JP7399058B2 - Average electricity cost calculation device - Google Patents

Description

The present invention relates to an average electricity consumption calculation device.

In a vehicle such as an electric vehicle that runs using electric power stored in a battery, the remaining travelable distance of the vehicle is calculated, for example, based on electricity consumption that indicates the distance that can be traveled per unit of electric power. For example, Patent Document 1 discloses a remaining drivable distance calculation device that more accurately refers to the remaining drivable distance based on current electricity consumption and past electricity consumption.

JP2020-29177A

In Patent Document 1, as the total amount of electricity that can be used to drive the vehicle decreases, the contribution of past electricity costs when calculating the remaining travel distance is made relatively smaller in a quadratic manner, and the contribution of current electricity costs is reduced. It is relatively large. However, in Patent Document 1, the current electricity cost is not significantly reflected in the calculated remaining travel distance unless the total amount of electric power that can be used for driving the vehicle decreases considerably. The remaining travel distance is calculated as the amount of energy available for driving the vehicle divided by the average electricity consumption. In other words, in Patent Document 1, the current electricity cost is not reflected in the average electricity cost unless the total amount of electricity decreases considerably.

For example, if a vehicle that is used for commuting on a daily basis is used for non-daily purposes such as leisure time on weekends, the average speed and travel time of the vehicle will be different from the average vehicle speed and travel time, so the actual remaining mileage may differ. The distance will vary greatly compared to the daily remaining mileage. In Patent Document 1, when the total amount of electricity that can be used for driving the vehicle is large, the average electricity cost is calculated based on past electricity costs (i.e., daily electricity costs). The electricity cost is not significantly reflected in the average electricity cost, making it impossible to accurately calculate the remaining travel distance.

The present invention has been made in view of the above-mentioned problems, and when a vehicle capable of running on electric power drives in an unusual manner, regardless of the remaining amount of energy that can be used to drive the vehicle, The purpose is to make it possible to calculate the average electricity consumption taking into account driving.

The present invention employs the following configuration as a means for solving the above problems.

The first invention is an average electricity cost calculation device that calculates an average electricity cost, and includes a current period average electricity cost acquisition unit that obtains the current period average electricity cost that is the average of the current period electricity costs, and a current period average electricity cost acquisition unit that obtains the current period average electricity cost that is the average of the current period electricity costs, and past data including past electricity costs. A past average electricity cost acquisition unit that obtains the past average electricity cost, which is the average of the electricity costs in the past period, based on the past period, and calculates an extraordinary index that indicates the degree of deviation of the vehicle running state in the current period from the past vehicle running state. an extraordinary index calculation unit; a weighting coefficient calculation unit that calculates a weighting coefficient based on the extraordinary index; and a contribution level between the current period average electricity cost and the past average electricity consumption based on the weighting coefficient. and an electricity cost calculation unit that calculates the average electricity cost.

A second invention is based on the first invention, wherein the extraordinary index calculation unit selects at least an average vehicle speed in the current period, a travel distance in the current period, and a travel time in the current period as parameters indicating the driving state in the current period. A configuration is adopted in which either one of these is used to calculate the above-mentioned extraordinary index.

A third invention is the first or second invention, wherein in the past data, the past electricity consumption is associated with at least one of a month, a day of the week, and a time zone, and the extraordinary index calculation unit However, a configuration is adopted in which the extraordinary index is calculated based on the above-mentioned past data matched to the month, day of the week, and time zone of the above-mentioned current period.

A fourth invention is, in any one of the first to third inventions, the past data includes a mileage learning value set based on past mileage and a period during which the extraordinary index is smaller than a threshold value. It includes the past daily average electricity cost, which is the average value of electricity costs, and the past non-daily average electricity cost, which is the average value of electricity costs during the period in which the above-mentioned non-daily index is larger than the above-mentioned threshold value. Until the distance exceeds the above mileage distance learning value, replace the current period average electricity cost with the past non-daily average electricity cost, calculate the above average electricity cost using the past daily average electricity cost as the past average electricity cost, and calculate the above average electricity cost for the current period. After the mileage exceeds the mileage learning value, the past daily average electricity cost is used as the past average electricity cost, and the average electricity cost is calculated based on the current period average electricity cost and the past average electricity cost. Adopt.

A fifth aspect of the present invention employs a configuration in which the vehicle according to any one of the first to fourth aspects includes a past data update section that updates the past data based on the driving state during the current period.

A sixth invention is based on the fifth invention, wherein the past data includes a past driving state learning value set based on a past driving state, and the past data updating unit is configured to update the past driving state learning value in the current period. A configuration is adopted in which the smaller the index, the greater the degree of reflection of the current period's driving state on the past driving state learning value, and the updating of the past driving state learning value.

According to the present invention, an extraordinary index indicating the degree of deviation of the vehicle running state during the current period from the past vehicle running state is obtained. Furthermore, the degree of contribution of the current period average electricity cost and the past average electricity cost for calculating the average electricity cost is set according to the weighting coefficient calculated based on this extraordinary index. Therefore, according to the present invention, when the vehicle performs unusual driving, it is possible to reflect the current period average electricity cost in the average electricity cost, regardless of the amount of remaining energy that can be used for driving. Therefore, according to the present invention, when a vehicle that can run on electric power runs in an unusual manner, the average electricity consumption that takes into account the unusual running is calculated regardless of the remaining amount of energy that can be used to drive the vehicle. It becomes possible to calculate.

BRIEF DESCRIPTION OF THE DRAWINGS It is a block diagram which shows the schematic structure of the average electricity consumption calculation apparatus in 1st Embodiment of this invention. It is a graph showing the relationship between running time and an extraordinary index. It is a flowchart for explaining operation of the average electricity cost calculation device in a 1st embodiment of the present invention. It is a flowchart for explaining the operation of the average electricity consumption calculation device in a second embodiment of the present invention. It is a block diagram showing a schematic structure of an average electricity consumption calculation device in a 3rd embodiment of the present invention.

EMBODIMENT OF THE INVENTION Hereinafter, with reference to drawings, one embodiment of the average electric cost calculation apparatus based on this invention is described.

(First embodiment)
FIG. 1 is a block diagram showing a schematic configuration of an average electricity consumption calculation device 1 according to the present embodiment. The average electricity cost calculation device 1 of the present embodiment is an average electricity cost calculation device 1 for calculating the remaining mileage of a vehicle based on the current period average electricity cost, which is the average electricity cost in the current period, and the past average electricity cost, which is the average electricity cost in the past period. This is a device that calculates electricity consumption (average electricity consumption for calculating remaining travel distance). Here, the current period is a period that includes the current period in which the remaining mileage needs to be displayed. This current period can be set in various ways. For example, the current period can be one day including the present (midnight to the present), it can be the period up to 24 hours ago including the present, or it can be the period when the ignition is turned on. It is also possible to specify the period from then to the present. Moreover, the past period means the past period excluding the current period.

The average electricity cost calculation device 1 of this embodiment is mounted on a vehicle that can run on electric power. For example, the average electricity cost calculation device 1 of this embodiment is installed in a vehicle as part of the functions of a computer device installed in the vehicle. As shown in FIG. 1, the average electric cost calculation device 1 of this embodiment receives driving data indicating the driving state of the vehicle from the outside. In this embodiment, vehicle speed, current period travel distance, and current period travel time are input as travel data. However, the driving data is not particularly limited as long as it indicates the driving state of the vehicle. For example, the number of times the ignition is turned on and off or the frequency of stopping the vehicle may be input as driving data.

As shown in FIG. 1, the average electricity cost calculation device 1 of the present embodiment includes a past data storage section 2, a current period average electricity cost acquisition section 3, a past average electricity cost acquisition section 4, an extraordinary index calculation section 5, It includes a weighting coefficient calculation section 6, an electricity cost calculation section 7, and a past data update section 8.

The past data storage unit 2 is a storage unit that stores past data D, which is a data group including past electricity costs. In the present embodiment, the past data D includes a past daily average electricity consumption D1, a past extraordinary average electricity consumption D2, and a past learning value D3 (past driving state learning value).

The past daily average electricity consumption D1 is determined by the period (for example, the days when the extraordinary index a is lower than the predetermined threshold) during the past period when the extraordinary index a, which will be described later, is lower than a predetermined threshold (for example, a=0.5). ) shows the average electricity consumption. This past daily average electricity cost indicates the average electricity cost during a period in which the value of the extraordinary index a is small and the vehicle was driven on a daily basis.

The past extraordinary average electricity consumption D2 indicates the average electricity consumption during a period in which the extraordinary index a is higher than a predetermined threshold (for example, a day when the extraordinary index a is higher than a predetermined threshold) in the past period. This past unusual average electricity cost indicates the average electricity cost during a period in which the value of the unusual index a was large and the vehicle traveled in an unusual manner.

The past learning value D3 is a learning value set based on past driving conditions. This past learning value D3 is set for each of the parameters referred to when calculating the extraordinary index a, and is set based on the past value of each parameter. This past learning value D3 is a value used as a reference when calculating the extraordinary index a for each parameter. In this embodiment, the average vehicle speed in the current period, the travel distance in the current period, and the travel time in the current period are used as parameters to be referred to when calculating the extraordinary index a. Therefore, past learning values D3 are set for each of the average vehicle speed in the current period, the travel distance in the current period, and the travel time in the current period.

In the following explanation, the past learning value D3 (past driving state learning value) set for the average vehicle speed in the current period will be referred to as the "past learning value D3 of average vehicle speed", and the past learning value D3 (past driving state learning value) set for the average vehicle speed in the current period will be The set past learned value D3 is referred to as a "past learned value D3 of travel distance", and the past learned value D3 set for the travel time in the current period is referred to as a "past learned value D3 of travel time".

Furthermore, in the present embodiment, in the past data D, the past daily average electricity cost D1, the past non-daily average electricity cost D2, and the past learned value D3 are associated with each of the month, day of the week, and time zone. That is, the past data D includes, for each month, a past daily average electricity cost D1, a past non-daily average electricity cost D2, and a past learned value D3, each of which uses the day of the week and the time of day as parameters.

Such past data storage unit 2 does not necessarily need to be included in the average electricity cost calculation device 1 of this embodiment. For example, a past data storage unit is installed in the average electricity cost calculation device 1 of this embodiment, and the average electricity consumption calculation device 1 of this embodiment is configured to transmit and receive past data, etc., with an external past data storage unit as necessary. It's okay.

The current period average electricity cost acquisition unit 3 obtains the current period average electricity cost, which is the average of electricity costs in the current period. In the present embodiment, the current period average electricity cost acquisition unit 3 calculates electricity costs continuously or periodically in the current period multiple times based on driving data input from the outside, and calculates the average value of these electricity costs as the current period average. Electricity expenses. The current period average electricity cost acquired by the current period average electricity cost acquisition section 3 is input to the electricity cost calculation section 7 and the past data update section 8.

The past average electricity cost acquisition unit 4 acquires the past average electricity cost, which is the average of the electricity costs in the past period, based on the past data D. In this embodiment, the past average electricity cost acquisition unit 4 acquires data on the month, day of the week, and time period to which the current period belongs from outside or inside the average electricity cost calculation device 1, and A past daily average electricity cost D1 and a past non-daily average electricity cost D2 corresponding to the above are acquired from past data D as past average electricity costs.

The extraordinary index calculation unit 5 calculates an extraordinary index indicating the degree of deviation of the vehicle running state in the current period from the past vehicle running state. Specifically, in this embodiment, the extraordinary index calculation unit 5 acquires the average vehicle speed of the current period, the travel distance of the current period, and the travel time of the current period from the driving data as parameters indicating the driving state of the current period. Further, the extraordinary index calculation unit 5 obtains from the past data D a past learned value D3 of average vehicle speed, a past learned value D3 of travel distance, and a past learned value D3 of travel time.

Here, the extraordinary index calculation unit 5 calculates an extraordinary index a for each parameter indicating the driving state in the current period, and sets the average value of these extraordinary indices a as the final extraordinary index a. For example, in the present embodiment, the extraordinary index calculation unit 5 compares the average vehicle speed of the current period with the past learned value D3 of the average vehicle speed, and if the average vehicle speed of the current period exceeds the past learned value D3 of the average vehicle speed, Then, the extraordinary index a related to the average vehicle speed is increased. In addition, in this embodiment, the extraordinary index a shall be set in the range of 0 to 1. In other words, if the running state of the vehicle during the current period does not deviate from the running state of the vehicle in the past, the extraordinary index a is set to 0. Therefore, in this embodiment, the extraordinary index calculation unit 5 approaches the extraordinary index a regarding the average vehicle speed from 0 to 1 when the average vehicle speed in the current period exceeds the past learned value D3 of the average vehicle speed.

In addition, the extraordinary index calculation unit 5 compares the mileage in the current period with the past learned value D3 of the mileage, and when the mileage in the current period exceeds the past learned value D3 of the mileage, Increase the extraordinary index a. In addition, the extraordinary index calculation unit 5 compares the driving time in the current period with the past learned value D3 of the driving time, and when the driving time in the current period exceeds the past learned value D3 of the driving time, Increase the extraordinary index a.

The extraordinary index calculation unit 5 calculates the average of the extraordinary index a regarding the average vehicle speed, the extraordinary index a regarding the traveling distance, and the extraordinary index a regarding the traveling time as the final extraordinary index a. As described above, in this embodiment, the extraordinary index calculation unit 5 uses the average vehicle speed, travel distance, and travel time as parameters indicating the driving state, and calculates the values of these parameters in the current period (i.e., the driving state in the current period). ) is deviated from the past value (that is, the past driving state), which is calculated as the extraordinary index a.

In addition, in calculating the extraordinary index a, the extraordinary index calculation unit 5 refers to the month, day of the week, and time zone of the current period, and calculates the past learned value D3 that matches these months, days of the week, and time zone from the past data. Obtained from D. That is, in this embodiment, the extraordinary index calculation unit 5 calculates the extraordinary index a based on the past data D that matches the month, day of the week, and time zone of the current period.

FIG. 2 is a graph showing the relationship between the current period of driving time (horizontal axis) and the unusual index a (vertical axis) in driving time, which is one of the parameters indicating the driving state. As shown in this figure, after the travel time in the current period exceeds the past learned value D3, the extraordinary index a continuously increases in a quadratic manner. The extraordinary index calculation unit 5 calculates the extraordinary index a based on the relational expression between the traveling time in the current period and the extraordinary index a. Note that, regardless of only the travel time, the average vehicle speed and travel distance similarly increase continuously in a quadratic manner after exceeding the past learned value D3.

The weighting coefficient calculation unit 6 calculates a weighting coefficient k based on the extraordinary index a. In this embodiment, the average electricity consumption for calculating the remaining travel distance is determined by the weighted average of the current period average electricity consumption and the past average electricity consumption. At this time, the coefficient by which the past average electricity consumption is multiplied is the weighting coefficient k. Note that when performing weighted averaging, the current period average electricity cost is multiplied by (1-k). In this embodiment, the weighting coefficient calculation unit 6 calculates the weighting coefficient k by subtracting the extraordinary index a calculated by the extraordinary index calculation unit 5 from 1.

The electricity cost calculation section 7 calculates the average electricity cost for calculating the remaining mileage by the weighted average of the current period average electricity cost obtained by the current period average electricity cost acquisition section 3 and the past average electricity cost obtained by the past average electricity cost acquisition section 4. . Specifically, the electricity cost calculation unit 7 calculates the average electricity cost for calculating the remaining travel distance by setting the degree of contribution between the current period average electricity cost and the past average electricity cost based on the weighting coefficient k.

Furthermore, in the present embodiment, the electricity cost calculation unit 7 replaces the current period average electricity cost with the past non-daily average electricity cost D2 until the current period mileage exceeds the past learned mileage value D3 (mileage distance learning value). The average electricity cost for calculating the remaining travel distance is calculated using the past daily average electricity cost D1 as the past average electricity cost. Note that after the mileage in the current period exceeds the past learning value D3 of mileage, the electricity cost calculation unit 7 uses the past daily average electricity cost D1 as the past average electricity cost, and calculates the current period average electricity cost and the past daily average electricity cost D1. Based on this, the average electricity consumption for calculating the remaining travel distance is calculated.

Furthermore, the electricity cost calculation unit 7 calculates whether the current period's mileage is the mileage distance so that the average electricity cost for calculating the remaining mileage does not suddenly change when the mileage distance in the current period exceeds the past learning value D3 of the mileage distance. For a certain period of time after the past learned value D3 has been exceeded, the method for calculating the average electricity cost for calculating the remaining travel distance is gradually changed in stages or continuously.

For example, for a certain period of time after the current period's mileage exceeds the past learning distance value D3, the current period's average electricity cost is replaced with the past non-daily average electricity cost D2, and the average electricity cost for calculating the remaining mileage is calculated. The weighted average of the average electricity cost and the average electricity cost for calculating the remaining travel distance calculated based on the past daily average electricity cost D1 is set as the average electricity cost for calculating the remaining travel distance. Furthermore, in calculating the weighted average, the ratio of the average electricity consumption for calculating the remaining mileage calculated based on the current period average electricity consumption and the past daily average electricity consumption D1 is adjusted gradually or as time passes or the mileage increases. Increase continuously.

In this way, by gradually changing the calculation method of the average electricity cost for calculating the remaining mileage, when the mileage in the current period exceeds the past learned value of mileage D3, the average electricity consumption for calculating the remaining mileage suddenly changes. can be prevented from changing.

The past data update unit 8 updates the past data D based on the driving state in the current period, as necessary. Specifically, the past data update unit 8 updates the past daily average electricity cost D1 or the past non-daily average electricity cost D2 using the current period average electricity cost in the current period calculated based on the driving state, as necessary. . For example, if the extraordinary index a in the current period is lower than a preset threshold, the past daily average electricity cost D1 whose month, day of the week, and time zone match the current period is updated based on the current period average electricity cost. On the other hand, if the extraordinary index a in the current period is greater than or equal to a preset threshold, the past extraordinary average electricity cost D2 whose month, day of the week, and time zone match the current period is updated based on the average electricity cost in the current period.

Note that it is not necessary to update the past daily average electricity cost D1 and the past daily average electricity cost D1. For example, a determination as to whether or not to update the past daily average electricity cost D1 and the past daily average electricity cost D1 can be made based on the difference between the current period average electricity cost and the past daily average electricity cost D1 or the past daily average electricity cost D1. For example, when the extraordinary index a is lower than a preset threshold value, the current period average electricity cost and the past daily average electricity cost D1 included in the past data D are compared. Only when these differences are above a certain level (that is, when the discrepancy between the current period average electricity consumption and the past daily average electricity consumption D1 is large), the current period average electricity consumption is taken in as a learning value and the past daily average electricity consumption D1 is updated. Also good. At this time, the current period average electricity consumption may be multiplied by a correction factor corresponding to the magnitude of the difference and taken in as a learning value. Alternatively, learning values read from a pre-stored table may be taken in depending on the magnitude of the difference. For example, in these correction factors and tables, the larger the deviation between the current period average electricity cost and the past daily average electricity cost D1 (the larger the extraordinary index a), the more the current period average electricity cost will be reflected in the updated past daily average. It is set to be larger than the electricity consumption D1.

Further, for example, when the extraordinary index a is equal to or greater than a preset threshold, the current period average electricity consumption and the past extraordinary electricity consumption D2 included in the past data D are compared. Only when these differences are above a certain level (that is, when the discrepancy between the current period average electricity cost and the past non-daily average electricity cost D2 is large), the current period average electricity cost is taken in as a learning value and the past non-daily average electricity cost D2 is updated. You can also do it. At this time, similarly, the current period average electricity consumption may be multiplied by a correction factor corresponding to the magnitude of the difference, and the result may be taken in as a learning value. Alternatively, learning values read from a pre-stored table may be taken in depending on the magnitude of the difference. For example, in these correction factors and tables, the larger the discrepancy between the current period average electricity cost and the past non-daily average electricity cost D2 (the larger the extraordinary index a), the more the past non-daily electricity cost will be reflected in the current period average electricity cost after the update. It is set to be larger than the daily average electricity consumption D2.

For example, the determination as to whether or not to update the past daily average electricity consumption D1 and the past daily average electricity consumption D1 can be made based on the ratio of the current period average electricity consumption and the past daily average electricity consumption D1 or the past daily average electricity consumption D1. For example, when the extraordinary index a is lower than a preset threshold value, the current period average electricity cost and the past daily average electricity cost D1 included in the past data D are compared. Only when these ratios are above a certain level (that is, when the discrepancy between the current period average electricity consumption and the past daily average electricity consumption D1 is large), the current period average electricity consumption is taken in as a learning value and the past daily average electricity consumption D1 is updated. Also good. At this time, the current period average electricity consumption may be multiplied by a correction factor corresponding to the magnitude of the ratio and taken in as a learning value. Alternatively, learning values read from a pre-stored table may be taken in depending on the magnitude of the ratio. For example, in these correction factors and tables, the larger the deviation between the current period average electricity cost and the past daily average electricity cost D1 (the larger the extraordinary index a), the more the current period average electricity cost will be reflected in the updated past daily average. It is set to be larger than the electricity consumption D1.

Further, for example, when the extraordinary index a is equal to or greater than a preset threshold, the current period average electricity consumption and the past extraordinary electricity consumption D2 included in the past data D are compared. Only when these ratios are above a certain level (that is, when there is a large discrepancy between the current period average electricity cost and the past non-daily average electricity cost D2), the current period average electricity cost is taken in as a learning value and the past non-daily average electricity cost D2 is updated. You can also do it. At this time, similarly, the current period average electricity consumption may be multiplied by a correction factor corresponding to the magnitude of the ratio and taken in as a learning value. Alternatively, learning values read from a pre-stored table may be taken in depending on the magnitude of the ratio. For example, in these correction factors and tables, the larger the discrepancy between the current period average electricity cost and the past non-daily average electricity cost D2 (the larger the extraordinary index a), the more the past non-daily electricity cost will be reflected in the current period average electricity cost after the update. It is set to be larger than the daily average electricity consumption D2.

Furthermore, the past data update unit 8 also updates the past learned value D3 of the past data D. Here, the past data update unit 8 updates the past learned value D3 whose month, day of the week, and time zone match the current period based on the travel data of the current period. In the present embodiment, the past data update unit 8 increases the degree of reflection of the travel data in the current period on the past learned value D3 after updating, as the extraordinary index a of the current period is smaller. Update.

In this embodiment, as described above, the vehicle speed, the current period of travel distance, and the current period of travel time are used as the travel data. Therefore, the past data update unit 8 updates the average vehicle speed so that the smaller the extraordinary index a of the current period, the greater the degree of reflection of the average vehicle speed of the current period on the past learned value D3 after updating the average value of the vehicle speed. The past learning value D3 of is updated. The past data update unit 8 also performs past learning of the mileage so that the smaller the extraordinary index a of the current period, the greater the degree of reflection of the mileage in the current period on the past learning value D3 after updating the mileage. Update value D3. In addition, the past data update unit 8 updates the past travel time so that the smaller the extraordinary index a of the current period, the greater the degree of reflection of the travel time after updating today's time in the current period on the past learned value D3. Update learning value D3.

In this way, the smaller the extraordinary index a in the current period, the greater the degree of reflection on the past learned value D3 after updating the travel data in the current period, and by updating the past learned value D3, the extraordinary index a It is possible to prevent large values (driving data during unusual driving) from being largely reflected in the past learned value D3.

Next, with reference to the flowchart of FIG. 3, the operation of the average electricity cost calculation device 1 of this embodiment will be described.

FIG. 3 is a flowchart showing the processing steps when calculating the average electricity cost for calculating the remaining travel distance by the average electricity cost calculation device 1 of this embodiment. As shown in this figure, first, the current period average electricity consumption is acquired (step S1). Here, the current period average electricity cost obtaining unit 3 obtains the current period average electricity cost which is the average of the electricity costs in the current period. The current period average electricity cost acquisition unit 3 calculates the electricity cost continuously or periodically in the current period multiple times based on the driving data inputted from the outside, and sets the average value of these electricity costs as the current period average electricity cost.

Subsequently, past average electricity consumption is acquired (step S2). Here, the past average electricity cost acquisition unit 4 acquires the past average electricity cost, which is the average of the electricity costs in the past period, based on the past data D. The past average electricity cost acquisition unit 4 obtains the data of the month, day of the week, and time period to which the current period belongs from outside or inside the average electricity cost calculation device 1, and obtains the past daily average according to the month, day of the week, and time period to which the current period belongs. Electricity cost D1 and past non-daily average electricity consumption D2 are acquired from past data D as past average electricity consumption.

Subsequently, an extraordinary index a is calculated (step S3). Here, the extraordinary index calculation unit 5 acquires the average vehicle speed for the current period, the travel distance for the current period, and the travel time for the current period from the travel data. Further, the extraordinary index calculation unit 5 obtains from the past data D a past learned value D3 of average vehicle speed, a past learned value D3 of travel distance, and a past learned value D3 of travel time. The extraordinary index calculation unit 5 calculates an extraordinary index a for each parameter indicating the driving state in the current period, and takes the average value of these extraordinary indices a as the final extraordinary index a.

The extraordinary index calculation unit 5 compares the average vehicle speed of the current period with the past learned value D3 of the average vehicle speed, and when the average vehicle speed of the current period exceeds the past learned value D3 of the average vehicle speed, the Bring the extraordinary index a closer to 1 from 0. Moreover, the extraordinary index calculation unit 5 approaches the extraordinary index a regarding the mileage from 0 to 1 when the mileage in the current period exceeds the past learning value D3 of the mileage. In addition, the extraordinary index calculation unit 5 compares the driving time in the current period with the past learned value D3 of the driving time, and when the driving time in the current period exceeds the past learned value D3 of the driving time, Bring the extraordinary index a closer to 1 from 0.

Subsequently, a weighting coefficient k is calculated (step S4). Here, the weighting coefficient calculation unit 6 calculates the weighting coefficient k based on the extraordinary index a. In this embodiment, the weighting coefficient calculation unit 6 calculates the weighting coefficient k by subtracting the extraordinary index a calculated by the extraordinary index calculation unit 5 from 1.

Subsequently, the average electricity cost for calculating the remaining travel distance (average electricity cost) is calculated (step S5). Here, the electricity cost calculation section 7 calculates the average electricity cost for calculating the remaining mileage by using the weighted average of the current period average electricity cost obtained by the current period average electricity cost acquisition section 3 and the past average electricity cost obtained by the past average electricity cost acquisition section 4. Calculate. The electricity cost calculation unit 7 calculates the average electricity cost for calculating the remaining travel distance by setting the degree of contribution between the current period average electricity cost and the past average electricity cost based on the weighting coefficient k.

In addition, when calculating the average electricity cost for calculating the remaining mileage, the current period average electricity cost is not equal to the past non-daily average electricity cost D2 until the current period's mileage exceeds the past learned mileage value D3 (mileage distance learning value). The past daily average electricity consumption D1 is used as the past average electricity consumption to calculate the average electricity consumption for calculating the remaining travel distance. On the other hand, after the mileage in the current period exceeds the past learning value D3 of mileage, the past daily average electricity consumption D1 is used as the past average electricity consumption, and the remaining mileage is based on the current period average electricity consumption and the past daily average electricity consumption D1. The average electric cost for distance calculation is calculated.

Subsequently, past data D is updated (step S5). Here, the past data update unit 8 updates the past data D based on the driving state in the current period. Specifically, the past daily average electricity cost D1 or the past non-daily average electricity cost D2 is updated using the current average electricity cost for the current period calculated based on the driving state. The past data update unit 8 also updates the past learned value D3 of the past data D. The past learned value D3 whose month, day of the week, and time zone match the current period is updated based on the travel data of the current period. In this embodiment, the smaller the extraordinary index a of the current period, the greater the degree of reflection of the updated driving data of the current period on the past learning value D3, and the past learning value D3 is updated. Note that the past data D may be updated only at the end of the current period.

The average electricity cost calculation device 1 of this embodiment as described above calculates the average electricity cost for calculating the remaining travel distance, and is used to obtain the current period average electricity cost which is the average of the electricity costs in the current period. a past average electricity cost acquisition part 4 that obtains a past average electricity cost that is an average of electricity costs in the past period based on past data D including past electricity costs; An extraordinary index calculation unit 5 that calculates an extraordinary index a indicating the degree of deviation from the state, a weighting coefficient calculation unit 6 that calculates a weighting coefficient k based on the extraordinary index a, and an average electricity consumption for the current period. It includes an electricity cost calculation unit 7 that calculates the average electricity cost by setting the degree of contribution to the past average electricity cost based on the weighting coefficient k.

According to the average electric cost calculation device 1 of the present embodiment, an extraordinary index a indicating the degree of deviation of the vehicle running state in the current period from the past vehicle running state is calculated. Further, according to the weighting coefficient k calculated based on the extraordinary index a, the degree of contribution of the current period average electricity cost and the past average electricity cost for calculating the average electricity cost for calculating the remaining travel distance is set. Therefore, according to the average electricity cost calculation device 1 of the present embodiment, when an unusual driving is performed, the current period average electricity cost is used as the average electricity cost for calculating the remaining travel distance, regardless of the amount of remaining energy that can be used for driving. It becomes possible to reflect the Therefore, according to the average electricity cost calculation device 1 of the present embodiment, when a vehicle that can run on electric power runs in an unusual manner, regardless of the remaining amount of energy that can be used to drive the vehicle, It becomes possible to calculate the average electricity consumption for calculating the remaining travel distance, taking into account the amount of travel.

Furthermore, in the average electricity cost calculation device 1 of the present embodiment, the extraordinary index calculation unit 5 uses the average vehicle speed of the current period, the travel distance of the current period, and the travel time of the current period as parameters indicating the driving state of the current period. Then, calculate the extraordinary index a. The average vehicle speed during the current period, the travel distance during the current period, and the travel time during the current period are parameters that are likely to change when the driving condition becomes unusual. Therefore, by calculating the unusual index a using at least one of the average vehicle speed in the current period, the distance traveled in the current period, and the driving time in the current period, it is possible to more accurately know that the driving is unusual. becomes possible. Note that among these three parameters, the average vehicle speed is more likely to change when the driving condition becomes unusual. Therefore, by calculating the unusual index a using the average vehicle speed during the current period, it becomes possible to more accurately know that the vehicle is traveling in an unusual manner.

Furthermore, in the average electricity cost calculation device 1 of the present embodiment, in the past data D, the past electricity costs are associated with at least one of the month, the day of the week, and the time period, and the extraordinary index calculation unit 5 An extraordinary index a is calculated based on past data D tailored to the month, day of the week, and time zone. For this reason, the unusual index a is calculated by comparing the current period's driving situation with past electricity costs that are close to each other, and the judgment of unusualness becomes more accurate.

In addition, in the average electricity cost calculation device 1 of the present embodiment, the past data D includes a past learning value D3 of mileage set based on past mileage, and electricity consumption during a period in which the extraordinary index a is smaller than the threshold value. It includes past daily average electricity consumption D1 which is the average value of , and past non-daily average electricity consumption D2 which is the average value of electricity consumption during the period in which the extraordinary index a is larger than the threshold value. In addition, until the mileage in the current period exceeds the past learned value of mileage D3, the electricity cost calculation unit 7 replaces the current period average electricity cost with the past non-daily average electricity cost D2, and uses the past daily average electricity cost D1 as the past average electricity cost. After the current period's mileage exceeds the mileage learning value, the past daily average electricity cost D1 is used as the past average electricity cost to calculate the remaining electricity cost based on the current period average electricity cost and the past average electricity cost. Calculate the average electricity cost for calculating mileage.

According to the average electricity cost calculation device 1 of this embodiment, even in daily driving, the average electricity consumption for calculating the remaining traveling distance is calculated except for the driving condition immediately after the driving, which has a large change compared to the past driving condition. It can be calculated. Therefore, it becomes possible to calculate the average electricity consumption for calculating the remaining travel distance during a more stable period.

Furthermore, the average electricity cost calculation device 1 of this embodiment includes a past data updating unit 8 that updates past data D based on the driving state in the current period. Therefore, it is possible to determine whether the vehicle is running on a daily basis or on an unusual basis based on recent driving trends.

In addition, in the average electricity cost calculation device 1 of the present embodiment, the past data D includes a past learning value D3 set based on past driving conditions, and the past data updating unit 8 stores an extraordinary index for the current period. The smaller a is, the greater the degree of reflection of the current period's driving state on the past learned value D3, and the past learned value D3 is updated. Therefore, according to the average electric cost calculation device 1 of the present embodiment, it is possible to prevent driving data during unusual driving from being largely reflected in the past learned value D3.

(Second embodiment)
Next, a second embodiment of the present invention will be described with reference to FIG. 4. In the description of this embodiment, the description of the same parts as in the first embodiment will be omitted or simplified.

FIG. 4 is a flowchart showing the process performed in the step of acquiring the past average electricity cost (step S2 in FIG. 3) of the average electricity cost calculation device of this embodiment. As shown in this figure, in the present embodiment, when acquiring the past average electricity consumption, it is first determined whether the mileage of the vehicle has exceeded a predetermined distance since shipment from the factory (step S21). ).

If the distance traveled by the vehicle exceeds a predetermined distance since shipment from the factory, the date and time information (month, day of the week, time zone) of the current period is acquired, as in the first embodiment (step S22). , the past average electricity consumption is acquired from the past data D based on the date and time information (step S23).

On the other hand, if the mileage of the vehicle has not exceeded the predetermined distance since shipment from the factory, the initial past average electricity cost stored in advance is used as the past average electricity cost (step S24). The initial past average electricity consumption is electricity consumption that is stored in advance for the vehicle before shipment from the factory. By storing such an initial past average electricity cost in advance, even if the accumulation of past data D is insufficient, it becomes possible to obtain the average electricity cost for calculating the remaining travel distance.

According to the average electricity cost calculation device of the present embodiment as described above, similarly to the average electricity cost calculation device 1 of the first embodiment, when an unusual drive is performed, the amount of remaining energy that can be used for driving is calculated. Regardless of the current period, it is possible to reflect the average electricity cost for the current period in the average electricity cost for calculating the remaining travel distance.

In addition, according to the average electricity cost calculation device of this embodiment, the initial past average electricity cost is stored in advance when the vehicle is shipped from the factory, and the extraordinary index a can be calculated using this initial past average electricity cost as the past average electricity cost. I can do it. Therefore, even in a state where past data D is not accumulated, it is possible to obtain the extraordinary index a, and further to obtain the weighting coefficient k and the average electricity cost for calculating the remaining travel distance.

(Third embodiment)
Next, a third embodiment of the present invention will be described with reference to FIG. Note that in the description of this embodiment as well, the description of the same parts as in the first embodiment will be omitted or simplified.

FIG. 5 is a block diagram showing a schematic configuration of the remaining mileage calculation device 10 of this embodiment. As shown in this figure, the remaining mileage calculation device 10 of this embodiment includes the average electric cost calculation device 1 of the first embodiment and a distance calculation section 20.

The distance calculation unit 20 calculates the remaining travel distance based on the average electricity cost for calculating the remaining travel distance that is input from the average electricity cost calculation device 1 . For example, the distance calculation unit 20 receives the remaining battery amount that can be used for driving, and calculates the remaining traveling distance by dividing this remaining battery amount by the average electricity consumption for calculating the remaining traveling distance. Such a distance calculation unit 20 is installed in a vehicle, for example, as part of the functions of a computer device installed in the vehicle.

Note that when the vehicle is a hybrid vehicle that has a running battery and an internal combustion engine, the distance calculation unit 20 calculates the amount of fuel that can be used for driving in addition to the distance that can be traveled with the remaining amount of battery that can be used for driving. Calculate the remaining distance by adding the distance that can be traveled.

The remaining mileage calculation device 10 of this embodiment includes the average electricity consumption calculation device 1. The average electricity cost calculation device 1 is capable of calculating the average electricity cost for calculating the remaining travel distance, taking into account unusual driving, regardless of the remaining amount of energy that can be used for driving the vehicle. Therefore, according to the remaining mileage calculating device 10 of the present embodiment, it is possible to calculate the remaining mileage taking into account extraordinary driving, regardless of the remaining amount of energy that can be used for driving the vehicle.

Although preferred embodiments of the present invention have been described above with reference to the accompanying drawings, it goes without saying that the present invention is not limited to the above embodiments. The various shapes and combinations of the constituent members shown in the embodiments described above are merely examples, and can be variously changed based on design requirements and the like without departing from the spirit of the present invention.

For example, in the above embodiment, a configuration has been described in which vehicle speed, travel distance in the current period, and travel time in the current period are used as the travel data. However, the present invention is not limited thereto. As described above, the driving data is not particularly limited as long as it indicates the driving state of the vehicle, and for example, the number of times the ignition is turned on and off or the frequency of stopping of the vehicle can be used as the driving data. In such a case, a past learned value D3 is also obtained for the number of times the ignition is turned on and off and the frequency of stopping of the vehicle, and an extraordinary index a is calculated for each by comparison with this past learned value D3.

Further, in the above embodiment, a configuration has been described in which the past daily average electricity cost D1 and the past non-daily average electricity cost D2 are used as the past average electricity cost. However, the present invention is not limited thereto. For example, it is also possible to adopt a configuration in which the past average electricity cost is not divided into the past daily average electricity cost D1 and the past non-daily average electricity cost D2.

Furthermore, in the above embodiment, a configuration has been described in which the extraordinary index a increases quadratically after each parameter indicating the driving state exceeds the past learned value D3. However, the present invention is not limited thereto. For example, it is also possible to adopt a configuration in which the extraordinary index a increases before each parameter indicating the driving state exceeds the past learned value D3. It is also possible to adopt a configuration in which the extraordinary index a increases linearly.

1... Average electricity cost calculation device, 2... Past data storage unit, 3... Current period average electricity cost acquisition unit, 4... Past average electricity cost acquisition unit, 5... Extraordinary index calculation unit, 6... Weighting coefficient Calculation unit, 7...Electricity cost calculation unit, 8...Past data update unit, 10...Remaining mileage calculation device, 20...Distance calculation unit, a...Extraordinary index, D...Past data, D1... Past daily average electricity consumption, D2...Past non-daily average electricity consumption, D3...Past learning value (past driving state learning value), k...Weighting coefficient

Claims (6)

An average electricity cost calculation device that calculates an average electricity cost,
a current period average electricity cost acquisition unit that obtains the current period average electricity cost which is the average of the current period electricity costs;
a past average electricity cost acquisition unit that obtains a past average electricity cost that is the average of electricity costs in the past period based on past data including past electricity costs;
an extraordinary index calculation unit that calculates an extraordinary index indicating the degree of deviation of the vehicle running state in the current period from the past vehicle running state;
a weighting coefficient calculation unit that calculates a weighting coefficient based on the extraordinary index;
An average electricity cost calculation device comprising: an electricity cost calculation unit that calculates the average electricity cost by setting a degree of contribution between the current period average electricity cost and the past average electricity cost based on the weighting coefficient. The extraordinary index calculation unit calculates the extraordinary index using at least one of an average vehicle speed in the current period, a travel distance in the current period, and a travel time in the current period as parameters indicating the driving state in the current period. The average electricity consumption calculation device according to claim 1. In the past data, the past electricity cost is associated with at least one of a month, a day of the week, and a time period,
The average electricity cost calculation device according to claim 1 or 2, wherein the extraordinary index calculation unit calculates the extraordinary index based on the past data matched to the month, day of the week, and time zone of the current period. The past data includes a mileage learning value set based on past mileage, a past daily average electricity cost which is an average value of electricity costs during a period in which the extraordinary index is smaller than a threshold, and a distance learning value set based on the past mileage. Includes the past non-daily average electricity cost, which is the average value of electricity costs for a period greater than the threshold,
The electricity cost calculation section is
Until the mileage in the current period exceeds the mileage distance learning value, the average electricity cost is calculated by replacing the current period average electricity cost with the past non-daily average electricity cost and using the past daily average electricity cost as the past average electricity cost. ,
After the mileage in the current period exceeds the learned mileage value, the past daily average electricity cost is used as the past average electricity cost, and the average electricity cost is calculated based on the current period average electricity cost and the past average electricity cost. The average electricity consumption calculation device according to any one of claims 1 to 3, characterized in that: The average electricity cost calculation device according to any one of claims 1 to 4, further comprising a past data update unit that updates the past data based on the driving state in the current period. The past data includes a past driving state learning value set based on a past driving state,
The past data updating unit updates the past driving state learned value by increasing the degree of reflection of the current period's driving state on the past driving state learning value as the extraordinary index of the current period is smaller. The average electricity cost calculation device according to claim 5.

Images