JP2021174203A - Vehicle computing device - Google Patents

Abstract

To provide a vehicle computing device capable of ensuring redundancy in calculation of a cruising range.SOLUTION: A prediction ECU 31 of a vehicle 10 includes: a route information acquisition unit 311 that acquires information on a route traveled by the vehicle 10; a remaining energy level acquisition unit 312 that acquires information on the remaining energy level of a battery 22; a parameter acquisition unit 310 that acquires predetermined parameters necessary for calculating a cruising range; and a calculation unit 313 that calculates the cruising range of the vehicle based on such information. The parameter acquisition unit 310 acquires the predetermined parameters by second acquisition means different from first acquisition means when the predetermined parameters cannot be acquired by the first acquisition means.SELECTED DRAWING: Figure 1

Description

The present disclosure relates to an arithmetic unit that calculates the cruising range of a vehicle.

Conventionally, there is a vehicle arithmetic unit described in Patent Document 1 below. This arithmetic unit calculates the energy consumption per unit time in a predetermined section in which the vehicle travels based on the vehicle information and the road information. Further, the calculation unit estimates the energy consumption of the vehicle in the predetermined section based on the calculated energy consumption per unit time and the traveling time required when the vehicle has moved in the predetermined section in the past. In addition, this arithmetic unit calculates the cruising distance of the vehicle from the amount of residual energy acquired from the vehicle and the estimated value of the energy consumption of the vehicle in a predetermined section.

International Publication No. 2012/0354847

By the way, when calculating the cruising range like the arithmetic unit described in Patent Document 1, information such as vehicle information, road information, and past travel history of the vehicle is required. In this regard, for example, when a vehicle uses a communication device to acquire road information from a server device or the like, if the communication device fails, the calculation unit of the vehicle may not be able to acquire the road information. In such a case, the arithmetic unit cannot calculate the cruising range. As described above, in the arithmetic unit described in Patent Document 1, if any one of the vehicle information, the road information, and the past travel history of the vehicle is lost for some reason, the cruising range cannot be calculated. there is a possibility.

The present disclosure has been made in view of such circumstances, and an object of the present invention is to provide a vehicle arithmetic unit capable of ensuring redundancy in the calculation of a cruising range.

The vehicle calculation device that solves the above problems is a calculation device (31) that calculates the cruising distance of the vehicle, and includes a route information acquisition unit (311) that acquires information on the vehicle's travel route and a vehicle's travel. A predetermined energy remaining amount acquisition unit (312) for acquiring information on the remaining amount of energy that can be used, and a predetermined value required for calculating the cruising distance separately from the information on the traveling route and the information on the remaining amount of energy. It is provided with a parameter acquisition unit (310) for acquiring the parameters of the above, an information on a traveling route, information on the remaining amount of energy, and a calculation unit (313) for calculating the cruising distance of the vehicle based on a predetermined parameter. When the parameter acquisition unit cannot acquire the predetermined parameter by the first acquisition means, the parameter acquisition unit acquires the predetermined parameter by a second acquisition means different from the first acquisition means.

According to this configuration, even if a predetermined parameter cannot be acquired by the first acquisition means, the predetermined parameter can be acquired by the second acquisition means, so that redundancy can be ensured in the calculation of the cruising range. ..
The reference numerals in parentheses described in the above means and claims are examples showing the correspondence with the specific means described in the embodiments described later.

According to the vehicle arithmetic unit of the present disclosure, redundancy can be ensured in the calculation of the cruising range.

FIG. 1 is a block diagram showing a schematic configuration of a vehicle according to an embodiment. FIG. 2 is a flowchart showing a procedure of processing executed by the prediction ECU of the embodiment. FIG. 3 is a flowchart showing a procedure of vehicle parameter acquisition processing executed by the prediction ECU of the embodiment. FIG. 4 is a flowchart showing a procedure of the environment parameter acquisition process executed by the prediction ECU of the embodiment. FIG. 5 is a map showing the relationship between the outside air temperature, the air conditioning power, and the weather, which is used by the prediction ECU of the embodiment. FIG. 6 is a flowchart showing a procedure of map information acquisition processing used by the prediction ECU of the embodiment. FIG. 7 is a graph showing a method of setting a vehicle speed profile by the prediction ECU of the embodiment. FIG. 8 is a graph showing a method of calculating the limit arrival point and the cruising range by the prediction ECU of the embodiment. FIG. 9 is a diagram schematically showing map information displayed on the HMI device of the embodiment.

Hereinafter, an embodiment of the arithmetic unit of the vehicle will be described with reference to the drawings. In order to facilitate understanding of the description, the same components are designated by the same reference numerals as much as possible in each drawing, and duplicate description is omitted.
First, a schematic configuration of a vehicle on which the arithmetic unit of the present embodiment is mounted will be described. As shown in FIG. 1, the vehicle 10 of the present embodiment includes a motor generator 20, an inverter device 21, a battery 22, and a clutch 23. The vehicle 10 of the present embodiment is a so-called electric vehicle that uses a motor generator 20 as a power source for traveling.

The battery 22 is composed of a secondary battery such as a lithium ion battery that can be charged and discharged. The inverter device 21 converts the DC power charged in the battery 22 into AC power, and supplies the converted AC power to the motor generator 20. The motor generator 20 is driven based on the AC power supplied from the inverter device 21 to rotate the first power transmission shaft 24. The first power transmission shaft 24 is connected to the second power transmission shaft 25 via a clutch 23. The clutch 23 can be switched between a connected state in which the first power transmission shaft 24 and the second power transmission shaft 25 are connected and a non-connected state in which the connection between the first power transmission shaft 24 and the second power transmission shaft 25 is released. When the clutch 23 is in the engaged state, power can be transmitted between the first power transmission shaft 24 and the second power transmission shaft 25. At this time, for example, the power transmitted from the motor generator 20 to the first power transmission shaft 24 is transmitted to the wheels 28 via the second power transmission shaft 25, the differential gear 26, and the drive shaft 27, so that the wheels 28 rotate. Then, the vehicle 10 runs. When the clutch 23 is in the unconnected state, the power transmission between the first power transmission shaft 24 and the second power transmission shaft 25 is cut off.

The motor generator 20 regenerates power when the vehicle 10 is braked. Specifically, the braking force acting on the wheels 28 when the vehicle 10 is braked is applied to the motor generator 20 via the drive shaft 27, the differential gear 26, the second power transmission shaft 25, the clutch 23, and the first power transmission shaft 24. Is entered in. The motor generator 20 generates electricity based on the power input back from the wheels 28. The electric power generated by the motor generator 20 is converted from AC electric power to DC electric power by the inverter device 21 and charged into the battery 22.

The vehicle 10 includes an EV (Electric Vehicle) ECU (Electronic Control Unit) 30, a prediction ECU 31, and an HMI (Human Machine Interface) ECU 32. Each of the ECUs 30 to 32 is mainly composed of a microcomputer having a CPU, a ROM, a RAM, and the like, and executes various controls by executing a program stored in the ROM in advance.

The EVECU 30 is a part that controls the motor generator 20. The output signal of the vehicle-mounted sensor 40 is input to the EVE C30. The in-vehicle sensor 40 is a general term for various sensors mounted on the vehicle 10 in order to detect various state quantities of the vehicle 10. The in-vehicle sensor 40 includes, for example, a vehicle speed sensor that detects the traveling speed of the vehicle 10, an acceleration sensor that detects the acceleration of the vehicle 10, an accelerator position sensor that detects the depression position of the accelerator pedal, and the like. The EVECU 30 calculates a torque command value, which is a target value of torque to be output from the motor generator 20, based on a vehicle state quantity such as a vehicle speed and an accelerator pedal depression amount detected by an in-vehicle sensor 40, and is calculated. Based on the torque command value, the control value of the energization amount to be supplied from the battery 22 to the motor generator 20 is calculated. The EVECU 30 controls the inverter device 21 based on the calculated energization control value. As a result, the electric power corresponding to the energization control value is supplied from the battery 22 to the motor generator 20, and the torque corresponding to the torque command value is output from the motor generator 20. Further, the EVACU 30 controls the inverter device 21 so that the electric power generated by the regenerative operation of the motor generator 20 is charged to the battery 22 when the vehicle 10 is decelerated.

The EVECU 30 can acquire information on its SOC (State Of Charge) value from the battery 22. The SOC value defines the fully discharged state of the battery 22 as "0 [%]", defines the fully charged state of the battery 22 as "100 [%]", and then defines the charged state of the battery 22 as "0 [%]". It is expressed in the range of "[%]" to "100 [%]". The EVECU 30 transmits information on the SOC value of the battery 22 to the prediction ECU 31 in response to a request from the prediction ECU 31. Further, the EV ECU 30 also transmits information on the energy efficiency η_d of the drive system, the driving force of the motor generator 20, and the efficiency of the motor generator 20 to the prediction ECU 31 in response to the request from the prediction ECU 31. The energy efficiency η_d of the drive system indicates the energy transmission efficiency when the energy of the battery 22 is transmitted to the wheels 28 via the power transmission system such as the inverter device 21, the motor generator 20, and the power transmission shafts 24 and 25. It is a thing. The information regarding the efficiency of the motor generator 20 may be a constant value, or may be expressed by a map in which the rotational speed and torque of the motor generator 20 are variables. Further, the information regarding the efficiency of the battery 22 may be a constant value or may be the internal resistance of the battery 22.

The prediction ECU 31 is a part that calculates the cruising range of the vehicle 10. The prediction ECU 31 has a parameter acquisition unit 310, a route information acquisition unit 311, an energy remaining amount acquisition unit 312, and a calculation unit 313. In this embodiment, the prediction ECU 31 corresponds to the arithmetic unit.
The parameter acquisition unit 310 acquires various vehicle state quantities of the vehicle 10 such as running speed and acceleration based on the output signal of the vehicle-mounted sensor 40.

Further, the parameter acquisition unit 310 can perform wireless communication with another vehicle 60 traveling around the vehicle 10, the traffic management system 61, and the server device 62 via the communication unit 41 of the vehicle 10. The parameter acquisition unit 310 acquires various information from the other vehicle 60, the traffic management system 61, the server device 62, etc. via the communication unit 41. The information that can be acquired from the other vehicle 60 includes information such as the traveling speed of the other vehicle 60 and the driving force of the power source. The information that can be acquired from the traffic management system 61 includes traffic congestion information and the like around the vehicle 10. The information that can be acquired from the server device 62 includes the average vehicle speed of other vehicles traveling at the predetermined point, the weather information at the predetermined point, and the like.

Further, the server device 62 stores information on the past traveling history of various vehicles measured in each vehicle as a database by communicating with a plurality of vehicles. The information on the past running history of the plurality of vehicles stored in the database in the server device 62 includes the running resistance of the vehicle, the driving force, the running speed of the vehicle, and the like at the point where the vehicle is running. .. The parameter acquisition unit 310 can acquire information on the past travel history of the plurality of vehicles stored in the database from the server device 62 via the communication unit 41.

Further, the parameter acquisition unit 310 can also read various information stored in the storage device 42 of the vehicle 10. The storage device 42 stores information such as the weight of the vehicle 10 and the fixed values of the running resistance.
Further, the parameter acquisition unit 310 acquires information on the energy efficiency η_d of the drive system, the energy efficiency of the battery 22, and the driving force of the motor generator 20 from the EV ECU 30. Further, the parameter acquisition unit 310 also acquires various information from other ECUs mounted on the vehicle 10. The parameter acquisition unit 310 can also acquire information such as the air conditioning power which is the output of the air conditioner and the energy efficiency η_a of the air conditioner from the air conditioner ECU which controls the air conditioner, for example.

The route information acquisition unit 311 can also acquire the map information stored in the storage device 42. The map information that can be acquired from the storage device 42 includes information such as the slope and curvature of the road. The map information stored in the storage device 42 includes information on the three-dimensional road shape, the speed limit on the route, the road congestion status that can be acquired by VICS (Vehicle Information and Communication System: registered trademark), and the like. include.

The energy remaining amount acquisition unit 312 acquires the current SOC value of the battery 22 from the EV ECU 30. In the present embodiment, the current SOC value of the battery 22 corresponds to the information on the remaining amount of energy that can be used for traveling the vehicle 10.
The calculation unit 313 creates a vehicle speed profile, which is a transition of the future traveling speed of the vehicle 10, based on the information that can be acquired by the parameter acquisition unit 310 and the information that can be acquired by the route information acquisition unit 311. In addition, the calculation unit 313 creates a power consumption profile, which is a transition of the power consumption of the battery 22, from the vehicle speed profile. Then, the calculation unit 313 determines the vehicle until the SOC value of the battery 22 drops to a predetermined value based on the current SOC value of the battery 22 acquired by the energy remaining amount acquisition unit 312 and the power consumption profile of the battery 22. Calculate the cruising range D that 10 can travel. The calculation unit 313 calculates a point that can be reached by the cruising distance D from the point where the vehicle 10 is currently located, and transmits the calculated information on the reachable point to the HMI ECU 32.

The HMI ECU 32 notifies the occupants of the vehicle 10 of the reachable points transmitted from the prediction ECU 31 by using the HMI device 50. The HMI device 50 of the present embodiment is a display device capable of displaying map information and the like. The HMI ECU 32 converts the information on the reachable point transmitted from the prediction ECU 31 into image information and the like that can be displayed on the HMI device 50, and displays the converted image information on the reachable point on the HMI device 50. As a result, the occupant of the vehicle 10 can grasp the area where the vehicle 10 can travel by confirming the reachable point displayed on the HMI device 50.

Next, the processing procedure of the calculation and display of the cruising range executed by the prediction ECU 31 and the HMI ECU 32 will be specifically described.
The route information acquisition unit 311 first extracts one or a plurality of predicted routes on which the vehicle 10 may travel in the future. For example, when a destination is set in the navigation device of the vehicle 10, the route information acquisition unit 311 sets a travel route from the current location of the vehicle 10 to the destination as a predicted route on which the vehicle 10 may travel. In addition to using it, one or more of the traveling routes are extracted. Alternatively, when the route information acquisition unit 311 learns the travel route of the vehicle 10, the route information acquisition unit 311 uses the learned travel route as a route on which the vehicle 10 may travel. , One or more predicted travel routes may be extracted. In the present embodiment, the predicted travel route of the vehicle 10 extracted by the route information acquisition unit 311 in this way corresponds to the information regarding the travel route of the vehicle 10.

The prediction ECU 31 extracts the single or a plurality of predicted routes on which the vehicle 10 may travel by the route information acquisition unit 311 as described above, and then each of the extracted single predicted routes or the plurality of predicted routes. The process shown in FIG. 2 is executed.
As shown in FIG. 2, the parameter acquisition unit 310 first executes a vehicle parameter acquisition process as the process of step S10. The specific procedure of this process is as shown in FIG.

When the parameter acquisition unit 310 starts the vehicle parameter acquisition process shown in FIG. 3, first, as the process of step S100, information on the weight and running resistance of the vehicle 10 that can be used for calculating the cruising distance D exists. Judge whether or not. For example, when the owner of the vehicle 10 can input the unique information of the vehicle 10 such as the vehicle weight and the running resistance by operating the operation panel, the input information is stored in the storage device 42. In this case, the parameter acquisition unit 310 makes a positive determination in the process of step S100 based on the fact that the vehicle weight input value ma and the running resistance input value Fra are stored in the storage device 42. When the parameter acquisition unit 310 makes a positive judgment in the process of step S100, the parameter acquisition unit 310 sets the vehicle weight input value ma and the running resistance input value Fra stored in the storage device 42 as the process of the subsequent step S101. After substituting into the value m and the running resistance set value Fr, respectively, the process shown in FIG. 3 is terminated.

When the input information of the vehicle weight and the running resistance is not stored in the storage device 42, the parameter acquisition unit 310 makes a negative determination in the process of step S100. In this case, the parameter acquisition unit 310 determines whether or not it is possible to estimate the vehicle weight and the running resistance as the process of step S102. The parameter acquisition unit 310 estimates the vehicle weight and the traveling resistance from the traveling speed of the vehicle 10 and the driving force of the motor generator 20 based on, for example, a model using a Kalman filter. The model using the Kalman filter may be created in advance by an experiment or the like, or may be created by the parameter acquisition unit 310 by learning or the like. The parameter acquisition unit 310 calculates the error variance values when calculating the respective estimated values of the vehicle weight and the running resistance using the Kalman filter. The parameter acquisition unit 310 determines that the vehicle weight and the running resistance can be estimated when the error variance values of the estimated value of the vehicle weight and the estimated value of the running resistance are less than a predetermined threshold value. A positive decision is made in the process of step S102. In this case, the parameter acquisition unit 310 substitutes the vehicle weight estimated value mb and the running resistance estimated value Frb calculated from the model using the Kalman filter into the vehicle weight set value m and the running resistance estimated value Frb, respectively, as the process of step S103. After that, the process shown in FIG. 3 is terminated.

The parameter acquisition unit 310 determines that it is difficult to estimate the vehicle weight and the running resistance when the error variance values of the estimated value of the vehicle weight and the estimated value of the running resistance are equal to or more than a predetermined threshold value. A negative determination is made in the process of step S101. In this case, the parameter acquisition unit 310 substitutes the vehicle weight fixed value mc stored in the storage device 42 into the vehicle weight set value m as the process of step S104. The vehicle weight fixed value mc is a value stored in advance in the storage device 42 as a value of the weight of the vehicle 10.

Whether or not the parameter acquisition unit 310 can acquire the travel resistance information of the vehicle 10 from the information on the past travel history of the other vehicle stored in the database in the server device 62 as the process of the step S105 following the step S104. To judge.
The server device 62 acquires information on the past travel history from various vehicles, and stores information on the travel history of each of the plurality of vehicles in a database. The server device 62 stores, for example, information on the running resistance of each of the plurality of vehicles in a database. The running resistance information is stored in the server device 62 as, for example, frequency distribution information. The server device 62 of the present embodiment determines the running resistance of the vehicle by statistically processing the stored information on the frequency distribution of the running resistance. The statistical process may be, for example, a process of obtaining an average value in the frequency distribution of running resistance, or a process of determining which of the values of the frequency distribution of running resistance is used based on meteorological information. It may be a process to be performed. The process using the meteorological information is, for example, a process using a value larger than the average value among the values of the frequency distribution in the case of rainy weather.

When the parameter acquisition unit 310 stores the statistical information of the running resistance of the vehicle in the server device 62 in this way, the parameter acquisition unit 310 can acquire the statistical information of the running resistance of the vehicle from the server device 62. The judgment is made, and a positive judgment is made in the process of step S105. In this case, as the process of step S106, after acquiring the statistical information of the traveling resistance of the vehicle 10 from the database of the server device 62 and substituting the acquired traveling resistance statistical value Frc into the traveling resistance set value Fr, FIG. Ends the process shown in.

On the other hand, if the information on the running resistance is not sufficiently stored in the database in the server device 62, or if the information on the running resistance is not stored in the database in the server device 62 in the first place, the parameter acquisition unit 310 is the server device 62 to the vehicle 10. Information on running resistance cannot be obtained. In this case, the parameter acquisition unit 310 makes a negative judgment in the process of step S105, and substitutes the travel resistance fixed value Frd stored in the storage device 42 into the travel resistance set value Fr as the subsequent process of step S107. After that, the process shown in FIG. 3 is terminated. The traveling resistance fixed value Frd is a value stored in advance in the storage device 42 as the traveling resistance value of the vehicle 10.

Among the values used for the vehicle weight set value m, the vehicle weight input value ma has the highest accuracy, and it is considered that the accuracy decreases in the order of the vehicle weight estimated value mb and the vehicle weight fixed value mc. Therefore, in the process shown in FIG. 3, the priority order used for the vehicle weight set value m is lower in the order of the vehicle weight input value ma, the vehicle weight estimated value mb, and the vehicle weight fixed value mc. Similarly, in the process shown in FIG. 3, the priority order used for the running resistance set value Fr becomes lower in the order of the running resistance input value Fra, the running resistance estimated value Frb, the running resistance statistical value Frc, and the running resistance fixed value Frd. ing.

After completing the process shown in FIG. 3, the parameter acquisition unit 310 executes the environment parameter acquisition process as the process of step S11 following step S10, as shown in FIG. The specific procedure of this process is as shown in FIG.
When the parameter acquisition unit 310 starts the environment parameter acquisition process shown in FIG. 4, it first determines whether or not the weather information on the predicted traveling route of the vehicle 10 can be acquired from the server device 62 as the process of step S110. do. The weather information acquired from the server device 62 includes information such as wind speed, weather, and outside air temperature at each point on the predicted traveling route of the vehicle 10. When the parameter acquisition unit 310 can acquire the weather information on the predicted traveling route of the vehicle 10 from the server device 62, the parameter acquisition unit 310 makes a positive determination in the process of step S110. In this case, the parameter acquisition unit 310 creates the wind power map M_Fw based on the information of the wind speed at each point on the predicted traveling route of the vehicle 10 as the process of step S111. Specifically, the parameter acquisition unit 310 calculates the wind power Fw, which is the force that the vehicle 10 is affected by the wind at each point, based on the information of the wind speed at each point acquired from the server device 62. A wind map M_Fw is created by calculating using. Calculation formulas and maps for calculating wind power Fw from wind speed have been obtained in advance by experiments and the like. The wind power map M_Fw is a map of the relationship between each point on the predicted traveling route and the wind power Fw received by the vehicle 10 at each point.

The parameter acquisition unit 310 creates an air conditioning power map M_Pa based on the information of the weather and the outside air temperature at each point on the predicted traveling route of the vehicle 10 as the process of step S112 following step S111. Specifically, the parameter acquisition unit 310 calculates the air conditioning power Pa, which is the output of the air conditioner of the vehicle 10 at each point, based on the weather and outside air temperature information of each point acquired from the server device 62. This operation is performed using, for example, the map shown in FIG.

The map shown in FIG. 5 shows the relationship between the outside air temperature Tout and the air conditioning power Pa for each of the cases where the weather is “clear”, the weather is “cloudy”, and the weather is “rainy”. Is stored in advance in the ROM of the prediction ECU 31. In FIG. 5, the map corresponding to the fine weather is shown by the solid line, the map corresponding to the cloudy weather is shown by the alternate long and short dash line, and the map corresponding to the rainy weather is indicated by the alternate long and short dash line.

As shown in FIG. 5, when the outside air temperature Tout is high, the air conditioner is driven for cooling the vehicle interior, so that the air conditioning power Pa is required. The higher the outside air temperature Tout, the larger the air conditioning power Pa for cooling. Further, when the outside air temperature Tout is low, the air conditioner is driven to heat the interior of the vehicle, so that the air conditioning power Pa is required. The lower the outside air temperature Tout, the larger the air conditioning power Pa for heating.

On the other hand, when the air conditioner is in cooling operation in fine weather, the air conditioning power Pa for cooling becomes larger due to the influence of solar radiation in fine weather. Further, when the air conditioner is operating for heating in fine weather, the same comfort can be realized even with a smaller air conditioning power Pa due to the influence of solar radiation in fine weather. In this way, the air conditioning power Pa changes according to the weather conditions.

The map shown in FIG. 5 is created in advance by obtaining the air conditioning power Pa according to the outside air temperature Tout and the weather condition as described above by an experiment or the like.
In the process of step S112 shown in FIG. 4, the parameter acquisition unit 310 creates a map corresponding to “sunny weather”, “cloudy weather”, based on the weather information at a predetermined point acquired from the server device 62. Select either the corresponding map or the map corresponding to "rainy weather", and calculate the air conditioning power Pa from the information on the outside air temperature at that point using the selected map. The parameter acquisition unit 310 creates the air conditioning power map M_Pa by performing the calculation of the air conditioning power Pa for each point on the predicted traveling route of the vehicle 10. The air-conditioning power map M_Pa is a map of the relationship between each point on the predicted traveling route and the air-conditioning power Pa of the vehicle 10 at each point. After executing the process of step S112, the parameter acquisition unit 310 ends the process shown in FIG.

As shown in FIG. 4, when the parameter acquisition unit 310 determines that the weather information on the predicted traveling route of the vehicle 10 cannot be acquired from the server device 62, the parameter acquisition unit 310 makes a negative determination in the process of step S110. In this case, the parameter acquisition unit 310 creates a wind power map M_Fw using the wind power Fw received by the vehicle 10 at the current location as the process of step S113.

Specifically, the driving force F of the vehicle 10 can be obtained by the following formula f1. In the formula f1, "m" indicates the vehicle weight, "v" indicates the traveling speed of the vehicle, "g" indicates the gravitational acceleration, "θ" indicates the road surface gradient, and "Fr" indicates the vehicle 10. "Fw" indicates the wind force received by the vehicle 10.

式ｆ１において、車両１０の現在の駆動力Ｆは、ＥＶＥＣＵ３０から取得可能なモータジェネレータ２０の現在の出力の情報から求めることができる。また、車両重量ｍ及び走行抵抗Ｆｒは、図３に示される処理で演算される値を用いることができる。さらに、車両の現在の走行速度ｖは、車載センサ４０の一つである車速センサの検出値を用いることができる。また、路面勾配θは、記憶装置４２に記憶されている地図情報から取得することができる。パラメータ取得部３１０は、これらの取得可能な値を用いることにより、上記の式ｆ１から、車両１０が受けている現在の風力Ｆｗを演算する。パラメータ取得部３１０は、このようにして演算した現在の風力Ｆｗを、車両１０の予測走行経路上の各地点の風力として用いることにより風力マップＭ＿Ｆｗを作成する。

In the formula f1, the current driving force F of the vehicle 10 can be obtained from the information of the current output of the motor generator 20 that can be obtained from the EV ECU 30. Further, as the vehicle weight m and the running resistance Fr, the values calculated by the process shown in FIG. 3 can be used. Further, as the current traveling speed v of the vehicle, the detection value of the vehicle speed sensor, which is one of the in-vehicle sensors 40, can be used. Further, the road surface gradient θ can be acquired from the map information stored in the storage device 42. The parameter acquisition unit 310 calculates the current wind force Fw received by the vehicle 10 from the above equation f1 by using these acquireable values. The parameter acquisition unit 310 creates a wind power map M_Fw by using the current wind power Fw calculated in this way as the wind power at each point on the predicted traveling route of the vehicle 10.

Further, the parameter acquisition unit 310 creates an air conditioning power map M_Pa based on the current air conditioning power Pa of the vehicle 10 as the process of step S114 following step S113. Specifically, the parameter acquisition unit 310 acquires information on the current air conditioning power from the air conditioning ECU. Then, the parameter acquisition unit 310 creates the air conditioning power map M_Pa by using the acquired current air conditioning power as the air conditioning power at each point on the predicted traveling route of the vehicle 10. After executing the process of step S114, the parameter acquisition unit 310 ends the process shown in FIG.

It is considered that the wind power map M_Fw created based on the wind speed information of each point acquired from the server device 62 is more accurate than the wind power map M_Fw created based on the wind power of the current location of the vehicle. Therefore, in the process shown in FIG. 4, the former is preferentially used. Similarly, in the process shown in FIG. 4, the air conditioning power map M_Pa created based on the weather and outside air temperature information of each point acquired from the server device 62 is created based on the air conditioning power Pa of the current location of the vehicle. It is used with priority over the air conditioning power map M_Pa.

After completing the process shown in FIG. 4, the parameter acquisition unit 310 executes the map information acquisition process as the process of step S12 following step S11 as shown in FIG. The specific procedure of this process is as shown in FIG.
When the parameter acquisition unit 310 starts the map information acquisition process shown in FIG. 6, it first determines whether or not there is map information that can be used offline as the process of step S120. When the map information is stored in the storage device 42, for example, the parameter acquisition unit 310 makes a positive determination in the process of step S120. In this case, the parameter acquisition unit 310 creates a gradient map M_θ and an upper limit vehicle speed map M_vmax based on the map information stored in the storage device 42 as the process of step S121. The gradient map M_θ is a map of the relationship between each point on the predicted traveling route and the road surface gradient θ at each point. The upper limit vehicle speed map M_vmax is a map of the relationship between each point on the predicted traveling route and the upper limit vehicle speed vmax at each point. As the upper limit vehicle speed vmax, for example, a legal speed is used. The parameter acquisition unit 310 creates the gradient map M_θ and the upper limit vehicle speed map M_vmax in the process of step S121, and then ends the process shown in FIG.

When the parameter acquisition unit 310 determines that there is no map information that can be used offline, it may make a negative determination in the process of step S120 and use it online as the subsequent process of step S122. Determine if there is possible map information. The parameter acquisition unit 310 can be used online when, for example, the server device 62 can communicate with the server device 62 via the communication unit 41 and the map information is stored in the server device 62. Is determined to exist, and a positive determination is made in the process of step S122. In this case, the parameter acquisition unit 310 acquires information on the road surface gradient and the upper limit vehicle speed of each point on the predicted traveling route from the server device 62 as the process of step S123, and then based on the information, the gradient map M_θ and the upper limit The vehicle speed map M_vmax is created, and the process shown in FIG. 6 is completed.

When the parameter acquisition unit 310 determines that there is no map information that can be used online, the parameter acquisition unit 310 makes a negative determination in the process of step S122. In this case, the parameter acquisition unit 310 determines, as the process of step S124, whether or not the information on the estimated values of the road surface gradient and the upper limit vehicle speed exists in the server device 62. For example, when the server device 62 stores information on the driving force of the power source of the other vehicle and information on the traveling speed at each point as information on the past traveling history of the plurality of other vehicles in a database. The server device 62 can calculate the estimated values of the road surface gradient and the upper limit vehicle speed.

Specifically, when the information on the traveling speed of other vehicles at each point stored in the server device 62 includes the information on the upper limit vehicle speed at each point, the prediction of the vehicle 10 is made from the information. It is possible to obtain an estimated value of the upper limit vehicle speed at each point on the traveling route. Further, when the information on the driving force and the traveling speed of the power source of the other vehicle at each point is stored in the database in the server device 62, the server device 62 uses the above formula f1 from the information to obtain the vehicle. It is possible to calculate an estimated value of the road surface gradient at each point on the 10 predicted traveling routes.

The server device 62 may calculate the road surface gradient and the upper limit vehicle speed by statistically processing the traveling speed of another vehicle and the like. The statistical process is, for example, a process of obtaining the average value of the past upper limit speeds of other vehicles.
Further, even if the server device 62 does not have the data of each point on the predicted traveling route of the vehicle 10, if the data of the peripheral points of the predicted traveling route exists in the server device 62, the data is used. Therefore, the estimated values of the road surface gradient and the upper limit vehicle speed can be calculated in the same manner.

When the parameter acquisition unit 310 stores the estimated values of the road surface gradient and the upper limit vehicle speed at each point in the server device 62, the parameter acquisition unit 310 makes a positive determination in the process of step S124. In this case, as the process of step S125, the parameter acquisition unit 310 acquires information on the estimated value of the road surface gradient and the estimated value of the upper limit vehicle speed at each point on the predicted traveling route from the server device 62, and then acquires the information from the server device 62. A gradient map M_θ and an upper limit vehicle speed map M_vmax are created based on the information obtained, and the process shown in FIG. 6 is completed.

When the estimated values of the road surface gradient and the upper limit vehicle speed at each point are not stored in the server device 62, the parameter acquisition unit 310 makes a negative determination in the process of step S124. In this case, the parameter acquisition unit 310 creates a gradient map M_θ and an upper limit vehicle speed map M_vmax based on the information stored in the storage device 42 of the own vehicle 10 as the process of step S126.

Specifically, the parameter acquisition unit 310 reads information on the past driving force and traveling speed of the own vehicle 10 at each point from the storage device 42. Then, the parameter acquisition unit 310 calculates an estimated value of the upper limit vehicle speed by statistically processing the past traveling speed of the own vehicle 10 at each point. The statistical process is, for example, a process of obtaining the average value of the past upper limit speeds of the vehicle 10. Further, the parameter acquisition unit 310 calculates the road surface gradient at each point by using the above equation f1 from the history of the past driving force of the motor generator 20 at each point, the history of the past running speed of the vehicle 10, and the like. A statistical process may also be used for the process of calculating the road surface gradient. The parameter acquisition unit 310 creates the gradient map M_θ and the upper limit vehicle speed map M_vmax based on the estimated value of the road surface gradient and the estimated value of the upper limit vehicle speed calculated in this way, and then ends the process shown in FIG.

If the vehicle 10 has never traveled on the predicted travel route this time, information on the past driving force and travel speed of the vehicle 10 at each point on the predicted travel route is stored in the storage device 42. It may not be. In such a case, the parameter acquisition unit 310 uses the information of the past driving force and the traveling speed of the vehicle 10 at the points around the predicted traveling route in the storage device 42 by using the information. The estimated value of the road surface gradient and the estimated value of the upper limit vehicle speed at each point on the predicted traveling route may be calculated. Further, when the parameter acquisition unit 310 does not store the information of the past driving force and the traveling speed of the vehicle 10 at the points around the predicted traveling route in the storage device 42, the road surface gradient of each point on the predicted traveling route A fixed value may be used as an estimated value of the above and an estimated value of the upper limit vehicle speed.

The parameter acquisition unit 310 ends the process shown in FIG. 6, that is, the parameter acquisition unit 310 ends the process of steps S10 to S12 shown in FIG. 2, so that the parameter acquisition unit 310 has a fixed vehicle weight value. Acquires mc, running resistance set value Fr, wind power map M_Fw, air conditioning power map M_Pa, gradient map M_θ, and upper limit vehicle speed map M_vmax. In the present embodiment, these parameters correspond to predetermined parameters required for calculating the cruising distance of the vehicle 10 separately from the information on the traveling route and the information on the remaining energy. After the parameter acquisition unit 310 acquires each parameter in this way, the calculation unit 313 executes the processes after step S13 shown in FIG. 2, so that the cruising range is calculated and displayed.

Specifically, the calculation unit 313 creates a vehicle speed profile v (x) indicating a transition of the future traveling speed of the vehicle 10 as the process of step S13. For example, the calculation unit 313 is based on the upper limit vehicle speed map M_vmax calculated through the process shown in FIG. 6 and the information on the stop location of the vehicle 10, and the final upper limit vehicle speed map as shown by the solid line in FIG. Create MF_vmax.

As shown in FIG. 7, the calculation unit 313 deforms the upper limit vehicle speed map M_vmax so as to be “0 [km / h]” at a predetermined stop point Ps, so that the final vehicle speed map M_vmax is as shown by a solid line. Create an upper limit vehicle speed map MF_vmax. When the position information of the traffic light is stored in the storage device 42, the calculation unit 313 determines the position of the traffic light randomly determined by a random number as the stop location Ps among all the traffic lights. Note that random means, for example, that 50% of all traffic lights are red lights. Further, the calculation unit 313 may determine the stop points Ps based on the cycle information of the traffic light at the current time. The stop time at the traffic light may be a fixed time such as 60 seconds, or may be determined based on the past travel history. Further, the calculation unit 313 may acquire and use the cycle information of the traffic light at the current time by the communication unit 41.

After creating the final upper limit vehicle speed map MF_vmax in this way, the calculation unit 313 creates a vehicle speed profile v (x) that satisfies this. For example, the calculation unit 313 assumes that the acceleration and deceleration take predetermined values under the rule that the vehicle travels at the fastest possible vehicle speed while satisfying the final upper limit vehicle speed map MF_vmax, and the vehicle speed profile v (x). ) May be created. Further, the calculation unit 313 may create a vehicle speed profile v (x) that satisfies the upper limit vehicle speed map M_vmax by using a traffic flow simulation. Through the above calculations, the calculation unit 313 creates a vehicle speed profile v (x) showing the transition of the vehicle speed at each point on the predicted traveling route of the vehicle 10, as shown by the alternate long and short dash line in FIG. Note that "x" indicates the distance from the current location to a predetermined point on the predicted traveling route of the vehicle 10.

As shown in FIG. 2, the calculation unit 313 creates a driving force profile F (x) as a process of step S14 following step S13. Specifically, the calculation unit 313 shows the vehicle weight set value m and the running resistance set value Fr calculated through the process shown in FIG. 3, the wind power map M_Fw calculated through the process shown in FIG. 4, and FIG. The driving force F at each point on the traveling path of the vehicle 10 is calculated by using the above equation f1 from the gradient map M_θ calculated through the processing and the vehicle speed profile v (x) calculated in the processing of step S13. .. As a result, the calculation unit 313 creates a driving force profile F (x) indicating a transition of the driving force at each point on the traveling path of the vehicle 10.

The calculation unit 313 creates a drive power profile Pd (x) as a process of step S15 following step S14. Specifically, the calculation unit 313 calculates the driving power profile Pd (x) from the driving force profile F (x) created in the process of step S14 and the vehicle speed profile v (x) based on the following equation f2. create.

演算部３１３は、ステップＳ１５に続くステップＳ１６の処理として、空調パワープロフィールＰａ（ｘ）を作成する。具体的には、演算部３１３は、図４に示される処理を通じて演算される空調パワーマップＭ＿Ｐａに基づいて空調パワープロフィールＰａ（ｘ）を作成する。

The calculation unit 313 creates an air conditioning power profile Pa (x) as a process of step S16 following step S15. Specifically, the calculation unit 313 creates the air conditioning power profile Pa (x) based on the air conditioning power map M_Pa calculated through the process shown in FIG.

The calculation unit 313 creates the power consumption profile Pb (x) of the battery 22 as the process of step S17 following step S16. Specifically, the calculation unit 313 is based on the following equation f3 from the drive power profile Pd (x) obtained in the process of step S15 and the air conditioning power profile Pa (x) obtained in the process of step S16. The power consumption profile Pb (x) of the battery 22 is created. In the formula f3, "η_d" indicates the energy efficiency of the drive system, and "η_a" indicates the energy efficiency of the air conditioner. As the energy efficiency η_d of the drive system, for example, the one acquired by the parameter acquisition unit 310 from the EV ECU 30 is used. As the energy efficiency η_a of the air conditioner, for example, one acquired by the parameter acquisition unit 310 from the air conditioner is used.

演算部３１３は、ステップＳ１７に続くステップＳ１８の処理として、車両１０の限界到達地点Ｋｂを探索する。具体的には、演算部３１３は、エネルギ残量取得部３１２により取得されているバッテリ２２の現在のＳＯＣ値と、ステップＳ１７の処理で得られるバッテリ２２の消費パワープロフィールＰｂ（ｘ）とに基づいて、図８に示されるようなバッテリ２２のＳＯＣ値の推移を作成する。そして、演算部３１３は、バッテリ２２のＳＯＣ値が所定の閾値に達する地点を車両１０の限界到達地点Ｋｂと判断するとともに、車両１０の現在地Ｋａから限界到達地点Ｋｂまでの距離を航続可能距離Ｄと判断する。

The calculation unit 313 searches for the limit arrival point Kb of the vehicle 10 as the process of step S18 following step S17. Specifically, the calculation unit 313 is based on the current SOC value of the battery 22 acquired by the energy remaining amount acquisition unit 312 and the power consumption profile Pb (x) of the battery 22 obtained in the process of step S17. Then, the transition of the SOC value of the battery 22 as shown in FIG. 8 is created. Then, the calculation unit 313 determines that the point where the SOC value of the battery 22 reaches a predetermined threshold value is the limit arrival point Kb of the vehicle 10, and the distance from the current location Ka of the vehicle 10 to the limit arrival point Kb is the cruising distance D. Judge.

As shown in FIG. 2, the calculation unit 313 determines whether or not the limit arrival point Kb has been calculated for all the predicted travel paths on which the vehicle 10 may travel as the process of step S19 following step S18. do. If there is a predicted travel route for which the limit arrival point Kb has not been calculated, the calculation unit 313 makes a negative determination in the process of step S19, and returns to the process of step S12.

On the other hand, when the calculation unit 313 calculates the limit arrival point Kb for all the predicted traveling routes, the calculation unit 313 makes a positive judgment in the process of step S19. In this case, the calculation unit 313 instructs the HMI ECU 32 to display the map information around the own vehicle 10 as the process of step S20. As a result, the HMI ECU 32 displays the map information around the vehicle 10 on the HMI device 50.

Subsequently, the calculation unit 313 instructs the HMIECU 32 to display the limit arrival point Kb of each predicted traveling route as the process of step S21. As a result, the HMI ECU 32 displays the limit arrival points Kb11 to Kb19 of each predicted traveling route on the HMI device 50 as shown in FIG. 9, and the straight line m11 to connect the points Kb11 to Kb19 next to each other. m19 is also displayed. The area surrounded by the straight lines m11 to m19 indicates an area that the vehicle 10 can reach. Therefore, the driver of the vehicle 10 can grasp the cruising distance of the vehicle 10 by looking at the straight lines m11 to m19 displayed on the HMI device 50.

According to the prediction ECU 31 of the present embodiment described above, the actions and effects shown in the following (1) to (7) can be obtained.
(1) The calculation unit 313 includes information on the traveling route acquired by the route information acquisition unit 311, information on the SOC value of the battery 22 acquired by the energy remaining amount acquisition unit 312, and a vehicle acquired by the parameter acquisition unit 310. The cruising range D of the vehicle 10 is calculated based on a predetermined parameter such as the weight set value m. When the parameter acquisition unit 310 cannot set the vehicle weight set value m and the running resistance set value Fr by the process of step S101 shown in FIG. 3, for example, the parameter acquisition unit 310 performs the process of any of steps S103, S104, S106, and S107 of the vehicle. The weight set value m and the running resistance set value Fr are set. In this case, the process of step S101 corresponds to the first acquisition means, and the processes of steps S103 and S106 correspond to the second acquisition means. Regarding the wind power map M_Fw and the air conditioning power map M_Pa, the processes of steps S111 and S112 shown in FIG. 4 correspond to the first acquisition means, and the processes of steps S113 and S114 correspond to the second acquisition means. Further, regarding the gradient map M_θ and the upper limit vehicle speed map M_vmax, the process of step S121 shown in FIG. 6 corresponds to the first acquisition means, and the process of steps S123, S125, and S126 corresponds to the second acquisition means. According to this configuration, even when a predetermined parameter such as the vehicle weight set value m cannot be acquired by the first acquisition means, the predetermined parameter can be acquired by the second acquisition means, so that the predetermined parameter can be obtained. It is possible to ensure redundancy in the operation.

(2) The parameter acquisition unit 310 in the own vehicle 10 by executing the process of step S103 shown in FIG. 3 as the second acquisition means for acquiring the vehicle weight set value m and the running resistance set value Fr. The vehicle weight set value m and the running resistance set value Fr are calculated based on the own vehicle detection information such as the detectable running speed of the vehicle 10 and the driving force of the motor generator 20. Regarding the wind power map M_Fw and the air conditioning power map M_Pa, the processes of steps S113 and S114 shown in FIG. 4 correspond to the same processes. Further, regarding the gradient map M_θ and the upper limit vehicle speed map M_vmax, the process of step S126 shown in FIG. 6 corresponds to the same process. According to this configuration, since each parameter is calculated based on the information detected in the own vehicle 10, the calculation accuracy of each parameter can be ensured.

(3) The process of step S126 shown in FIG. 6 is based on information on the past traveling history of the own vehicle 10, such as the history of the past traveling speed of the own vehicle 10 and the history of the past driving force of the motor generator 20. This is a process for calculating the gradient map M_θ and the upper limit vehicle speed map M_vmax. Specifically, the parameter acquisition unit 310 statistically processes the history of the past traveling speed of the own vehicle 10 and the history of the past driving force of the motor generator 20 as the process of step S126, so that the gradient map M_θ And the upper limit vehicle speed map M_vmax is calculated. In the present embodiment, the past traveling speed of the own vehicle 10 and the past driving force of the motor generator 20 correspond to the past own vehicle detection information. According to this configuration, even when the gradient map M_θ and the upper limit vehicle speed map M_vmax cannot be acquired by using the process of step S121, they can be calculated with high accuracy.

(4) The parameter acquisition unit 310 executes the process of step S106 shown in FIG. 3 as the second acquisition means for acquiring the traveling resistance set value Fr, and is stored in the server device 62 for another vehicle. The running resistance set value Fr is set using the running resistance information of. Further, the parameter acquisition unit 310 is stored in the server device 62 by executing the process of step S125 shown in FIG. 6 as the second acquisition means for acquiring the gradient map M_θ and the upper limit vehicle speed map M_vmax. The gradient map M_θ and the upper limit vehicle speed map M_vmax are acquired. The server device 62 creates a gradient map M_θ and an upper limit vehicle speed map M_vmax based on information that can be acquired from a plurality of other vehicles other than the vehicle 10. According to this configuration, since each parameter is calculated based on the information of other vehicles, the calculation accuracy of each parameter can be ensured.

(5) When the parameter acquisition unit 310 cannot execute the process of step S103 shown in FIG. 3, that is, when the travel resistance set value Fr cannot be set based on the detection information of the own vehicle 10, the process of step S106 By executing the above, the running resistance set value Fr is set using the running resistance information of the other vehicle. According to this configuration, the traveling resistance set value Fr is preferentially set based on the detection information of the own vehicle, so that the accuracy of the traveling resistance set value Fr can be ensured.

(6) The gradient map M_θ and the upper limit vehicle speed map M_vmax created by the process of step S125 shown in FIG. 6 relate to the past running history of the other vehicle such as the past running speed and the upper limit vehicle speed of the other vehicle by the server device 62. Created based on statistically processed data of information. According to this configuration, even if the gradient map M_θ and the upper limit vehicle speed map M_vmax cannot be obtained by using the processes of steps S121 and S123, the gradient map M_θ and the upper limit vehicle speed map M_vmax can be calculated with high accuracy. Can be done.

(7) When the parameter acquisition unit 310 cannot set the vehicle weight set value m in the processes of steps S101 and S103 shown in FIG. 3, the parameter acquisition unit 310 sets the vehicle weight set value m to a fixed value mc as the process of step S104. do. If the parameter acquisition unit 310 cannot set the running resistance set value Fr in the process of steps S101, S103, and S106 shown in FIG. 3, the parameter acquisition unit 310 sets the running resistance set value Fr to a fixed value Frd as the process of step S107. Set. According to this configuration, it is possible to avoid a situation in which the vehicle weight set value m and the running resistance set value Fr cannot be obtained, so that the cruising distance D and the limit arrival point Kb can be calculated more reliably.

The above embodiment can also be implemented in the following embodiments.
-The method of displaying the cruising distance D on the HMI device 50 can be changed as appropriate. For example, the cruising range D may be numerically displayed on the HMI device 50.

The configuration of the prediction ECU 31 of the above embodiment is not limited to the vehicle 10 powered by the motor generator 20, but also to an engine vehicle powered by the engine and a hybrid vehicle powered by both the motor generator and the engine. Applicable. When the prediction ECU 31 of the above embodiment is applied to an engine vehicle, the information regarding the remaining amount of energy that can be used for traveling of the vehicle is, for example, information regarding the remaining amount of fuel.

The predictive ECU 31 and its control method described in the present disclosure are provided by configuring a processor and memory programmed to perform one or more functions embodied by a computer program. It may be realized by a dedicated computer of. The prediction ECU 31 and its control method described in the present disclosure may be realized by a dedicated computer provided by configuring a processor including one or more dedicated hardware logic circuits. The predictive ECU 31 and its control method described in the present disclosure consist of a combination of a processor and memory programmed to perform one or more functions and a processor including one or more hardware logic circuits. It may be realized by one or more dedicated computers. The computer program may be stored on a computer-readable non-transitional tangible recording medium as an instruction executed by the computer. The dedicated hardware logic circuit and the hardware logic circuit may be realized by a digital circuit including a plurality of logic circuits or an analog circuit.

-The present disclosure is not limited to the above specific examples. Specific examples described above with appropriate design changes by those skilled in the art are also included in the scope of the present disclosure as long as they have the features of the present disclosure. Each element included in each of the above-mentioned specific examples, and their arrangement, conditions, shape, and the like are not limited to those illustrated, and can be changed as appropriate. The combinations of the elements included in each of the above-mentioned specific examples can be appropriately changed as long as there is no technical contradiction.

31: Prediction ECU (arithmetic logic unit)
310: Parameter acquisition unit 311: Path information acquisition unit 312: Energy remaining amount acquisition unit 313: Calculation unit

Claims (11)

An arithmetic unit (31) that calculates the cruising range of a vehicle.
A route information acquisition unit (311) for acquiring information on the traveling route of the vehicle, and
An energy remaining amount acquisition unit (312) for acquiring information on the remaining amount of energy that can be used for traveling of the vehicle, and
A parameter acquisition unit (310) that acquires a predetermined parameter necessary for calculating the cruising distance separately from the information on the traveling route and the information on the remaining amount of energy.
It includes information on the traveling route, information on the remaining amount of energy, and a calculation unit (313) for calculating the cruising distance of the vehicle based on the predetermined parameters.
The parameter acquisition unit is a vehicle arithmetic unit that acquires the predetermined parameter by a second acquisition means different from the first acquisition means when the predetermined parameter cannot be acquired by the first acquisition means. The arithmetic unit for a vehicle according to claim 1, wherein the parameter acquisition unit sets the predetermined parameters based on the own vehicle detection information which is information that can be detected in the own vehicle as the second acquisition means. The vehicle arithmetic unit according to claim 2, wherein the parameter acquisition unit uses past own vehicle detection information as the own vehicle detection information. The parameter acquisition unit
As the past own vehicle detection information, information on the past running history of the own vehicle is used, and the information is used.
The vehicle arithmetic unit according to claim 3, wherein as the second acquisition means, the predetermined parameter is set based on a value obtained by statistically processing information on the past travel history of the own vehicle. The calculation device for a vehicle according to claim 4, wherein the information on the past travel history of the own vehicle includes at least one of information on the traveling speed of the own vehicle and information on the driving force of the power source of the own vehicle. .. The parameter acquisition unit sets the predetermined parameter based on the information acquired from another vehicle when the predetermined parameter cannot be calculated from the own vehicle detection information as the second acquisition means. The arithmetic unit of the vehicle according to any one of 5. The arithmetic unit for a vehicle according to claim 1, wherein the parameter acquisition unit sets the predetermined parameters based on information acquired from another vehicle as the second acquisition means. The vehicle arithmetic unit according to claim 6 or 7, wherein the information acquired from the other vehicle is information detected in the other vehicle. The vehicle arithmetic unit according to claim 8, wherein the parameter acquisition unit sets the predetermined parameters by statistically processing information detected in a plurality of other vehicles. The vehicle arithmetic unit according to claim 9, wherein the information detected in the other vehicle includes at least one of information on the traveling speed of the other vehicle and information on the driving force of the power source of the other vehicle. The vehicle according to any one of claims 1 to 10, wherein the parameter acquisition unit uses a predetermined value as the predetermined parameter when the second acquisition means cannot acquire the predetermined parameter. Arithmetic logic unit.

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