Vehicle control device

Abstract

To enable a predicted power cost in future travel to be calculated suitably while considering the use of an air conditioner not in a driving period.SOLUTION: A vehicular control device controls a vehicle which comprises a motor driven by power from a battery, and an air conditioner operated by power from the battery. The control device comprises a processor. The processor is so constituted as to execute calculation processing for calculating the predicted power cost of a vehicle in future not during a vehicle travel period. In the calculation processing, the processor corrects a basic value of the predicted power cost on the basis of past air conditioning operation information of a vehicle, and one or a plurality of other vehicles.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present disclosure relates to a control device for a vehicle. [Background technology]

[0002] Patent Document 1 discloses a technology for calculating a vehicle's mileage based on its electric power consumption and remaining battery charge. This electric power consumption, more specifically, is the actual electric power consumption, which is calculated by taking into account the actual power consumed by the vehicle while traveling as well as the power consumption of electrical components. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2018-064329 Summary of the Invention [Problem to be solved by the invention]

[0004] The technology described in Patent Document 1 cannot predict future electricity consumption during driving while taking into account the use of the air conditioning system when the vehicle is not in a driving period, such as when charging. As such, there is room for improvement in the application of the technology to calculating predicted electricity consumption outside of a driving period.

[0005] The present disclosure has been made in consideration of the above-mentioned problems, and aims to provide a vehicle control device that can appropriately calculate predicted electricity consumption for future driving when the driving period is not in progress, taking into account the use of the air conditioning system. [Means for solving the problem]

[0006] A vehicle control device according to the present disclosure controls a vehicle equipped with an electric motor driven by power from a battery and an air conditioner operated by power from the battery. The control device includes a processor. The processor is configured to execute a calculation process to calculate a predicted electric fuel consumption of the vehicle for future travel when the vehicle is not currently traveling. In the calculation process, the processor corrects a base value of the predicted electric fuel consumption based on past air conditioning operation information of at least one of the vehicle and one or more other vehicles. [Effects of the Invention]

[0007] According to the present disclosure, when the vehicle is not currently in a driving period, it is possible to appropriately calculate predicted electricity consumption for future driving while taking into account the use of the air conditioner. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a diagram illustrating a schematic configuration of a vehicle according to an embodiment. [Figure 2] 5 is a flowchart showing an example of a process for calculating a predicted electricity consumption Ep and displaying a cruising range L based on the calculated predicted electricity consumption Ep according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] 1. Example of vehicle configuration 1 is a diagram that schematically illustrates the configuration of a vehicle 10 according to an embodiment. Vehicle 10 is a battery electric vehicle (BEV) that includes a battery 12 and an electric motor 14. Vehicle 10 is capable of electric running (EV running) using electric motor 14 that is driven by power from battery 12. The "vehicle" according to the present disclosure may be any vehicle that is capable of electric running, and may be, for example, a plug-in hybrid electric vehicle (PHEV).

[0010] The vehicle 10 further includes an air conditioning system 16, a power control unit (PCU) 18, an electronic control unit (ECU) 20, sensors 22, a navigation system 24, and a display device 26.

[0011] The air conditioner 16 operates using power from the battery 12 and performs air conditioning, more specifically, at least one of cooling and heating, of the interior of the vehicle 10. The PCU 18 is a power conversion device that includes an inverter for driving the electric motor 14. The PCU 18 controls the electric motor 14 using the power from the battery 12 based on commands from the ECU 20.

[0012] The ECU 20 is a computer that controls the vehicle 10 and corresponds to an example of a "vehicle control device" according to the present disclosure. The ECU 20 includes a processor 28 and a storage device 30. The processor 28 executes various processes. The various processes include processes related to the control of the electric motor 14 and the air conditioning device 16, and processes related to the display of the predicted electricity consumption Ep and the cruising range L based on the predicted electricity consumption Ep, which will be described later. The storage device 30 stores various information required for the processes performed by the processor 28. The various processes performed by the ECU 20 are realized by the processor 28 executing a computer program. The computer program is stored in the storage device 30. Alternatively, the computer program may be recorded on a computer-readable recording medium. The ECU 20 operates, for example, using power from an auxiliary battery (not shown). The ECU 20 may be configured by combining multiple ECUs.

[0013] The sensors 22 include, for example, an outside air temperature sensor, a vehicle interior temperature sensor, a battery current sensor, and a power sensor. The battery current sensor detects the charge / discharge current of the battery 12. The ECU 20 calculates the state of charge (SOC) of the battery 12 based on the detected charge / discharge current. The power sensor detects the power consumption (air conditioning power consumption) Pac of the air conditioner 16. The navigation device 24 is also configured to be able to communicate with external systems via a wireless communication network, and can acquire various information from the external systems.

[0014] The various information described above includes vehicle environment information I2 related to the use of the air conditioning. Specifically, the vehicle environment information I2 is information related to various parameters that indicate the environment surrounding the vehicle 10, such as the vehicle, driving environment, and driving conditions. The various parameters are acquired using, for example, the sensors 22 and the navigation device 24, and include, for example, the outside air temperature, the day of the week, the time, and the temperature inside the vehicle cabin. In addition, the various parameters correspond to explanatory variables related to the operation of the air conditioning by the occupants of the vehicle 10.

[0015] The display device 26 is, for example, a display such as a meter panel mounted on the instrument panel of the vehicle 10. The display device 26 displays, for example, the cruising range L. Note that the "display device" according to the present disclosure does not necessarily have to be mounted on the vehicle, and may be, for example, a communication terminal operated by a vehicle occupant.

[0016] 2. Calculation of predicted electricity consumption and display of possible driving range based on this In this embodiment, the ECU 20 (processor 28) executes a "calculation process PR1" to display the cruising range L on the display device 26 when the vehicle 10 is not in a driving period. Here, "when the vehicle 10 is not in a driving period" refers to a period when the system of the vehicle 10 is not running, for example, when the vehicle 10 (battery 12) is being charged, as exemplified below. Another example of "when the vehicle is not in a driving period" is when the vehicle is stopped and not being charged. The cruising range L refers to the distance (cruising distance) that can be traveled by electric driving using the remaining battery capacity Wb of the battery 12.

[0017] Calculation process PR1 is executed by ECU 20, which is operated by the auxiliary battery, when the system of vehicle 10 is not activated. According to calculation process PR1, predicted electricity consumption Ep of vehicle 10 for future travel is calculated. "Electricity consumption" is an electricity consumption rate, and is specified, for example, as the amount of electricity per unit distance [Wh / km]. "Future travel" here refers, for example, to the next scheduled travel.

[0018] In calculation process PR1, ECU 20 corrects basic value Epb of predicted power consumption Ep based on air conditioning operation information I during past travel of vehicle 10. More specifically, "air conditioning operation information I" is, for example, information regarding operation of air conditioning device 16 by a passenger such as a driver during one or more past trips of vehicle 10.

[0019] More specifically, the air conditioning operation information I includes air conditioning operation result information I1 and the above-mentioned vehicle environment information I2. Based on the air conditioning operation result information I1 and the vehicle environment information I2, the ECU 20 executes a "learning process PR2" to learn an air conditioning operation probability X, which is the probability that an air conditioning operation will be performed during future travel (more specifically, during a future trip). The air conditioning operation probability X is, for example, a number between 0 and 1, inclusive, in other words, a number between 0% and 100%.

[0020] Then, in calculation process PR1, ECU 20 calculates air-conditioning electric power cost correction amount Cac, which is a correction amount for electric power cost Eac of air conditioner 16, based on the product of air-conditioning operation probability X learned in learning process PR2 and air-conditioning electric power consumption. Then, ECU 20 corrects base value Epb of predicted electric power cost Ep by air-conditioning electric power cost correction amount Cac.

[0021] 2 is a flowchart showing an example of a process related to calculation of predicted electricity efficiency Ep and display of the resulting cruising range L according to the embodiment. The process of this flowchart starts when the system of vehicle 10 is started, that is, when the driver turns on the power switch (ignition switch) of vehicle 10.

[0022] In step S100, the ECU 20 (processor 28) acquires the air conditioning operation result information I1 and the vehicle environment information I2.

[0023] The air conditioning operation result information (or simply, operation result information) I1 is information regarding the results of the air conditioning operation performed by the occupant while the vehicle system is ON, i.e., during the current trip of the vehicle 10. For example, the operation result information I1 is a signal from an operating device of the air conditioner 16 operated by the occupant (e.g., a signal indicating ON / OFF of the air conditioning). Alternatively, the operation result information I1 may be, for example, the air conditioning power consumption Pac detected by the above-mentioned power sensor, or the time-integrated value of the air conditioning power consumption Pac. The processing of this step S100 is repeatedly executed while the vehicle system is ON (S102; No). Therefore, the operation result information I1 is repeatedly acquired during the current trip. As a result, information regarding the occupant's use history of the air conditioning during the current trip is acquired as the operation result information I1.

[0024] Furthermore, the acquisition of various parameters included in the vehicle environment information I2, such as the outside air temperature, day of the week, time, and cabin temperature, does not necessarily have to be performed repeatedly during the current trip; for example, it may be performed only once during the current trip. In addition, the acquired vehicle environment information I2 may also include information identifying the occupants, such as the driver of the vehicle 10, because the way the air conditioning is used varies depending on the occupant. The occupant can be identified, for example, by using images from an interior camera.

[0025] On the other hand, if ECU 20 determines in step S102 that the vehicle system has been turned off (ignition OFF), processing proceeds to step S104. In step S104, ECU 20 executes the above-mentioned learning process PR2. The method for learning the air conditioning operation probability X using learning process PR2 is not particularly limited, but this learning can be performed using, for example, an air conditioning operation probability model. This air conditioning operation probability model is a machine learning model constructed using the above-mentioned various parameters (multiple parameters) included in vehicle environment information I2 as input and the air conditioning operation probability X as output. The air conditioning operation probability model is learned using the learning data acquired during the most recent trip in step S100, i.e., the above-mentioned various parameters as explanatory variables (input) and operation result information I1 as a target variable.

[0026] According to the processing of step S104 described above, learning of the air conditioning operation probability model progresses each time a trip of vehicle 10 ends. In this way, learning of the air conditioning operation probability model is performed using operation result information I1 and vehicle environment information I2 from multiple past trips.

[0027] In step S106 following step S104, the ECU 20 determines whether the vehicle 10 is being charged. This determination can be made, for example, based on the charge / discharge current of the battery 12 detected by the battery current sensor described above. As a result, if the vehicle 10 is not being charged (step S106; No), the process proceeds to END. On the other hand, if the vehicle 10 is being charged (step S106; Yes), the process proceeds to step S108.

[0028] In step S108, the ECU 20 calculates the air conditioning operation probability X for the next scheduled driving time. Specifically, the ECU 20 calculates the air conditioning operation probability X from the air conditioning operation probability model and the predicted values ​​of the various parameters described above for the next scheduled driving time. The "predicted parameter values" here refer to predicted values ​​of the outside air temperature, day of the week, time, and cabin temperature for the next scheduled driving time, which are obtained using, for example, the following method.

[0029] Here, the navigation device 24 receives input of information regarding the next travel plan from the user of the vehicle 10. The input information includes, for example, the day of the week and departure time when the vehicle 10 is planned to be used, as well as the departure point and destination. The navigation device 24 generates travel route information from the departure point to the destination based on the input information. The travel route information includes, for example, a predicted arrival time at the destination, and the distance (trip distance) and time (trip time) from the departure point to the destination. Based on such travel route information for the next planned travel, the navigation device 24 acquires, for example, the time period for the next planned travel, and acquires (estimates) the outside air temperature and interior temperature for that time period from weather forecast information for that time period (e.g., air temperature and solar radiation). The ECU 20 then acquires predicted values ​​of various parameters, such as the outside air temperature, from the navigation device 24.

[0030] The input information from the user may be acquired using, for example, a mobile terminal of the user. At least a part of the process for calculating the predicted value based on the input information may be executed by the ECU 20 that acquires the input information from the navigation device 24 or the mobile terminal, instead of the navigation device 24 or the mobile terminal.

[0031] Next, in step S110, ECU 20 calculates the air conditioning power cost correction amount Cac based on the product of the air conditioning operation probability X calculated in step S108 and the air conditioning power consumption Pac. Specifically, the air conditioning power consumption Pac used in this calculation is a pre-calculated value, such as the rated power consumption of the air conditioner 16. Alternatively, the air conditioning power consumption Pac may be, for example, a learned value. As with the air conditioning operation probability X, the learned value may be calculated using an air conditioning power consumption model that is learned based on the various parameters included in the above-mentioned vehicle environment information and the operation result information I1. In other words, the learned value may be calculated from the air conditioning power consumption model and predicted values ​​of the various parameters for the next scheduled driving time.

[0032] Then, in step S110, ECU 20 calculates the air conditioning power cost correction amount Cac [Wh / km] by multiplying the product of the air conditioning operation probability X (0≦X≦1) and the air conditioning power consumption Pac [W] by a conversion coefficient k1. Coefficient k1 can be obtained, for example, by dividing the trip time included in the travel route information used in step S108 by the trip distance.

[0033] Next, in step S112, ECU 20 calculates predicted electricity consumption Ep. The predicted electricity consumption Ep is calculated, for example, by subtracting the air-conditioning electricity cost correction amount Cac from the basic value Epb of the predicted electricity consumption Ep. That is, the predicted electricity consumption Ep is calculated by correcting the basic value Epb with the air-conditioning electricity cost correction amount Cac. The method of calculating the basic value Epb is not particularly limited, and for example, the basic value Epb may be calculated using travel route information including information on the travel load of the next planned travel route. Note that the predicted electricity consumption Ep may be corrected using one or more other correction amounts in addition to the air-conditioning electricity cost correction amount Cac.

[0034] Next, in step S114, the ECU 20 calculates the cruising range L. Specifically, the ECU 20 calculates the remaining battery capacity (current battery capacity) Wb [Wh] by multiplying the current charging rate SOC [%] of the battery 12 by the battery capacity of the battery 12 when fully charged. Next, the ECU 20 calculates the cruising range L by dividing the remaining battery capacity Wb by the predicted electricity consumption Ep calculated in step S112. Then, the ECU 20 causes the display device 26 to display the calculated cruising range L.

[0035] The air conditioning operation information I, including the air conditioning operation result information I1 and the vehicle environment information I2, is not necessarily limited to information acquired in the vehicle 10 (i.e., the vehicle itself). In other words, the air conditioning operation information I may be collected in, for example, one or more other vehicles instead of or in addition to the vehicle 10, and may be acquired via the external system.

[0036] As described above, according to this embodiment, in calculation process PR1, the basic value Epb of the predicted electricity efficiency Ep is corrected based on the air conditioning operation information I obtained during past travel of vehicle 10. This makes it possible to appropriately calculate the predicted electricity efficiency Ep for future travel while taking into account the use of air conditioning device 16 when not currently travelling.

[0037] More specifically, according to this embodiment, in learning process PR2, the probability X of air conditioning operation during future driving is learned based on air conditioning operation result information I1 and vehicle environment information I2. Then, in calculation process PR1, the air conditioning electricity cost correction amount Cac is calculated based on the product of the air conditioning operation probability X learned in learning process PR2 and the air conditioning power consumption. Then, the basic value Epb of the predicted electricity cost Ep is corrected by the air conditioning electricity cost correction amount Cac. This allows the predicted electricity cost Ep to be appropriately corrected while taking the electricity cost of the air conditioner 16 into consideration.

[0038] Furthermore, in learning process PR2, an air conditioning operation probability model is learned based on the air conditioning operation result information I1 and the vehicle environment information I2, with multiple parameters included in the vehicle environment information I2 as input and an air conditioning operation probability X as output. The air conditioning operation probability X used to calculate the air conditioning electricity cost correction amount Cac is calculated from the air conditioning operation probability model and predicted values ​​of multiple parameters for the next scheduled trip, which corresponds to an example of a future trip. This allows the predicted electricity cost Ep for the next trip to be appropriately calculated using the learned air conditioning operation probability model when the trip is not currently in progress.

[0039] According to this embodiment, the cruising range L is calculated from the predicted electricity consumption Ep calculated as described above and the remaining battery capacity Wb of the battery 12. The calculated cruising range L is displayed on the display device 26. This makes it possible to display the cruising range L that is appropriately calculated based on the predicted electricity consumption Ep.

[0040] 3. Other examples of correction methods for predicted electricity consumption Ep According to the above-described correction method (see step S110), the air conditioning electric cost correction amount Cac used to correct the predicted electric cost Ep is determined to be a value corresponding to the air conditioning operation probability X, which is calculated as a value within a range of 0 to 1. Alternatively, the air conditioning operation probability X used to calculate the air conditioning electric cost correction amount Cac may be determined as follows.

[0041] That is, it may be determined whether the air conditioning operation probability X calculated by the processing in step S108 is equal to or greater than a predetermined threshold value TH (e.g., 0.5). If the calculated air conditioning operation probability X is equal to or greater than the threshold value TH, 1 may be used as the air conditioning operation probability X to be multiplied by the air conditioning power consumption Pac in calculating the air conditioning electricity cost correction amount Cac. If the calculated air conditioning operation probability X is less than the threshold value TH, 0 may be used as the air conditioning operation probability X to be multiplied by the air conditioning power consumption Pac.

[0042] According to this method, whether or not the air conditioner 16 will be used during future travel is determined (predicted) based on the air conditioner operation probability X. If it is determined that the air conditioner 16 will be used, the basic value Epb of the predicted electricity cost Ep is corrected using the air conditioning electricity cost correction amount Cac. On the other hand, if it is determined that the air conditioner 16 will not be used, the basic value Epb is not corrected using the air conditioning electricity cost correction amount Cac. [Explanation of symbols]

[0043] 10 vehicle, 12 battery, 14 electric motor, 16 air conditioning device, 18 power control unit (PCU), 20 electronic control unit (ECU), 22 sensors, 24 navigation device, 26 display device, 28 processor, 30 storage device

Claims

1. A control device for controlling a vehicle including an electric motor driven by power from a battery and an air conditioner operated by power from the battery, a processor that executes a calculation process to calculate a predicted electric consumption of the vehicle in a future traveling time when a system of the vehicle is not activated; In the calculation process, the processor corrects the base value of the predicted electricity consumption based on past air conditioning operation information of at least one of the vehicle and one or more other vehicles. Vehicle control device.

2. The air conditioning operation information includes air conditioning operation result information and vehicle environment information, the processor executes a learning process to learn an air conditioning operation probability, which is the probability that an air conditioning operation will be performed by an occupant of the vehicle during the future traveling, based on the air conditioning operation result information and the vehicle environment information; In the calculation process, the processor: calculating an air conditioning power cost correction amount, which is a correction amount for the power cost of the air conditioning device, based on the product of the air conditioning operation probability learned by the learning process and the air conditioning power consumption; The base value is corrected based on the air conditioning electricity cost correction amount. The vehicle control device according to claim 1 .

3. In the learning process, the processor learns an air conditioning operation probability model that uses a plurality of parameters included in the vehicle environment information as input and outputs the air conditioning operation probability based on the air conditioning operation result information and the vehicle environment information; The air conditioning operation probability used to calculate the air conditioning electricity cost correction amount is calculated from the air conditioning operation probability model and predicted values ​​of the plurality of parameters at the time of the next scheduled trip corresponding to the future trip. The vehicle control device according to claim 2.

4. The processor: calculating a cruising range of the vehicle, which is a distance that can be traveled with the remaining capacity, from the predicted electricity consumption calculated by the calculation process and the remaining capacity of the battery; The calculated cruising range is displayed on a display device. The vehicle control device according to any one of claims 1 to 3.

Images