to the X axis of the vehicle. Step (iii) of measuring the inclination angle, any detection of an acceleration beyond a certain predefined threshold can be considered as a fall of the intelligent communication device, step (iii) measure to be repeated. The step (iv) of calculating the load value on the front and rear wheel trains can be obtained by interpolation in a load / deflection mapping. Another aspect of the invention relates to an intelligent communication device configured to enable the implementation of the method according to any one of the preceding claims, characterized in that the intelligent communication device comprises a programmed application adapted to activate a method 30 for estimating the mass of a vehicle, a man-machine interface suitable for launching the mass estimation application of a vehicle, vehicle identification means, a camera adapted for take a photograph of at least one wheel with at least one point of the vehicle being sinking together when loading the vehicle with the vehicle wheel suspension, - at least one accelerometer and / or inclinometer adapted to measure an angle tilt between the terrestrial reference and the vehicle mark, - a calculation unit programmed to perform image processing steps and t of calculating clearance values and load values including at least one calculation step of at least one invariant, and at least one graphic and / or sound interface adapted to warn the user of the state of charge of his vehicle. Other features and advantages of the present invention will emerge more clearly on reading the following detailed description of an embodiment of the invention given by way of non-limiting example and illustrated by the appended drawings, in which: FIG. 1 schematically represents an intelligent communication device according to one embodiment of the invention; FIG. 2 represents a diagram of the method for estimating the mass of a vehicle according to one embodiment of the invention; FIG. 3 diagrammatically shows the movement of the front and rear wheel sets following the loading of the vehicle; FIG. 4 represents a detailed diagram of the image processing step according to one embodiment of the invention; Figure 5 shows schematically the acquisition by the intelligent communication device of an image according to an embodiment of the invention; FIGS. 6A-6B show an image of the wheel such in two different situations; FIG. 7A represents an example of the load / deflection law of a wheel suspension for a predefined model of vehicle; FIG. 7B represents the experimental results for determining the total load of a vehicle; FIG. 8 represents an example of definition of the axes for an intelligent communication device. FIG. 1 schematically represents an intelligent communication device according to one embodiment of the invention. The intelligent communication device 10 comprises a programmable central unit 12. An application 14 for estimating the mass of a vehicle is programmed on this central unit 12. A man-machine interface 16 makes it possible to launch the application 14 for estimating the mass of a vehicle. Vehicle identification means are provided, for example, in the form of a selection via the man-machine interface 16 of a vehicle model 20 from a list of pre-recorded models in a non-volatile memory 18. It is also provided a camera 20 for taking a photograph of at least one wheel of the vehicle and at least one accelerometer 22 and / or an inclinometer 24 for measuring the inclination angle of the intelligent communication device, the central unit 12 being programmed to 25 perform image processing steps and calculation of deflection values and load values. In addition, at least one graphical and / or audible interface 26 is provided to warn the user of the state of charge of his vehicle. This graphic and / or sound interface 26 may be partially or completely linked to the man-machine interface 16. For information purposes, the x, y and z axes as generally defined for such a communication device are represented in FIG. Figure 8. Figure 2 shows a diagram of the method of estimating the mass of a vehicle according to one embodiment of the invention. A preliminary step is to launch the vehicle load estimating application. Once the application is launched, in order to estimate the mass of the vehicle, the user must in a first step (i) identify his vehicle. For this purpose, he may for example be invited through the man-machine interface to select his vehicle model from a prerecorded list. The pre-registered vehicle model shall include at least the information relating to the distance between the wheel center and the wheel well center of the wheel to be photographed (step i.1) and the total permissible load for that model of vehicle ( step i.3). Alternatively, the determination of the distance between the wheel center and the wheel center of the wheel to be photographed (step i.1) can be carried out manually by taking a photograph of a wheel of the vehicle before loading. whose subsequent processing will be similar to that detailed in Figure 4 for steps (ii.1) to (ii.8). Additionally, the vehicle identification may include determining an angle of inclination of the vehicle prior to loading (step i.2). This tilt measurement will preferably be made along the X axis of the vehicle, that is to say along the longitudinal axis of the vehicle, between the terrestrial reference (linked to the gravity) and the vehicle mark (linked to the vehicle ). To do this, the intelligent communication device will preferably be positioned on a location in the vehicle provided for this purpose, for example in the form of a docking station whose orientation is known. In a second step (ii), the user is invited to take a photograph of at least one wheel of his vehicle after loading. Preferably, the user is prompted to take a photograph of a wheel located on the load space side. Thus, for most -8 vehicles, the loading space being located at the rear of the vehicle, the user will be asked to take a photograph of a rear wheel of his vehicle. This photograph is then processed according to an image processing method the details of which are given in relation to FIG. 4. On the basis of the image processing performed, the application determines the travel of the wheel of the photographed wheel, namely in general the movement of the rear axle. During a third step (iii), the user will preferably position the intelligent communication device in his docking station to perform at least one measurement of the inclination along the X axis of the vehicle between the terrestrial reference frame and the vehicle mark after loading the vehicle. To this end, the communication device must be positioned correctly on the location to ensure that the inclination measured is that along the X axis of the vehicle. If a similar measurement has been done before loading during the vehicle identification, this will make it possible to accurately calculate the difference in inclination before and after loading, in order to compensate for any inclination of the ground on which the vehicle is parked when it is parked. loading. On the basis of the inclination measured after loading and advantageously before and after loading, the application determines the travel of the opposite train to that of the wheel photographed, for example the nose gear. In a fourth step (iv), the application calculates the load value on the front and rear trains of the vehicle and deduces the total load value of the vehicle by adding the two loads. This total charge value can then be displayed by the communication device. During a fifth step (y), the application controls the graphic and / or audio interface of the communication device to warn the user about the state of charge of the vehicle. For example, the communication device displays a red alert if the mass is greater than 0.95 * massemax, where massemax is a calibration constant corresponding to the maximum allowed load. The device displays a yellow -9 alert if the mass is between 0.8 * massemax and 0.95 * massemax. The device displays a green alert if the mass is less than 0.8 * massemax. Levels 0.8 and 0.95 are 2 thresholds which are also calibration parameters. They can of course be modified as needed. The number of alert levels can vary and depend on the type of application. It is also possible to display the overload probability or the load and the 95% or 99% confidence interval (for example). Figure 3 shows schematically the movement of the front wheel sets AAv and rear AARR following the loading of the vehicle. In the example shown in the figure, the vehicle is parked on a horizontal ground. The vehicle is shown diagrammatically by two points representing the center of front wheel CRAv and rear CRARR of the vehicle, as well as by the wheel arch centers of the vehicle before CPAv and rear CPARR, these points to determine the deflections of the trains of the vehicle. However, it will be understood that other points of the vehicle could be considered as the centers of wheel arches, other points which would be made to sink together with the suspension of the wheel during the loading of the vehicle. The distance between the CRAv and CRARR front wheel centers of the vehicle is the wheelbase L of the vehicle.
    [0004] Furthermore, generally speaking, by travel, the distance corresponding to the vertical oscillation of an axle relative to the chassis, due to the flexibility of the suspension during loading. In the rest of this example, the deflection will correspond to the vertical oscillation of the wheel arch center with respect to the corresponding wheel center.
    [0005] Before loading, the identification makes it possible to determine, in particular, the rear distance before loading between the wheel center CRARR and the wheel arch center CPARR, in particular in the case where the loading space is situated at the rear of the vehicle, as well as that eventually the angle of inclination along the X axis of the vehicle between the terrestrial reference and the vehicle mark 30 if it is non-zero. This measurement can be automatically performed and recorded by the intelligent communication device if the latter detects a non-zero inclination during the initial identification step. During step (iii), which will be detailed hereinafter with reference to FIG. 4, the communication device determines the rear distance after loading between the CRARR wheel center and the CPARR wheel arch center which has pressed. During step (iv), the communication device calculates the movement of the train opposite to the wheel photographed, that is to say the nose gear in our example. To do this, the communication device is preferably placed in the docking station provided for this purpose in the vehicle. When the communication device is in the predefined position, then it can automatically or manually (i.e. on the action of the user) perform a measurement of the inclination of the vehicle. Thus for example, for 3 seconds the average communication device the 3 components measured by its accelerometer. We obtain the values gxiPh, gyiPh and gziPh. In the case where the communication device falls during the 3 seconds of measurement, at least one of the components of the acceleration exceeds 1.5g, and it is then estimated that the device has moved and the measurement must be redone. The same can be done if one of the angular velocities exceeds in absolute value the threshold of 0.1 rad / s. Advantageously, the communication device displays a progress bar during the measurement. During this measurement, it must also verify that the communication device is held in the correct direction, which can result in a negative value of the gyiPh and gziPh parameters. .
    [0006] When the calculation is complete, the communication device estimates the angle of inclination after loading (laps along the X axis of the vehicle between the terrestrial reference and the vehicle mark by calculating for example: 04, = 0.5 (a cosIgyiP + a The communication device then deduces the distance before after loading, between the center of wheel CRAv and the center of wheel well CPAv which is depressed by application of the following formula: In the case where 'we want to take into account the slope of the ground, we can use the following general formula: where aavc is the inclination before loading defined during the identification of the vehicle.It is the wheelbase of the vehicle also defined at the time of the 4 shows a detailed diagram of the step (ii) of taking and processing images according to a preferred embodiment of the invention As has been indicated above, the user is invited to r the application to take a photograph (step ii.0) of at least one wheel of its vehicle, for example a rear wheel. The taking of photographs will be carried out under conditions as shown in FIG. 5, ie when the measurements of the accelerometers that it comprises indicate an almost zero component, a component z <0 and a component y <0 (non-inverted telephone) . The x, y and z components of the intelligent communication device are shown in FIGS. 5 and 8. A light and / or sound and / or vibration signal can indicate to the user the verification of these conditions so that it can trigger the capture. of view. Alternatively, an automatic shooting of the photograph can be provided when the conditions are satisfied.
    [0007] Two cases then arise: the case in which the component z is almost zero (not shown, where the communication device is in a vertical position), then the acquired image is that represented in FIG. 6A this configuration makes it possible to have a direct measurement of the distances between the - 12 different points after image processing, but this forces the user to make the optical axis of the camera coincide with that of the center of the wheel where the component z> 0 (FIG. 5), then the acquired image is that represented in FIG. 6B, this configuration introduces a distortion of the acquired image and consequently does not allow to have a direct measurement, this situation is a more ergonomic situation for the user because the photo can be taken upright. As shown in FIG. 5, the acquisition of an image comprising at least one point A of the vehicle that is made to sink together during the loading of the vehicle with the suspension of the vehicle wheel and several points of wheel B, C , D, E, F (the points E and F are not shown in Figure 5 for reasons of clarity) is on a plane y ', which is the focal plane of the camera 20. The plane y It is not parallel to the vertical plane on which the points are aligned, which induces the effect of disortion of the image, as represented in FIG. 6B. The points acquire in this way, on the plane y ', are instantiated B', C ', D', E ', F' in FIG. 6B. Then, the communication device starts processing the photograph of the rear wheel made by the user so as to calculate the movement of the corresponding suspension. Once the photograph is taken, if the communication device does not offer the possibility to take the grayscale photography directly, then the photograph is transformed into gray scale. (step ii.1, only if necessary) This transformation can be carried out for example with the following weights applied on each RGB level of the signal: gray image = 0.3 * photo red + 0.59 * photo green + 0.11 photo blue; where photo_red is the red light intensity, photo_green is the green light intensity, and photo_blue is the blue light intensity. Once the image is transformed into a gray scale, the processing begins with a blurring of the image with a Gaussian type filter (step ii.2). This treatment reduces artificial image gradients, defects, etc. Next, a "Sobel" filtering (step ii.3) is applied which calculates the derivative of the image in the width and height direction and then combines them. This treatment makes it possible to obtain the contours present in the image. In the following, the image is broken down into two parts: the wheel well and the wheel (step ii.4). With the cut of the wheel arch is calculated by least squares 10 (step ii.5) the circle that contains the points that constitute the contour. The center and radius of the wheel well are thus obtained in pixels. We thus deduce the point A '. With the cutting of the wheel we begin by calculating the "map direction", which is a matrix that contains the normal directions at the intensity gradient calculated during Sobel filtering. Then we accumulate in the image the points in the direction indicated by this vector and whose distance varies between r_min and r_max. These values r_min and r_max are calculated (step ii.6) by virtue of the value of the radius of the wheel well estimated in the preceding step in pixels and the theoretical ratio RJ / pR (known) between the radius of the rim and the rim. wheel arch radius. We thus deduce the points B ', D'. Processing is continued by filtering the resulting image with a mexican hat or wavelet Mexican hat filter (step ii.7), similar to a cardinal sinus. This improves the concentration of points near the center of the wheel. The center of the rouen is then calculated (step ii.8) based on the accumulation of points in the wheel center. We thus deduce the point C '. In the context of the present invention, other image processing can be used to define the wheel center as well as the wheel center. At this stage, it is possible to know the value of the travel C'A '5 with the distortion off this value is not the actual value of the travel. To do so, we apply biraport, theory of invariants in Euclidean geometry. An invariant of a given transformation is a property that remains unchanged if the transformation in question is applied one or more times. For example, in the context of Euclidean geometry, the distance is an invariant with respect to a transformation of rotation or translation type. Likewise, the angle is also an invariant in Euclidean geometry with respect to translations and rotations. In the context of the algebra of projections-type transformations, one of the invariants is the birapport. Let 4 points be aligned P "P2'P3 and P4, the double ratio (crossratio in English) is defined as: fl 031 P2 P3 P4) Pi P3 - P2 P4 PP4 P2 P3 We are going to use the birapport that we have defined above. By expressing its value in the projected image and in the plane of the wheel, we get: ## EQU1 ## Moreover, we know that the birapport is an invariant of the projections-type transformations hence:, e (D ', A'). =, e (D, C, B, A) - Thus, D 'B', C 'A' DB 'CA D' A '' C 'B' DA CB The birapport / 3 () '' is calculated C'B''A ') which will be called P. It is also known that DB = 2R, that CB = R and that DA = 2R + CA Which gives us the following equation: 2R, CA P - ( R + CA) R Which finally allows us to find again the distance between the center of the wheel and the high point of the wheel arch on the plane of the wheel: C7 - PR 2 - P 10 The computation of the birapport is particularly advantageous because it does not require time calculation too important, unlike other image processing method with distortion. To conclude the treatment we calculate the distance in pixels between the wheel center and the center of the wheel well and it is converted into meters 15 thanks to the ratio between the radius of the wheel arch in pixels and meters (the theoretical). The experimental results are shown in Figure 7B. The result of the calculations is the distance daaprcr between the center of the wheel and the center of the wheel arch after loading. The more the vehicle is loaded, the lower the distance. Therefore, an initial step of calibration in the factory makes it possible to establish a map giving this distance daaprcr according to a known weight of the vehicle, allowing, subsequently to know this weight by the estimate of apc - 16 We can imagine more advanced versions of the application, in which the user is asked to take a picture of the two rear wheels to calculate a distance d aa pr ci- that is the average between the two wheels.
    [0008] However, in order to take account of aging, and in particular creep phenomena in the connection between the chassis and the suspensions, the application then deduces (step ii.9) the displacement of the rear axle by performing the following operation Ad = d stop arrc ic darr or, avc represents the back distance before loading (unladen). This value will be deducted during the vehicle identification phase: for example either by asking the user to take a picture of the empty vehicle, or by having access to a database and interrogating it with the identifier. of the vehicle.
    [0009] The user may be required to regularly take a picture of the unladen vehicle (for example once or twice a year), in order to take account of variations in this empty distance essentially related to the aging of the different elements of the suspensions. Figure 7A shows an example of the law load / deflection of a wheel suspension for a predefined model of vehicle. The value of rear deflection obtained at the end of the processing step (ii) makes it possible during the step to calculate by interpolating in a map (as for example that represented in FIG. 7A) the value of the load on the rear axle.
    [0010] This figure shows a hysteresis: when the vehicle is loaded progressively, the deflection follows the curve al, whereas when the vehicle is unloaded, the relation follows the curve a2. In order to limit the uncertainties, the median curve, shown in dashed lines, is used. According to another embodiment of the invention, the user is asked to take a picture of the four wheels of the vehicle, which makes it possible to increase the accuracy of the mass estimation, by a better evaluation of the loading conditions in particular.
    [0011] The photographic taking of each of the wheels and the image processing as it has been defined, or any other image processing leading to the determination of the centers of wheels and wheel-passing centers, then make it possible to determine for each train , the travel of each wheel. During the identification of the vehicle, if a determination of the displacement of each wheel is provided, thus requiring the photographic catch of each of the wheels, it is then no longer necessary to determine the longitudinal and transverse inclination angles of the vehicle, the unloaded travel of each of the wheels being then only related to the known characteristics of the vehicle, and the slope of the road, which can therefore be easily determined, for example by interpolation of the known deflections on flat ground. A simplified variant consists in measuring only one of the wheels of each train for determining the travel of the trains. It will be understood that various modifications and / or improvements evident to those skilled in the art can be made to the various embodiments of the invention described herein without departing from the scope of the invention defined by the appended claims. In particular, the identification of the vehicle may be based on the use of VIN (for "Vehicle Identification Number"), which is the unique alphanumeric code 25 given to each vehicle. The use of the VIN can be used to obtain, from a centralized server, the parameters necessary for the various calculations. This VIN could be obtained by a request sent by the intelligent communication device to the car, for example via the OBD diagnostic interface (for "On Board Diagnostic"), the response - 18 can then be transmitted in turn to a database, which would return the necessary parameters to the various calculations. Moreover, in order to improve the accuracy of the device, during the vehicle identification step (step (iii)), the user is asked to position the intelligent communication device in his station. home to perform at least one measurement of the inclination along the X axis of the vehicle between the terrestrial mark and the vehicle mark before the vehicle is loaded, it is also advantageous to determine the inclination along the Y axis of the vehicle (inclination transverse), in order to correct the subsequent 10 determinations of the distance between the wheel center and the wheel center from this inclination. Advantageously, when determining the inclination after loading along the X axis, it will also be possible to determine the inclination along the Y axis, this determination advantageously coupling with the measurement of a single wheel of each train. Thus, the difference of inclination is measured with more precision. The inclination along the Y axis of the vehicle may be due to a sloping ground, but may also occur when the vehicle is parked with one of the wheels, or both wheels on the same side, arranged on one sidewalk, the other two wheels being on the roadway.
    权利要求:
    Claims (9)
    [0001]
    REVENDICATIONS1. A method of estimating the mass of a motor vehicle comprising a front wheel train and a rear wheel train, by means of an intelligent communication device, after loading the vehicle, the method comprising the steps of: i) identify the vehicle in the intelligent communication device; (ii) taking and processing, by means of a camera of the intelligent communication device, a photograph of at least one wheel with at least one point of the vehicle being allowed to sink together during the loading of the vehicle with the suspension of the wheel of the vehicle, after loading, to determine the movement of the wheel train photographed according to the identified vehicle, the taking of a photograph of a wheel is subordinate to the maintenance of the phone in a plane perpendicular to the plane of the wheel photographed except in the vertical position of the phone; (iii) determining the displacement of the train opposite to the wheel photographed in step (ii), either by measuring the angle of inclination of the vehicle after loading, by means of at least one accelerometer or inclinometer of the device intelligent communication device, either by taking and processing, by means of the camera of the intelligent communication device, a photograph of at least one wheel with at least one point of the vehicle which is sinking together during the loading the vehicle 25 with the suspension of a wheel of the train opposite the wheel train photographed in step (ii); (iv) calculating, by means of a computing unit of the intelligent communication device, the load value on the train of the wheel photographed and the load value on the opposite train as a function of the respective deflection of these trains, for determine the total load value of the vehicle; (v) inform the user by means of the intelligent communication device of the state of charge of the vehicle.
    [0002]
    2. A method for estimating the mass of a vehicle according to claim 1, wherein the processing of the photograph comprises at least one step of calculating an invariant.
    [0003]
    3. Method for estimating the mass of a vehicle according to claim 1 or 2, characterized in that the calculation of the invariant is a birapport performed on at least one point of the wheel and at least one point of the vehicle. brought to sink together when loading the vehicle with the suspension of the vehicle wheel.
    [0004]
    4. A method for estimating the mass of a vehicle according to one of claims 1 to 3, characterized in that the step (i) of identifying the vehicle comprises the steps of: (i.1) determining before loading the distance between the wheel center and the wheel well center of the wheel to be photographed in step (ii); (i.2) determine the angle of inclination of the vehicle before loading; (I.3) determine the total permissible load of the identified vehicle.
    [0005]
    5. Method for estimating the mass of a vehicle according to one of claims 1 to 4, characterized in that the step (ii) of setting and image processing comprises the following substeps consisting of: .0) take a photograph of a vehicle wheel; (Ii.1) transforming the captured wheel photograph into a grayscale image; (ii.2) applying a first Gaussian blur filter to improve the image sharpness quality; (ii.3) applying a second Sobel filter to obtain the contours of the image; -21 (ii.4) decomposing the image into two parts, a first part relating to the wheel and a second part relating to the tire tracks ; (ii.5) calculate the center and radius of the wheel arch by the least squares method; (ii.6) calculating the minimum and maximum radius values of the wheel according to the radius of the wheel well and the identified vehicle; (ii.7) applying a third Mexican wavelet-type filter to improve the concentration of points near the center of the wheel; (ii.8) calculate the center of the wheel based on the accumulation of points in the center of the wheel, calculate the distance after loading between the wheel center and the center of the wheel well, calculate the ratio of at least one point of the wheel and of said at least one point of the vehicle being allowed to sink together during the loading of the vehicle with the suspension of the vehicle wheel; (ii.9) calculate the clearance of the wheel train photographed by the difference in distance between the wheel center and the wheel center after and before loading.
    [0006]
    6. Method for estimating the mass of a vehicle according to one of claims 1 to 5, characterized in that the step (iii) of determining the displacement of the opposite train is based on a measurement of the difference of the weight of the vehicle. angle of inclination of the vehicle before and after loading, the angle of inclination being chosen as the angle between an earth marker and a vehicle mark along the X axis of the vehicle.
    [0007]
    7. Method for estimating the mass of a vehicle according to one of claims 1 to 6, characterized in that during step (iii) of measuring the angle of inclination, any detection of an acceleration beyond a certain predefined threshold is considered as a fall of the intelligent communication device, the measurement step (iii) to be repeated.
    [0008]
    8. Method for estimating the mass of a vehicle according to one of claims 1 to 7, characterized in that the step (iv) of calculating the value-22 of load on the front and rear wheel trains is obtained by interpolation in a load / deflection map.
    [0009]
    An intelligent communication device (10) configured to enable implementation of the method according to any of the preceding claims, characterized in that the intelligent communication device comprises - a programmed application (14) adapted to activate a method for estimating the mass of a vehicle, - a man-machine interface (16) adapted to launch the vehicle mass estimation application, vehicle identification means, - a camera ( 20) adapted to take a photograph of at least one wheel with at least one point of the vehicle collectively sinking when loading the vehicle with the suspension of the vehicle wheel, - at least one accelerometer (22) and or inclinometer (24) adapted to measure an angle of inclination between the terrestrial reference and the vehicle mark, - a calculation unit (12) programmed to perform image processing steps and for calculating travel values and load values including at least one calculation step of at least one invariant, and at least one graphic and / or sound interface (26) adapted to warn the user of the state of charge of his vehicle. 25
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    US10060782B2|2018-08-28|
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    法律状态:
    2015-12-21| PLFP| Fee payment|Year of fee payment: 3 |
    2016-12-22| PLFP| Fee payment|Year of fee payment: 4 |
    2017-12-21| PLFP| Fee payment|Year of fee payment: 5 |
    2018-12-19| PLFP| Fee payment|Year of fee payment: 6 |
    2020-10-16| ST| Notification of lapse|Effective date: 20200910 |
    优先权:
    申请号 | 申请日 | 专利标题
    FR1362176A|FR3014557B1|2013-12-05|2013-12-05|METHOD FOR ESTIMATING THE MASS OF A VEHICLE|FR1362176A| FR3014557B1|2013-12-05|2013-12-05|METHOD FOR ESTIMATING THE MASS OF A VEHICLE|
    EP14814945.3A| EP3077780B1|2013-12-05|2014-11-24|Method for estimating the mass of a vehicle|
    US15/101,253| US10060782B2|2013-12-05|2014-11-24|Method for estimating the mass of a vehicle|
    CN201480065493.5A| CN105814415B|2013-12-05|2014-11-24|Method for estimating vehicle mass|
    PCT/FR2014/053008| WO2015082797A1|2013-12-05|2014-11-24|Method for estimating the mass of a vehicle|
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