Information processing method and information processing device

Abstract

When it is predicted that an engine drive request will occur before a hybrid vehicle arrives at a destination, an information processing device according to an embodiment of the present invention: drives an engine with output power smaller than an average travel load, which is an average value of travel loads to the destination, at a timing earlier than a travel start timing in an EV mode executed at a time when it is predicted that the engine drive request will not occur; and starts execution of processing for reducing an SOC of a battery such that the SOC reaches a target SOC.

Description

Information processing method and information processing device

[0001] The present invention relates to an information processing method and an information processing device.

[0002] Conventionally, there has been known a method for managing the state of charge (SOC) of a battery in a hybrid electric vehicle (hereinafter sometimes abbreviated as "HEV (Hybrid Electric Vehicle)") equipped with an engine and a motor generator. For example, Patent Document 1 listed below discloses a control device for an HEV that, when it is estimated that there will be a request to use the heater during the next trip, sets a target SOC value for the current trip at the time of arrival at the destination to a value smaller than a normal target value, which is a normal SOC target value.

[0003] JP 2015-223859 A

[0004] However, in the above-described conventional technology, for example, when the vehicle is driven using only the motor generator as a drive source to reduce the SOC, there is a possibility that sufficient heating capacity cannot be obtained for heating using engine coolant. The above-described conventional technology has a problem in that it may be impossible to appropriately adjust a request to drive the engine (engine drive request) for heating the vehicle interior, etc., and a request to reduce the SOC (SOC reduction request) so that the SOC will reach a target value upon arrival at the destination.

[0005] In one aspect, the present invention has been made in consideration of the above circumstances, and its purpose is to provide an information processing method and information processing device that can appropriately adjust engine drive requests and SOC reduction requests in an HEV.

[0006] In order to solve the above-described problems, an information processing method according to one aspect of the present invention is a hybrid vehicle including an engine, a power generation motor generator driven by the engine to generate electricity, a traction motor generator, and a battery that is charged with electricity generated by the power generation motor generator and supplies electricity to the traction motor generator, the method comprising the steps of: a processor predicting whether or not an engine drive request that is a request to drive the engine will occur before the hybrid vehicle arrives at the destination, using average road load information that can identify an average road load that is an average value of the road load of the hybrid vehicle up to the destination of the hybrid vehicle; and a step of reducing the SOC of the battery so that the SOC at the time of arrival at the destination will become a target SOC, the hybrid vehicle being in a first driving mode in which the engine is stopped and the traction motor generator is driven by electric power supplied from the battery, or a second driving mode in which the output power of the engine is greater than 0 and less than the average road load. and a step of reducing the SOC by running the hybrid vehicle in a second running mode in which the traction motor generator is driven by electric power supplied from the battery while controlling operation of the engine so that the SOC is reduced. When the processor predicts in the predicting step that the engine drive request will not be generated by the time the vehicle arrives at the destination, the processor runs the hybrid vehicle in the first running mode in the SOC reducing step, and when the processor predicts in the predicting step that the engine drive request will be generated by the time the vehicle arrives at the destination, the processor runs the hybrid vehicle in the second running mode in the SOC reducing step, and when the processor predicts that the engine drive request will be generated by the time the vehicle arrives at the destination, the processor starts reducing the SOC by running the hybrid vehicle in the second running mode at an earlier timing than the timing at which the SOC would be reduced by running the hybrid vehicle in the first running mode if it was predicted that the engine drive request would not be generated.

[0007] According to the present invention, it is possible to provide an information processing method and an information processing device that can appropriately adjust an engine drive request and an SOC reduction request in an HEV.

[0008] 1 is a block diagram showing a schematic configuration of a vehicle equipped with an information processing device according to an embodiment; FIG. 2 is a schematic diagram showing an example of a hardware configuration of an information processing device according to an embodiment; FIG. 3 is a schematic diagram showing an example of a software configuration of an information processing device according to an embodiment; FIG. 4 is a diagram showing an example of a method by which an information processing device according to an embodiment calculates an adjusted start timing; and FIG. 5 is a diagram showing an outline of a processing procedure of an information processing device according to an embodiment.

[0009] An embodiment according to one aspect of the present invention (hereinafter also referred to as "the present embodiment") will be described below with reference to the drawings. However, the present embodiment described below is merely an example of the present invention in all respects. Needless to say, various improvements and modifications can be made without departing from the scope of the present invention. In other words, when implementing the present invention, specific configurations according to the embodiment may be appropriately adopted. Note that, although data appearing in the present embodiment are described in natural language, more specifically, they are specified using pseudo-language, commands, parameters, machine language, etc. that can be recognized by a computer.

[0010] §1 Application Example FIG. 1 is a block diagram showing a schematic configuration of a vehicle VH equipped with an information processing device (information processing device 1) according to this embodiment. The vehicle VH is an example of a "hybrid vehicle" of the present invention. The vehicle VH includes the information processing device 1, an engine 21, a first motor-generator 22, a second motor-generator 23, a first inverter 24, a second inverter 25, a battery 26, a differential mechanism 27, and drive wheels 28. Hereinafter, the "motor-generator" will be referred to as "MG" and the "inverter" will be referred to as "INV."

[0011] The engine 21 is an internal combustion engine and is connected to the first MG 22, for example, via a reduction gear mechanism (not shown). The first MG 22 is an example of a "power generating motor generator" of the present invention and is driven by the engine 21 to generate electricity. The second MG 23 is an example of a "traveling motor generator" of the present invention and is connected to drive wheels 28, for example, via a differential mechanism 27. The second MG 23 drives the vehicle VH and also generates electricity regeneratively during deceleration.

[0012] The first MG 22 and the second MG 23, together with the first INV 24, the second INV 25, and the battery 26, form a high-voltage voltage circuit 29. The first INV 24 is used to control the first MG 22, and the second INV 25 is used to control the second MG 23. The first INV 24 and the second INV 25 each generate three-phase AC based on commands from the information processing device 1 and apply the generated three-phase AC to the corresponding MG of the first MG 22 or the second MG 23. The first INV 24 and the second INV 25 may be integrated. The battery 26 is an example of a "battery" in the present invention and constitutes a power source for the second MG 23, supplying power to the second MG 23. The battery 26 is charged by power generated by the first MG 22 and power regenerated by the second MG 23.

[0013] The information processing device 1 performs integrated control of the engine 21, the first INV 24, the second INV 25, etc. The information processing device 1 receives map information and the like from a navigation system 31 (abbreviated as "navigation system" in FIG. 1 ). The information processing device 1 also receives various signals indicating detection results from various sensors 32. The various sensors 32 include, for example, an SOC sensor for detecting the state of charge (SOC) of the battery 26 and a coolant temperature sensor for detecting the temperature of the coolant (engine water temperature) of the engine 21. The various sensors 32 also include, for example, an interior thermometer for detecting the temperature inside the vehicle VH and an outside air temperature sensor for detecting the temperature outside the vehicle (the outside air temperature around the vehicle VH). These signals and information input to the information processing device 1 are used for the control performed by the information processing device 1.

[0014] The information processing device 1 has two driving modes for the vehicle VH: an EV mode and a series hybrid mode (hereinafter referred to as an HEV mode). The EV mode is an example of a "first driving mode" in the present invention, and is a mode in which the engine 21 is stopped, the second MG 23 is driven by electric power supplied from the battery 26, and the vehicle travels using only the driving force of the second MG 23. The HEV mode is a mode in which the engine 21 is driven and the second MG 23 is driven while the first MG 22 generates electricity.

[0015] In this embodiment, the HEV mode, in which the engine 21 is controlled to output a determined output power DOP and the second MG 23 is driven while the first MG 22 generates electricity, is specifically referred to as a "specific HEV mode." The specific HEV mode is an example of a "second driving mode" in the present invention. The determined output power DOP is greater than 0 and less than an average running load ARL, which is an average value of the running load of the vehicle VH up to the destination DN of the vehicle VH. The determined output power DOP may be determined so that the torque and rotation speed that achieve the determined output power DOP are not included in a predefined avoidance area on a two-dimensional map of torque and rotation speed. Such avoidance areas include, for example, a "region where noise and vibration worsen due to low rotation speed and high torque," a "region where noise occurs due to excessively high rotation speed," and a "region where the efficiency of the output power of the engine 21 (e.g., fuel economy) deteriorates excessively." These avoidance areas are predefined in a two-dimensional map determined from the torque and rotation speed of the engine 21. In the specific HEV mode, the driving of the engine 21 is controlled so that the output power of the engine 21 becomes the determined output power DOP.

[0016] As described above, the vehicle VH according to this embodiment is a series hybrid vehicle in which the engine 21 is used exclusively to drive the first MG 22 and the drive wheels 28 are driven exclusively by the second MG 23. However, the vehicle VH may also be a parallel hybrid vehicle in which the engine 21 is also used to drive the drive wheels 28. When the vehicle VH is a parallel hybrid vehicle, the engine 21 stops in EV mode and operates in HEV mode, just as in the case of a series hybrid vehicle. Regardless of whether the vehicle VH is a series hybrid vehicle or a parallel hybrid vehicle, from the standpoint of charging and discharging, hybrid vehicles generally run while charging when the engine output power is greater than the running load, and run while discharging when the engine output power is not greater. Therefore, by controlling the driving of the engine 21 to achieve a determined output power DOP that is smaller than the average running load ARL and running the vehicle VH to the destination DN, the information processing device 1 can reduce the SOC of the battery 26. In other words, by driving the vehicle VH to the destination DN in a specific HEV mode, the information processing device 1 can reduce the SOC of the battery 26 so that the SOC of the battery 26 at the arrival time TA at the destination DN becomes the target SOC.

[0017] The information processing device 1 predicts whether an engine drive request EDR, which is a request to drive the engine 21, will occur before the vehicle VH arrives at the destination DN. For example, the information processing device 1 predicts whether an engine drive request EDR will occur before the vehicle VH arrives at the destination DN using (predictable) average driving load information IAL that can identify an average driving load ARL, which is an average value of the driving load of the vehicle VH up to the destination DN. If the information processing device 1 predicts that an engine drive request EDR will not occur before the vehicle VH arrives at the destination DN, the information processing device 1 causes the vehicle VH to travel in EV mode, thereby reducing the SOC of the battery 26 so that the SOC of the battery 26 at the arrival time TA at the destination DN becomes the target SOC. In particular, the information processing device 1 starts traveling in EV mode at the standard start timing RT, thereby reducing the SOC of the battery 26 so that the SOC of the battery 26 at the arrival time TA becomes the target SOC. When it is predicted that an engine drive request EDR will be generated before arrival at the destination DN, the information processing device 1 causes the vehicle VH to travel in a specific HEV mode, thereby reducing the SOC of the battery 26 so that the SOC of the battery 26 at the arrival time TA becomes the target SOC. In particular, the information processing device 1 causes the vehicle VH to start traveling in the specific HEV mode at an adjusted start timing AT earlier than the standard start timing RT, thereby reducing the SOC of the battery 26 so that the SOC of the battery 26 at the arrival time TA becomes the target SOC.

[0018] That is, if the information processing device 1 predicts that the engine drive request EDR will not be generated by the time the vehicle arrives at the destination DN, the information processing device 1 starts driving in the EV mode at the standard start timing RT. On the other hand, if the information processing device 1 predicts that the engine drive request EDR will be generated by the time the vehicle arrives at the destination DN, the information processing device 1 starts driving in the specific HEV mode at the adjusted start timing AT, which is earlier than the standard start timing RT. Since the determined output power DOP is smaller than the average driving load ARL, the information processing device 1 can reduce the SOC of the battery 26 by driving in the specific HEV mode, and in particular, can reduce the SOC so that the SOC at the arrival time TA becomes the target SOC. Furthermore, since the determined output power DOP is greater than 0, the information processing device 1 can satisfy the engine drive request EDR by driving in the specific HEV mode. The information processing device 1, for example, drives the engine 21 to achieve the determined output power DOP, thereby raising the water temperature (engine water temperature) of the engine 21's coolant, and can use this coolant to heat the interior of the vehicle VH.

[0019] However, because the engine 21 is driven when traveling in the specific HEV mode, the rate of decrease in the SOC of the battery 26 is slower than when traveling in the EV mode, in which the engine 21 is stopped, the second MG 23 is driven by power supplied from the battery 26, and the vehicle travels solely on the driving force of the second MG 23. Therefore, if the information processing device 1 predicts that an engine drive request EDR will be generated before the vehicle arrives at the destination DN, the information processing device 1 advances the timing at which the execution of the process to reduce the SOC is started compared to when the information processing device 1 predicts that an engine drive request EDR will not be generated before the vehicle arrives at the destination DN. When the information processing device 1 predicts that an engine drive request EDR will be generated, the information processing device 1 starts traveling in the specific HEV mode at a timing earlier than the standard start timing RT at which traveling in the EV mode is started when the information processing device 1 predicts that an engine drive request EDR will not be generated. In this embodiment, when the information processing device 1 predicts that an engine drive request EDR will be generated before the vehicle arrives at the destination DN, the information processing device 1 starts traveling in the specific HEV mode at an adjusted start timing AT earlier than the standard start timing RT. Therefore, even when the information processing device 1 predicts that the engine drive request EDR will be generated, the information processing device 1 can reliably reduce the SOC of the battery 26 so that the SOC becomes the target SOC by starting traveling in the specific HEV mode at the post-adjustment start timing AT. That is, the information processing device 1 can appropriately adjust the engine drive request EDR and the "request to reduce the SOC (SOC reduction request) so that the SOC of the battery 26 at the arrival time TA becomes the target SOC" in the vehicle VH. The information processing device 1, which has been outlined above, will be described in detail below with reference to FIGS. 2 to 6.

[0020] §2 Configuration Example [Hardware Configuration] Fig. 2 schematically illustrates an example of the hardware configuration of the information processing device 1 according to this embodiment. As shown in Fig. 2, the information processing device 1 according to this embodiment includes a CPU (Central Processing Unit) 11, a RAM (Random Access Memory) 12, and a non-volatile memory 13. The CPU 11, RAM 12, and non-volatile memory 13 constitute, for example, a microcomputer. In the illustrated example, the non-volatile memory 13 stores an information processing program PG and various basic information BIS.

[0021] The information processing program PG is a program for causing the information processing device 1 to execute information processing (see FIG. 5 and the like) described below for reducing the SOC of the battery 26 so that the SOC of the battery 26 becomes a target SOC at the arrival time TA of the vehicle VH at the destination DN. The information processing program PG includes a series of instructions for the information processing. The CPU 11 executes the information processing program PG read from the non-volatile memory 13 using the RAM 12 as a work area, thereby executing the information processing program PG read from the non-volatile memory 13 and reducing the SOC of the battery 26.

[0022] The various basic information BIS is information related to the specifications, settings, etc. of the vehicle VH, which is used for various determinations and calculations performed by the information processing device 1. For example, the various basic information BIS indicates the "air conditioner set temperature of the vehicle VH" set by the occupants of the vehicle VH, etc. Also, for example, the various basic information BIS indicates the "compartment volume of the vehicle VH," the "engine 21 displacement," etc. However, it is not necessary for the various basic information BIS to indicate all of the "air conditioner set temperature of the vehicle VH," the "compartment volume of the vehicle VH," and the "engine 21 displacement." The various basic information BIS does not have to indicate at least one of the specifications and settings of the vehicle VH described above. Details of the determinations and calculations performed by the information processing device 1 using the "air conditioner set temperature of the vehicle VH," the "compartment volume of the vehicle VH," the "engine 21 displacement," etc. indicated by the various basic information BIS will be described later.

[0023] [Software Configuration] Figure 3 schematically illustrates an example of the software configuration of the information processing device 1 according to this embodiment. The CPU 11 loads the information processing program PG stored in the non-volatile memory 13 into the RAM 12 and interprets and executes instructions included in the loaded information processing program PG, thereby controlling each component. As a result, as shown in Figure 3, the information processing device 1 operates as a computer including, as software modules, a road load information acquisition unit 111, a detection result signal acquisition unit 112, a drive request prediction unit 113, a timing determination unit 114, and an energy management unit 115. That is, in this embodiment, each software module of the information processing device 1 is realized by the CPU 11.

[0024] The road load information acquisition unit 111 acquires average road load information IAL, and acquires, for example, map information from the navigation system 31, which indicates the distance to the destination DN, the road gradient, the statistical average vehicle speed, the speed limit, etc. The average road load information IAL is information that can identify an average road load ARL predicted as an average value of the road load of the vehicle VH up to the destination DN of the vehicle VH. The road load information acquisition unit 111 may acquire, as the average road load information IAL, road load history information that indicates the history of the road load, vehicle speed, etc. of the vehicle VH up to the destination DN, instead of or in addition to the map information.

[0025] The detection result signal acquisition unit 112 acquires various signals indicating the detection results detected by the various sensors 32. For example, the detection result signal acquisition unit 112 acquires a signal indicating the SOC of the battery 26 from an SOC sensor and a signal indicating the engine water temperature of the engine 21 from a coolant temperature sensor. Furthermore, for example, the detection result signal acquisition unit 112 acquires a signal indicating the cabin temperature of the vehicle VH from an interior thermometer and a signal indicating the outside air temperature around the vehicle VH from an outside air temperature sensor.

[0026] The driving demand prediction unit 113 predicts whether an engine driving demand EDR will occur before the vehicle VH arrives at the destination DN. For example, the driving demand prediction unit 113 predicts whether an engine driving demand EDR will occur before the vehicle VH arrives at the destination DN, using the average driving load information IAL acquired by the driving load information acquisition unit 111. As an example, the driving demand prediction unit 113 may predict whether an engine driving demand EDR will occur before the vehicle VH arrives at the destination DN, taking into account a total driving load TRL, which is a total value (sum) of the driving loads up to the destination DN predicted (calculated) from the average driving load ARL, and the (current) SOC of the battery 26. However, the method by which the driving demand prediction unit 113 predicts "whether an engine driving demand EDR will occur before the vehicle VH arrives at the destination DN" is not limited to the example described above. For example, the drive request prediction unit 113 may predict whether an engine drive request EDR will occur before arriving at the destination DN, taking into account at least one of the average driving load information IAL, whether there is a heating request for the interior of the vehicle VH, the interior temperature, the outside air temperature, and the engine water temperature.

[0027] The timing determination unit 114 determines the timing to start execution of a process (SOC reduction process) for "reducing the SOC of the battery 26 to a target SOC by running the vehicle VH in an EV mode or a specific HEV mode." Specifically, when the driving demand prediction unit 113 predicts that "an engine driving demand EDR will not be generated before the vehicle VH arrives at the destination DN," the timing determination unit 114 determines the standard start timing RT as the timing to start execution of the SOC reduction process (first SOC reduction process) for running the vehicle VH in the EV mode. When the driving demand prediction unit 113 predicts that "an engine driving demand EDR will be generated before the vehicle VH arrives at the destination DN," the timing determination unit 114 determines the adjusted start timing AT, which is earlier than the standard start timing RT, as the timing to start execution of the SOC reduction process (second SOC reduction process) for running the vehicle VH in the specific HEV mode. In the example shown in FIG. 3, the timing determination unit 114 includes a standard timing calculation unit 1141 , a drive time calculation unit 1142 , a power generation amount calculation unit 1143 , a total running load calculation unit 1144 , and a timing adjustment unit 1145 .

[0028] The standard timing calculation unit 1141 calculates the standard start timing RT. For example, the standard timing calculation unit 1141 calculates the standard start timing RT by taking into account the (current) SOC and target SOC of the battery 26. The standard timing calculation unit 1141 may calculate the standard start timing RT by taking into account the total running load TRL and the like in addition to these. However, the method by which the standard timing calculation unit 1141 calculates the standard start timing RT is not limited to the example described above. It is sufficient for the standard timing calculation unit 1141 to determine (calculate) when to start running in EV mode (standard start timing RT) so that the SOC of the battery 26 at the arrival time TA becomes the target SOC.

[0029] The drive time calculation unit 1142 predicts an engine drive request period DRP, which is a period during which an engine drive request EDR will occur by the arrival time TA. In particular, the drive time calculation unit 1142 predicts the engine drive request period DRP when the drive request prediction unit 113 predicts that "an engine drive request EDR will occur by the time of arrival at the destination DN." The longer the engine drive request period DRP predicted by the drive time calculation unit 1142, the earlier the information processing device 1 starts execution of the second SOC reduction process (a process of reducing the SOC of the battery 26 by running the vehicle VH in a specific HEV mode so that the SOC of the battery 26 at the arrival time TA becomes a target SOC). In other words, the longer the engine drive request period DRP predicted by the drive time calculation unit 1142, the earlier the timing adjustment unit 1145 sets the adjusted start timing AT relative to the standard start timing RT.

[0030] The longer the engine drive request period DRP during which the engine drive request EDR is generated, the longer the time the engine 21 is driven to satisfy the engine drive request EDR, and the greater the amount of power generated by the first MG 22 due to the engine 21 being driven. To ensure that the SOC of the battery 26 at the arrival time TA is the target SOC, the earlier the SOC reduction process (second SOC reduction process) needs to be started. Therefore, the information processing device 1 determines (calculates) the timing at which to start the second SOC reduction process (adjusted start timing AT) based on the amount of power generated by the first MG 22 due to the engine 21 being driven, i.e., based on the engine drive request period DRP. Specifically, the information processing device 1 advances the timing at which to start the second SOC reduction process (adjusted start timing AT) based on the predicted amount of power generated by the first MG 22 (i.e., the longer the predicted engine drive request period DRP). In other words, the longer the predicted engine drive request period DRP, the earlier the information processing device 1 starts the execution of the second SOC lowering process. With this configuration, even if the engine drive request period DRP is long, the information processing device 1 can lower the SOC of the battery 26 and reliably make the SOC at the arrival time TA the target SOC by starting the execution of the second SOC lowering process at an appropriate timing.

[0031] 4 , the drive time calculation unit 1142 may predict the engine drive request period DRP taking into account the outside air temperature around the vehicle VH. For example, the lower the outside air temperature, the longer the predicted engine drive request period DRP. The lower the outside air temperature, the higher the possibility that an engine drive request EDR, such as a request to warm up the vehicle VH or a request to heat the passenger compartment, will occur. In other words, the predicted engine drive request period DRP is longer. Therefore, the information processing device 1 predicts the engine drive request period DRP to be longer as the outside air temperature is lower. With this configuration, the information processing device 1 can predict the engine drive request period DRP with high accuracy taking into account the outside air temperature around the vehicle VH.

[0032] As illustrated in FIG. 4 , the drive time calculation unit 1142 may predict the engine drive request period DRP taking into account the engine water temperature of the engine 21. For example, the lower the engine water temperature, the longer the predicted engine drive request period DRP. The lower the engine water temperature, the higher the likelihood that a request to warm up the vehicle VH will be generated, i.e., the higher the likelihood that an engine drive request EDR will be generated. Furthermore, the lower the engine water temperature, the greater the need to drive the engine 21 for heating using the engine coolant when a request to heat the vehicle cabin is generated, i.e., the higher the likelihood that an engine drive request EDR will be generated. Therefore, the lower the engine water temperature, the higher the likelihood that an engine drive request EDR will be generated, i.e., the longer the predicted engine drive request period DRP. Therefore, the information processing device 1 predicts the engine drive request period DRP to be longer as the engine water temperature decreases. With this configuration, the information processing device 1 can predict the engine drive request period DRP with high accuracy, taking into account the engine water temperature of the engine 21.

[0033] The drive time calculation unit 1142 may predict the engine drive request period DRP by taking into account the set temperature of the air conditioner of the vehicle VH, instead of or in addition to at least one of the "outside air temperature around the vehicle VH" and the "engine water temperature of the engine 21." For example, the drive time calculation unit 1142 may predict a longer engine drive request period DRP as the set temperature of the air conditioner increases. The higher the set temperature of the air conditioner, the greater the need to drive the engine 21 for heating using the coolant of the engine 21, i.e., the higher the possibility of an engine drive request EDR occurring. Therefore, the higher the set temperature of the air conditioner, the higher the possibility of an engine drive request EDR occurring, i.e., the longer the predicted engine drive request period DRP. Therefore, the information processing device 1 predicts a longer engine drive request period DRP as the set temperature of the air conditioner increases. With this configuration, the information processing device 1 can predict the engine drive request period DRP with high accuracy by taking into account the set temperature of the air conditioner of the vehicle VH.

[0034] The drive time calculation unit 1142 may also predict the engine drive request period DRP taking into account the difference between the set temperature of the air conditioner of the vehicle VH and the interior temperature of the vehicle VH. For example, the drive time calculation unit 1142 may predict a longer engine drive request period DRP as the difference between the set temperature of the air conditioner of the vehicle VH and the interior temperature of the vehicle VH increases. The greater the difference between the set temperature of the air conditioner of the vehicle VH and the interior temperature of the vehicle VH, the greater the need to drive the engine 21 for heating using the coolant of the engine 21, i.e., the higher the possibility of an engine drive request EDR occurring. Therefore, the greater the difference between the set temperature of the air conditioner of the vehicle VH and the interior temperature of the vehicle VH, the higher the possibility of an engine drive request EDR occurring, i.e., the longer the predicted engine drive request period DRP. Therefore, the information processing device 1 predicts a longer engine drive request period DRP as the difference between the set temperature of the air conditioner of the vehicle VH and the interior temperature of the vehicle VH increases. With this configuration, the information processing device 1 can predict the engine drive request period DRP with high accuracy, taking into consideration the difference between the air conditioner temperature setting of the vehicle VH and the cabin temperature of the vehicle VH.

[0035] The drive time calculation unit 1142 may further predict the engine drive request period DRP taking into account the volume of the passenger compartment of the vehicle VH. For example, the larger the volume of the passenger compartment of the vehicle VH, the longer the predicted engine drive request period DRP. The larger the volume of the passenger compartment of the vehicle VH, the greater the need to drive the engine 21 for heating using the engine coolant, i.e., the higher the likelihood of an engine drive request EDR occurring. Therefore, the larger the volume of the passenger compartment of the vehicle VH, the higher the likelihood of an engine drive request EDR occurring, i.e., the longer the predicted engine drive request period DRP. Therefore, the information processing device 1 predicts the longer the predicted engine drive request period DRP taking into account the volume of the passenger compartment of the vehicle VH. With this configuration, the information processing device 1 can predict the engine drive request period DRP with high accuracy, taking into account the volume of the passenger compartment of the vehicle VH.

[0036] The power generation amount calculation unit 1143 predicts the total power amount TEP. The total power amount TEP is the total value (sum) of power generated by the first MG 22 by the arrival time TA by driving the vehicle VH in the specific HEV mode (i.e., by driving the engine 21 while controlling the output power of the engine 21 to be equal to the determined output power DOP). In particular, the power generation amount calculation unit 1143 predicts the total power amount TEP when the drive demand prediction unit 113 predicts that an engine drive demand EDR will be generated before the vehicle arrives at the destination DN. The information processing device 1 starts the second SOC reduction process earlier the greater the total power amount TEP predicted by the power generation amount calculation unit 1143. In other words, the greater the total power amount TEP predicted by the power generation amount calculation unit 1143, the earlier the timing adjustment unit 1145 sets the adjusted start timing AT relative to the standard start timing RT.

[0037] The greater the output power (determined output power DOP) of the engine 21 in the specific HEV mode and the greater the amount of power generated by the first MG 22 (amount of power generated per unit time) due to the driving of the engine 21, the greater the total electric power amount TEP. Therefore, in order to make the SOC of the battery 26 at the arrival time TA the target SOC, the greater the total electric power amount TEP, the earlier the timing at which the SOC reduction process (second SOC reduction process) needs to be started. Therefore, the information processing device 1 determines (calculates) the timing at which the second SOC reduction process is started (adjusted start timing AT) based on the total electric power amount TEP. Specifically, the greater the predicted total electric power amount TEP, the earlier the information processing device 1 starts the second SOC reduction process (adjusted start timing AT), i.e., the earlier the information processing device 1 starts the second SOC reduction process. With this configuration, the information processing device 1 can reduce the SOC of the battery 26 by starting the second SOC reduction process at an appropriate time, even if the total power amount TEP is large, and can reliably make the SOC at the arrival time TA the target SOC.

[0038] As illustrated in FIG. 4 , the power generation amount calculation unit 1143 may predict the total power amount TEP taking into account the output power (determined output power DOP) of the engine 21 in the specific HEV mode. For example, the power generation amount calculation unit 1143 may predict a larger value for the total power amount TEP as the predicted determined output power DOP is larger. As described above, the total power amount TEP increases as the amount of power generated per unit time by the first MG 22 increases, and the amount of power generated per unit time by the first MG 22 increases as the determined output power DOP increases. Therefore, the information processing device 1 predicts a larger value for the total power amount TEP as the output power (determined output power DOP) of the engine 21 in the specific HEV mode increases. With this configuration, the information processing device 1 can predict the total power amount TEP with high accuracy, taking into account the determined output power DOP.

[0039] In the example shown in FIG. 4 , the power generation amount calculation unit 1143 predicts the total electric power amount TEP using the output power (determined output power DOP) of the engine 21 in the specific HEV mode and the engine drive request period DRP predicted (calculated) by the drive time calculation unit 1142. As described above, the engine drive request period DRP is predicted taking into consideration at least one of the outside air temperature around the vehicle VH, the engine water temperature of the engine 21, the set temperature of the air conditioner of the vehicle VH, the difference between the set temperature of the air conditioner of the vehicle VH and the temperature inside the vehicle VH, and the volume of the vehicle VH's cabin. Therefore, the power generation amount calculation unit 1143 may predict the total electric power amount TEP to be a larger value as the outside air temperature around the vehicle VH is lower. The power generation amount calculation unit 1143 may predict the total electric power amount TEP to be a larger value as the engine water temperature of the engine 21 is lower. The power generation amount calculation unit 1143 may predict the total power amount TEP to be a larger value as the set temperature of the air conditioner of the vehicle VH is higher. The power generation amount calculation unit 1143 may predict the total power amount TEP to be a larger value as the "difference between the set temperature of the air conditioner of the vehicle VH and the temperature inside the vehicle cabin of the vehicle VH" is larger. The power generation amount calculation unit 1143 may predict the total power amount TEP to be a larger value as the volume of the passenger compartment of the vehicle VH is larger.

[0040] However, it is not essential that the power generation amount calculation unit 1143 use the determined output power DOP and the engine drive request period DRP to predict the total power amount TEP. The power generation amount calculation unit 1143 may predict the total power amount TEP using the following information instead of or in addition to at least one of the determined output power DOP and the engine drive request period DRP.

[0041] That is, the power generation amount calculation unit 1143 may predict the total electric power amount TEP taking into account the displacement of the engine 21. For example, the predicted total electric power amount TEP may be greater as the displacement of the engine 21 increases. It is considered that the output power (determined output power DOP) of the engine 21 in the specific HEV mode increases as the displacement of the engine 21 increases. Therefore, the information processing device 1 predicts the total electric power amount TEP to be greater as the displacement of the engine 21 increases. With this configuration, the information processing device 1 can predict the total electric power amount TEP with high accuracy taking into account the displacement of the engine 21.

[0042] Furthermore, the power generation amount calculation unit 1143 may predict the total power amount TEP taking into account the distance (from the current position of the vehicle VH) to the destination DN. For example, the longer the distance to the destination DN, the larger the predicted value of the total power amount TEP. For example, the power generation amount calculation unit 1143 may determine the distance from the current position of the vehicle VH to the destination DN using map information (average running load information IAL) obtained from the navigation system 31. It is considered that the longer the distance to the destination DN, the longer the engine drive request period DRP. Therefore, the information processing device 1 predicts the total power amount TEP to be a larger value as the distance to the destination DN increases. With this configuration, the information processing device 1 can predict the total power amount TEP with high accuracy taking into account the distance to the destination DN.

[0043] Furthermore, the power generation amount calculation unit 1143 may predict the total power amount TEP taking into account the time (from the current time) until the arrival time TA. For example, the longer the time until the arrival time TA, the larger the predicted value of the total power amount TEP. For example, the power generation amount calculation unit 1143 may predict the arrival time TA using map information (average running load information IAL) obtained from the navigation system 31, and determine the time until the arrival time TA from the predicted arrival time TA and the current time. It is considered that the longer the time until the arrival time TA, the longer the engine drive request period DRP. Therefore, the information processing device 1 predicts the total power amount TEP to be a larger value as the time until the arrival time TA becomes longer. With this configuration, the information processing device 1 can predict the total power amount TEP with high accuracy taking into account the time until the arrival time TA.

[0044] The total road load calculation unit 1144 predicts the sum of the road loads (total road load TRL) of the vehicle VH up to the arrival time TA when the vehicle VH arrives at the destination DN. In particular, the total road load calculation unit 1144 predicts the total road load TRL when the drive demand prediction unit 113 predicts that "an engine drive demand EDR will be generated before the vehicle VH arrives at the destination DN." The information processing device 1 starts the second SOC reduction process earlier the smaller the total road load TRL predicted by the total road load calculation unit 1144. In other words, the smaller the total road load TRL predicted by the total road load calculation unit 1144, the earlier the timing adjustment unit 1145 sets the adjusted start timing AT compared to the standard start timing RT.

[0045] For example, even if the total power amount TEP up to the arrival time TA is the same, it is considered that the smaller the total running load TRL up to the arrival time TA, the smaller the power consumed by the second MG 23 up to the arrival time TA. In other words, it is considered that the smaller the total running load TRL up to the arrival time TA, the less likely the SOC of the battery 26 is to decrease. Therefore, in order to make the SOC of the battery 26 at the arrival time TA the target SOC, the smaller the total running load TRL, the earlier the execution of the SOC reduction process (second SOC reduction process) needs to be started. Therefore, the information processing device 1 determines (calculates) the timing to start the execution of the second SOC reduction process (adjusted start timing AT) depending on the total running load TRL. Specifically, the information processing device 1 advances the timing to start the execution of the second SOC reduction process (adjusted start timing AT) as the predicted total running load TRL decreases, i.e., starts the execution of the second SOC reduction process earlier. With this configuration, the information processing device 1 can reduce the SOC of the battery 26 by starting the second SOC reduction process at an appropriate time, even when the total running load TRL is small, and can reliably make the SOC at the arrival time TA the target SOC.

[0046] The total running load calculation unit 1144 may predict the total running load TRL using average running load information IAL (e.g., at least one of map information and running load history information) that can identify the average running load ARL. For example, the total running load calculation unit 1144 may predict the total running load TRL using the average running load ARL indicated by the average running load information IAL and at least one of the distance and time to the destination DN. For example, the total running load calculation unit 1144 may predict the total running load TRL from running load history information that indicates the history of the running load of the vehicle VH up to the destination DN. However, the method by which the total running load calculation unit 1144 predicts the total running load TRL is not limited to the example described above.

[0047] For example, the total running load calculation unit 1144 may predict the total running load TRL taking into account the average vehicle speed of the vehicle VH up to the arrival time TA. For example, the total running load calculation unit 1144 may predict a smaller value for the total running load TRL as the predicted average vehicle speed up to the arrival time TA decreases. For example, the total running load calculation unit 1144 may determine the average vehicle speed of the vehicle VH up to the arrival time TA by using the "statistical average vehicle speed up to the destination DN" indicated in the map information (average running load information IAL) acquired from the navigation system 31. For example, the total running load calculation unit 1144 may determine the average vehicle speed of the vehicle VH up to the arrival time TA by using running load history information (average running load information IAL) indicating the history of the vehicle speed of the vehicle VH up to the destination DN. In general, the lower the vehicle speed of the vehicle VH, the smaller the air resistance experienced by the vehicle VH. Therefore, it is considered that the lower the average vehicle speed of the vehicle VH, the smaller the total running load TRL. Therefore, the information processing device 1 predicts the total running load TRL to be a smaller value as the average vehicle speed of the vehicle VH decreases. With this configuration, the information processing device 1 can predict the total running load TRL with high accuracy, taking into account the average vehicle speed of the vehicle VH.

[0048] Furthermore, the total road load calculation unit 1144 may predict the total road load TRL taking into account the gradient to the destination DN. For example, the smaller the predicted gradient to the destination DN, the smaller the predicted value of the total road load TRL. For example, the total road load calculation unit 1144 may determine the gradient to the destination DN using the "gradient to the destination DN (road gradient)" indicated by the map information (average road load information IAL) acquired from the navigation system 31. Generally, the smaller the gradient, the smaller the road load on the vehicle VH. Therefore, it is considered that the smaller the gradient to the destination DN, the smaller the total road load TRL. Therefore, the information processing device 1 predicts the total road load TRL to be a smaller value as the gradient to the destination DN becomes smaller. With this configuration, the information processing device 1 can predict the total road load TRL with high accuracy, taking into account the gradient to the destination DN.

[0049] The timing adjustment unit 1145 sets the adjusted start timing AT for starting the execution of the SOC reduction process (second SOC reduction process) for driving the vehicle VH in the specific HEV mode to be earlier than the standard start timing RT for starting the execution of the first SOC reduction process. In other words, when the information processing device 1 predicts that an engine drive request EDR will be generated before the vehicle VH arrives at the destination DN, the information processing device 1 starts reducing the SOC by driving the vehicle VH in the specific HEV mode at a timing (adjusted start timing AT) that is earlier than the timing (standard start timing RT) for starting the SOC reduction by driving the vehicle VH in the EV mode if it is predicted that no engine drive request EDR will be generated. When the drive request prediction unit 113 predicts that "an engine drive request EDR will be generated before the vehicle VH arrives at the destination DN," the timing determination unit 114 calculates the timing (adjusted start timing AT) for starting the execution of the SOC reduction process (second SOC reduction process) for driving the vehicle VH in the specific HEV mode.

[0050] 4 , the timing adjustment unit 1145 calculates the adjusted start timing AT using at least one of the total electric power TEP predicted by the power generation amount calculation unit 1143, the total running load TRL predicted by the total running load calculation unit 1144, the (current) SOC of the battery 26, and the target SOC. For example, the timing adjustment unit 1145 calculates the timing (adjusted start timing AT) to start running in the specific HEV mode in order to "set the current SOC of the battery 26 to the target SOC at the arrival time TA" using the total electric power TEP up to the arrival time TA and the total running load TRL up to the arrival time TA.

[0051] The energy management unit 115 executes the SOC lowering process (first SOC lowering process or second SOC lowering process). In particular, the energy management unit 115 starts the execution of the SOC lowering process at the timing (standard start timing RT or adjusted start timing AT) determined by the timing determination unit 114. Specifically, when the drive demand prediction unit 113 predicts that "an engine drive demand EDR will not be generated before the vehicle arrives at the destination DN," the energy management unit 115 starts the execution of the first SOC lowering process at the standard start timing RT. Furthermore, when the drive demand prediction unit 113 predicts that "an engine drive demand EDR will be generated before the vehicle arrives at the destination DN," the energy management unit 115 starts the execution of the second SOC lowering process at the adjusted start timing AT, which is earlier than the standard start timing RT.

[0052] That is, when it is predicted that "an engine drive request EDR will not occur before arriving at the destination DN," the energy management unit 115 causes the vehicle VH to run in EV mode, thereby reducing the SOC of the battery 26 so that the SOC of the battery 26 at the arrival time TA becomes the target SOC. Furthermore, when it is predicted that "an engine drive request EDR will occur before arriving at the destination DN," the energy management unit 115 causes the vehicle VH to run in a specific HEV mode, thereby reducing the SOC of the battery 26 so that the SOC of the battery 26 at the arrival time TA becomes the target SOC. In particular, when it is predicted that "an engine drive request EDR will occur before arriving at the destination DN," the energy management unit 115 starts reducing the SOC by running the vehicle VH in the specific HEV mode at a timing (adjusted start timing AT) earlier than the timing (standard start timing RT) at which the SOC would be reduced by running the vehicle VH in EV mode if it was predicted that "an engine drive request EDR will not occur before arriving at the destination DN." The energy management unit 115 that causes the vehicle VH to run in the specific HEV mode may control at least one of the operating point and ignition timing of the engine 21 to achieve the determined output power DOP.

[0053] §3 Operation Example FIG. 5 is a flowchart showing an example of a processing procedure of the information processing device 1 according to this embodiment. The processing procedure described below is an example of a processing procedure of an information processing method PM that causes a processor (e.g., the CPU 11 of the information processing device 1) to execute a process of "reducing the SOC of the battery 26 so that the SOC of the battery 26 at the arrival time TA of the vehicle VH at the destination DN becomes a target SOC." However, the processing procedure described below is merely an example, and each step may be modified as much as possible. Furthermore, steps may be omitted, replaced, or added to the processing procedure described below as appropriate depending on the embodiment.

[0054] (Step S110) In step S110, the CPU 11 operates as the timing determination unit 114 (particularly, the standard timing calculation unit 1141) and calculates the start timing (standard start timing RT) of the SOC reduction process (first SOC reduction process) when driving in EV mode.

[0055] (Step S120) In step S120, the CPU 11 operates as the drive request prediction unit 113 and predicts whether an engine drive request EDR will occur before the vehicle VH arrives at the destination DN. For example, the CPU 11 predicts whether an engine drive request EDR will occur before the vehicle VH arrives at the destination DN using the average road load information IAL. The CPU 11 may predict whether an engine drive request EDR will occur before the vehicle VH arrives at the destination DN by taking into account at least one of the following in addition to the average road load information IAL: whether or not a heating request is required for the vehicle VH's interior, the interior temperature, the outside air temperature, and the engine water temperature. If the CPU 11 predicts that an engine drive request EDR will occur before the vehicle VH arrives at the destination DN (Yes in step S120), the CPU 11 proceeds to step S130. If the CPU 11 predicts that an engine drive request EDR will not occur before the vehicle VH arrives at the destination DN (No in step S120), the CPU 11 proceeds to step S150.

[0056] (Step S130) In step S130, the CPU 11 operates as the timing determination unit 114 (particularly, the timing adjustment unit 1145) and adjusts the start timing (adjusted start timing AT) of the SOC reduction process (second SOC reduction process) when the vehicle is driven in the specific HEV mode so that it is earlier than the standard start timing RT. In other words, in step S130, the CPU 11 determines (calculates) the adjusted start timing AT.

[0057] For example, the CPU 11 calculates the adjusted start timing AT at which to start driving in a specific HEV mode in order to "make the current SOC of the battery 26 the target SOC at the arrival time TA" using the total electric energy TEP and total driving load TRL up to the arrival time TA.

[0058] The CPU 11 may start the execution of the second SOC reduction process earlier the greater the total power amount TEP, that is, the greater the total power amount TEP, the earlier the adjusted start timing AT may be compared to the standard start timing RT.

[0059] The CPU 11 may predict the total electric power amount TEP, for example, by taking into account the output power (determined output power DOP) of the engine 21 in the specific HEV mode. For example, the CPU 11 may predict a larger value for the total electric power amount TEP as the predicted determined output power DOP increases. The CPU 11 may predict the total electric power amount TEP using the determined output power DOP and the engine drive request period DRP. The CPU 11 may predict the total electric power amount TEP by taking into account the displacement of the engine 21, for example, the larger the displacement of the engine 21, the larger the predicted value for the total electric power amount TEP. The CPU 11 may predict the total electric power amount TEP by taking into account the distance to the destination DN, for example, the longer the distance to the destination DN, the larger the predicted value for the total electric power amount TEP. The CPU 11 may predict the total amount of power TEP taking into consideration the time until the arrival time TA. For example, the CPU 11 may predict a larger value for the total amount of power TEP as the time until the arrival time TA increases.

[0060] The CPU 11 may start the execution of the second SOC reduction process earlier the smaller the total running load TRL, that is, the smaller the total running load TRL, the earlier the adjusted start timing AT may be compared to the standard start timing RT.

[0061] The CPU 11 may predict the total running load TRL, for example, by taking into account the average vehicle speed of the vehicle VH up to the arrival time TA. For example, the CPU 11 may predict a smaller value for the total running load TRL as the average vehicle speed up to the arrival time TA is predicted to be smaller. Furthermore, for example, the CPU 11 may predict the total running load TRL by taking into account the gradient to the destination DN, for example, by taking into account the gradient to the destination DN. For example, the CPU 11 may predict a smaller value for the total running load TRL as the gradient to the destination DN is predicted to be smaller.

[0062] As described above, the CPU 11 may predict the total electric power amount TEP using the determined output power DOP and the engine drive request period DRP, and the CPU 11 may predict the engine drive request period DRP. The CPU 11 may start the execution of the second SOC lowering process earlier as the predicted engine drive request period DRP is longer. In other words, the CPU 11 may set the adjusted start timing AT earlier than the standard start timing RT as the engine drive request period DRP is longer.

[0063] The CPU 11 may predict the engine drive request period DRP taking into account the outside air temperature around the vehicle VH. For example, the lower the outside air temperature, the longer the predicted engine drive request period DRP. The CPU 11 may predict the engine drive request period DRP taking into account the engine water temperature of the engine 21. For example, the lower the engine water temperature, the longer the predicted engine drive request period DRP. The CPU 11 may predict the engine drive request period DRP taking into account the set temperature of the air conditioner of the vehicle VH. For example, the higher the set temperature of the air conditioner, the longer the predicted engine drive request period DRP. The CPU 11 may predict the engine drive request period DRP taking into account the difference between the set temperature of the air conditioner of the vehicle VH and the interior temperature of the vehicle VH. For example, the CPU 11 may predict the engine drive request period DRP taking into account the difference between the set temperature of the air conditioner of the vehicle VH and the interior temperature of the vehicle VH. The CPU 11 may predict the engine drive request period DRP taking into consideration the volume of the passenger compartment of the vehicle VH. For example, the CPU 11 may predict a longer engine drive request period DRP as the volume of the passenger compartment of the vehicle VH increases.

[0064] (Step S140) In step S140, the CPU 11 operates as the energy management unit 115 and starts running in the specific HEV mode at the post-adjustment start timing AT determined (calculated) in step S130, thereby reducing the SOC of the battery 26. That is, in step S140, the CPU 11 starts executing the second SOC reduction process at the post-adjustment start timing AT. As described above, the post-adjustment start timing AT is earlier than the standard start timing RT.

[0065] (Step S150) In step S150, CPU 11 operates as energy management unit 115 and starts running in EV mode at the standard start timing RT calculated in step S110 to reduce the SOC of battery 26. That is, in step S150, CPU 11 starts executing the first SOC reduction process at the standard start timing RT. The standard start timing RT is later than the adjusted start timing AT.

[0066] [Features] As described above, the information processing device 1 according to this embodiment is an information processing device included in a vehicle VH. The vehicle VH includes an engine 21, a first MG 22 (motor generator for generating electricity) driven by the engine 21 to generate electricity, a second MG 23 (motor generator for driving), and a battery 26 that is charged with the electricity generated by the first MG 22 and supplies the electricity to the second MG 23. The information processing device 1 includes a drive request prediction unit 113 and an energy management unit 115.

[0067] The drive request prediction unit 113 predicts whether an engine drive request EDR will be generated before the vehicle VH arrives at the destination DN, using average drive load information IAL that can identify an average drive load ARL, which is an average value of the drive load of the vehicle VH up to the destination DN of the vehicle VH. The engine drive request EDR is a request to drive the engine 21.

[0068] The energy management unit 115 reduces the SOC of the battery 26 so that the SOC of the battery 26 at the arrival time TA at the destination DN becomes a target SOC. The energy management unit 115 reduces the SOC of the battery 26 by running the vehicle VH in an EV mode (first running mode) or a specific HEV mode (second running mode). The EV mode is a running mode in which the engine 21 is stopped and the second MG 23 is driven by electric power supplied from the battery 26. The specific HEV mode is a running mode in which the second MG 23 is driven by electric power supplied from the battery 26 while controlling the operation of the engine 21 so that the output power of the engine 21 is greater than 0 and smaller than an average running load ARL. When the running request prediction unit 113 predicts that "an engine running request EDR will not be generated by the time the vehicle VH arrives at the destination DN," the energy management unit 115 runs the vehicle VH in the EV mode. When the driving demand prediction unit 113 predicts that "an engine driving demand EDR will occur before the vehicle VH arrives at the destination DN," the energy management unit 115 causes the vehicle VH to run in the specific HEV mode. When the driving demand prediction unit 113 predicts that "an engine driving demand EDR will occur before the vehicle VH arrives at the destination DN," the energy management unit 115 starts reducing the SOC by causing the vehicle VH to run in the specific HEV mode at a timing (adjusted start timing AT) earlier than the timing (standard start timing RT) at which reducing the SOC starts by causing the vehicle VH to run in the EV mode when it is predicted that "an engine driving demand EDR will not occur."

[0069] The information processing method PM according to this embodiment causes a processor (e.g., the CPU 11 of the information processing device 1) to execute steps S120, S140, and S150 illustrated in FIG. 5 . In step S120, the processor uses the average traveling load information IAL to predict whether an engine drive request EDR will be generated before the vehicle VH arrives at the destination DN. In step S140 or S150, the processor reduces the SOC of the battery 26 so that the SOC of the battery 26 at the arrival time TA at the destination DN becomes a target SOC. In step S140 or S150, the processor reduces the SOC of the battery 26 by running the vehicle VH in the EV mode (first traveling mode) or the specific HEV mode (second traveling mode). If the CPU 11 predicts in step S120 (prediction step) that "an engine drive request EDR will not occur before the vehicle arrives at the destination DN" (No in step S120), the CPU 11 causes the vehicle VH to run in the EV mode in step S150 (a step of reducing the SOC of the battery 26). If the CPU 11 predicts in step S120 (prediction step) that "an engine drive request EDR will occur before the vehicle arrives at the destination DN" (Yes in step S120), the CPU 11 causes the vehicle VH to run in the specific HEV mode in step S140 (a step of reducing the SOC of the battery 26). When the CPU 11 predicts in step S120 that "an engine drive request EDR will occur before the vehicle arrives at the destination DN," it starts reducing the SOC by running the vehicle VH in a specific HEV mode at a timing (adjusted start timing AT) earlier than the timing (standard start timing RT) at which reducing the SOC by running the vehicle VH in EV mode would start if it predicted that "an engine drive request EDR will not occur before the vehicle arrives at the destination DN."

[0070] As described above, if the information processing device 1 (information processing method PM) predicts that the engine drive request EDR will not be generated by the time the vehicle arrives at the destination DN, the information processing device 1 (information processing method PM) starts driving in the EV mode at the standard start timing RT. On the other hand, if the information processing device 1 (information processing method PM) predicts that the engine drive request EDR will be generated by the time the vehicle arrives at the destination DN, the information processing device 1 (information processing method PM) starts driving in the specific HEV mode at the adjusted start timing AT, which is earlier than the standard start timing RT. Since the determined output power DOP is smaller than the average running load ARL, the information processing device 1 (information processing method PM) can reduce the SOC of the battery 26 by driving in the specific HEV mode, and in particular, can reduce the SOC so that the SOC at the arrival time TA becomes the target SOC. Furthermore, since the determined output power DOP is greater than 0, the information processing device 1 (information processing method PM) can satisfy the engine drive request EDR by driving in the specific HEV mode. The information processing device 1 (information processing method PM) can, for example, drive the engine 21 so as to achieve the determined output power DOP, thereby increasing the water temperature (engine water temperature) of the coolant of the engine 21 and using the coolant to heat the interior of the vehicle.

[0071] However, because the engine 21 is driven when traveling in the specific HEV mode, the rate of decrease in the SOC of the battery 26 is slower than when traveling in the EV mode, in which "the engine 21 is stopped, the second MG 23 is driven by power supplied from the battery 26, and the vehicle travels using only the driving force of the second MG 23." Therefore, when the information processing device 1 (information processing method PM) predicts that an engine drive request EDR will be generated before the vehicle arrives at the destination DN, the information processing device 1 (information processing method PM) advances the timing of executing the process to reduce the SOC compared to when it predicts that an engine drive request EDR will not be generated before the vehicle arrives at the destination DN. When the information processing device 1 (information processing method PM) predicts that an engine drive request EDR will be generated, the information processing device 1 (information processing method PM) starts traveling in the specific HEV mode at a timing earlier than the standard start timing RT for starting traveling in the EV mode when it predicts that an engine drive request EDR will not be generated. Specifically, when it is predicted that an engine drive request EDR will be generated before arrival at the destination DN, the information processing device 1 (information processing method PM) starts traveling in the specific HEV mode at the adjusted start timing AT, which is earlier than the standard start timing RT. Therefore, even when it is predicted that an engine drive request EDR will be generated, the information processing device 1 (information processing method PM) starts traveling in the specific HEV mode at the adjusted start timing AT, thereby reliably reducing the SOC of the battery 26 so that the SOC becomes the target SOC. In other words, the information processing device 1 (information processing method PM) can appropriately adjust the engine drive request EDR and the "request to reduce the SOC (SOC reduction request) so that the SOC of the battery 26 at the arrival time TA becomes the target SOC" in the vehicle VH.

[0072] §4 Modifications Although the embodiments of the present invention have been described above in detail, the above description is merely an example of the present invention in every respect. It goes without saying that various improvements and modifications can be made without departing from the scope of the present invention. For example, the following modifications are possible. Note that, in the following, the same reference numerals are used for components similar to those in the above embodiment, and descriptions of similar points to those in the above embodiment are omitted where appropriate. The following modifications can be combined as appropriate.

[0073] In the above embodiment, an example has been described in which the information processing device 1 is realized as a single computer. However, the configuration of the information processing device according to this embodiment is not limited to this example and may be determined appropriately depending on the embodiment. For example, the information processing device 1 may be configured by multiple computers.

[0074] REFERENCE SIGNS LIST 1...information processing device, 21...engine, 22...first MG (motor generator for power generation), 23...second MG (motor generator for driving), 26...battery, 113...driving demand prediction unit, 115...energy management unit, ARL...average driving load, DN...destination, DRP...engine driving demand period, EDR...engine driving demand, IAL...average driving load information, PM...information processing method, TA...arrival time, TEP...total electric energy, TRL...total driving load (sum of driving loads), VH...vehicle (hybrid vehicle)

Claims

1. A hybrid vehicle including an engine, a power generation motor generator driven by the engine to generate electricity, a traction motor generator, and a battery charged with electricity generated by the power generation motor generator and supplying power to the traction motor generator, wherein a processor executes the following steps: predicting whether an engine drive request, which is a request to drive the engine, will occur before the hybrid vehicle reaches the destination, using average road load information that can identify an average road load that is an average value of the road load of the hybrid vehicle up to the destination of the hybrid vehicle; and reducing the SOC of the battery so that the SOC at the time of arrival at the destination will become a target SOC, by running the hybrid vehicle in either a first running mode in which the engine is stopped and the traction motor generator is driven by electric power supplied from the battery, or a second running mode in which the traction motor generator is driven by electric power supplied from the battery while controlling the operation of the engine so that the output power of the engine is greater than 0 and smaller than the average road load, and the processor executes the following steps: an information processing method comprising: when it is predicted in the predicting step that the engine drive request will not occur before the vehicle arrives at the destination, running the hybrid vehicle in the first driving mode in the SOC reducing step; when it is predicted in the predicting step that the engine drive request will occur before the vehicle arrives at the destination, running the hybrid vehicle in the second driving mode in the SOC reducing step; and when it is predicted in the predicting step that the engine drive request will occur before the vehicle arrives at the destination, running the hybrid vehicle in the second driving mode starts to reduce the SOC at an earlier timing than a timing at which the SOC would start to reduce by running the hybrid vehicle in the first driving mode if it was predicted that the engine drive request would not occur.

2. The information processing method of claim 1, wherein the processor further executes a step of predicting an engine drive request period, which is a period during which the engine drive request will occur up to the arrival time, and the longer the engine drive request period predicted in the step of predicting the engine drive request period, the earlier the processor starts executing the step of reducing the SOC.

3. The information processing method according to claim 2, wherein in the step of predicting the engine drive request period, the processor predicts the engine drive request period to be a longer period as the outside air temperature around the hybrid vehicle is lower.

4. The information processing method according to claim 2, wherein in the step of predicting the engine drive request period, the processor predicts the engine drive request period to be a longer period as the engine water temperature of the engine is lower.

5. The information processing method according to claim 2, wherein in the step of predicting the engine drive request period, the processor predicts the engine drive request period to be longer the higher the set temperature of an air conditioner of the hybrid vehicle.

6. The information processing method according to claim 2, wherein in the step of predicting the engine drive request period, the processor predicts the engine drive request period to be a longer period the greater the difference between the air conditioner setting temperature of the hybrid vehicle and the cabin temperature of the hybrid vehicle.

7. The information processing method according to claim 2, wherein in the step of predicting the engine drive request period, the processor predicts the engine drive request period to be longer as the volume of the vehicle interior of the hybrid vehicle increases.

8. The information processing method of claim 1 or 2, wherein the processor further executes a step of predicting a total amount of power to be generated by the power generating motor generator by the time of arrival by running the hybrid vehicle in the second running mode, and the processor starts execution of the step of lowering the SOC earlier the total amount of power predicted in the step of predicting the total amount of power is larger.

9. The information processing method according to claim 8, wherein in the step of predicting the total amount of electric power, the processor predicts the total amount of electric power to be a larger value as the displacement of the engine increases.

10. The information processing method according to claim 8, wherein in the step of predicting the total amount of power, the processor predicts the total amount of power to be a larger value as the distance to the destination increases.

11. The information processing method according to claim 8, wherein in the step of predicting the total amount of power, the processor predicts the total amount of power to be a larger value as the time until the arrival time is longer.

12. The information processing method according to claim 8, wherein in the step of predicting the total amount of electric power, the processor predicts the total amount of electric power to be a larger value as the predicted output power of the engine in the second running mode is greater.

13. The information processing method of claim 1 or 2, wherein the processor further executes a step of predicting a total sum of the running load of the hybrid vehicle up to the arrival time, and the smaller the total sum of the running load predicted in the step of predicting the total sum of the running load, the earlier the processor starts executing the step of reducing the SOC.

14. The information processing method according to claim 13, wherein in the step of predicting the total sum of the road loads, the processor predicts the total sum of the road loads to be a smaller value as the predicted average vehicle speed of the hybrid vehicle up to the arrival time is smaller.

15. An information processing device included in a hybrid vehicle having an engine, a power generation motor generator driven by the engine to generate electricity, a traction motor generator, and a battery charged with electricity generated by the power generation motor generator and supplying power to the traction motor generator, the information processing device comprising: a drive request prediction unit that predicts whether an engine drive request, which is a request to drive the engine, will occur before the hybrid vehicle reaches the destination, using average road load information that can identify an average road load that is an average value of the road load of the hybrid vehicle up to the destination of the hybrid vehicle; and an energy management unit that reduces the SOC of the battery so that the SOC of the battery at the time of arrival at the destination will become a target SOC, and the energy management unit reduces the SOC by running the hybrid vehicle in: a first running mode in which the engine is stopped and the traction motor generator is driven by electric power supplied from the battery, or a second running mode in which the drive of the engine is controlled so that the output power of the engine is greater than 0 and smaller than the average road load, the energy management unit, when the drive demand prediction unit predicts that the engine drive demand will not be generated by the time the vehicle arrives at the destination, causes the hybrid vehicle to run in the first driving mode; when the drive demand prediction unit predicts that the engine drive demand will be generated by the time the vehicle arrives at the destination, causes the hybrid vehicle to run in the second driving mode; and when the drive demand prediction unit predicts that the engine drive demand will be generated by the time the vehicle arrives at the destination, starts reducing the SOC by running the hybrid vehicle in the second driving mode at an earlier timing than a timing at which reducing the SOC would start by running the hybrid vehicle in the first driving mode if it was predicted that the engine drive demand would not be generated.

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