JP7523325B2 - Electric vehicle control method and electric vehicle control device - Google Patents

Description

The present invention relates to an electric vehicle control method and an electric vehicle control device that estimate the energy consumed during driving.

Conventionally, electric vehicles are known that estimate energy consumption based on driving history and implement a power generation plan based on the estimated energy consumption. For example, in the vehicle control system of Patent Document 1, the amount of energy that the vehicle will consume in the future is estimated based on the driving history with the highest energy consumption or the driving history with the highest application frequency, and the power generation engine is driven based on this.

JP 2019-131108 A

Conventionally, energy consumption is estimated based on information about the driving route to the destination (so-called route information). However, depending on the nature of the destination, even after arriving at the destination, the electric vehicle may consume more energy by driving through sections for which there is no route information. For this reason, depending on the nature of the destination, it is not possible to accurately estimate the energy consumption until the electric vehicle is parked.

For example, when the destination is a commercial facility such as a shopping mall with a large multi-story parking lot, route information to the commercial facility can be obtained, but there is no route information for the multi-story parking lot within the commercial facility. Furthermore, in facilities such as companies and factories with vast premises, employees may travel by electric vehicles. However, since these are privately owned premises, route information for the interior of the facility is not usually provided. In addition, even for public facilities, new facilities may not have complete route information. In this way, when the destination is one that requires further energy consumption after arrival by driving through sections for which there is no route information, the energy consumption until the electric vehicle is parked cannot be accurately estimated.

The present invention aims to provide an electric vehicle control method and an electric vehicle control device that can more accurately estimate energy consumption and execute control related to battery discharging or charging.

One aspect of the present invention is an electric vehicle control method that is executed in an electric vehicle that includes a motor as a driving source and a battery that supplies power to the motor, estimates energy consumption caused by the traveling of the electric vehicle, and executes control related to discharging or charging of the battery based on the estimated energy consumption. In this electric vehicle control method, route information related to a traveling route until arriving at a preset destination is acquired, and a first consumed energy that is energy consumed until arriving at the destination is estimated using the route information. Then, when the destination is a specific destination that requires further energy consumption by traveling through an unknown route section where there is no information about the route after arriving, a traveling history of the unknown route section is acquired, and a second consumed energy that is energy consumed until the electric vehicle is parked after arriving at the specific destination is estimated using the traveling history of the unknown route section. Then, the energy consumption of the electric vehicle is estimated using the first consumed energy and the second consumed energy. Furthermore, a schedule for discharging or charging the battery until arriving at the specific destination is set using the first consumed energy and the second consumed energy so that the battery has power equivalent to the second consumed energy at the time of arriving at the specific destination.

The present invention provides an electric vehicle control method and an electric vehicle control device that can more accurately estimate energy consumption and execute control related to discharging or charging the battery.

FIG. 1 is a block diagram showing the configuration of an electric vehicle. FIG. 2 is an explanatory diagram showing a destination and an unknown route section. FIG. 3 is a block diagram showing a configuration of a controller for estimating energy consumption and setting a charging and discharging schedule. FIG. 4 is a block diagram showing a configuration of the second consumed energy estimation unit. FIG. 5 is a flowchart showing the operation of the electric vehicle.

The following describes an embodiment of the present invention with reference to the drawings.

[First embodiment]
Fig. 1 is a block diagram showing the configuration of an electric vehicle 100. As shown in Fig. 1, the electric vehicle 100 of this embodiment is a so-called series type hybrid vehicle (HEV: Hybrid Electric Vehicle). The electric vehicle 100 includes a drive motor 10, drive wheels 11, a battery 12, a generator motor 13, an engine 14, and a controller 15.

The drive motor 10 is an electric motor that functions as a driving source for the electric vehicle 100. That is, the drive motor 10 generates torque (driving force) in the drive wheels 11 to drive the electric vehicle 100. The drive of the drive motor 10 is controlled by the controller 15.

The drive wheels 11 are wheels that rotate when they receive the torque generated by the drive motor 10. The electric vehicle 100 can have one or more drive wheels 11. In this embodiment, the electric vehicle 100 is an automobile that has two or four drive wheels 11.

The battery 12 holds the power to operate the drive motor 10. The power of the battery 12 can be charged by so-called regenerative power. The battery 12 can also be charged by receiving a supply of power generated by the generator motor 13.

The generator motor 13 is an electric motor for generating power to charge the battery 12. The generator motor 13 is driven by the engine 14. That is, the generator motor 13 and the engine 14 constitute a power generation device for supplying power to the battery 12. The generator motor 13 is driven appropriately to generate power according to the SOC (State Of Charge) of the battery 12 and the power consumed or recovered. The generator motor 13 may be driven using regenerated power or power stored in the battery 12. In this case, the operation of the generator motor 13 is controlled by the controller 15.

The engine 14 is an internal combustion engine that generates torque (driving force) for driving the generator motor 13 by burning fuel such as gasoline. The driving or stopping of the engine 14 and the operation of the engine 14 are controlled by the controller 15. For example, when the battery 12 needs to be charged, the engine 14 is driven according to the required amount of power to be charged. As a result, the generator motor 13 can generate the power to be supplied to the battery 12.

The controller 15 is a control device that controls the operation of the electric vehicle 100, such as driving, by comprehensively controlling the above-mentioned parts and other controlled objects (e.g., auxiliary equipment, etc.). The controller 15 is composed of, for example, a central processing unit (CPU), a random access memory (RAM), and an input/output interface (I/O interface). The controller 15 is also programmed to periodically control the above-mentioned parts and other controlled objects at a predetermined control cycle.

In this embodiment, the controller 15 estimates the energy consumed by the electric vehicle 100 from the arrival at the destination until the vehicle is stopped, and executes control regarding the discharge or charging of the battery 12 based on the estimated energy consumption. Specifically, the controller 15 sets (plans) a discharge and charging schedule for the battery 12 based on the estimated energy consumption. Then, the controller 15 consumes the power of the battery 12 or charges the battery 12 according to the set discharge and charging schedule. The discharge and charging schedule for the battery 12 refers to a schedule that determines the consumption of the power of the battery 12 and the timing and amount of charging of the battery 12 over time along the progress of the electric vehicle 100 on the planned driving route. Therefore, in this embodiment in which the electric vehicle 100 is an HEV, the discharge and charging schedule for the battery 12 determines the drive timing and drive amount (i.e., the amount of power generation) of the engine 14 and the generator motor 13. That is, when the electric vehicle 100 is equipped with the engine 14 used to charge the battery 12, the engine 14 is driven according to the above discharge and charging schedule. The estimation of energy consumption by the controller 15 and the setting of the charging and discharging schedule will be described in detail later.

In this embodiment, consumed energy includes energy related to the consumption of electric power held by the battery 12 (power consumption) and energy related to the consumption of fuel by driving the engine 14 (fuel consumption). In addition, the energy related to the consumption of electric power held by the battery 12 includes the electric energy recovered when regenerative electric power is recovered. For example, if the consumption of energy is positive, the recovered regenerative electric power is negative consumed energy.

The controller 15 can obtain information necessary for the above control (hereinafter referred to as vehicle information) as needed by communicating with various components of the electric vehicle 100. For example, the electric vehicle 100 obtains the operating state of components that change depending on the driver's operation in addition to the components controlled by the controller 15 such as the above-mentioned parts, and controls the operation of the drive motor 10 based on this. Components that change depending on the driver's operation include, for example, an accelerator pedal, brake pedal, shift lever, and steering wheel (none of which are shown). The controller 15 can also obtain vehicle information as needed from components of the electric vehicle 100 that do not require active control from the controller 15, such as a measuring instrument that measures the current flowing through the drive motor 10 and a GPS (Global Positioning System) (none of which are shown).

In addition to the above, the electric vehicle 100 is equipped with a navigation system 16 and a driving history database 19.

The navigation system 16 is a system that provides the driver or passenger (hereinafter referred to as the passenger) of the electric vehicle 100 with guidance on the route to the destination, etc. The navigation system 16 has an operation unit (not shown) that allows the passenger to set the destination, etc., and a display unit (not shown) that displays the set destination, the current location of the electric vehicle 100, and a map of the surrounding area, the driving route to the destination, and the congestion level 18, etc. For this reason, the navigation system 16 holds or acquires information such as map information (not shown), route information 17, and congestion level 18. The destination in the navigation system 16 (hereinafter simply referred to as the destination) is set by the passenger. The destination may also be estimated and automatically set by the navigation system 16 or the controller 15, etc. based on the driving pattern of the electric vehicle 100, etc.

The route information 17 is information about a route, and in particular, is information that represents the planned route to the destination (hereinafter referred to as the driving route) and the state of that driving route. The state of the driving route refers to the substantially unchanging state of the driving route, such as the undulations of the driving route and/or speed and other restrictions on the driving route. The information that represents the state of the driving route includes information that represents factors that cause fluctuations in the energy consumption required when the electric vehicle 100 travels along that driving route, and the degree of that fluctuation.

In addition, the route information 17 is information associated with the map information. For this reason, there is no route information 17 for sections (areas) where there is no detailed map information to the extent that a driving route can be specified, such as private land and three-dimensional buildings that vehicles can enter. For example, the hierarchical structure of roads and buildings for private land, etc. is not generally disclosed. In addition, even if the hierarchical structure of roads and multi-story parking lots for the premises of commercial facilities such as shopping malls is disclosed, it may not be maintained as map information. Therefore, for these private lands, etc., even if the existence of private lands, etc. is shown on the map, the driving route on private lands, etc. cannot be specified, so there is no route information 17. In addition, when the map information becomes inaccurate over time, such as when roads, facilities, etc. are newly constructed but the map information has not been updated, there is no route information 17 for the newly constructed roads or routes within the facilities. Hereinafter, a section without route information 17 is referred to as a route-unknown section 36 (see FIG. 2).

The congestion degree 18 is information that indicates the degree to which roads, facilities, etc. are congested. The congestion degree 18 is provided for each of a portion or parts of the travel route, a destination that is the end point of the travel route, the current location of the electric vehicle 100, or roads, facilities, etc. in the vicinity of these. In this embodiment, the congestion degree 18 is obtained by the navigation system 16 from an information providing system, etc., that is external to the electric vehicle 100, via communication. Therefore, in the electric vehicle 100 of this embodiment, the congestion degree 18 is known information.

However, the controller 15 may be configured to directly acquire the congestion degree 18 without going through the navigation system 16. The controller 15 may also be configured to estimate the congestion degree 18 without relying on information acquired from the outside. In this case, the controller 15 can estimate the congestion degree 18 based on people and vehicles around the electric vehicle 100 detected by a sensor (not shown), for example, and their presence density, movement speed, etc.

The above route information 17 and congestion level 18 are used by the navigation system 16, and are also acquired by the controller 15 and used to estimate energy consumption.

The travel history database 19 stores the travel history 20 of the electric vehicle 100. The travel history 20 is a history of travel routes traveled by the electric vehicle 100, the altitude of the travel route, the travel speed, or other information related to travel. In this embodiment, the travel history 20 includes at least information related to the altitude at which the electric vehicle 100 traveled or parked (or stopped) (hereinafter referred to as altitude information) in addition to position information (planar position information on a map) of the travel route of the electric vehicle 100. However, in addition to these pieces of information, the travel history 20 may include, for example, a travel time that is the time required to travel the route and a travel distance that is the length of the route. In addition, the travel history 20 is separated from the map information of the navigation system 16, and includes a travel history in an unknown route section 36 where there is no route information 17. Hereinafter, the travel history 20 in the unknown route section 36 is referred to as an unknown route section travel history 21. In this embodiment, the unknown route section travel history 21 includes at least the travel route in the unknown route section 36 and its altitude information.

The above-mentioned driving history 20, particularly the unknown route section driving history 21, is acquired by the controller 15 and used to estimate the energy consumption. In this embodiment, the energy consumption (particularly the second energy consumption described later) is estimated based on the driving route and altitude information in the unknown route section 36.

Figure 2 is an explanatory diagram showing the destination and an unknown route section 36. As shown in Figure 2, in this embodiment, the subjective destination of the occupant is, for example, a shopping mall 30. The shopping mall 30 is a so-called complex commercial facility and its site is large. The shopping mall 30 has, for example, a first building 31 for selling food, clothing, and other merchandise, and a second building 32 for providing services such as a movie theater and an amusement facility. The shopping mall 30 also has, for example, a multi-storey parking lot 33, which is a parking lot with a three-dimensional tiered structure, as a parking lot for visitors to each of these buildings.

When the electric vehicle 100 heads for the shopping mall 30, the subjective destination set in the navigation system 16 is the shopping mall 30. However, while the location of the shopping mall 30 is registered in the map information of the navigation system 16, information about the hierarchical structure of the parking garage 33 is not registered. Therefore, the navigation system 16 can only provide route guidance up to the entrance 34 of the parking garage 33 (hereinafter referred to as the parking garage entrance). For this reason, when the electric vehicle 100 reaches the parking garage entrance 34, the route guidance by the navigation system 16 ends with an announcement such as "You have arrived at your destination" or "You have arrived near your destination". Therefore, regardless of how the driver sets the navigation system 16, the destination in the system is the parking garage entrance 34.

In this embodiment, the destination does not simply refer to a destination that represents a subjective area of the occupant, such as the entire shopping mall 30, but rather refers to a destination in the system where route guidance ends, such as the parking lot entrance 34. In other words, as shown by the dashed arrow, the end point of the driving section on the driving route where route information 17 can be obtained (hereinafter referred to as the route clear section 35) is the destination in the system, that is, the destination in this embodiment.

On the other hand, the electric vehicle 100 needs to travel in the multi-storey car park 33 even after arriving at the parking lot entrance 34, which is the destination. This is because the driver takes into consideration the building to be visited, the location of the entrance to the building, the walking distance to the building, the congestion level 18, etc., and searches for an available parking space to park (continuously stop) the electric vehicle 100. Since the multi-storey car park 33 does not have route information 17, the travel section from the parking lot entrance 34 to the parking position 37 is an unknown route section 36, as shown by the two-dot chain line arrow. In other words, the travel section from the arrival at the destination until the electric vehicle 100 is parked is the unknown route section 36. As long as the electric vehicle 100 travels, energy is consumed in the electric vehicle 100 even in such an unknown route section 36. When the unknown route section 36 is relatively long, such as the unknown route section 36 in the multi-storey car park 33 in the shopping mall 30, the energy consumption in the unknown route section 36 causes a non-negligible error in the estimation of the energy consumption.

In the following, a special destination such as a parking lot entrance 34 that, after arrival, requires further energy consumption by traveling through an unknown route section 36 that does not have route information 17, is referred to as a "specific destination."

In this embodiment, the destination (destination on the system) can include not only the final destination, but also points equivalent to the destination, such as waypoints (hereinafter referred to as quasi-destinations). Waypoints are areas that include a section of the route from the final destination to the return to the route. For example, when a passenger passes through a service area for a meal or the like and heads for the final destination, the service area is a quasi-destination. If there is no route information 17 within this service area, its entrance becomes a temporary end point of the clear route section 35. Therefore, the entrance of the service area can be a destination on the system (quasi-destination). Therefore, when a waypoint that does not have route information 17 is set in the navigation system 16 in addition to the final destination, the waypoint (especially its entrance) is treated as the destination in this embodiment.

[Estimation of energy consumption and setting of charging and discharging schedule]
Fig. 3 is a block diagram showing the configuration of the controller 15 for estimating energy consumption and setting a charging/discharging schedule. As shown in Fig. 3, the controller 15 includes an information acquisition unit 41, a first energy consumption estimation unit 42, a destination type determination unit 43, a second energy consumption estimation unit 44, and a charging/discharging schedule setting unit 45.

The information acquisition unit 41 acquires information necessary for estimating energy consumption and setting a charging/discharging schedule for the battery 12 from the navigation system 16, the driving history database 19, etc. In this embodiment, the information necessary for estimating energy consumption and setting a charging/discharging schedule for the battery 12 is the route information 17, the congestion degree 18, and the driving history 21 of unknown route sections. This acquired information is provided to the first energy consumption estimation unit 42, the destination type determination unit 43, and the second energy consumption estimation unit 44 as necessary.

More specifically, the information acquisition unit 41 acquires route information 17 relating to the driving route to arrive at a preset destination from the navigation system 16. The information acquisition unit 41 also acquires from the navigation system 16 the congestion degree 18 for each of the clear route section 35, the unknown route section 36 included in the driving route, and facilities at the destination (e.g., a multi-story parking lot 33). The information acquisition unit 41 also acquires a driving history 20 from the driving history database 19. In this embodiment, the information acquisition unit 41 acquires at least the unknown route section driving history 21 relating to the unknown route section 36 related to the set driving route. The unknown route section 36 related to the set driving route refers to the unknown route section 36 that the electric vehicle 100 can enter after arriving at the destination.

The above route information 17, etc. can be acquired or reacquired at any timing. When it is necessary to estimate the energy consumption or set the charging/discharging schedule again, the information acquisition unit 41 acquires or reacquires the route information 17, etc. The route information 17, etc. is acquired or reacquired, for example, when the destination is set or changed, when the driving route is set or changed, or when the SOC of the battery 12, etc., deviates significantly from the plan. In this embodiment, the timing at which the information acquisition unit 41 acquires the route information 17, etc. is approximately equal to the timing at which the controller 15 estimates the energy consumption and sets or resets the charging/discharging schedule. The unknown route section driving history 21 is acquired when the set destination is a specific destination.

The first energy consumption estimation unit 42 estimates the first energy consumption using the route information 17. The first energy consumption is the energy consumed until the vehicle reaches the destination. For example, when the electric vehicle 100 heads towards the shopping mall 30, the first energy consumption is the energy consumed from the position (current location) when the route information 17 is acquired until the vehicle reaches the parking lot entrance 34. The first energy consumption is calculated based on, for example, the length of the travel route included in the route information 17 (the actual distance to the destination) and the estimated travel time (the actual travel time to the destination) taking into account the speed limit and the congestion level 18 of the travel route.

The destination type determination unit 43 determines whether the set destination is a specific destination. This determination is made based on the past driving pattern after arrival at the destination. That is, the destination type determination unit 43 determines whether the destination is a specific destination based on the driving pattern indicated by the driving history 20 (particularly the unknown route section driving history 21 related to the unknown route section 36) continuing to the destination. For example, for a shopping mall 30 (see FIG. 2) that the occupant has visited in the electric vehicle 100, the driving history 20 in the multi-storey parking lot 33 continuing from the destination parking lot entrance 34 is accumulated as the unknown route section driving history 21. For this reason, when the parking lot entrance 34 of the shopping mall 30 is the destination, it can be determined that further energy consumption is required by driving the unknown route section 36 in the multi-storey parking lot 33 after arrival. Therefore, the parking lot entrance 34 of the shopping mall 30 is determined to be a specific destination.

The driving pattern indicated by the driving history 20 (unknown route section driving history 21) includes the driving history 20 (unknown route section driving history 21) itself as well as the results of analyzing the driving history 20 (unknown route section driving history 21). The driving pattern includes information such as the number of 90-degree turns per unit time, whether the key is turned off, whether the vehicle is being driven slowly (low speed driving) at a speed lower than a predetermined value, and whether pedestrians are detected by sonar or the like. The determination by the destination type determination unit 43 can be realized by a program that has learned past driving patterns by machine learning or the like. In this case, the destination type determination unit 43 is a so-called AI (Artificial Intelligence), which receives input of a set destination and outputs a determination result as to whether the destination is a specific destination or not.

When the destination is a specific destination, the second energy consumption estimation unit 44 acquires the unknown route section driving history 21 by the information acquisition unit 41. When the destination is a specific destination, the second energy consumption estimation unit 44 estimates the second energy consumption using the acquired unknown route section driving history 21. The second energy consumption is energy consumed from the arrival at the specific destination until the electric vehicle 100 is parked. The second energy consumption estimation unit 44 estimates the driving time of the unknown route section 36 using the unknown route section driving history 21. The second energy consumption estimation unit 44 also estimates the energy consumption per unit time when driving the unknown route section 36 using the unknown route section driving history 21. The second energy consumption estimation unit 44 estimates the driving time of the unknown route section 36 and the energy consumption per unit time in the unknown route section 36. The second energy consumption is estimated based on the driving time of the unknown route section 36 and the energy consumption per unit time in the unknown route section 36. A specific method for estimating the second energy consumption will be described in detail later.

The discharge/charge schedule setting unit 45 sets a discharge/charge schedule for the battery 12 using the first consumption energy or the first consumption energy and the second consumption energy. Specifically, when the destination is not a specific destination, the discharge/charge schedule setting unit 45 sets a discharge/charge schedule optimized to improve the power consumption and/or fuel consumption using the first consumption energy. On the other hand, when the destination is a specific destination, the energy consumption of the electric vehicle 100 is estimated using the first consumption energy and the second consumption energy. More specifically, the sum of the first consumption energy and the second consumption energy is the overall energy consumption of the electric vehicle 100. Therefore, when the destination is a specific destination, the discharge/charge schedule setting unit 45 sets a discharge/charge schedule until the specific destination is reached using the first consumption energy and the second consumption energy. In particular, when the destination is a specific destination, the discharge/charge main module setting unit 45 sets a discharge/charge schedule so that the battery 12 holds power equivalent to the second consumption energy at the time of arrival at the specific destination. The charging and discharging schedule also takes into consideration the energy consumption associated with warming up the engine 14 when it is started and air conditioning for the electric vehicle 100 (so-called HVAC (Heating, Ventilation, and Air Conditioning)).

[Second method for estimating energy consumption]
Fig. 4 is a block diagram showing the configuration of the second energy consumption estimation unit 44. As shown in Fig. 4, the second energy consumption estimation unit 44 includes a basic information acquisition unit 50, a running time estimation unit 56, and a unit energy consumption calculation unit 57.

The basic information acquisition unit 50 acquires information used in the calculations of the driving time estimation unit 56 and the unit energy consumption calculation unit 57, or calculates the information. The basic information acquisition unit 50 includes, for example, a driving history classification unit 51, a congestion degree acquisition unit 52, a width estimation unit 53, an altitude estimation unit 54, and a driving tendency analysis unit 55.

The driving history classification unit 51 acquires the location of the specific destination, the location information of the entrance to the unknown route section 36 that can be entered (merged) directly from the specific destination without passing through the clear route section 35, and the unknown route section driving history 21 from the route information 17 and/or the driving history 20. The entrance to the unknown route section 36 is a point that can become a specific destination. When there are multiple entrances to a substantially identical unknown route section 36, the driving history classification unit 51 classifies the unknown route section driving history 21 related to the unknown route section 36 by each of the entrances. In this way, the driving history classification unit 51 extracts the unknown route section driving history 21 when entering the unknown route section 36 from the current destination (specific destination).

For example, suppose that there are two entrances to the multi-storey car park 33 (see FIG. 2), a first entrance (not shown) and a second entrance (not shown). In this case, the driving history classification unit 51 classifies the unknown route section driving history 21 for the multi-storey car park 33 into the unknown route section driving history when entering the multi-storey car park 33 from the first entrance, and the unknown route section driving history when entering the multi-storey car park 33 from the second entrance. Then, when the parking lot entrance 34, which is the current destination (specific destination), is the first entrance, the unknown route section driving history when entering from the first entrance is identified from the entire unknown route section driving history 21 for the unknown route section 36 of the multi-storey car park 33.

When the unknown route section driving history 21 is stored in a state classified by the entrance to the unknown route section 36, the driving history classification unit 51 selects the unknown route section driving history 21 to be used for estimating the second energy consumption according to the current specific destination.

As described above, when the unknown route section driving history 21 is classified according to the entrance in this manner and the unknown route section driving history when entering from the current specific destination is identified, the second energy consumption is estimated using the identified unknown route section driving history.

The congestion degree acquisition unit 52 acquires the congestion degree 18 of the unknown route section 36 from the navigation system 16 by the information acquisition unit 41. For example, when the parking lot entrance 34 is the current destination (specific destination), the congestion degree 18 for the multi-story parking lot 33 is acquired. The congestion degree 18 of the unknown route section 36 is used to estimate the travel time in the unknown route section 36.

The width estimation unit 53 estimates the width of the unknown route section 36 entered from a specific destination based on the unknown route section driving history 21, etc. For example, when entering the unknown route section 36 of the multi-storey car park 33 from the specific destination, which is the parking lot entrance 34 (see FIG. 2), the width (total area, etc.) of the multi-storey car park 33 is estimated. The width of the unknown route section 36 is estimated, for example, based on the history of the distance traveled in the unknown route section 36. In this case, the average or maximum value of the distance traveled in the unknown route section 36 is calculated based on the corresponding unknown route section driving history 21, and the calculated average value of the distance traveled is used as a parameter representing the width of the unknown route section 36 (hereinafter referred to as the estimated width). The estimated width is used to estimate the travel time in the unknown route section 36.

The altitude estimation unit 54 estimates the altitude of the unknown route section 36 entered from the specific destination based on the unknown route section driving history 21, etc. In particular, the altitude estimation unit 54 estimates the maximum altitude among the altitude information of the unknown route section driving history 21 as the height of the facility in the unknown route section 36. For example, when entering the unknown route section 36 of the multi-storey parking lot 33 from the parking lot entrance 34, which is the specific destination (see FIG. 2), the altitude of the multi-storey parking lot 33 (e.g., the altitude of each floor) is estimated using the altitude information included in the unknown route section driving history 21. In particular, the maximum altitude among the altitude information included in the unknown route section driving history 21 in the multi-storey parking lot 33 is estimated as the facility in the unknown route section 36, that is, the altitude of the multi-storey parking lot 33. The altitude of the unknown route section 36 estimated by the altitude estimation unit 54 (hereinafter referred to as the estimated altitude) is used to estimate the driving time in the unknown route section 36 and to calculate the energy consumption per unit time in the unknown route section 36. In this embodiment, the height of the facility in the unknown route section 36 (the height of the parking structure 33) based on the unknown route section driving history 21 is used as the estimated altitude when estimating the driving time and calculating the energy consumption per unit time.

The driving tendency analysis unit 55 analyzes the tendency of driving in the unknown route section 36 (hereinafter referred to as the driving tendency) based on the unknown route section driving history 21 and the like. The driving tendency is the personal tendency of the occupant of the electric vehicle 100 when driving in the unknown route section 36. The personal tendency of the occupant refers to the bias of the driving pattern in the unknown route section 36 that is expressed due to the personality of the occupant, etc. For example, the unknown route section driving history 21 may show a tendency to preferentially use vacant parking spaces in the multi-storey parking lot 33, etc. This is the result of the occupant of the electric vehicle 100 having a driving tendency to prioritize shortening the time required to park. Conversely, the unknown route section driving history 21 may show a tendency to wait for a parking space near the target facility (for example, the first building 31) to become available. This is the result of the occupant of the electric vehicle 100 having a driving tendency to prioritize shortening the walking time until re-boarding after getting off, even if the multi-storey parking lot 33, etc. is crowded. Similar driving tendencies may also be seen with regard to which floor of the multi-storey car park 33 the occupant chooses to park on. In other words, the occupant has driving tendencies, such as whether to prioritize driving time of the electric vehicle 100 or walking time. The driving tendencies that are the analysis results are used to estimate the driving time in the route unknown section 36.

The travel time estimation unit 56 estimates the travel time in the unknown route section 36 based on the estimated width, congestion level 18, estimated altitude, and/or travel tendency of the unknown route section 36. The second energy consumption is calculated using this estimated travel time in the unknown route section 36 (hereinafter referred to as the estimated travel time).

The estimated travel time is correlated with the estimated width and estimated altitude of the unknown route section 36. Therefore, the estimated travel time can be calculated using the estimated width and/or estimated altitude of the unknown route section 36. For example, the larger the estimated width of the unknown route section 36, the longer the estimated travel time. Also, the higher the estimated altitude of the unknown route section 36, the longer the estimated travel time.

The more congested the unknown route section 36 is, the longer the travel time in the unknown route section 36 will be. For this reason, the estimated travel time is corrected according to the congestion degree 18 so that the higher the congestion degree 18 is, the longer the estimated travel time will be.

In addition, when a passenger has a particular driving tendency, the estimated travel time is corrected to match that driving tendency. For example, when a passenger has a driving tendency that prioritizes shortening walking time, the estimated travel time is corrected to be longer. On the other hand, when a passenger has a driving tendency that prioritizes shortening riding time, the estimated travel time is corrected to be shorter.

When the unknown route section driving history 21 is classified by entrance to the unknown route section 36, the unknown route section driving history 21 in which each of the above parts is classified by entrance is used. Therefore, the estimated width, congestion degree 18, estimated altitude, and/or driving tendency of the unknown route section 36 are estimated according to the entrance into the unknown route section 36. As a result, when the unknown route section driving history 21 is classified by entrance into the unknown route section 36, the estimated driving time is estimated according to the entrance into the unknown route section 36, i.e., according to the position of the specific destination.

The unit energy consumption calculation unit 57 calculates the energy consumed per unit time when the electric vehicle 100 travels through the unknown route section 36 (hereinafter referred to as unit energy consumption) based on the unknown route section travel history 21. The unit energy consumption is generally determined by the vehicle speed of the electric vehicle 100. For this reason, the unit energy consumption calculation unit 57 can calculate the average or maximum vehicle speed in the unknown route section 36 based on the unknown route section travel history 21, for example, and calculate the unit energy consumption according to the average vehicle speed calculated in this way. However, since most of the unknown route section 36 is within a multi-storey car park 33 or other private property and is not a public road, the electric vehicle 100 generally drives slowly in the unknown route section 36. For this reason, the vehicle speed and unit energy consumption in the unknown route section 36 can be considered to be approximately constant without undergoing the above-mentioned calculation. In this embodiment, the vehicle speed in the unknown route section 36 is uniformly considered to be a predetermined slow speed, and the unit energy consumption corresponding to this predetermined slow speed is used as the standard.

The unit energy consumption calculation unit 57 also estimates the potential energy that the electric vehicle 100 will gain or lose when traveling through the unknown route section 36, based on the estimated altitude. The unit energy consumption is then corrected based on the increase or decrease in this estimated potential energy. For example, in the multi-storey car park 33, the altitude of the electric vehicle 100 changes, so the electric vehicle 100 gains or loses energy equivalent to the potential energy before it is parked. For this reason, when it is expected that the electric vehicle 100 will consume energy equivalent to the potential energy before parking, the unit energy consumption is corrected to be higher by that amount. On the other hand, when it is expected that the electric vehicle 100 will gain energy equivalent to the potential energy before parking in an underground car park or the like, the unit energy consumption is corrected to be lower by that amount.

The second energy consumption estimation unit 44 calculates the second energy consumption based on the above-mentioned estimated running time and unit energy consumption. For example, the second energy consumption is calculated as the product of the estimated running time and unit energy consumption.

The operation of the electric vehicle 100 configured as described above will be described below. FIG. 5 is a flowchart showing the operation of the electric vehicle 100. As shown in FIG. 5, in step S101, route information 17 is acquired in response to, for example, the setting or change of a destination by the occupant. For this reason, in step S102, the energy consumed until the destination is reached (first consumed energy) is estimated. On the other hand, in step S103, the characteristics of the set destination are determined with respect to whether the set destination is a specific destination. That is, it is determined whether further energy consumption is required by traveling through the unknown route section 36 after arriving at the set destination. If, as a result of this determination in step S104, the destination is a specific destination, in step S105, the unknown route section travel history 21 is acquired for the unknown route section 36 related to the specific destination. When there are multiple entrances to the unknown route section 36, the unknown route section travel history 21 is classified according to the entrance when it is acquired in this manner.

In the next step S106, the congestion level of the unknown route section 36 is obtained. In step S107, the width of the unknown route section 36 is estimated, and in step S108, the altitude of the unknown route section 36 is estimated. In step S109, the driving tendency of the occupant is analyzed with respect to driving in the unknown route section 36.

Then, in step S110, the travel time in the unknown route section 36 is estimated based on the estimated width, congestion level 18, estimated altitude, and travel tendency of the unknown route section 36. In addition, in step S111, the unit energy consumption for travel in the unknown route section 36 is calculated. As a result, in step S112, the second energy consumption, which is the energy consumed in the unknown route section 36, is estimated based on the estimated travel time and unit energy consumption in the unknown route section 36.

When the first and second consumed energies are estimated as described above, a discharge and charge schedule is set in step S113. That is, a discharge and charge schedule is set until the specific destination is reached using the first and second consumed energies so that the battery 12 has power equivalent to the second consumed energy at the time of arrival at the specific destination.

Then, in step S114, control is performed according to a charging/discharging schedule that takes into account this second consumed energy. That is, the engine 14 is driven and the battery 12 is charged at appropriate times along the travel route so that fuel economy and/or electricity efficiency are optimized while leaving power equivalent to the second consumed energy at the time of arrival at the specific destination.

When the destination set in step S104 is not a specific destination, the calculations for estimating the second consumed energy in steps S105 to S111 and the estimation of the second consumed energy in step S112 are omitted. Therefore, in step S113, a charging/discharging schedule is set based on the first consumed energy. Therefore, when control according to this charging/discharging schedule is executed in step S114, fuel economy and/or electricity consumption are optimized for the journey to the destination.

As described above, the electric vehicle control method according to the present embodiment is executed by an electric vehicle 100 including a drive motor 10 as a drive source and a battery 12 that supplies power to the drive motor 10. In this electric vehicle control method, the energy consumed by the electric vehicle 100 during travel is estimated, and control related to discharging or charging the battery 12 is executed based on the estimated energy consumption. In addition, in this electric vehicle control method, route information 17 related to a travel route until arriving at a preset destination is acquired, and the route information 17 is used to estimate a first energy consumption, which is the energy consumed until arriving at the destination. In addition, when the destination is a specific destination that requires further energy consumption by travelling through an unknown route section 36 where no information on the route exists after arrival, a travel history 20 (unknown route section travel history 21) of the unknown route section 36 is acquired. Then, using this unknown route section travel history 21, a second energy consumption, which is the energy consumed until the electric vehicle 100 is parked after arriving at the specific destination, is estimated.

As a result, even when further energy consumption is required after arriving at the destination by traveling through an unknown route section 36 where there is no route information 17, such as a multi-story parking garage 33, this additional energy consumption is taken into consideration and the energy consumption is accurately estimated. In other words, according to the electric vehicle control method of this embodiment, the accuracy of estimating the energy consumption is improved. As a result, the electric vehicle 100 has better electricity consumption and/or fuel economy than conventional electric vehicles.

In addition, in the electric vehicle control method according to this embodiment, the first consumption energy and the second consumption energy are used as described above to set a schedule for discharging or charging the battery 12 until the specific destination is reached so that the battery 12 has power equivalent to the second consumption energy at the time of arrival at the specific destination.

In this way, the highly accurate estimation result of the consumed energy using the second consumed energy in addition to the first consumed energy is used to set the charging schedule, so that a more accurate battery charging and discharging schedule can be set than when the second consumed energy is not taken into consideration. This battery charging and discharging schedule is set so that the battery 12 has power equivalent to the second consumed energy at the time of arrival at the specific destination. As a result, in the unknown route section 36 (e.g., the unknown route section 36 of the multi-storey car park 33) entered from the specific destination (e.g., the parking lot entrance 34), the electric vehicle 100 can run only with the power of the battery 12 without driving the engine 14 for charging. Since the vehicle is often driven slowly in the unknown route section 36 as described above, a relatively high sound vibration performance is required compared to when driving on a public road. This is because the sound vibration caused by the driving of the engine 14 becomes relatively more noticeable as the vehicle speed is suppressed by driving slowly. As described above, by making it possible to reliably travel through the unknown route section 36 using only the power of the battery 12, the sound and vibration performance requirements ("EVness") expected of the electric vehicle 100 in the unknown route section 36 are reliably met.

In the electric vehicle control method according to this embodiment, when the electric vehicle 100 is equipped with an engine 14 used to charge the battery 12, the engine 14 is driven according to a set discharge/charge schedule. That is, when the electric vehicle 100 is an HEV, the operation of the engine 14 is controlled according to the discharge/charge schedule. As a result, when the discharge/charge schedule is set using the second consumption energy, the discharge/charge of the battery 12 is automatically optimized. As a result, fuel efficiency and/or electricity consumption are improved.

In the electric vehicle control method according to this embodiment, the driving history of the unknown route section 36 (unknown route section driving history 21) is used to estimate the driving time of the unknown route section 36, and the second consumed energy is estimated based on this driving time. In this way, by calculating the estimated driving time using the unknown route section driving history 21, the second consumed energy is estimated particularly accurately.

In the electric vehicle control method according to this embodiment, the congestion degree 18 of the unknown route section 36 is acquired, and the travel time (estimated travel time) of the unknown route section 36 is corrected according to the congestion degree 18. This allows the travel time of the unknown route section 36 to be estimated more accurately. As a result, the accuracy of the second energy consumption is improved.

In the electric vehicle control method according to this embodiment, the driving tendency in the unknown route section 36 is analyzed using the driving history of the unknown route section 36, and the driving time is corrected according to the driving tendency. This allows the driving time in the unknown route section 36 to be estimated more accurately. As a result, the accuracy of the second energy consumption is improved.

In the electric vehicle control method according to this embodiment, when the same unknown route section 36 has multiple entrances that can be specific destinations, the driving history 20 (unknown route section driving history 21) of the unknown route section 36 is classified by entrance, and the driving time is estimated according to the entrance. In this way, when there are multiple entrances to the unknown route section 36, the accuracy of the estimated driving time is improved by estimating the driving time in the unknown route section 36 according to the entrance at which the unknown route section 36 is entered. As a result, the accuracy of the second consumed energy is improved.

In the electric vehicle control method according to this embodiment, the driving history 20 (unknown route section driving history 21) of the unknown route section 36 includes altitude information, which is information on the altitude at which the electric vehicle 100 has traveled or parked, and the second consumed energy is estimated based on the altitude information. In this way, when the altitude information of the unknown route section 36 is taken into consideration, firstly, the second consumed energy is accurately estimated even for a three-dimensional unknown route section 36 such as a multi-story parking garage 33 or an underground parking garage. In particular, the second consumed energy is accurately estimated even when the electric vehicle 100 gains or loses energy equivalent to potential energy by traveling through the unknown route section 36.

Furthermore, in the electric vehicle control method according to this embodiment, the maximum altitude among the altitude information is estimated as the height of the facility in the unknown route section 36, and the second consumed energy is estimated including the potential energy equivalent to the height of the facility in the unknown route section 36. In this way, by using the maximum altitude included in the unknown route section driving history 21, it is possible to reliably leave enough power in the battery 12 to travel through the unknown route section 36 using only electric power, even if the altitude at which the electric vehicle 100 will actually be parked in the future is uncertain.

In the electric vehicle control method according to this embodiment, whether or not the destination is a specific destination is determined based on the driving pattern indicated by the driving history 20 (unknown route section driving history 21) of the unknown route section 36. Then, when it is determined that the destination is a specific destination, the second consumed energy is estimated. In this way, when it is determined that the destination is a specific destination based on the past driving pattern, the accuracy of the determination is particularly improved. As a result, the estimation of the consumed energy becomes particularly accurate.

The electric vehicle 100 according to the above embodiment is a series hybrid vehicle, but the present invention can also be suitably implemented in other types of HEVs, such as parallel type, and in electric vehicles (BEVs: Battery Electric Vehicles) that do not have an engine 14 for charging the battery 12.

For example, when the electric vehicle 100 is a BEV, the charging/discharging schedule set based on the consumed energy in the above embodiment is a schedule that suggests to the occupant that the battery 12 be charged. This schedule suggestion is left unattended, for example, by display on the display screen of the navigation system 16 or on the instrument panel of the electric vehicle 100, or by sound or voice. That is, when the battery 12 can be charged by an external power source, the occupant of the electric vehicle 100 is notified that the battery 12 should be charged by an external power source according to the charging/discharging schedule that takes into account the second consumed energy. In this way, by notifying the occupant that the battery 12 should be charged when the battery 12 can be charged by an external power source, it is possible to make the battery 12 hold power equivalent to the second consumed energy at the time of arrival at the specific destination, as in the above embodiment.

The notification that the battery 12 should be charged includes notification of charging stations on or near the driving route, and notification of the required charge amount. The electric vehicle 100 can also communicate with the charging station via the controller 15 and automatically set the required charge amount at the time of charging. For example, when charging the battery 12 while the occupant is shopping in a multi-storey car park 33, an appropriate charge amount less than full charge can be set, taking into account the potential energy acquired as regenerative power when leaving the multi-storey car park 33. This reduces the waste of energy consumption.

The present invention is also suitable when the electric vehicle 100 is a plug-in hybrid electric vehicle (PHEV) that combines the features of both an HEV and a BEV. In addition, although the electric vehicle 100 in the above embodiment is an automobile, the present invention is also suitable for motorcycles and other vehicles.

In the above embodiment, an example was given of visiting a shopping mall 30 having a multi-storey car park 33 with an electric vehicle 100, but this is not limited to this. For example, the present invention is also suitable for visiting facilities having an unknown route section 36 with no route information 17, such as companies or factories with vast premises, and other private land.

Although the embodiments of the present invention have been described above, the configurations described in the above embodiments merely show some of the application examples of the present invention and are not intended to limit the technical scope of the present invention. For example, the power generation device composed of the generator motor 13 and the engine 14 can be replaced with another power generation device or system that generates electricity, such as a solid oxide fuel cell (SOFC). In addition, the electric vehicle 100 can obtain route information 17, etc., from systems other than the navigation system 16 (for example, systems outside the electric vehicle 100) through communication. In addition, the controller 15 may incorporate some or all of the functions of the navigation system 16.

10: Drive motor 12: Battery 13: Generator motor 14: Engine 15: Controller 16: Navigation system 17: Route information 18: Congestion level 19: Driving history database 20: Driving history 21: Unknown route section driving history 30: Shopping mall 33: Multi-storey car park 34: Car park entrance 35: Clear route section 36: Unknown route section 37: Parking position 41: Information acquisition unit 42: First energy estimation unit 43: Destination type determination unit 44: Second energy consumption estimation unit 45: Discharge/charge schedule setting unit 51: Driving history classification unit 52: Congestion level acquisition unit 53: Area estimation unit 54: Altitude estimation unit 55: Driving tendency analysis unit 56: Driving time estimation unit 57: Unit energy consumption calculation unit

Claims (11)

An electric vehicle control method is executed in an electric vehicle including a motor as a driving source for traveling and a battery that supplies power to the motor, the method estimating energy consumption due to traveling of the electric vehicle, and executing control related to discharging or charging of the battery based on the estimated energy consumption,
Obtaining route information regarding the driving route to arrive at a preset destination,
Using the route information, estimate a first consumed energy, which is energy consumed until arriving at the destination;
When the destination is a specific destination that requires further consumption of energy after arrival by traveling through an unknown route section where there is no information about the route,
Acquire a driving history of the route unknown section;
Using the travel history of the unknown route section, estimate a second consumed energy, which is energy consumed from the arrival at the specific destination until the electric vehicle is parked;
estimating the energy consumption of the electric vehicle using the first consumed energy and the second consumed energy;
setting a schedule for discharging or charging the battery until the specific destination is reached, using the first consumed energy and the second consumed energy, so that the battery holds power equivalent to the second consumed energy at the time of arriving at the specific destination;
An electric vehicle control method. 2. The electric vehicle control method according to claim 1 ,
When the electric vehicle includes a power generation device used for charging the battery, the power generation device is driven according to the schedule.
An electric vehicle control method. 2. The electric vehicle control method according to claim 1 ,
when the battery is chargeable by an external power source, notifying an occupant of the electric vehicle that the battery should be charged by the external power source according to the schedule;
An electric vehicle control method. The electric vehicle control method according to any one of claims 1 to 3 ,
estimating a travel time for the unknown route section using a travel history for the unknown route section;
The second consumed energy is estimated based on the running time.
An electric vehicle control method. The electric vehicle control method according to claim 4 ,
Obtain a congestion degree of the route unknown section;
The travel time is corrected according to the congestion degree.
An electric vehicle control method. The electric vehicle control method according to claim 4 or 5 ,
Analyzing a driving tendency in the unknown route section using a driving history of the unknown route section;
The driving time is corrected according to the driving tendency.
An electric vehicle control method. The electric vehicle control method according to any one of claims 4 to 6 ,
When there are a plurality of entrances that can be the specific destination in the same route unknown section,
The driving history of the route unknown section is classified by the entrance,
The travel time is estimated according to the entrance.
An electric vehicle control method. The electric vehicle control method according to any one of claims 1 to 7 ,
The travel history of the unknown route section includes altitude information that is information regarding an altitude at which the electric vehicle traveled or was parked,
The second consumed energy is estimated based on the altitude information.
An electric vehicle control method. 9. The electric vehicle control method according to claim 8 ,
Estimating the maximum altitude of the altitude information as the height of the facility in the route unknown section;
The second consumed energy is estimated including potential energy corresponding to a height of a facility in the unknown route section.
An electric vehicle control method. The electric vehicle control method according to any one of claims 1 to 9 ,
determining whether the destination is the specific destination based on a driving pattern indicated by a driving history of the unknown route section;
When the destination is determined to be the specific destination, the second consumed energy is estimated.
An electric vehicle control method. An electric vehicle control device that controls traveling of an electric vehicle including a motor as a traveling drive source and a battery that supplies power to the motor, estimates energy consumption due to the traveling of the electric vehicle, and executes control related to discharging or charging of the battery based on the estimated energy consumption,
Obtaining route information regarding the driving route to arrive at a preset destination,
Using the route information, estimate a first consumed energy, which is energy consumed until arriving at the destination;
When the destination is a specific destination that requires further consumption of energy after arrival by traveling through an unknown route section where there is no information about the route,
Acquire a driving history of the route unknown section;
Using the travel history of the unknown route section, estimate a second consumed energy, which is energy consumed from the arrival at the specific destination until the electric vehicle is parked;
estimating the energy consumption of the electric vehicle using the first consumed energy and the second consumed energy;
setting a schedule for discharging or charging the battery until the specific destination is reached, using the first consumed energy and the second consumed energy, so that the battery holds power equivalent to the second consumed energy at the time of arriving at the specific destination;
Electric vehicle control device.