Parameter estimation system and driving diagnostic system

Abstract

To provide a parameter estimation system, and the like, configured to improve the accuracy of estimating a parameter.SOLUTION: A parameter estimation system for estimating a parameter corresponding to at least one of acceleration and angular velocity includes: an inertial sensor which is disposed inside a mobile body to acquire a parameter in a first coordinate system, to be output as first parameter data; and an arithmetic unit which estimates a parameter in a second coordinate system, which is a coordinate system of the mobile body, on the basis of the first parameter data of the first coordinate system output from the inertial sensor, and outputs the parameter as second parameter data. The arithmetic unit performs arithmetic processing so that correlation between a plurality of coordinate axes in the second coordinate system may be minimized, on the basis of the first parameter data, to generate the second parameter data.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present disclosure relates to a parameter estimation system and a driving diagnosis system. [Background technology]

[0002] BACKGROUND ART Various technologies have been disclosed as systems for estimating various parameters (for example, acceleration, angular velocity, etc.) related to moving bodies (for example, various vehicles and aircraft) (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-71326 Summary of the Invention [Problem to be solved by the invention]

[0004] In such a parameter estimation system, for example, it is required to improve the accuracy of parameter estimation. It is desirable to provide a parameter estimation system capable of improving the accuracy of parameter estimation, and a driving diagnosis system including such a parameter estimation system. [Means for solving the problem]

[0005] A parameter estimation system according to an embodiment of the present disclosure is a system for estimating a parameter corresponding to at least one of acceleration and angular velocity, and includes an inertial sensor installed inside a moving body, which acquires the parameter in a first coordinate system and outputs it as first parameter data, and a calculation unit which estimates a parameter in a second coordinate system, which is a coordinate system of the moving body, based on the first parameter data in the first coordinate system output from the inertial sensor, and outputs it as second parameter data. The calculation unit generates the second parameter data by performing calculation processing based on the first parameter data so as to minimize correlation between multiple coordinate axes in the second coordinate system.

[0006] A driving diagnosis system according to one embodiment of the present disclosure includes the parameter estimation system according to the embodiment of the present disclosure and a diagnosis unit that performs a diagnosis regarding driving of a moving object based on the second parameter data output from the calculation unit. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a schematic diagram illustrating an example of a general configuration of a vehicle to which various systems according to an embodiment of the present disclosure are applied. [Figure 2] FIG. 2 is a block diagram illustrating an example of a detailed configuration of the vehicle and electronic devices illustrated in FIG. [Figure 3] FIG. 3 is a schematic diagram illustrating an example of a coordinate system in the electronic device shown in FIG. [Figure 4] FIG. 4 is a schematic diagram illustrating an example of a coordinate system in the vehicle shown in FIG. [Figure 5] FIG. 5 is a flowchart illustrating various processing examples according to the embodiment. [Figure 6] FIG. 6 is a block diagram showing an example of the configuration of a vehicle, an electronic device, and a server according to a modified example. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. The description will be made in the following order. 1. Embodiment (Example of a case where a calculation unit is built into an electronic device installed inside a vehicle) 2. Modification (Example of a case where a computing unit is built into a server provided outside a mobile object) 3. Other Modifications

[0009] <1. Embodiment> [composition] Fig. 1 is a schematic diagram illustrating an example of the overall configuration of a vehicle 1 to which various systems (a parameter estimation system and a driving diagnosis system described later) according to an embodiment of the present disclosure are applied. Fig. 2 is a block diagram illustrating an example of the detailed configuration of the vehicle 1 and electronic devices (electronic device 8 described later) shown in Fig. 1. Fig. 3 is a schematic diagram illustrating an example of a coordinate system (an xyz coordinate system described later) in the electronic device 8, and Fig. 4 is a schematic diagram illustrating an example of a coordinate system (an XYZ coordinate system described later) in the vehicle 1.

[0010] 1 and 2, the vehicle 1 includes a vehicle control unit 11, a battery 12, and a communication device 13. As shown in Fig. 1, an electronic device 8 is installed in a predetermined position inside the vehicle 1. The electronic device 8 is, for example, a device owned by or loaned to a user 9 of the vehicle 1 (such as a passenger including the driver), and is configured, for example, as a smartphone, a tablet, or the like.

[0011] The electronic device 8 includes, for example, an inertial sensor 811, a magnetic sensor 812, a calculation unit 82, a diagnosis unit 83, a display unit 841, an audio output unit 842, and a communication device 85, as shown in FIG.

[0012] Here, vehicle 1 corresponds to a specific example of a "mobile body" in an embodiment of the present disclosure. Also, inertial sensor 811 and calculation unit 82 (parameter estimation unit 821 and parameter correction unit 823 described below) correspond to a specific example of a "parameter estimation system" in an embodiment of the present disclosure. Inertial sensor 811, calculation unit 82, and diagnosis unit 83 correspond to a specific example of a "driving diagnosis system" in an embodiment of the present disclosure.

[0013] (A. Vehicle control unit 11, battery 12, communication device 13) The vehicle control unit 11 is a component (control unit) that controls various operations in the vehicle 1 and performs various arithmetic processing. Specifically, the vehicle control unit 11 includes, for example, one or more processors (CPU: Central Processing Unit) that execute programs, and one or more memories communicably connected to these processors. Furthermore, such memories include, for example, RAM (Random Access Memory) that temporarily stores processing data, and ROM (Read Only Memory) that stores programs.

[0014] (Vehicle control unit 11) In the example shown in FIG. 2, the vehicle control unit 11 includes a driving control unit 111, a battery control unit 112, a communication control unit 113, and an information acquisition unit 114.

[0015] The driving control unit 111 is a unit that controls the driving operation of the vehicle 1, and performs overall control regarding the driving of the vehicle 1. Specifically, the driving control unit 111 controls, for example, the drive system, braking system, steering system, and the like of the vehicle 1.

[0016] The battery control unit 112 is a unit that controls the operation (charging operation, discharging operation, etc.) of the battery 12, which will be described later. The communication control unit 113 is a unit that controls the communication operation of the communicator 13, which will be described later.

[0017] The information acquisition unit 114 is a unit that acquires various information (vehicle data) related to the vehicle 1. Examples of such vehicle data include the vehicle identification number of the vehicle 1, driving information (travel distance, image data of the surroundings of the vehicle 1, etc.), etc.

[0018] (Battery 12, communication device 13) The battery 12 is a component that functions as a power source for the vehicle 1, and is configured using various types of secondary batteries such as lithium ion batteries. The communicator 13 is a device that performs various types of communication with the outside of the vehicle 1 (for example, an information processing device such as a server, or other vehicles other than the vehicle 1).

[0019] (B.Electronic equipment 8) The inertial sensor 811 is installed inside the vehicle 1, and in the example shown in FIGS. 1 and 2, it is built into the electronic device 8 (described above) installed inside the vehicle 1. This inertial sensor 811 is a sensor that acquires a predetermined parameter Pr in a predetermined coordinate system (an xyz coordinate system described below) and outputs it as parameter data Dp1. The predetermined parameter Pr may be, for example, a parameter corresponding to at least one of acceleration and angular velocity.

[0020] 3, for example, in a case where the inertial sensor 811 is built into the electronic device 8, the coordinate system of this inertial sensor 811 is defined as an xyz coordinate system having multiple coordinate axes (x-axis, y-axis, z-axis). In the example of Fig. 3, the x-axis (axis along the long axis direction of the electronic device 8) is defined as the roll axis, the y-axis (axis along the short axis direction of the electronic device 8) is defined as the pitch axis, and the z-axis (axis along the thickness direction of the electronic device 8) is defined as the yaw axis.

[0021] The parameter data Dp1 described above corresponds to a specific example of "first parameter data" in an embodiment of the present disclosure. Also, the coordinate system (xyz coordinate system) of the inertial sensor 811 described above corresponds to a specific example of "first coordinate system" in an embodiment of the present disclosure.

[0022] The magnetic sensor 812 is installed inside the vehicle 1, and in the example shown in Figures 1 and 2, it is built into the electronic device 8, similar to the inertial sensor 811. This magnetic sensor 812 is a sensor that acquires and outputs parameter data (magnetic data) other than the above-mentioned parameter Pr.

[0023] The magnetic sensor 812 corresponds to a specific example of "another sensor" in an embodiment of the present disclosure. The magnetic data described above corresponds to a specific example of "another parameter data" in an embodiment of the present disclosure.

[0024] (Computation unit 82) The arithmetic unit 82 is a component (arithmetic unit) that performs various types of arithmetic processing in the electronic device 8. Specifically, the arithmetic unit 82 includes, for example, one or more processors (CPUs) that execute programs, and one or more memories communicably connected to these processors. Such memories are also configured, for example, by RAM that temporarily stores processing data, ROM that stores programs, etc.

[0025] In the example shown in FIG. 2, the calculation unit 82 includes a parameter estimation unit 821 and a parameter correction unit 823.

[0026] The parameter estimation unit 821 is a unit that estimates parameters Pr in the coordinate system of the vehicle 1 (XYZ coordinate system described below) based on parameter data Dp1 (xyz coordinate system) output from the inertial sensor 811 and outputs it as parameter data Dp2.

[0027] Here, for example, as shown in Fig. 4, the coordinate system of this vehicle 1 is defined as an XYZ coordinate system having multiple coordinate axes (X-axis, Y-axis, Z-axis). In the example of Fig. 4, the X-axis (axis along the front-rear direction of the vehicle 1) is defined as the roll axis, the Y-axis (axis along the width direction of the vehicle 1) is defined as the pitch axis, and the Z-axis (axis along the height direction of the vehicle 1) is defined as the yaw axis.

[0028] The parameter data Dp2 described above corresponds to a specific example of "second parameter data" in an embodiment of the present disclosure. Also, the coordinate system (XYZ coordinate system) of the vehicle 1 described above corresponds to a specific example of "second coordinate system" in an embodiment of the present disclosure.

[0029] The parameter estimation unit 821, the details of which will be described later, performs an estimation process for parameter data Dp2 (XYZ coordinate system) based on parameter data Dp1 (xyz coordinate system). Furthermore, when a predetermined condition, which will be described later, is satisfied, the parameter estimation unit 821 performs a calculation process based on the parameter data Dp1 (xyz coordinate system) so as to minimize the correlation between multiple coordinate axes (X-axis, Y-axis, and Z-axis in the example of FIG. 4) in the XYZ coordinate system. The parameter data Dp2 (XYZ coordinate system) is generated by such a calculation process. Note that the phrase "so as to minimize" here refers to a concept that includes error variations and the like during various calculations, which will be described later. Furthermore, in the example shown in FIG. 2, the parameter estimation unit 821 includes an analysis unit 821a, a correlation calculation unit 821b, and a conversion unit 821c.

[0030] The analysis unit 821a is a unit that determines a first coordinate axis (for example, Z axis: yaw axis) in the XYZ coordinate system by performing a predetermined analysis, which will be described later, based on the parameter data Dp1 (xyz coordinate system).

[0031] The correlation calculation unit 821b is a unit that determines the second and third coordinate axes in the XYZ coordinate system by performing a predetermined calculation process (correlation calculation process) while the first coordinate axis determined by the analysis unit 821a is fixed. Specifically, the correlation calculation unit 821b performs the calculation process so that the correlation between the first coordinate axis (e.g., Z axis: yaw axis) and the second coordinate axis (e.g., Y axis: pitch axis) and the third coordinate axis (e.g., X axis: roll axis) is minimized as described above.

[0032] The conversion unit 821c is a unit that converts parameter data Dp1 (xyz coordinate system) into parameter data Dp2 (XYZ coordinate system) using an XYZ coordinate system having first to third coordinate axes (Z-axis, Y-axis, X-axis) determined by the analysis unit 821a and the correlation calculation unit 821b. In other words, the conversion unit 821c performs a conversion process from parameter data Dp1 to parameter data Dp2.

[0033] Here, the Z axis (yaw axis) in the above-described XYZ coordinate system corresponds to a specific example of the "first coordinate axis" in one embodiment of the present disclosure. The Y axis (pitch axis) corresponds to a specific example of the "second coordinate axis" in one embodiment of the present disclosure, and the X axis (roll axis) corresponds to a specific example of the "third coordinate axis" in one embodiment of the present disclosure. However, this example is not limiting, and for example, other combinations of the "first coordinate axis," "second coordinate axis," and "third coordinate axis" in one embodiment of the present disclosure with the X axis, Y axis, and Z axis may also be used.

[0034] The parameter correction unit 823 is a unit that performs correction processing on other parameter data acquired by other sensors, using parameter data Dp2 (XYZ coordinate system) estimated based on parameter data Dp1 (xyz coordinate system) in the parameter estimation unit 821. Specifically, in the example of Fig. 2, the parameter correction unit 823 performs correction processing (parameter correction processing) on ​​magnetic data acquired by the magnetic sensor 812, using the estimated parameter data Dp2.

[0035] (Diagnosis Section 83) The diagnosis unit 83 is a unit that performs diagnostic processing (driving diagnostic processing) related to the driving of the vehicle 1 based on the parameter data Dp2 (XYZ coordinate system) output from the parameter estimation unit 821. The results of the driving diagnostic processing by the diagnosis unit 83 are provided to the user 9 of the vehicle 1 (such as passengers including the driver) via, for example, a display unit 841 and an audio output unit 842, which will be described below.

[0036] In addition, like the calculation unit 82 described above, such a diagnosis unit 83 is also configured to include, for example, one or more processors (CPUs) that execute programs and one or more memories that are communicatively connected to these processors.

[0037] (Display unit 841, audio output unit 842, communication device 85) The display unit 841 is a member that displays various types of information. The display unit 841 is configured using various types of displays (for example, a liquid crystal display, an organic EL (Electro-Luminescence) display, etc.).

[0038] The audio output unit 842 is a member that outputs various types of audio, and is configured using, for example, various types of speakers.

[0039] The communicator 85 is a device that performs various communications with the outside of the electronic device 8 (for example, an information processing device such as a server, a communication base station, the vehicle 1, etc.).

[0040] [Operation, Actions and Effects] Next, the operation, functions, and effects of this embodiment will be described in detail.

[0041] (A. General parameter estimation methods) First, in a typical parameter estimation method (a conventionally known method), vehicle parameters (such as acceleration and angular velocity) are acquired using an inertial sensor built into an electronic device installed inside the vehicle as follows. That is, in this conventional method, when the vehicle is on a horizontal plane, a transformation matrix (rotation matrix) is calculated to convert the three-axis parameters acquired by the inertial sensor when the vehicle is stopped and traveling straight into three-axis parameters of the vehicle. Then, this transformation matrix is ​​used to make the coordinate axes of the inertial sensor correspond to the coordinate axes of the vehicle.

[0042] However, when attempting to obtain data on vehicle parameters (acceleration and angular velocity) based solely on parameter data acquired by an inertial sensor while a vehicle is traveling along an arbitrary course including corners and uphill slopes, this conventional method has the following problems, for example: First, there is a possibility that the above-described transformation matrix cannot be obtained from parameter data acquired by traveling along, for example, the above-described arbitrary course. Furthermore, in order to accurately determine (determine) whether the vehicle is stopped or traveling straight, measurement data such as azimuth angle and GPS (Global Positioning System) is also required. Furthermore, with this conventional method, whenever the attitude (installation state) of the electronic device is changed, it is necessary to acquire (re-measure) the parameter data using an inertial sensor.

[0043] In this way, with conventional methods, the estimation of the above-mentioned parameters may be significantly affected by the vehicle's driving conditions and the attitude (installation state) of the electronic device inside the vehicle, which may result in a decrease in the accuracy of parameter estimation.

[0044] (B. Parameter Estimation Process, etc., of the Present Embodiment) Therefore, in this embodiment, the estimation process of the above-mentioned parameter Pr (parameter data Dp2) is performed, for example, as follows.

[0045] FIG. 5 is a flowchart showing various processing examples (such as the above-described parameter Pr estimation processing) according to this embodiment.

[0046] 5, first, the parameter estimation unit 821 acquires parameter data Dp1 (xyz coordinate system) from the inertial sensor 811 (step S11). Next, the parameter estimation unit 821 determines whether or not the parameter data Dp1 includes parameter data Dp1 acquired when the vehicle 1 is stopped and when the vehicle 1 is traveling straight (step S12).

[0047] Here, if the parameter data Dp1 for when the vehicle 1 is stopped and traveling straight is included (step S12: Y), the following occurs. That is, in this case, the parameter estimation unit 821 estimates the parameter data Dp2 (XYZ coordinate system) using the conventional method described above based on the parameter data Dp1 for when the vehicle 1 is stopped and traveling straight (step S13). On the other hand, if the parameter data Dp1 for when the vehicle 1 is stopped and traveling straight is not included (step S12: N), the following occurs. That is, in this case, the parameter estimation unit 821 estimates the parameter data Dp2 (XYZ coordinate system) using the method of this embodiment described above (a method of minimizing the correlation between multiple coordinate axes in the XYZ coordinate system) based on the parameter data Dp1 acquired in other states of the vehicle 1 (excluding when stopped and traveling straight) (step S14).

[0048] (B-1. Details of the estimation process of the parameter data Dp2 by each method) Here, the details of the estimation process of the parameter data Dp2 by the above-mentioned conventional method and the method of this embodiment will be described below.

[0049] First, when the acceleration a and angular velocity ω are respectively specified as examples of the parameters Pr, a matrix for transforming from the xyz coordinate system (the coordinate system of the inertial sensor 811) to the XYZ coordinate system (the coordinate system of the vehicle 1) is defined as a transformation matrix (rotation matrix) R. Then, in this model, it is assumed that the following equations (1) and (2) hold true for the acceleration a and angular velocity ω.

[0050]

number

[0051] Note that ax, ay, and az are accelerations a in the x-axis, y-axis, and z-axis directions, respectively, and aX, aY, and aZ are accelerations a in the X-axis, Y-axis, and Z-axis directions, respectively. Similarly, ωx, ωy, and ωz are angular velocities ω in the x-axis, y-axis, and z-axis directions, respectively, and ωX (=0), ωY, and ωZ are angular velocities ω in the X-axis, Y-axis, and Z-axis directions, respectively. Also, referring to FIG. 4, the parameters Pr (acceleration a and angular velocity ω) in the X-axis direction (front-rear direction), Y-axis direction (width direction), and Z-axis direction (height direction) of vehicle 1 correspond to the following elements, respectively. X-axis direction parameter Pr: Accelerator operation of vehicle 1 Parameter Pr in the Y-axis direction: Steering operation of vehicle 1 Z-axis parameter Pr: gradient of the road and roughness of the road surface

[0052] (Traditional method) Here, in the estimation process of the parameter data Dp2 by the above-mentioned conventional method (step S13), the parameter estimation unit 821 obtains the above-mentioned transformation matrix (rotation matrix) R as follows.

[0053] Specifically, first, when the above-mentioned XYZ coordinate system is used as a reference, if the angular differences (rotation angles) with respect to the above-mentioned xyz coordinate system are respectively a roll rotation angle α, a pitch rotation angle β, and a yaw rotation angle γ, the transformation matrix R is expressed as shown in the following equation (3).

[0054] Then, when the vehicle 1 is stationary, if the gravitational acceleration G (gravitational accelerations Gx, Gy, Gz in the x-axis direction, y-axis direction, and z-axis direction) is specified, the acceleration acting on the inertial sensor 811 is only the gravitational acceleration G, and therefore, using the following equation (4), the following is obtained: That is, the above-mentioned roll rotation angle α and pitch rotation angle β are each determined, and the vertical direction is known.

[0055] Furthermore, when the vehicle 1 is traveling straight, in addition to the gravitational acceleration G, a longitudinal acceleration (acceleration in the traveling direction of the vehicle 1) M occurs in the inertial sensor 811, and therefore, using the following equation (5), the following is obtained: That is, the remaining yaw rotation angle γ is determined, and the longitudinal direction is known.

[0056]

number

[0057] By determining the roll rotation angle α, pitch rotation angle β, and yaw rotation angle γ in this manner, the transformation matrix R can be calculated using the above equation (3), and the parameter estimation unit 821 uses this transformation matrix R to perform estimation processing of the parameter data Dp2 using a conventional method.

[0058] (Method of this embodiment) On the other hand, in the estimation process of the parameter data Dp2 according to the method of this embodiment (step S14), the parameter estimation unit 821 performs the estimation process of the parameter data Dp2 as follows.

[0059] Specifically, in the method of this embodiment, if it is assumed that the elements on each axis in the elements (aX, aY, aZ) on the right side of the above-mentioned formula (1) and the elements (ωX (=0), ωY, ωZ) on the right side of the formula (2) are uncorrelated, the following holds: That is, by uncorrelating the elements (ax, ay, az) on the left side of the formula (1) and the elements (ωx, ωy, ωz) on the left side of the formula (2), it becomes possible to decompose into the form of each right side of the formulas (1) and (2) even when the transformation matrix R described above is unknown.

[0060] Therefore, for example, if the parameter data Dp1 acquired by the inertial sensor 811 is A, it can be expressed as shown in the following equation (6) using, for example, singular value decomposition. Note that (ΣV) in this equation (6) corresponds to the elements on the right-hand sides of equations (1) and (2) (parameter data Dp2 in vehicle 1), and U in equation (6) corresponds to the transformation matrix R described above.

[0061]

number

[0062] In this manner, in the method of this embodiment, the parameter estimation unit 821 performs calculations based on the parameter data Dp1 (xyz coordinate system) so as to minimize the correlation between the multiple coordinate axes (X-axis, Y-axis, Z-axis) in the XYZ coordinate system. Through such calculations, the parameter data Dp2 (XYZ coordinate system) is generated.

[0063] In addition, in the example shown in Figure 2, the parameter estimation unit 821 is configured to perform estimation processing of parameter data Dp2 (XYZ coordinate system) by performing a predetermined analysis (principal component analysis) in the above-mentioned analysis unit 821a, correlation calculation unit 821b, and conversion unit 821c.

[0064] Specifically, the analysis unit 821a determines a first coordinate axis (e.g., Z axis: yaw axis) in the XYZ coordinate system by performing principal component analysis based on the parameter data Dp1 (xyz coordinate system). Next, the correlation calculation unit 821b determines the second and third coordinate axes in the XYZ coordinate system by performing correlation calculation processing while fixing the first coordinate axis determined by the analysis unit 821a. In particular, the correlation calculation unit 821b performs calculation processing so that the correlation between the first coordinate axis (e.g., Z axis: yaw axis) and the second coordinate axis (e.g., Y axis: pitch axis) and the third coordinate axis (e.g., X axis: roll axis) is minimized as described above. Next, the conversion unit 821c converts the parameter data Dp1 (xyz coordinate system) into parameter data (XYZ coordinate system) using the XYZ coordinate system having the first to third coordinate axes (Z-axis, Y-axis, X-axis) determined by the analysis unit 821a and the correlation calculation unit 821b. In other words, the conversion unit 821c performs a conversion process from the parameter data Dp1 to the parameter data Dp2, thereby generating the parameter data Dp2.

[0065] (B-2. Correction of other parameter data Here, after the above-mentioned step S14 (the estimation process of the parameter data Dp2 using the method of this embodiment), the parameter correction unit 823 performs the correction process of the other parameter data described above (step S15). That is, the parameter correction unit 823 uses the parameter data Dp2 (XYZ coordinate system) estimated in step S14 to perform the correction process on the other parameter data (magnetic data, etc.) acquired by the other sensor (magnetic sensor 812, etc.).

[0066] B-3. ​​Driving diagnosis processing After each of the above steps S13 and S15, the diagnosis unit 83 performs a diagnosis process (driving diagnosis process) regarding the driving of the vehicle 1 based on the parameter data Dp2 (XYZ coordinate system) estimated in steps S13 and S15. The results of the driving diagnosis process by the diagnosis unit 83 are provided to the user 9 of the vehicle 1 (such as passengers including the driver) via, for example, the display unit 841 or the audio output unit 842.

[0067] This completes the series of processes shown in FIG.

[0068] (C. Actions and Effects) In this manner, in this embodiment, when estimating the parameters Pr in the coordinate system (XYZ coordinate system) of the vehicle 1 based on the parameter data Dp1 (xyz coordinate system) output from the inertial sensor 811, the following calculation process is performed. That is, the parameter data Dp2 (XYZ coordinate system) is generated by performing calculation process so as to minimize the correlation between multiple coordinate axes (X axis, Y axis, Z axis) in this XYZ coordinate system. As a result, in this embodiment, the influence on the estimation of the parameters Pr caused by the movement status (driving status) of the vehicle 1 and the attitude (installation status) of the electronic device 8 in the vehicle 1 is reduced. As a result, in this embodiment, it is possible to improve the estimation accuracy of the parameters Pr.

[0069] Furthermore, in this embodiment, if there is no parameter data Dp1 acquired when the vehicle 1 is stopped or traveling straight, the parameters Pr are estimated based on the parameter data Dp1 acquired when the vehicle 1 is in another state, and parameter data Dp2 is generated, as follows: That is, even if there is no parameter data Dp1 acquired when the vehicle 1 is stopped or traveling straight (when traveling on an arbitrary course), it is possible to estimate the parameter data Dp2, unlike the conventional method (see step S13 in FIG. 5).

[0070] Furthermore, in this embodiment, parameter data Dp2 (XYZ coordinate system) estimated based on parameter data Dp1 (xyz coordinate system) is used to perform correction processing on other parameter data acquired by other sensors (such as magnetic sensor 812), resulting in the following: That is, since correction processing is performed using parameter data Dp2 estimated in this way, it is possible to improve the accuracy of the data values ​​of the other parameter data described above as well.

[0071] Furthermore, in this embodiment, the diagnosis unit 83 performs a diagnostic process related to the driving of the vehicle 1 based on the parameter data Dp2 output from the parameter estimation unit 821, resulting in the following: That is, since the driving diagnostic process is performed based on the estimated parameter data Dp2 (XYZ coordinate system in the vehicle 1), it becomes possible to provide highly accurate driving diagnostic results to the user 9 of the vehicle 1 (passengers including the driver, etc.).

[0072] <2. Modifications> Next, a modified example of the above embodiment will be described. Note that, in the following, the same components as those in the embodiment will be given the same reference numerals, and the description thereof will be omitted as appropriate.

[0073] Fig. 6 is a block diagram showing a detailed configuration example of a vehicle 1, an electronic device 8A, and a server 2 according to a modified example. In the modified example shown in Fig. 6, electronic device 8A is provided instead of electronic device 8 in the embodiment shown in Fig. 2, and a server 2 is added outside vehicle 1, but the other configurations are basically the same.

[0074] (Electronic equipment 8A) The electronic device 8A is the same as the electronic device 8 shown in FIG. 2 except that it has a calculation unit 82A instead of the calculation unit 82, and does not have (omits) the diagnostic unit 83, but the other configurations are basically the same.

[0075] The calculation unit 82A has a configuration that does not include the parameter estimation unit 821 and the parameter correction unit 823 in the calculation unit 82 shown in FIG. 2, but the other configurations are basically the same.

[0076] (Server 2) The server 2 is an information processing device provided outside the vehicle 1, and includes the parameter estimation unit 821, the parameter correction unit 823, and the diagnosis unit 83 described in the embodiment.

[0077] As shown in FIG. 6, various data are transmitted and received between the server 2 and the electronic device 8A (communication device 85).

[0078] As described above, in the above embodiment, the inertial sensor 811, the calculation unit 82 (parameter estimation unit 821 and parameter correction unit 823), and the diagnosis unit 83 are each built into the electronic device 8 installed inside the vehicle 1, whereas in the present modification, the configuration is as described above. That is, in the present modification, the inertial sensor 811 is built into the electronic device 8A installed inside the vehicle 1, and the parameter estimation unit 821, the parameter correction unit 823, and the diagnosis unit 83 are each built into the server 2 (information processing device) provided outside the vehicle 1.

[0079] Here, in this modification, the parameter estimation unit 821 and the parameter correction unit 823 correspond to a specific example of a "calculation unit" in an embodiment of the present disclosure. Also, in this modification, as in the above embodiment, the inertial sensor 811, the parameter estimation unit 821, and the parameter correction unit 823 correspond to a specific example of a "parameter estimation system" in an embodiment of the present disclosure. Also, in this modification, as in the above embodiment, the inertial sensor 811, the parameter estimation unit 821, the parameter correction unit 823, and the diagnosis unit 83 correspond to a specific example of a "driving diagnosis system" in an embodiment of the present disclosure.

[0080] In this modified example having such a configuration, basically, the same effects as those of the above embodiment can be obtained through the same actions.

[0081] <3. Other Modifications> The present disclosure has been described above by giving embodiments and modifications, but the present disclosure is not limited to these embodiments and can be modified in various ways.

[0082] For example, the configuration (type, arrangement, number, etc.) of each component in the vehicle, electronic device, server, etc. is not limited to that described in the above embodiment. That is, the configuration of each component may be of a different type, arrangement, number, etc. Specifically, for example, in the above embodiment, an example is described in which the "calculation unit" in an embodiment of the present disclosure is built into an electronic device or a server, but the present disclosure is not limited to these examples. That is, for example, the "calculation unit" in an embodiment of the present disclosure may be built into the "mobile body" in an embodiment of the present disclosure itself. Furthermore, the values, ranges, magnitude relationships, etc. of the various parameters described in the above embodiment are not limited to those described in the above embodiment, and other values, ranges, magnitude relationships, etc. may be used.

[0083] Furthermore, in the above embodiments, various processing examples (parameter estimation processing, correction processing, driving diagnosis processing, etc.) have been specifically described, but the methods are not limited to those described in the above embodiments, and other methods may be used, for example.

[0084] Furthermore, in the above embodiment, acceleration and angular velocity have been described as examples of "parameters" in an embodiment of the present disclosure, but other types of parameters may be applied as "parameters" in an embodiment of the present disclosure. Furthermore, in the above embodiment, magnetic sensor 812 and magnetic data have been described as examples of "other sensors" and "other parameters" in an embodiment of the present disclosure, but other types of sensors and parameters may be applied, for example. Furthermore, in the above embodiment, the inertial sensor 811 and the respective coordinate systems (xyz coordinate system and XYZ coordinate system) in vehicles 1 and 1A have been specifically described, but the present disclosure is not limited to these coordinate system examples, and other types of coordinate systems may be applied, for example.

[0085] Additionally, in the above-described embodiments, a vehicle has been described as an example of a "mobile body" in one embodiment of the present disclosure, but the present disclosure is not limited to this example and may be applied to other types of mobile bodies, such as an airplane. Furthermore, in the above-described embodiments, the vehicle 1, 1A is provided with a battery 12 as a power source, i.e., the vehicle 1, 1A is an electric vehicle (EV) or a hybrid electric vehicle (HEV), but the present disclosure is not limited to this example. For example, the vehicle 1, 1A may be a gasoline-powered vehicle or a fuel-powered vehicle.

[0086] Furthermore, the series of processes described in the above embodiments may be performed by hardware (circuits), software (programs), or a combination of hardware and software. When performed by software, the software is composed of a group of programs for causing a computer to execute each function. Each program may be, for example, pre-installed in the computer, or may be installed on the computer from a network or a recording medium.

[0087] Furthermore, the various examples described above may be applied in any combination.

[0088] The effects described in this specification are merely examples and are not limiting, and other effects may also be present.

[0089] The present disclosure can also be configured as follows. (1) 1. A system for estimating a parameter corresponding to at least one of acceleration and angular velocity, comprising: an inertial sensor installed inside the moving body, which acquires the parameters in a first coordinate system and outputs them as first parameter data; a calculation unit that estimates the parameters in a second coordinate system that is a coordinate system of the moving body based on the first parameter data in the first coordinate system output from the inertial sensor, and outputs the estimated parameters as second parameter data; Equipped with The calculation unit generates the second parameter data by performing calculation processing based on the first parameter data so as to minimize correlation between a plurality of coordinate axes in the second coordinate system. Parameter estimation system. (2) The calculation unit an analysis unit that determines a first coordinate axis in the second coordinate system by performing a predetermined analysis based on the first parameter data of the first coordinate system; a correlation calculation unit that performs the calculation process so that the correlation between the first coordinate axis and the second and third coordinate axes in the second coordinate system is minimized while the first coordinate axis is fixed, and determines the second and third coordinate axes, respectively; a conversion unit that converts the first parameter data into the second parameter data using the second coordinate system having the determined first to third coordinate axes; have The parameter estimation system according to (1) above. (3) In the second coordinate system, the first coordinate axis is a yaw axis, and The second and third coordinate axes are the pitch axis and the roll axis, respectively. The parameter estimation system according to (2) above. (4) The calculation unit When there is no first parameter data acquired when the moving body is stopped or moving straight, The parameter is estimated based on the first parameter data acquired in another state of the moving body, and the second parameter data is generated. A parameter estimation system according to any one of (1) to (3) above. (5) The calculation unit using the second parameter data estimated based on the first parameter data, Correction processing is performed on other parameter data acquired by other sensors. A parameter estimation system according to any one of (1) to (4) above. (6) The inertial sensor and the calculation unit are each built into an electronic device installed inside the moving body. A parameter estimation system according to any one of (1) to (5) above. (7) The inertial sensor is built into an electronic device installed inside the moving body, The computing unit is built into a server provided outside the mobile object. A parameter estimation system according to any one of (1) to (5) above. (8) The parameter estimation system according to any one of (1) to (7) above; a diagnosis unit that performs a diagnosis regarding the operation of the moving body based on the second parameter data output from the calculation unit; A driving diagnostic system equipped with [Explanation of symbols]

[0090] 1...vehicle, 11...vehicle control unit, 111...driving control unit, 112...battery control unit, 113...communication control unit, 114...information acquisition unit, 12...battery, 13...communication device, 2...server, 8, 8A...electronic device, 811...inertial sensor, 812...magnetic sensor, 82, 82A...calculation unit, 821...parameter estimation unit, 821a...analysis unit, 821b...correlation calculation unit, 821c...conversion unit, 823...parameter estimation unit, 83...diagnosis unit, 841...display unit, 842...audio output unit, 85...communication device, 9...user, Pr...parameter, Dp1, Dp2...parameter data.

Claims

1. 1. A system for estimating a parameter corresponding to at least one of acceleration and angular velocity, comprising: an inertial sensor installed inside the moving body, which acquires the parameters in a first coordinate system and outputs them as first parameter data; a calculation unit that estimates the parameters in a second coordinate system that is a coordinate system of the moving body based on the first parameter data in the first coordinate system output from the inertial sensor, and outputs the estimated parameters as second parameter data; Equipped with The calculation unit generates the second parameter data by performing calculation processing based on the first parameter data so as to minimize correlation between a plurality of coordinate axes in the second coordinate system. Parameter estimation system.

2. The calculation unit an analysis unit that determines a first coordinate axis in the second coordinate system by performing a predetermined analysis based on the first parameter data of the first coordinate system; a correlation calculation unit that performs the calculation process so that the correlation between the first coordinate axis and the second and third coordinate axes in the second coordinate system is minimized while the first coordinate axis is fixed, and determines the second and third coordinate axes, respectively; a conversion unit that converts the first parameter data into the second parameter data using the second coordinate system having the determined first to third coordinate axes; have The parameter estimation system of claim 1 .

3. In the second coordinate system, the first coordinate axis is a yaw axis; and The second and third coordinate axes are a pitch axis and a roll axis, respectively. The parameter estimation system of claim 2 .

4. The calculation unit When there is no first parameter data acquired when the moving body is stopped or moving straight, The parameter is estimated based on the first parameter data acquired in another state of the moving body, and the second parameter data is generated. The parameter estimation system according to any one of claims 1 to 3.

5. The calculation unit using the second parameter data estimated based on the first parameter data, Correction processing is performed on other parameter data acquired by other sensors. The parameter estimation system according to any one of claims 1 to 3.

6. The inertial sensor and the calculation unit are each built into an electronic device installed inside the moving body. The parameter estimation system according to any one of claims 1 to 3.

7. The inertial sensor is built into an electronic device installed inside the moving body, The computing unit is built into a server provided outside the mobile object. The parameter estimation system according to any one of claims 1 to 3.

8. A parameter estimation system according to any one of claims 1 to 3; a diagnosis unit that performs a diagnosis regarding the operation of the moving body based on the second parameter data output from the calculation unit; A driving diagnostic system equipped with

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