Control device of vehicle

A control device of a vehicle comprises a vehicle control part 61 configured to use a probability distribution of at least one predetermined parameter to calculate an expected value of each of at least one evaluation value and control the vehicle 1 based on the expected value.

FIELD

The present invention relates to a control device of a vehicle.

BACKGROUND

In the past, it has been known to predict a predetermined parameter relating to driving of a vehicle and use the predicted value of the parameter to control the vehicle (for example PTL 1).

In a hybrid vehicle provided with an internal combustion engine and a motor as sources of power able to output power for driving, the EV mode and HV mode can be selected as the driving mode. In the EV mode, power for driving is output by only the motor, while in the HV mode, power for driving is output by the internal combustion engine and motor. In the EV mode, the internal combustion engine is stopped, so it is possible to select the EV mode as the driving mode to improve the fuel efficiency of the hybrid vehicle.

However, if the amount of stored power of the battery is insufficient, the EV mode cannot be selected as the driving mode. For this reason, if driving the vehicle for a long time without charging the battery, it is necessary to jointly use the EV mode and HV mode as the driving mode.

CITATIONS LIST

Patent Literature

SUMMARY

Technical Problem

If a vehicle is driven from a current position to a destination, the driving modes in the different driving sections of the driving route are preferably selected so that the amount of fuel consumption becomes the smallest. For this reason, it may be considered to calculate an evaluation value such as an amount of fuel consumption or an amount of electric power consumption based on the predicted values of the vehicle speeds at the driving sections and select the driving modes so that the evaluation value becomes optimal.

In this connection, in the control device of the vehicle described in PTL 1, the value of the vehicle speed at the maximum probability in the probability distribution generated in advance is used as the predicted value of the vehicle speed. However, the actual vehicle speed will not necessarily match the value at the maximum probability in the probability distribution. If the driving mode is selected so that the evaluation value calculated based on an erroneous predicted value becomes optimum, the fuel efficiency of the vehicle etc., are liable to deteriorate.

Therefore, considering the above technical issue, the object of the present invention is to improve the precision of prediction of an evaluation value used in control of a vehicle.

Solution to Problem

The summary of the present disclosure is as follows.

(1) A control device of a vehicle comprising a vehicle control part configured to use a probability distribution of at least one predetermined parameter to calculate an expected value of each of at least one evaluation value and control the vehicle based on the expected value.

(2) The control device of a vehicle described in above (1), further comprising a driving data acquiring device acquiring the at least one predetermined parameter as driving data and a probability distribution generating part configured to generate the probability distribution based on the driving data acquired by the driving data acquiring device.

(3) The control device of a vehicle described in above (2), wherein the probability distribution generating part is provided at an outside of the vehicle and is configured to receive the driving data from driving data acquiring devices provided at the plurality of vehicles.

(4) The control device of a vehicle described in any one of above (1) to (3), wherein the at least one predetermined parameter is a vehicle speed.

(5) The control device of a vehicle described in above (4), wherein the vehicle comprises an internal combustion engine and a motor able to output power for driving and a battery supplying electric power to the motor and able to be charged by an external power supply, the at least one evaluation value is an amount of electric power consumption when the vehicle is being driven over a driving route from a current position to a destination or an amount of electric power consumption and an amount of fuel consumption when the vehicle is being driven over the driving route, and the vehicle control part is configured to select the driving mode of the vehicle at each driving section of the driving route based on the expected value of each of the at least one evaluation value.

(6) The control device of a vehicle described in above (4), wherein the at least one evaluation value is a time of arrival of the vehicle at a destination, and the vehicle control part configured to set a target value of a vehicle speed based on the expected value each of the at least one evaluation value.

(7) The control device of a vehicle described in any one of above (1) to (3), wherein the vehicle comprises a generator able to use regenerated energy to generate regenerated electric power at the time of braking of the vehicle and a battery to which the regenerated electric power generated by the generator is supplied, the at least one predetermined parameter is a brake pressure, while the at least one evaluation value is an amount of loss of the regenerated electric power, and the vehicle control part is configured to set the target value of the vehicle speed based on the expected value of each of the at least one evaluation value.

(8) The control device of a vehicle described in any one of above (1) to (3), wherein the vehicle comprises an internal combustion engine and a motor able to output power for driving, a battery supplying electric power to the motor and able to be charged by an external power supply, and an air-conditioner, the at least one predetermined parameter is a combination of an outside air temperature and an outside air humidity or the outside air temperature, and the at least one evaluation value is an electric power consumed by the air-conditioner in a predetermined time period in the future, and the vehicle control part is configured to control a state of charge of the battery based on the expected value of each of the at least one evaluation value.

(9) The control device of a vehicle described in any one of above (1) to (3), wherein the vehicle comprises an internal combustion engine and a motor able to output power for driving, a battery supplying electric power to the motor and able to be charged by an external power supply, and an air-conditioner, the at least one predetermined parameter is an outside air temperature, and the at least one evaluation value is an amount of fuel consumption for warmup in a predetermined time period in the future, and the vehicle control part is configured to select a driving mode of the vehicle based on the expected value of each of the at least one evaluation value.

(10) The control device of a vehicle described in any one of above (1) to (3), wherein the vehicle comprises an internal combustion engine and a motor able to output power for driving and a battery supplying electric power to the motor and able to be charged by an external power supply, the at least one predetermined parameter is a time of departure and an amount of electric power consumption of the battery from departure until recharging, and the at least one evaluation value is an amount of stored power of the battery at the time of departure and the amount of electric power consumption from departure until recharging, and the vehicle control part is configured to set a time of start of charging of the battery based on the expected value of each of the at least one evaluation value.

Advantageous Effects of Invention

According to the present invention, it is possible to improve the precision of prediction of an evaluation value used in control of a vehicle.

DESCRIPTION OF EMBODIMENTS

Below, referring to the drawings, embodiments of the present invention will be explained in detail. Note that, in the following explanation, similar components are assigned the same reference signs.

First Embodiment

Below, referring toFIG. 1toFIG. 6, a first embodiment of the present invention will be explained.

FIG. 1is a view schematically showing the configuration of a vehicle in which a control device of a vehicle according to the first embodiment of the present invention is used. A vehicle1is provided with an internal combustion engine10, first motor-generator12, power distributing mechanism14, second motor-generator16, power control unit (PCU)18, and battery20.

The internal combustion engine10burns an air-fuel mixture of fuel and air in cylinders to output power. The internal combustion engine10, for example, is a gasoline engine or a diesel engine An output shaft of the internal combustion engine10(crankshaft) is mechanically connected to the power distributing mechanism14, and output of the internal combustion engine10is input to the power distributing mechanism14.

The first motor-generator12functions as a generator and motor. The first motor-generator12is mechanically connected to the power distributing mechanism14, and the output of the first motor-generator12is input to the power distributing mechanism14. Further, the first motor-generator12is electrically connected to the PCU18. When the first motor-generator12functions as a generator, the electric power generated by the first motor-generator12is supplied through the PCU18to at least one of the second motor-generator16and battery20. On the other hand, when the first motor-generator12functions as a motor, the electric power stored in the battery20is supplied through the PCU18to the first motor-generator12.

The power distributing mechanism14is configured as a known planetary gear mechanism including a sun gear, ring gear, pinion gears, and a planetary carrier. The output shaft of the internal combustion engine10is coupled with the planetary carrier, the first motor-generator12is coupled with the sun gear, and a speed reducer32is coupled with the ring gear. The power distributing mechanism14distributes the output of the internal combustion engine10to the first motor-generator12and the speed reducer32.

Specifically, when the first motor-generator12functions as a generator, the output of the internal combustion engine10input to the planetary carrier is distributed to the sun gear coupled with the first motor-generator12and the ring gear coupled with the speed reducer32in accordance with the gear ratio. The output of the internal combustion engine10distributed to the first motor-generator12is used to generate electric power by the first motor-generator12. On the other hand, the output of the internal combustion engine10distributed to the speed reducer32is transmitted as power for driving through an axle34to the wheels36. Therefore, the internal combustion engine10can output power for driving. Further, when the first motor-generator12functions as a motor, the output of the first motor-generator12is supplied through the sun gear and planetary carrier to the output shaft of the internal combustion engine10whereby the internal combustion engine10is cranked.

The second motor-generator16functions as a generator and motor. The second motor-generator16is mechanically connected to the speed reducer32, and the output of the second motor-generator16is supplied to the speed reducer32. The output of the second motor-generator16supplied to the speed reducer32is transmitted as power for driving to the wheels36through the axle34. Therefore, the second motor-generator16can output power for driving.

Further, the second motor-generator16is electrically connected to the PCU18. At the time of deceleration of the vehicle1, due to rotation of the wheels36, the second motor-generator16is driven and the second motor-generator16functions as a generator. As a result, so-called regeneration is performed. When the second motor-generator16functions as a generator, the regenerative power generated by the second motor-generator16using the regenerative energy is supplied through the PCU18to the battery20. On the other hand, when the second motor-generator16functions as a motor, the power stored in the battery20is supplied through the PCU18to the second motor-generator16.

The PCU18is electrically connected to the first motor-generator12, second motor-generator16, and battery20. The PCU18includes an inverter, a booster converter, and a DC-DC converter. The inverter converts DC power supplied from the battery20to AC power and converts AC power generated by the first motor-generator12or second motor-generator16to DC power. The booster converter boosts the voltage of the battery20in accordance with need when the power stored in the battery20is supplied to the first motor-generator12or the second motor-generator16. The DC-DC converter lowers the voltage of the battery20when the electric power stored in the battery20is supplied to the headlights or other electronic equipment.

The power generated by the first motor generator12using the output of the internal combustion engine10and the regenerative power generated by the second motor generator16using regenerated energy are supplied to the battery20. Therefore, the battery20can be charged by the output of the internal combustion engine10and the regenerated energy. The battery20, for example, is a lithium ion battery, nickel hydrogen battery, or other secondary battery.

The vehicle1is further provided with a charging port22and charger24. The battery20can be charged by an external power source70as well. Therefore, the vehicle1is a so-called “plug-in hybrid vehicle (PHV)”.

The charging port22is configured so as to receive the electric power from the external power source70through a charging connector74of a charging cable72. When the battery20is charged by the external power source70, the charging connector74is connected to the charging port22. The charger24converts the electric power supplied from the external power source70to electric power which can be supplied to the battery20. Note that, the charging port22may also be connected to the PCU18, and the PCU18may also function as the charger24.

Note that, the first motor-generator12may be a generator not functioning as a motor. Further, the second motor-generator16may be a motor not functioning as a generator. Further, the vehicle1is a so-called series-parallel type of hybrid vehicle. However, the vehicle1may be a so-called series type, parallel type, or other type of hybrid vehicle.

<Control Device of Vehicle>

FIG. 2is a block diagram schematically showing the configuration of a control device of a vehicle etc., according to the first embodiment of the present invention. The control device of the vehicle is provided with an electronic control unit (ECU)60. The ECU60is provided with a read only memory (ROM) and random access memory (RAM) or other such memory, a processor, input port, output port, communication module, etc. The ECU60is provided at the vehicle. In the present embodiment, a single ECU60is provided, but a plurality of ECUs may be provided for the different functions.

The ECU60is connected to various sensors provided at the vehicle1. The outputs of the various sensors are input to the ECU60. In the present embodiment, the outputs of a voltage sensor51and a GPS receiver52are input to the ECU60.

The voltage sensor51is provided at the battery20and detects the voltage across the electrodes of the battery20. The voltage sensor51is connected to the ECU60, so the output of the voltage sensor51is transmitted to the ECU60. The ECU60calculates the state of charge (SOC: State Of Charge) of the battery20based on the output of the voltage sensor51, etc.

The GPS receiver52is provided at the vehicle1. The GPS receiver52receives signals from three or more GPS satellites and detects the current position of the vehicle1(for example, the longitude and latitude of the vehicle1). The GPS receiver52is connected to the ECU60, so the output of the GPS receiver52is transmitted to the ECU60.

Further, the ECU60is connected to a map database53provided at the vehicle1. The map database53is a database relating to map information. The map information includes the position information of roads, shape information of the roads (for example curved or straight types, radii of curvature of the curves, road gradients, etc.), types of roads, speed limits, and other road information. The ECU60acquires map information from the map database53.

Further, the ECU60is connected to a navigation system54provided at the vehicle1. The navigation system54sets a driving route of the vehicle1from the current position to the destination based on the output of the GPS receiver52, the map information of the map database53, the input by the driver, etc. The driving route set by the navigation system54is sent to the ECU60. Note that, the GPS receiver52and map database53may be built into the navigation system54.

Further, the ECU60is connected to the various actuators provided at the vehicle1and controls the various actuators. In the present embodiment, the ECU60is connected to the internal combustion engine10, first motor-generator12, second motor-generator16, power split mechanism14, PCU18, and charger24and controls these.

In the present embodiment, the ECU60has a vehicle control part61. The vehicle control part61is a functional block realized by a program stored in the memory of the ECU60being run by the processor of the ECU60. The vehicle control part61uses the probability distribution of a predetermined parameter to calculate an expected value of an evaluation value and controls the vehicle1based on the expected value of the evaluation value.

As explained above, the vehicle1is provided with an internal combustion engine10and second motor-generator16as sources of power able to output power for driving. For this reason, at the vehicle1, as the driving mode, an EV mode and HV mode can be selected.

At the EV mode, the internal combustion engine10is stopped and only the second motor-generator16is used to output power for driving. For this reason, in the EV mode, power is supplied from the battery20to the second motor-generator16. As a result, in the EV mode, the amount of stored power of the battery20is decreased and the SOC of the battery20falls. Note that, a one-way clutch transmitting rotational force in only one direction may be provided at the power split mechanism14and in the EV mode, power for driving may be output from the first motor-generator12and the second motor-generator16.

On the other hand, in the HV mode, the internal combustion engine10is started up and power for driving is output by the internal combustion engine10and the second motor-generator16. In the HV mode, basically, the power generated by the first motor-generator12using the output of the internal combustion engine10is supplied to the second motor-generator16and the supply of power from the battery20is stopped. Note that, in the HV mode, temporarily, the battery20may be charged by the output of the internal combustion engine10or temporarily power may be supplied from the battery20to the second motor-generator16. In the HV mode, the amount of stored power and the SOC of the battery20are maintained substantially constant. Therefore, the degree of drop of the SOC in the EV mode is larger than the degree of drop of the SOC in the HV mode.

In the HV mode, fuel is consumed in the internal combustion engine10, while in the EV mode, fuel is not consumed in the internal combustion engine10. For this reason, to improve the fuel efficiency of the vehicle1, it is preferable to maintain the driving mode in the EV mode as much as possible. However, if the amount of stored power of the battery20is insufficient, it is not possible to select the EV mode as the driving mode. For this reason, if driving the vehicle1for a long period of time without charging the battery20by the external power supply70, it is necessary to jointly use the EV mode and HV mode as the driving mode.

When the vehicle1is driven over a driving route from the current position to the destination (below, simply referred to as the “driving route”), the amount of electric power which can be consumed for driving is limited by the amount of stored power of the battery20at the time of departure. To improve the fuel efficiency of the vehicle1, the driving mode is preferably selected so that the amount of fuel consumption when the vehicle1is being driven over the driving route becomes minimum under this restriction.

The amount of electric power consumption and amount of fuel consumption fluctuate in accordance with the road gradient and vehicle speed (speed of the vehicle1) at the time of driving. For this reason, the amount of electric power consumption and the amount of fuel consumption are expressed as functions of the road gradient and vehicle speed. Further, the electric power stored in the battery20is consumed in the EV mode and is not consumed in the HV mode. On the other hand, in the EV mode, the internal combustion engine10is stopped, while in the HV mode, fuel is consumed in the internal combustion engine10.

For this reason, if the driving route is divided into a plurality of driving sections, the amount of electric power consumption Ekat a driving section “k” is expressed by the following equation (1):
Ek=e(xk,vk)×uk(1)

Further, the amount of fuel consumption Fkat a driving section “k” is expressed by the following equation (2):
Fk=f(xk,vk)×(1−uk)  (2)

Here, “e” is a function for calculating the amount of electric power consumption based on the road gradient and vehicle speed and has the road gradient xkand vehicle speed vkat a driving section “k” as variables, “f” is a function for calculating the amount of fuel consumption based on the road gradient and vehicle speed and has the road gradient xkand vehicle speed vkat a driving section “k” as variables.

Further, ukshows the driving mode at a driving section “k”. In the EV mode, it is set to “1”, while in the HV mode, it is set to “0”. For this reason, as clear from the above equations (1) and (2), the amount of electric power consumption Ekbecomes 0 at the HV mode and the amount of fuel consumption Fkbecomes 0 at the EV mode.

By cumulatively adding the amounts of electric power consumption at all of the driving sections of a driving route, it is possible to calculate the amount of electric power consumption when the vehicle1is being driven aver the driving route (below, referred to as the “total amount of electric power consumption”). Similarly, by cumulatively adding the amounts of fuel consumption at all of the driving sections of a driving route, it is possible to calculate the amount of fuel consumption when the vehicle1is being driven over the driving route (below, referred to as the “total amount of fuel consumption”). Therefore, if the road gradient and vehicle speed at each driving section are known, it is possible to predict the total amount of electric power consumption and total amount of fuel consumption when changing the driving mode at each driving section.

The road gradients are stored in advance in the map database53for the different driving sections. On the other hand, a vehicle speed differs from a road gradient and fluctuates in accordance with a state of congestion of a road etc. For this reason, the vehicle speed corresponding to each driving section can conceivably be predicted probabilistically based on past driving data. For example, the probability distribution of the vehicle speed for a predetermined driving section is generated as follows using past driving data:

TABLE IVehicle speed (km/h)0 to 2020 to 4040 to 6060 to 8080 to 100Probability (%)53050105

In this case, the probability becomes maximum in a speed class of 40 to 60 km/h. The average vehicle speed of this speed class is 50 km/h. For this reason, if the vehicle speed at the maximum probability in the probability distribution is used as the predicted value, the predicted value of the vehicle speed at the driving section becomes 50 km/h. However, according to the above probability distribution, this prediction will be wrong with a probability of 50%. For this reason, if using the thus predicted vehicle speed to predict the amount of electric power consumption and the amount of fuel consumption at each driving section, a large discrepancy is liable to be generated between the predicted value and the actual value.

FIG. 3is a view showing measurement data of the vehicle speed on a predetermined driving route. In this figure, a driving position is shown as a distance from the current position. Further, the actual vehicle speed is shown by the solid line, while the predicted value of the vehicle speed is shown as a broken line. In the example ofFIG. 3, as the predicted value of the vehicle speed, the value at the maximum probability in the probability distribution is used. As a result, in the example ofFIG. 3, in particular, at the driving position near 8 to 11 km, a large discrepancy is generated between the predicted value and the actual value. Therefore, there is room for improvement in calculation of a predicted value using probability distribution.

Therefore, in the present embodiment, the vehicle control part61uses the probability distribution of a predetermined parameter to calculate an expected value of an evaluation value and controls the vehicle1based on the expected value of the evaluation value. By doing this, variation in the probability distribution is also considered in calculation of the evaluation value, so it is possible to improve the precision of prediction of the evaluation value. As a result, the control performed in the vehicle can be optimized.

In the present embodiment, the predetermined parameter is the vehicle speed, and the evaluation values are the total amount of electric power consumption and the total amount of fuel consumption. In this case, the vehicle control part61uses the probability distribution of the vehicle speed for each driving section to calculate the expected values of the total amount of electric power consumption and total amount of fuel consumption.FIG. 4is a view showing one example of the probability distribution of the vehicle speed for the different driving sections. In this figure, each driving section is shown as a distance from the current position.

The probability distribution such as shown inFIG. 4is stored in the memory of the ECU60as a three-dimensional map showing the probability corresponding to a driving section and vehicle speed. Each driving section is determined based on the distance, position of intersections, road. ID included in the map information of the map database53, etc. Each driving section is given an identification label for identifying the driving section.

The vehicle control part61predicts the driving route of the vehicle1and uses the probability distribution of the vehicle speed for the different driving sections of the driving route to calculate the expected values of the total amount of electric power consumption and the total amount of fuel consumption. Specifically, the vehicle control part61uses the following equation (3) to calculate the expected value Eeof the total amount of electric power consumption:

The following equation (4) is a part of the right side of the above equation (3) and corresponds to the expected value Ekeof the amount of electric power consumption at a driving section “k”:

Here, Pvkis the probability of the vehicle speed becoming “v” at a driving section “k” and is acquired from the probability distribution of the vehicle speed for the driving section “k”. As will be understood from the above equation (4), the expected value Ekeof the amount of electric power consumption at the driving section “k” is calculated by cumulatively adding the values obtained by multiplying the probabilities Pvkcorresponding to the different vehicle speeds “v” with the amount of electric power consumption (e(xk, v)×uk) calculated by the above equation (1) using the different vehicle speeds “v”. The number of vehicle speeds “v” cumulatively added becomes the number of speed classes in the probability distribution of the vehicle speed (in the above Table 1, five). Further, as the value of the vehicle speed “v”, the average value of each speed class is used. Note that, the vehicle speed “v” may be a continuous value such as shown inFIG. 4.

Therefore, as will be understood from the above equation (3), the vehicle control part61cumulatively adds the expected values Ekeof the amounts of electric power consumption at the driving sections “k” to calculate the expected value Eeof total amount of electric power consumption. The number of driving sections “k” which are cumulatively added becomes the number of the driving sections on the driving route.

Further, the vehicle control part61uses the following equation (5) to calculate the expected value Feof total amount of fuel consumption:

The following equation (6) is a part of the right side of the above equation (5) and corresponds to the expected value Fkeof the amount of fuel consumption at a driving section “k”.

Here, Pvkis the probability of the vehicle speed becoming “v” in a driving section “k” and is acquired from the probability distribution of the vehicle speed with respect to the driving sections “k”. As will be understood from the above equation (6), the expected value Fkeof the amount of fuel consumption at a driving section “k” is calculated by cumulatively adding the values obtained by multiplying the probabilities Pvkcorresponding to the different vehicle speeds “v” with the amounts of fuel consumption (f(xk, vk)×(1−uk)) calculated by the above equation (2) using the different vehicle speeds “v”. The number of vehicle speeds “v” which are cumulatively added becomes the number of speed classes in the probability distribution (in the above Table 1, five). Further, as the value of the vehicle speed “v”, the average value of each speed class is used. Note that, the vehicle speed “v” may be a continuous value such as shown inFIG. 4.

Therefore, as will be understood from the above equation (5), the vehicle control part.61cumulatively adds the expected values Fkeof the amounts of fuel consumption at the driving sections “k” to calculate the expected value Feof total amount of fuel consumption. The number of driving sections “k” which are cumulatively added becomes the number of the driving sections on the driving route.

Further, the vehicle control part61selects the driving mode of the vehicle1based on the expected value of the total amount of electric power consumption and the expected value of the total amount of fuel consumption. Specifically, the vehicle control part61selects the driving mode of the vehicle1at each driving section of a driving route so that the expected value of the total amount of electric power consumption satisfies a restricting condition and so that the expected value of the total amount of fuel consumption becomes the minimum. By doing this, the driving mode is optimized, and the fuel efficiency when the vehicle1is being driven over the driving route can be improved.

Specifically, the vehicle control part61calculates the ukat the above equations (3) and (5) so that the expected value of the total amount of electric power consumption satisfies the restricting condition and so that the expected value of the total amount of fuel consumption becomes the minimum. Note that, ukshows the driving mode at a driving section “k” and is set for each driving section of a driving mute.

The restricting condition is defined by the following equation (7). That is, the restricting condition is the expected value Eeof the total amount of electric power consumption becoming equal to or less than the amount of electric power left Eleftof the battery20. The remaining amount of electric power Eleftof the battery20is calculated based on the output of the voltage sensor51etc.
Ee≤Eleft(7)

Note that, the restricting condition may be defined by the following equation (8). That is, the restricting condition may be the expected value Eeof the total amount of electric power consumption becoming equal to or less than the value of the remaining amount of electric power Eleftof the battery20minus a predetermined value α (α>0).
Ee≤Eleft−α  (8)

Further, the restricting condition may be defined by the following equation (9): That is, the restricting condition may be the expected value Eeof the total amount of electric power consumption becoming equal to or less than the value of the remaining amount of electric power Eleftof the battery20multiplied with a predetermined value β(0<β<1).
Ee≤Eleft×β  (9)

<Processing for Selecting Driving Mode>

FIG. 5is a flow chart showing the control routine of processing for selecting a driving mode in the first embodiment of the present invention. The present control routine is repeatedly performed by the ECU60.

First, at step S101, the vehicle control part61predicts the driving route of the vehicle1and identifies all of the driving sections of the driving route. If the driving route is set by the navigation system54, the vehicle control part61acquires the driving route from the navigation system54.

Note that, the vehicle control part61may predict the driving route of the vehicle1from the current position of the vehicle1, the current time, etc., based on the past driving data of the vehicle1stored in the memory of the ECU60. The current position of the vehicle1is detected by the GPS receiver52. The current time is detected by a digital clock built in the ECU60or by receiving information from outside the vehicle1through a vehicle-mounted communicating device. In this case, the navigation system54may be omitted from the vehicle1.

Next, at step S102, the vehicle control part61acquires the road gradients of the driving sections of the driving route from the map database53. Next, at step S103, the vehicle control part61acquires the probability distribution of the vehicle speed for the driving sections of the driving route from the memory of the ECU60.

Next, at step S104, the vehicle control part61uses the probability distribution of the vehicle speed for the driving sections and the road gradients of the driving sections to calculate the expected values of the total amount of electric power consumption and the total amount of fuel consumption. Further, the vehicle control part61selects the driving mode of the vehicle1at each driving section of the driving route based on the expected values of the total amount of electric power consumption and the total amount of fuel consumption. Specifically, the vehicle control part61selects the driving mode of the vehicle1at each driving section of the driving route so that the expected value of the total amount of electric power consumption satisfies the restricting condition and so that the expected value of the total amount of fuel consumption becomes the minimum. After step S104, the present control routine ends.

Note that, at step S104, the vehicle control part61may calculate the expected value of the total amount of electric power consumption and select the driving mode of the vehicle1at each driving section of the driving route based on the expected value of the total amount of electric power consumption. For example, the vehicle control part61may successively select the EV mode as the driving mode in order from the driving section with the smallest amount of electric power consumption so that the expected value of the total amount of electric power consumption satisfies the restricting condition. By doing this, it is possible to increase the ratio of the driving sections for which the EV mode is selected as the driving mode and possible to improve the fuel efficiency of the vehicle1.

Further, the function “e” for calculating the amount of electric power consumption and the function “f” for calculating the amount of fuel consumption may have only the vehicle speed as a variable. That is, the vehicle control part61may use only the probability distribution of the vehicle speed for the driving sections to calculate the expected values of the total amount of electric power consumption and total amount of fuel consumption. In this case, step S102is omitted.

FIG. 6is a flow chart showing the control routine of vehicle control in the first embodiment of the present invention. The present control routine is repeatedly performed by the ECU60.

First, at step S201, the vehicle control part61detects the current driving section of the vehicle1based on the output of the GPS receiver52and the map information of the map database53.

Next, at step S202, the vehicle control part61controls the vehicle1based on the driving mode selected for each driving section in the control routine ofFIG. 5. Specifically, the vehicle control part61stops the internal combustion engine10in the EV mode and operates the internal combustion engine10in the HV mode. Further, the vehicle control part61supplies electric power from the battery20to the second motor-generator16or the first motor-generator12and the second motor-generator16in the EV mode. After step S202, the present control routine ends.

Second Embodiment

The control device of a vehicle according to a second embodiment is basically similar in configuration and control of the control device of the vehicle according to the first embodiment except for the points explained below. For this reason, below, the second embodiment of the present invention will be explained focusing on the parts different from the first embodiment.

FIG. 7is a block diagram schematically showing the configuration of the control device of the vehicle according to the second embodiment of the present invention. In the second embodiment, the ECU60is connected to a driving data acquiring device55in addition to the voltage sensor51, GPS receiver52, map database53, and navigation system54.

The driving data acquiring device55is provided at the vehicle1and acquires a predetermined parameter as driving data. The driving data acquiring device55is connected to the ECU60. The output of the driving data acquiring device55is sent to the ECU60.

Further, in the second embodiment, the ECU60has a probability distribution generating part62in addition to the vehicle control part61. The vehicle control part61and probability distribution generating part62are respectively functional blocks realized by a program stored in the memory of the ECU60being run by the processor of the ECU60.

The probability distribution generating part62generates the probability distribution of a predetermined parameter based on the driving data acquired by the driving data acquiring device55. By doing this, in the second embodiment, a probability distribution in which a trend in the vehicle1is reflected can be efficiently generated using the vehicle1. In this case, it is not necessary to load probability distribution generated in advance in the ECU60at the manufacturing factory etc.

If the predetermined parameter for which the probability distribution is generated is the vehicle speed, the driving data acquiring device55, for example, includes a vehicle speed sensor detecting the vehicle speed. In this case, the driving data acquiring device55acquires the vehicle speed during driving of the vehicle1as the driving data. Further, the probability distribution generating part62generates the probability distribution of the vehicle speed for the driving sections based on the vehicle speed acquired by the driving data acquiring device55. The driving section when the vehicle speed is acquired by the driving data acquiring device55is detected based on the output of the GPS receiver52and the map information of the map database53. The probability distribution generated by the probability distribution generating part62is stored in the memory of the ECU60.

Third Embodiment

The control device of a vehicle according to a third embodiment is basically similar in configuration and control to the control device of the vehicle according to the second embodiment except for the points explained below. For this reason, below, the third embodiment of the present invention will be explained focusing on the parts different from the second embodiment.

FIG. 8is a view schematically showing the configuration of the control device of the vehicle according to the third embodiment of the present invention. In the third embodiment, the control device of the vehicle is provided with an ECU60provided at the vehicle1and a server80provided at the outside of the vehicle1. The ECU60and the server80are respectively provided with communication modules and can communicate with each other through the network90.

The server80is provided with, in addition to a communication module, a hard disk and random access memory (RAM) or other such storage device, processor, etc. Further, in the third embodiment, instead of the vehicle1, the server80is provided with the map database53.

The server80has a probability distribution generating part62. The probability distribution generating part62is a functional block realized by the processor of the server80running a program stored in the storage device of the server80.

The probability distribution generating part62receives driving data acquired by the driving data acquiring device55provided at the vehicle1from the driving data acquiring device55. Further, in the same way as the second embodiment, the probability distribution generating part62generates the probability distribution of a predetermined parameter based on the driving data acquired by the driving data acquiring device55. The probability distribution generated by the probability distribution generating part62is sent to the ECU60and stored in the memory of the ECU60.

In the third embodiment, instead of the ECU60of the vehicle1, the server80is used to generate the probability distribution. For this reason, the processing load of the ECU60can be reduced and in turn the manufacturing costs of the ECU60can be reduced.

Note that, the server80can communicate with a plurality of vehicles. In this case, the probability distribution generating part62receives the driving data acquired by the driving data acquiring devices55provided at the plurality of vehicles. By doing this, the big data can be used to efficiently generate the probability distribution of a predetermined parameter. As a result, for example, the number of the driving sections for which the probability distribution of the vehicle speed is generated can be increased.

Further, the server80may have the vehicle control part61and probability distribution generating part62. By doing this, the processing load of the ECU60can be reduced more.

Fourth Embodiment

The control device of a vehicle according to a fourth embodiment is basically similar in configuration and control to the control device of the vehicle according to the first embodiment except for the points explained below. For this reason, below, the fourth embodiment of the present invention will be explained focusing on the parts different from the first embodiment.

In the fourth embodiment, the vehicle control part61predicts the driving route of the vehicle1and uses the probability distribution of the vehicle speed for the driving sections of the driving route to calculate the expected value of the time of arrival of the vehicle1at the destination. Further, the vehicle control part61sets the target value of the vehicle speed based on the expected value of the time of arrival at the destination. For example, the vehicle control part61raises the target value of the vehicle speed if the expected value of the time of arrival at the destination is later than a set time. By doing this, it is possible to keep the time of arrival from becoming later than the set time.

Specifically, the vehicle control part61uses the following equation (10) to calculate the expected value AT at the time of arrival at the destination:

The following equation (11) is a part of the right side of the above equation (10) and corresponds to the expected value Tkeof the required driving time at a driving section “k”:

Here, Pvkis the probability of the vehicle speed becoming “v” at a driving section “k” and is acquired from the probability distribution of the vehicle speed for the driving section “k”. As will be understood from the above equation (11), the expected value Tkeof the required driving time at the driving section “k” is calculated by cumulatively adding the values obtained by multiplying the probabilities Pvkcorresponding to the different vehicle speeds “v” with the values obtained by dividing the distances dkof the driving sections “k” by the different vehicle speeds “v”. The distances dkof the driving sections “k” are stored in the map database53. The number of vehicle speeds “v” which are cumulatively added becomes the number of speed classes in the probability distribution (in the above Table 1, five). Further, as the value of the vehicle speed “v”, the average value of each speed class is used. Note that, the vehicle speed “v” may be a continuous value such as shown inFIG. 4.

Therefore, as will be understood from the above equation (10), the vehicle control part61adds the current time PT to the value obtained by cumulatively adding the expected values Tkeof required driving times at the driving sections “k” to thereby calculate the expected value AT of the time of arrival at the destination. The number of driving sections “k” which are cumulatively added becomes the number of driving sections of the driving route.

<Processing for Setting Vehicle Speed>

FIG. 9is a flow chart showing the control routine of processing for setting a vehicle speed in the fourth embodiment of the present invention. The present control routine is repeatedly performed by the ECU60.

First, at step S301, in the same way as step S101ofFIG. 5, the vehicle control part61predicts the driving route of the vehicle1and identifies all of the driving sections of the driving route. Next, at step S302, the vehicle control part61acquires the probability distribution of the vehicle speed for the driving sections of the driving route from the memory of the ECU60.

Next, at step S303, the vehicle control part61uses the probability distribution of the vehicle speed for the driving sections to calculate the expected value of the time of arrival at the destination of the vehicle1. Next, at step S304, the vehicle control part61judges whether the expected value of the time of arrival is later than a set time. The set time is, for example, the desired time of arrival at the destination input by the driver of the vehicle1to the navigation system54etc. If it is judged that the expected value of the time of arrival is equal to or earlier than the set time, the present control routine ends. On the other hand, if it is judged that the expected time of the time of arrival is later than the set time, the present control routine proceeds to step S305.

At step S305, the vehicle control part61raises the target value of the vehicle speed. Specifically, the vehicle control part61notifies the driver of the target value of the vehicle speed through the navigation system54or other human-machine interface (HMI). Note that, if acceleration and braking are automated in the vehicle1, the vehicle control part61controls the various actuators so that the vehicle speed approaches the target value. After step S305, the present control routine ends.

Note that, in the fourth embodiment, the charging port22and charger24may be omitted from the vehicle1, and the battery20need not be charged by the external power supply70. That is, the vehicle1need not be a plug-in hybrid vehicle. Further, the vehicle1may be provided with only an internal combustion engine10as a power source able to output the power for driving. That is, the vehicle1need not be a hybrid vehicle. Further, the vehicle1may be provided with only a motor (first motor-generator12, second motor-generator16, etc.) as a power source able to output the power for driving. That is, the vehicle1may be an electric vehicle (EV).

Fifth Embodiment

The control device of the vehicle according to a fifth embodiment is basically similar in configuration and control to the control device of the vehicle according to the first embodiment except for the points explained below. For this reason, below, the fifth embodiment of the present invention will be explained focusing on the parts different from the first embodiment.

FIG. 10is a block diagram schematically showing the configuration of the control device of the vehicle according to the fifth embodiment of the present invention etc. In the fifth embodiment, the ECU60is connected to the vehicle speed sensor56in addition to the voltage sensor51, GPS receiver52, map database53, and navigation system54.

The vehicle speed sensor56is provided at the vehicle1and detects the vehicle speed. The vehicle speed sensor56is connected with the ECU60. The output of the vehicle speed sensor56is sent to the ECU60.

As explained above, electric power is regenerated at the time of deceleration of the vehicle1. The regenerated electric power generated by the second motor-generator16is stored in the battery20. However, the regenerated electric power able to be generated by the second motor-generator16is limited by the properties of the second motor-generator16(size etc.). For this reason, if the brake pressure exceeds a predetermined value, braking is performed by a mechanical brake and regenerated electric power can no longer be recovered. As a result, the amount of electric power able to be consumed in the EV mode falls. Note that, the “brake pressure” means the force of depression of brake pedal provided at the vehicle1.

Therefore, in the fifth embodiment, the vehicle control part61uses the probability distribution of the brake pressure for the driving section and vehicle speed to calculate the expected value of the amount of loss of the regenerated electric power. Further, the vehicle control part61sets the target value of the vehicle speed based on the expected value of the amount of loss of the regenerated electric power. The larger the vehicle speed, the larger the brake pressure becomes and the larger the amount of loss of regenerated electric power tends to become. For this reason, the vehicle control part61lowers the target value of the vehicle speed if the expected value of the amount of loss of the regenerated electric power is larger than a threshold value. By doing this, it is possible to decrease the amount of loss of the regenerated electric power.

Specifically, the vehicle control part61uses the following equation (12) to calculate the expected value L of the amount of loss of the regenerated electric power:

Here, “g” is a function for calculating the amount of loss of the regenerated electric power based on the brake pressure and has the brake pressure “b” as a variable. The function “g” is set to become zero when the brake pressure “b” is equal to or less than a predetermined value and to become larger the larger the brake pressure “b”. Pvkbis the probability of the brake pressure becoming “b” at a driving section “k” and vehicle speed “v” and is acquired from the probability distribution of the brake pressure with respect to the driving section “k” and vehicle speed “v”. The probability distribution of the brake pressure with respect to the driving section “k” and vehicle speed “v” is stored in advance in the memory of the ECU60.

As will be understood from the above equation (12), the expected value L of the amount of loss of the regenerated electric power is calculated by cumulatively adding the values obtained by multiplying the probabilities Pvkbcorresponding to the brake pressures “b” with the values calculated by the function “g” using the brake pressures “b”. The number of brake pressures “b” which are cumulatively added becomes the number of classes of brake pressure at the probability distribution of the brake pressure. Further, as the value of the brake pressure “b”, the average value of each class is used. Note that, the brake pressure “b” may be a continuous value.

<Processing for Setting Vehicle Speed>

FIG. 11is a flow chart showing the control routine of processing for setting the vehicle speed in the fifth embodiment of the present invention. The present control routine is repeatedly performed by the ECU60.

First, at step S401, the vehicle control part61detects the current driving section of the vehicle1based on the output of the GI′S receiver52and the map information of the map database53. Next, at step S402, the vehicle control part61acquires the vehicle speed detected by the vehicle speed sensor56.

Next, at step S403, the vehicle control part61acquires the probability distribution of the brake pressure with respect to the current driving section and vehicle speed. Next, at step S404, the vehicle control part61uses the probability distribution of brake pressure with respect to the current driving section and vehicle speed to calculate the expected value of the amount of loss of the regenerated electric power.

Next, at step S405, the vehicle control part61judges whether the expected value of the amount of loss of the regenerated electric power is larger than a threshold value. The threshold value is determined in advance. If it is judged that the expected value of the amount of loss of the regenerated electric power is equal to or less than the threshold value, the present control routine ends. On the other hand, if it is judged that the expected value of the amount of loss of the regenerated electric power is larger than the threshold value, the present control routine proceeds to step S406.

At step S406, the vehicle control part61lowers the target value of the vehicle speed, Specifically, the vehicle control part61notifies the target value of the vehicle speed to the driver through the navigation system54or other HMI. Note that, if acceleration and braking are automated in the vehicle1, the vehicle control part61controls the various actuators so that the vehicle speed approaches the target value. After step S406, the present control routine ends.

Note that, the probability distribution of the vehicle speed for the driving section may be used for calculating the expected value of the amount of loss of the regenerated electric power. In this case, the vehicle control part61acquires the probability distribution of the vehicle speed for the current driving section at step S402and acquires the probability distribution of the brake pressure for the current driving section and vehicle speeds at step S403.

Note that, in the fifth embodiment, the charging port22and charger24may be omitted from the vehicle1and the battery20does not have to be charged by the external power supply70. That is, the vehicle1need not be a plug-in hybrid vehicle. Further, the vehicle1may be provided with only a motor (first motor-generator12, second motor-generator16, etc.) as a power source able to output power for driving. That is, the vehicle1may be an electric vehicle (EV).

Sixth Embodiment

The control device of the vehicle according to a sixth embodiment is basically similar in configuration and control to the control device of the vehicle according to the first embodiment except for the points explained below. For this reason, below, the sixth embodiment of the present invention will be explained focusing on the parts different from the first embodiment.

FIG. 12is a view schematically showing the configuration of a vehicle in which the control device of the vehicle according to the sixth embodiment of the present invention is used. The vehicle1′ is provided with an air-conditioner40(below, referred to as an “AC”).

At the time of operation of the AC40, electric power is supplied from the battery20through the PCU18to the AC40. For this reason, at the time of operation of the AC40, the electric power of the battery20is consumed by the AC40. To maintain the inside of the vehicle at a comfortable temperature by the AC40, it is necessary to store the required amount of electric power corresponding to the AC load in the battery20. However, if the amount of stored power of the battery20is maintained at an excessive value, the amount of electric power able to be consumed in the EV mode becomes smaller and the fuel efficiency of the vehicle1deteriorates.

Further, the AC load is correlated with the outside air temperature and the outside air humidity. Therefore, in the sixth embodiment, the vehicle control part61uses the probability distribution of the combination of the outside air temperature and the outside air humidity with respect to the date and time to calculate the expected value of the consumed electric power of the AC40in a predetermined time period in the future (below, referred to as the “future consumed electric power of the AC40”). Further, the vehicle control part61controls the SOC of the battery20based on the expected value of the future consumed electric power of the AC40. Specifically, the vehicle control part61controls the SOC of the battery20so that the amount of stored power of the battery20becomes equal to or more than the expected value of the future consumed electric power of the AC40. By doing this, the temperature inside the vehicle can be kept from fluctuating due to insufficient electric power.

Specifically, the vehicle control part61uses the following equation (13) to calculate the expected value CP of the future consumed electric power of the AC40:

The following equation (14) is a part of the right side of the above equation (13) and corresponds to the expected value CPtof the consumed electric power of the AC40at the date and time “1”.

Here, “h” is a function for calculating the AC load based on the outside air temperature and the outside air humidity and has the outside air temperature T and the outside air humidity “a.” as variables. PtTais the probability of the outside air temperature becoming T and the outside air humidity becoming “a” at the date and time “t” and is acquired from the probability distribution of the combination of the outside air temperature T and the outside air humidity “a” at the date and time “t”. The probability distribution of the combination of the outside air temperature T and the outside air humidity “a” at the date and time “t” is stored in advance in the memory of the ECU60.

As will be understood from the above equation (14), the expected value CPtof the consumed electric power of the AC40at the date and time “t” can calculated by cumulatively adding the values obtained by multiplying the probabilities PtTacorresponding to the combinations of the outside air temperature T and the outside air humidity “a” with the values calculated by the function “h” using the combinations. The number of the combinations of the outside air temperatures T and the outside air humidities “a” which are cumulatively added becomes the number of combinations in the probability distribution of the combinations of the outside air temperature and the outside air humidity.

Therefore, as will be understood from the above equation (13), the vehicle control part61cumulatively adds the expected values CPtof the consumed electric power of the AC40at different dates and times “t” over a predetermined time period to thereby calculate the expected value CP of the future consumed electric power of the AC40. In the above equation (13), the date and time t1is the date and time a predetermined time after the current date and time, while the date and time t2is the date and time a predetermined time after the date and time t1. The time period from the date and time t1to the date and time t2corresponds to a future predetermined time period.

FIG. 13is a flow chart showing the control routine of SOC control in the sixth embodiment of the present invention. The present control routine is repeatedly performed by the ECU60.

First, at step S501, the vehicle control part61detects the current date and time based on the output of a digital clock built in the ECU60or the information received from outside the vehicle1through a vehicle-mounted communicating device. Next, at step S502, the vehicle control part61calculates the date and time t1and the date and time12from the current date and time and acquires the probability distribution of the combination of the outside air temperature and the outside air humidity with respect to the date and time t1and the date and time t2. Next, at step S503, the vehicle control part61uses the probability distribution of the combination of the outside air temperature and outside air humidity with respect to the date and time t1and the date and time t2to calculate the expected value of the future consumed electric power of the AC40.

Next, at step S504, the vehicle control part61controls the SOC of the battery20so that the amount of stored power of the battery20becomes equal to or more than the expected value of the future consumed electric power of the AC40. For example, the vehicle control part61sets the target SOC of the battery20to the value of the SOC of the battery20corresponding to the expected value of the future consumed electric power of the AC40. The target SOC is, for example, realized by control of the driving mode of the vehicle1. After step S504, the present control routine ends.

Note that, the function “h” for calculating the AC load may have only the outside air temperature T as a variable. That is, the vehicle control part61may use the probability distribution of the outside air temperature for the date and time to calculate the expected value of the future consumed electric power of the AC40. In this case, at step S502, the vehicle control part61acquires the probability distribution of the outside air temperature for the date and time t1to the date and time t2.

Seventh Embodiment

The control device of the vehicle according to a seventh embodiment is basically similar in configuration and control to the control device of the vehicle according to the first embodiment except for the points explained below. For this reason, below, the seventh embodiment of the present invention will be explained focusing on the parts different from the first embodiment.

In the seventh embodiment, in the same way as the sixth embodiment, as shown inFIG. 12, the vehicle is provided with an AC40. The AC40has a heating function. However, if in particular the AC40is a heat pump, at the time of cold weather, less heat is taken in from the atmosphere, so the heating ability of the AC40falls. For this reason, at the time of cold weather, the waste heat of the internal combustion engine10has to be used to heat the inside of the passenger compartment. However, if frequently operating the internal combustion engine10in preparation for a drop in the outside air temperature, the fuel efficiency of the vehicle1deteriorates.

Therefore, in the seventh embodiment, the vehicle control part61calculates the expected value of the amount of fuel consumption for warmup in a future predetermined time period using the probability distribution of the outside air temperature with respect to the date and time (below, referred to as the “future amount of fuel consumption”). Further, the vehicle control part61selects the driving mode of the vehicle1based on the expected value of the future amount of fuel consumption. Specifically, the vehicle control part61selects the HV mode as the current driving mode of the vehicle1if the expected value of the future amount of fuel consumption is larger than the threshold value. By doing this, it is possible to keep the fuel efficiency of the vehicle1from deteriorating while keeping the temperature in the passenger compartment from fluctuating.

Specifically, the vehicle control part61uses the following equation (15) to calculate the expected value of the future amount of fuel consumption FF:

The following equation (16) is a part of the right side of the above equation (15) and corresponds to the expected value FFtof the amount of fuel consumption for warmup at the date and time “t”:

Here, “i” is a function for calculating the amount of fuel consumption for warmup based on the outside air temperature and has the outside air temperature T as a variable. The function “i” is set to become zero when the outside air temperature T is equal to or more than a predetermined value and to become larger the lower the outside air temperature T. PtTis the probability of the outside air temperature becoming T at the date and time “t” and is acquired from the probability distribution of the outside air temperature T with respect to the date and time “t”. The probability distribution of the outside air temperature T with respect to the date and time “t” is stored in advance in the memory of the ECU60.

As will be understood from the above equation (16), the expected value FFtof the amount of fuel consumption for warmup at the date and time “t” is calculated by cumulatively adding the values obtained by multiplying the probabilities PtTcorresponding to the outside air temperatures T with the values calculated by the function “i” using the different outside air temperatures T. The number of the outside air temperatures T which are cumulatively added becomes the number of classes of temperature of the probability distribution of the outside air temperature. Further, as the value of the outside air temperature T, the average value of each temperature class is used. Note that, the outside air temperature T may be a continuous value.

Therefore, as will be understood from the above equation (15), the vehicle control part61cumulatively adds the expected value FFtof the amount of fuel consumption for warmup at the different dates and times “t” over a predetermined time period to calculate the expected value of the future amount of fuel consumption FF. In the above equation (15), the date and time t1is a date and time a predetermined time after the current date and time, while the date and time t2is a date and time a predetermined time after the date and time t1. The time period from the date and time t1to the date and time t2corresponds to the predetermined time period in the future.

<Processing for Selecting Driving Mode>

FIG. 14is a flow chart showing the control routine of processing for selection of the driving mode in a seventh embodiment of the present invention. The present control routine is repeatedly performed by the ECU60.

First, at step S601, the vehicle control part61detects the current date and time based on the output of a digital clock built in the ECU60or the information received from outside the vehicle1through a vehicle-mounted communicating device. Next, at step S602, the vehicle control part61calculates the date and time t1and the date and time t2from the current date and time and acquires the probability distribution of the outside air temperature with respect to the date and time t1to the date and time t2. Next, at step S603, the vehicle control part61uses the probability distribution of the outside air temperature with respect to the date and time t1to the date and time t2to calculate the expected value of the future amount of fuel consumption.

Next, at step S604, the vehicle control part61judges whether the expected value of the future amount of fuel consumption is larger than the threshold value. The threshold value is determined in advance. If it is judged that the expected value of the future amount of fuel consumption is equal to or less than the threshold value, the present control routine ends. On the other hand, if it is judged that the expected value of the future amount of fuel consumption is larger than the threshold value, the present control routine proceeds to step S605.

At step S605, the vehicle control part61selects the mode as the current driving mode of the vehicle1. Specifically, the vehicle control part61operates the internal combustion engine10. After step S605, the present control routine ends.

Eighth Embodiment

The control device of the vehicle according to an eighth embodiment is basically similar in configuration and control to the control device of the vehicle according to the first embodiment except for the points explained below. For this reason, below, the eighth embodiment of the present invention will be explained focusing on the parts different from the first embodiment.

As explained above, in the vehicle1, it is possible to charge the battery20by the external power supply70. For this reason, by rendering the battery20a fully charged state before departure, it is possible to extend the driving distance in the EV mode and in turn possible to improve the fuel efficiency of the vehicle1. However, if the battery20is maintained in a fully charged state, deterioration of the battery20progresses. For this reason, to suppress deterioration of the battery20while improving the fuel efficiency of the vehicle1, it is necessary to start charging the battery20at a suitable timing before departure.

Therefore, at the eighth embodiment, the vehicle control part61sets the charging start time of the battery20based on the expected value of the amount of stored power by the battery20at the time of departure and the expected value of the amount of electric power consumption of the battery20from departure to recharging (below, referred to as the “predicted amount of electric power consumption”). Specifically, the vehicle control part61sets the charging start time of the battery so that the expected value of the amount of stored power of the battery20at the time of departure becomes equal to or more than an expected value of the predicted amount of electric power consumption. By doing this, it is possible to keep the electric power for driving from becoming insufficient while reducing the time at which the battery20is maintained at the fully charged state. As a result, it is possible to suppress deterioration of the battery20while improving the fuel efficiency of the vehicle1.

The vehicle control part61uses the probability distribution of the time of departure with respect to the time of arrival at the charging point to calculate the expected value of the amount of stored power of the battery20at the time of departure. Specifically, the vehicle control part61uses the following equation (17) to calculate the expected value BC of the amount of stored power of the battery20at the time of departure:

Here, C is the amount of stored power of the battery20before starting charging. The second term at the right side of the above equation (17) shows the expected value of the amount of stored power stored in the battery20due to charging. A is the amount of stored power per unit time and is determined in advance. “y” is the time of departure, while “s” is the charging start time. Note that, the time of departure “y” and the charging start time “s” are expressed as the difference from the time of arrival at the charging point. Ppy, is the probability of the time of departure becoming “y” at the time of arrival “p” at the charging point and is acquired from the probability distribution of the time of departure with respect to time of arrival “p” at the charging point. The probability distribution of the time of departure with respect to time of arrival “p” at the charging point is stored in advance in the memory of the ECU60.

The expected value BC of the amount of stored power of the battery20at the time of departure is calculated by adding the expected value of the amount of stored power stored in the battery20by charging to the amount of stored power of the battery20before start of charging. The expected value of the amount of stored power stored in the battery20by charging is calculated by multiplying the amount of stored power A per unit time with the expected value of the charging time. The expected value of the charging time is calculated by subtracting the charging start time from the expected value of the time of departure.

Further, the probability distribution of the time of departure with respect to the time of arrival at the charging point and the probability distribution of the predicted amount of electric power consumption with respect to the time of departure are used to calculate the expected value of the predicted amount of electric power consumption. Specifically, the vehicle control part61uses the following equation (18) to calculate the expected value EC of the predicted amount of electric power consumption.

Here, Ppyis the probability of the time of departure becoming “y” at the time of arrival “p” at the charging point and is acquired from the probability distribution of the time of departure with respect to the time of arrival “p” at the charging point time. The probability distribution of the time of departure with respect to the time of arrival “p” at the charging point time is stored in advance in the memory of the ECU60.

The following equation (19) is a part of the right side of the above equation (18) and corresponds to the expected value ECyof the predicted amount of electric power consumption with respect to the time of departure “y”.

Here, Pycis the probability of the predicted amount of electric power consumption becoming “c” at the time of departure “y” and is acquired from the probability distribution of the predicted amount of electric power consumption with respect to the time of departure “y”. The probability distribution of the predicted amount of electric power consumption with respect to the time of departure “y” is stored in advance in the memory of the ECU60.

As will be understood from the above equation (19), the expected value ECyof the predicted amount of electric power consumption for the time of departure “y” is calculated by cumulatively adding the values obtained by multiplying the probabilities Pyccorresponding to the predicted amounts of electric power consumption “c” with the predicted amounts of electric power consumption “c”. The number of the predicted amounts of electric power consumption “c” which are cumulatively added becomes the number of classes of the predicted amount of electric power consumption in the probability distribution of the predicted amount of electric power consumption. Further, as the value of the predicted amount of electric power consumption “c”, the average value of each class is used. Note that, the predicted amount of electric power consumption “c” may be a continuous value.

Therefore, as will be understood from the above equation (18), the vehicle control part61cumulatively adds the values obtained by multiplying the probability Ppycorresponding to the different times of departure “y” with the expected values ECyof the predicted amount of electric power consumption for the different times of departure “y” to calculate the expected value EC of the predicted amount of electric power consumption,

<Processing for Setting Charging Start Time>

FIG. 15is a flow chart showing the control routine of processing for setting the charging start time in an eighth embodiment of the present invention. The present control routine is repeatedly performed by the ECU60.

First, at step S701, the vehicle control part61judges whether the vehicle1has reached a charging point based on the output of the GPS receiver52and the map information of the map database53. The charging point is, for example, the home, a parking lot at which an external power supply70is provided, a charging station, etc. The charging points are recorded in advance in the map database53. For example, the charging points are successively recorded in accordance with entry by the driver or state of utilization of an external power supply70of a charging point.

Next, at step S702, the vehicle control part61detects the current time, that is, the time of arrival at the charging point based on output of a digital clock built in the ECU60or the information received from outside the vehicle1through a vehicle-mounted communicating device. Next, at step S703, the vehicle control part61acquires the probability distribution of the time of departure with respect to the time of arrival at the charging point.

Next, at step S704, the vehicle control part61uses the probability distribution of the time of departure with respect to the time of arrival at a charging point and the probability distribution of the predicted amount of electric power consumption with respect to the time of departure to calculate the expected value of the predicted amount of the electric power consumption. Next, at step S705, the vehicle control part61uses the probability distribution of the time of departure with respect to the time of arrival at the charging point to calculate the expected value of the amount of stored power of the battery20at the time of departure and sets the charging start time so that this expected value becomes equal to or more than an expected value of the predicted amount of electric power consumption.

Next, at step S706, the vehicle control part61notifies the driver of the charging start time through the navigation system54or another HMI. Note that, at step S706, the vehicle control part61may control the charger24etc., so that the battery20starts being charged at the charging start time. After step S706, the present control routine ends.

Other Embodiments

Above, preferred embodiments according to the present invention were explained, but the present invention is not limited to these embodiments and can be corrected and changed in various ways within the language of the claims.

For example, the predetermined parameters for which the probability distribution is generated is not limited to the vehicle speed, brake pressure, outside air temperature, outside air humidity, time of departure, and amount of electric power consumption of the battery. The predetermined parameter may be the demanded torque, relative speed with a preceding vehicle, relative distance with a preceding vehicle, AC load, acceleration of the vehicle, number of passengers, etc.

Further, in the above embodiments, the probability distribution of a predetermined parameter for a predetermined condition is used to calculate an expected value of an evaluation value, but the predetermined condition is not limited to a driving section, vehicle speed, date and time, time of arrival at a charging point, and time of departure. The predetermined condition may be the direction of advance of the vehicle, type of road (highway, toll road, bypass road, general road, private road, school road, one-way road, etc.), hours, season, weekends and holidays/weekdays, driver, gender of driver, age of driver, presence of any passengers, number of passengers, vehicle model, output of the power train (internal combustion engine, motor, battery, etc.), remaining amount of electric power of battery, weather, presence of sunlight, presence of a preceding vehicle, presence of a traffic light, presence of any railroad crossing, presence of a stop sign, etc.

The direction of advance of the vehicle, type of road, presence of a traffic light, presence of a railroad crossing, and presence of a stop sign are detected, for example, based on the output of a GPS receiver and map information of a map database. The hours, season, weekends and holidays/weekdays, for example, are detected by a digital clock built in the ECU or detected by receiving information from outside of the vehicle through a vehicle-mounted communicating device.

The driver, for example, is detected by the technique of learning of the seat position, voice recognition, image recognition using a camera (drive recorder, driver monitor camera, etc.), acquisition of an identifying number (MAC address etc.) of a mobile device (smart phone, tablet, etc.), learning of a past pattern of behavior, etc. The gender and age of the driver are detected by image recognition etc., or stored in advance in the ECU for each driver. The presence of any passengers and the number of passengers are, for example, detected by the above-mentioned method of detection of a driver or detected using a weight sensor detecting the weight of the load on each seat of the vehicle.

The vehicle model is stored in advance in the memory of the ECU. The output of the power train is detected from the command values etc., from the ECU. The remaining amount of electric power of the battery is detected based on the output of the voltage sensor etc. The weather and presence of any sunlight are detected based on outputs of a rain sensor, luminance sensor, etc., provided at the vehicle or detected by receiving information from outside of the vehicle through a vehicle-mounted communicating device. The presence of any vehicle in front is detected using a camera, radar, Lidar, etc., provided at the vehicle.

Further, the evaluation value for which the expected value is calculated using the probability distribution is not limited to the amount of electric power consumption, the amount of fuel consumption, the time of arrival at the destination, the amount of loss of regenerated electric power, the future consumed electric power of the AC, the future amount of fuel consumption, the amount of stored power of the battery20at the time of departure, and the predicted amount of electric power consumption. The evaluation value may be the concentration of a toxic substance discharged from the vehicle (CO, HC, NOx, PM, etc.), the temperature in the vehicle, vibration of the vehicle, front-back G, a parameter showing safety (number of times of sudden braking etc.), a parameter showing drivability (response to accelerator operation, response to steering operation, response to brake operation, number of times of behavior unrelated to operation, etc.), etc.

Further, the above embodiments can be freely combined. For example, the second embodiment or third embodiment can be combined with the fourth embodiment, fifth embodiment, sixth embodiment, seventh embodiment, or eighth embodiment.

If the second embodiment or third embodiment is combined with the fourth embodiment, the driving data acquiring device55, for example, includes a vehicle speed sensor detecting a vehicle speed and acquires the vehicle speed as driving data while the vehicle1is being driven. The driving section when a vehicle speed is acquired by the driving data acquiring device55is detected based on the output of the GPS receiver52and the map information of the map database53.

If the second embodiment or third embodiment is combined with the fifth embodiment, the driving data acquiring device55, for example, includes a brake pressure sensor detecting a brake pressure and acquires the brake pressure as driving data while the vehicle1is being driven. The driving section when a brake pressure is acquired by the driving data acquiring device55is detected based on the output of the GPS receiver52and the map information of the map database53. Further, the vehicle speed when a brake pressure is acquired by the driving data acquiring device55is detected by the vehicle speed sensor56.

If the second embodiment or third embodiment is combined with the sixth embodiment, the driving data acquiring device55, for example, includes a temperature sensor detecting an outside air temperature and a humidity sensor detecting an outside air humidity and acquires the outside air temperature and the outside air humidity as driving data while the vehicle1is being driven. Note that, the driving data acquiring device55may receive information from outside of the vehicle through a vehicle-mounted communicating device to detect the outside air temperature and the outside air humidity. The date and time when the outside air temperature and the outside air humidity are acquired by the driving data acquiring device55are detected by a digital clock built in the ECU or detected by receiving information from outside the vehicle through a vehicle-mounted communicating device.

If the second embodiment or third embodiment is combined with the seventh embodiment, the driving data acquiring device55, for example, includes a temperature sensor detecting an outside air temperature and acquires the outside air temperature during driving of the vehicle1as the driving data. Note that, the driving data acquiring device55may receive information from outside the vehicle through the vehicle-mounted communicating device to detect the outside air temperature. The date and time when the outside air temperature is acquired by the driving data acquiring device55are detected by a digital clock built in the ECU or detected by receiving information from outside of the vehicle through a vehicle-mounted communicating device.

If the second embodiment or third embodiment is combined with the eighth embodiment, the driving data acquiring device55includes a voltage sensor51etc., and acquires the time of departure and predicted amount of electric power consumption as the driving data. The time of arrival at the charging point when the time of departure is acquired by the driving data acquiring device55and the time of departure when the predicted amount of electric power consumption is acquired by the driving data acquiring device55are detected by a digital clock built in the ECU or detected by receiving information from outside of the vehicle through a vehicle-mounted communicating device.

REFERENCE SIGNS LIST

1,1′. vehicle55. driving data acquiring device60. electronic control unit (ECU)61. vehicle control part62. probability distribution generating part