Information processing apparatus, control method, program, and storage medium

Abstract

To provide an information processing apparatus configured to accurately estimate energy consumption of an air-conditioner.SOLUTION: An information processing apparatus includes an acquisition unit, a consumption distribution generation unit, and a calculation unit. The acquisition unit acquires travel schedule information including a scheduled area and a scheduled time for travel. The consumption distribution generation unit generates a consumption distribution of an air-conditioner based on the travel schedule information and past temperature data. The calculation unit calculates, based on the consumption distribution of the air-conditioner, consumption higher than an expected value, as energy consumption of the air-conditioner.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to estimating the energy consumption of an air conditioner. [Background technology]

[0002] There are known techniques for estimating the energy consumption of a moving object. For example, Patent Document 1 discloses a technique for estimating the energy consumption that is close to the actual driving conditions. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. WO2013-080312 Summary of the Invention [Problem to be solved by the invention]

[0004] In order to simulate whether a business entity can switch from gasoline-powered vehicles to electric vehicles (EVs), it is necessary to estimate the energy consumption of those gasoline-powered vehicles. In this case, it is necessary to take into account the energy consumption of heating and cooling equipment and air conditioning equipment (hereinafter referred to as "air conditioners") as an indicator of whether the switch can be made without any problems.

[0005] In view of the above-mentioned problems, one object of the present invention is to provide an information processing device that can accurately estimate the energy consumption of an air conditioner. [Means for solving the problem]

[0006] The claimed invention is an information processing device, an acquisition unit that acquires travel schedule information including a planned travel area and a planned travel time; a consumption distribution generating unit that generates a consumption distribution of an air conditioner based on the travel schedule information and past temperature data; a calculation unit that calculates a consumption amount higher than an expected value as the energy consumption amount of the air conditioner based on the consumption amount distribution of the air conditioner; The information processing device is characterized by comprising:

[0007] The claimed invention is a control method executed by an information processing device, an acquisition step of acquiring travel schedule information including a planned travel area and a planned travel time; a consumption distribution generating step of generating a consumption distribution of an air conditioner based on the travel schedule information and past temperature data; a calculation step of calculating a consumption amount higher than an expected value as the energy consumption of the air conditioner based on the consumption distribution of the air conditioner; The control method is characterized by having the following.

[0008] The claimed invention is a program executed by a computer, an acquisition means for acquiring travel schedule information including a planned travel area and a planned travel time; a consumption distribution generating means for generating a consumption distribution of an air conditioner based on the travel schedule information and past temperature data; The program causes a computer to function as calculation means for calculating a consumption amount higher than an expected value as the energy consumption amount of the air conditioner based on the consumption amount distribution of the air conditioner. [Brief explanation of the drawings]

[0009] [Figure 1] 1 illustrates an example of the configuration of an energy consumption estimation system according to an embodiment. [Figure 2] 1 shows an example of a schematic configuration of a server device. [Figure 3] 2 shows an example of a functional configuration of a server device. [Figure 4] 10 shows an example of generating a consumption distribution. [Figure 5] 1 is a flowchart illustrating a processing procedure according to an embodiment. [Figure 6] An example of past temperature data is shown below. [Figure 7] An example of the energy consumption distribution of an air conditioner is shown below. DETAILED DESCRIPTION OF THE INVENTION

[0010] In one preferred embodiment of the present invention, an information processing device includes an acquisition unit that acquires driving schedule information including a planned driving area and a planned driving time, a consumption distribution generation unit that generates an air conditioner consumption distribution based on the driving schedule information and past temperature data, and a calculation unit that calculates a consumption amount that is higher than an expected value as the air conditioner energy consumption based on the air conditioner consumption distribution.

[0011] The information processing device can generate a distribution of air conditioner energy consumption based on past temperature data in the planned driving area. The information processing device can also estimate air conditioner energy consumption by taking into account the distribution of air conditioner energy consumption. The estimated air conditioner energy consumption can be used in a simulation for switching from a gasoline-powered vehicle to an EV.

[0012] In one aspect of the information processing device, the calculation unit determines the 95th percentile value of the consumption distribution as the energy consumption of the air conditioner. This aspect allows the information processing device to estimate the energy consumption of the air conditioner while taking into account cases where the energy consumption is statistically high.

[0013] In another aspect of the information processing device, the consumption distribution generating unit generates the air conditioner energy consumption distribution based on the travel schedule information, past temperature data, and future temperature forecast data. This aspect allows the information processing device to estimate the energy consumption of the air conditioner taking into account the effect of future temperature increases.

[0014] In another aspect of the information processing device, the air conditioner is an air conditioner mounted on a vehicle. With this aspect, the information processing device can estimate the energy consumption of an air conditioner mounted on a vehicle, rather than an air conditioner installed in a home or office.

[0015] In another preferred embodiment of the present invention, a control method executed by an information processing device includes: an acquisition step of acquiring travel schedule information including a planned travel area and a planned travel time; a consumption distribution generation step of generating an air conditioner consumption distribution based on the travel schedule information and past temperature data; and a calculation step of calculating an air conditioner energy consumption that is higher than an expected value based on the air conditioner consumption distribution. By executing this control method, the information processing device can generate an air conditioner energy consumption distribution based on past temperature data of the planned travel area. Furthermore, by executing this control method, the information processing device can estimate the air conditioner's energy consumption taking into account the air conditioner energy consumption distribution.

[0016] In yet another embodiment of the present invention, a program executed by a computer causes the computer to function as: an acquisition means for acquiring travel schedule information including a planned travel area and a planned travel time; a consumption distribution generation means for generating an air conditioner consumption distribution based on the travel schedule information and past temperature data; and a calculation means for calculating an air conditioner energy consumption amount that is higher than an expected value based on the air conditioner consumption distribution. By executing this program, the computer of the information processing device can generate a distribution of air conditioner energy consumption based on past temperature data of the planned travel area. Also, by executing this program, the computer of the information processing device can estimate the air conditioner energy consumption taking into account the distribution of air conditioner energy consumption.

[0017] Preferably, the program is stored in a storage medium. [Example]

[0018] Preferred embodiments of the present invention will now be described with reference to the drawings.

[0019] <System configuration> [Overall configuration] FIG. 1 shows an example of the configuration of an energy consumption estimation system according to an embodiment. The energy consumption estimation system includes a server device 1, an on-board device 2 installed in a vehicle, and a user terminal 3 used by a business entity. The server device 1 and the on-board device 2 communicate data via a communication network 4 such as the Internet or a dedicated communication network. The server device 1 and the user terminal 3 also communicate data via the communication network 4. The server device 1 is an example of an "information processing device."

[0020] The server device 1 estimates the energy consumption of vehicles owned by a business entity. In particular, the server device 1 of this embodiment is characterized in that it can estimate the energy consumption with a margin, taking into account the area and time period in which the vehicle is scheduled to travel. The energy consumption estimated by the server device 1 includes the fuel consumption rate (fuel efficiency) and the power consumption rate (electricity efficiency).

[0021] The vehicle-mounted device 2 is a terminal device that travels with the vehicle. The vehicle-mounted device 2 acquires vehicle travel data (probe data) for each trip and transmits the data to the server device 1. In this embodiment, it is assumed that there are multiple vehicles equipped with the vehicle-mounted devices 2, and the travel data of the multiple vehicles is transmitted to the server device 1.

[0022] The user terminal 3 is a terminal device used by a business entity that uses the energy consumption estimation system, and is, for example, the business entity's server device or a personal computer (PC). The user terminal 3 stores driving data of a vehicle owned by the business entity (hereinafter also referred to as a "target vehicle"). When using the energy consumption estimation system, the user terminal 3 transmits the driving data of the target vehicle to the server device 1. The target vehicle is an example of a "mobile body to be evaluated."

[0023] [Server device] 2 shows an example of a schematic configuration of the server device 1. The server device 1 mainly includes a communication unit 11, a storage unit 12, and a control unit 13. The elements within the server device 1 are connected to each other via a bus line 19.

[0024] The communication unit 11 performs data communication with external devices such as the in-vehicle device 2 and the user terminal 3 under the control of the control unit 13 .

[0025] The storage unit 12 is configured with various types of memory such as RAM (Random Access Memory), ROM (Read Only Memory), and non-volatile memory (including a hard disk drive, flash memory, etc.). The storage unit 12 stores programs for the server device 1 to execute predetermined processes. The storage unit 12 is also used as a working memory for the control unit 13. The programs executed by the server device 1 may be stored in a storage medium other than the storage unit 12.

[0026] The storage unit 12 also stores a map DB (DataBase) 121, a travel information DB 122, a target vehicle DB 123, a consumption amount DB 124, and a temperature DB 125.

[0027] The map DB 121 is a database including, for example, road data, facility data, and data on features around the roads. The road data includes, for example, data representing a road network using a combination of nodes and links. The road data also includes, for example, data indicating the link length and attributes of each link constituting the road network. The data indicating the road attributes may include, for example, the road type, facilities on the road, and the road name. Note that, in this embodiment, links can be set as sections obtained by dividing the road network in any manner. For example, in this embodiment, links can be set as sections having any length and / or any shape. In this embodiment, links can be set as sections including nodes, or as sections not including nodes.

[0028] The travel information DB 122 stores travel data received by the server device 1 from the on-vehicle device 2 (i.e., travel data of the vehicle equipped with the on-vehicle device 2). The travel data of the vehicle equipped with the on-vehicle device 2 includes the travel date and time of the vehicle, travel path, travel status (travel speed, acceleration, etc.), etc. The travel data is stored in the travel information DB 122 for each travel, for example.

[0029] The target vehicle DB 123 stores travel data of the target vehicle received by the server device 1 from the user terminal 3. The travel data of the target vehicle includes at least one of information on travel distance, departure point and destination, and travel trajectory.

[0030] The consumption DB 124 stores links constituting a road network and average energy consumption of a vehicle when traveling on the links in association with each other. The average energy consumption of a vehicle is estimated based on, for example, road data (such as gradient) and traffic volume of a certain link, and the traveling conditions of the vehicle traveling on the link (such as traveling speed and acceleration). The consumption DB 124 may also store areas such as prefectures in association with average energy consumption of a vehicle when traveling in the area.

[0031] Past temperature data for each area is stored in the temperature DB 125. The server device 1 acquires weather information including the temperature data for each area from a weather system that provides weather information, and stores the information in the temperature DB 125.

[0032] The control unit 13 includes a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), etc., and controls the entire server device 1. The control unit 13 also executes programs stored in the storage unit 12 to perform various processes.

[0033] The configuration of the server device 1 shown in FIG. 2 is an example, and various modifications may be made to the configuration shown in FIG.

[0034] [Function Configuration] 3 shows an example of the functional configuration of the server device. The server device 1 includes the above-mentioned travel information DB 122, target vehicle DB 123, and consumption DB 124, as well as a consumption distribution creation unit 101, an energy consumption calculation unit 102, and an output unit 103. The consumption distribution creation unit 101, the energy consumption calculation unit 102, and the output unit 103 are configured by the control unit 13 shown in FIG. 2.

[0035] When a business entity wishes to estimate the energy consumption of a target vehicle, the business entity transmits the area in which the target vehicle is scheduled to travel (hereinafter also referred to as the "scheduled travel area") or the time period in which the target vehicle is scheduled to travel (hereinafter also referred to as the "scheduled travel time") to the server device 1 via the user terminal 3. The business entity can specify the planned travel area in units of prefectures, etc. The business entity can also specify the planned travel time in units of months, days, etc. The planned travel area or planned travel time is input to the consumption distribution creation unit 101.

[0036] The consumption distribution creation unit 101 creates a distribution of the vehicle's energy consumption in the planned travel area or planned travel period.

[0037] First, the consumption distribution creation unit 101 calculates the average energy consumption of the vehicle by area and by date and time. Specifically, the consumption distribution creation unit 101 acquires driving data of the vehicle equipped with the on-board device 2 from the driving information DB 122, and calculates the energy consumption from each driving data. The consumption distribution creation unit 101 aggregates the calculated energy consumption by area and by date and time, and finds the average value. The data indicating the average energy consumption by area and by date and time will hereinafter be referred to as "aggregated data."

[0038] The energy consumption is calculated based on, for example, the vehicle's travel path and travel state, road data and traffic volume on the travel path, etc. The consumption distribution creating unit 101 may also calculate the energy consumption from the vehicle's travel path by referring to the consumption DB 124.

[0039] Next, the consumption distribution creating unit 101 extracts the average energy consumption for the planned travel area or planned travel period from the aggregated data and creates a distribution. The distribution created by the consumption distribution creating unit 101 will be referred to as the "consumption distribution" hereinafter.

[0040] FIG. 4 shows an example of generating a consumption distribution. In FIG. 4, it is assumed that "XX area" is specified as the planned travel area and "December" is specified as the planned travel time. In this case, the consumption distribution generating unit 101 extracts a list such as the example shown in FIG. 4(A) from the aggregated data and generates a consumption distribution such as the example shown in FIG. 4(B). In FIG. 4(B), "e" indicates an expected value and "p" indicates a percentile value.

[0041] Returning to FIG. 3, the energy consumption calculation unit 102 calculates the energy consumption of the target vehicle (also referred to as "estimated energy consumption") based on the consumption distribution and the travel data of the target vehicle.

[0042] The energy consumption calculation unit 102 acquires travel data of the target vehicle from the target vehicle DB 123. The travel data of the target vehicle includes at least one of information on travel distance, departure point and destination, and travel trajectory. The energy consumption calculation unit 102 determines a calculation method for the energy consumption of the target vehicle based on the information included in the travel data of the target vehicle, and performs calculations. The calculation method for the energy consumption of the target vehicle will be described below.

[0043] (Method 1) When the travel data of the target vehicle includes only the travel distance, the energy consumption calculation unit 102 calculates the energy consumption of the target vehicle using the following formula (1). "p" in formula (1) represents the 95th percentile value of the consumption distribution. Note that the above percentile value is an example, and p may be set to be higher than the expected value e. "p" in formula (1) is an example of the first percentile value. Energy consumption (l / km) = mileage (km) × p …(1)

[0044] As described above, the energy consumption calculation unit 102 can estimate energy consumption taking into account the planned travel area and planned travel time, and with a margin of error, by multiplying the travel distance by a predetermined percentile value of the consumption distribution.

[0045] (Method 2) When the travel data of the target vehicle includes a departure point and a destination but does not include a travel trajectory, the energy consumption calculation unit 102 can calculate the energy consumption using the following equation (2). Energy consumption (l / km) = Representative route consumption (l / km) × p / e … (2)

[0046] The "representative route consumption" in formula (2) is the average energy consumption on a representative route from the departure point to the destination (hereinafter also referred to as the "representative route"). The energy consumption calculation unit 102 refers to the map DB 121 to determine a representative route from the departure point to the destination. Then, the energy consumption calculation unit 102 refers to the consumption DB 124 to calculate the average energy consumption when the target vehicle travels along the representative route. Furthermore, "p" in formula (2) represents the 95th percentile value of the consumption distribution. "e" represents the expected value of the consumption distribution. Note that the above percentile values ​​are examples, and p may be set to be higher than the expected value e. "p" in formula (2) is an example of the second percentile value.

[0047] (Method 3) When the travel data of the target vehicle includes a travel trajectory, the energy consumption calculation unit 102 can calculate the energy consumption using the following equation (3). Energy consumption (l / km) = Driving trajectory consumption (l / km) × p / e … (3)

[0048] "Travel trajectory consumption" in formula (3) is the average energy consumption on the travel trajectory of the target vehicle. The energy consumption calculation unit 102 calculates the average energy consumption when the target vehicle travels the travel trajectory by referring to the consumption DB 124. Furthermore, "p" in formula (3) represents the 95th percentile value of the consumption distribution. "e" represents the expected value of the consumption distribution. Note that the above percentile values ​​are examples, and p may be set to be higher than the expected value e. "p" in formula (3) is an example of the second percentile value.

[0049] As described above, the energy consumption calculation unit 102 can estimate the energy consumption of the target vehicle taking into account the planned travel area and planned travel time, and with some leeway, by multiplying the representative route consumption or the travel trajectory consumption by the ratio between a predetermined percentile value of the consumption distribution and the expected value.

[0050] The output unit 103 outputs the energy consumption of the target vehicle calculated by the energy consumption calculation unit 102. The energy consumption can be used for simulations such as switching from a gasoline vehicle to an EV.

[0051] In the above configuration, the consumption distribution creation unit 101 is an example of the travel schedule acquisition unit, second travel data acquisition unit, and consumption distribution generation unit of the present invention, and the energy consumption calculation unit 102 is an example of the first travel data acquisition unit and calculation unit of the present invention.

[0052] [Processing flow] 5 is an example of a flowchart showing the procedure of a process executed by the server device 1. This process is realized by the control unit 13 shown in FIG. 2 executing a program prepared in advance.

[0053] First, the consumption distribution creation unit 101 generates aggregated data based on driving data of the vehicle equipped with the on-board device 2 (step S11). The aggregated data is data indicating average energy consumption by area and by date and time. Next, the consumption distribution creation unit 101 acquires the planned driving area or planned driving period from the user terminal 3 (step S12). The planned driving area is specified by prefecture or the like. The planned driving period is specified by month or day.

[0054] Next, the consumption distribution creation unit 101 extracts the average energy consumption for the planned travel area or planned travel period from the aggregated data and creates a distribution (step S13). Next, the energy consumption calculation unit 102 acquires travel data of the target vehicle from the target vehicle DB 123. The energy consumption calculation unit 102 calculates the energy consumption of the target vehicle based on the consumption distribution and the travel data of the target vehicle (step S14). The output unit 103 outputs the calculated energy consumption (step S15). Then, the processing ends.

[0055] [Variations] Next, preferred modifications of the above-described embodiment will be described. The following modifications may be applied to the above-described embodiment in combination.

[0056] (Variation 1) The server device 1 may estimate the energy consumption of an air conditioner installed in the vehicle. The energy consumption of the air conditioner can be added to the energy consumption of the target vehicle, for example. This allows the server device 1 to estimate the energy consumption of the target vehicle in more detail.

[0057] For example, the server device 1 generates an air conditioner energy consumption distribution from past temperature data for a certain area and a certain time period, and then estimates the air conditioner energy consumption of the target vehicle based on the generated distribution.

[0058] Specifically, when a business entity wants to estimate the energy consumption of an air conditioner, the business entity first transmits the planned driving area or planned driving time of the target vehicle to the server device 1 via the user terminal 3. The business entity can specify the planned driving area in units of prefectures, etc. The business entity can also specify the planned driving time in units of months, days, etc.

[0059] Next, the control unit 13 extracts past temperature data for the planned travel area and planned travel time from the temperature DB 125. Fig. 6 shows an example of past temperature data. For example, if the planned travel area is "Tokyo" and the planned travel time is "August 10th," the control unit 13 extracts past temperature data from the temperature DB 125, as shown in Fig. 6.

[0060] Next, the control unit 13 calculates the energy consumption of the air conditioner from past temperature data using a temperature / consumption model. For example, the control unit 13 calculates the energy consumption of the air conditioner by year and by hour for past temperature data such as the example shown in FIG. 6. The temperature / consumption model is a machine learning model that has been trained in advance, and takes the outside temperature as input and the energy consumption of the air conditioner as output. The control unit 13 may also calculate the energy consumption of the air conditioner by performing a driving simulation in a virtual environment using the past temperature data.

[0061] Note that the control unit 13 may calculate the energy consumption of the air conditioner from future temperature forecast data in addition to past temperature data, and use the calculated energy consumption for distribution, which will be described later. For example, the communication unit 11 obtains future temperature forecasts from a weather system that provides weather information. The control unit 13 then calculates the energy consumption of the air conditioner for the next year and thereafter from the future temperature forecast data using a temperature / consumption model or a driving simulation.

[0062] Next, the control unit 13 distributes the energy consumption of the air conditioner by year and by hour calculated from the past temperature data. The distribution generated by the control unit 13 is hereinafter referred to as the "air conditioner consumption distribution." The control unit 13 estimates the energy consumption of the air conditioner based on the air conditioner consumption distribution. Specifically, the control unit 13 generates an air conditioner consumption distribution as shown in FIG. 7. "p" in FIG. 7 indicates the 95th percentile value. "e" in FIG. 7 indicates the expected value of the consumption distribution. The control unit 13 estimates the 95th percentile value as the energy consumption of the air conditioner based on the distribution in FIG. 7. Note that the above percentile values ​​are examples, and p may be set to be higher than the expected value e.

[0063] As described above, the server device 1 of the first modification can estimate the energy consumption of the air conditioner by using the air conditioner consumption distribution, taking into account the planned travel area and planned travel time, and leaving some margin.

[0064] (Variation 2) The server device 1 can simulate switching from a gasoline-powered vehicle to an EV based on the energy consumption of the target vehicle. For example, the server device 1 estimates electricity consumption as the energy consumption of the target vehicle. The server device 1 calculates the battery capacity required for the EV based on the estimated electricity consumption and the operating period or planned driving distance desired by the business entity. The server device 1 then extracts vehicles that meet the required battery capacity from sales information for new and used cars, and outputs the extracted information to the user terminal 3. At this time, the server device 1 may also output to the user terminal 3 information comparing the costs, such as electricity charges, vehicle costs, and equipment costs, that would be incurred if the business entity switched to an EV with the costs of switching to a gasoline-powered vehicle. Based on the above information, the business entity can consider switching from a gasoline-powered vehicle to an EV.

[0065] (Variation 3) In the above configuration, the server device 1 and the user terminal 3 may be the same device. For example, the server device 1 may execute the processes executed by the user terminal 3. In this case, the server device 1 accumulates driving data of vehicles owned by the business entity. In addition, the business entity directly inputs the planned driving area and planned driving time into the server device 1.

[0066] (Variation 4) The energy consumption estimation system does not need to include the on-board device 2. In this case, the server device 1 only needs to be able to acquire travel data collected by a plurality of on-board devices. The travel data may be text that records the departure and destination of the vehicle. Even in this case, the server device 1 can estimate past energy consumption based on the text and generate a consumption distribution.

[0067] In each of the above-described embodiments, the program can be stored using various types of non-transitory computer-readable media and supplied to a control unit, such as a computer. Non-transitory computer-readable media include various types of tangible storage media (tangible storage media). Examples of non-transitory computer-readable media 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 memories (e.g., mask ROMs, PROMs (Programmable ROMs), EPROMs (Erasable PROMs), flash ROMs, and RAMs (Random Access Memory).

[0068] Although the present invention has been described above with reference to the embodiments, the present invention is not limited to the above embodiments. Various modifications within the scope of the present invention that would be understood by those skilled in the art can be made to the configuration and details of the present invention. In other words, the present invention naturally includes various modifications and alterations that would be possible for those skilled in the art based on the entire disclosure, including the claims, and the technical ideas. Furthermore, the disclosures of the above-cited patent documents and other documents are incorporated herein by reference. [Explanation of symbols]

[0069] 1. Server device 2 On-vehicle device 3. User terminal 4. Communication Network 11 Communications Department 12 Storage section 13 Control Unit 101 Consumption Distribution Creation Department 102 Energy consumption calculation unit 103 Output section 121 Map DB 122 Driving Information DB 123 Target vehicle DB 124 Consumption DB 125 Temperature DB

Claims

1. an acquisition unit that acquires travel schedule information including a planned travel area and a planned travel time; a consumption distribution generating unit that generates a consumption distribution of an air conditioner based on the travel schedule information and past temperature data; a calculation unit that calculates a consumption amount higher than an expected value as the energy consumption amount of the air conditioner based on the consumption amount distribution of the air conditioner; An information processing device comprising:

2. The information processing device according to claim 1 , wherein the calculation unit determines the energy consumption of the air conditioner to be a 95th percentile value of the consumption distribution.

3. The information processing device according to claim 1 , wherein the consumption distribution generating unit generates a consumption distribution of the air conditioner based on the travel schedule information, past temperature data, and future temperature prediction data.

4. 2. The information processing device according to claim 1, wherein the air conditioner is an air conditioner mounted in a vehicle.

5. A control method executed by an information processing device, an acquisition step of acquiring travel schedule information including a planned travel area and a planned travel time; a consumption distribution generating step of generating a consumption distribution of an air conditioner based on the travel schedule information and past temperature data; a calculation step of calculating a consumption amount higher than an expected value as the energy consumption of the air conditioner based on the consumption distribution of the air conditioner; A control method comprising:

6. A computer-executable program, an acquisition means for acquiring travel schedule information including a planned travel area and a planned travel time; a consumption distribution generating means for generating a consumption distribution of an air conditioner based on the travel schedule information and past temperature data; A program that causes a computer to function as calculation means for calculating a consumption amount that is higher than an expected value as the energy consumption amount of the air conditioner based on the consumption amount distribution of the air conditioner.

7. A storage medium storing the program according to claim 6.

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