Energy consumption estimation device, energy consumption estimation method, program, and storage medium

Abstract

The present invention provides an energy consumption estimation device that can improve the estimation accuracy when estimating the energy consumption of a moving object. [Solution] The energy consumption estimation device comprises estimation means and parameter acquisition means. The estimation means estimates the energy consumption of a mobile body based on an energy consumption estimation formula that includes first information relating to the energy consumed when the mobile body's drive source is operating and the mobile body is stopped, second information relating to the energy consumed and recovered during acceleration and deceleration of the mobile body, and third information relating to the energy consumed by the resistance generated when the mobile body is running. The parameter acquisition means uses mobile body information relating to the mobile body to acquire a first parameter corresponding to the first information, a second parameter corresponding to the second information, and a third, fourth, and fifth parameter corresponding to the third information.

Description

[Technical Field]

[0001] This invention relates to a technique for estimating the energy consumption of a moving object. [Background technology]

[0002] Techniques have been proposed to estimate the energy consumption of mobile objects.

[0003] Specifically, for example, Patent Document 1 discloses a method for estimating the amount of energy consumed when a moving body travels a travel section, based on an energy consumption estimation formula consisting of first information regarding the energy consumed when the moving body is stopped while the drive source is in motion, second information regarding the energy consumed and recovered when the moving body is accelerating and decelerating, and third information regarding the energy consumed by the resistance generated when the moving body is traveling. [Prior art documents] [Patent Documents]

[0004] [Patent Document 1] Patent No. 4861534 [Overview of the project] [Problems that the invention aims to solve]

[0005] However, according to the perspective disclosed in Patent Document 1, for example, the estimation accuracy when estimating the energy consumption corresponding to each of the multiple mobile bodies may decrease because some information indicating the differences between each of the multiple mobile bodies is not taken into consideration in the energy consumption estimation formula.

[0006] In view of the above-mentioned problems, the main objective of the present invention is to provide an energy consumption estimation device that can improve the estimation accuracy when estimating the energy consumption of a moving object. [Means for solving the problem]

[0007] The invention described in the claim is an energy consumption estimation device comprising: estimation means for estimating the energy consumption of a mobile body based on an energy consumption estimation formula that includes first information relating to the energy consumed when the drive source of the mobile body is operating and the mobile body is stopped, second information relating to the energy consumed and recovered when the mobile body is accelerating and decelerating, and third information relating to the energy consumed by the resistance generated when the mobile body is running; and parameter acquisition means for acquiring a set of parameters using mobile body information relating to the mobile body, including a first parameter corresponding to the first information, a second parameter corresponding to the second information, a third parameter corresponding to the third information, a fourth parameter corresponding to the third information, and a fifth parameter corresponding to the third information.

[0008] Furthermore, the invention described in the claims is a computer-based energy consumption estimation method, which estimates the energy consumption of a mobile body based on an energy consumption estimation formula that includes first information relating to the energy consumed when the mobile body's drive source is operating and the mobile body is stopped, second information relating to the energy consumed and recovered when the mobile body accelerates and decelerates, and third information relating to the energy consumed by the resistance generated when the mobile body is running, and uses mobile body information relating to the mobile body to obtain a set of parameters including a first parameter corresponding to the first information, a second parameter corresponding to the second information, a third parameter corresponding to the third information, a fourth parameter corresponding to the third information, and a fifth parameter corresponding to the third information.

[0009] Furthermore, the invention described in the claim is a program executed by a computer that estimates the energy consumption of a mobile body based on an energy consumption estimation formula that includes first information relating to the energy consumed when the drive source of the mobile body is operating and the mobile body is stopped, second information relating to the energy consumed and recovered when the mobile body is accelerating and decelerating, and third information relating to the energy consumed by the resistance generated when the mobile body is running, and causes the computer to execute a process to obtain a set of parameters including a first parameter corresponding to the first information, a second parameter corresponding to the second information, a third parameter corresponding to the third information, a fourth parameter corresponding to the third information, and a fifth parameter corresponding to the third information, using mobile body information relating to the mobile body. [Brief explanation of the drawing]

[0010] [Figure 1] A diagram showing an example of the configuration of the energy consumption estimation system according to the embodiment. [Figure 2] A diagram showing an example of the configuration of an information processing device according to the embodiment. [Figure 3] A flowchart showing an example of processing performed by the information processing device according to the embodiment. [Figure 4] A diagram showing an example configuration of the energy consumption estimation system in a modified form. [Figure 5] A diagram showing the schematic configuration of a modified server device. [Modes for carrying out the invention]

[0011] In one preferred embodiment of the present invention, the energy consumption estimation device includes estimation means for estimating the energy consumption of a mobile body based on an energy consumption estimation formula that includes first information relating to the energy consumed when the mobile body's drive source is operating and the mobile body is stopped, second information relating to the energy consumed and recovered when the mobile body accelerates and decelerates, and third information relating to the energy consumed by the resistance generated when the mobile body is running; and parameter acquisition means for acquiring a set of parameters using mobile body information relating to the mobile body, which includes a first parameter corresponding to the first information, a second parameter corresponding to the second information, a third parameter corresponding to the third information, a fourth parameter corresponding to the third information, and a fifth parameter corresponding to the third information.

[0012] The above-described energy consumption estimation device comprises estimation means and parameter acquisition means. The estimation means estimates the energy consumption of a mobile body based on an energy consumption estimation formula that includes first information relating to the energy consumed when the mobile body's drive source is operating and the mobile body is stopped, second information relating to the energy consumed and recovered during acceleration and deceleration of the mobile body, and third information relating to the energy consumed by the resistance generated when the mobile body is running. The parameter acquisition means uses the mobile body information relating to the mobile body to acquire a set of parameters including a first parameter corresponding to the first information, a second parameter corresponding to the second information, a third parameter corresponding to the third information, a fourth parameter corresponding to the third information, and a fifth parameter corresponding to the third information. This improves the estimation accuracy when estimating the energy consumption of the mobile body.

[0013] In one embodiment of the energy consumption estimation device described above, the mobile body information includes the weight of the mobile body, the width of the mobile body, the height of the mobile body, and an output performance value corresponding to the rated output or displacement of the mobile body.

[0014] In one embodiment of the above-described energy consumption estimation device, the device further includes a calculation means that calculates the total weight of the mobile body by adding the weight of the main body and the load weight of the mobile body, and calculates the front projected area of ​​the mobile body by multiplying the width and the height, and the parameter acquisition means acquires, as a first parameter, a value that depends on the weight of the main body or a value that depends on the output performance value, as a second parameter, a value that changes linearly according to the total weight, as a third parameter, a value that depends on the front projected area, as a fourth parameter, a value that changes linearly according to the total weight or a value that depends on the front projected area, and as a fifth parameter, a value that depends on the weight of the main body and changes linearly according to the total weight relative to the weight of the main body or a value that depends on the front projected area.

[0015] One embodiment of the above-described energy consumption estimation device further includes a parameter correction means that corrects each parameter included in the parameter group using an energy consumption rate corresponding to the power consumption rate or fuel consumption rate of the mobile body.

[0016] In one embodiment of the energy consumption estimation device described above, the parameter correction means corrects each parameter included in the parameter group using the calculated value of the energy consumption rate calculated using the parameter group and the catalog value of the energy consumption rate when the mobile body is driven under predetermined driving conditions.

[0017] In one embodiment of the energy consumption estimation device described above, the parameter correction means calculates the energy consumption rate using each parameter included in the parameter group and the average speed and average acceleration when the moving body is driven under the predetermined driving conditions.

[0018] In one embodiment of the energy consumption estimation device described above, the parameter correction means further corrects each parameter other than the first parameter included in the parameter group using the temperature measured while the moving body is in motion, or the predicted temperature for each link included in the path of the moving body obtained as a result of path searching.

[0019] In another preferred embodiment of the present invention, a computer-based energy consumption estimation method estimates the energy consumption of a mobile body based on an energy consumption estimation formula that includes first information relating to the energy consumed when the mobile body's power source is operating and the mobile body is stopped, second information relating to the energy consumed and recovered during acceleration and deceleration of the mobile body, and third information relating to the energy consumed by the resistance generated when the mobile body is moving. Using the mobile body information relating to the mobile body, a parameter group is obtained that includes a first parameter corresponding to the first information, a second parameter corresponding to the second information, a third parameter corresponding to the third information, a fourth parameter corresponding to the third information, and a fifth parameter corresponding to the third information. This improves the estimation accuracy when estimating the energy consumption of the mobile body.

[0020] In yet another preferred embodiment of the present invention, a program executed by a computer estimates the energy consumption of a mobile body based on an energy consumption estimation formula that includes first information relating to the energy consumed when the mobile body's power source is operating and the mobile body is stopped, second information relating to the energy consumed and recovered during acceleration and deceleration of the mobile body, and third information relating to the energy consumed by the resistance generated when the mobile body is moving. The computer is then instructed to perform a process to obtain a set of parameters using mobile body information relating to the mobile body, including a first parameter corresponding to the first information, a second parameter corresponding to the second information, a third parameter corresponding to the third information, a fourth parameter corresponding to the third information, and a fifth parameter corresponding to the third information. This program can be stored and used on a storage medium. This improves the estimation accuracy when estimating the energy consumption of a mobile body. [Examples]

[0021] Preferred embodiments of the present invention will be described below with reference to the drawings.

[0022] <System Configuration> [Overall structure] Figure 1 shows an example of the configuration of an energy consumption estimation system according to an embodiment. The energy consumption estimation system 100 has an information processing device 1 that moves together with the vehicle Ve in which the user is riding. The vehicle Ve can be treated as an example of a moving object.

[0023] [Information Processing Device] The information processing device 1 functions as an energy consumption estimation device. The information processing device 1 acquires vehicle Ve driving information RJ and vehicle information VJ of the vehicle Ve. It also acquires catalog value information CJ, which includes catalog values ​​related to the vehicle Ve. Furthermore, it acquires temperature information TJ, which relates to the temperature of the vehicle Ve during operation. Using the vehicle information VJ, the information processing device 1 calculates multiple parameters corresponding to each of the multiple pieces of information included in the energy consumption estimation model SM. The information processing device 1 also performs correction calculations for the aforementioned multiple parameters using the catalog value information CJ and temperature information TJ. Finally, using the energy consumption estimation model SM to which the multiple parameters obtained from the correction calculations are applied, the information processing device 1 calculates an estimated value SV of energy consumption due to the operation of the vehicle Ve, and outputs an estimation result SR, including the calculated estimated value SV, to the outside. The processing performed by the information processing device 1 can be applied to various types of vehicles, such as gasoline cars and electric vehicles. In the following explanation, unless otherwise specified, the processing performed by the information processing device 1 will be described using the example of its application to an electric vehicle.

[0024] The driving information RJ contains data related to the driving status of vehicle Ve at the time the driving information RJ was acquired. Specifically, the driving information RJ includes data such as the position, speed, acceleration, and road gradient of vehicle Ve while it is driving.

[0025] The vehicle information VJ contains information indicating values ​​related to the specifications of the vehicle Ve. Specifically, the vehicle information VJ includes, for example, the vehicle's body weight MV, its width VB, its height VC, and its output performance value PV, which corresponds to the vehicle's rated output. If the vehicle Ve is a gasoline vehicle, the information processing device 1 obtains the vehicle's displacement as the output performance value PV instead of its rated output.

[0026] The catalog value information CJ includes data corresponding to actual measured values ​​obtained when the vehicle Ve is actually driven under predetermined driving conditions. Specifically, the catalog value information CJ includes, for example, the AC power consumption rate E obtained when the vehicle Ve is actually driven under driving conditions that conform to WLTC (Worldwide harmonized Light vehicles Test Cycle). WLTC This includes data showing the average acceleration Aa and the average velocity Va. Note that if the vehicle Ve is a gasoline vehicle, the AC power consumption rate E is also included. WLTC Instead, the fuel consumption rate F obtained when the vehicle Ve was actually driven under driving conditions compliant with WLTC. WLTC It is sufficient if the data indicating this is included in the catalog value information CJ.

[0027] Temperature information TJ includes, for example, the temperature T of at least one link included in the route of vehicle Ve from its origin to its destination. r This includes information indicating the following. Note that in this embodiment, links can be defined as sections that divide the road network in any way. For example, links in this embodiment can be defined as sections of any length and / or any shape. Furthermore, links in this embodiment may be defined as sections that include nodes, or as sections that do not include nodes.

[0028] The energy consumption estimation model SM is structured as an energy consumption estimation formula that can calculate an estimated value SV using data included in the driving information RJ or the driving data described later. A specific example of the energy consumption estimation model SM will be explained later.

[0029] The information processing device 1 may be a device installed in the vehicle Ve, or it may be a portable terminal such as a smartphone carried by the user. Alternatively, the information processing device 1 may be integrated into the vehicle Ve.

[0030] Figure 2 shows an example of the configuration of an information processing device according to an embodiment. The information processing device 1 includes a communication unit 11, a storage unit 12, an input unit 13, a control unit 14, a sensor group 15, and a display unit 16. Each element of the information processing device 1 is interconnected via a bus line 10.

[0031] The communication unit 11 performs data communication with an external device based on the control of the control unit 14. The communication unit 11 can acquire driving data from an external device that shows the driving status and / or driving history of multiple vehicles, such as probe data. The communication unit 11 can also acquire map data and road data from an external device, such as map data and road data.

[0032] The memory unit 12 is composed of various storage media such as RAM (Random Access Memory), ROM (Read Only Memory), and non-volatile memory (including hard disk drives, flash memory, etc.). The memory unit 12 also stores programs for the information processing device 1 to execute predetermined processes. Furthermore, the memory unit 12 is used as working memory for the control unit 14. Note that the programs executed by the information processing device 1 may be stored in storage media other than the memory unit 12.

[0033] The memory unit 12 stores the database 4, driving information RJ, vehicle information VJ, catalog value information CJ, temperature information TJ, and energy estimation model SM. The memory unit 12 also stores the driving information RJ acquired by the control unit 14.

[0034] Database 4 stores driving data, map data, and road data obtained by the communication unit 11. Driving data includes, for example, data of the same type as the data acquired as driving information RJ. Map data includes, for example, data necessary for displaying a map based on a predetermined location such as the current location of vehicle Ve. Road data includes, for example, data representing the road network by combinations of nodes and links. The driving data, map data, and road data contained in Database 4 can be updated to the latest data at regular intervals according to the control of the control unit 14.

[0035] The input unit 13 has a user interface that accepts user input. The input unit 13 may include at least one user interface, such as a button, a touch panel, and a remote controller. The display unit 16 displays information based on the control of the control unit 14. The display unit 16 may include at least one device, such as a display and a projector.

[0036] The sensor group 15 includes various sensors that perform sensing of the vehicle Ve or the environment outside the vehicle. The sensor group 15 has an external sensor 20 and an internal sensor 21.

[0037] The external sensor 20 has one or more sensors for recognizing the surrounding environment of the vehicle Ve. The external sensor 20 may include, for example, a lidar, radar, ultrasonic sensor, infrared sensor, sonar, and camera.

[0038] The internal sensor 21 has one or more sensors for positioning the vehicle Ve. The internal sensor 21 may include, for example, a GNSS (Global Navigation Satellite System) receiver, a gyro sensor, a tilt sensor, an acceleration sensor, an IMU (Inertial Measurement Unit), and a vehicle speed sensor.

[0039] The internal sensor 21 has one or more sensors capable of measuring parameters related to the energy consumption of the vehicle Ve. The internal sensor 21 may include, for example, a current sensor, a voltage sensor, and a fuel sensor.

[0040] Furthermore, the sensor group 15 only needs to include sensors from which the control unit 14 can directly or indirectly derive the vehicle's speed and acceleration from the output of the sensor group 15. Additionally, the sensor group 15 only needs to include sensors from which the control unit 14 can directly or indirectly derive measured values ​​of the vehicle's energy consumption from the output of the sensor group 15.

[0041] The control unit 14 includes a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), and other components, and controls the entire information processing device 1. For example, the control unit 14 acquires driving information RJ based on the output of one or more sensors included in the sensor group 15, and stores the acquired driving information RJ in the storage unit 12. The control unit 14 can be treated as an example of a computer. Furthermore, the control unit 14 has the functions of estimation means, parameter acquisition means, calculation means, and parameter correction means.

[0042] Furthermore, the processing performed by the control unit 14 is not limited to being implemented by software through a program, but may also be implemented by any combination of hardware, firmware, and software. Also, the processing performed by the control unit 14 may be implemented using a user-programmable integrated circuit, such as an FPGA (Field-Programmable Gate Array) or a microcontroller. In this case, the program that the control unit 14 performs in this embodiment may be implemented using this integrated circuit. Thus, the control unit 14 may be implemented using hardware other than a processor.

[0043] The configuration of the information processing device 1 shown in Figure 2 is an example, and various modifications may be made to the configuration shown in Figure 2. For example, instead of the storage unit 12 storing map data and road data, the control unit 14 may receive information equivalent to map data and road data from a server device (not shown) via the communication unit 11. In another example, the input unit 13 may be provided inside the target vehicle as an external device of the information processing device 1, and the generated signals may be supplied to the information processing device 1. Also, at least some of the sensors in the sensor group 15 may be sensors installed on the vehicle Ve. In this case, the information processing device 1 may acquire information output by the sensors installed on the vehicle Ve from the vehicle Ve based on a communication protocol such as CAN (Controller Area Network).

[0044] <Specific example> Next, we will describe a specific example of the processing performed by the information processing device 1.

[0045] [Energy Consumption Estimation Model] In this specific example, for example, when estimating the energy consumption of a vehicle Ve actually traveling on a road, the energy consumption estimation model SM is stored in the memory unit 12, as shown in the estimation formulas (1) and (2) below. In formulas (1) and (2) below, P represents a value corresponding to the estimated value SV. In formulas (1) and (2) below, V represents velocity, α represents acceleration, θ represents road gradient, and g represents gravitational acceleration. In formulas (1) and (2) below, the coefficients k1 to k5 represent parameters before correction calculated by the method described later. In formula (2) below, the variable β is set to a predetermined value, such as "0.89".

[0046]

number

number

[0047] The first term on the right-hand side of the above equations (1) and (2) represents information about the energy consumed by the vehicle Ve in an idling state. The idling state of the vehicle Ve corresponds, for example, to a state in which power is supplied from the battery of the vehicle Ve to the motor drive control system and the vehicle Ve is stopped. In other words, the idling state of the vehicle Ve can be rephrased as a state in which the drive source of the vehicle Ve is operating and the vehicle Ve is stopped. If the vehicle Ve is driven by an engine (internal combustion engine), the idling state of the vehicle Ve can be rephrased as the idling state of the engine.

[0048] The second term on the right-hand side of equation (1) above represents information about the energy consumed when the vehicle Ve is accelerating. The second term on the right-hand side of equation (2) above represents information about the energy recovered when the vehicle Ve is decelerating. The control unit 14 calculates the estimated value SV using equation (1) above if the acceleration included in the driving information RJ is 0 or greater. The control unit 14 also calculates the estimated value SV using equation (2) above if the acceleration included in the driving information RJ is less than 0.

[0049] The third, fourth, and fifth terms on the right-hand side of the above equations (1) and (2) represent information about the energy consumed by the resistance generated when the vehicle Ve is in motion.

[0050] The control unit 14 can calculate an estimated value SV corresponding to the latest driving information RJ by applying the speed, acceleration, and road gradient data included in the latest driving information RJ obtained while the vehicle Ve is in motion to the above formulas (1) and (2). The control unit 14 can also estimate the energy consumption of the vehicle Ve from its starting point to its current location by accumulating the estimated value SV calculated at regular intervals while the vehicle Ve is in motion. Furthermore, the control unit 14 can acquire an estimated result SR related to the energy consumption of the vehicle Ve from its starting point to its current location while the vehicle Ve is in motion, and display the information related to the acquired estimated result SR on the display unit 16. Specifically, the control unit 14 can display information related to the estimated result SR on the display unit 16, for example, the cruising range of the vehicle Ve and / or the battery level at the time the vehicle Ve arrives at its destination. Furthermore, the control unit 14 can perform processing to display information related to the estimated result SR, such as the total energy consumption and / or carbon dioxide emissions when the vehicle Ve travels from the starting point to the destination, on the display unit 16.

[0051] In this specific example, for example, when estimating the energy consumption of vehicle Ve assuming that the vehicle Ve travels along the route obtained as a result of route searching, the energy consumption estimation model SM used is stored in the memory unit 12 as the estimation formulas shown in equations (3) and (4) below. In equations (3) and (4) below, P represents a value corresponding to the estimated value SV. Also, in equations (3) and (4) below, V L α represents the average speed for each link. L V represents the average acceleration for each link, Δh represents the elevation difference for each link, and g represents the acceleration due to gravity. Average velocity V L and average acceleration α LFor example, this can be calculated based on driving data stored in database 4. The elevation difference Δh can be determined based on map data and road data stored in database 4. Furthermore, the coefficients k1 to k5 in the following formulas (3) and (4) represent the parameters before correction, which are calculated by the method described later. Furthermore, the variable β in the following formulas (3) and (4) represents the parameters calculated by the method described later.

[0052]

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[0053] The first term on the right-hand side of equations (3) and (4) above represents information about the energy consumed by the vehicle Ve while idling.

[0054] The second and third terms on the right-hand side of equation (3) above represent information about the energy consumed when the vehicle Ve is accelerating. The second and third terms on the right-hand side of equation (4) above represent information about the energy consumed when the vehicle Ve is decelerating. The control unit 14 calculates an estimated value SV using equation (3) above if the links included in the vehicle Ve's path obtained as a result of the path search are on flat ground or an uphill slope. The control unit 14 also calculates an estimated value SV using equation (4) above if the links included in the vehicle Ve's path obtained as a result of the path search are on a downhill slope.

[0055] The fourth, fifth, and sixth terms on the right-hand side of the above equations (3) and (4) represent information about the energy consumed by the resistance generated when the vehicle Ve is in motion.

[0056] The control unit 14 can estimate the energy consumption when the vehicle Ve travels the entire route obtained as a result of the route search by, for example, accumulating the estimated value SV calculated for each link. The control unit 14 can also acquire an estimated result SR related to the energy consumption when the vehicle Ve travels the entire route obtained as a result of the route search, and display the information related to the acquired estimated result SR together with the route search results on the display unit 16. Specifically, the control unit 14 can process the information related to the estimated result SR to display on the display unit 16 information such as the total energy consumption and / or carbon dioxide emissions when the vehicle Ve travels the entire route obtained as a result of the route search.

[0057] Here, in order to improve the accuracy of calculating the estimated value SV for the vehicle Ve, it is desirable to apply coefficients k1 to k5 and the variable β corresponding to the vehicle Ve to the above formulas (1) to (4). According to this embodiment, by applying the coefficients k1 to k5 and the variable β obtained by the process described below to the energy consumption estimation model SM, the accuracy of calculating the estimated value SV for the vehicle Ve can be improved.

[0058] [Processing related to parameter calculation] Next, we will explain the process for calculating the parameters applied to the energy consumption estimation model SM.

[0059] (Calculation of parameters before correction) The control unit 14 calculates the coefficient k1 by applying the vehicle weight MV of the vehicle Ve included in the vehicle information VJ to the following formula (5). In the following formula (5), the value in kilograms is applied as the vehicle weight MV. In addition, the constants D1 and Q1 in the following formula (5) are set to predetermined values.

[0060]

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[0061] The control unit 14 can calculate the coefficient k1 as a value dependent on the main unit weight MV by performing calculations using the above formula (5). Alternatively, the control unit 14 may calculate the coefficient k1 as a value dependent on the output performance value PV by performing calculations using a formula in which the units of constants D1 and Q1 in the above formula (5) have been adjusted. Furthermore, the control unit 14 may select one coefficient k1 corresponding to the main unit weight MV from among a plurality of coefficients k1 that have been set in advance using, for example, table data.

[0062] The control unit 14 calculates the total weight MA of the vehicle Ve by adding the vehicle body weight MV of the vehicle Ve, which is included in the vehicle information VJ, and the load weight MS of the vehicle Ve, which includes the weight of the occupants of the vehicle Ve. For example, if the load weight MS is 0, the control unit 14 can obtain the vehicle body weight MV as the total weight MA of the vehicle Ve. The control unit 14 also calculates the coefficient k2 by applying the total weight MA of the vehicle Ve to the following formula (6). In the following formula (6), the value in kilograms is applied as the total weight MA. The constant D2 in the following formula (6) is set to a predetermined value.

[0063]

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[0064] The control unit 14 can calculate the coefficient k2 as a value that changes linearly according to the total weight MA by performing calculations using the above formula (6).

[0065] The control unit 14 calculates the front projected area FS of the vehicle Ve by multiplying the width VB of the vehicle Ve included in the vehicle information VJ by the height VC of the vehicle Ve included in the vehicle information VJ. The control unit 14 also calculates the coefficient k3 by applying the front projected area FS of the vehicle Ve to the following formula (7). In the following formula (7), the value in square meters is applied as the front projected area FS. The constants D3 and Q3 in the following formula (7) are set to predetermined values.

[0066]

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[0067] The control unit 14 can calculate the coefficient k3 as a value that depends on the front projection area FS by performing calculations using the above formula (7).

[0068] The control unit 14 calculates the coefficient k4 by applying the total weight MA of the vehicle Ve to the following formula (8). In the following formula (8), the value in kilograms is applied as the total weight MA. In addition, the constant D4 in the following formula (8) is set to a predetermined value.

[0069]

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[0070] The control unit 14 can calculate the coefficient k4 as a value that changes linearly according to the total weight MA by performing calculations using the above formula (8). Alternatively, the control unit 14 may calculate the coefficient k4 as a value that depends on the front projection area FS by performing calculations using a formula in which the units of the constant D4 in the above formula (8) have been adjusted.

[0071] The control unit 14 calculates the coefficient k5 by applying the vehicle body weight MV and gross weight MA of the vehicle Ve to the following formula (9). In the following formula (9), values ​​in kilograms are applied as the vehicle body weight MV and gross weight MA. In addition, the constants D5 and Q5 in the following formula (9) are set to predetermined values.

[0072]

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[0073] By performing the calculation using the above formula (9), the control unit 14 can calculate the coefficient k5 as a value that depends on the body weight MV and linearly changes according to the total weight MA with respect to the body weight MV. Note that the control unit 14 may calculate the coefficient k5 as a value that depends on the front projection area FS, for example, by performing the calculation using a formula obtained by adjusting the units of the constant D5 and the constant Q5 in the above formula (9).

[0074] According to the processing described above, the control unit 14 can obtain a parameter group including the coefficients k1 to k5 by using the vehicle information VJ related to the vehicle Ve. The coefficient k1 is obtained as a value corresponding to the information on the energy consumed when the vehicle Ve is in the idling state. The coefficient k2 is obtained as a value corresponding to the information on the energy consumed and recovered during acceleration and deceleration of the vehicle Ve. The coefficients k3, k4, and k5 are obtained as values corresponding to the information on the energy consumed due to the resistance generated during the running of the vehicle Ve.

[0075] (Correction calculation of parameters using catalog values) The control unit 14 calculates the coefficients K1 to K5 for correction calculation by performing the calculation using the above formulas (5) to (9) in a state where the loaded weight MS of the vehicle Ve is set to the provisional value MZ for correction calculation. The provisional value MZ is, for example, the number of passengers T of the vehicle Ve max If it is known, it can be set to the value obtained by calculating "100 + 8.25×(T max -1)". Also, the provisional value MZ is, for example, when the vehicle Ve is a goods vehicle with a maximum load capacity S max It can be set to the value obtained by calculating "110 + 0.28×S max ". Also, the provisional value MZ can be set as a predetermined value such as 133 kilograms, for example.

[0076] The control unit 14 calculates the variable β for correction calculation by applying the coefficients K2 and K3 to the following formula (10). Note that the constants D6 and Q6 in the following formula (10) are set as predetermined values. c ​

[0077]

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[0078] The control unit 14 uses the average acceleration Aa and average velocity Va included in the catalog value information CJ, along with the coefficients K1 to K5 and the variable β for correction calculations. c By applying this to the following formula (11), the energy consumption P for correction calculations is obtained. calc The control unit 14 calculates the energy consumption P. calc By applying the following formula (12), the AC power consumption rate E for correction calculations is obtained. calc Calculate.

[0079]

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[0080] The control unit 14 processes the AC power consumption rate E included in the catalog value information CJ. WLTC And, AC power consumption rate E for correction calculation calc By applying the above to the following formula (13), the correction coefficient W corresponding to the catalog value information CJ is obtained. c The following is calculated. Note that the constants D7 and Q7 in the following formula (13) are set to predetermined values. Also, η in the following formula (13) represents the charging efficiency. The charging efficiency η can be set to any value within the range of 0.5 to 1.0, for example.

[0081]

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[0082] The control unit 14 controls the correction coefficient W cBy performing a correction calculation using the above formulas (5) to (9), the coefficients k1 to k5 calculated using the above formulas are corrected. For example, the control unit 14 corrects the coefficients k1 to k5 calculated using the above formulas (5) to (9) by the correction coefficient W c By multiplying by this, a coefficient corresponding to the catalog value information CJ is obtained. Through this process, the control unit 14 applies a correction coefficient W to the coefficient k1. c The coefficient k multiplied by 11 The coefficient k2 is then used with the correction coefficient W. c The coefficient k multiplied by 21 The coefficient k3 is then converted to the correction coefficient W. c The coefficient k multiplied by 31 The coefficient k4 is then adjusted for the correction coefficient W. c The coefficient k multiplied by 41 The coefficient k5 is then the correction coefficient W. c The coefficient k multiplied by 51 And you can obtain that.

[0083] The control unit 14, when the vehicle Ve is a gasoline vehicle, modifies at least a part of the correction calculation described above as necessary, thereby determining the AC power consumption rate E WLTC Instead, fuel consumption rate F WLTC Using the correction coefficient W c It is possible to calculate this.

[0084] According to the process described above, the control unit 14 determines the AC power consumption rate E of the vehicle Ve. WLTC Or fuel consumption rate F WLTC The coefficients k1 to k5 can be corrected using the corresponding energy consumption rate. In addition, the control unit 14 calculates the AC power consumption rate E using the correction calculation coefficients K1 to K5. calc And the AC power consumption rate E, which corresponds to the catalog value of the energy consumption rate. WLTC The coefficients k1 to k5 can be corrected using the and . The control unit 14 also uses the coefficients K1 to K5 for correction calculation, the average acceleration Aa and the average velocity Va to calculate the AC power consumption rate E calc It is possible to calculate this.

[0085] (Parameter correction calculation using temperature) The control unit 14 processes the temperature T included in the temperature information TJ. r The temperature of the vehicle Ve during operation is obtained, and the obtained temperature T r By applying this to the following formula (14), the temperature T r The corresponding correction factor T C The following formula (14) calculates the temperature T. r It is applied as follows. Also, in the following formula (14), either the temperature measured while the vehicle Ve is driving, or the predicted temperature for each link included in the vehicle Ve's route obtained as a result of route searching, is used as the temperature T. r It should be applied as follows. Also, the constants D8 and Q8 in the following formula (14) are set as predetermined values.

[0086]

number

[0087] The control unit 14 sets the correction coefficient T c By performing a correction calculation using the coefficient k, 21 coefficient k 31 coefficient k 41 and coefficient k 51 The coefficient k is corrected. For example, the control unit 14 corrects the coefficient k 21 coefficient k 31 coefficient k 41 and coefficient k 51 Correction coefficient T for each of the following c By multiplying by, the temperature T r The coefficient corresponding to is obtained. Through this process, the control unit 14 obtains the coefficient k 21 Correction coefficient T c The coefficient k multiplied by 22 And the coefficient k 31 The correction coefficient T c The coefficient k multiplied by 32 And the coefficient k 41 The correction coefficient T c The coefficient k multiplied by 42 And the coefficient k 51 The correction coefficient T c The coefficient k multiplied by 52 And you can obtain that.

[0088] According to the process described above, the control unit 14 uses the temperature measured while the vehicle Ve is in motion, or the predicted temperature for each link included in the vehicle Ve's route obtained as a result of route searching, and calculates the coefficient k 21 coefficient k 31 coefficient k 41 and coefficient k 51 This can be corrected.

[0089] (Calculation of the variable β during pathfinding) When the control unit 14 estimates the energy consumption of the vehicle Ve assuming that the vehicle Ve travels along the path obtained as a result of the path search, it calculates the variable β using one of the following two calculation methods. h This is applied to the energy consumption estimation model SM.

[0090] In the first calculation method, the control unit 14 calculates the coefficient k 22 and coefficient k 32 By applying this to the following formula (15), the variable β h The following is calculated. Note that the constants D9 and Q9 in the formula (15) below are set to predetermined values.

[0091]

number

[0092] In the second calculation method, the control unit 14 calculates the coefficient k 22 and coefficient k 32 By applying this to the following formula (16), the variable β h The control unit 14 calculates the average speed V for each link using the following formula (17). L By applying this, the variable C in the following formula (16) a The control unit 14 can calculate the average speed V for each link using the following formula (18). L By applying this, the variable C in the following formula (16) b It is possible to calculate this.

[0093] [Number] [Number] [Number]

[0094] According to the second calculation method described above, the control unit 14 calculates the variable β for each link included in the route of the vehicle Ve obtained as a result of the route search by performing calculations using the above mathematical formulas (16) to (18). h can be calculated.

[0095] [Calculation of Estimated Energy Consumption] The control unit 14 applies the new coefficients calculated by the above correction calculation to the coefficients k1 to k5 included in the above mathematical formulas (1) to (4). Specifically, for each of the above mathematical formulas (1) to (4), the control unit 14 applies the coefficient k 11 to the coefficient k1, the coefficient k 22 to the coefficient k2, the coefficient k 32 to the coefficient k3, the coefficient k 42 to the coefficient k4, and the coefficient k 52 to the coefficient k5. Also, the control unit 14 applies the variable β h calculated by the above calculation to the variable β included in the above mathematical formulas (3) and (4).

[0096] The control unit 14 uses the mathematical formulas (1) and (2) to which the coefficients k 11 , the coefficient k 22 , the coefficient k 32 , the coefficient k 42 , and the coefficient k 52 are applied to calculate the estimated value SV of the energy consumption in the traveling vehicle Ve. Also, the control unit 14 uses the coefficients k 11 , the coefficient k 22 , the coefficient k 32 , the coefficient k 42 , the coefficient k 52 , and the variable β hUsing equations (3) and (4) to which the above is applied, we calculate the estimated energy consumption SV of the vehicle Ve, assuming that the vehicle Ve travels along the path obtained as a result of the path search.

[0097] [Processing flow] Next, we will explain the processing flow performed by the information processing device 1. Figure 3 is a flowchart showing an example of processing performed by the information processing device according to the embodiment.

[0098] First, the information processing device 1 obtains an energy consumption estimation model SM from the storage unit 12 that corresponds to the situation for estimating the energy consumption of vehicle Ve (step S11). For example, if vehicle Ve is actually traveling on a road, the information processing device 1 obtains the above formulas (1) and (2) as the energy consumption estimation model SM. Also, for example, if the information processing device 1 is searching for the planned travel route of vehicle Ve, it obtains the above formulas (3) and (4) as the energy consumption estimation model SM.

[0099] Next, the information processing device 1 calculates the uncorrected parameters in the energy consumption estimation model SM obtained in step S11 (step S12). As uncorrected parameters, the information processing device 1 calculates, for example, the coefficients k1 to k5 included in the above formulas (1) to (4).

[0100] Next, the information processing device 1 performs a correction calculation using catalog value information CJ on the parameters before correction calculated in step S12 (step S13). Through this process, the information processing device 1 calculates the coefficient k 11 And, k 21 And the coefficient k 31 And the coefficient k 41 And the coefficient k 51 And you can obtain that.

[0101] Next, the information processing device 1 performs a correction calculation using temperature information TJ on the parameters obtained as a result of the processing in step S13 (step S14). Through this process, the information processing device 1 calculates the coefficient k 22And the coefficient k 32 And the coefficient k 42 And the coefficient k 52 And you can obtain that.

[0102] Next, the information processing device 1 sets a predetermined coefficient to be applied to the information regarding the energy consumed during acceleration and deceleration of the vehicle Ve in the energy consumption estimation model SM acquired in step S11 (step S15). Through this process, the information processing device 1 can set the variable β in the above formula (2) to a predetermined value. Furthermore, through the above process, the information processing device 1 sets the variable β in the above formulas (3) and (4) to the variable β h The value obtained as a result of the calculation can be set.

[0103] Next, the information processing device 1 uses the energy consumption estimation model SM, to which the corrected parameters obtained as processing results in steps S13 and S14 and a predetermined coefficient set in step S15 are applied, to calculate an estimated value SV of energy consumption in the vehicle Ve (step S16).

[0104] When the vehicle Ve is actually traveling on the road, the information processing device 1 performs the processing in steps S11 to S15, for example, and then repeatedly performs the processing in step S16 at regular intervals.

[0105] When the information processing device 1 searches for the planned route of vehicle Ve, for example, after performing the processes in steps S11 to S13, it performs the processes in steps S14 to S16 for each link included in the route obtained as a result of the search. The information processing device 1 calculates the variable β using the first calculation method described above. h To calculate this, the process in step S15 only needs to be performed once.

[0106] As described above, according to this embodiment, the vehicle information VJ of the vehicle Ve can be used to calculate parameters corresponding to each piece of information included in the energy consumption estimation model SM. Furthermore, according to this embodiment, the calculation results of the parameters corresponding to each piece of information included in the energy consumption estimation model SM can be corrected using the catalog value information CJ and temperature information TJ. Furthermore, according to this embodiment, the energy consumption estimation model SM to which the corrected parameters have been applied can be used to calculate the estimated energy consumption SV of the vehicle Ve during operation. Therefore, according to this embodiment, the estimation accuracy when estimating the energy consumption of a moving object can be improved.

[0107] <Variation> Next, we will describe a suitable modification of the above-described embodiment.

[0108] According to the embodiment described above, at least some of the processes performed by the information processing device 1 may be performed by a server device that communicates data with the information processing device 1.

[0109] Figure 4 shows an example configuration of a modified energy consumption estimation system. The energy consumption estimation system 100A includes an information processing device 1A and a server device 200. The information processing device 1A and the server device 200 communicate data via a network 150.

[0110] The information processing device 1A has the same configuration as the information processing device 1 described in the above embodiment (see Figure 2). The information processing device 1A also transmits the information input at the input unit 13 and the information obtained by the sensor group 15 to the server device 200. For example, the information processing device 1A transmits driving information RJ, which includes data such as the position, speed, acceleration, and road gradient of the vehicle Ve while it is in motion, to the server device 200. The information processing device 1A also transmits information related to the origin and destination of the vehicle Ve to the server device 200.

[0111] Figure 5 shows a schematic configuration of a modified server device. As shown in Figure 5, the server device 200 includes a communication unit 301, a storage unit 302, and a control unit 304. The communication unit 301, the storage unit 302, and the control unit 304 are interconnected via a bus line 300.

[0112] The communication unit 301 transmits and receives various data via the network 150 based on the control of the control unit 304. The storage unit 302 is composed of, for example, an HDD. The storage unit 302 also stores data that can be used to calculate the estimated value SV, such as the database 4, driving information RJ, vehicle information VJ, catalog value information CJ, temperature information TJ, and energy estimation model SM. The control unit 304 has memory such as a CPU, ROM, and RAM, and performs overall control of the server device 200 by executing programs stored in memory. The control unit 304 can also be treated as an example of a computer.

[0113] With the configuration described above, the control unit 304 can estimate the energy consumption of the vehicle Ve based on the energy estimation model SM illustrated in the above formulas (1) to (4). Furthermore, the control unit 304 can use the vehicle information VJ related to the vehicle Ve to obtain a set of parameters including coefficients k1 to k5.

[0114] According to this modified example, the same processing performed in server device 200 may be performed in a server system having multiple server devices.

[0115] In the embodiments described above, the program can be stored using various types of non-transitory computer-readable medium and supplied to a control unit, which is a computer. Non-transitory computer-readable medium includes various types of tangible storage medium. Examples of non-transitory computer-readable medium include magnetic storage media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical storage media (e.g., magneto-optical disks), CD-ROMs (Read Only Memory), CD-Rs, CD-R / Ws, and semiconductor memory (e.g., mask ROMs, PROMs (Programmable ROMs), EPROMs (Erasable PROMs), flash ROMs, and RAMs (Random Access Memory)).

[0116] Although the present invention has been described above with reference to embodiments, the present invention is not limited to the above embodiments. Various modifications to the structure and details of the present invention can be made that are understandable to those skilled in the art within the scope of the present invention. That is, the present invention naturally includes the full disclosure, including the claims, and various modifications and alterations that those skilled in the art could make in accordance with the technical idea. Furthermore, each disclosure of the above-mentioned patent documents and other references is incorporated herein by reference. [Explanation of symbols]

[0117] 1. 1A Information Processing Device 11, 301 Communications Department 12, 302 Storage section 14, 304 Control Unit 15 Sensor Groups

Claims

1. An estimation means for estimating the energy consumption of a mobile body based on an energy consumption estimation formula that includes first information regarding the energy consumed when the mobile body's power source is operating and the mobile body is stopped, second information regarding the energy consumed and recovered during acceleration and deceleration of the mobile body, and third information regarding the energy consumed by the resistance generated when the mobile body is moving. A parameter acquisition means that uses the mobile body information relating to the mobile body to acquire a parameter group including a first parameter corresponding to the first information, a second parameter corresponding to the second information, a third parameter corresponding to the third information, a fourth parameter corresponding to the third information, and a fifth parameter corresponding to the third information. An energy consumption estimation device having the following features.

2. The energy consumption estimation device according to claim 1, wherein the mobile body information includes the main body weight of the mobile body, the width of the mobile body, the height of the mobile body, and an output performance value corresponding to the rated output or displacement of the mobile body.

3. The system further includes a calculation means for calculating the total weight of the mobile body by adding the weight of the main body and the load weight of the mobile body, and for calculating the front projected area of ​​the mobile body by multiplying the width and the height. The energy consumption estimation device according to claim 2, wherein the parameter acquisition means acquires, as a first parameter, a value that depends on the weight of the main unit or a value that depends on the output performance value; as a second parameter, a value that changes linearly according to the total weight; as a third parameter, a value that depends on the front projection area; as a fourth parameter, a value that changes linearly according to the total weight or a value that depends on the front projection area; and as a fifth parameter, a value that depends on the weight of the main unit and changes linearly according to the total weight relative to the weight of the main unit or a value that depends on the front projection area.

4. The energy consumption estimation device according to claim 1, further comprising a parameter correction means for correcting each parameter included in the parameter group using an energy consumption rate corresponding to the power consumption rate or fuel consumption rate of the mobile body.

5. The energy consumption estimation device according to claim 4, wherein the parameter correction means corrects each parameter included in the parameter group using the calculated value of the energy consumption rate calculated using the parameter group and the catalog value of the energy consumption rate when the mobile body is driven under predetermined driving conditions.

6. The energy consumption estimation device according to claim 5, wherein the parameter correction means calculates the calculated value of the energy consumption rate using each parameter included in the parameter group and the average speed and average acceleration when the moving body is driven under the predetermined driving conditions.

7. The energy consumption estimation device according to claim 4, wherein the parameter correction means further corrects each parameter other than the first parameter included in the parameter group using the temperature measured while the moving body is in motion, or the predicted temperature for each link included in the path of the moving body obtained as a result of path searching.

8. A method for estimating energy consumption performed by a computer, Based on an energy consumption estimation formula that includes first information regarding the energy consumed when the power source of the mobile body is operating and the mobile body is stopped, second information regarding the energy consumed and recovered during acceleration and deceleration of the mobile body, and third information regarding the energy consumed by the resistance generated when the mobile body is moving, the energy consumption of the mobile body is estimated. A method for estimating energy consumption, which uses mobile body information relating to the mobile body to obtain a set of parameters including a first parameter corresponding to the first piece of information, a second parameter corresponding to the second piece of information, a third parameter corresponding to the third piece of information, a fourth parameter corresponding to the third piece of information, and a fifth parameter corresponding to the third piece of information.

9. A program executed by a computer, Based on an energy consumption estimation formula that includes first information regarding the energy consumed when the power source of the mobile body is operating and the mobile body is stopped, second information regarding the energy consumed and recovered during acceleration and deceleration of the mobile body, and third information regarding the energy consumed by the resistance generated when the mobile body is moving, the energy consumption of the mobile body is estimated. A program that causes a computer to perform a process to obtain a set of parameters, which includes a first parameter corresponding to the first piece of information, a second parameter corresponding to the second piece of information, a third parameter corresponding to the third piece of information, a fourth parameter corresponding to the third piece of information, and a fifth parameter corresponding to the third piece of information, using the mobile information relating to the mobile body.

10. A storage medium storing the program described in claim 9.

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