Vehicle management device, vehicle management method, and vehicle management program

Abstract

To provide a vehicle management device that enables more accurate estimation of power consumption patterns during the operation of buses and other vehicles. [Solution] The vehicle management device 1 of the present invention includes: a setting unit 10 that sets a driving schedule Da which includes location information of a route on which vehicle C travels, location information of one or more stopping positions included in the route, and the stopping time at each of the one or more stopping positions; a generation unit 20 that generates time-series data Db which shows the temporal change in the driving state of vehicle C when vehicle C travels the route based on the driving schedule Da; and a calculation unit 30 that calculates the total power consumption when vehicle C travels the route according to the driving schedule Da based on the time-series data Db.

Description

Technical Field

[0001] The present disclosure relates to a vehicle management device, a vehicle management method, and a vehicle management program.

Background Art

[0002] In recent years, in the field of electric vehicles, technologies for estimating in advance the amount of power consumption and electricity cost when the vehicle is running have been developed from the viewpoints of energy management and operation planning / vehicle management.

[0003] For example, in the device described in Patent Document 1, the travel route of the host vehicle is calculated, and the energy consumption of the host vehicle is corrected based on the measured travel characteristics (speed, acceleration, frequency of acceleration, stop frequency, etc.) when another vehicle (ordinary vehicle) travels on the travel route. Specifically, first, the travel characteristics when the host vehicle travels on a specific travel route are acquired, and energy consumption information corresponding to the travel characteristics is acquired. The travel characteristics of the ordinary vehicle that has traveled on the same route are compared with the travel characteristics of the host vehicle, and the energy consumption information is corrected according to the difference. Calculations of the energy consumption amount are performed from the obtained energy consumption information.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] In recent years, there has been a growing demand for more accurate estimation of power consumption and energy efficiency in the field of commercial vehicles such as route buses and garbage trucks (hereinafter collectively referred to as "buses, etc."). Such technology can be used, for example, to accurately determine the amount of battery power required for a vehicle when changing the route or type of bus, etc. This technology is also necessary when considering the timing of stops at charging stations along the route of bus, etc. Furthermore, energy efficiency serves as a useful indicator when changing the type of vehicle.

[0006] In this regard, prior art such as Patent Document 1 does not take into account the specific driving patterns of commercial vehicles such as buses, and therefore has issues in terms of the accuracy of power consumption estimation.

[0007] Generally, commercial vehicles such as buses travel at low speeds, stopping frequently to make stops at multiple locations (for example, bus stops for buses and garbage collection points for garbage trucks). This results in frequent deceleration and acceleration. In addition, commercial vehicles such as buses spend long periods of time stopped while driving. Therefore, the power consumption patterns of commercial vehicles such as buses during route travel inevitably differ from those of ordinary passenger cars.

[0008] If power consumption is estimated based on actual measurement data obtained from ordinary passenger cars, as in the prior art described in Patent Document 1, without considering such driving patterns, the estimation error will also be large.

[0009] This invention has been made in view of the above-mentioned problems, and aims to provide a vehicle management device, a vehicle management method, and a vehicle management program that enable more accurate calculation of power consumption during the operation of buses and the like. [Means for solving the problem]

[0010] The main present invention that solves the aforementioned problems is: A setting unit sets a driving schedule that includes location information for the route on which the vehicle will travel, location information for one or more stopping points included in the route, and the stopping time at each of the one or more stopping points. A generation unit generates time-series data showing the temporal changes in the vehicle's driving state when the vehicle travels along the aforementioned route, based on the aforementioned driving schedule. A calculation unit that calculates the total power consumption when the vehicle travels along the route according to the travel schedule based on the time-series data, Vehicle management system equipped with That is the case.

[0011] Also, in other situations, A process for setting a driving schedule that includes location information of the route on which the vehicle will travel, location information of one or more stopping points included in the route, and the stopping time at each of the one or more stopping points. A process for generating time-series data showing the temporal changes in the vehicle's driving state when the vehicle travels the route based on the aforementioned driving schedule, A process for calculating the total power consumption when the vehicle travels the route according to the travel schedule based on the time-series data, This is a vehicle management method that involves the following:

[0012] Also, in other situations, A process for setting a driving schedule that includes location information of the route on which the vehicle will travel, location information of one or more stopping points included in the route, and the stopping time at each of the one or more stopping points. A process to generate time-series data showing the temporal changes in the vehicle's driving state when the vehicle travels along the aforementioned route, based on the aforementioned driving schedule; A process for calculating the total power consumption when the vehicle travels the route according to the travel schedule based on the time-series data, This is a vehicle management program that has the following features. [Effects of the Invention]

[0013] According to the vehicle management device of the present invention, it is possible to estimate the mode of power consumption during the operation of a bus or the like with higher precision.

Brief Description of the Drawings

[0014] [Figure 1] Figure showing an example of a vehicle to which the vehicle management device is applied [Figure 2] Block diagram showing an example of the functional configuration of the vehicle management device [Figure 3] Figure showing an example of the hardware configuration of the vehicle management device [Figure 4] Figure showing an example of an operation display screen when the setting unit receives the setting of the vehicle's driving route from the user [Figure 5] Figure showing an example of vehicle speed calculation processing in the generation unit [Figure 6] Figure showing an example of gradient calculation processing in the generation unit [Figure 7] Figure showing an example of time series data generated by the generation unit [Figure 8] Figure for explaining the calculation process of the power consumption in the drive motor of the vehicle [Figure 9] Figure showing an example of calculation model data for calculating the power consumption in the air conditioning equipment [Figure 10] Figure showing an example of the presentation mode of the time variation and total power consumption of the power consumption when the vehicle is driven according to the driving schedule calculated by the calculation unit [Figure 11] Flowchart showing an example of the process for calculating the electricity bill by the vehicle management device [Figure 12] Figure showing an example of the presentation mode of the total power consumption and electricity bill in each reference month calculated by the flow shown in FIG. 11 [Figure 13] Figure for explaining another calculation process (method using physical model data) of the power consumption in the drive motor [Figure 14] Figure showing a modified example of the operation display screen when the setting unit receives the setting of the vehicle's driving route from the user

Modes for Carrying Out the Invention

[0015] Preferred embodiments of the present invention will be described in detail below with reference to the attached drawings. In this specification and the drawings, components having substantially the same function are denoted by the same reference numerals, and redundant explanations will be omitted.

[0016] [Configuration of the vehicle management system] The configuration of a vehicle management device (hereinafter referred to as "vehicle management device 1") according to one embodiment of the present invention will be described below.

[0017] Figure 1 shows an example of a vehicle C to which the vehicle management device 1 is applied. In this embodiment, vehicle C is, for example, a route bus (hereinafter referred to as "vehicle" or "EV vehicle") that runs using electricity from a battery Cd that it has installed on it. In addition to the battery Cd, vehicle C has, for example, a drive motor Ca that generates the drive output for vehicle C to run, air conditioning equipment Cb for adjusting the temperature of the interior environment (e.g., an air conditioner or heater), and auxiliary equipment Cc necessary for the operation of the bus (e.g., a fare management device or interior lights). The drive motor Ca, air conditioning equipment Cb, and auxiliary equipment Cc operate using electricity supplied from the battery Cd, for example.

[0018] Figure 2 is a block diagram showing an example of the functional configuration of the vehicle management device 1. Figure 3 is a diagram showing an example of the hardware configuration of the vehicle management device 1.

[0019] The vehicle management device 1 is a device that calculates the temporal changes in the amount of power consumed when vehicle C travels along a route set by the user, and also calculates the total amount of power consumed by accumulating these changes. The vehicle management device 1 may be mounted on vehicle C or installed outside of vehicle C.

[0020] The vehicle management device 1 is a computer whose main components include a CPU 101, ROM 102, RAM 103, external storage device (e.g., flash memory) 104, communication unit (e.g., internet-connected communication module) 105, input unit (e.g., keyboard and mouse) 106 for receiving user input operations, and display unit (e.g., liquid crystal display) 107 for presenting information to the user.

[0021] Each of the functions of the vehicle management device 1, as described later, is realized, for example, by the CPU 101 referring to processing programs and various data stored in the ROM 102, RAM 103, external storage device 104, etc. The external storage device 104 stores not only the programs for the vehicle management device 1 to realize each of the functions described later, but also map data D1, operation route data D2, driving condition data D3, and calculation model data D4, etc.

[0022] The vehicle management device 1 has the functions of a setting unit 10, a generation unit 20, and a calculation unit 30. These functions are realized by utilizing map data D1, route data D2, driving condition data D3, and calculation model data D4 stored in the external storage device 104.

[0023] Here, map data D1 is data that stores a road map and its coordinates in association. The road map in map data D1 used in this embodiment includes, for example, the location information of each road, as well as the locations of intersections and traffic lights. The road map also includes information on the speed limit of each road. The coordinates on the road map are represented, for example, by latitude, longitude, and elevation.

[0024] Route data D2 is data relating to bus routes throughout Japan. Route data D2 stores, for example, location information of the route and location information of bus stops along that route, associated with the bus route name.

[0025] Driving condition data D3 is data that specifies the driving conditions when vehicle C travels along a route set by the user through simulation (details are described below). Driving conditions specified by driving condition data D3 include, for example, the acceleration and deceleration of vehicle C, conditions that specify whether or not to consider the speed limits of the roads along the driving route, conditions that specify the vehicle speed when turning right or left along the driving route, and conditions that specify the driving state when vehicle C switches from normal driving to regenerative driving.

[0026] The calculated model data D4 is model data for calculating the amount of power consumed per unit time in vehicle C when traveling along a set route, based on the state of vehicle C (time-series data Db described later). The calculated model data D4 includes model data for calculating the amount of power consumed per unit time in the drive motor Ca, model data for calculating the amount of power consumed per unit time in the air conditioning Cb, and model data for calculating the amount of power consumed per unit time in the auxiliary equipment Cc, etc. (details are described later).

[0027] <Settings section 10> The setting unit 10 sets a driving schedule Da based on user input, which includes location information for the route on which vehicle C will travel, the speed limits of each road along the route, location information for one or more stopping points along the route, and the stopping time at each of the one or more stopping points. Here, a stopping point refers to, for example, a bus stop. In this embodiment, in addition to bus stops, the driving schedule can also be set to stop vehicle C at traffic lights and / or pedestrian crossings installed along the driving route.

[0028] Figure 4 shows an example of the operation display screen when the setting unit 10 receives input from the user regarding the driving route of vehicle C.

[0029] The operation display screen includes a first input section m1 (e.g., a text box) for entering the name of the bus route to be set as the travel route, a second input section m2 (e.g., a text box) for setting the stopping time at each bus stop along the travel route, a third input section m3 (e.g., a pull-down selection box) for setting whether or not to stop at each traffic light and intersection along the travel route, a display area n1 for displaying a road map of the travel route, and a confirmation button m4, etc.

[0030] The process by which the setting unit 10 accepts input for the travel route on the operation display screen shown in Figure 4 is as follows, for example:

[0031] For example, the user first enters the name of the bus route to be set as the travel route into the text box of the first input unit m1. Upon receiving the bus route name input into the first input unit m1, the setting unit 10 reads the data (i.e., location information) of the bus route name from the route data D2. The setting unit 10 refers to the map data D1 and reads the road map corresponding to the travel route, the location information of each road associated with the road map, the location of intersections and traffic lights, and the speed limit of each road. Then, it displays the image of the road map in the display area n1.

[0032] In this process, the setting unit 10 also displays the location information of bus stops along the route stored in the route data D2, and the location information of intersections and pedestrian crossings along the route stored in the map data D1, on the road map in the display area n1. The setting unit 10 then displays a second input unit m2 on the operation display screen for setting the stopping time at each bus stop along the route, and a third input unit m3 for setting whether or not to stop at each intersection and pedestrian crossing along the route.

[0033] Next, the user enters the stopping time at each stop along the route into the text box of the second input unit m2. The user also enters whether or not to stop at each intersection and pedestrian crossing along the route using the pull-down menu of the third input unit m3. At this time, the setting unit 10 may set the stopping time at each intersection and pedestrian crossing to a default value, or it may provide an input section to allow the user to change the setting. Finally, the user presses the confirmation button m4 to confirm the driving schedule Da related to the driving route of vehicle C.

[0034] Through the above process, the setting unit 10 sets a driving schedule Da which includes location information of the route on which vehicle C will travel, the speed limit of each road in the route, location information of one or more stopping points included in the route, and the stopping time at each of the one or more stopping points.

[0035] <Generation part 20> The generation unit 20 performs a simulation based on the driving schedule Da set in the setting unit 10 and generates time-series data Db that shows the temporal changes in the driving state of vehicle C when vehicle C travels along the said route. Here, the driving state includes, for example, the vehicle speed, acceleration / deceleration, driving position, road gradient at the driving position, and cumulative distance traveled. At this time, the generation unit 20 performs the simulation under the driving conditions specified in the driving condition data D3.

[0036] In this embodiment, the following conditions are set as the driving condition data D3. (1) The acceleration and deceleration of vehicle C shall be constant (for example, acceleration: 0.49 m / s²). 2 , Deceleration: 0.49m / s 2 ). (2) When accelerating vehicle C, the upper limit of the vehicle speed shall be the speed limit of each road along the route (for example, 50 km / h). (3) When turning vehicle C left or right, the vehicle speed shall be a constant value of slow speed (for example, 10 km / h). (4) When vehicle C is decelerating, the drive motor Ca is switched from normal operation to regenerative operation.

[0037] The routes of buses and similar vehicles are typically on public roads, and these routes contain many stopping points such as bus stops, intersections, and pedestrian crossings. Furthermore, buses and similar vehicles are required to operate at low acceleration and low speed at all times so that they can stop immediately if an object suddenly appears in the road. In this embodiment, conditions (1) to (3) were set from this perspective. Condition (4) is no different from that of a typical vehicle.

[0038] Figure 5 shows an example of the vehicle speed calculation process in the generation unit 20. Figure 6 shows an example of the gradient calculation process in the generation unit 20. Figure 7 shows an example of the time-series data Db generated by the generation unit 20.

[0039] In the simulation, the generation unit 20 drives vehicle C along the route set in the driving schedule Da. At the same time, vehicle C is stopped at the locations of bus stops, intersections, and pedestrian crossings along the route set in the driving schedule Da. Furthermore, at the bus stops along the route, vehicle C is stopped for the duration set in the driving schedule Da. Then, in the simulation, vehicle C is driven under the driving conditions (1) to (4) specified in the driving condition data D3 described above.

[0040] For example, in Figure 5, vehicle C is controlled to stop at each stopping position (i.e., bus stops, intersections, and pedestrian crossings). Specifically, after departing from one stopping position, vehicle C increases its speed at a constant acceleration. When vehicle C reaches the road's speed limit, it continues to travel at that speed. Then, in order to stop at the next stopping position, vehicle C decreases its speed at a constant deceleration from a predetermined distance before the next stopping position. By repeating this process, vehicle C travels from the starting point to the ending point set in the travel schedule Da.

[0041] In Figure 5, it is assumed that vehicle C stops at all intersections and pedestrian crossings. However, in the driving schedule Da, vehicle C continues driving without slowing down or stopping at intersections and pedestrian crossings where stopping is not specified.

[0042] This calculates time-series data Db related to vehicle speed, as shown in Figure 5. Specifically, the time-series data Db calculates the position of vehicle C (e.g., latitude and longitude), the acceleration / deceleration of vehicle C, and the vehicle speed at each timing (in this case, each second) while vehicle C is traveling along the route. In addition, the cumulative distance traveled at each timing (in this case, each second) is also calculated from the temporal change in the position of vehicle C.

[0043] Furthermore, in the simulation, the generation unit 20 calculates the road gradient at each position of vehicle C in order to determine the gradient resistance of vehicle C at each timing (in this case, each second) while vehicle C is traveling along the route. For example, as shown in Figure 6, the generation unit 20 calculates the road gradient at each position along the route based on the elevation difference at each position along the route. Specifically, the generation unit 20 uses the elevation information of each point stored in the map data D1.

[0044] The generation unit 20 extracts flat sections (i.e., zero gradient) from the travel route based on changes in elevation along the route. The generation unit 20 then calculates the gradient of the road between adjacent flat sections from the elevation difference between those points (gradient Θ = elevation difference ΔH / distance between points ΔL).

[0045] Through the processing described above, the generation unit 20 generates time-series data Db showing the temporal changes in the driving state of vehicle C, as shown in Figure 7. The time-series data Db includes, for example, data related to the vehicle speed, acceleration / deceleration, driving position, road gradient at the driving position, and cumulative distance traveled at each timing since vehicle C started driving along the driving route.

[0046] A notable feature of this embodiment is that, when identifying the driving state of vehicle C, it is identified not by the transition of position along the driving route, but by the temporal changes (time-series data Db) at each timing during driving. This is because buses and similar vehicles stop frequently during operation, resulting in frequent deceleration and acceleration. In addition, commercial vehicles such as buses also have long stopping times during driving. During such stopping times, power consumption occurs not only in the drive motor Ca due to idling, but also in the air conditioning equipment Cb and auxiliary equipment Cc. In other words, by identifying the driving state of vehicle C using time-series data Db, the power consumption pattern during route driving in buses and similar vehicles can be calculated with high accuracy.

[0047] In this embodiment, the drive motor Ca is switched from normal operation to regenerative operation each time the vehicle C is decelerating (specified condition (4) above), so the time-series data Db does not include an item to specify the section in which vehicle C is performing regenerative operation, separate from the acceleration / deceleration item. However, if the conditions for switching the drive motor Ca from normal operation to regenerative operation are to be defined in more detail (for example, considering vehicle speed in addition to acceleration / deceleration), it is desirable to include an item in the time-series data Db to specify the section in which vehicle C is performing regenerative operation, separate from the acceleration / deceleration item.

[0048] <Calculation Unit 30> The calculation unit 30 performs a simulation based on the time-series data Db generated by the generation unit 20 to calculate the temporal change in the power consumption of vehicle C when vehicle C is driven according to the driving schedule Da, and also calculates the total power consumption by accumulating these values. In this process, the calculation unit 30 performs the simulation using the calculation model data D4.

[0049] In this embodiment, the calculation unit 30 calculates the temporal change in the power consumption of vehicle C when the vehicle C is driven according to the driving schedule Da. In addition to the power consumption due to the operation of the drive motor Ca that drives the vehicle C, it also calculates the power consumption due to the operation of the air conditioning equipment Cb mounted on the vehicle C and the power consumption due to the operation of the auxiliary equipment Cc mounted on the vehicle. This is because, in the case of commercial vehicles such as buses, the power consumption due to the operation of the air conditioning equipment Cb and the auxiliary equipment Cc mounted on the vehicle C are larger than those of passenger cars, and it is desirable to consider these in order to obtain an accurate power consumption figure.

[0050] First, referring to Figure 8, we will explain the process for calculating the power consumption due to the operation of the drive motor Ca of vehicle C.

[0051] The power consumption of the drive motor Ca typically depends on the output of the drive motor Ca. If the required acceleration and vehicle speed are fixed, the output of the drive motor Ca is fed back to the control system to overcome the acceleration resistance, air resistance, rolling resistance, and gradient resistance experienced by the vehicle C, so that the required acceleration and vehicle speed are achieved.

[0052] The acceleration resistance experienced by vehicle C is the resistance force encountered when accelerating vehicle C, and is generally determined by the acceleration and the weight of vehicle C. Air resistance is the resistance force generated by friction between the vehicle surface and the air, and is determined by the vehicle speed. Rolling resistance is the resistance force generated by energy loss due to tire deformation, and increases in proportion to the total weight of vehicle C. Gradient resistance is the resistance force generated when climbing a slope, and increases in proportion to the weight of vehicle C and the angle of the road gradient. From the above, the output of the drive motor Ca (i.e., the amount of power consumed) is determined almost uniquely from the acceleration of vehicle C, the vehicle speed, and the road gradient identified in the time-series data Db.

[0053] However, the drive motor Ca experiences drive losses. The drive losses of the drive motor Ca vary depending on the ambient temperature (i.e., air temperature). Generally, as the ambient temperature of the drive motor Ca rises, the drive losses of the drive motor Ca also increase. Therefore, in this case, in addition to the acceleration, vehicle speed, and road gradient of vehicle C specified in the time-series data Db, air temperature is set as an explanatory variable. This air temperature may be estimated from the calendar month in which vehicle C is driven. Note that the number of passengers in Figure 8 is a variable that determines the weight of vehicle C. This is an auxiliary explanatory variable and will be discussed later in Modification 2.

[0054] In this embodiment, the calculation unit 30 uses, for example, model data of a classifier trained by machine learning (see Figure 8) as the calculation model data D4. For example, a neural network can be used as such a classifier model.

[0055] Such a classifier model is trained using machine learning with driving history data of vehicle C or vehicles of the same type as vehicle C as training data. Specifically, the training data used is a dataset that associates various driving conditions (acceleration, vehicle speed, and road gradient) of vehicle C or vehicles of the same type with the power consumption per unit time [kWh] of the drive motor Ca at that time.

[0056] The machine learning method itself is the same as known methods, so a detailed explanation will be omitted here. In the learning process, various driving condition data (acceleration, vehicle speed, and road gradient) are input from the input layer, and the output layer outputs the power consumption per unit time [kWh] of the drive motor Ca. Then, the error between this output power consumption [kWh] and the ground truth power consumption [kWh] is taken, and the error is propagated from the output layer to each layer using backpropagation, adjusting the network parameters (i.e., weight coefficients and biases) to approach the ground truth value.

[0057] The trained classifier model data, which has undergone this learning process, is stored as calculated model data D4 in the vehicle C's external storage device 104. Specifically, the external storage device 104 stores model data for the input layer, hidden layer, and output layer of the neural network, as well as network parameters (i.e., weight coefficients and biases) adjusted through the learning process.

[0058] The calculation unit 30 takes the data from the time-series data Db generated by the generation unit 20 at each timing point as input to the classifier model that has undergone the learning process in this manner, performs a simulation (for example, forward propagation of a neural network), and calculates the amount of power consumed by the vehicle C (drive motor Ca) during that simulation. The calculation unit 30 then calculates the time progression of the power consumption of the vehicle C when the vehicle C is driven according to the driving schedule Da by performing the power consumption calculation process on all the data in the time-series data Db. Finally, it calculates the total power consumption by accumulating and adding these values ​​together.

[0059] Furthermore, in this embodiment, vehicle C is configured to regenerate power from the drive motor Ca when decelerating (i.e., the negative power consumption in Figure 8 represents regenerative power). Therefore, the amount of power consumption identified from the time-series data Db is regenerative power when decelerating. Accordingly, when the calculation unit 30 calculates the total power consumption of the drive motor Ca, it calculates a value obtained by subtracting the amount of regenerative power generated by regenerative power operation while vehicle C travels the route from the amount of power consumed by vehicle C traveling the route.

[0060] Furthermore, the classifier used in the calculated model data D4 may be an SVM (Support Vector Machine), a Bayesian classifier, or an ensemble model. Alternatively, it may be composed of a combination of multiple types of classifiers.

[0061] Next, we will explain the calculation process for the power consumption due to the operation of the air conditioning equipment Cb and the power consumption due to the operation of the auxiliary equipment Cc.

[0062] The power consumption of the air conditioning unit Cb generally depends on the temperature and the duration of use. Therefore, the calculation model data D4 for calculating the power consumption of the air conditioning unit Cb in vehicle C may, for example, define the relationship between the temperature or calendar month when vehicle C is running and the power consumption.

[0063] Figure 9 shows an example of calculation model data D4 for calculating the power consumption of the air conditioning unit Cb. In the model data D4 of Figure 9, the ON ratio of the air conditioner (i.e., cooling) to the key ON time and the power consumption when the air conditioner is ON are correlated for each calendar month when vehicle C is running. In addition, in the model data D4 of Figure 9, the ON ratio of the heater (i.e., heating) to the key ON time and the power consumption when the heater is ON are correlated for each calendar month when vehicle C is running.

[0064] In other words, according to this model data D4, it is possible to calculate the total power consumption of the air conditioning unit Cb of vehicle C based on the calendar month in which vehicle C is traveling and the total time that vehicle C is traveling as specified in the time series data Db. Furthermore, it is also possible to calculate the power consumption of vehicle C at each point during its journey by, for example, equally dividing the total power consumption of the air conditioning unit Cb of vehicle C by the total time that vehicle C is traveling.

[0065] The power consumption of the auxiliary equipment Cc depends on the usage time. In this embodiment, the auxiliary equipment Cc is assumed to be a fare management device and an electronic display board, etc., which do not depend on the driving state of vehicle C. In other words, the power consumption of the auxiliary equipment Cc at each timing during route travel is considered to be a constant value. By multiplying the power consumption of the auxiliary equipment Cc (specified value) by the total driving time of vehicle C, which is identified from the time-series data Db, it is possible to calculate the total power consumption of the auxiliary equipment Cc of vehicle C.

[0066] As described above, the vehicle management device 1 according to this embodiment calculates the temporal changes and total power consumption of vehicle C when it is driven according to the driving schedule Da, taking into account the power consumption of the drive motor Ca, the power consumption of the air conditioning equipment Cb, and the power consumption of the auxiliary equipment Cc. By this method, the vehicle management device 1 according to this embodiment can calculate the temporal changes and total power consumption of vehicle C with high accuracy.

[0067] Figure 10 is a diagram showing an example of how the time progression of power consumption and the total power consumption are presented when vehicle C, calculated by the calculation unit 30, is driven according to the driving schedule Da.

[0068] Figure 10 shows the time progression of power consumption when vehicle C is driven according to the driving schedule Da, as a graph of cumulative power consumption. The plots in Figure 10 represent the locations of bus stops. The vehicle management device 1 displays the graphed power consumption progression on the display unit 107, for example. In this case, the vehicle management device 1 may also show a comparison with the rechargeable capacity of the battery Cd installed in vehicle C.

[0069] Furthermore, the calculation unit 30 according to this embodiment calculates the energy consumption when vehicle C is driven according to the driving schedule Da, so that the user can compare the characteristics of each type of vehicle C. The energy consumption can be calculated, for example, using the following formula (1). That is, the energy consumption can be calculated by dividing the total power consumption of vehicle C when vehicle C is driven according to the driving schedule Da by the distance traveled when vehicle C travels the route set in the driving schedule Da. Note that the distance traveled [km] in formula (1) can be calculated based on the route set in the driving schedule Da. Alternatively, the distance traveled [km] may be the cumulative distance data specified in the time series data Db.

[0070] Fuel consumption [km / kWh] = Distance traveled [km] / (Energy consumption of drive motor Ca [kWh] + Energy consumption of air conditioning equipment Cb [kWh] + Energy consumption of auxiliary equipment Cc [kWh]) ... Equation (1)

[0071] [Operation Flow of Vehicle Management System 1] Figure 11 is a flowchart showing an example of the process for calculating electricity consumption in the vehicle management device 1. In this embodiment, the flowchart shows how to calculate electricity consumption for each calendar month, taking into account that the power consumption of the drive motor Ca and the air conditioning equipment Cb changes according to the temperature.

[0072] In step S1, when the energy consumption calculation program is started, the vehicle management device 1 displays an operation display screen, for example, as shown in Figure 4, and accepts input of the bus route name from the user.

[0073] In step S2, the vehicle management device 1 reads data (i.e., location information) corresponding to the bus route name entered from the route data D2. Then, the vehicle management device 1 refers to the map data D1 to read the road map corresponding to the route of the bus route name and displays the image of the road map in the display area n1 of the operation display screen (Figure 4).

[0074] In this process, the vehicle management device 1 also displays the location information of bus stops along the route stored in the route data D2, and the location information of intersections and pedestrian crossings along the route stored in the map data D1, on the road map in the display area n1. The vehicle management device 1 then displays a second input unit m2 for setting the stopping time at each bus stop along the route, and a third input unit m3 for setting whether or not to stop at each intersection and pedestrian crossing along the route, on the operation display screen (Figure 4).

[0075] In step S3, the vehicle management device 1 receives user input to the second input section m2 (stopping time at bus stops) and the third input section m3 (whether or not to stop at intersections and pedestrian crossings) on the operation display screen (Figure 4). Then, when the user presses the confirmation button m4 to confirm the driving schedule Da related to the vehicle C's route, the driving schedule Da that reflects these input information is set.

[0076] In step S4, the vehicle management device 1 performs a simulation based on the set travel schedule Da and generates time-series data Db that shows the temporal changes in the driving state of vehicle C when vehicle C travels along the route specified in the travel schedule Da.

[0077] In the following steps S5 to S10, the vehicle management device 1 calculates the total power consumption and energy consumption for each calendar month when vehicle C is driven according to the driving schedule Da, based on the time-series data Db.

[0078] In step S5, the vehicle management device 1 sets the calendar month for which the electricity consumption calculation will be performed as the variable N. Then, the vehicle management device 1 first performs the calculation using N=1 (January).

[0079] In step S6, the vehicle management device 1 calculates the amount of power consumed per second (i.e., the power of the drive motor Ca) while traveling along the route specified in the travel schedule Da, based on the time-series data Db. The vehicle management device 1 then accumulates these per-second power consumption amounts into the total power consumption amount, starting from the beginning of travel.

[0080] In step S7, if the vehicle management device 1 has not yet finished calculating the power consumption up to the last record of the time-series data Db (S7:NO), it returns to S6 and calculates the power consumption for each record. Then, as the calculation of power consumption up to the last record of the time-series data Db is completed (S7:YES), it proceeds to S8.

[0081] In step S8, the vehicle management device 1 obtains the total driving time from the time-series data Db, and based on this total driving time, calculates the power consumption of auxiliary equipment Cc and air conditioning equipment Cb when vehicle C is driven according to the driving schedule Da. Then, it integrates this into the total power consumption.

[0082] In step S9, the vehicle management device 1 uses equation (1) described above to calculate the electricity consumption for month N from the total power consumption and mileage. Then, it increments the variable N for the calendar month used in the electricity consumption calculation (N ⇒ N+1).

[0083] In step S10, the vehicle management device 1 determines whether processing has been completed up to December for the purpose of calculating electricity consumption (i.e., N=13), and repeatedly executes the processes S6 to S9 until processing is completed up to December (S10: NO). Then, as processing is completed up to December (S10: YES), the flow shown in Figure 11 is terminated.

[0084] When the vehicle management device 1 has finished calculating the electricity consumption, it displays, for example, the display screen shown in Figure 12 on the display unit 107. The display screen shown in Figure 12 shows the total power consumption and electricity consumption for each reference month, which were calculated according to the flow shown in Figure 11.

[0085] [effect] As described above, in this embodiment, A setting unit sets a driving schedule that includes location information for the route on which the vehicle will travel, location information for one or more stopping points included in the route, and the stopping time at each of the one or more stopping points. A generation unit generates time-series data showing the temporal changes in the vehicle's driving state when the vehicle travels along the aforementioned route, based on the aforementioned driving schedule. A calculation unit that calculates the total power consumption when the vehicle travels along the route according to the travel schedule based on the time-series data, A vehicle management system equipped with the following was disclosed.

[0086] According to the vehicle management device of this embodiment, a driving schedule is set according to the driving patterns specific to vehicles such as buses, and time-series data showing the temporal changes in the driving state when the vehicle is driven according to the driving schedule is generated. This makes it possible to calculate the temporal changes in power consumption, total power consumption, and energy consumption of buses and other vehicles with high accuracy.

[0087] <Example 1> In the above embodiment, the vehicle management device 1 (calculation unit 30) uses a machine learning-based classifier model as the calculation model data D4 for calculating the temporal change in the power consumption of the drive motor Ca.

[0088] However, as the calculation model data D4, physical model data may be used in which the output of the drive motor Ca, etc., is calculated from the driving state of vehicle C using physical calculations.

[0089] Figure 13 illustrates other methods for calculating the power consumption of the drive motor Ca (methods using physical model data).

[0090] In this modified example, the calculation unit 30 calculates the power consumption of the drive motor Ca using pre-prepared physical model data. Since this physical model data is based on known technology, its explanation is omitted here. However, it involves identifying the correspondence between the acceleration / deceleration, vehicle speed, and gradient (i.e., time-series data Db) of the vehicle C and the acceleration resistance, air resistance, rolling resistance, and gradient resistance acting on the vehicle C, using equations of motion, etc. The physical model data then identifies the drive output required for the drive motor Ca in accordance with these resistances.

[0091] In other words, in this modified example, the calculation unit 30 uses pre-prepared physical model data to calculate the acceleration resistance, air resistance, rolling resistance, and gradient resistance applied to vehicle C based on time-series data Db (i.e., the required acceleration / deceleration, required vehicle speed, and road gradient), and also calculates the required drive output for vehicle C.

[0092] The calculation unit 30 then takes into account the drive losses of the drive motor Ca (e.g., iron loss, copper loss, and mechanical loss) which are set proportionally to the drive output, and calculates the power to be supplied to the drive motor Ca (i.e., the amount of power consumed). Using this method, as in the above case, it is possible to calculate the temporal change in the amount of power consumed by the vehicle C while traveling along the route, and the total amount of power consumed by accumulating these.

[0093] <Modification 2> When setting the travel schedule Da, the vehicle management device 1 may allow setting the weight of vehicle C before and after each of the one or more stopping positions, and may calculate the amount of power consumed according to the weight of vehicle C.

[0094] The weight of vehicle C affects the acceleration resistance, rolling resistance, and gradient resistance acting on vehicle C, and the amount of power consumed by the drive motor Ca changes depending on the weight of vehicle C. In particular, in the case of buses, the weight of vehicle C changes before and after bus stops depending on the number of passengers while traveling according to the travel schedule Da. Therefore, it is desirable that the setting unit 10 be able to set the weight of vehicle C before and after each of one or more bus stops.

[0095] Figure 14 shows a modified example of the operation display screen when the setting unit 10 accepts the setting of the travel route of vehicle C from the user. In Figure 14, a fourth input unit m5 (for example, a text box) for setting the number of passengers at each stop along the travel route is displayed on the operation display screen, allowing the user to set the number of passengers after passengers have boarded at each stop.

[0096] The calculation unit 30 then calculates the amount of power consumed at each timing while the vehicle C is running, and calculates the amount of power consumed according to the weight of the vehicle C. However, in this case, it is necessary to construct the calculation model data D4 by adding the weight of the vehicle C (for example, the number of occupants) as an explanatory variable.

[0097] In this way, by calculating the power consumption of vehicle C (for example, the drive motor Ca) according to the change in the weight of vehicle C, it is possible to calculate the power consumption of vehicle C with greater accuracy.

[0098] <Variation 3> In the above embodiment, the user decides whether or not to stop at a traffic light or pedestrian crossing. However, the setting unit 10 may be configured so that whether or not to stop at a traffic light or pedestrian crossing is determined with a predetermined probability. Furthermore, in this case, the setting unit 10 may be configured so that the predetermined probability can be set individually for each traffic light or pedestrian crossing along the route by user input.

[0099] In this case, the setting unit 10 determines whether or not to stop at each traffic light or pedestrian crossing by performing a pseudo-probability calculation, and then sets the driving schedule Da.

[0100] <Modification 4> In the above embodiment, the power consumption when the calendar month variable N=12 was calculated from the power consumption when N=1. However, the temperature or calendar month when the vehicle C is driven according to the driving schedule Da may be set individually.

[0101] In this case, the setting unit 10 may accept input from the user for the calendar month in which the vehicle C for which power consumption is to be calculated will be driven. When the setting unit 10 accepts input for the calendar month, it sets a driving schedule Da that includes the input calendar month. The generation unit 20 generates time-series data Db that includes the calendar month set in the driving schedule Da. Then, the calculation unit 30 calculates the power consumption based on the set calendar month. Specifically, the calculation unit 30 calculates the power consumption when the calendar month variable N is the value corresponding to the set calendar month. Alternatively, the setting unit 10 may accept input for the temperature in which the vehicle C will be driven instead of the calendar month. In that case, the setting unit 10 sets a driving schedule Da that includes the input temperature. Then, the calculation unit 30 calculates the power consumption based on the set temperature.

[0102] <Modification 5> In generating time-series data Db when vehicle C travels along a route, a simulation may be performed according to a timetable (i.e., a schedule) that shows the times when vehicle C visits one or more stopping points.

[0103] In this case, the route data D2 stores the location information of the bus route, the location information of the bus stops, the bus route name, and the bus schedule associated with the bus route. When setting the driving schedule Da, the setting unit 10 can refer to the schedule stored in the route data D2 and set the driving schedule Da including the schedule. Specifically, it can set the driving schedule Da including the departure time at each bus stop based on the schedule. The generation unit 20 may perform a simulation by appropriately changing the stopping time at each bus stop so that vehicle C departs each bus stop at the departure time specified based on the schedule. Specifically, at each bus stop, if the stopping time corresponding to the stopping position has elapsed since vehicle C arrived but the departure time has not passed, the stopping time may be extended until the departure time. At this time, if the departure time has passed since vehicle C arrived and the stopping time corresponding to the stopping position has elapsed, the stopping time is retained.

[0104] Furthermore, the setting unit 10 may set a driving schedule Da, including the arrival time at each stop, based on the timetable. In this case, the generation unit 20 may perform a simulation by appropriately changing the acceleration / deceleration and vehicle speed based on the travel time between adjacent stops, so that the vehicle C arrives at each stop at the arrival time specified in the timetable.

[0105] Although specific examples of the present invention have been described in detail above, these are merely illustrative and do not limit the scope of the claims. The technologies described in the claims include various modifications and changes to the specific examples illustrated above. Furthermore, the specific examples illustrated above may be combined as appropriate. [Industrial applicability]

[0106] According to the vehicle management device of the present invention, it is possible to estimate the pattern of power consumption during the operation of buses and the like with higher accuracy. [Explanation of symbols]

[0107] 1. Vehicle management system 10. Settings section 20 Generation part 30 Calculation Section C Vehicle Ca drive motor Ca drive motor every time Cb air conditioning equipment Cc auxiliary equipment CD battery D1 Map Data D2 Route Data D3 Driving Conditions Data D4 Calculation Model Data Da Driving Schedule Db Time Series Data

Claims

1. A setting unit sets a driving schedule that includes location information for the route on which the vehicle will travel, location information for one or more stopping points included in the route, and the stopping time at each of the one or more stopping points. A generation unit generates time-series data showing the temporal changes in the vehicle's driving state when the vehicle travels along the aforementioned route, based on the aforementioned driving schedule. A calculation unit that calculates the total power consumption when the vehicle travels along the route according to the travel schedule based on the time-series data, A vehicle management system equipped with the following features.

2. The calculation unit calculates the electricity consumption based on the total power consumption and the distance of the route. The vehicle management device according to claim 1.

3. The calculation unit applies a calculation model based on the time-series data to calculate the temporal progression of power consumption when the vehicle travels along the route, and presents the temporal progression of power consumption to the user. The vehicle management device according to claim 1.

4. The calculation unit applies a calculation model to the time-series data to calculate the total power consumption, which includes the power consumption due to the operation of the drive motor that drives the vehicle, the power consumption due to the operation of the air conditioning equipment mounted on the vehicle, and the power consumption due to the operation of the auxiliary equipment mounted on the vehicle. The vehicle management device according to claim 1.

5. The vehicle for which the total power consumption is to be calculated is driven according to the driving schedule, and the setting unit has a setting unit for setting the temperature or calendar month when the vehicle is driven according to the driving schedule. The calculation unit calculates the total power consumption based on the temperature or calendar month when the vehicle is driven, as set above. The vehicle management device according to claim 1.

6. The time-series data generated by the generation unit includes the time changes in the acceleration / deceleration of the vehicle, the vehicle speed, and the road gradient over which the vehicle travels when traveling along the route according to the travel schedule. The calculation unit calculates the amount of power consumed at each timing of the time-series data according to the acceleration / deceleration, the vehicle speed, and the road gradient, and calculates the total amount of power consumed by accumulating and adding up the amounts of power consumed. The vehicle management device according to claim 1.

7. The aforementioned travel schedule further includes the speed limits of each road along the route, The generation unit performs a simulation based on the driving schedule, under the conditions that the acceleration and deceleration when acceleration or deceleration is necessary for the vehicle is set to a constant value, and the upper limit of the vehicle's speed is set to the speed limit. The vehicle management device according to claim 1.

8. The time-series data generated by the generation unit includes the time change in the regenerative driving state of the vehicle when it travels along the route according to the travel schedule, The calculation unit calculates the total power consumption by subtracting the amount of regenerative power generated by regenerative operation while the vehicle travels along the route from the amount of power consumed by the vehicle traveling along the route, which is calculated based on the time-series data. The vehicle management device according to claim 1.

9. The aforementioned vehicle is a route bus, The one or more stopping locations mentioned above include bus stops where the route bus allows passengers to board and alight. The vehicle management device according to claim 1.

10. The setting unit is capable of setting location information relating to traffic signals and / or pedestrian crossings installed within the route, The generation unit generates the time-series data based on the driving schedule, with settings to stop the vehicle at the traffic light or pedestrian crossing based on user specifications or with a predetermined probability. The vehicle management device according to claim 1.

11. The setting unit allows the predetermined probability to be set for each traffic light or pedestrian crossing within the route. The vehicle management device according to claim 10.

12. The setting unit allows the weight of the vehicle to be set before and after each of the one or more parking positions. The calculation unit calculates the amount of power consumed by the vehicle at each timing of the time-series data, according to the vehicle's weight. The vehicle management device according to claim 1.

13. The location information of the aforementioned route includes the latitude, longitude, and altitude of each location within the route. The generation unit extracts flat roads within the route based on the elevation of each location within the route, and calculates the road gradient at each location within the route based on the elevation difference between adjacent flat roads. The vehicle management device according to claim 1.

14. The aforementioned power consumption calculation model is a classifier model that has been pre-machine-trained using past driving data of the vehicle or a vehicle of the same type as the aforementioned vehicle. The vehicle management device according to claim 1.

15. The aforementioned travel schedule further includes a timetable showing the times for visiting the one or more aforementioned stopping locations, The setting unit sets the departure time for each of the one or more stopping positions based on the timetable. The generating unit, at each of the stopping positions, retains the stopping time if the stopping time corresponding to the stopping position elapses after the vehicle arrives and the departure time has passed. If the aforementioned vehicle arrives and the aforementioned stopping time corresponding to the stopping position has elapsed but the aforementioned departure time has not yet passed, the simulation will be performed based on the aforementioned travel schedule, with the condition that the stopping time will be extended until the aforementioned departure time. The vehicle management device according to claim 1.

16. A process for setting a driving schedule that includes location information of the route on which the vehicle will travel, location information of one or more stopping points included in the route, and the stopping time at each of the one or more stopping points. A process to generate time-series data showing the temporal changes in the vehicle's driving state when the vehicle travels along the aforementioned route, based on the aforementioned driving schedule; A process to calculate the total power consumption when the vehicle travels along the route according to the travel schedule, based on the aforementioned time-series data, A vehicle management method that involves performing the following actions.

17. A process for setting a driving schedule that includes location information of the route on which the vehicle will travel, location information of one or more stopping points included in the route, and the stopping time at each of the one or more stopping points. A process to generate time-series data showing the temporal changes in the vehicle's driving state when the vehicle travels along the aforementioned route, based on the aforementioned driving schedule; A process to calculate the total power consumption when the vehicle travels along the route according to the travel schedule, based on the aforementioned time-series data, A vehicle management program that includes the following features.

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